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Luo Y, Cheng K, Liu J, Pei J, Xu S, Zhao X, Wang S, Zhao K, Li W, Liu J, Yu J. Potential of C-X-C-Chemokine-Receptor-Type-4-Directed PET/CT Using [¹⁸F]AlF-NOTA-QHY-04 in Identifying Molecular Subtypes of Small Cell Lung Cancer. Korean J Radiol 2025; 26:593-603. [PMID: 40432263 PMCID: PMC12123077 DOI: 10.3348/kjr.2024.1266] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2024] [Revised: 02/24/2025] [Accepted: 03/06/2025] [Indexed: 05/29/2025] Open
Abstract
OBJECTIVE Molecular subtyping of small-cell lung cancer (SCLC) has major implications for prognostic relevance and treatment guidance. This study aimed to explore the feasibility of a novel tracer targeting C-X-C-chemokine-receptor-type-4 (CXCR4) for distinguishing different SCLC subtypes. MATERIALS AND METHODS Thirty-five patients with pathologically confirmed SCLC were enrolled in this prospective study. Immunohistochemical staining was performed to classify the molecular subtypes into SCLC-A, SCLC-N, SCLC-P, and SCLC-I. [¹⁸F]AlF-NOTA-QHY-04 PET/CT parameters were obtained, including the maximum, mean, and peak standard uptake values (SUVmax, SUVmean, and SUVpeak, respectively) and the ratios of tumors (T) and normal tissues (NT) based on the SUVmax (T/NT). These parameters were compared among the molecular subtypes. A receiver operating characteristic (ROC) curve was used to analyze the performance of the parameters for distinguishing SCLC-N from other subtypes and neuroendocrine (NE) subtypes (SCLC-A and SCLC-N) from non-NE subtypes (SCLC-P and SCLC-I). RESULTS The molecular subtypes were SCLC-A (n = 17), SCLC-N (n = 6), SCLC-P (n = 7), and SCLC-I (n = 5). The SCLC-N subtype exhibited significantly higher uptake in both primary tumors and lymph node metastases than the other three subtypes (P < 0.05). When SCLC-N was compared with the other three subtypes combined (referred to as "other SCLCs"), all parameters were significantly higher in the SCLC-N group (P < 0.05). ROC analysis showed that these parameters had high accuracy in distinguishing SCLC-N from other SCLCs (area under ROC curve: 0.868-0.948 for primary tumors and 0.783-0.888 for lymph node metastases). Compared with the non-NE group, the SUVmax, SUVmean, and T/NTlung were significantly higher in the NE group for primary tumors. ROC analysis showed moderate accuracy in distinguishing between the NE and non-NE groups (ROC area: 0.692-0.786 for primary tumors and 0.692-0.815 for lymph node metastases). CONCLUSION Our preliminary findings indicate that CXCR4-directed PET/CT imaging using [¹⁸F]AlF-NOTA-QHY-04 may differentiate between SCLC-N and other molecular subtypes and between NE and non-NE subtypes of SCLC.
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Affiliation(s)
- Yuxi Luo
- Department of Oncology, The Affiliated Hospital of Southwest Medical University, College of Clinical Medicine, Southwest Medical University, Luzhou, China
- Shandong Provincial Key Laboratory of Precision Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Kai Cheng
- Department of PET/CT Center, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Jingru Liu
- Shandong Provincial Key Laboratory of Precision Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
- Department of Oncology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Jinli Pei
- Shandong Provincial Key Laboratory of Precision Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Shengnan Xu
- Shandong Provincial Key Laboratory of Precision Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Xinzhi Zhao
- Shandong Provincial Key Laboratory of Precision Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Shijie Wang
- Shandong Provincial Key Laboratory of Precision Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Kunlong Zhao
- Shandong Provincial Key Laboratory of Precision Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Wanhu Li
- Department of PET/CT Center, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Jie Liu
- Shandong Provincial Key Laboratory of Precision Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.
| | - Jinming Yu
- Department of Oncology, The Affiliated Hospital of Southwest Medical University, College of Clinical Medicine, Southwest Medical University, Luzhou, China
- Shandong Provincial Key Laboratory of Precision Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.
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Sun H, Zhang CY, Zhang XH, Tai ZX, Su JW, Lin XC, Zhang SL, Li YF, Zhang C, Cai M, Zhang XC, Chen HJ, Zhou Q, Wu YL, Feng WN, Yang JJ. Transcriptomic analysis of transformed small-cell lung cancer from EGFR-mutated lung adenocarcinoma reveals distinct subgroups and precision therapy opportunities. Biomark Res 2025; 13:79. [PMID: 40437627 PMCID: PMC12121208 DOI: 10.1186/s40364-025-00789-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2024] [Accepted: 05/14/2025] [Indexed: 06/01/2025] Open
Abstract
BACKGROUND Small-cell lung cancer (SCLC) transformation is one of the major mechanisms of resistance to Epidermal Growth Factor Receptor tyrosine kinase inhibitors (EGFR-TKIs). Chemotherapy is typically the recommended treatment for transformed SCLC (T-SCLC), similar to primary SCLC. However, the benefits of chemotherapy alone are minimal. Prior research highlights differences between the biological traits of T-SCLC and primary SCLC or EGFR-mutated lung adenocarcinoma (LUAD). This study aims to elucidate the molecular characteristics of T-SCLC and identify potential treatment modalities. METHODS We retrospectively collected tissue samples from LUAD, T-SCLC post-EGFR-TKI resistance, and primary SCLC. Genomics, transcriptomics, and proteomics were performed to clarify the differences between T-SCLC, LUAD, and primary SCLC. Hierarchical clustering analysis was then used to categorize the molecular subtype of T-SCLC, followed by a survival analysis based on these subtypes. RESULTS A study involving 61 patients investigated differences between LUAD, SCLC, and primary SCLC. RNA sequencing revealed distinct gene expression variations, particularly up-regulation in PPM1E, INSM1, and KCNC1 genes in T-SCLC. Pathway analysis linked T-SCLC to the cell cycle and neural differentiation. By conducting Hierarchical clustering analysis on RNA-seq data, the entire population can be categorized into two distinct groups. While certain T-SCLC showed similarities and differences compared to SCLC, with subtypes: LUAD-like and Non-LUAD-like. Notably, the LUAD-like subtype had significantly higher NKX2-1 expression (mean 371.8 vs. 41.8, P < 0.0001). T-SCLC treatment approaches were categorized into matched and unmatched groups, delineated by the alignment of specific therapies with corresponding pathologies. The matched group (13 cases) exhibited a significantly prolonged median progression-free survival compared to the unmatched group (10 cases) (5.4 months vs. 3.6 months, P = 0.02). CONCLUSIONS T-SCLC exhibits marked molecular distinctiveness, setting it apart not only from LUAD but also from classical SCLC. This distinction extends to its classification into two discernible molecular subtypes: LUAD-like and Non-LUAD-like. Customizing therapeutic protocols to align with these specific subtypes have the potential to identify the most appropriate treatment for T-SCLC.
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Affiliation(s)
- Hao Sun
- Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, No 106, Zhongshan Second Road, Guangzhou, 510080, China
| | - Chan-Yuan Zhang
- Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, No 106, Zhongshan Second Road, Guangzhou, 510080, China
- Department of Pulmonary Oncology, The First People's Hospital of Foshan, Foshan, Guangdong, 528000, China
| | - Xiu-Hao Zhang
- Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, No 106, Zhongshan Second Road, Guangzhou, 510080, China
| | | | - Jun-Wei Su
- Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, No 106, Zhongshan Second Road, Guangzhou, 510080, China
| | - Xiao-Cheng Lin
- Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, No 106, Zhongshan Second Road, Guangzhou, 510080, China
| | - Shi-Ling Zhang
- Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, No 106, Zhongshan Second Road, Guangzhou, 510080, China
| | - Yu-Fa Li
- Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, No 106, Zhongshan Second Road, Guangzhou, 510080, China
| | | | - Miao Cai
- Geneplus-Beijing, Beijing, China
| | - Xu-Chao Zhang
- Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, No 106, Zhongshan Second Road, Guangzhou, 510080, China
| | - Hua-Jun Chen
- Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, No 106, Zhongshan Second Road, Guangzhou, 510080, China
| | - Qing Zhou
- Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, No 106, Zhongshan Second Road, Guangzhou, 510080, China
| | - Yi-Long Wu
- Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, No 106, Zhongshan Second Road, Guangzhou, 510080, China.
| | - Wei-Neng Feng
- Department of Pulmonary Oncology, The First People's Hospital of Foshan, Foshan, Guangdong, 528000, China.
| | - Jin-Ji Yang
- Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, No 106, Zhongshan Second Road, Guangzhou, 510080, China.
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Chen Y, Tong Y, Ye X, Yang Y, Li H, Wu H, Zhai W, Li Y, Zhang Q, Zhou L, Sun J, Fan Y. A four gene risk score model for prognosis and immune microenvironment insights in small cell lung cancer based on CAF functional-related genes. Discov Oncol 2025; 16:923. [PMID: 40415048 DOI: 10.1007/s12672-025-02781-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/23/2025] [Accepted: 05/22/2025] [Indexed: 05/27/2025] Open
Abstract
Small cell lung cancer (SCLC) is still one of the most formidable challenges in oncology. In this study, we introduce an innovative risk scoring model rooted in cancer-associated fibroblast (CAF)-related functional genes, designed to predict patient prognosis and illuminate the microenvironment of SCLC. Through Kaplan-Meier survival analysis and receiver operating characteristic (ROC) curves, our model could effectively classify patients into high- and low-risk groups, with distinct survival outcomes and remarkable predictive accuracy, which has been evidenced by the AUC values. The low-risk patients showed a more active immune environment, characterized by more infiltration of dendritic cells, natural killer cells, and higher expression of immune co-stimulation molecules. On the contrary, high-risk patients displayed an enrichment of DNA repair and glycolysis pathways associated with tumor aggressiveness and treatment resistance. These results suggest that the risk model offers a nuanced view of response to immunotherapy that may guide the identification of patients who may benefit from immunotherapy. Moreover, we also verified the function of the key gene UBE2E2 by SCLC cell line experiments. Silencing UBE2E2 results in decreased cell proliferation and migration as well as increased apoptosis, which enhances its important role in SCLC biology. In summary, our study highlights the prognostic potential of the CAF-related functional gene risk model and its implications for predicting immune microenvironment status and guiding SCLC treatment strategies.
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Affiliation(s)
- Yunfei Chen
- Postgraduate Training Base Alliance, Wenzhou Medical University, Wenzhou, 325035, China
| | - Yunfeng Tong
- Postgraduate Training Base Alliance, Wenzhou Medical University, Wenzhou, 325035, China
| | - Xinyuan Ye
- Postgraduate Training Base Alliance, Wenzhou Medical University, Wenzhou, 325035, China
| | - Yehao Yang
- Postgraduate Training Base Alliance, Wenzhou Medical University, Wenzhou, 325035, China
| | - Hui Li
- Department of Thoracic Medical Oncology, Zhejiang Cancer Hospital, Hangzhou, 310022, Zhejiang, China
| | - Haicheng Wu
- Postgraduate Training Base Alliance, Wenzhou Medical University, Wenzhou, 325035, China
| | - Wanchen Zhai
- Department of Thoracic Medical Oncology, Zhejiang Cancer Hospital, Hangzhou, 310022, Zhejiang, China
| | - Yuwei Li
- Postgraduate Training Base Alliance, Wenzhou Medical University, Wenzhou, 325035, China
| | - Qian Zhang
- Department of Thoracic Medical Oncology, Zhejiang Cancer Hospital, Hangzhou, 310022, Zhejiang, China
| | - Linjing Zhou
- Department of Thoracic Medical Oncology, Zhejiang Cancer Hospital, Hangzhou, 310022, Zhejiang, China
| | - Jing Sun
- Postgraduate Training Base Alliance, Wenzhou Medical University, Wenzhou, 325035, China
| | - Yun Fan
- Postgraduate Training Base Alliance, Wenzhou Medical University, Wenzhou, 325035, China.
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Raj P, Gupta H, Anantha P, Barman I. Cell-TIMP: Cellular Trajectory Inference Based on Morphological Parameters. NANO LETTERS 2025; 25:7845-7852. [PMID: 40317256 DOI: 10.1021/acs.nanolett.5c01009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/07/2025]
Abstract
Traditional approaches to studying cellular morphology rely on geometric metrics from stained images. However, staining processes can disrupt the cell's natural state and diminish accuracy due to photobleaching, while conventional analysis techniques, which categorize cells based on shape to discern pathophysiological conditions, often fail to capture the continuous and asynchronous nature of biological processes such as cell differentiation, immune responses, and cancer progression. In this work, we propose the use of quantitative phase imaging for morphological assessment due to its label-free nature. For analysis, we repurposed the genomic analysis toolbox to perform trajectory inference analysis purely based on morphology information. We applied the developed framework to study the progression of leukemia and breast cancer metastasis. Applying this framework to leukemia and breast cancer metastasis, we identified key shape changes linked to disease progression, highlighting the method's potential to enhance understanding of complex biological dynamics.
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Affiliation(s)
- Piyush Raj
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, United States
| | - Himanshu Gupta
- Centre for Applied Autonomous Sensor Systems (AASS), Örebro University, Örebro 70182, Sweden
| | - Pooja Anantha
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, United States
| | - Ishan Barman
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, United States
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University, School of Medicine, Baltimore, Maryland 21205, United States
- The Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, Maryland 21287, United States
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Cognigni V, Toscani I, D’Agnelli S, Pecci F, Righi L, Berardi R, Tiseo M. Molecular heterogeneity of small cell lung cancer and new therapeutic possibilities: a narrative review of the literature. Transl Lung Cancer Res 2025; 14:1441-1455. [PMID: 40386726 PMCID: PMC12082233 DOI: 10.21037/tlcr-24-755] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2024] [Accepted: 01/08/2025] [Indexed: 05/20/2025]
Abstract
Background and Objective Small cell lung cancer (SCLC) is an aggressive disease commonly occurring in individuals with a history of heavy smoking. Despite recent approvals of chemotherapy and immunotherapy in the first-line treatment of extensive-stage SCLC, it maintains a poor prognosis. Moreover, only a small percentage of patients benefits from the addition of immunotherapy to platinum-based chemotherapy. The lack of significant progress in therapeutic options unrevealed the urgent need for a deeper understanding of tumor biology and easy-to-use predictive biomarkers, aiming to better tailor the treatment strategy. The aim of this review is to summarize recent evidence about the biology, molecular heterogeneity, as well as tumor microenvironment (TME) of SCLC and their forefront therapeutic implications. Methods A literature search was conducted using PubMed, focusing on articles published in English from 1981 to October 2024. Studies on SCLC biology and subclassification were selected for further analysis and integrated in the current narrative review. Key Content and Findings SCLC entity implies four distinct molecular subtypes based on transcription factors expression, specifically achaete-scute homolog 1 (ASCL1), neurogenic differentiation 1 (NEUROD1), POU class 2 homeobox 3 (POU2F3), and yes-associated protein 1 (YAP1), reflecting the tumor heterogeneity in terms of gene expression, transcriptional profiles, immune infiltration, and treatment sensitivity. Recently, a new subgroup, "SCLC-I", has been proposed to replace the YAP1 subtype, showing higher responsiveness to immunotherapy. The TME, implying immune cell infiltration and their interactions with cancer cells, plays a crucial role in determining SCLC's sensitivity to immunotherapy. Conclusions Advances in SCLC molecular characterization and the development of targeted therapies against specific molecular pathways might improve patients' clinical outcome, supporting a more personalized approach to this complex disease.
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Affiliation(s)
- Valeria Cognigni
- Department of Medical Oncology, Università Politecnica delle Marche, Azienda Ospedaliero-Universitaria delle Marche, Ancona, Italy
| | - Ilaria Toscani
- Medical Oncology Unit, Hospital of Piacenza, Piacenza, Italy
| | - Simona D’Agnelli
- Department of Medicine and Surgery, University of Parma, Parma, Italy
- Medical Oncology Unit, University Hospital of Parma, Parma, Italy
| | - Federica Pecci
- Department of Medicine and Surgery, University of Parma, Parma, Italy
- Medical Oncology Unit, University Hospital of Parma, Parma, Italy
| | - Luisella Righi
- Pathology Unit, Department of Oncology, University of Torino at San Luigi Hospital, Orbassano, Italy
| | - Rossana Berardi
- Department of Medical Oncology, Università Politecnica delle Marche, Azienda Ospedaliero-Universitaria delle Marche, Ancona, Italy
| | - Marcello Tiseo
- Department of Medicine and Surgery, University of Parma, Parma, Italy
- Medical Oncology Unit, University Hospital of Parma, Parma, Italy
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Gu Z, Heng Y, Fan R, Luo J, Ju L. Single-cell RNA sequencing reveals cellular and molecular heterogeneity in extensive-stage small cell lung cancer with different chemotherapy responses. Cancer Cell Int 2025; 25:157. [PMID: 40259334 PMCID: PMC12013103 DOI: 10.1186/s12935-025-03785-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2024] [Accepted: 04/08/2025] [Indexed: 04/23/2025] Open
Abstract
Despite its rapid growth and early metastasis, small cell lung cancer (SCLC) is more chemosensitive than other lung cancers. However, some patients with extensive-stage SCLC (ES-SCLC) do not respond to first-line chemotherapy, resulting in poorer prognoses due to inter- and intratumoral heterogeneity. In this study, we conducted single-cell RNA sequencing of 9 treatment-naive ES-SCLC samples. Based on comprehensive imaging evidence collected before and after two cycles of first-line chemotherapy and sample types, the 9 samples were categorized into three groups: progressive disease with the pleural effusion sample (PD_PE group, n = 1), progressive disease with the primary tumor samples (PD_TU group, n = 2), and partial response with the primary tumor samples (PR_TU group, n = 6). Based on transcriptomic landscape and cell type composition, the PD samples represent a multicellular ecosystem distinct from PR samples. The immune response, along with the elevated expression of immune-related genes such as LTF, SLPI, SPARC and IGLV1-51, might correlate with a poor first-line chemotherapy response in ES-SCLC. We also observed that T cells, particularly effector T cells, were more abundant in PD_TU group, with TNFA signaling via NFκB being significantly enriched. The PD_TU group was strongly enriched with macrophages and tumor-associated macrophages (TAMs), and angiogenesis in TAMs was highly enriched. Immunomodulatory fibroblasts were highly abundant in PD_TU group, and the pathways of epithelial-mesenchymal transition and angiogenesis were upregulated. This study offers the first comprehensive insights into the cellular and molecular heterogeneity in treatment-naive patients with ES-SCLC with different chemotherapy responses.
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Affiliation(s)
- Zhan Gu
- Department of Integrative Medicine, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China
| | - Yongqing Heng
- Department of Integrative Medicine, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China
| | - Rui Fan
- Department of Integrative Medicine, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China
| | - Jie Luo
- Department of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China
| | - Lixia Ju
- Department of Integrative Medicine, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China.
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Lin G, Yao Z, Kang K, Luo R, Yi L, Lu Y. Dynamic evolution and antitumor mechanisms of CXCR6 +CD8 + T cells in small cell lung cancer treated with low-dose radiotherapy and immunotherapy. J Transl Med 2025; 23:453. [PMID: 40247265 PMCID: PMC12007177 DOI: 10.1186/s12967-025-06450-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2025] [Accepted: 04/03/2025] [Indexed: 04/19/2025] Open
Abstract
BACKGROUND Patients with small-cell lung cancer (SCLC) have the poor prognosis. Current research suggested that low-dose radiotherapy (LDRT) combined with immunotherapy can enhance the immunogenicity of tumor cells, thereby improving antigen presentation and promoting the intratumoral infiltration of CD8+ T cells, which significantly extends the survival of patients. However, the change trajectory of T cells, and the mechanisms underlying the promotion of intratumoral infiltration of CD8+ T cells, and the enhancement of their cytotoxic functions remain to be elucidated. METHODS To delineate the dynamic changes of T cells, we collected tumors from Kaede tumor-bearing mice that had undergone radioimmunotherapy. Using flow cytometry, we sorted intratumoral-infiltrating immune cells, which were required for single-cell RNA sequencing, at various time points (Kaede Red: derived from tumor-draining lymph node [TDLN]). The results obtained from the sequencing analysis were further validated through experiments, such as flow cytometry, immunofluorescence, and analysis of clinical cohort data. RESULTS Here, we observed stem-like T cells migrating from the TDLN to the tumor site and differentiating into effector phenotypes within the tumor. Dendritic cells (DCs) are the key cluster that induces the differentiation of stem-like T cell into effector phenotypes. Moreover, SCLC patients with a high infiltration of tumor-specific CXCR6+CD8+ T cells exhibited a supportive TME and longer survival time (P < 0.001). CONCLUSIONS This study delineates the change trajectory of CD8+ T cells, identifies the crucial role of DCs in T cell differentiation, and highlights the significance of tumor-specific CXCR6+CD8+ T cells in anti-tumor immunity. Future therapeutic strategies for SCLC could focus on enhancing the infiltration of activated DCs and CXCR6+CD8+ T cells within the tumor microenvironment to improve treatment efficacy.
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Affiliation(s)
- Guo Lin
- Division of Thoracic Tumor Multimodality Treatment and Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
- Laboratory of Clinical Cell Therapy, West China Hospital, Sichuan University, Chengdu, China
| | - Zhuoran Yao
- Division of Thoracic Tumor Multimodality Treatment and Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
- Laboratory of Clinical Cell Therapy, West China Hospital, Sichuan University, Chengdu, China
| | - Kai Kang
- Division of Thoracic Tumor Multimodality Treatment and Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
- Laboratory of Clinical Cell Therapy, West China Hospital, Sichuan University, Chengdu, China
| | - Ren Luo
- Division of Thoracic Tumor Multimodality Treatment and Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
- Laboratory of Clinical Cell Therapy, West China Hospital, Sichuan University, Chengdu, China
| | - Linglu Yi
- Laboratory of Clinical Cell Therapy, West China Hospital, Sichuan University, Chengdu, China
- Frontiers Medical Center, Tianfu Jincheng Laboratory, Chengdu, China
| | - You Lu
- Division of Thoracic Tumor Multimodality Treatment and Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China.
- Laboratory of Clinical Cell Therapy, West China Hospital, Sichuan University, Chengdu, China.
- Frontiers Medical Center, Tianfu Jincheng Laboratory, Chengdu, China.
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Peng H, Jabbari JS, Tian L, Wang C, You Y, Chua CC, Anstee NS, Amin N, Wei AH, Davidson NM, Roberts AW, Huang DCS, Ritchie ME, Thijssen R. Single-cell Rapid Capture Hybridization sequencing reliably detects isoform usage and coding mutations in targeted genes. Genome Res 2025; 35:942-955. [PMID: 39794120 PMCID: PMC12047256 DOI: 10.1101/gr.279322.124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2024] [Accepted: 12/10/2024] [Indexed: 01/13/2025]
Abstract
Single-cell long-read sequencing has transformed our understanding of isoform usage and the mutation heterogeneity between cells. Despite unbiased in-depth analysis, the low sequencing throughput often results in insufficient read coverage, thereby limiting our ability to perform mutation calling for specific genes. Here, we developed a single-cell Rapid Capture Hybridization sequencing (scRaCH-seq) method that demonstrates high specificity and efficiency in capturing targeted transcripts using long-read sequencing, allowing an in-depth analysis of mutation status and transcript usage for genes of interest. The method includes creating a probe panel for transcript capture, using barcoded primers for pooling and efficient sequencing via Oxford Nanopore Technologies platforms. scRaCH-seq is applicable to stored and indexed single-cell cDNA, which allows analysis to be combined with existing short-read RNA-seq data sets. In our investigation of BTK and SF3B1 genes in samples from patients with chronic lymphocytic leukemia (CLL), we detect SF3B1 isoforms and mutations with high sensitivity. Integration with short-read single-cell RNA sequencing (scRNA-seq) data reveals significant gene expression differences in SF3B1-mutated CLL cells, although it does not impact the sensitivity of the anticancer drug venetoclax. scRaCH-seq's capability to study long-read transcripts of multiple genes makes it a powerful tool for single-cell genomics.
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Affiliation(s)
- Hongke Peng
- The Walter and Eliza Hall Institute of Medical Research, Melbourne 3052, Australia
- Department of Medical Biology, University of Melbourne, Melbourne 3052, Australia
| | - Jafar S Jabbari
- The Walter and Eliza Hall Institute of Medical Research, Melbourne 3052, Australia
- Department of Medical Biology, University of Melbourne, Melbourne 3052, Australia
| | - Luyi Tian
- The Walter and Eliza Hall Institute of Medical Research, Melbourne 3052, Australia
- Department of Medical Biology, University of Melbourne, Melbourne 3052, Australia
| | - Changqing Wang
- The Walter and Eliza Hall Institute of Medical Research, Melbourne 3052, Australia
- Department of Medical Biology, University of Melbourne, Melbourne 3052, Australia
| | - Yupei You
- The Walter and Eliza Hall Institute of Medical Research, Melbourne 3052, Australia
- Department of Medical Biology, University of Melbourne, Melbourne 3052, Australia
| | - Chong Chyn Chua
- The Walter and Eliza Hall Institute of Medical Research, Melbourne 3052, Australia
- Department of Medical Biology, University of Melbourne, Melbourne 3052, Australia
- Monash Haematology, Monash Health, Melbourne 3168, Australia
- Clinical Haematology, Northern Health, Melbourne 3076, Australia
| | - Natasha S Anstee
- The Walter and Eliza Hall Institute of Medical Research, Melbourne 3052, Australia
- Department of Medical Biology, University of Melbourne, Melbourne 3052, Australia
| | - Noorul Amin
- The Walter and Eliza Hall Institute of Medical Research, Melbourne 3052, Australia
- Department of Medical Biology, University of Melbourne, Melbourne 3052, Australia
| | - Andrew H Wei
- The Walter and Eliza Hall Institute of Medical Research, Melbourne 3052, Australia
- Department of Medical Biology, University of Melbourne, Melbourne 3052, Australia
- Department of Clinical Haematology, Royal Melbourne Hospital and Peter MacCallum Cancer Centre, Melbourne 3052, Australia
| | - Nadia M Davidson
- The Walter and Eliza Hall Institute of Medical Research, Melbourne 3052, Australia
- Department of Medical Biology, University of Melbourne, Melbourne 3052, Australia
| | - Andrew W Roberts
- The Walter and Eliza Hall Institute of Medical Research, Melbourne 3052, Australia
- Department of Medical Biology, University of Melbourne, Melbourne 3052, Australia
- Department of Clinical Haematology, Royal Melbourne Hospital and Peter MacCallum Cancer Centre, Melbourne 3052, Australia
| | - David C S Huang
- The Walter and Eliza Hall Institute of Medical Research, Melbourne 3052, Australia
- Department of Medical Biology, University of Melbourne, Melbourne 3052, Australia
| | - Matthew E Ritchie
- The Walter and Eliza Hall Institute of Medical Research, Melbourne 3052, Australia
- Department of Medical Biology, University of Melbourne, Melbourne 3052, Australia
| | - Rachel Thijssen
- The Walter and Eliza Hall Institute of Medical Research, Melbourne 3052, Australia;
- Department of Medical Biology, University of Melbourne, Melbourne 3052, Australia
- Department of Hematology, Amsterdam UMC, Amsterdam 1081HV, the Netherlands
- Cancer Center Amsterdam, Cancer Biology and Immunology, Amsterdam 1081HV, the Netherlands
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9
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Zhai X, Zhang Z, Chen Y, Wu Y, Zhen C, Liu Y, Lin Y, Chen C. Current and future therapies for small cell lung carcinoma. J Hematol Oncol 2025; 18:37. [PMID: 40170056 PMCID: PMC11959764 DOI: 10.1186/s13045-025-01690-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2025] [Accepted: 03/14/2025] [Indexed: 04/03/2025] Open
Abstract
Small cell lung cancer (SCLC) is an aggressive malignancy characterized by rapid proliferation and high metastatic potential. It is characterized by universal inactivation of and RB1, overexpression of the MYC family and dysregulation of multiple oncogenic signaling pathways. Among different patients, SCLCs are similar at the genetic level but exhibit significant heterogeneity at the molecular level. The classification of SCLC has evolved from a simple neuroendocrine (NE)/non-neuroendocrine (non-NE) classification system to a transcription factor-based molecular subtype system; lineage plasticity adds further complexity and poses challenges for therapeutic development. While SCLC is initially sensitive to platinum-based chemotherapy, resistance develops rapidly, leading to a dismal prognosis. Various antibodies, including PD-1/PD-L1 inhibitors and antibody‒drug conjugates, have been introduced into clinical practice or are being evaluated in clinical trials. However, their therapeutic benefits for SCLC patients remain limited. This review summarizes SCLC carcinogenic mechanisms, tumor heterogeneity, and the immune microenvironment of SCLC, with a focus on recent advances in metastasis and resistance mechanisms. Additionally, the corresponding clinical progress in tackling these challenges is discussed.
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Affiliation(s)
- Xiaoqian Zhai
- Department of Medical Oncology, State Key Laboratory of Biotherapy and Cancer Center and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, No. 1, Keyuan 4th Road, Gaopeng Avenue, Chengdu, 610041, Sichuan, China
- Lung Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Zhengkun Zhang
- State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- College of Life Sciences, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Yuxin Chen
- West China School of Medicine, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Yanmou Wu
- State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- College of Life Sciences, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Cheng Zhen
- West China School of Medicine, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Yu Liu
- Department of Hematology and Institute of Hematology, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, No. 1, Keyuan 4th Road, Gaopeng Avenue, Chengdu, 610041, Sichuan, China.
| | - Yiyun Lin
- Department of Medicine, Weill Cornell Medicine, East 69th Street, New York, NY, 10021, USA.
| | - Chong Chen
- Department of Medical Oncology, State Key Laboratory of Biotherapy and Cancer Center and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, No. 1, Keyuan 4th Road, Gaopeng Avenue, Chengdu, 610041, Sichuan, China.
- Lung Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
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10
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Anantha P, Raj P, Saracino E, Kim JH, Kim JH, Convertino A, Gu L, Barman I. Uncovering Astrocyte Morphological Dynamics Using Optical Diffraction Tomography and Shape-Based Trajectory Inference. Adv Healthc Mater 2025; 14:e2402960. [PMID: 39740118 DOI: 10.1002/adhm.202402960] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2024] [Revised: 12/19/2024] [Indexed: 01/02/2025]
Abstract
Astrocytes, integral components of the central nervous system, are increasingly recognized for their multifaceted roles beyond support cells. Despite their acknowledged importance, understanding the intricacies of astrocyte morphological dynamics remains limited. Our study marks the first exploration of astrocytes using optical diffraction tomography (ODT), establishing a label-free, quantitative method to observe morphological changes in astrocytes over a 7-day in-vitro period. ODT offers quantitative insights into cell volume, dry mass, and area through label-free, real-time measurements-capabilities that are challenging to achieve with conventional imaging techniques. Through comprehensive analysis of 3D refractive index maps and shape characterization techniques, we capture the developmental trajectory and dynamic morphological transformations of astrocytes. Specifically, our observations reveal increased area and a transition to larger, flattened shapes, with alterations in cell volume and density, indicating shifts in cellular composition. By employing unsupervised clustering and pseudotime trajectory analysis, we introduce a novel morphological trajectory inference for neural cells, tracking the morphological evolution of astrocytes from elongated to evenly spread shapes. This analysis marks the first use of trajectory inference based solely on morphology for neural cell types, laying a foundation for future studies employing ODT to examine astrocyte dynamics and neural cell interactions across diverse substrates.
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Affiliation(s)
- Pooja Anantha
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Piyush Raj
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Emanuela Saracino
- Institute for Organic Synthesis and Photoreactivity (ISOF), National Research Council of Italy (CNR), Via P. Gobetti 101, Bologna, I-40129, Italy
| | - Joo Ho Kim
- Department of Materials Science and Engineering, Institute for NanoBioTechnology, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Jeong Hee Kim
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Annalisa Convertino
- Institute for Microelectronics and Microsystems, National Research Council, via Fosso del Cavaliere 100, Rome, 00133, Italy
| | - Luo Gu
- Department of Materials Science and Engineering, Institute for NanoBioTechnology, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Ishan Barman
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA
- Department of Oncology, Johns Hopkins University, Baltimore, MD, 21287, USA
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of Cancer Imaging Research, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
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11
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Huang S, Shi J, Shen J, Fan X. Metabolic reprogramming of neutrophils in the tumor microenvironment: Emerging therapeutic targets. Cancer Lett 2025; 612:217466. [PMID: 39862916 DOI: 10.1016/j.canlet.2025.217466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2024] [Revised: 01/12/2025] [Accepted: 01/13/2025] [Indexed: 01/27/2025]
Abstract
Neutrophils are pivotal in the immune system and have been recognized as significant contributors to cancer development and progression. These cells undergo metabolic reprogramming in response to various stimulus, including infections, diseases, and the tumor microenvironment (TME). Under normal conditions, neutrophils primarily rely on aerobic glucose metabolism for energy production. However, within the TME featured by hypoxic and nutrient-deprived conditions, they shift to altered anaerobic glycolysis, lipid metabolism, mitochondrial metabolism and amino acid metabolism to perform their immunosuppressive functions and facilitate tumor progression. Targeting neutrophils within the TME is a promising therapeutic approach. Yet, focusing on their metabolic pathways presents a novel strategy to enhance cancer immunotherapy. This review synthesizes the current understanding of neutrophil metabolic reprogramming in the TME, with an emphasis on the underlying molecular mechanisms and signaling pathways. Studying neutrophil metabolism in the TME poses challenges, such as their short lifespan and the metabolic complexity of the environment, necessitating the development of advanced research methodologies. This review also discusses emerging solutions to these challenges. In conclusion, given their integral role in the TME, targeting the metabolic pathways of neutrophils could offer a promising avenue for cancer therapy.
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Affiliation(s)
- Shiyun Huang
- Department of Ophthalmology, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China; Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, 200025, China.
| | - Jiahao Shi
- Department of Ophthalmology, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China; Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, 200025, China.
| | - Jianfeng Shen
- Department of Ophthalmology, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China; Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, 200025, China.
| | - Xianqun Fan
- Department of Ophthalmology, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China; Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, 200025, China.
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12
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Luo L, Xia R, Mao S, Liu Q, Du H, Jiang T, Yang S, Wang Y, Li W, Zhou F, Yu J, Gao G, Li X, Zhao C, Cheng L, Shi J, Chen X, Zhou C, Chen L, Ren S, Wu F. Differential expression of the MYC-Notch axis drives divergent responses to the front-line therapy in central and peripheral extensive-stage small-cell lung cancer. MedComm (Beijing) 2025; 6:e70112. [PMID: 39974662 PMCID: PMC11836348 DOI: 10.1002/mco2.70112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2024] [Revised: 01/08/2025] [Accepted: 01/15/2025] [Indexed: 02/21/2025] Open
Abstract
Central and peripheral extensive-stage small-cell lung cancer (ES-SCLC) are reported to be two distinct tumor entities, but their responses to the front-line therapies and underlying biological mechanisms remain elusive. In this study, we first compared the outcomes of central and peripheral ES-SCLC receiving front-line chemotherapy or chemo-immunotherapy with a cohort of 265 patients. Then we performed single-cell RNA sequencing (scRNA-seq) on nine treatment-naïve ES-SCLC samples to investigate potential mechanisms underlying the response differences. Under chemotherapy, the peripheral type had a lower objective response rate (44.8% vs. 71.2%, p = 0.008) and shorter progression-free survival (median 3.4 vs. 5.1 months, p = 0.001) than the central type. When comparing chemo-immunotherapy with chemotherapy, the peripheral type showed a greater potential to reduce progression (HR, 0.18 and 0.52, respectively) and death (HR, 0.44 and 0.91 respectively) risks than the central type. Concerning the scRNA-seq data, the peripheral type was associated with chemo-resistant and immune-responsive tumoral and microenvironmental features, including a higher expression level of MYC-Notch-non-neuroendocrine (MYC-Notch-non-NE) axis and a more potent antigen presentation and immune activation status. Our results revealed that central and peripheral ES-SCLC had distinct responses to front-line treatments, potentially due to differential activation statuses of the MYC-Notch-non-NE axis.
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Affiliation(s)
- Libo Luo
- Department of Medical OncologyShanghai Pulmonary HospitalTongji University School of MedicineShanghaiChina
| | - Rui Xia
- Key Laboratory of Systems BiologyCenter for Excellence in Molecular Cell ScienceShanghai Institute of Biochemistry and Cell BiologyChinese Academy of SciencesShanghaiChina
- University of Chinese Academy of SciencesBeijingChina
| | - Shiqi Mao
- Department of Medical OncologyShanghai Pulmonary HospitalTongji University School of MedicineShanghaiChina
| | - Qian Liu
- Department of OncologyXiangyang No. 1 People's HospitalHubei University of MedicineXiangyangChina
| | - He Du
- Department of Medical OncologyShanghai Pulmonary HospitalTongji University School of MedicineShanghaiChina
| | - Tao Jiang
- Department of Medical OncologyShanghai Pulmonary HospitalTongji University School of MedicineShanghaiChina
| | - Shuo Yang
- Department of Medical OncologyShanghai Pulmonary HospitalTongji University School of MedicineShanghaiChina
| | - Yan Wang
- Department of Medical OncologyShanghai Pulmonary HospitalTongji University School of MedicineShanghaiChina
| | - Wei Li
- Department of RadiologyShanghai Pulmonary HospitalTongji University School of MedicineShanghaiChina
| | - Fei Zhou
- Department of Medical OncologyShanghai Pulmonary HospitalTongji University School of MedicineShanghaiChina
| | - Jia Yu
- Department of Medical OncologyShanghai Pulmonary HospitalTongji University School of MedicineShanghaiChina
| | - Guanghui Gao
- Department of Medical OncologyShanghai Pulmonary HospitalTongji University School of MedicineShanghaiChina
| | - Xuefei Li
- Department of Lung Cancer and ImmunologyShanghai Pulmonary HospitalTongji University School of MedicineShanghaiChina
| | - Chao Zhao
- Department of Lung Cancer and ImmunologyShanghai Pulmonary HospitalTongji University School of MedicineShanghaiChina
| | - Lei Cheng
- Department of Lung Cancer and ImmunologyShanghai Pulmonary HospitalTongji University School of MedicineShanghaiChina
| | - Jingyun Shi
- Department of RadiologyShanghai Pulmonary HospitalTongji University School of MedicineShanghaiChina
| | - Xiaoxia Chen
- Department of Medical OncologyShanghai Pulmonary HospitalTongji University School of MedicineShanghaiChina
| | - Caicun Zhou
- Department of Medical OncologyShanghai Pulmonary HospitalTongji University School of MedicineShanghaiChina
| | - Luonan Chen
- Key Laboratory of Systems BiologyCenter for Excellence in Molecular Cell ScienceShanghai Institute of Biochemistry and Cell BiologyChinese Academy of SciencesShanghaiChina
- University of Chinese Academy of SciencesBeijingChina
- Key Laboratory of Systems Health Science of Zhejiang ProvinceSchool of Life ScienceHangzhou Institute for Advanced StudyUniversity of Chinese Academy of SciencesChinese Academy of SciencesHangzhouChina
| | - Shengxiang Ren
- Department of Medical OncologyShanghai Pulmonary HospitalTongji University School of MedicineShanghaiChina
| | - Fengying Wu
- Department of Medical OncologyShanghai Pulmonary HospitalTongji University School of MedicineShanghaiChina
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13
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Zhu Y, Wu J, Wang H, Chi K, Diao X, Zhuo M, Lin D. Whole-section digital analysis of immune profiles in surgically resected small cell lung carcinoma and their associations with molecular subtypes. Transl Lung Cancer Res 2025; 14:449-466. [PMID: 40114934 PMCID: PMC11921296 DOI: 10.21037/tlcr-24-924] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2024] [Accepted: 01/09/2025] [Indexed: 03/22/2025]
Abstract
Background The molecular subtype-specific features of the tumor immune microenvironment (TIME) in small cell lung carcinoma (SCLC) remain poorly understood. We aimed to analyze the immune profiles in surgically resected SCLC and their associations with molecular subtypes. Methods Tumor samples from 83 treatment-naive SCLC patients who underwent surgical resection were analyzed. The protein expression of subtype-defining markers (ASCL1, NEUROD1, POU2F3, and YAP1) and nine immune-related markers were assessed using whole-section immunohistochemistry. Digital image analysis was employed for precise quantification of immune cell infiltrates and distributions. The findings were subsequently correlated with clinicopathological parameters and patient prognoses. Results Unsupervised hierarchical clustering categorized the tumors into four molecular subtypes: achaete-scute homologue 1-dominant (ASCL1; SCLC-A, 71.1%, n=59), neuronal differentiation factor 1-dominant (NEUROD1; SCLC-N, 12.1%, n=10), POU class 2 homeobox 3-dominant (POU2F3; SCLC-P, 10.8%, n=9), and quadruple-negative (SCLC-QN, 6.0%, n=5). Expression of major histocompatibility complex class I (MHC I) and class II (MHC II; P=0.02, P=0.02), tumor programmed death-ligand 1 (PD-L1; P=0.006), and an inflamed phenotype characterized by CD8+/CD3+ T cells (P=0.001, P=0.003) were more prominent in SCLC-P tumors compared to other subtypes. Additionally, SCLC-P tumors demonstrated the highest levels of MHC II (P=0.04) and PD-L1 expression on both tumor and stromal cells (P=0.003, P=0.01). The tumor proportion score of PD-L1 positively correlated with tumor expression levels of POU2F3 (rho=0.297, P=0.006) and MHC I (rho=0.239, P=0.03), as well as the combined positive score of PD-L1 (rho=0.222, P=0.04; rho=0.433, P<0.001). Intra-tumoral tertiary lymphoid structures (intra-TLS) and peri-tumoral TLS (peri-TLS) were observed in 60.2% (n=50) and 96.4% (n=80) of patients, respectively. High intra-TLS density was more frequently associated with SCLC-P tumors (P=0.02). Notably, low peri-TLS density and stromal PD-L1 expression were linked to improved overall survival (OS) and progression-free survival (PFS), respectively. Conclusions This study highlights the heterogeneity of the TIME across molecular subtypes of SCLC. The SCLC-P subtype and MHC I expression may serve as predictive biomarkers for immunotherapy response, while peri-TLS density and stromal PD-L1 expression might serve as prognostic indicators in resected SCLC.
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Affiliation(s)
- Yanli Zhu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Pathology, Peking University Cancer Hospital and Institute, Beijing, China
| | - Jianghua Wu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Pathology, Peking University Cancer Hospital and Institute, Beijing, China
| | - Haiyue Wang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Pathology, Peking University Cancer Hospital and Institute, Beijing, China
| | - Kaiwen Chi
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Pathology, Peking University Cancer Hospital and Institute, Beijing, China
| | - Xinting Diao
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Pathology, Peking University Cancer Hospital and Institute, Beijing, China
| | - Minglei Zhuo
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department I of Thoracic Oncology, Peking University Cancer Hospital and Institute, Beijing, China
| | - Dongmei Lin
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Pathology, Peking University Cancer Hospital and Institute, Beijing, China
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14
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Nussinov R, Yavuz BR, Jang H. Molecular principles underlying aggressive cancers. Signal Transduct Target Ther 2025; 10:42. [PMID: 39956859 PMCID: PMC11830828 DOI: 10.1038/s41392-025-02129-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2024] [Revised: 12/02/2024] [Accepted: 01/07/2025] [Indexed: 02/18/2025] Open
Abstract
Aggressive tumors pose ultra-challenges to drug resistance. Anti-cancer treatments are often unsuccessful, and single-cell technologies to rein drug resistance mechanisms are still fruitless. The National Cancer Institute defines aggressive cancers at the tissue level, describing them as those that spread rapidly, despite severe treatment. At the molecular, foundational level, the quantitative biophysics discipline defines aggressive cancers as harboring a large number of (overexpressed, or mutated) crucial signaling proteins in major proliferation pathways populating their active conformations, primed for their signal transduction roles. This comprehensive review explores highly aggressive cancers on the foundational and cell signaling levels, focusing on the differences between highly aggressive cancers and the more treatable ones. It showcases aggressive tumors as harboring massive, cancer-promoting, catalysis-primed oncogenic proteins, especially through certain overexpression scenarios, as predisposed aggressive tumor candidates. Our examples narrate strong activation of ERK1/2, and other oncogenic proteins, through malfunctioning chromatin and crosslinked signaling, and how they activate multiple proliferation pathways. They show the increased cancer heterogeneity, plasticity, and drug resistance. Our review formulates the principles underlying cancer aggressiveness on the molecular level, discusses scenarios, and describes drug regimen (single drugs and drug combinations) for PDAC, NSCLC, CRC, HCC, breast and prostate cancers, glioblastoma, neuroblastoma, and leukemia as examples. All show overexpression scenarios of master transcription factors, transcription factors with gene fusions, copy number alterations, dysregulation of the epigenetic codes and epithelial-to-mesenchymal transitions in aggressive tumors, as well as high mutation loads of vital upstream signaling regulators, such as EGFR, c-MET, and K-Ras, befitting these principles.
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Affiliation(s)
- Ruth Nussinov
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research, Frederick, MD, 21702, USA.
- Cancer Innovation Laboratory, National Cancer Institute at Frederick, Frederick, MD, 21702, USA.
- Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, 69978, Tel Aviv, Israel.
| | - Bengi Ruken Yavuz
- Cancer Innovation Laboratory, National Cancer Institute at Frederick, Frederick, MD, 21702, USA
| | - Hyunbum Jang
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research, Frederick, MD, 21702, USA
- Cancer Innovation Laboratory, National Cancer Institute at Frederick, Frederick, MD, 21702, USA
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15
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Moeng S, Chamorro-Parejo AD, Jeon MS, Cai JJ, Ramos KS. Single-Cell RNA Sequencing Reveals Extensive Heterogeneity and Unique Gene Trajectories in Non-Transformed and Transformed Human Lung Epithelial Cells: Insights into the Role of LncRNAs in Tumor Heterogeneity. Int J Mol Sci 2025; 26:1690. [PMID: 40004153 PMCID: PMC11855061 DOI: 10.3390/ijms26041690] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2025] [Revised: 02/14/2025] [Accepted: 02/14/2025] [Indexed: 02/27/2025] Open
Abstract
Lung cancer exhibits substantial inter- and intra-tumor heterogeneity, with features that present significant challenges in advancing biomarker discovery and the development of targeted therapeutics. To fill this gap, we employed single-cell RNA sequencing (scRNA-seq) and advanced bioinformatics tools to evaluate the transcriptomic heterogeneity of immortalized, non-transformed (BEAS2B) and transformed (H460) lung epithelial cell lines and their responses to carcinogen challenge. Gene expression profiles resolved four primary clusters further discretized into unique subclusters based on genetic signatures and phenotypic profiles. Profiles of long non-coding RNAs (lncRNAs) identified microRNA host genes, antisense RNA genes, divergent transcript, and long intergenic non-coding RNAs as contributors to cellular heterogeneity. These findings indicate that distinct patterns of gene expression, remarkably in lncRNAs, define cellular heterogeneity in non-transformed versus transformed cells. These features can be exploited for the development of therapies directed at specific cell subpopulations in precancerous lesions and within lung tumors.
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Affiliation(s)
- Sokviseth Moeng
- Center for Genomic and Precision Medicine, Texas A&M Institute of Biosciences and Technology, Texas Medical Center, Houston, TX 77030, USA; (S.M.); (A.D.C.-P.)
| | - Andres D. Chamorro-Parejo
- Center for Genomic and Precision Medicine, Texas A&M Institute of Biosciences and Technology, Texas Medical Center, Houston, TX 77030, USA; (S.M.); (A.D.C.-P.)
| | - Minsun S. Jeon
- Center for Epigenetics and Disease Prevention, Texas A&M Institute of Biosciences and Technology, Texas Medical Center, Houston, TX 77030, USA;
| | - James J. Cai
- Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, TX 77843, USA;
| | - Kenneth S. Ramos
- Center for Genomic and Precision Medicine, Texas A&M Institute of Biosciences and Technology, Texas Medical Center, Houston, TX 77030, USA; (S.M.); (A.D.C.-P.)
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16
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An Q, Duan L, Wang Y, Wang F, Liu X, Liu C, Hu Q. Role of CD4 + T cells in cancer immunity: a single-cell sequencing exploration of tumor microenvironment. J Transl Med 2025; 23:179. [PMID: 39953548 PMCID: PMC11829416 DOI: 10.1186/s12967-025-06167-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2024] [Accepted: 01/22/2025] [Indexed: 02/17/2025] Open
Abstract
Recent oncological research has intensely focused on the tumor immune microenvironment (TME), particularly the functions of CD4 + T lymphocytes. CD4+ T lymphocytes have been implicated in antigen presentation, cytokine release, and cytotoxicity, suggesting their contribution to the dynamics of the TME. Furthermore, the application of single-cell sequencing has yielded profound insights into the phenotypic diversity and functional specificity of CD4+ T cells in the TME. In this review, we discuss the current findings from single-cell analyses, emphasizing the heterogeneity of CD4+ T cell subsets and their implications in tumor immunology. In addition, we review the critical signaling pathways and molecular networks underpinning CD4+ T cell activities, thereby offering novel perspectives on therapeutic targets and strategies for cancer treatment and prognosis.
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Affiliation(s)
- Qi An
- Department of Oncology, Renmin Hospital of Wuhan University, Wuhan, 430060, China
| | - Li Duan
- Department of Oncology, Renmin Hospital of Wuhan University, Wuhan, 430060, China
| | - Yuanyuan Wang
- Department of Oncology, Renmin Hospital of Wuhan University, Wuhan, 430060, China
| | - Fuxin Wang
- Department of Oncology, Renmin Hospital of Wuhan University, Wuhan, 430060, China
| | - Xiang Liu
- Department of Radiation Oncology, The Affiliated Cancer Hospital of Gannan Medical University, Jiangxi, 341000, China.
| | - Chao Liu
- Department of Radiation Oncology, Peking University First Hospital, Beijing, 100034, China.
| | - Qinyong Hu
- Department of Oncology, Renmin Hospital of Wuhan University, Wuhan, 430060, China.
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17
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Yoo S, Patel AS, Karam S, Zhong Y, Wang L, Jiang F, Kong R, Bikvan S, Wang W, Sinha A, Powell CA, Zhu J, Watanabe H. Transcriptional regulatory network analysis identifies GRN as a key regulator bridging chemotherapy and immunotherapy response in small cell lung cancer. J Hematol Oncol 2025; 18:14. [PMID: 39910394 PMCID: PMC11796135 DOI: 10.1186/s13045-025-01667-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2024] [Accepted: 01/25/2025] [Indexed: 02/07/2025] Open
Abstract
Small cell lung cancer (SCLC) is an aggressive and heterogeneous subtype, representing 15% of lung cancer cases. Although SCLC initially responds to etoposide and platinum (EP) chemotherapy, nearly all patients relapse with resistant tumors. While recent advances in immunotherapy have shown promise, only 10-20% of patients benefit, and effective stratification methods are lacking. The mechanisms of resistance to both therapeutics remain obscure. In this study, we aimed to gain insights into those leveraging a recent surge in the field of SCLC genomics. We constructed a regulatory network for SCLC and identified granulin precursor (GRN) as a hub of EP response associated genes. GRN-low patients showed improved survival with chemotherapy, while GRN-high patients exhibited resistance. GRN overexpression in SCLC cells conferred resistance to EP treatment and suppressed neuroendocrine features. GRN and its associated genes were linked to cancer cell intrinsic immunogenicity, and single-cell RNA-seq data revealed that GRN expression is particularly high in subsets of tumor-associated macrophages. In concordance with these findings, GRN-low tumors showed significantly better survival with chemo-immunotherapy, while GRN-high tumors did not benefit from additional immunotherapy. GRN-high tumors, associated with non-neuroendocrine (non-NE) subtypes, had a higher level of macrophage infiltration, potentially contributing to immunotherapy resistance. These results highlight GRN as a critical regulator of chemo-resistance and a potential biomarker for immunotherapy resistance in SCLC. Targeted therapeutic strategies for GRN-low patients could improve outcomes, while new approaches are needed for GRN-high patients. Overall, our findings implicate GRN as a bridge between chemotherapy and immunotherapy resistance through GRN-mediated mechanisms.
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Affiliation(s)
- Seungyeul Yoo
- GeneDx, 333 Ludlow Street, North Tower, 6th Floor, Stamford, CT, 06902, USA
| | - Ayushi S Patel
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, 1468 Madison Avenue, New York, NY, 10029, USA
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY, 10029, USA
| | - Sarah Karam
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, 1468 Madison Avenue, New York, NY, 10029, USA
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY, 10029, USA
| | - Yi Zhong
- GeneDx, 333 Ludlow Street, North Tower, 6th Floor, Stamford, CT, 06902, USA
| | - Li Wang
- GeneDx, 333 Ludlow Street, North Tower, 6th Floor, Stamford, CT, 06902, USA
| | - Feng Jiang
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, 1468 Madison Avenue, New York, NY, 10029, USA
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY, 10029, USA
| | - Ranran Kong
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, 1468 Madison Avenue, New York, NY, 10029, USA
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY, 10029, USA
- Department of Thoracic Surgery, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Sharon Bikvan
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, 1468 Madison Avenue, New York, NY, 10029, USA
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY, 10029, USA
| | - Wenhui Wang
- GeneDx, 333 Ludlow Street, North Tower, 6th Floor, Stamford, CT, 06902, USA
| | - Abhilasha Sinha
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, 1468 Madison Avenue, New York, NY, 10029, USA
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY, 10029, USA
| | - Charles A Powell
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, 1468 Madison Avenue, New York, NY, 10029, USA
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY, 10029, USA
| | - Jun Zhu
- GeneDx, 333 Ludlow Street, North Tower, 6th Floor, Stamford, CT, 06902, USA.
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY, 10029, USA.
| | - Hideo Watanabe
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, 1468 Madison Avenue, New York, NY, 10029, USA.
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY, 10029, USA.
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1468 Madison Avenue, New York, NY, 10029, USA.
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18
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Xiang X, Tao X, Hua K, Jiang H, Ding J. Single-cell RNA sequencing reveals tumor heterogeneity in small cell neuroendocrine cervical carcinoma. Commun Biol 2025; 8:184. [PMID: 39910262 PMCID: PMC11799506 DOI: 10.1038/s42003-025-07605-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2024] [Accepted: 01/26/2025] [Indexed: 02/07/2025] Open
Abstract
Small cell neuroendocrine cervical carcinoma (SCNECC) is an aggressive gynecological malignancy with poor prognosis. The precision therapeutic strategies for SCNECC are severely limited by the complex tumor microenvironment. Here, we mapped the single-cell landscape of a total of six samples from matched SCNECC cancerous foci and normal adjacent cervical tissues. Through analysis of 68,455 high-quality cells, malignant epithelial cells were identified with increased neuroendocrine differentiation and reduced keratinization. Within four epithelial cell clusters, the key transcription factors ASCL1, NEUROD1, POU2F3, and YAP1 defined molecular subtypes. Transitional trajectory among subtypes characterized two distinct carcinogenesis pathways in SCNECC. The P-type SCNECC showed potentially enhanced immune infiltration over other subtypes. Intercellular communication analysis identified several immune checkpoints and differentially expressed signaling pathways among subtypes. Through western blotting, the TC-YIK cell line was identified as an N-type SCNECC cell with high expression of SLFN11 and mTOR. Based on immunohistochemical staining of malignant subtyping markers, a cohort of 66 SCNECC patients from our hospital were divided into five subtypes. We further combined YAP1 expression with other clinicopathological factors (Cox p < 0.05) to establish a prognostic nomogram. Overall, these findings provide clues for tumorigenesis, precision treatments and prognostic prediction in SCNECC.
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Affiliation(s)
- Xuesong Xiang
- Department of Gynecological Oncology, The Obstetrics and Gynecology Hospital of Fudan University, Shanghai, P. R. China
- Shanghai Key Laboratory of Female Reproductive Endocrine-related Diseases, The Obstetrics and Gynecology Hospital of Fudan University, Shanghai, P. R. China
| | - Xiang Tao
- Department of Pathology, The Obstetrics and Gynecology Hospital of Fudan University, Shanghai, P.R. China
| | - Keqin Hua
- Department of Gynecological Oncology, The Obstetrics and Gynecology Hospital of Fudan University, Shanghai, P. R. China.
- Shanghai Key Laboratory of Female Reproductive Endocrine-related Diseases, The Obstetrics and Gynecology Hospital of Fudan University, Shanghai, P. R. China.
| | - Hua Jiang
- Department of Gynecological Oncology, The Obstetrics and Gynecology Hospital of Fudan University, Shanghai, P. R. China.
- Shanghai Key Laboratory of Female Reproductive Endocrine-related Diseases, The Obstetrics and Gynecology Hospital of Fudan University, Shanghai, P. R. China.
| | - Jingxin Ding
- Department of Gynecological Oncology, The Obstetrics and Gynecology Hospital of Fudan University, Shanghai, P. R. China.
- Shanghai Key Laboratory of Female Reproductive Endocrine-related Diseases, The Obstetrics and Gynecology Hospital of Fudan University, Shanghai, P. R. China.
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19
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Li M, Wang X, Gong J, Lu H. The analysis of molecular classification of pulmonary neuroendocrine tumors and relationship between YAP1 and efficacy. Invest New Drugs 2025; 43:108-117. [PMID: 39786663 DOI: 10.1007/s10637-024-01492-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2024] [Accepted: 12/12/2024] [Indexed: 01/12/2025]
Abstract
A novel molecular classification for small cell lung cancer (SCLC) has been established utilizing the transcription factors achaete-scute homologue 1 (ASCL1), neurogenic differentiation factor 1 (NeuroD1), POU class 2 homeobox 3 (POU2F3), and yes-associated protein 1 (YAP1). This classification was predicated on the transcription factors. Conversely, there is a paucity of information regarding the distribution of these markers in other subtypes of pulmonary neuroendocrine tumors (PNET). Clinical and survival data for PNET patients were gathered from January 2008 to December 2020. Immunohistochemical analysis was employed to evaluate the expression. The relationship between YAP1 expression and outcomes in patients with pulmonary large cell neuroendocrine carcinoma (LCNEC) was examined. Data from low-grade PNET patients who had previously undergone immunotherapy were retrospectively gathered and analyzed. The ASCL1 positive rate was markedly elevated in SCLC (7.1% vs. 60%; P < 0.001) and LCNEC patients (7.1% vs. 38.5%; P = 0.034) compared to PC patients. The YAP1-positive rate was elevated in LCNEC compared to SCLC (43.6% vs. 20%, P = 0.028) and pulmonary carcinoid (PC) patients (43.6% vs. 21.4%; P = 0.021). The DLL3-positive rate in SCLC patients was greater than in SCLC and PC patients (37.1% vs. 23.1% vs. 0%; P = 0.028, P = 0.021). A significant level of tumor heterogeneity was noted, with SCLC and LCNEC patients exhibiting markedly higher heterogeneity than PC patients (65.7% vs. 56.3% vs. 21.4%; P = 0.005, P = 0.025). In patients with LCNEC, YAP1 positivity exhibited no correlation with PD-L1 expression (17.1% vs. 45.7%, P = 0.518). Tumor heterogeneity was also noted in transformed SCLC, with no significant differences in the expression levels of transcription factors between transformed and traditional SCLC. In 13 LCNEC patients with a history of ICI application, YAP1 exhibited no significant effect on PFS (P = 0.331) or OS (P = 0.17) in the subgroup analysis of LCNEC patients. Among the 14 patients with low-grade PNET who underwent immunotherapy, the disease control rate was 85.7%. Patients with high-grade PNET have high levels of expression of ASCL1 and DLL3, whereas patients with LCNEC have high levels of expression of YAP1. With regard to the transcription factor level, it was found that patients with SCLC and LCNEC had a much higher degree of tumor heterogeneity than those with PC. In patients with LCNEC who were receiving monotherapy of ICIs or chemotherapy in combination with ICIs, the expression of YAP1 did not appear to have any clear impact on the prognosis. This is due to the limited sample size of the study, which requires additional investigation. When compared to the expression of TFs in regular SCLC, the expression of TFs in converted SCLC is comparable.
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Affiliation(s)
- Meihui Li
- Department of Radiotherapy, Shaoxing Second Hospital, Shaoxing, Zhejiang, China
| | - Xinyuan Wang
- Postgraduate Training Base Alliance, Wenzhou Medical University (Zhejiang Cancer Hospital), Hangzhou, 310022, Zhejiang, China
- Department of Thoracic Medical Oncology, Zhejiang Cancer Hospital, Hangzhou, 310022, China
| | - Jiali Gong
- Department of Hematology and Oncology, Ningbo No. 2 Hospital, Ningbo, Zhejiang, China
| | - Hongyang Lu
- Postgraduate Training Base Alliance, Wenzhou Medical University (Zhejiang Cancer Hospital), Hangzhou, 310022, Zhejiang, China.
- Department of Thoracic Medical Oncology, Zhejiang Cancer Hospital, Hangzhou, 310022, China.
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20
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Yuan L, Li S, Zhu Y, Yang L, Zhang X, Qu Y, Wang Z, Duan J, Zhong J, Tian Y, Liu L, Sun B, Fei K, Liu Z, Zhang J, He Y, Guo Y, He D, Zhuang W, Zhang J, Ma Z, Bai H, Wang J. ATAD2 is a potential immunotherapy target for patients with small cell lung cancer harboring HLA-A∗0201. EBioMedicine 2025; 112:105515. [PMID: 39808946 PMCID: PMC11782892 DOI: 10.1016/j.ebiom.2024.105515] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2024] [Revised: 12/05/2024] [Accepted: 12/06/2024] [Indexed: 01/16/2025] Open
Abstract
BACKGROUND Small cell lung cancer (SCLC) represents a highly aggressive neuroendocrine tumour with a dismal prognosis. Currently, the identification of a specific tumour antigen that can facilitate immune-based therapies for SCLC remains elusive. METHODS We employed liquid chromatography-tandem mass spectrometry (LC-MS/MS) to analyse cancer/testis antigens (CTAs) in SCLC cell lines and human tumour specimens. Immunohistochemistry of clinical specimens was performed to compare protein expression in SCLC, non-small cell lung cancer (NSCLC), and matched normal-adjacent tissues. Additionally, publicly available RNA sequencing databases were interrogated to identify gene expression patterns in different SCLC subtypes and in different disease stages. FINDINGS Distinct numbers and types of CTAs were identified across SCLC subtypes, with significantly higher expression levels of ATPase family AAA domain-containing protein 2 (ATAD2) observed in SCLC compared to normal adjacent tissues and NSCLC tissues. A dynamic expression pattern of ATAD2 was found throughout the clinical course of SCLC and exhibited a positive correlation with achaete-scute family bHLH transcription factor 1 (ASCL1) expression in SCLC. Immunopeptidomics analysis identified the YSDDDVPSV sequence derived from the HLA-A∗02:01 restriction epitope of ATAD2 as a highly promising tumour antigen candidate for potential immunotherapy applications. YSDDDVPSV immunopeptides were confirmed to be present in SCLC-A and SCLC-N with HLA-A∗02:01 restriction. Notably, HLA-A∗02:01 T cells exhibited a robust response upon stimulation with YSDDDVPSV immunopeptide pulsed by T2 cells. INTERPRETATION Our findings highlight the potential of targeting the ATAD2 YSDDDVPSV immunopeptide for SCLC immunotherapy, thereby offering a promising avenue for the development of adoptive T cell therapies to effectively treat ASCL1-positive or NEUROD1-positive SCLC carrying HLA-A∗02:01. FUNDING This study was supported by the National key R&D program of China (2022YFC2505000); National Natural Science Foundation of China (NSFC) general program (82272796) NSFC special program (82241229); CAMS Innovation Fund for Medical Sciences (CIFMS 2022-I2M-1-009); CAMS Key Laboratory of Translational Research on Lung Cancer (2018PT31035); Aiyou foundation (KY201701). National key R&D program of China (2022YFC2505004). NSFC general program (81972905). Medical Oncology Key Foundation of Cancer Hospital Chinese Academy of Medical Sciences (CICAMS-MOCP2022012).
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Affiliation(s)
- Li Yuan
- State Key Laboratory of Molecular Oncology, CAMS Key Laboratory of Translational Research on Lung Cancer, Department of Medical Oncology, National Cancer Centre/National Clinical Research Centre for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences Peking Union Medical College, Beijing, 100021, China
| | - Sini Li
- Department of Medical Thoracic Oncology, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, 310022, China
| | - Yixiang Zhu
- State Key Laboratory of Molecular Oncology, CAMS Key Laboratory of Translational Research on Lung Cancer, Department of Medical Oncology, National Cancer Centre/National Clinical Research Centre for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences Peking Union Medical College, Beijing, 100021, China
| | - Lin Yang
- Department of Pathology, National Cancer Centre/National Clinical Research Centre for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Xue Zhang
- State Key Laboratory of Molecular Oncology, CAMS Key Laboratory of Translational Research on Lung Cancer, Department of Medical Oncology, National Cancer Centre/National Clinical Research Centre for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences Peking Union Medical College, Beijing, 100021, China
| | - Yan Qu
- Department of Radiotherapy, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250021, China
| | - Zhijie Wang
- State Key Laboratory of Molecular Oncology, CAMS Key Laboratory of Translational Research on Lung Cancer, Department of Medical Oncology, National Cancer Centre/National Clinical Research Centre for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences Peking Union Medical College, Beijing, 100021, China
| | - Jianchun Duan
- State Key Laboratory of Molecular Oncology, CAMS Key Laboratory of Translational Research on Lung Cancer, Department of Medical Oncology, National Cancer Centre/National Clinical Research Centre for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences Peking Union Medical College, Beijing, 100021, China
| | - Jia Zhong
- State Key Laboratory of Molecular Oncology, CAMS Key Laboratory of Translational Research on Lung Cancer, Department of Medical Oncology, National Cancer Centre/National Clinical Research Centre for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences Peking Union Medical College, Beijing, 100021, China
| | - Yanhua Tian
- State Key Laboratory of Molecular Oncology, CAMS Key Laboratory of Translational Research on Lung Cancer, Department of Medical Oncology, National Cancer Centre/National Clinical Research Centre for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences Peking Union Medical College, Beijing, 100021, China
| | - Lihui Liu
- State Key Laboratory of Molecular Oncology, CAMS Key Laboratory of Translational Research on Lung Cancer, Department of Medical Oncology, National Cancer Centre/National Clinical Research Centre for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences Peking Union Medical College, Beijing, 100021, China
| | - Boyang Sun
- State Key Laboratory of Molecular Oncology, CAMS Key Laboratory of Translational Research on Lung Cancer, Department of Medical Oncology, National Cancer Centre/National Clinical Research Centre for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences Peking Union Medical College, Beijing, 100021, China
| | - Kailun Fei
- State Key Laboratory of Molecular Oncology, CAMS Key Laboratory of Translational Research on Lung Cancer, Department of Medical Oncology, National Cancer Centre/National Clinical Research Centre for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences Peking Union Medical College, Beijing, 100021, China
| | - Zheng Liu
- State Key Laboratory of Molecular Oncology, CAMS Key Laboratory of Translational Research on Lung Cancer, Department of Medical Oncology, National Cancer Centre/National Clinical Research Centre for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences Peking Union Medical College, Beijing, 100021, China
| | - Jian Zhang
- State Key Laboratory of Molecular Oncology, CAMS Key Laboratory of Translational Research on Lung Cancer, Department of Medical Oncology, National Cancer Centre/National Clinical Research Centre for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences Peking Union Medical College, Beijing, 100021, China
| | - Yan He
- State Key Laboratory of Molecular Oncology, CAMS Key Laboratory of Translational Research on Lung Cancer, Department of Medical Oncology, National Cancer Centre/National Clinical Research Centre for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences Peking Union Medical College, Beijing, 100021, China
| | - Yufeng Guo
- State Key Laboratory of Molecular Oncology, CAMS Key Laboratory of Translational Research on Lung Cancer, Department of Medical Oncology, National Cancer Centre/National Clinical Research Centre for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences Peking Union Medical College, Beijing, 100021, China
| | - DanMing He
- State Key Laboratory of Molecular Oncology, CAMS Key Laboratory of Translational Research on Lung Cancer, Department of Medical Oncology, National Cancer Centre/National Clinical Research Centre for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences Peking Union Medical College, Beijing, 100021, China
| | - Wei Zhuang
- State Key Laboratory of Molecular Oncology, CAMS Key Laboratory of Translational Research on Lung Cancer, Department of Medical Oncology, National Cancer Centre/National Clinical Research Centre for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences Peking Union Medical College, Beijing, 100021, China
| | - Jinsong Zhang
- State Key Laboratory of Molecular Oncology, CAMS Key Laboratory of Translational Research on Lung Cancer, Department of Medical Oncology, National Cancer Centre/National Clinical Research Centre for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences Peking Union Medical College, Beijing, 100021, China
| | - Zixiao Ma
- State Key Laboratory of Molecular Oncology, CAMS Key Laboratory of Translational Research on Lung Cancer, Department of Medical Oncology, National Cancer Centre/National Clinical Research Centre for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences Peking Union Medical College, Beijing, 100021, China
| | - Hua Bai
- State Key Laboratory of Molecular Oncology, CAMS Key Laboratory of Translational Research on Lung Cancer, Department of Medical Oncology, National Cancer Centre/National Clinical Research Centre for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences Peking Union Medical College, Beijing, 100021, China
| | - Jie Wang
- State Key Laboratory of Molecular Oncology, CAMS Key Laboratory of Translational Research on Lung Cancer, Department of Medical Oncology, National Cancer Centre/National Clinical Research Centre for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences Peking Union Medical College, Beijing, 100021, China.
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21
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Shi Z, Jia L, Wang B, Wang S, He L, Li Y, Wang G, Song W, He X, Liu Z, Shi C, Tian Y, Zhu K. Integration of Single-Cell and Bulk Transcriptomes to Identify a Poor Prognostic Tumor Subgroup to Predict the Prognosis of Patients with Early-stage Lung Adenocarcinoma. J Cancer 2025; 16:1397-1412. [PMID: 39895784 PMCID: PMC11786047 DOI: 10.7150/jca.105926] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2024] [Accepted: 12/29/2024] [Indexed: 02/04/2025] Open
Abstract
Background: Single-cell RNA sequencing (scRNA-seq) has emerged as a pivotal technology for investigating novel therapeutic targets in cancer. Despite its significance, there remains a scarcity of studies utilizing this technology to address treatment strategies specifically tailored for early-stage lung adenocarcinoma (LUAD). Consequently, this study aimed to investigate the tumor microenvironment (TME) characteristics and develop a prognostic model for early-stage LUAD. Methods: The markers identifying cell types were obtained from the CellMarker database and published research. The SCEVAN package was employed for identifying malignant lung epithelial cells. Single-cell downstream analyses were conducted using the SCP package, encompassing gene set enrichment analysis, enrichment analysis, pseudotime trajectory analysis, and differential expression analysis. Calibration curves, receiver operating characteristic curves, and decision curve analysis were employed to assess the performance of the prognostic model for LUAD. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR), western blot, cell transfection, cell proliferation, and cell invasion assays were performed to validate the expression and biological function. Results: Seven cell types were distinguished in the scRNA-seq dataset through the utilization of cell markers documented in published literature. Four subpopulations of early-stage LUAD tumor cells exhibited a high degree of heterogeneity. The prognostic model constructed by PERP and KRT8 showed a great prediction for distinguishing the early-stage LUAD and normal tissues. The validation of PERP and KRT8 expression levels was carried out through both RT-qPCR and western blot analyses. Eventually, in vitro experiments, including CCK8, colony formation, EdU, and transwell assays, confirmed that KRT8 and PERP could promote LUAD cell proliferation and migration. Conclusions: Our study provided a comprehensive characterization of the TME in LUAD through integrative single-cell and bulk transcriptomic analyses. We identified dynamic transitions from normal epithelial cells to tumor cells, revealing the heterogeneity and evolution of malignant LUAD cells. The novel prognostic model based on KRT8 and PERP demonstrated robust predictive performance, offering a promising tool for early-stage LUAD risk stratification. Functional experiments further confirmed that KRT8 and PERP promote tumor proliferation and migration, providing new insights into their roles as therapeutic targets.
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Affiliation(s)
- Zijian Shi
- Department of Thoracic Surgery, Ningbo Medical Center Lihuili Hospital, Ningbo University, Ningbo, Zhejiang Province, 315040, China
- Department of Lung Cancer Surgery, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Linchuang Jia
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Tianjin Medical University Cancer, Tianjin, 300070, China
| | - Baichuan Wang
- Anhui Chest Hospital, Anhui Medical University Clinical College of Chest, Hefei, Anhui Province, 230022, China
| | - Shuo Wang
- The First Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin 300060, China
| | - Long He
- Department of General Surgery, Tianjin Medical University General Hospital, Tianjin Key Laboratory of Precise Vascular Reconstruction and Organ Function Repair, Tianjin General Surgery Institute, Tianjin, 300052, China
| | - Yingxi Li
- Immunology Department, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), Tianjin Medical University, Tianjin, 300070, China
| | - Guixin Wang
- The First Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin 300060, China
| | - Wenbin Song
- Department of General Surgery, Tianjin Medical University General Hospital, Tianjin Key Laboratory of Precise Vascular Reconstruction and Organ Function Repair, Tianjin General Surgery Institute, Tianjin, 300052, China
| | - Xianneng He
- Health Science Center, Ningbo University, Ningbo, Zhejiang Province, 315040, China
| | - Zhaoyi Liu
- Department of General Surgery, Tianjin Medical University General Hospital, Tianjin Key Laboratory of Precise Vascular Reconstruction and Organ Function Repair, Tianjin General Surgery Institute, Tianjin, 300052, China
| | - Cangchang Shi
- Department of General Surgery, Tianjin Medical University General Hospital, Tianjin Key Laboratory of Precise Vascular Reconstruction and Organ Function Repair, Tianjin General Surgery Institute, Tianjin, 300052, China
| | - Yao Tian
- The First Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin 300060, China
- Department of General Surgery, Tianjin Medical University General Hospital, Tianjin Key Laboratory of Precise Vascular Reconstruction and Organ Function Repair, Tianjin General Surgery Institute, Tianjin, 300052, China
| | - Keyun Zhu
- Department of Thoracic Surgery, Ningbo Medical Center Lihuili Hospital, Ningbo University, Ningbo, Zhejiang Province, 315040, China
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22
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Sun F, Li H, Sun D, Fu S, Gu L, Shao X, Wang Q, Dong X, Duan B, Xing F, Wu J, Xiao M, Zhao F, Han JDJ, Liu Q, Fan X, Li C, Wang C, Shi T. Single-cell omics: experimental workflow, data analyses and applications. SCIENCE CHINA. LIFE SCIENCES 2025; 68:5-102. [PMID: 39060615 DOI: 10.1007/s11427-023-2561-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 04/18/2024] [Indexed: 07/28/2024]
Abstract
Cells are the fundamental units of biological systems and exhibit unique development trajectories and molecular features. Our exploration of how the genomes orchestrate the formation and maintenance of each cell, and control the cellular phenotypes of various organismsis, is both captivating and intricate. Since the inception of the first single-cell RNA technology, technologies related to single-cell sequencing have experienced rapid advancements in recent years. These technologies have expanded horizontally to include single-cell genome, epigenome, proteome, and metabolome, while vertically, they have progressed to integrate multiple omics data and incorporate additional information such as spatial scRNA-seq and CRISPR screening. Single-cell omics represent a groundbreaking advancement in the biomedical field, offering profound insights into the understanding of complex diseases, including cancers. Here, we comprehensively summarize recent advances in single-cell omics technologies, with a specific focus on the methodology section. This overview aims to guide researchers in selecting appropriate methods for single-cell sequencing and related data analysis.
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Affiliation(s)
- Fengying Sun
- Department of Clinical Laboratory, the Affiliated Wuhu Hospital of East China Normal University (The Second People's Hospital of Wuhu City), Wuhu, 241000, China
| | - Haoyan Li
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Dongqing Sun
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Frontier Science Center for Stem Cells, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Shaliu Fu
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine, Shanghai East Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Research Institute of Intelligent Computing, Zhejiang Lab, Hangzhou, 311121, China
- Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai, 201210, China
| | - Lei Gu
- Center for Single-cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xin Shao
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
- National Key Laboratory of Chinese Medicine Modernization, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing, 314103, China
| | - Qinqin Wang
- Center for Single-cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xin Dong
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Frontier Science Center for Stem Cells, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Bin Duan
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine, Shanghai East Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Research Institute of Intelligent Computing, Zhejiang Lab, Hangzhou, 311121, China
- Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai, 201210, China
| | - Feiyang Xing
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Frontier Science Center for Stem Cells, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Jun Wu
- Center for Bioinformatics and Computational Biology, Shanghai Key Laboratory of Regulatory Biology, the Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China
| | - Minmin Xiao
- Department of Clinical Laboratory, the Affiliated Wuhu Hospital of East China Normal University (The Second People's Hospital of Wuhu City), Wuhu, 241000, China.
| | - Fangqing Zhao
- Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Jing-Dong J Han
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, 100871, China.
| | - Qi Liu
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China.
- Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine, Shanghai East Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China.
- Research Institute of Intelligent Computing, Zhejiang Lab, Hangzhou, 311121, China.
- Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai, 201210, China.
| | - Xiaohui Fan
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China.
- National Key Laboratory of Chinese Medicine Modernization, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing, 314103, China.
- Zhejiang Key Laboratory of Precision Diagnosis and Therapy for Major Gynecological Diseases, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, 310006, China.
| | - Chen Li
- Center for Single-cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
| | - Chenfei Wang
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China.
- Frontier Science Center for Stem Cells, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China.
| | - Tieliu Shi
- Department of Clinical Laboratory, the Affiliated Wuhu Hospital of East China Normal University (The Second People's Hospital of Wuhu City), Wuhu, 241000, China.
- Center for Bioinformatics and Computational Biology, Shanghai Key Laboratory of Regulatory Biology, the Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China.
- Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE, School of Statistics, East China Normal University, Shanghai, 200062, China.
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Lee E, Lee SY, Seong YJ, Ku B, Cho HJ, Kim K, Hwang Y, Park CK, Choi JY, Kim SW, Kim SJ, Lim JU, Yeo CD, Lee DW. Lung cancer organoid-based drug evaluation models and new drug development application trends. Transl Lung Cancer Res 2024; 13:3741-3763. [PMID: 39830742 PMCID: PMC11736608 DOI: 10.21037/tlcr-24-603] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2024] [Accepted: 11/26/2024] [Indexed: 01/22/2025]
Abstract
Lung cancer is a malignant tumor with high incidence and mortality rates in both men and women worldwide. Although anticancer drugs are prescribed to treat lung cancer patients, individual responses to these drugs vary, making it crucial to identify the most suitable treatment for each patient. Therefore, it is necessary to develop an anticancer drug efficacy prediction model that can analyze drug efficacy before patient treatment and establish personalized treatment strategies. Unlike two-dimensional (2D) cultured lung cancer cells, lung cancer organoid (LCO) models have a three-dimensional (3D) structure that effectively mimics the characteristics and heterogeneity of lung cancer cells. Lung cancer patient-derived organoids (PDOs) also have the advantage of recapitulating histological and genetic characteristics similar to those of patient tissues under in vitro conditions. Due to these advantages, LCO models are utilized in various fields, including cancer research, and precision medicine, and are especially employed in various new drug development processes, such as targeted therapies and immunotherapy. LCO models demonstrate potential applications in precision medicine and new drug development research. This review discusses the various methods for implementing LCO models, LCO-based anticancer drug efficacy analysis models, and new trends in lung cancer-targeted drug development.
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Affiliation(s)
- Eunyoung Lee
- Division of Pulmonology, Department of Internal Medicine, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
- Postech-Catholic Biomedical Engineering Institute, Songeui Multiplex Hall, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Sang-Yun Lee
- Department of Biomedical Engineering, Gachon University, Seongnam, Republic of Korea
- Central Research and Development Center, Medical & Bio Decision (MBD) Co., Ltd., Suwon, Republic of Korea
| | - Yu-Jeong Seong
- Department of Biomedical Engineering, Gachon University, Seongnam, Republic of Korea
| | - Bosung Ku
- Central Research and Development Center, Medical & Bio Decision (MBD) Co., Ltd., Suwon, Republic of Korea
| | - Hyeong Jun Cho
- Division of Pulmonology, Department of Internal Medicine, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
- Postech-Catholic Biomedical Engineering Institute, Songeui Multiplex Hall, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Kyuhwan Kim
- Division of Pulmonology, Department of Internal Medicine, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
- Postech-Catholic Biomedical Engineering Institute, Songeui Multiplex Hall, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Yongki Hwang
- Division of Pulmonology, Department of Internal Medicine, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
- Postech-Catholic Biomedical Engineering Institute, Songeui Multiplex Hall, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Chan Kwon Park
- Division of Pulmonary, Critical Care and Allergy, Department of Internal Medicine, Yeouido St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Joon Young Choi
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Incheon St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Sung Won Kim
- Department of Otorhinolaryngology-Head and Neck Surgery, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
- Department of Biomedicine & Health Sciences, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Seung Joon Kim
- Division of Pulmonology, Department of Internal Medicine, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
- Postech-Catholic Biomedical Engineering Institute, Songeui Multiplex Hall, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Jeong Uk Lim
- Division of Pulmonary, Critical Care and Allergy, Department of Internal Medicine, Yeouido St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Chang Dong Yeo
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Eunpyeong St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Dong Woo Lee
- Department of Biomedical Engineering, Gachon University, Seongnam, Republic of Korea
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Schneider JL, Han S, Nabel CS. Fuel for thought: targeting metabolism in lung cancer. Transl Lung Cancer Res 2024; 13:3692-3717. [PMID: 39830762 PMCID: PMC11736591 DOI: 10.21037/tlcr-24-662] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2024] [Accepted: 11/22/2024] [Indexed: 01/22/2025]
Abstract
For over a century, we have appreciated that the biochemical processes through which micro- and macronutrients are anabolized and catabolized-collectively referred to as "cellular metabolism"-are reprogrammed in malignancies. Cancer cells in lung tumors rewire pathways of nutrient acquisition and metabolism to meet the bioenergetic demands for unchecked proliferation. Advances in precision medicine have ushered in routine genotyping of patient lung tumors, enabling a deeper understanding of the contribution of altered metabolism to tumor biology and patient outcomes. This paradigm shift in thoracic oncology has spawned a new enthusiasm for dissecting oncogenotype-specific metabolic phenotypes and creates opportunity for selective targeting of essential tumor metabolic pathways. In this review, we discuss metabolic states across histologic and molecular subtypes of lung cancers and the additional changes in tumor metabolic pathways that occur during acquired therapeutic resistance. We summarize the clinical investigation of metabolism-specific therapies, addressing successes and limitations to guide the evaluation of these novel strategies in the clinic. Beyond changes in tumor metabolism, we also highlight how non-cellular autonomous processes merit particular consideration when manipulating metabolic processes systemically, such as efforts to disentangle how lung tumor cells influence immunometabolism. As the future of metabolic therapeutics hinges on use of models that faithfully recapitulate metabolic rewiring in lung cancer, we also discuss best practices for harmonizing workflows to capture patient specimens for translational metabolic analyses.
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Affiliation(s)
- Jaime L. Schneider
- Department of Medicine and Cancer Center, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | | | - Christopher S. Nabel
- Department of Medicine and Cancer Center, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA
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25
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Lu Y, Li H, Zhao P, Wang X, Shao W, Liu Y, Tian L, Zhong R, Liu H, Cheng Y. Crosstalk between cancer-associated fibroblasts and non-neuroendocrine tumor cells in small cell lung cancer involves in glycolysis and antigen-presenting features. Mol Med 2024; 30:274. [PMID: 39722014 DOI: 10.1186/s10020-024-01051-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2024] [Accepted: 12/18/2024] [Indexed: 12/28/2024] Open
Abstract
BACKGROUND Small cell lung cancer (SCLC) is a highly fatal malignancy, the complex tumor microenvironment (TME) is a critical factor affecting SCLC progression. Cancer-associated fibroblasts (CAFs) are crucial components of TME, yet their role in SCLC and the underlying mechanisms during their interaction with SCLC cells remain to be determined. METHODS Microenvironmental cell components were estimated using transcriptome data from SCLC tissue available in public databases, analyzed with bioinformatic algorithms. A co-culture system comprising MRC5 fibroblasts and SCLC cell lines was constructed. RNA sequencing (RNA-seq) was performed on co-cultured and separately cultured MRC5 and H196 cells to identify differentially expressed genes (DEGs) and enriched signaling pathways. Glycolysis and STING signaling in SCLC cells were assessed using glucose uptake assays, qRT-PCR, and Western blot analysis. Immunohistochemical staining of SCLC tissue arrays quantified α-SMA, HLA-DRA and CD8 expression. RESULTS Non-neuroendocrine (non-NE) SCLC-derived CAFs exhibited more abundance and DEGs than NE SCLC-derived CAFs did, which interact with non-NE SCLC cells can induce the enrichment of glycolysis-related genes, increasement of glucose uptake, upregulation of glycolytic signaling proteins in non-NE SCLC cells and accumulation of lactate in the extracellular environment, confirming CAF-mediated glycolysis promotion. Additionally, glycolysis-induced ATP production activated STING signaling in non-NE SCLC cells, which upregulated T cell chemo-attractants. However, CAF abundance did not correlate with CD8 + T cell numbers in SCLC tissues. Additionally, non-NE SCLC cell-educated CAFs exhibited features of antigen-presenting CAFs (apCAFs), as indicated by the expression of major histocompatibility complex (MHC) molecules. Co-localization of HLA-DRA and α-SMA signals in SCLC tissues confirmed apCAF presence. The apCAFs and CD8 + T cells were co-located in the SCLC stroma, and there was a positive correlation between CAFs and regulatory T cell (Treg) abundance. CONCLUSION Our findings suggest that crosstalk between CAFs and non-NE SCLC cells promotes glycolysis in non-NE SCLC cells, thereby increase T cell chemo-attractant expression via activating STING signaling. On the other hand, it promotes the presence of apCAFs, which probably contributes to CD8 + T cell trapping and Treg differentiation. This study emphasizes the pro-tumor function of CAFs in SCLC by promoting glycolysis and impairing T cell function, providing direction for the development of novel therapeutic approaches targeting CAF in SCLC.
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Affiliation(s)
- Yuanhua Lu
- Postdoctoral Research Workstation, Jilin Cancer Hospital, Changchun, 130012, China
| | - Hui Li
- Medical Oncology Translational Research Lab, Jilin Cancer Hospital, Changchun, 130012, China
| | - Peiyan Zhao
- Medical Oncology Translational Research Lab, Jilin Cancer Hospital, Changchun, 130012, China
| | - Xinyue Wang
- Postdoctoral Research Workstation, Jilin Cancer Hospital, Changchun, 130012, China
| | - Wenjun Shao
- Postdoctoral Research Workstation, Jilin Cancer Hospital, Changchun, 130012, China
| | - Yan Liu
- Medical Oncology Translational Research Lab, Jilin Cancer Hospital, Changchun, 130012, China
| | - Lin Tian
- Postdoctoral Research Workstation, Jilin Cancer Hospital, Changchun, 130012, China
| | - Rui Zhong
- Medical Oncology Translational Research Lab, Jilin Cancer Hospital, Changchun, 130012, China
| | - Haifeng Liu
- Jilin Cancer Hospital, Changchun, 130012, China.
| | - Ying Cheng
- Medical Oncology Translational Research Lab, Jilin Cancer Hospital, Changchun, 130012, China.
- Department of Medical Thoracic Oncology, Jilin Cancer Hospital, Changchun, 130012, China.
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Li H, Zhao P, Tian L, Lu Y, Wang X, Shao W, Cheng Y. Advances in biomarkers for immunotherapy in small-cell lung cancer. Front Immunol 2024; 15:1490590. [PMID: 39723215 PMCID: PMC11668642 DOI: 10.3389/fimmu.2024.1490590] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2024] [Accepted: 11/18/2024] [Indexed: 12/28/2024] Open
Abstract
Small-cell lung cancer (SCLC) is a refractory cancer with rapid growth and high aggressiveness. Extensive-stage SCLC is initially sensitive to chemotherapy; however, drug resistance and recurrence occur rapidly, resulting in a poor survival outcome due to lack of subsequently efficient therapy. The emergence of immune checkpoint inhibitors (ICIs) generated a new landscape of SCLC treatment and significantly prolonged the survival of patients. However, the unselected immunotherapy restrains both beneficiary population and responsive period in SCLC compared to the other tumors. The complex tumor origin, high heterogeneity, and immunosuppressive microenvironment may disturb the value of conventional biomarkers in SCLC including programmed cell death 1 ligand 1 and tumor mutation burden. Transcriptional regulator-based subtypes of SCLC are current research hotspot, revealing that Y (I) subtype can benefit from ICIs. Additionally, molecules related to immune microenvironment, immunogenicity, epigenetics, and SCLC itself also indicated the therapeutic benefits of ICIs, becoming potential predictive biomarkers. In this review, we discussed the advances of biomarkers for prediction and prognosis of immunotherapy, promising directions in the future, and provide reference and options for precision immunotherapy and survival improvement in patients with SCLC.
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Affiliation(s)
- Hui Li
- Medical Oncology Translational Research Lab, Jilin Cancer Hospital, Changchun, China
- Jilin Provincial Key Laboratory of Molecular Diagnostics for Lung Cancer, Jilin Cancer Hospital, Changchun, China
| | - Peiyan Zhao
- Medical Oncology Translational Research Lab, Jilin Cancer Hospital, Changchun, China
- Jilin Provincial Key Laboratory of Molecular Diagnostics for Lung Cancer, Jilin Cancer Hospital, Changchun, China
| | - Lin Tian
- Medical Oncology Translational Research Lab, Jilin Cancer Hospital, Changchun, China
- Jilin Provincial Key Laboratory of Molecular Diagnostics for Lung Cancer, Jilin Cancer Hospital, Changchun, China
- Postdoctoral Research Workstation, Jilin Cancer Hospital, Changchun, China
| | - Yuanhua Lu
- Medical Oncology Translational Research Lab, Jilin Cancer Hospital, Changchun, China
- Jilin Provincial Key Laboratory of Molecular Diagnostics for Lung Cancer, Jilin Cancer Hospital, Changchun, China
- Postdoctoral Research Workstation, Jilin Cancer Hospital, Changchun, China
| | - Xinyue Wang
- Medical Oncology Translational Research Lab, Jilin Cancer Hospital, Changchun, China
- Jilin Provincial Key Laboratory of Molecular Diagnostics for Lung Cancer, Jilin Cancer Hospital, Changchun, China
- Postdoctoral Research Workstation, Jilin Cancer Hospital, Changchun, China
| | - Wenjun Shao
- Medical Oncology Translational Research Lab, Jilin Cancer Hospital, Changchun, China
- Jilin Provincial Key Laboratory of Molecular Diagnostics for Lung Cancer, Jilin Cancer Hospital, Changchun, China
- Postdoctoral Research Workstation, Jilin Cancer Hospital, Changchun, China
| | - Ying Cheng
- Medical Oncology Translational Research Lab, Jilin Cancer Hospital, Changchun, China
- Jilin Provincial Key Laboratory of Molecular Diagnostics for Lung Cancer, Jilin Cancer Hospital, Changchun, China
- Department of Thoracic Oncology, Jilin Cancer Hospital, Changchun, China
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Lin F, Zhu LX, Ye ZM, Peng F, Chen MC, Li XM, Zhu ZH, Zhu Y. Computed Tomography-Based Intratumor Heterogeneity Predicts Response to Immunotherapy Plus Chemotherapy in Esophageal Squamous Cell Carcinoma. Acad Radiol 2024; 31:4886-4899. [PMID: 38981774 DOI: 10.1016/j.acra.2024.06.032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2024] [Revised: 06/20/2024] [Accepted: 06/21/2024] [Indexed: 07/11/2024]
Abstract
RATIONALE AND OBJECTIVES This study explored the intratumor heterogeneity (ITH) of esophageal squamous cell carcinoma (ESCC) using computed tomography (CT) and investigated the value of CT-based ITH in predicting the response to immune checkpoint inhibitor (ICI) plus chemotherapy in patients with ESCC. MATERIALS AND METHODS This retrospective study included 416 patients with ESCC who received ICI plus chemotherapy at two independent hospitals between January 2019 and July 2022. Multiparametric CT features were extracted from ESCC lesions and screened using hierarchical clustering and dimensionality reduction algorithms. Logistic regression and machine learning models based on selected features were developed to predict treatment response and validated in separate datasets. ITH was quantified using the score calculated by the best-performing model and visualized through feature clustering and feature contribution heatmaps. A gene set enrichment analysis (GSEA) was performed to identify the biological pathways underlying the CT-based ITH. RESULTS The extreme gradient boosting model based on CT-derived ITH had higher discriminative power, with areas under the receiver operating characteristic curve of 0.864 (95% confidence interval [CI]: 0.774-0.954) and 0.796 (95% CI: 0.698-0.893) in the internal and external validation sets. The CT-based ITH pattern differed significantly between responding and non-responding patients. The GSEA indicated that CT-based ITH was associated with immunity-, keratinization-, and epidermal cell differentiation-related pathways. CONCLUSION CT-based ITH is an effective biomarker for identifying patients with ESCC who could benefit from ICI plus chemotherapy. Immunity-, keratinization-, and epidermal cell differentiation-related pathways may influence the patient's response to ICI plus chemotherapy.
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Affiliation(s)
- Fangzeng Lin
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou 510080, Guangdong Province, People's Republic of China (F.L., M.C.C., Y.Z.)
| | - Lian-Xin Zhu
- Medical College of Nanchang University, Nanchang 330000, Jiangxi Province, People's Republic of China (L.X.Z.); Queen Mary University of London, London, United Kingdom (L.X.Z.)
| | - Zi-Ming Ye
- Department of Thoracic Surgery, Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Guangzhou 510060, Guangdong Province, People's Republic of China (Z.M.Y., Z.H.Z.)
| | - Fang Peng
- Department of Radiation Oncology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou 510080, Guangdong Province, People's Republic of China (F.P.)
| | - Mei-Cheng Chen
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou 510080, Guangdong Province, People's Republic of China (F.L., M.C.C., Y.Z.)
| | - Xiang-Min Li
- Department of Radiology, Hui Ya Hospital of The First Affiliated Hospital, Sun Yat-sen University, Huizhou 516080, Guangdong Province, People's Republic of China (X.M.L.)
| | - Zhi-Hua Zhu
- Department of Thoracic Surgery, Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Guangzhou 510060, Guangdong Province, People's Republic of China (Z.M.Y., Z.H.Z.)
| | - Ying Zhu
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou 510080, Guangdong Province, People's Republic of China (F.L., M.C.C., Y.Z.).
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Yu Z, Zou J, Xu F. The molecular subtypes of small cell lung cancer defined by key transcription factors and their clinical significance. Lung Cancer 2024; 198:108033. [PMID: 39571251 DOI: 10.1016/j.lungcan.2024.108033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2024] [Revised: 10/23/2024] [Accepted: 11/14/2024] [Indexed: 12/07/2024]
Abstract
BACKGROUND Lung cancer, a prevalent and deadly malignancy, is classified into small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC). SCLC is further subdivided into four molecular subtypes-SCLC-A, SCLC-N, SCLC-P, and SCLC-I-based on key transcription factor expression. METHODS Immunohistochemistry (IHC) was used to assess ASCL1, NEUROD1, and POU2F3 expression in tumor tissues. The H-Score quantified these results. Clinical characteristics, overall survival (OS), progression-free survival (PFS), and treatment responses were analyzed by subtype, and sensitivity to different treatments was assessed. Risk factors were identified through univariate and multivariate analyses. RESULTS IHC and H-Score analysis showed that POU2F3 expression was mutually exclusive with ASCL1 or NEUROD1. Subtype distribution was as follows: SCLC-A (40 %), SCLC-N (33 %), SCLC-P (7 %), and SCLC-I (20 %). There were no significant differences in baseline characteristics, OS (p = 0.829), or PFS (p = 0.924) among subtypes. However, the SCLC-I subtype showed a trend toward improved outcomes with platinum-based doublet chemotherapy plus immune checkpoint inhibitors. Multivariate COX regression identified M stage (HR: 1.72, 95 % CI: 1.13-2.63, p = 0.012) and bone metastasis at diagnosis (HR: 1.58, 95 % CI: 1.02-2.43, p = 0.040) as independent risk factors. CONCLUSION This study confirmed the SCLC subtyping based on key transcription factors. While no significant differences in OS and PFS among subtypes were found, the SCLC-I subtype showed potential benefit from platinum-based chemotherapy combined with immune checkpoint inhibitors. M stage and bone metastasis at diagnosis were identified as independent risk factors for SCLC.
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Affiliation(s)
- Zhuchen Yu
- Clinical Medicine, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Jiangxi, China
| | - Juntao Zou
- Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Jiangxi, China.
| | - Fei Xu
- Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Jiangxi, China.
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29
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Xu Y, Li M, Bai L. Pulmonary Epithelium Cell Fate Determination: Chronic Obstructive Pulmonary Disease, Lung Cancer, or Both. Am J Respir Cell Mol Biol 2024; 71:632-645. [PMID: 39078237 DOI: 10.1165/rcmb.2023-0448tr] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Accepted: 07/30/2024] [Indexed: 07/31/2024] Open
Abstract
The concurrence of chronic obstructive pulmonary disease (COPD) and lung cancer has been widely reported and extensively addressed by pulmonologists and oncologists. However, most studies have focused on shared risk factors, DNA damage pathways, immune microenvironments, inflammation, and imbalanced proteases/antiproteases. In the present review, we explore the association between COPD and lung cancer in terms of airway pluripotent cell fate determination and discuss the various cell types and signaling pathways involved in the maintenance of lung epithelium homeostasis and their involvement in the pathogenesis of co-occurring COPD and lung cancer.
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Affiliation(s)
- Yu Xu
- Department of Clinical Oncology, Army Medical Center, and
| | - Mengxia Li
- Department of Clinical Oncology, Army Medical Center, and
| | - Li Bai
- Department of Respiratory and Critical Medicine, The Second Affiliated Hospital, Army Medical University, Chongqing, China
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30
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Vigdorovits A, Olteanu GE, Pascalau AV, Pirlog R, Berindan-Neagoe I, Pop OL. Novel Immunohistochemical Profiling of Small-Cell Lung Cancer: Correlations Between Tumor Subtypes and Immune Microenvironment. Diagnostics (Basel) 2024; 14:2660. [PMID: 39682568 DOI: 10.3390/diagnostics14232660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2024] [Revised: 11/20/2024] [Accepted: 11/21/2024] [Indexed: 12/18/2024] Open
Abstract
BACKGROUND/OBJECTIVES Small-cell lung cancer (SCLC) is a highly aggressive malignancy with an emerging molecular classification based on the expression of the transcription factors ASCL1, NEUROD1, and POU2F3. This study aimed to explore the relationship between these novel subtypes and the tumor immune microenvironment (TIME), particularly CD8+ and CD4+ tumor-infiltrating lymphocytes (TILs). METHODS In 51 cases of patients with SCLC, immunohistochemical (IHC) stains for ASCL1, NEUROD1, POU2F3, CD56, Ki67, CD8, and CD4 were performed. H-scores for the novel transcription factors were calculated to determine tumor subtype. CD8+ and CD4+ TIL counts were averaged across 10 high-power fields. The Kruskal-Wallis test and subsequent post hoc Dunn tests were used to determine the differences in transcription factor expression and TILs across subtypes. RESULTS In our cohort, 68.62% of our cases were SCLC-A, 9.80% were SCLC-N, 7.84% were SCLC-P, and 13.72% were SCLC-I. Significant differences were observed in the expression of ASCL1, NEUROD1, and POU2F3 across subtypes. CD8+ TILs were more abundant in SCLC-P and SCLC-I. CD8+ TILs were negatively correlated with ASCL1 expression (p < 0.05) and positively correlated with POU2F3 expression (p < 0.005). CONCLUSIONS This study highlights the need to integrate the novel SCLC classification with data regarding the TIME to better inform patient prognosis and treatment.
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Affiliation(s)
- Alon Vigdorovits
- Department of Morphological Disciplines, University of Oradea, 410087 Oradea, Romania
| | - Gheorghe-Emilian Olteanu
- British Columbia Cancer, Department of Pathology, Vancouver, BC V5Z 4E6, Canada
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC V6T 1Z7, Canada
| | | | - Radu Pirlog
- Département de Pathologie, Hôpitaux Universitaires Henri Mondor, AP-HP, 94010 Créteil, France
- INSERM U955, Université Paris Est Créteil, 94010 Créteil, France
- Research Center for Functional Genomics, Biomedicine and Translational Medicine, Iuliu Hatieganu University of Medicine and Pharmacy, 400337 Cluj-Napoca, Romania
| | - Ioana Berindan-Neagoe
- Research Center for Functional Genomics, Biomedicine and Translational Medicine, Iuliu Hatieganu University of Medicine and Pharmacy, 400337 Cluj-Napoca, Romania
- Doctoral School, Iuliu Hatieganu University of Medicine and Pharmacy, 400337 Cluj-Napoca, Romania
| | - Ovidiu-Laurean Pop
- Department of Morphological Disciplines, University of Oradea, 410087 Oradea, Romania
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31
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Jiang Y, Xie J, Cheng Q, Cai Z, Xu K, Lu W, Wang F, Wu X, Song Y, Lv T, Zhan P. Comprehensive genomic and spatial immune infiltration analysis of survival outliers in extensive-stage small cell lung cancer receiving first-line chemoimmunotherapy. Int Immunopharmacol 2024; 141:112901. [PMID: 39151386 DOI: 10.1016/j.intimp.2024.112901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2024] [Revised: 07/20/2024] [Accepted: 08/05/2024] [Indexed: 08/19/2024]
Abstract
BACKGROUND A minority of patients with extensive-stage small cell lung cancer (ES-SCLC) exhibit prolonged survival following first-line chemoimmunotherapy, which warrants the use of reliable biomarkers. Here, we investigated the disparities in genomics and immune cell spatial distribution between long- and short-term survival of patients with ES-SCLC. METHODS We retrospectively recruited 11 long-term (>2 years) and 13 short-term (<9 months) ES-SCLC survivors receiving first-line chemoimmunotherapy. The samples were processed using targeted next-generation sequencing (tNGS), programmed death ligand-1 staining, multiplex immunohistochemical staining for immune cells (mIHC), tumor mutation burden (TMB), and chromosomal instability score measurements. The expression of putative genes in SCLC at the bulk and single-cell RNA-sequencing levels, as well as the role of putative genes in pan-cancer immunotherapy cohorts, were analyzed. RESULTS At the genomic level, a greater proportion of the smoking signature and higher TMB (>3.1) were associated with favorable survival. At the single-gene and pathway levels, tNGS revealed that MCL1 and STMN1 amplification and alterations in the apoptosis pathway were more common in short-term survivors, whereas alterations in the DLL3, KMT2B, HGF, EPHA3, ADGRB3, lysine deprivation, and HGF-cMET pathways were observed more frequently in long-term survivors. mIHC analysis of immune cells with different spatial distributions revealed that long-term survivors presented increased numbers of M1-like macrophages in all locations and decreased numbers of CD8+ T cells in the tumor stroma. Bulk transcriptomic analysis demonstrated that high levels of STMN1 and DLL3 represented an immune-suppressive tumor immune microenvironment (TIME), whereas HGF indicated an immune-responsive TIME. The expression levels of our putative genes were comparative in both TP53/RB1 mutant-type and TP53/RB1 wild-type. At the single-cell level, STMN1, MCL1, and DLL3 were highly expressed among all molecular subtypes (SCLC-A, SCLC-N, and SCLC-P), with STMN1 being enriched in cell division and G2M checkpoint pathways. CONCLUSIONS For ES-SCLC patients receiving first-line chemoimmunotherapy, alterations in DLL3, KMT2B, HGF, EPHA3, and ADGRB3 and a greater proportion of M1-like macrophages infiltration in all locations were predictors of favorable survival, while MCL1 and STMN1 amplification, as well as a greater proportion of CD8+ T cells infiltrating the tumor stroma, predicted worse survival.
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Affiliation(s)
- Yuxin Jiang
- School of Medicine, Southeast University, Nanjing 210000, China
| | - Jingyuan Xie
- Department of Respiratory and Critical Care Medicine, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210002, China
| | - Qinpei Cheng
- Department of Respiratory and Critical Care Medicine, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210002, China
| | - Zijing Cai
- Department of Respiratory and Critical Care Medicine, Jinling Hospital, Affiliated Hospital of Nanjing Medical School, Nanjing 210002, China
| | - Ke Xu
- Department of Respiratory and Critical Care Medicine, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210002, China
| | - Wanjun Lu
- Department of Respiratory and Critical Care Medicine, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210002, China
| | - Fufeng Wang
- Nanjing Geneseeq Technology Inc., Nanjing, Jiangsu, China
| | - Xiaoying Wu
- Nanjing Geneseeq Technology Inc., Nanjing, Jiangsu, China
| | - Yong Song
- School of Medicine, Southeast University, Nanjing 210000, China; Department of Respiratory and Critical Care Medicine, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210002, China; Department of Respiratory and Critical Care Medicine, Jinling Hospital, Affiliated Hospital of Nanjing Medical School, Nanjing 210002, China; Department of Respiratory and Critical Care Medicine, Jinling Hospital, School of Medicine, Southeast University, Nanjing 210002, China.
| | - Tangfeng Lv
- School of Medicine, Southeast University, Nanjing 210000, China; Department of Respiratory and Critical Care Medicine, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210002, China; Department of Respiratory and Critical Care Medicine, Jinling Hospital, Affiliated Hospital of Nanjing Medical School, Nanjing 210002, China; Department of Respiratory and Critical Care Medicine, Jinling Hospital, School of Medicine, Southeast University, Nanjing 210002, China.
| | - Ping Zhan
- School of Medicine, Southeast University, Nanjing 210000, China; Department of Respiratory and Critical Care Medicine, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210002, China; Department of Respiratory and Critical Care Medicine, Jinling Hospital, Affiliated Hospital of Nanjing Medical School, Nanjing 210002, China; Department of Respiratory and Critical Care Medicine, Jinling Hospital, School of Medicine, Southeast University, Nanjing 210002, China.
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Oh S, Koh J, Kim TM, Kim S, Youk J, Kim M, Keam B, Jeon YK, Ku JL, Kim DW, Chung DH, Heo DS. Transcriptomic Heterogeneity of EGFR-Mutant Non-Small Cell Lung Cancer Evolution Toward Small-Cell Lung Cancer. Clin Cancer Res 2024; 30:4729-4742. [PMID: 39150541 DOI: 10.1158/1078-0432.ccr-24-0160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Revised: 06/25/2024] [Accepted: 08/14/2024] [Indexed: 08/17/2024]
Abstract
PURPOSE Histologic transformation from EGFR-mutant non-small cell lung cancer (NSCLC) to small-cell lung cancer (SCLC) is a key mechanism of resistance to EGFR tyrosine kinase inhibitors (TKI). However, transcriptomic changes between NSCLC and transformed SCLC (t-SCLC) remain unexplored. EXPERIMENTAL DESIGN We conducted whole-transcriptome analysis of 59 regions of interest through the spatial profiling of formalin-fixed, paraffin-embedded tissues obtained from 10 patients (lung adenocarcinoma, 22; combined SCLC/NSCLC, 7; and t-SCLC, 30 regions of interests). Transcriptomic profiles and differentially expressed genes were compared between pre- and post-transformed tumors. RESULTS Following EGFR-TKI treatment, 93.7% (15/16) of t-SCLC components evolved into neuroendocrine-high subtypes (SCLC-A or SCLC-N). The transition to t-SCLC occurred regardless of EGFR-TKI treatment and EGFR mutational status, with a notable decrease in EGFR expression (P < 0.001) at both mRNA and protein levels. Pathway analysis revealed that gene overexpression was related to epigenetic alterations in t-SCLC. Interestingly, histone deacetylase inhibitors restored EGFR expression in SNU-2962A cells and their organoid model. The synergistic effects of third-generation EGFR-TKI osimertinib and the histone deacetylase inhibitor fimepinostat were validated in both in vitro and in vivo models. CONCLUSIONS Our study demonstrated that most t-SCLC cases showed neuronal subtypes with low EGFR expression. Differentially expressed gene analysis and t-SCLC preclinical models identified an epigenetic modifier as a promising treatment strategy for t-SCLC.
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Affiliation(s)
- Songji Oh
- Cancer Research Institute, Seoul National University, Seoul, South Korea
- Integrated Major in Innovative Medical Science, Seoul National University College of Medicine, Seoul, South Korea
| | - Jaemoon Koh
- Department of Pathology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, South Korea
| | - Tae Min Kim
- Cancer Research Institute, Seoul National University, Seoul, South Korea
- Department of Internal Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, South Korea
| | - Soyeon Kim
- Cancer Research Institute, Seoul National University, Seoul, South Korea
- Integrated Major in Innovative Medical Science, Seoul National University College of Medicine, Seoul, South Korea
| | - Jeonghwan Youk
- Cancer Research Institute, Seoul National University, Seoul, South Korea
- Department of Internal Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, South Korea
| | - Miso Kim
- Cancer Research Institute, Seoul National University, Seoul, South Korea
- Department of Internal Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, South Korea
| | - Bhumsuk Keam
- Cancer Research Institute, Seoul National University, Seoul, South Korea
- Department of Internal Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, South Korea
| | - Yoon Kyung Jeon
- Cancer Research Institute, Seoul National University, Seoul, South Korea
- Integrated Major in Innovative Medical Science, Seoul National University College of Medicine, Seoul, South Korea
- Department of Pathology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, South Korea
| | - Ja-Lok Ku
- Cancer Research Institute, Seoul National University, Seoul, South Korea
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, South Korea
| | - Dong-Wan Kim
- Cancer Research Institute, Seoul National University, Seoul, South Korea
- Integrated Major in Innovative Medical Science, Seoul National University College of Medicine, Seoul, South Korea
- Department of Internal Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, South Korea
| | - Doo Hyun Chung
- Cancer Research Institute, Seoul National University, Seoul, South Korea
- Department of Pathology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, South Korea
| | - Dae Seog Heo
- Cancer Research Institute, Seoul National University, Seoul, South Korea
- Department of Internal Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, South Korea
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Xiao N, Liu H, Zhang C, Chen H, Li Y, Yang Y, Liu H, Wan J. Applications of single-cell analysis in immunotherapy for lung cancer: Current progress, new challenges and expectations. J Adv Res 2024:S2090-1232(24)00462-4. [PMID: 39401694 DOI: 10.1016/j.jare.2024.10.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2024] [Revised: 06/28/2024] [Accepted: 10/11/2024] [Indexed: 10/20/2024] Open
Abstract
BACKGROUND Lung cancer is a prevalent form of cancer worldwide, presenting a substantial risk to human well-being. Lung cancer is classified into two main types: non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC). The advancement of tumor immunotherapy, specifically immune checkpoint inhibitors and adaptive T-cell therapy, has encountered substantial obstacles due to the rapid progression of SCLC and the metastasis, recurrence, and drug resistance of NSCLC. These challenges are believed to stem from the tumor heterogeneity of lung cancer within the tumor microenvironment. AIM OF REVIEW This review aims to comprehensively explore recent strides in single-cell analysis, a robust sequencing technology, concerning its application in the realm of tumor immunotherapy for lung cancer. It has been effectively integrated with transcriptomics, epigenomics, genomics, and proteomics for various applications. Specifically, these techniques have proven valuable in mapping the transcriptional activity of tumor-infiltrating lymphocytes in patients with NSCLC, identifying circulating tumor cells, and elucidating the heterogeneity of the tumor microenvironment. KEY SCIENTIFIC CONCEPTS OF REVIEW The review emphasizes the paramount significance of single-cell analysis in mapping the immune cells within NSCLC patients, unveiling circulating tumor cells, and elucidating the tumor microenvironment heterogeneity. Notably, these advancements highlight the potential of single-cell analysis to revolutionize lung cancer immunotherapy by characterizing immune cell fates, improving therapeutic strategies, and identifying promising targets or prognostic biomarkers. It is potential to unravel the complexities within the tumor microenvironment and enhance treatment strategies marks a significant step towards more effective therapies and improved patient outcomes.
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Affiliation(s)
- Nan Xiao
- Department of Clinical Laboratory, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Hongyang Liu
- Department of Obstetrics and Gynecology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Chenxing Zhang
- Department of Clinical Laboratory, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Huanxiang Chen
- Department of Clinical Laboratory, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Yang Li
- Department of Clinical Laboratory, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Ying Yang
- Department of Clinical Laboratory, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Hongchun Liu
- Department of Clinical Laboratory, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China.
| | - Junhu Wan
- Department of Clinical Laboratory, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China.
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He C. Activating Invasion and Metastasis in Small Cell Lung Cancer: Role of the Tumour Immune Microenvironment and Mechanisms of Vasculogenesis, Epithelial-Mesenchymal Transition, Cell Migration, and Organ Tropism. Cancer Rep (Hoboken) 2024; 7:e70018. [PMID: 39376011 PMCID: PMC11458887 DOI: 10.1002/cnr2.70018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Revised: 08/06/2024] [Accepted: 09/09/2024] [Indexed: 10/09/2024] Open
Abstract
BACKGROUND Small cell lung cancer (SCLC) harbours the most aggressive phenotype of all lung cancers to correlate with its bleak prognosis. The aggression of SCLC is partially attributable to its strong metastatic tendencies. The biological processes facilitating the metastasis in SCLC are still poorly understood and garnering a deeper understanding of these processes may enable the exploration of additional targets against this cancer hallmark in the treatment of SCLC. RECENT FINDINGS This narrative review will discuss the proposed molecular mechanisms by which the cancer hallmark of activating invasion and metastasis is featured in SCLC through important steps of the metastatic pathway, and address the various molecular targets that may be considered for therapeutic intervention. The tumour immune microenvironment plays an important role in facilitating immunotherapy resistance, whilst the poor infiltration of natural killer cells in particular fosters a pro-metastatic environment in SCLC. SCLC vasculogenesis is achieved through VEGF expression and vascular mimicry, and epithelial-mesenchymal transition is facilitated by the expression of the transcriptional repressors of E-cadherin, the suppression of the Notch signalling pathway and tumour heterogeneity. Nuclear factor I/B, selectin and B1 integrin hold important roles in SCLC migration, whilst various molecular markers are expressed by SCLC to assist organ-specific homing during metastasis. The review will also discuss a recent article observing miR-1 mRNA upregulation as a potential therapeutic option in targeting the metastatic activity of SCLC. CONCLUSION Treatment of SCLC remains a clinical challenge due to its recalcitrant and aggressive nature. Amongst the many hallmarks used by SCLC to enable its aggressive behaviour, that of its ability to invade surrounding tissue and metastasise is particularly notable and understanding the molecular mechanisms in SCLC metastasis can identify therapeutic targets to attenuate SCLC aggression and improve mortality.
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Affiliation(s)
- Carl He
- Department of Oncology, Eastern HealthUniversity of MelbourneMelbourneAustralia
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Jin Y, Wu Y, Reuben A, Zhu L, Gay CM, Wu Q, Zhou X, Mo H, Zheng Q, Ren J, Fang Z, Peng T, Wang N, Ma L, Fan Y, Song H, Zhang J, Chen M. Single-cell and spatial proteo-transcriptomic profiling reveals immune infiltration heterogeneity associated with neuroendocrine features in small cell lung cancer. Cell Discov 2024; 10:93. [PMID: 39231924 PMCID: PMC11375181 DOI: 10.1038/s41421-024-00703-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Accepted: 06/23/2024] [Indexed: 09/06/2024] Open
Abstract
Small cell lung cancer (SCLC) is an aggressive pulmonary neuroendocrine malignancy featured by cold tumor immune microenvironment (TIME), limited benefit from immunotherapy, and poor survival. The spatial heterogeneity of TIME significantly associated with anti-tumor immunity has not been systemically studied in SCLC. We performed ultra-high-plex Digital Spatial Profiling on 132 tissue microarray cores from 44 treatment-naive limited-stage SCLC tumors. Incorporating single-cell RNA-sequencing data from a local cohort and published SCLC data, we established a spatial proteo-transcriptomic landscape covering over 18,000 genes and 60 key immuno-oncology proteins that participate in signaling pathways affecting tumorigenesis, immune regulation, and cancer metabolism across 3 pathologically defined spatial compartments (pan-CK-positive tumor nest; CD45/CD3-positive tumor stroma; para-tumor). Our study depicted the spatial transcriptomic and proteomic TIME architecture of SCLC, indicating clear intra-tumor heterogeneity dictated via canonical neuroendocrine subtyping markers; revealed the enrichment of innate immune cells and functionally impaired B cells in tumor nest and suggested potentially important immunoregulatory roles of monocytes/macrophages. We identified RE1 silencing factor (REST) as a potential biomarker for SCLC associated with low neuroendocrine features, more active anti-tumor immunity, and prolonged survival.
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Affiliation(s)
- Ying Jin
- Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, China
- Zhejiang Key Laboratory of Radiation Oncology, Hangzhou, Zhejiang, China
| | - Yuefeng Wu
- The MOE Key Laboratory of Biosystems Homeostasis and Protection, Zhejiang Provincial Key Laboratory for Cancer Molecular Cell Biology and Innovation Center for Cell Signaling Network, Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang, China
- School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China
- Department of Cardiovascular Surgery, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
- Zhejiang University-University of Edinburgh Institute (ZJU-UoE), School of Medicine, Zhejiang University, Haining, Zhejiang, China
| | - Alexandre Reuben
- Department of Thoracic/Head and Neck Medical Oncology, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Liang Zhu
- Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, China
| | - Carl M Gay
- Department of Thoracic/Head and Neck Medical Oncology, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Qingzhe Wu
- The MOE Key Laboratory of Biosystems Homeostasis and Protection, Zhejiang Provincial Key Laboratory for Cancer Molecular Cell Biology and Innovation Center for Cell Signaling Network, Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang, China
| | - Xintong Zhou
- The MOE Key Laboratory of Biosystems Homeostasis and Protection, Zhejiang Provincial Key Laboratory for Cancer Molecular Cell Biology and Innovation Center for Cell Signaling Network, Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang, China
| | - Haomin Mo
- The MOE Key Laboratory of Biosystems Homeostasis and Protection, Zhejiang Provincial Key Laboratory for Cancer Molecular Cell Biology and Innovation Center for Cell Signaling Network, Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang, China
| | - Qi Zheng
- Department of Cardiovascular Surgery, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Junyu Ren
- College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, Zhejiang, China
| | - Zhaoyuan Fang
- Zhejiang University-University of Edinburgh Institute (ZJU-UoE), School of Medicine, Zhejiang University, Haining, Zhejiang, China
| | - Teng Peng
- Department of Cardiovascular Surgery, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Nan Wang
- Cosmos Wisdom Biotech Co. Ltd., Hangzhou, Zhejiang, China
| | - Liang Ma
- Department of Cardiovascular Surgery, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Yun Fan
- Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, China.
| | - Hai Song
- The MOE Key Laboratory of Biosystems Homeostasis and Protection, Zhejiang Provincial Key Laboratory for Cancer Molecular Cell Biology and Innovation Center for Cell Signaling Network, Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang, China.
- Center for Oncology Medicine, The Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, Yiwu, Zhejiang, China.
| | - Jianjun Zhang
- Department of Thoracic/Head and Neck Medical Oncology, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
- Department of Genomic Medicine, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
| | - Ming Chen
- Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, China.
- State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China.
- United Laboratory of Frontier Radiotherapy Technology of Sun Yat-sen University & Chinese Academy of Sciences Ion Medical Technology Co., Ltd, Guangzhou, Guangdong, China.
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Fan G, Xie T, Tang L, Li L, Han X, Shi Y. The co-location of CD14+APOE+ cells and MMP7+ tumour cells contributed to worse immunotherapy response in non-small cell lung cancer. Clin Transl Med 2024; 14:e70009. [PMID: 39187937 PMCID: PMC11347392 DOI: 10.1002/ctm2.70009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Revised: 08/13/2024] [Accepted: 08/15/2024] [Indexed: 08/28/2024] Open
Abstract
Intra-tumour immune infiltration is a crucial determinant affecting immunotherapy response in non-small cell lung cancer (NSCLC). However, its phenotype and related spatial structure have remained elusive. To overcome these restrictions, we undertook a comprehensive study comprising spatial transcriptomic (ST) data (28 712 spots from six samples). We identified two distinct intra-tumour infiltration patterns: immune exclusion (characterised by myeloid cells) and immune activation (characterised by plasma cells). The immune exclusion and immune activation signatures showed adverse and favourable roles in NSCLC patients' survival, respectively. Notably, CD14+APOE+ cells were recognised as the main cell type in immune exclusion samples, with increased epithelial‒mesenchymal transition and decreased immune activities. The co-location of CD14+APOE+ cells and MMP7+ tumour cells was observed in both ST and bulk transcriptomics data, validated by multiplex immunofluorescence performed on 20 NSCLC samples. The co-location area exhibited the upregulation of proliferation-related pathways and hypoxia activities. This co-localisation inhibited T-cell infiltration and the formation of tertiary lymphoid structures. Both CD14+APOE+ cells and MMP7+ tumour cells were associated with worse survival. In an immunotherapy cohort from the ORIENT-3 clinical trial, NSCLC patients who responded unfavourably exhibited higher infiltration of CD14+APOE+ cells and MMP7+ tumour cells. Within the co-location area, the MK, SEMA3 and Macrophage migration inhibitory factor (MIF) signalling pathway was most active in cell‒cell communication. This study identified immune exclusion and activation patterns in NSCLC and the co-location of CD14+APOE+ cells and MMP7+ tumour cells as contributors to immune resistance.
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Affiliation(s)
- Guangyu Fan
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical CollegeBeijing Key Laboratory of Clinical Study on Anticancer Molecular Targeted DrugsBeijingChina
| | - Tongji Xie
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical CollegeBeijing Key Laboratory of Clinical Study on Anticancer Molecular Targeted DrugsBeijingChina
| | - Le Tang
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical CollegeBeijing Key Laboratory of Clinical Study on Anticancer Molecular Targeted DrugsBeijingChina
| | - Lin Li
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences & Peking Union Medical CollegeBeijingChina
| | - Xiaohong Han
- Clinical Pharmacology Research Center, Peking Union Medical College Hospital, State Key Laboratory of Complex Severe and Rare Diseases, NMPA Key Laboratory for Clinical Research and Evaluation of Drug, Beijing Key Laboratory of Clinical PK & PD Investigation for Innovative DrugsChinese Academy of Medical Sciences & Peking Union Medical CollegeBeijingChina
| | - Yuankai Shi
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical CollegeBeijing Key Laboratory of Clinical Study on Anticancer Molecular Targeted DrugsBeijingChina
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37
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Ali A, Manzoor S, Ali T, Asim M, Muhammad G, Ahmad A, Jamaludin MI, Devaraj S, Munawar N. Innovative aspects and applications of single cell technology for different diseases. Am J Cancer Res 2024; 14:4028-4048. [PMID: 39267684 PMCID: PMC11387862 DOI: 10.62347/vufu1836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2024] [Accepted: 08/24/2024] [Indexed: 09/15/2024] Open
Abstract
Recent developments in single-cell technologies have provided valuable insights from cancer genomics to complex microbial communities. Single-cell technologies including the RNA-seq, next-generation sequencing (NGS), epigenomics, genomics, and transcriptomics can be used to uncover the single cell nature and molecular characterization of individual cells. These technologies also reveal the cellular transition states, evolutionary relationships between genes, the complex structure of single-cell populations, cell-to-cell interaction leading to biological discoveries and more reliable than traditional bulk technologies. These technologies are becoming the first choice for the early detection of inflammatory biomarkers affecting the proliferation and progression of tumor cells in the tumor microenvironment and improving the clinical efficacy of patients undergoing immunotherapy. These technologies also hold a central position in the detection of checkpoint inhibitors and thus determining the signaling pathways evoked by tumor invasion. This review addressed the emerging approaches of single cell-based technologies in cancer immunotherapies and different human diseases at cellular and molecular levels and the emerging role of sequencing technologies leading to drug discovery. Advancements in these technologies paved for discovering novel diagnostic markers for better understanding the pathological and biochemical mechanisms also for controlling the rate of different diseases.
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Affiliation(s)
- Ashiq Ali
- Department of Histology and Embryology, Shantou University Medical College Shantou 515041, Guangdong, China
| | - Saba Manzoor
- Department of Zoology, University of Sialkot Sialkot 51310, Pakistan
| | - Tayyab Ali
- Clinico-Molecular Biochemistry Laboratory, Department of Biochemistry, University of Agriculture Faisalabad 38000, Pakistan
| | - Muhammad Asim
- Clinico-Molecular Biochemistry Laboratory, Department of Biochemistry, University of Agriculture Faisalabad 38000, Pakistan
| | - Ghulam Muhammad
- Jinnah Burn and Reconstructive Surgery Centre, Jinnah Hospital, Allama Iqbal Medical College Lahore 54000, Pakistan
| | - Aftab Ahmad
- Biochemistry/Center for Advanced Studies in Agriculture and Food Security (CAS-AFS), University of Agriculture Faisalabad 38040, Pakistan
| | - Mohamad Ikhwan Jamaludin
- BioInspired Device and Tissue Engineering Research Group (BioInspira), Department of Biomedical Engineering and Health Sciences, Faculty of Electrical Engineering, Universiti Teknologi Malaysia Johor Bahru 81310, Johor, Malaysia
| | - Sutha Devaraj
- Graduate School of Medicine, Perdana University Wisma Chase Perdana, Changkat Semantan, Damansara Heights, Kuala Lumpur 50490, Malaysia
| | - Nayla Munawar
- Department of Chemistry, College of Science, United Arab Emirates University Al-Ain 15551, United Arab Emirates
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Li J, Kong Z, Qi Y, Wang W, Su Q, Huang W, Zhang Z, Li S, Du E. Single-cell and bulk RNA-sequence identified fibroblasts signature and CD8 + T-cell - fibroblast subtype predicting prognosis and immune therapeutic response of bladder cancer, based on machine learning: bioinformatics multi-omics study. Int J Surg 2024; 110:4911-4931. [PMID: 38759695 PMCID: PMC11325897 DOI: 10.1097/js9.0000000000001516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Accepted: 04/14/2024] [Indexed: 05/19/2024]
Abstract
BACKGROUND Cancer-associated fibroblasts (CAFs) are found in primary and advanced tumours. They are primarily involved in tumour progression through complex mechanisms with other types of cells in the tumour microenvironment. However, essential fibroblasts-related genes (FRG) in bladder cancer still need to be explored, and there is a shortage of an ideal predictive model or molecular subtype for the progression and immune therapeutic assessment for bladder cancer, especially muscular-invasive bladder cancer based on the FRG. MATERIALS AND METHODS CAF-related genes of bladder cancer were identified by analysing single-cell RNA sequence datasets, and bulk transcriptome datasets and gene signatures were used to characterize them. Then, 10 types of machine learning algorithms were utilised to determine the hallmark FRG and construct the FRG index (FRGI) and subtypes. Further molecular subtypes combined with CD8+ T-cells were established to predict the prognosis and immune therapy response. RESULTS Fifty-four BLCA-related FRG were screened by large-scale scRNA-sequence datasets. The machine learning algorithm established a 3-genes FRGI. High FRGI represented a worse outcome. Then, FRGI combined clinical variables to construct a nomogram, which shows high predictive performance for the prognosis of bladder cancer. Furthermore, the BLCA datasets were separated into two subtypes - fibroblast hot and cold types. In five independent BLCA cohorts, the fibroblast hot type showed worse outcomes than the cold type. Multiple cancer-related hallmark pathways are distinctively enriched in these two types. In addition, high FRGI or fibroblast hot type shows a worse immune therapeutic response. Then, four subtypes called CD8-FRG subtypes were established under the combination of FRG signature and activity of CD8+ T-cells, which turned out to be effective in predicting the prognosis and immune therapeutic response of bladder cancer in multiple independent datasets. Pathway enrichment analysis, multiple gene signatures, and epigenetic alteration characterize the CD8-FRG subtypes and provide a potential combination strategy method against bladder cancer. CONCLUSIONS In summary, the authors established a novel FRGI and CD8-FRG subtype by large-scale datasets and organised analyses, which could accurately predict clinical outcomes and immune therapeutic response of BLCA after surgery.
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Affiliation(s)
- Jingxian Li
- Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University
| | - Zheng Kong
- Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University
| | - Yuanjiong Qi
- Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University
| | - Wei Wang
- Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University
| | - Qiang Su
- Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University
| | - Wei Huang
- Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University
| | - Zhihong Zhang
- Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University
| | - Shuai Li
- Department of Colorectal Surgery, The Second Hospital of Tianjin Medical University, Tianjin, People's Republic of China
| | - E Du
- Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University
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Zhang Z, Sun X, Liu Y, Zhang Y, Yang Z, Dong J, Wang N, Ying J, Zhou M, Yang L. Spatial Transcriptome-Wide Profiling of Small Cell Lung Cancer Reveals Intra-Tumoral Molecular and Subtype Heterogeneity. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2402716. [PMID: 38896789 PMCID: PMC11336901 DOI: 10.1002/advs.202402716] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Revised: 05/21/2024] [Indexed: 06/21/2024]
Abstract
Small cell lung cancer (SCLC) is a highly aggressive malignancy characterized by rapid growth and early metastasis and is susceptible to treatment resistance and recurrence. Understanding the intra-tumoral spatial heterogeneity in SCLC is crucial for improving patient outcomes and clinically relevant subtyping. In this study, a spatial whole transcriptome-wide analysis of 25 SCLC patients at sub-histological resolution using GeoMx Digital Spatial Profiling technology is performed. This analysis deciphered intra-tumoral multi-regional heterogeneity, characterized by distinct molecular profiles, biological functions, immune features, and molecular subtypes within spatially localized histological regions. Connections between different transcript-defined intra-tumoral phenotypes and their impact on patient survival and therapeutic response are also established. Finally, a gene signature, termed ITHtyper, based on the prevalence of intra-tumoral heterogeneity levels, which enables patient risk stratification from bulk RNA-seq profiles is identified. The prognostic value of ITHtyper is rigorously validated in independent multicenter patient cohorts. This study introduces a preliminary tumor-centric, regionally targeted spatial transcriptome resource that sheds light on previously unexplored intra-tumoral spatial heterogeneity in SCLC. These findings hold promise to improve tumor reclassification and facilitate the development of personalized treatments for SCLC patients.
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Affiliation(s)
- Zicheng Zhang
- School of Biomedical EngineeringNational Clinical Research Center for Ocular DiseasesEye HospitalWenzhou Medical UniversityWenzhou325027P. R. China
- Department of PathologyNational Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijing100021P. R. China
| | - Xujie Sun
- Department of PathologyNational Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijing100021P. R. China
| | - Yutao Liu
- Department of Medical OncologyNational Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijing100021P. R. China
| | - Yibo Zhang
- School of Biomedical EngineeringNational Clinical Research Center for Ocular DiseasesEye HospitalWenzhou Medical UniversityWenzhou325027P. R. China
| | - Zijian Yang
- School of Biomedical EngineeringNational Clinical Research Center for Ocular DiseasesEye HospitalWenzhou Medical UniversityWenzhou325027P. R. China
| | - Jiyan Dong
- Department of PathologyNational Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijing100021P. R. China
| | - Nan Wang
- Cosmos Wisdom Biotech Co. LtdBuilding 10thNo. 617 Jiner RoadHangzhou311215P. R. China
| | - Jianming Ying
- Department of PathologyNational Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijing100021P. R. China
| | - Meng Zhou
- School of Biomedical EngineeringNational Clinical Research Center for Ocular DiseasesEye HospitalWenzhou Medical UniversityWenzhou325027P. R. China
| | - Lin Yang
- Department of PathologyNational Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijing100021P. R. China
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Sen T, Takahashi N, Chakraborty S, Takebe N, Nassar AH, Karim NA, Puri S, Naqash AR. Emerging advances in defining the molecular and therapeutic landscape of small-cell lung cancer. Nat Rev Clin Oncol 2024; 21:610-627. [PMID: 38965396 PMCID: PMC11875021 DOI: 10.1038/s41571-024-00914-x] [Citation(s) in RCA: 25] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/06/2024] [Indexed: 07/06/2024]
Abstract
Small-cell lung cancer (SCLC) has traditionally been considered a recalcitrant cancer with a dismal prognosis, with only modest advances in therapeutic strategies over the past several decades. Comprehensive genomic assessments of SCLC have revealed that most of these tumours harbour deletions of the tumour-suppressor genes TP53 and RB1 but, in contrast to non-small-cell lung cancer, have failed to identify targetable alterations. The expression status of four transcription factors with key roles in SCLC pathogenesis defines distinct molecular subtypes of the disease, potentially enabling specific therapeutic approaches. Overexpression and amplification of MYC paralogues also affect the biology and therapeutic vulnerabilities of SCLC. Several other attractive targets have emerged in the past few years, including inhibitors of DNA-damage-response pathways, epigenetic modifiers, antibody-drug conjugates and chimeric antigen receptor T cells. However, the rapid development of therapeutic resistance and lack of biomarkers for effective selection of patients with SCLC are ongoing challenges. Emerging single-cell RNA sequencing data are providing insights into the plasticity and intratumoural and intertumoural heterogeneity of SCLC that might be associated with therapeutic resistance. In this Review, we provide a comprehensive overview of the latest advances in genomic and transcriptomic characterization of SCLC with a particular focus on opportunities for translation into new therapeutic approaches to improve patient outcomes.
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Affiliation(s)
- Triparna Sen
- Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Nobuyuki Takahashi
- Department of Medical Oncology, National Cancer Center Hospital East, Kashiwa, Japan
| | - Subhamoy Chakraborty
- Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Naoko Takebe
- Developmental Therapeutics Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD, USA
| | - Amin H Nassar
- Division of Oncology, Yale University School of Medicine, New Haven, CT, USA
| | - Nagla A Karim
- Inova Schar Cancer Institute Virginia, Fairfax, VA, USA
| | - Sonam Puri
- Division of Medical Oncology, Huntsman Cancer Institute, Salt Lake City, UT, USA
| | - Abdul Rafeh Naqash
- Medical Oncology/ TSET Phase 1 program, University of Oklahoma, Oklahoma City, OK, USA.
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Shukla V, Wang H, Varticovski L, Baek S, Wang R, Wu X, Echtenkamp F, Villa-Hernandez F, Prothro KP, Gara SK, Zhang MR, Shiffka S, Raziuddin R, Neckers LM, Linehan WM, Chen H, Hager GL, Schrump DS. Genome-Wide Analysis Identifies Nuclear Factor 1C as a Novel Transcription Factor and Potential Therapeutic Target in SCLC. J Thorac Oncol 2024; 19:1201-1217. [PMID: 38583771 DOI: 10.1016/j.jtho.2024.03.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 03/14/2024] [Accepted: 03/30/2024] [Indexed: 04/09/2024]
Abstract
INTRODUCTION Recent insights regarding mechanisms mediating stemness, heterogeneity, and metastatic potential of lung cancers have yet to be fully translated to effective regimens for the treatment of these malignancies. This study sought to identify novel targets for lung cancer therapy. METHODS Transcriptomes and DNA methylomes of 14 SCLC and 10 NSCLC lines were compared with normal human small airway epithelial cells (SAECs) and induced pluripotent stem cell (iPSC) clones derived from SAEC. SCLC lines, lung iPSC (Lu-iPSC), and SAEC were further evaluated by DNase I hypersensitive site sequencing (DHS-seq). Changes in chromatin accessibility and depths of transcription factor (TF) footprints were quantified using Bivariate analysis of Genomic Footprint. Standard techniques were used to evaluate growth, tumorigenicity, and changes in transcriptomes and glucose metabolism of SCLC cells after NFIC knockdown and to evaluate NFIC expression in SCLC cells after exposure to BET inhibitors. RESULTS Considerable commonality of transcriptomes and DNA methylomes was observed between Lu-iPSC and SCLC; however, this analysis was uninformative regarding pathways unique to lung cancer. Linking results of DHS-seq to RNA sequencing enabled identification of networks not previously associated with SCLC. When combined with footprint depth, NFIC, a transcription factor not previously associated with SCLC, had the highest score of occupancy at open chromatin sites. Knockdown of NFIC impaired glucose metabolism, decreased stemness, and inhibited growth of SCLC cells in vitro and in vivo. ChIP-seq analysis identified numerous sites occupied by BRD4 in the NFIC promoter region. Knockdown of BRD4 or treatment with Bromodomain and extra-terminal domain (BET) inhibitors (BETis) markedly reduced NFIC expression in SCLC cells and SCLC PDX models. Approximately 8% of genes down-regulated by BETi treatment were repressed by NFIC knockdown in SCLC, whereas 34% of genes repressed after NFIC knockdown were also down-regulated in SCLC cells after BETi treatment. CONCLUSIONS NFIC is a key TF and possible mediator of transcriptional regulation by BET family proteins in SCLC. Our findings highlight the potential of genome-wide chromatin accessibility analysis for elucidating mechanisms of pulmonary carcinogenesis and identifying novel targets for lung cancer therapy.
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Affiliation(s)
- Vivek Shukla
- Thoracic Epigenetics Section, Thoracic Surgery Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland; Present Address: Division of Nonclinical Sciences (DNCS), FDA, Silver Spring, Maryland
| | - Haitao Wang
- Thoracic Epigenetics Section, Thoracic Surgery Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Lyuba Varticovski
- Laboratory of Receptor Biology and Gene Expression, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Songjoon Baek
- Laboratory of Receptor Biology and Gene Expression, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Ruihong Wang
- Thoracic Epigenetics Section, Thoracic Surgery Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Xinwei Wu
- Thoracic Epigenetics Section, Thoracic Surgery Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Frank Echtenkamp
- Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Frank Villa-Hernandez
- Thoracic Epigenetics Section, Thoracic Surgery Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Katherine P Prothro
- Thoracic Epigenetics Section, Thoracic Surgery Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Sudheer K Gara
- Thoracic Epigenetics Section, Thoracic Surgery Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Mary R Zhang
- Thoracic Epigenetics Section, Thoracic Surgery Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Stephanie Shiffka
- Thoracic Epigenetics Section, Thoracic Surgery Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Razi Raziuddin
- Laboratory of Receptor Biology and Gene Expression, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Leonard M Neckers
- Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - W Marston Linehan
- Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Haobin Chen
- Thoracic Epigenetics Section, Thoracic Surgery Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland; Present Address: Department of Medicine, Division of Oncology, Washington University School of Medicine, St. Louis, Missouri
| | - Gordon L Hager
- Laboratory of Receptor Biology and Gene Expression, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - David S Schrump
- Thoracic Epigenetics Section, Thoracic Surgery Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
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Chen Y, Han K, Liu Y, Wang Q, Wu Y, Chen S, Yu J, Luo Y, Tan L. Identification of effective diagnostic genes and immune cell infiltration characteristics in small cell lung cancer by integrating bioinformatics analysis and machine learning algorithms. Saudi Med J 2024; 45:771-782. [PMID: 39074893 PMCID: PMC11288485 DOI: 10.15537/smj.2024.45.8.20240170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Accepted: 07/04/2024] [Indexed: 07/31/2024] Open
Abstract
OBJECTIVES To identify potential diagnostic markers for small cell lung cancer (SCLC) and investigate the correlation with immune cell infiltration. METHODS GSE149507 and GSE6044 were used as the training group, while GSE108055 served as validation group A and GSE73160 served as validation group B. Differentially expressed genes (DEGs) were identified and analyzed for functional enrichment. Machine learning (ML) was used to identify candidate diagnostic genes for SCLC. The area under the receiver operating characteristic curves was applied to assess diagnostic efficacy. Immune cell infiltration analyses were carried out. RESULTS There were 181 DEGs identified. The gene ontology analysis showed that DEGs were enriched in 455 functional annotations, some of which were associated with immunity. The kyoto encyclopedia of genes and genomes analysis revealed that there were 9 signaling pathways enriched. The disease ontology analysis indicated that DEGs were related to 116 diseases. The gene set enrichment analysis results displayed multiple items closely related to immunity. ZWINT and NRCAM were screened using ML and further validated as diagnostic genes. Significant differences were observed in SCLC with normal lung tissue samples among immune cell infiltration characteristics. Strong associations were found between the diagnostic genes and immune cell infiltration. CONCLUSION This study identified 2 diagnostic genes, ZWINT and NRCAM, that were related to immune cell infiltration by integrating bioinformatics analysis and ML algorithms. These genes could serve as potential diagnostic biomarkers and provide possible molecular targets for immunotherapy in SCLC.
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Affiliation(s)
- Yinyi Chen
- From the Department of Clinical Laboratory (Chen, Han, Liu, Wang, Wu, Yu, Tan); from the Department of Blood Transfusion (Chen), The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, and from the Department of Clinical Laboratory (Luo), The Second Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine, Jiangxi, China.
| | - Kexin Han
- From the Department of Clinical Laboratory (Chen, Han, Liu, Wang, Wu, Yu, Tan); from the Department of Blood Transfusion (Chen), The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, and from the Department of Clinical Laboratory (Luo), The Second Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine, Jiangxi, China.
| | - Yanzhao Liu
- From the Department of Clinical Laboratory (Chen, Han, Liu, Wang, Wu, Yu, Tan); from the Department of Blood Transfusion (Chen), The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, and from the Department of Clinical Laboratory (Luo), The Second Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine, Jiangxi, China.
| | - Qunxia Wang
- From the Department of Clinical Laboratory (Chen, Han, Liu, Wang, Wu, Yu, Tan); from the Department of Blood Transfusion (Chen), The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, and from the Department of Clinical Laboratory (Luo), The Second Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine, Jiangxi, China.
| | - Yang Wu
- From the Department of Clinical Laboratory (Chen, Han, Liu, Wang, Wu, Yu, Tan); from the Department of Blood Transfusion (Chen), The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, and from the Department of Clinical Laboratory (Luo), The Second Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine, Jiangxi, China.
| | - Simei Chen
- From the Department of Clinical Laboratory (Chen, Han, Liu, Wang, Wu, Yu, Tan); from the Department of Blood Transfusion (Chen), The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, and from the Department of Clinical Laboratory (Luo), The Second Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine, Jiangxi, China.
| | - Jianlin Yu
- From the Department of Clinical Laboratory (Chen, Han, Liu, Wang, Wu, Yu, Tan); from the Department of Blood Transfusion (Chen), The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, and from the Department of Clinical Laboratory (Luo), The Second Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine, Jiangxi, China.
| | - Yi Luo
- From the Department of Clinical Laboratory (Chen, Han, Liu, Wang, Wu, Yu, Tan); from the Department of Blood Transfusion (Chen), The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, and from the Department of Clinical Laboratory (Luo), The Second Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine, Jiangxi, China.
| | - Liming Tan
- From the Department of Clinical Laboratory (Chen, Han, Liu, Wang, Wu, Yu, Tan); from the Department of Blood Transfusion (Chen), The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, and from the Department of Clinical Laboratory (Luo), The Second Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine, Jiangxi, China.
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Kabeer F, Tran H, Andronescu M, Singh G, Lee H, Salehi S, Wang B, Biele J, Brimhall J, Gee D, Cerda V, O'Flanagan C, Algara T, Kono T, Beatty S, Zaikova E, Lai D, Lee E, Moore R, Mungall AJ, Williams MJ, Roth A, Campbell KR, Shah SP, Aparicio S. Single-cell decoding of drug induced transcriptomic reprogramming in triple negative breast cancers. Genome Biol 2024; 25:191. [PMID: 39026273 PMCID: PMC11256464 DOI: 10.1186/s13059-024-03318-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Accepted: 06/20/2024] [Indexed: 07/20/2024] Open
Abstract
BACKGROUND The encoding of cell intrinsic drug resistance states in breast cancer reflects the contributions of genomic and non-genomic variations and requires accurate estimation of clonal fitness from co-measurement of transcriptomic and genomic data. Somatic copy number (CN) variation is the dominant mutational mechanism leading to transcriptional variation and notably contributes to platinum chemotherapy resistance cell states. Here, we deploy time series measurements of triple negative breast cancer (TNBC) single-cell transcriptomes, along with co-measured single-cell CN fitness, identifying genomic and transcriptomic mechanisms in drug-associated transcriptional cell states. RESULTS We present scRNA-seq data (53,641 filtered cells) from serial passaging TNBC patient-derived xenograft (PDX) experiments spanning 2.5 years, matched with genomic single-cell CN data from the same samples. Our findings reveal distinct clonal responses within TNBC tumors exposed to platinum. Clones with high drug fitness undergo clonal sweeps and show subtle transcriptional reversion, while those with weak fitness exhibit dynamic transcription upon drug withdrawal. Pathway analysis highlights convergence on epithelial-mesenchymal transition and cytokine signaling, associated with resistance. Furthermore, pseudotime analysis demonstrates hysteresis in transcriptional reversion, indicating generation of new intermediate transcriptional states upon platinum exposure. CONCLUSIONS Within a polyclonal tumor, clones with strong genotype-associated fitness under platinum remained fixed, minimizing transcriptional reversion upon drug withdrawal. Conversely, clones with weaker fitness display non-genomic transcriptional plasticity. This suggests CN-associated and CN-independent transcriptional states could both contribute to platinum resistance. The dominance of genomic or non-genomic mechanisms within polyclonal tumors has implications for drug sensitivity, restoration, and re-treatment strategies.
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Affiliation(s)
- Farhia Kabeer
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
- Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, BC, Canada
| | - Hoa Tran
- Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, BC, Canada
| | - Mirela Andronescu
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
- Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, BC, Canada
| | - Gurdeep Singh
- Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, BC, Canada
| | - Hakwoo Lee
- Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, BC, Canada
| | - Sohrab Salehi
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Irving Institute for Cancer Dynamics, Columbia University, New York, NY, USA
| | - Beixi Wang
- Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, BC, Canada
| | - Justina Biele
- Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, BC, Canada
| | - Jazmine Brimhall
- Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, BC, Canada
| | - David Gee
- Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, BC, Canada
| | - Viviana Cerda
- Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, BC, Canada
| | - Ciara O'Flanagan
- Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, BC, Canada
| | - Teresa Algara
- Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, BC, Canada
| | - Takako Kono
- Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, BC, Canada
| | - Sean Beatty
- Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, BC, Canada
| | - Elena Zaikova
- Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, BC, Canada
| | - Daniel Lai
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
- Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, BC, Canada
| | - Eric Lee
- Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, BC, Canada
| | - Richard Moore
- Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, BC, Canada
| | - Andrew J Mungall
- Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, BC, Canada
| | - Marc J Williams
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Andrew Roth
- Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, BC, Canada
| | - Kieran R Campbell
- Lunenfeld-Tanenbaum Research Institute, University of Toronto, Toronto, ON, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Sohrab P Shah
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Irving Institute for Cancer Dynamics, Columbia University, New York, NY, USA
| | - Samuel Aparicio
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada.
- Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, BC, Canada.
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Nussinov R, Yavuz BR, Demirel HC, Arici MK, Jang H, Tuncbag N. Review: Cancer and neurodevelopmental disorders: multi-scale reasoning and computational guide. Front Cell Dev Biol 2024; 12:1376639. [PMID: 39015651 PMCID: PMC11249571 DOI: 10.3389/fcell.2024.1376639] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Accepted: 06/10/2024] [Indexed: 07/18/2024] Open
Abstract
The connection and causality between cancer and neurodevelopmental disorders have been puzzling. How can the same cellular pathways, proteins, and mutations lead to pathologies with vastly different clinical presentations? And why do individuals with neurodevelopmental disorders, such as autism and schizophrenia, face higher chances of cancer emerging throughout their lifetime? Our broad review emphasizes the multi-scale aspect of this type of reasoning. As these examples demonstrate, rather than focusing on a specific organ system or disease, we aim at the new understanding that can be gained. Within this framework, our review calls attention to computational strategies which can be powerful in discovering connections, causalities, predicting clinical outcomes, and are vital for drug discovery. Thus, rather than centering on the clinical features, we draw on the rapidly increasing data on the molecular level, including mutations, isoforms, three-dimensional structures, and expression levels of the respective disease-associated genes. Their integrated analysis, together with chromatin states, can delineate how, despite being connected, neurodevelopmental disorders and cancer differ, and how the same mutations can lead to different clinical symptoms. Here, we seek to uncover the emerging connection between cancer, including pediatric tumors, and neurodevelopmental disorders, and the tantalizing questions that this connection raises.
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Affiliation(s)
- Ruth Nussinov
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Cancer Innovation Laboratory, National Cancer Institute, Frederick, MD, United States
- Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv-Yafo, Israel
| | - Bengi Ruken Yavuz
- Cancer Innovation Laboratory, National Cancer Institute, Frederick, MD, United States
| | | | - M. Kaan Arici
- Graduate School of Informatics, Middle East Technical University, Ankara, Türkiye
| | - Hyunbum Jang
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Cancer Innovation Laboratory, National Cancer Institute, Frederick, MD, United States
| | - Nurcan Tuncbag
- Department of Chemical and Biological Engineering, Koc University, Istanbul, Türkiye
- School of Medicine, Koc University, Istanbul, Türkiye
- Koc University Research Center for Translational Medicine (KUTTAM), Istanbul, Türkiye
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Go S, Yang JW, Lee WJ, Jeong EJ, Park S, Lee G. Lipocalin-2 as a prognostic biomarker and its association with systemic inflammation in small cell lung cancer. Thorac Cancer 2024; 15:1646-1655. [PMID: 38886905 PMCID: PMC11260553 DOI: 10.1111/1759-7714.15389] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2024] [Revised: 05/15/2024] [Accepted: 05/20/2024] [Indexed: 06/20/2024] Open
Abstract
BACKGROUND Systemic inflammation is believed to contribute to small cell lung cancer (SCLC) progression, but the underlying relationship remains unclear. Lipocalin-2, a potential biomarker of inflammation, has been implicated in various cancers but its prognostic value in SCLC is underexplored. METHODS We retrospectively analyzed 191 patients with SCLC (72 with limited-stage [LD] and 119 with extensive-stage) treated using platinum-based chemotherapy. Lipocalin-2 expression was evaluated using immunohistochemistry. Optimal cutoff values for lipocalin-2 and neutrophil-to-lymphocyte ratio (NLR) were determined using time-dependent receiver operating characteristic curve analysis. The pectoralis muscle index was used to assess sarcopenia. RESULTS In LD-SCLC, high lipocalin-2 expression was associated with worse progression-free survival (PFS; median: 7.0 vs. 15.9 months, p = 0.015) and overall survival (OS; median: 12.9 vs. 30.3 months, p = 0.035) compared with low lipocalin-2 expression. Patients were stratified into three prognostic groups by combining lipocalin-2 with NLR: low lipocalin-2/low NLR, high lipocalin-2/low NLR or low lipocalin-2/high NLR, and high lipocalin-2/high NLR (median PFS: 17.3 vs. 11.0 vs. 6.3 months, p = 0.004; median OS: 30.5 vs. 17.3 vs. 8.6 months, p = 0.002). Similar trends were observed when combining lipocalin-2 with the pectoralis muscle index. High lipocalin-2 expression was also associated with lower complete response rates (18.9% vs. 34.3%, p = 0.035). No significant prognostic implications were found for lipocalin-2 in extensive-stage SCLC. CONCLUSIONS High lipocalin-2 expression is potentially associated with poorer survival in LD-SCLC. Combining lipocalin-2 with other inflammation-related markers could improve prognostic stratification.
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Affiliation(s)
- Se‐Il Go
- Department of Internal MedicineGyeongsang National University Changwon HospitalChangwonKorea
- Department of Internal MedicineGyeongsang National University College of MedicineJinjuKorea
- Institute of Medical Science, Gyeongsang National UniversityJinjuKorea
| | - Jung Wook Yang
- Institute of Medical Science, Gyeongsang National UniversityJinjuKorea
- Department of PathologyGyeongsang National University HospitalJinjuKorea
- Department of PathologyGyeongsang National University College of MedicineJinjuKorea
| | - Woo Je Lee
- Division of Hematology and Oncology, Department of Internal MedicineGyeongsang National University HospitalJinjuKorea
| | - Eun Jeong Jeong
- Division of Hematology and Oncology, Department of Internal MedicineGyeongsang National University HospitalJinjuKorea
| | - Sungwoo Park
- Department of Internal MedicineGyeongsang National University College of MedicineJinjuKorea
- Institute of Medical Science, Gyeongsang National UniversityJinjuKorea
- Division of Hematology and Oncology, Department of Internal MedicineGyeongsang National University HospitalJinjuKorea
| | - Gyeong‐Won Lee
- Department of Internal MedicineGyeongsang National University College of MedicineJinjuKorea
- Institute of Medical Science, Gyeongsang National UniversityJinjuKorea
- Division of Hematology and Oncology, Department of Internal MedicineGyeongsang National University HospitalJinjuKorea
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WANG Y, LUO B, WANG Z, QUE Z, JIANG L, TIAN J. [Advancements in Single-cell RNA Sequencing Technology
in the Study of the Tumor Microenvironment in Lung Cancer]. ZHONGGUO FEI AI ZA ZHI = CHINESE JOURNAL OF LUNG CANCER 2024; 27:441-450. [PMID: 39026495 PMCID: PMC11258646 DOI: 10.3779/j.issn.1009-3419.2024.101.15] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 03/26/2024] [Indexed: 07/20/2024]
Abstract
The immune microenvironment plays a key role in the development and progression of tumors. In recent years, with the rapid advancement of high-throughput sequencing technologies, researchers have gained a deeper understanding of the composition and function of immune cells in the tumor microenvironment. However, traditional bulk sequencing technologies are limited in resolving heterogeneity at the single-cell level, constraining a comprehensive understanding of the complexity of the tumor microenvironment. The advent of single-cell RNA sequencing technology has brought new opportunities to uncover the heterogeneity of the immune microenvironment in lung cancer. Currently, T-cell-centered immunotherapy in clinical settings is prone to side effects affecting prognosis, such as immunogenic drug resistance or immune-related pneumonia, with the key factor being changes in the interactions between immune cells and tumor cells in the tumor microenvironment. Single-cell RNA sequencing technology can reveal the origins and functions of different subgroups within the tumor microenvironment from perspectives such as intercellular interactions and pseudotime analysis, thereby discovering new cell subgroups or novel biomarkers, providing new avenues for uncovering resistance to immunotherapy and monitoring therapeutic efficacy. This review comprehensively discusses the newest research techniques and advancements in single-cell RNA sequencing technology for unveiling the heterogeneity of the tumor microenvironment after lung cancer immunotherapy, offering insights for enhancing the precision and personalization of immunotherapy.
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Ng J, Cai L, Girard L, Prall OW, Rajan N, Khoo C, Batrouney A, Byrne DJ, Boyd DK, Kersbergen AJ, Christie M, Minna JD, Burr ML, Sutherland KD. Molecular and Pathologic Characterization of YAP1-Expressing Small Cell Lung Cancer Cell Lines Leads to Reclassification as SMARCA4-Deficient Malignancies. Clin Cancer Res 2024; 30:1846-1858. [PMID: 38180245 PMCID: PMC11061608 DOI: 10.1158/1078-0432.ccr-23-2360] [Citation(s) in RCA: 23] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 10/08/2023] [Accepted: 12/01/2023] [Indexed: 01/06/2024]
Abstract
PURPOSE The classification of small cell lung cancer (SCLC) into distinct molecular subtypes defined by ASCL1, NEUROD1, POU2F3, or YAP1 (SCLC-A, -N, -P, or -Y) expression, paves the way for a personalized treatment approach. However, the existence of a distinct YAP1-expressing SCLC subtype remains controversial. EXPERIMENTAL DESIGN To better understand YAP1-expressing SCLC, the mutational landscape of human SCLC cell lines was interrogated to identify pathogenic alterations unique to SCLC-Y. Xenograft tumors, generated from cell lines representing the four SCLC molecular subtypes, were evaluated by a panel of pathologists who routinely diagnose thoracic malignancies. Diagnoses were complemented by transcriptomic analysis of primary tumors and human cell line datasets. Protein expression profiles were validated in patient tumor tissue. RESULTS Unexpectedly, pathogenic mutations in SMARCA4 were identified in six of eight SCLC-Y cell lines and correlated with reduced SMARCA4 mRNA and protein expression. Pathologist evaluations revealed that SMARCA4-deficient SCLC-Y tumors exhibited features consistent with thoracic SMARCA4-deficient undifferentiated tumors (SMARCA4-UT). Similarly, the transcriptional profile SMARCA4-mutant SCLC-Y lines more closely resembled primary SMARCA4-UT, or SMARCA4-deficient non-small cell carcinoma, than SCLC. Furthermore, SMARCA4-UT patient samples were associated with a YAP1 transcriptional signature and exhibited strong YAP1 protein expression. Together, we found little evidence to support a diagnosis of SCLC for any of the YAP1-expressing cell lines originally used to define the SCLC-Y subtype. CONCLUSIONS SMARCA4-mutant SCLC-Y cell lines exhibit characteristics consistent with SMARCA4-deficient malignancies rather than SCLC. Our findings suggest that, unlike ASCL1, NEUROD1, and POU2F3, YAP1 is not a subtype defining transcription factor in SCLC. See related commentary by Rekhtman, p. 1708.
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Affiliation(s)
- Jin Ng
- ACRF Cancer Biology and Stem Cells Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, Victoria, Australia
| | - Ling Cai
- Quantitative Biomedical Research Center, Peter O'Donnell Jr. School of Public Health, UT Southwestern Medical Center, Dallas, Texas
- Children's Research Institute, UT Southwestern Medical Center, Dallas, Texas
- Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, Texas
| | - Luc Girard
- Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, Texas
- Hamon Center for Therapeutic Oncology Research, UT Southwestern Medical Center, Dallas, Texas
| | - Owen W.J. Prall
- Department of Anatomical Pathology, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Neeha Rajan
- Department of Anatomical Pathology, The Royal Melbourne Hospital, Parkville, Victoria, Australia
| | - Christine Khoo
- Department of Anatomical Pathology, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Ahida Batrouney
- Department of Anatomical Pathology, The Royal Melbourne Hospital, Parkville, Victoria, Australia
| | - David J. Byrne
- Department of Anatomical Pathology, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Danielle K. Boyd
- ACRF Cancer Biology and Stem Cells Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia
| | - Ariena J. Kersbergen
- ACRF Cancer Biology and Stem Cells Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia
| | - Michael Christie
- Department of Anatomical Pathology, The Royal Melbourne Hospital, Parkville, Victoria, Australia
- Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia
| | - John D. Minna
- Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, Texas
- Hamon Center for Therapeutic Oncology Research, UT Southwestern Medical Center, Dallas, Texas
- Department of Internal Medicine, UT Southwestern Medical Center, Dallas, Texas
- Department of Pharmacology, UT Southwestern Medical Center, Dallas, Texas
| | - Marian L. Burr
- Division of Genome Science and Cancer, The John Curtin School of Medical Research, The Australian National University, Canberra, Australian Capital Territory, Australia
- Department of Anatomical Pathology, ACT Pathology, Canberra Health Services, Canberra, Australian Capital Territory, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Victoria, Australia
| | - Kate D. Sutherland
- ACRF Cancer Biology and Stem Cells Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, Victoria, Australia
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Wu Y, Li Y, Yan N, Huang J, Li X, Zhang K, Lu Z, Qiu Z, Cheng H. Nuclear-targeted chimeric peptide nanorods to amplify innate anti-tumor immunity through localized DNA damage and STING activation. J Control Release 2024; 369:531-544. [PMID: 38580138 DOI: 10.1016/j.jconrel.2024.04.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2023] [Revised: 03/31/2024] [Accepted: 04/02/2024] [Indexed: 04/07/2024]
Abstract
Stimulator of the interferon genes (STING) pathway is appealing but challenging to potentiate the innate anti-tumor immunity. In this work, nuclear-targeted chimeric peptide nanorods (designated as PFPD) are constructed to amplify innate immunity through localized DNA damage and STING activation. Among which, the chimeric peptide (PpIX-FFVLKPKKKRKV) is fabricated with photosensitizer and nucleus targeting peptide sequence, which can self-assemble into nanorods and load STING agonist of DMXAA. The uniform nanosize distribution and good stability of PFPD improve the sequential targeting delivery of drugs towards tumor cells and nuclei. Under light irradiation, PFPD produce a large amount of reactive oxygen species (ROS) to destroy nuclear DNA in situ, and the released cytosolic DNA fragment will efficiently activate innate anti-tumor immunity in combination with STING agonist. In vitro and in vivo results indicate the superior ability of PFPD to activate natural killer cells and T cells, thus efficiently eradicating lung metastatic tumor without inducing unwanted side effects. This work provides a sophisticated strategy for localized activation of innate immunity for systemic tumor treatment, which may inspire the rational design of nanomedicine for tumor precision therapy.
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Affiliation(s)
- Yeyang Wu
- School of Biomedical Engineering & Guangdong Provincial Key Laboratory of Construction and Detection in Tissue Engineering, Southern Medical University, Guangzhou 510515, PR China
| | - Yanmei Li
- School of Biomedical Engineering & Guangdong Provincial Key Laboratory of Construction and Detection in Tissue Engineering, Southern Medical University, Guangzhou 510515, PR China
| | - Ni Yan
- School of Biomedical Engineering & Guangdong Provincial Key Laboratory of Construction and Detection in Tissue Engineering, Southern Medical University, Guangzhou 510515, PR China
| | - Jiaqi Huang
- School of Biomedical Engineering & Guangdong Provincial Key Laboratory of Construction and Detection in Tissue Engineering, Southern Medical University, Guangzhou 510515, PR China
| | - Xinyu Li
- School of Biomedical Engineering & Guangdong Provincial Key Laboratory of Construction and Detection in Tissue Engineering, Southern Medical University, Guangzhou 510515, PR China
| | - Keyan Zhang
- School of Biomedical Engineering & Guangdong Provincial Key Laboratory of Construction and Detection in Tissue Engineering, Southern Medical University, Guangzhou 510515, PR China
| | - Zhenming Lu
- School of Biomedical Engineering & Guangdong Provincial Key Laboratory of Construction and Detection in Tissue Engineering, Southern Medical University, Guangzhou 510515, PR China
| | - Ziwen Qiu
- School of Biomedical Engineering & Guangdong Provincial Key Laboratory of Construction and Detection in Tissue Engineering, Southern Medical University, Guangzhou 510515, PR China
| | - Hong Cheng
- School of Biomedical Engineering & Guangdong Provincial Key Laboratory of Construction and Detection in Tissue Engineering, Southern Medical University, Guangzhou 510515, PR China.
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49
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Raj P, Gupta H, Anantha P, Barman I. Cell-TIMP: Cellular Trajectory Inference based on Morphological Parameter. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.18.590109. [PMID: 38712120 PMCID: PMC11071304 DOI: 10.1101/2024.04.18.590109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Cellular morphology, shaped by various genetic and environmental influences, is pivotal to studying experimental cell biology, necessitating precise measurement and analysis techniques. Traditional approaches, which rely on geometric metrics derived from stained images, encounter obstacles stemming from both the imaging and analytical domains. Staining processes can disrupt the cell's natural state and diminish accuracy due to photobleaching, while conventional analysis techniques, which categorize cells based on shape to discern pathophysiological conditions, often fail to capture the continuous and asynchronous nature of biological processes such as cell differentiation, immune responses, and cancer progression. In this work, we propose the use of quantitative phase imaging for morphological assessment due to its label-free nature. For analysis, we repurposed the genomic analysis toolbox to perform trajectory inference analysis purely based on morphology information. We applied the developed framework to study the progression of leukemia and breast cancer metastasis. Our approach revealed a clear pattern of morphological evolution tied to the diseases' advancement, highlighting the efficacy of our method in identifying functionally significant shape changes where conventional techniques falter. This advancement offers a fresh perspective on analyzing cellular morphology and holds significant potential for the broader research community, enabling a deeper understanding of complex biological dynamics.
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Affiliation(s)
- Piyush Raj
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, Maryland, USA
| | - Himanshu Gupta
- Centre for Applied Autonomous Sensor Systems (AASS), Örebro University, Örebro, Sweden
| | - Pooja Anantha
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, Maryland, USA
| | - Ishan Barman
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, Maryland, USA
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University, School of Medicine, Baltimore, Maryland, USA
- Department of Oncology, Johns Hopkins University, Baltimore, Maryland, USA
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50
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Ma S, Tian Z, Liu L, Zhu J, Wang J, Zhao S, Zhu Y, Zhu J, Wang W, Jiang R, Qu Y, Lei J, Zhao J, Jiang T. Cold to Hot: Tumor Immunotherapy by Promoting Vascular Normalization Based on PDGFB Nanocomposites. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2024; 20:e2308638. [PMID: 38018295 DOI: 10.1002/smll.202308638] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 11/04/2023] [Indexed: 11/30/2023]
Abstract
Immunotherapy is a promising cancer therapeutic strategy. However, the "cold" tumor immune microenvironment (TIME), characterized by insufficient immune cell infiltration and immunosuppressive status, limits the efficacy of immunotherapy. Tumor vascular abnormalities due to defective pericyte coverage are gradually recognized as a profound determinant in "cold" TIME establishment by hindering immune cell trafficking. Recently, several vascular normalization strategies by improving pericyte coverage have been reported, whereas have unsatisfactory efficacy and high rates of resistance. Herein, a combinatorial strategy to induce tumor vasculature-targeted pericyte recruitment and zinc ion-mediated immune activation with a platelet-derived growth factor B (PDGFB)-loaded, cyclo (Arg-Gly-Asp-D-Phe-Lys)-modified zeolitic imidazolate framework 8 (PDGFB@ZIF8-RGD) nanoplatform is proposed. PDGFB@ZIF8-RGD effectively induced tumor vascular normalization, which facilitated trafficking and infiltration of immune effector cells, including natural killer (NK) cells, M1-like macrophages and CD8+ T cells, into tumor microenvironment. Simultaneously, vascular normalization promoted the accumulation of zinc ions inside tumors to trigger effector cell immune activation and effector molecule production. The synergy between these two effects endowed PDGFB@ZIF8-RGD with superior capabilities in reprogramming the "cold" TIME to a "hot" TIME, thereby initiating robust antitumor immunity and suppressing tumor growth. This combinatorial strategy for improving immune effector cell infiltration and activation is a promising paradigm for solid tumor immunotherapy.
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Affiliation(s)
- Shouzheng Ma
- Department of Thoracic Surgery, Tangdu Hospital, Air Force Medical University, Xi'an, 710038, China
| | - Zhimin Tian
- Key Laboratory of Special Functional and Smart Polymer Materials of Ministry of Industry and Information Technology, School of Chemistry and Chemical Engineering, Northwestern Polytechnical University, Xi'an, 710072, China
| | - Lei Liu
- State Key Laboratory of Cancer Biology and National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Fourth Military Medical University, Xi'an, Shaanxi Province, 710032, China
| | - Jun Zhu
- The Southern Theater Air Force Hospital, Guangzhou, 510000, China
| | - Jing Wang
- Department of Immunology, Air Force Medical University, Xi'an, 710032, China
| | - Shoujie Zhao
- Department of General Surgery, Tangdu Hospital, Air Force Medical University, Xi'an, 710038, China
| | - Yejing Zhu
- Department of General Surgery, Tangdu Hospital, Air Force Medical University, Xi'an, 710038, China
| | - Jianfei Zhu
- Department of Thoracic Surgery, Shaanxi Provincial People's Hospital, Xi'an, 710068, China
| | - Wenchen Wang
- Department of Thoracic Surgery, Tangdu Hospital, Air Force Medical University, Xi'an, 710038, China
| | - Runmin Jiang
- Department of Thoracic Surgery, Tangdu Hospital, Air Force Medical University, Xi'an, 710038, China
| | - Yongquan Qu
- Key Laboratory of Special Functional and Smart Polymer Materials of Ministry of Industry and Information Technology, School of Chemistry and Chemical Engineering, Northwestern Polytechnical University, Xi'an, 710072, China
| | - Jie Lei
- Department of Thoracic Surgery, Tangdu Hospital, Air Force Medical University, Xi'an, 710038, China
| | - Junlong Zhao
- State Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers, Medical Genetics and Development Biology, Air Force Medical University, Xi'an, 710032, China
- Department of Pediatrics, Tangdu Hospital, Air Force Medical University, Xi'an, 710000, China
| | - Tao Jiang
- Department of Thoracic Surgery, Tangdu Hospital, Air Force Medical University, Xi'an, 710038, China
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