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Ziblat A, Horton BL, Higgs EF, Hatogai K, Martinez A, Shapiro JW, Kim DEC, Zha Y, Sweis RF, Gajewski TF. Batf3 + DCs and the 4-1BB/4-1BBL axis are required at the effector phase in the tumor microenvironment for PD-1/PD-L1 blockade efficacy. Cell Rep 2024; 43:114141. [PMID: 38656869 DOI: 10.1016/j.celrep.2024.114141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 02/29/2024] [Accepted: 04/08/2024] [Indexed: 04/26/2024] Open
Abstract
The cellular source of positive signals that reinvigorate T cells within the tumor microenvironment (TME) for the therapeutic efficacy of programmed death-1 (PD-1)/programmed death-ligand 1 (PD-L1) blockade has not been clearly defined. We now show that Batf3-lineage dendritic cells (DCs) are essential in this process. Flow cytometric analysis, gene-targeted mice, and blocking antibody studies revealed that 4-1BBL is a major positive co-stimulatory signal provided by these DCs within the TME that translates to CD8+ T cell functional reinvigoration and tumor regression. Immunofluorescence and spatial transcriptomics on human tumor samples revealed clustering of Batf3+ DCs and CD8+ T cells, which correlates with anti-PD-1 efficacy. In addition, proximity to Batf3+ DCs within the TME is associated with CD8+ T cell transcriptional states linked to anti-PD-1 response. Our results demonstrate that Batf3+ DCs within the TME are critical for PD-1/PD-L1 blockade efficacy and indicate a major role for the 4-1BB/4-1BB ligand (4-1BBL) axis during this process.
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Affiliation(s)
- Andrea Ziblat
- Department of Pathology, Section of Hematology/Oncology, University of Chicago, Chicago, IL 60637, USA
| | - Brendan L Horton
- Department of Pathology, Section of Hematology/Oncology, University of Chicago, Chicago, IL 60637, USA
| | - Emily F Higgs
- Department of Pathology, Section of Hematology/Oncology, University of Chicago, Chicago, IL 60637, USA
| | - Ken Hatogai
- Department of Pathology, Section of Hematology/Oncology, University of Chicago, Chicago, IL 60637, USA
| | - Anna Martinez
- Department of Pathology, Section of Hematology/Oncology, University of Chicago, Chicago, IL 60637, USA
| | - Jason W Shapiro
- Center for Research Informatics, University of Chicago, Chicago, IL 60637, USA
| | - Danny E C Kim
- Department of Pathology, Section of Hematology/Oncology, University of Chicago, Chicago, IL 60637, USA
| | - YuanYuan Zha
- Human Immunological Monitoring Facility, University of Chicago, Chicago, IL 60637, USA
| | - Randy F Sweis
- Department of Medicine, University of Chicago, Chicago, IL 60612, USA
| | - Thomas F Gajewski
- Department of Pathology, Section of Hematology/Oncology, University of Chicago, Chicago, IL 60637, USA; Department of Medicine, University of Chicago, Chicago, IL 60612, USA.
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Mei SQ, Liu JQ, Huang ZJ, Luo WC, Peng YL, Chen ZH, Deng Y, Xu CR, Zhou Q. Identification of a risk score model based on tertiary lymphoid structure-related genes for predicting immunotherapy efficacy in non-small cell lung cancer. Thorac Cancer 2024. [PMID: 38558529 DOI: 10.1111/1759-7714.15299] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Revised: 03/10/2024] [Accepted: 03/13/2024] [Indexed: 04/04/2024] Open
Abstract
BACKGROUND Tertiary lymphoid structures (TLSs) affect the prognosis and efficacy of immunotherapy in patients with non-small cell lung cancer (NSCLC), but the underlying mechanisms are not well understood. METHODS TLSs were identified and categorized online from the Cancer Digital Slide Archive (CDSA). Overall survival (OS) and disease-free survival (DFS) were analyzed. GSE111414 and GSE136961 datasets were downloaded from the GEO database. GSVA, GO and KEGG were used to explore the signaling pathways. Immune cell infiltration was analyzed by xCell, ssGSEA and MCP-counter. The analysis of WGCNA, Lasso and multivariate cox regression were conducted to develop a gene risk score model based on the SU2C-MARK cohort. RESULTS TLS-positive was a protective factor for OS according to multivariate cox regression analysis (p = 0.029). Both the TLS-positive and TLS-mature groups exhibited genes enrichment in immune activation pathways. The TLS-mature group showed more activated dendritic cell infiltration than the TLS-immature group. We screened TLS-related genes using WGCNA. Lasso and multivariate cox regression analysis were used to construct a five-genes (RGS8, RUF4, HLA-DQB2, THEMIS, and TRBV12-5) risk score model, the progression free survival (PFS) and OS of patients in the low-risk group were markedly superior to those in the high-risk group (p < 0.0001; p = 0.0015, respectively). Calibration and ROC curves indicated that the combined model with gene risk score and clinical features could predict the PFS of patients who have received immunotherapy more accurately than a single clinical factor. CONCLUSIONS Our data suggested a pivotal role of TLSs formation in survival outcome and immunotherapy response of NSCLC patients. Tumors with mature TLS formation showed more activated immune microenvironment. In addition, the model constructed by TLS-related genes could predict the response to immunotherapy and is meaningful for clinical decision-making.
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Affiliation(s)
- Shi-Qi Mei
- Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Jia-Qi Liu
- Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Zi-Jian Huang
- Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Wei-Chi Luo
- Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Ying-Long Peng
- Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
- School of Medicine South China University of Technology, Guangzhou, China
| | - Zhi-Hong Chen
- Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Yu Deng
- Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Chong-Rui Xu
- Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Qing Zhou
- Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
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Xu Y, Sun X, Liu G, Li H, Yu M, Zhu Y. Integration of multi-omics and clinical treatment data reveals bladder cancer therapeutic vulnerability gene combinations and prognostic risks. Front Immunol 2024; 14:1301157. [PMID: 38299148 PMCID: PMC10827994 DOI: 10.3389/fimmu.2023.1301157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2023] [Accepted: 12/29/2023] [Indexed: 02/02/2024] Open
Abstract
Background Bladder cancer (BCa) is a common malignancy of the urinary tract. Due to the high heterogeneity of BCa, patients have poor prognosis and treatment outcomes. Immunotherapy has changed the clinical treatment landscape for many advanced malignancies, opening new avenues for the precise treatment of malignancies. However, effective predictors and models to guide clinical treatment and predict immunotherapeutic outcomes are still lacking. Methods We downloaded BCa sample data from The Cancer Genome Atlas to identify anti-PD-L1 immunotherapy-related genes through an immunotherapy dataset and used machine learning algorithms to build a new PD-L1 multidimensional regulatory index (PMRI) based on these genes. PMRI-related column-line graphs were constructed to provide quantitative tools for clinical practice. We analyzed the clinical characteristics, tumor immune microenvironment, chemotherapy response, and immunotherapy response of patients based on PMRI system. Further, we performed function validation of classical PMRI genes and their correlation with PD-L1 in BCa cells and screening of potential small-molecule drugs targeting PMRI core target proteins through molecular docking. Results PMRI, which consists of four anti-PD-L1 immunotherapy-associated genes (IGF2BP3, P4HB, RAC3, and CLK2), is a reliable predictor of survival in patients with BCa and has been validated using multiple external datasets. We found higher levels of immune cell infiltration and better responses to immunotherapy and cisplatin chemotherapy in the high PMRI group than in the low PMRI group, which can also be used to predict immune efficacy in a variety of solid tumors other than BCa. Knockdown of IGF2BP3 inhibited BCa cell proliferation and migration, and IGF2BP3 was positively correlated with PD-L1 expression. We performed molecular docking prediction for each of the core proteins comprising PMRI and identified 16 small-molecule drugs with the highest affinity to the target proteins. Conclusions Our PD-L1 multidimensional expression regulation model based on anti-PD-L1 immunotherapy-related genes can accurately assess the prognosis of patients with BCa and identify patient populations that will benefit from immunotherapy, providing a new tool for the clinical management of intermediate and advanced BCa.
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Affiliation(s)
- Yan Xu
- Department of Urology, The First Hospital of China Medical University, Shenyang, China
| | - Xiaoyu Sun
- Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang, China
| | - Guangxu Liu
- Department of Urology, The First Hospital of China Medical University, Shenyang, China
| | - Hongze Li
- Department of Urology, The First Hospital of China Medical University, Shenyang, China
| | - Meng Yu
- Department of Laboratory Animal Science, China Medical University, Liaoning, Shenyang, China
- Key Laboratory of Transgenetic Animal Research, China Medical University, Liaoning, Shenyang, China
| | - Yuyan Zhu
- Department of Urology, The First Hospital of China Medical University, Shenyang, China
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Wu Z, Jin M, Xin P, Zhang H. Leveraging diverse cell-death related signature predicts the prognosis and immunotherapy response in renal clear cell carcinoma. Front Immunol 2023; 14:1293729. [PMID: 38146369 PMCID: PMC10749459 DOI: 10.3389/fimmu.2023.1293729] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 11/28/2023] [Indexed: 12/27/2023] Open
Abstract
Background Modulation of programmed cell death in tumor cells alters the tumor microenvironment and the influx of tumor-infiltrating lymphocytes, and the combination of its inducers and immune checkpoint inhibitors plays a synergistic role in enhancing antitumor effects. Methods We downloaded the data of clear cell renal cell carcinoma samples from The Cancer Genome Atlas and used a machine learning approach to build a new programmed cell death index (PCDI) through 13 programmed cell death-related genes. Based on PCDI, clinical features, tumor immune microenvironment, chemotherapy response and immunotherapy response were systematically analyzed. Results PCDI consists of eight programmed cell death-related genes (TBX3, BID, TCIRG1, IDUA, KDR, PYCARD, IFNG and LRRK2). PCDI is a reliable predictor of survival in clear cell renal cell carcinoma patients and has been validated in multiple external datasets. We found that the high PCDI group showed higher levels of immune cell infiltration and better response to immunotherapy compared to the low PCDI group, and PCDI can also be used for prognostic prediction in a variety of cancers other than clear cell renal cell carcinoma. In vitro experiments demonstrated that knockdown of IDUA inhibited the proliferation and migration of clear cell renal cell carcinoma. Conclusions The PCDI identified in this study provides valuable insights into the clinical management of clear cell renal cell carcinoma by accurately evaluating the prognosis of patients with clear cell renal carcinoma and identifying the patient population that would benefit from immunotherapy.
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Affiliation(s)
- Zhengqi Wu
- Department of Urology, The First Hospital of China Medical University, Shenyang, Liaoning, China
| | - Mingyue Jin
- Department of Endocrinology, Shenzhen University General Hospital, Shenzhen, Guangdong, China
| | - Peng Xin
- Department of Urology, The First Hospital of China Medical University, Shenyang, Liaoning, China
| | - Hao Zhang
- Department of Urology, The First Hospital of China Medical University, Shenyang, Liaoning, China
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Zeng W, Zhu J, Zeng D, Guo J, Huang G, Zeng Y, Wang L, Bin J, Liao Y, Shi M, Liao W. Epigenetic Modification-Associated Molecular Classification of Gastric Cancer. J Transl Med 2023; 103:100170. [PMID: 37150296 DOI: 10.1016/j.labinv.2023.100170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2023] [Revised: 04/02/2023] [Accepted: 04/20/2023] [Indexed: 05/09/2023] Open
Abstract
Epigenetic modification is involved in tumorigenesis and cancer progression. We developed an epigenetic modification-associated molecular classification of gastric cancer (GC) to identify signature genes that accurately predict prognosis and the efficacy of immunotherapy. Least absolute shrinkage and selection operator and multivariate Cox regression analysis were conducted to develop an epigenetic modification-associated molecular classification. We investigated the significance of PIP4P2, an independent prognostic factor of the classification system, in predicting the prognosis and immunotherapy efficacy of patients with GC. The epigenetic modification-associated molecular classification was highly associated with the clinicopathological characteristics of patients and the existing classification of GC. PIP4P2 was highly expressed in GC tissue and tumor-associated macrophages. High PIP4P2 expression in GC tissue-induced tumor progression by activating PI3K/AKT signal transduction had a negative impact on immunotherapy efficacy. High expression of PIP4P2 in macrophages was correlated with poor prognosis in patients with GC. PIP4P2 is an independent unfavorable prognostic factor of epigenetic modification-associated molecular classification, is involved in tumorigenic progression, and is essential for assessing the prognosis and immunotherapy efficacy of GC.
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Affiliation(s)
- Wei Zeng
- Department of Oncology, First Peoples Hospital of Shunde, Shunde Hospital of Southern Medical University, Shunde, China; Department of Hematology and Oncology, Shenzhen University General Hospital, Shenzhen University, Shenzhen, China
| | - Jinfeng Zhu
- Department of General Surgery, Shenzhen University General Hospital, Shenzhen University, Shenzhen, China
| | - Dongqiang Zeng
- Department of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, China; Guangdong Province Key Laboratory of Molecular Tumor Pathology, Southern Medical University, Guangzhou, China
| | - Jian Guo
- Department of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, China; Guangdong Province Key Laboratory of Molecular Tumor Pathology, Southern Medical University, Guangzhou, China
| | - Genjie Huang
- Department of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, China; Guangdong Province Key Laboratory of Molecular Tumor Pathology, Southern Medical University, Guangzhou, China
| | - Yu Zeng
- Department of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, China; Guangdong Province Key Laboratory of Molecular Tumor Pathology, Southern Medical University, Guangzhou, China
| | - Ling Wang
- Department of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, China; Guangdong Province Key Laboratory of Molecular Tumor Pathology, Southern Medical University, Guangzhou, China
| | - Jianping Bin
- Department of Cardiology, State Key Laboratory of Organ Failure Research, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Yulin Liao
- Department of Cardiology, State Key Laboratory of Organ Failure Research, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Min Shi
- Department of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, China; Guangdong Province Key Laboratory of Molecular Tumor Pathology, Southern Medical University, Guangzhou, China
| | - Wangjun Liao
- Department of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, China; Guangdong Province Key Laboratory of Molecular Tumor Pathology, Southern Medical University, Guangzhou, China.
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Zeng W, Wang J, Yang J, Chen Z, Cui Y, Li Q, Luo G, Ding H, Ju S, Li B, Chen J, Xie Y, Tong X, Liu M, Zhao J. Identification of immune activation-related gene signature for predicting prognosis and immunotherapy efficacy in lung adenocarcinoma. Front Immunol 2023; 14:1217590. [PMID: 37492563 PMCID: PMC10364982 DOI: 10.3389/fimmu.2023.1217590] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 06/23/2023] [Indexed: 07/27/2023] Open
Abstract
Background Lung adenocarcinoma (LUAD) is a major subtype of non-small cell lung cancer (NSCLC) with a highly heterogeneous tumor microenvironment. Immune checkpoint inhibitors (ICIs) are more effective in tumors with a pre-activated immune status. However, the potential of the immune activation-associated gene (IAG) signature for prognosis prediction and immunotherapy response assessment in LUAD has not been established. Therefore, it is critical to explore such gene signatures. Methods RNA sequencing profiles and corresponding clinical parameters of LUAD were extracted from the TCGA and GEO databases. Unsupervised consistency clustering analysis based on immune activation-related genes was performed on the enrolled samples. Subsequently, prognostic models based on genes associated with prognosis were built using the last absolute shrinkage and selection operator (LASSO) method and univariate Cox regression. The expression levels of four immune activation related gene index (IARGI) related genes were validated in 12 pairs of LUAD tumor and normal tissue samples using qPCR. Using the ESTIMATE, TIMER, and ssGSEA algorithms, immune cell infiltration analysis was carried out for different groups, and the tumor immune dysfunction and rejection (TIDE) score was used to evaluate the effectiveness of immunotherapy. Results Based on the expression patterns of IAGs, the TCGA LUAD cohort was classified into two clusters, with those in the IAG-high pattern demonstrating significantly better survival outcomes and immune cell infiltration compared to those in the IAG-low pattern. Then, we developed an IARGI model that effectively stratified patients into different risk groups, revealing differences in prognosis, mutation profiles, and immune cell infiltration within the tumor microenvironment between the high and low-risk groups. Notably, significant disparities in TIDE score between the two groups suggest that the low-risk group may exhibit better responses to ICIs therapy. The IARGI risk model was validated across multiple datasets and demonstrated exceptional performance in predicting overall survival in LUAD, and an IARGI-integrated nomogram was established as a quantitative tool for clinical practice. Conclusion The IARGI can serve as valuable biomarkers for evaluating the tumor microenvironment and predicting the prognosis of LUAD patients. Furthermore, these genes probably provide valuable guidance for establishing effective immunotherapy regimens for LUAD patients.
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Affiliation(s)
- Weibiao Zeng
- Institute of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China
- Department of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Jin Wang
- Department of Pharmaceutics, College of Pharmaceutical Sciences, Soochow University, Suzhou, China
| | - Jian Yang
- Institute of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China
- Department of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Zhike Chen
- Institute of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China
- Department of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Yuan Cui
- Institute of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China
- Department of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Qifan Li
- Institute of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China
- Department of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Gaomeng Luo
- Institute of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China
- Department of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Hao Ding
- Institute of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China
- Department of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Sheng Ju
- Institute of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China
- Department of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Baisong Li
- Department of Pharmaceutics, College of Pharmaceutical Sciences, Soochow University, Suzhou, China
| | - Jun Chen
- Institute of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China
- Department of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Yufeng Xie
- Institute of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China
- Department of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Xin Tong
- Institute of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China
- Department of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Mi Liu
- Department of Pharmaceutics, College of Pharmaceutical Sciences, Soochow University, Suzhou, China
| | - Jun Zhao
- Institute of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China
- Department of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China
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Zhang Z, Chen P, Yun J. Comprehensive analysis of a novel RNA modifications-related model in the prognostic characterization, immune landscape and drug therapy of bladder cancer. Front Genet 2023; 14:1156095. [PMID: 37124622 PMCID: PMC10131083 DOI: 10.3389/fgene.2023.1156095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 03/31/2023] [Indexed: 05/02/2023] Open
Abstract
Background: Bladder cancer (BCa) is the leading reason for death among genitourinary malignancies. RNA modifications in tumors closely link to the immune microenvironment. Our study aimed to propose a promising model associated with the "writer" enzymes of five primary RNA adenosine modifications (including m6A, m6Am, m1A, APA, and A-to-I editing), thus characterizing the clinical outcome, immune landscape and therapeutic efficacy of BCa. Methods: Unsupervised clustering was employed to categorize BCa into different RNA modification patterns based on gene expression profiles of 34 RNA modification "writers". The RNA modification "writers" score (RMS) signature composed of RNA phenotype-associated differentially expressed genes (DEGs) was established using the least absolute shrinkage and selection operator (LASSO), which was evaluated in meta-GEO (including eight independent GEO datasets) training cohort and the TCGA-BLCA validation cohort. The hub genes in the RMS model were determined via weighted gene co-expression network analysis (WGCNA) and were further validated using human specimen. The potential applicability of the RMS model in predicting the therapeutic responsiveness was assessed through the Genomics of Drug Sensitivity in Cancer database and multiple immunotherapy datasets. Results: Two distinct RNA modification patterns were determined among 1,410 BCa samples from a meta-GEO cohort, showing radically varying clinical outcomes and biological characteristics. The RMS model comprising 14 RNA modification phenotype-associated prognostic DEGs positively correlated with the unsatisfactory outcome of BCa patients in meta-GEO training cohort (HR = 3.00, 95% CI = 2.19-4.12) and TCGA-BLCA validation cohort (HR = 1.53, 95% CI = 1.13-2.09). The infiltration of immunosuppressive cells and the activation of EMT, angiogenesis, IL-6/JAK/STAT3 signaling were markedly enriched in RMS-high group. A nomogram exhibited high prognostic prediction accuracy, with a concordance index of 0.785. The therapeutic effect of chemotherapeutic agents and antibody-drug conjugates was significantly different between RMS-low and -high groups. The combination of the RMS model and conventional characteristics (TMB, TNB and PD-L1) achieved an optimal AUC value of 0.828 in differentiating responders from non-responders to immunotherapy. Conclusion: We conferred the first landscape of five forms of RNA modifications in BCa and emphasized the excellent power of an RNA modifications-related model in evaluating BCa prognosis and immune landscape.
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Affiliation(s)
- Ziying Zhang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China
- Department of Pathology, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China
| | - Peng Chen
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Jingping Yun
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China
- Department of Pathology, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China
- *Correspondence: Jingping Yun,
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Xu Y, Xia Z, Sun X, Wei B, Fu Y, Shi D, Zhu Y. Identification of a glutamine metabolism reprogramming signature for predicting prognosis, immunotherapy efficacy, and drug candidates in bladder cancer. Front Immunol 2023; 14:1111319. [PMID: 36911676 PMCID: PMC9995899 DOI: 10.3389/fimmu.2023.1111319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 02/14/2023] [Indexed: 02/25/2023] Open
Abstract
Background Bladder cancer is the most common malignancy of the urinary system. However, patient prognosis and treatment outcomes in bladder cancer are difficult to predict owing to high tumor heterogeneity. Given that abnormal glutamine metabolism has been identified as a key factor driving the progression of bladder cancer, it is necessary to assess the prognosis and therapeutic efficacy of bladder cancer treatments based on an analysis of glutamine metabolism-related genes. Methods We used bladder cancer sample data downloaded from The Cancer Genome Atlas to identify glutamine metabolism-related genes as prognostic markers, and established a novel Glutamine Metabolism Immunity Index (GMII) based on univariate and multivariate COX regression analyses. On the basis of GMII values, bladder cancer patients were divided into high- and low-risk groups, and systematic analysis was conducted for clinical features, somatic mutations, immune cell infiltration, chemotherapeutic response, and immunotherapeutic efficacy. Candidate small-molecule drugs targeting the GMII core target proteins were identified based on molecular docking analysis. Results The GMII consisting of eight independent prognostic genes was established to be an excellent tool for predicting the survival in patients with bladder cancer and was validated using multiple datasets. Compared with patients in the high-risk group, those in the low-risk group had significantly better responses to gemcitabine and immune checkpoint blockade. In addition, we predicted 12 potential small-molecule drugs that could bind to three of the GMII core target proteins. Conclusions The GMII can be used to accurately predict the prognosis and immunotherapeutic response of bladder cancer patients, as well as candidate small-molecule drugs. Furthermore, the novel "Glutamine Metabolism-related Gene"-guided strategy for predicting survival and chemo-immunotherapeutic efficacy may also be applicable for cancers other than bladder cancer.
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Affiliation(s)
- Yan Xu
- Department of Urology, The First Hospital of China Medical University, Shenyang, China
| | - Zhixiu Xia
- Colorectal Tumor Surgery Ward, Department of General Surgery, Shengjing Hospital of China Medical University, Shenyang, China
| | - Xiaoyu Sun
- Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang, China
| | - Baojun Wei
- Department of Urology, The First Hospital of China Medical University, Shenyang, China
| | - Yang Fu
- Department of Urology, The First Hospital of China Medical University, Shenyang, China
| | - Du Shi
- Department of Urology, The First Hospital of China Medical University, Shenyang, China
| | - Yuyan Zhu
- Department of Urology, The First Hospital of China Medical University, Shenyang, China
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An B, Guo Z, Wang J, Zhang C, Zhang G, Yan L. Derivation and external validation of dendritic cell-related gene signatures for predicting prognosis and immunotherapy efficacy in bladder urothelial carcinoma. Front Immunol 2022; 13:1080947. [PMID: 36578478 PMCID: PMC9790929 DOI: 10.3389/fimmu.2022.1080947] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 11/21/2022] [Indexed: 12/14/2022] Open
Abstract
Background In the regulation of tumor-related immunity, dendritic cells (DCs) are crucial sentinel cells; they are powerful to present antigens and initiate immune responses. Therefore, we concentrated on investigating the DC-related gene profile, prognosis, and gene mutations in bladder urothelial carcinoma (BLCA) patients to identify sensitivity to immunotherapy of patients. Methods According to DC infiltration, BLCA patients were divided into two subgroups, and differentially expressed genes (DEGs) were obtained. Patients were classified by unsupervised clustering into new subgroups. The least absolute shrinkage and selection operator (LASSO) regression analysis and Cox regression were used to develop a DC-related risk model. CIBERSORT, xCell, and GSEA were used to infer immune cells' relative abundance separately and enriched immune pathways. Results A total of 29 prognosis-related DEGs were identified from the unsupervised cluster. Among them, 22 genes were selected for constructing the DC-related risk model. The dendritic cell-related risk score (DCRS) can accurately distinguish patients with different sensitive responses to immunotherapy and overall survival outcomes. Furthermore, patients with ryanodine receptor 2 (RYR2) mutation had a better prognosis. Conclusions The DCRS played an essential part in immunity pathway and formation of TME diversity. Our study indicated that RYR2 mutation combined with DCRS is useful for predicting the prognosis and discovering appropriate patients for immunotherapy.
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Affiliation(s)
- Bingzheng An
- Department of Urology, Qilu Hospital of Shandong University, Jinan, China
| | - Zhaoxin Guo
- Department of Urology, Qilu Hospital of Shandong University, Jinan, China
| | - Junyan Wang
- Department of Urology, Qilu Hospital of Shandong University, Jinan, China
| | - Chen Zhang
- Department of Urology, Qilu Hospital of Shandong University, Jinan, China
| | - Guanghao Zhang
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, United States
| | - Lei Yan
- Department of Urology, Qilu Hospital of Shandong University, Jinan, China,*Correspondence: Lei Yan,
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10
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Tang Y, Guo C, Yang Z, Wang Y, Zhang Y, Wang D. Identification of a Tumor Immunological Phenotype-Related Gene Signature for Predicting Prognosis, Immunotherapy Efficacy, and Drug Candidates in Hepatocellular Carcinoma. Front Immunol 2022; 13:862527. [PMID: 35493471 PMCID: PMC9039265 DOI: 10.3389/fimmu.2022.862527] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Accepted: 03/22/2022] [Indexed: 02/05/2023] Open
Abstract
Hepatocellular carcinoma (HCC) is the predominant subtype of primary liver cancer and represents a highly heterogeneous disease, making it hard to predict the prognosis and therapy efficacy. Here, we established a novel tumor immunological phenotype-related gene index (TIPRGPI) consisting of 11 genes by Univariate Cox regression and the least absolute shrinkage and selection operator (LASSO) algorithm to predict HCC prognosis and immunotherapy response. TIPRGPI was validated in multiple datasets and exhibited outstanding performance in predicting the overall survival of HCC. Multivariate analysis verified it as an independent predictor and a TIPRGPI-integrated nomogram was constructed to provide a quantitative tool for clinical practice. Distinct mutation profiles, hallmark pathways, and infiltration of immune cells in tumor microenvironment were shown between the TIPRGPI high and low-risk groups. Notably, significant differences in tumor immunogenicity and tumor immune dysfunction and exclusion (TIDE) were observed between the two risk groups, suggesting a better response to immune checkpoint blockade (ICB) therapy of the low-risk group. Besides, six potential drugs binding to the core target of the TIPRGPI signature were predicted via molecular docking. Taken together, our study shows that the proposed TIPRGPI was a reliable signature to predict the risk classification, immunotherapy response, and drugs candidate with potential application in the clinical decision and treatment of HCC. The novel “TIP genes”-guided strategy for predicting the survival and immunotherapy efficacy, we reported here, might be also applied to more cancers other than HCC.
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Affiliation(s)
- Yuqin Tang
- State Key Laboratory of Southwestern Chinese Medicine Resources, School of Basic Medical Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Chengbin Guo
- Faculty of Medicine, Macau University of Science and Technology, Macau, China
| | - Zhao Yang
- West China School of Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - Yumei Wang
- State Key Laboratory of Southwestern Chinese Medicine Resources, School of Basic Medical Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Yongqiang Zhang
- Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Dong Wang
- State Key Laboratory of Southwestern Chinese Medicine Resources, School of Basic Medical Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu, China
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11
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Zhang W, Li Y, Lyu J, Shi F, Kong Y, Sheng C, Wang S, Wang Q. An aging-related signature predicts favorable outcome and immunogenicity in lung adenocarcinoma. Cancer Sci 2021; 113:891-903. [PMID: 34967077 PMCID: PMC8898732 DOI: 10.1111/cas.15254] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Revised: 12/22/2021] [Accepted: 12/24/2021] [Indexed: 12/01/2022] Open
Abstract
Aging has been demonstrated to play vital roles in the prognosis and treatment efficacy of cancers, including lung adenocarcinoma (LUAD). This novel study aimed to construct an aging‐related risk signature to evaluate the prognosis and immunogenicity of LUAD. Transcriptomic profiles and clinical information were collected from a total of 2518 LUAD patients from 12 independent cohorts. The risk signature was developed by combining specific gene expression with the corresponding regression coefficients. One cohort treated with the immune checkpoint inhibitor (ICI) was also used. Subsequently, a risk signature was developed based on 21 aging‐related genes. LUAD patients with low‐risk scores exhibited improved survival outcomes in both the discovery and validation cohorts. Further immunology analysis revealed elevated lymphocyte infiltration, decreased infiltration of immune‐suppressive cells, immune response‐related pathways, and favorable ICI predictor enrichment in the low‐risk subgroup. Genomic mutation exploration indicated the enhanced mutation burden and higher mutation rates in significantly driver genes of TP53, KEAP1, SMARCA4, and RBM10 were enriched in patients with a low‐risk signature. In the immunotherapeutic cohort, it was observed that low‐risk aging scores were markedly associated with prolonged ICI prognosis. Overall, the estimated aging signature proved capable of evaluating the prognosis, tumor microenvironment, and immunogenicity, which further provided clues for tailoring prognosis prediction and immunotherapy strategies, apart from promoting individualized treatment plans for LUAD patients.
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Affiliation(s)
- Wenjing Zhang
- Department of Health Statistics, Key Laboratory of Medicine and Health of Shandong Province, School of Public Health, Weifang Medical University, Weifang, Shandong, 261053, China
| | - Yuting Li
- Tianjin Cancer Institute, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin, 300060, China
| | - Juncheng Lyu
- Department of Health Statistics, Key Laboratory of Medicine and Health of Shandong Province, School of Public Health, Weifang Medical University, Weifang, Shandong, 261053, China
| | - Fuyan Shi
- Department of Health Statistics, Key Laboratory of Medicine and Health of Shandong Province, School of Public Health, Weifang Medical University, Weifang, Shandong, 261053, China
| | - Yujia Kong
- Department of Health Statistics, Key Laboratory of Medicine and Health of Shandong Province, School of Public Health, Weifang Medical University, Weifang, Shandong, 261053, China
| | - Chao Sheng
- Department of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin, 300060, China
| | - Suzhen Wang
- Department of Health Statistics, Key Laboratory of Medicine and Health of Shandong Province, School of Public Health, Weifang Medical University, Weifang, Shandong, 261053, China
| | - Qinghua Wang
- Department of Health Statistics, Key Laboratory of Medicine and Health of Shandong Province, School of Public Health, Weifang Medical University, Weifang, Shandong, 261053, China
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12
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Zhong C, Wang L, Hu S, Huang C, Xia Z, Liao J, Yi W, Chen J. Poly(I:C) enhances the efficacy of phagocytosis checkpoint blockade immunotherapy by inducing IL-6 production. J Leukoc Biol 2021; 110:1197-1208. [PMID: 33988261 DOI: 10.1002/jlb.5ma0421-013r] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2021] [Revised: 04/16/2021] [Accepted: 04/27/2021] [Indexed: 01/19/2023] Open
Abstract
Macrophage phagocytosis plays essential roles in antitumor immunity. CD47/SIRPα phagocytosis checkpoint blockade has demonstrated therapeutic potential in several hematopoietic cancers, but recent clinical studies reported very limited efficacy against solid malignancies. Here, we show that polyinosinic-polycytidylic acid (Poly(I:C)), a synthetic analog of double-stranded RNA, enhances the antitumor activity of CD47 blockade in colorectal cancer in vitro and in vivo. Poly(I:C) activation leads to a potent immune response characterized by the production of proinflammatory cytokines, especially IL-6. Stimulation with IL-6 promotes the PI3K signaling and cytoskeletal reorganization required for macrophage phagocytosis mediated by CD47 blockade. Our findings demonstrate the potential of Poly(I:C) to synergize the efficacy of CD47 blockade therapy and a novel role for IL-6 in macrophage phagocytosis, which provide new strategy for combinational cancer immunotherapy.
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Affiliation(s)
- Cheng Zhong
- Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Lixiang Wang
- Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Shengzhao Hu
- The First Affiliated Hospital, Nanchang University, Nanchang, China
| | - Chunliu Huang
- Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Zijin Xia
- Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Jing Liao
- The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Wei Yi
- Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, China
| | - Jun Chen
- Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
- Guangdong Engineering & Technology Research Center for Disease-Model Animals, Laboratory Animal Center, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Key Laboratory of Tropical Disease Control of the Ministry of Education, Sun Yat-sen University, Guangzhou, China
- Center for Precision Medicine, Sun Yat-sen University, Guangzhou, China
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13
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Wang Q, Zhang W, Guo Y, Li Y, Fu K. Development of an immune-related signature for predicting survival outcome and immunotherapy response in osteosarcoma. Aging (Albany NY) 2021; 13:24155-24170. [PMID: 34747719 PMCID: PMC8610143 DOI: 10.18632/aging.203671] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2021] [Accepted: 10/28/2021] [Indexed: 11/25/2022]
Abstract
Osteosarcoma (OS) is the most common bone cancer, mainly diagnosed in children and adolescents. So far, no reliable molecular biomarkers have been identified to effectively evaluate OS prognosis and immune infiltration. Herein, we curated transcriptome profiles and clinical information from the publicly available OS cohorts to establish an immune-related prognostic signature. Besides, immunotherapeutic cohorts of urothelial cancer and melanoma patients were also employed to infer immunotherapy prediction roles of the identified signature. Lymphocytes infiltration, immune response-related pathways and signatures in the microenvironment were assessed according to distinct risk subgroups. Based on the univariate Cox analysis and further feature selection implemented by the LASSO regression model in the TARGET cohort, a 21-immune-gene signature was identified by combing the expression values and corresponding coefficients. We observed that the low-risk score of this signature was significantly linked with the preferable survival outcome (Log-rank test P < 0.001). The consistent results of better prognoses of the low-risk group were also obtained in subsequent two validation cohorts. Immunology analyses showed that favorable immune infiltration and elevated enrichment of immune response signals may contribute to the better outcome of the low-risk OS subgroup. The immunotherapeutic efficacy analyses demonstrated that low-risk patients harbored significantly enhanced response rates and improved immunotherapy survival outcomes. Together, our established signature could evaluate survival risk and represent the immune microenvironment status of OS, which promotes precision treatment and provides a potential biomarker for prognosis prediction and immunotherapy efficacy assessment.
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Affiliation(s)
- Qinghua Wang
- Department of Health Statistics, Key Laboratory of Medicine and Health of Shandong Province, School of Public Health, Weifang Medical University, Weifang, Shandong 261053, China
| | - Wenjing Zhang
- Department of Health Statistics, Key Laboratory of Medicine and Health of Shandong Province, School of Public Health, Weifang Medical University, Weifang, Shandong 261053, China
| | - Yuxian Guo
- Department of Health Statistics, Key Laboratory of Medicine and Health of Shandong Province, School of Public Health, Weifang Medical University, Weifang, Shandong 261053, China
| | - Yuting Li
- Tianjin Cancer Institute, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300060, China
| | - Kaifeng Fu
- Department of Orthopedics, Sunshine Union Hospital, Weifang, Shandong 261061, China
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14
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Gao Z, Chen J, Tao Y, Wang Q, Peng S, Yu S, Zeng J, Li K, Xie Z, Huang H. Immune Signatures Combined With BRCA1-Associated Protein 1 Mutations Predict Prognosis and Immunotherapy Efficacy in Clear Cell Renal Cell Carcinoma. Front Cell Dev Biol 2021; 9:747985. [PMID: 34733850 PMCID: PMC8558467 DOI: 10.3389/fcell.2021.747985] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Accepted: 09/20/2021] [Indexed: 12/19/2022] Open
Abstract
Immunotherapy is gradually emerging in the field of tumor treatment. However, because of the complexity of the tumor microenvironment (TME), some patients cannot benefit from immunotherapy. Therefore, we comprehensively analyzed the TME and gene mutations of ccRCC to identify a comprehensive index that could more accurately guide the immunotherapy of patients with ccRCC. We divided ccRCC patients into two groups based on immune infiltration activity. Next, we investigated the differentially expressed genes (DEGs) and constructed a prognostic immune score using univariate Cox regression analysis, unsupervised cluster analysis, and principal component analysis (PCA) and validated its predictive power in both internal and total sets. Subsequently, the gene mutations in the groups were investigated, and patients suitable for immunotherapy were selected in combination with the immune score. The prognosis of the immune score-low group was significantly worse than that of the immune score-high group. The patients with BRCA1-associated protein 1 (BAP1) mutation had a poor prognosis. Thus, this study indicated that establishing an immune score model combined with BAP1 mutation can better predict the prognosis of patients, screen suitable ccRCC patients for immunotherapy, and select more appropriate drug combinations.
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Affiliation(s)
- Ze Gao
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Junxiu Chen
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Yiran Tao
- Department of Urology, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Qiong Wang
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.,Department of Pathology, School of Medicine, University of Virginia, Charlottesville, VA, United States
| | - Shirong Peng
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Shunli Yu
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Jianwen Zeng
- Department of Urology, Qingyuan People's Hospital, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan, China
| | - Kaiwen Li
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Zhongqiu Xie
- Department of Pathology, School of Medicine, University of Virginia, Charlottesville, VA, United States
| | - Hai Huang
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.,Department of Urology, Qingyuan People's Hospital, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan, China
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15
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Yue T, Zuo S, Zhu J, Guo S, Huang Z, Li J, Wang X, Liu Y, Chen S, Wang P. Two Similar Signatures for Predicting the Prognosis and Immunotherapy Efficacy of Stomach Adenocarcinoma Patients. Front Cell Dev Biol 2021; 9:704242. [PMID: 34414187 PMCID: PMC8369372 DOI: 10.3389/fcell.2021.704242] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2021] [Accepted: 07/15/2021] [Indexed: 12/14/2022] Open
Abstract
Background Globally, stomach adenocarcinoma (STAD)’s high morbidity and mortality should arouse our urgent attention. How long can STAD patients survive after surgery and whether novel immunotherapy is effective are questions that our clinicians cannot escape. Methods Various R packages, GSEA software, Metascape, STRING, Cytoscape, Venn diagram, TIMER2.0 website, TCGA, and GEO databases were used in our study. Results In the TCGA and GEO, macrophage abundance of STAD tissues was significantly higher than that of adjacent tissues and was an independent prognostic factor, significantly related to the overall survival (OS) of STAD patients. Between the high- and low- macrophage abundance, we conducted differential expression, univariate and multivariate Cox analysis, and obtained 12 candidate genes, and finally constructed a 3-gene signature. Both low macrophage abundance group and group D had higher TMB and PD-L1 expression. Furthermore, top 5 common gene-mutated STAD tissues had lower macrophage abundance. Macrophage abundance and 3 key genes expression were also lower in the Epstein-Barr Virus (EBV) and HM-indel STAD subtypes and significantly correlated with the tumor microenvironment score. The functional enrichment and ssGSEA revealed 2 signatures were similar and closely related to BOQUEST_STEM_CELL_UP, including genes up-regulated in proliferative stromal stem cells. Hsa-miR-335-5p simultaneously regulated 3 key genes and significantly related to the expression of PD-L1, CD8A and PDCD1. Conclusion macrophage abundance and 3-gene signature could simultaneously predict the OS and immunotherapy efficacy, and both 2 signatures had remarkable similarities. Hsa-miR-335-5p and BOQUEST_STEM_CELL_UP might be novel immunotherapy targets.
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Affiliation(s)
- Taohua Yue
- Division of General Surgery, Peking University First Hospital, Peking University, Beijing, China
| | - Shuai Zuo
- Division of General Surgery, Peking University First Hospital, Peking University, Beijing, China
| | - Jing Zhu
- Division of General Surgery, Peking University First Hospital, Peking University, Beijing, China
| | - Shihao Guo
- Division of General Surgery, Peking University First Hospital, Peking University, Beijing, China
| | - Zhihao Huang
- Division of General Surgery, Peking University First Hospital, Peking University, Beijing, China
| | - Jichang Li
- Division of General Surgery, Peking University First Hospital, Peking University, Beijing, China
| | - Xin Wang
- Division of General Surgery, Peking University First Hospital, Peking University, Beijing, China
| | - Yucun Liu
- Division of General Surgery, Peking University First Hospital, Peking University, Beijing, China
| | - Shanwen Chen
- Division of General Surgery, Peking University First Hospital, Peking University, Beijing, China
| | - Pengyuan Wang
- Division of General Surgery, Peking University First Hospital, Peking University, Beijing, China
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16
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Han W, Ye Y. A repository of microbial marker genes related to human health and diseases for host phenotype prediction using microbiome data. Pac Symp Biocomput 2019; 24:236-247. [PMID: 30864326 PMCID: PMC6417824] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
The microbiome research is going through an evolutionary transition from focusing on the characterization of reference microbiomes associated with different environments/hosts to the translational applications, including using microbiome for disease diagnosis, improving the effcacy of cancer treatments, and prevention of diseases (e.g., using probiotics). Microbial markers have been identified from microbiome data derived from cohorts of patients with different diseases, treatment responsiveness, etc, and often predictors based on these markers were built for predicting host phenotype given a microbiome dataset (e.g., to predict if a person has type 2 diabetes given his or her microbiome data). Unfortunately, these microbial markers and predictors are often not published so are not reusable by others. In this paper, we report the curation of a repository of microbial marker genes and predictors built from these markers for microbiome-based prediction of host phenotype, and a computational pipeline called Mi2P (from Microbiome to Phenotype) for using the repository. As an initial effort, we focus on microbial marker genes related to two diseases, type 2 diabetes and liver cirrhosis, and immunotherapy efficacy for two types of cancer, non-small-cell lung cancer (NSCLC) and renal cell carcinoma (RCC). We characterized the marker genes from metagenomic data using our recently developed subtractive assembly approach. We showed that predictors built from these microbial marker genes can provide fast and reasonably accurate prediction of host phenotype given microbiome data. As understanding and making use of microbiome data (our second genome) is becoming vital as we move forward in this age of precision health and precision medicine, we believe that such a repository will be useful for enabling translational applications of microbiome data.
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MESH Headings
- Carcinoma, Non-Small-Cell Lung/genetics
- Carcinoma, Non-Small-Cell Lung/microbiology
- Carcinoma, Non-Small-Cell Lung/therapy
- Carcinoma, Renal Cell/genetics
- Carcinoma, Renal Cell/microbiology
- Carcinoma, Renal Cell/therapy
- Computational Biology/methods
- Databases, Genetic
- Diabetes Mellitus, Type 2/genetics
- Diabetes Mellitus, Type 2/microbiology
- Genes, Microbial
- Genetic Markers
- Host Microbial Interactions/genetics
- Humans
- Immunotherapy
- Kidney Neoplasms/genetics
- Kidney Neoplasms/microbiology
- Kidney Neoplasms/therapy
- Liver Cirrhosis/genetics
- Liver Cirrhosis/microbiology
- Lung Neoplasms/genetics
- Lung Neoplasms/microbiology
- Lung Neoplasms/therapy
- Machine Learning
- Metagenomics/methods
- Metagenomics/statistics & numerical data
- Microbiota/genetics
- Phenotype
- Translational Research, Biomedical
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Affiliation(s)
- Wontack Han
- Computer Science Department, Indiana University, Bloomington, IN 47408, USA
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