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Wang C, Yuan L, Wu X, Wang Y, Tian H, Zhang G, Wan A, Xiong S, Wang C, Zhou Y, Ma D, Bao Y, Qu M, Jiang J, Zhang Y, Qi X. Taxane combined with lobaplatin or anthracycline for neoadjuvant chemotherapy of triple-negative breast cancer: a randomized, controlled, phase II study. BMC Med 2024; 22:252. [PMID: 38886794 PMCID: PMC11184884 DOI: 10.1186/s12916-024-03474-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 06/10/2024] [Indexed: 06/20/2024] Open
Abstract
BACKGROUND Previous studies have shown that the addition of platinum to neoadjuvant chemotherapy (NAC) improved outcomes for patients with triple-negative breast cancer (TNBC). However, no studies have assessed the efficacy and safety of the combination of taxane and lobaplatin. In this study, we conducted a randomized controlled phase II clinical study to compare the efficacy and safety of taxane combined with lobaplatin or anthracycline. METHODS We randomly allocated patients with stage I-III TNBC into Arm A and Arm B. Arm A received six cycles of taxane combined with lobaplatin (TL). Arm B received six cycles of taxane combined with anthracycline and cyclophosphamide (TEC) or eight cycles of anthracycline combined with cyclophosphamide and sequential use of taxane (EC-T). Both Arms underwent surgery after NAC. The primary endpoint was the pathologic complete response (pCR). Secondary endpoints were event-free survival (EFS), overall survival (OS), and safety. RESULTS A total of 103 patients (51 in Arm A and 52 in Arm B) were assessed. The pCR rate of Arm A was significantly higher than that of Arm B (41.2% vs. 21.2%, P = 0.028). Patients with positive lymph nodes and low neutrophil-to-lymphocyte ratio (NLR) benefited significantly more from Arm A than those with negative lymph nodes and high NLR (Pinteraction = 0.001, Pinteraction = 0.012, respectively). There was no significant difference in EFS (P = 0.895) or OS (P = 0.633) between the two arms. The prevalence of grade-3/4 anemia was higher in Arm A (P = 0.015), and the prevalence of grade-3/4 neutropenia was higher in Arm B (P = 0.044). CONCLUSIONS Neoadjuvant taxane plus lobaplatin has shown better efficacy than taxane plus anthracycline, and both regimens have similar toxicity profiles. This trial may provide a reference for a better combination strategy of immunotherapy in NAC for TNBC in the future.
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Affiliation(s)
- Cheng Wang
- Department of Breast and Thyroid Surgery, Southwest Hospital, Army Medical University, Chongqing, China
| | - Long Yuan
- Department of Breast and Thyroid Surgery, Southwest Hospital, Army Medical University, Chongqing, China
| | - Xiujuan Wu
- Department of Breast and Thyroid Surgery, Southwest Hospital, Army Medical University, Chongqing, China
| | - Yan Wang
- Department of Breast and Thyroid Surgery, Southwest Hospital, Army Medical University, Chongqing, China
| | - Hao Tian
- Department of Breast and Thyroid Surgery, Southwest Hospital, Army Medical University, Chongqing, China
| | - Guozhi Zhang
- Department of Breast and Thyroid Surgery, Southwest Hospital, Army Medical University, Chongqing, China
| | - Andi Wan
- Department of Breast and Thyroid Surgery, Southwest Hospital, Army Medical University, Chongqing, China
| | - Siyi Xiong
- Department of Breast and Thyroid Surgery, Southwest Hospital, Army Medical University, Chongqing, China
| | - Chengfang Wang
- Department of Breast and Thyroid Surgery, Southwest Hospital, Army Medical University, Chongqing, China
| | - Yuqin Zhou
- Department of Breast and Thyroid Surgery, Southwest Hospital, Army Medical University, Chongqing, China
| | - Dandan Ma
- Department of Breast and Thyroid Surgery, Southwest Hospital, Army Medical University, Chongqing, China
| | - Yangqiu Bao
- Department of Breast and Thyroid Surgery, Southwest Hospital, Army Medical University, Chongqing, China
| | - Man Qu
- Department of Breast and Thyroid Surgery, Southwest Hospital, Army Medical University, Chongqing, China
| | - Jun Jiang
- Department of Breast and Thyroid Surgery, Southwest Hospital, Army Medical University, Chongqing, China.
| | - Yi Zhang
- Department of Breast and Thyroid Surgery, Southwest Hospital, Army Medical University, Chongqing, China.
| | - Xiaowei Qi
- Department of Breast and Thyroid Surgery, Southwest Hospital, Army Medical University, Chongqing, China.
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Chen Q, Gao F, Wu J, Zhang K, Du T, Chen Y, Cai R, Zhao D, Deng R, Tang J. Comprehensive pan-cancer analysis of mitochondrial outer membrane permeabilisation activity reveals positive immunomodulation and assists in identifying potential therapeutic targets for immunotherapy resistance. Clin Transl Med 2024; 14:e1735. [PMID: 38899748 PMCID: PMC11187817 DOI: 10.1002/ctm2.1735] [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: 01/25/2024] [Revised: 05/20/2024] [Accepted: 05/24/2024] [Indexed: 06/21/2024] Open
Abstract
BACKGROUND Mitochondrial outer membrane permeabilisation (MOMP) plays a pivotal role in cellular death and immune activation. A deeper understanding of the impact of tumour MOMP on immunity will aid in guiding more effective immunotherapeutic strategies. METHODS A comprehensive pan-cancer dataset comprising 30 cancer-type transcriptomic cohorts, 20 immunotherapy transcriptomic cohorts and three immunotherapy scRNA-seq datasets was collected and analysed to determine the influence of tumour MOMP activity on clinical prognosis, immune infiltration and immunotherapy effectiveness. Leveraging 65 scRNA-Seq datasets, the MOMP signature (MOMP.Sig) was developed to accurately reflect tumour MOMP activity. The clinical predictive value of MOMP.Sig was explored through machine learning models. Integration of the MOMP.Sig model and a pan-cancer immunotherapy CRISPR screen further investigated potential targets to overcome immunotherapy resistance, which subsequently underwent clinical validation. RESULTS Our research revealed that elevated MOMP activity reduces mortality risk in cancer patients, drives the formation of an anti-tumour immune environment and enhances the response to immunotherapy. This finding emphasises the potential clinical application value of MOMP activity in immunotherapy. MOMP.Sig, offering a more precise indicator of tumour cell MOMP activity, demonstrated outstanding predictive efficacy in machine-learning models. Moreover, with the assistance of the MOMP.Sig model, FOXO1 was identified as a core modulator that promotes immune resistance. Finally, these findings were successfully validated in clinical immunotherapy cohorts of skin cutaneous melanoma and triple-negative breast cancer patients. CONCLUSIONS This study enhances our understanding of MOMP activity in immune modulation, providing valuable insights for more effective immunotherapeutic strategies across diverse tumours.
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Affiliation(s)
- Qingshan Chen
- State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for CancerSun Yat‐sen University Cancer CenterGuangzhouChina
- Department of Breast OncologySun Yat‐sen University Cancer CenterGuangzhouChina
| | - Fenglin Gao
- Department of Respiratory and Critical Care MedicineThe Second Affiliated Hospital of Nanjing Medical UniversityNanjingChina
| | - Junwan Wu
- State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for CancerSun Yat‐sen University Cancer CenterGuangzhouChina
- Biotherapy Center, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for CancerSun Yat‐sen University Cancer CenterGuangzhouChina
| | - Kaiming Zhang
- State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for CancerSun Yat‐sen University Cancer CenterGuangzhouChina
- Department of Breast OncologySun Yat‐sen University Cancer CenterGuangzhouChina
| | - Tian Du
- State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for CancerSun Yat‐sen University Cancer CenterGuangzhouChina
- Department of Breast OncologySun Yat‐sen University Cancer CenterGuangzhouChina
| | - Yuhong Chen
- State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for CancerSun Yat‐sen University Cancer CenterGuangzhouChina
| | - Ruizhao Cai
- State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for CancerSun Yat‐sen University Cancer CenterGuangzhouChina
- Department of Breast OncologySun Yat‐sen University Cancer CenterGuangzhouChina
| | - Dechang Zhao
- State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for CancerSun Yat‐sen University Cancer CenterGuangzhouChina
- Department of Breast OncologySun Yat‐sen University Cancer CenterGuangzhouChina
| | - Rong Deng
- State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for CancerSun Yat‐sen University Cancer CenterGuangzhouChina
| | - Jun Tang
- State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for CancerSun Yat‐sen University Cancer CenterGuangzhouChina
- Department of Breast OncologySun Yat‐sen University Cancer CenterGuangzhouChina
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3
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Yang S, Wang Z, Wang C, Li C, Wang B. Comparative Evaluation of Machine Learning Models for Subtyping Triple-Negative Breast Cancer: A Deep Learning-Based Multi-Omics Data Integration Approach. J Cancer 2024; 15:3943-3957. [PMID: 38911381 PMCID: PMC11190774 DOI: 10.7150/jca.93215] [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: 12/14/2023] [Accepted: 05/19/2024] [Indexed: 06/25/2024] Open
Abstract
Objective: Triple-negative breast cancer (TNBC) poses significant diagnostic challenges due to its aggressive nature. This research develops an innovative deep learning (DL) model based on the latest multi-omics data to enhance the accuracy of TNBC subtype and prognosis prediction. The study focuses on addressing the constraints of prior studies by showcasing a model with substantial advancements in data integration, statistical performance, and algorithmic optimization. Methods: Breast cancer-related molecular characteristic data, including mRNA, miRNA, gene mutations, DNA methylation, and magnetic resonance imaging (MRI) images, were retrieved from the TCGA and TCIA databases. This study not only compared single-omics with multi-omics machine learning models but also applied Bayesian optimization to innovatively optimize the neural network structure of a DL model for multi-omics data. Results: The DL model for multi-omics data significantly outperformed single-omics models in subtype prediction, achieving a 98.0% accuracy in cross-validation, 97.0% in the validation set, and 91.0% in an external test set. Additionally, the MRI radiomics model showed promising performance, especially with the training set; however, a decrease in performance during transfer testing underscored the advantages of the DL model for multi-omics data in data consistency and digital processing. Conclusion: Our multi-omics DL model presents notable innovations in statistical performance and transfer learning capability, bearing significant clinical relevance for TNBC classification and prognosis prediction. While the MRI radiomics model proved effective, it requires further optimization for cross-dataset application to enhance accuracy and consistency. Our findings offer new insights into improving TNBC classification and prognosis through multi-omics data and DL algorithms.
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Affiliation(s)
| | | | | | | | - Binjie Wang
- Department of Imaging, Huaihe Hospital of Henan University, Kaifeng 475000, P. R. China
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4
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Xi Y, Zheng K, Deng F, Liu Y, Sun H, Zheng Y, Tong HHY, Ji Y, Zhang Y, Chen W, Zhang Y, Zou X, Hao J. Themis: advancing precision oncology through comprehensive molecular subtyping and optimization. Brief Bioinform 2024; 25:bbae261. [PMID: 38833322 PMCID: PMC11149663 DOI: 10.1093/bib/bbae261] [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: 01/30/2024] [Revised: 04/30/2024] [Accepted: 05/21/2024] [Indexed: 06/06/2024] Open
Abstract
Recent advances in tumor molecular subtyping have revolutionized precision oncology, offering novel avenues for patient-specific treatment strategies. However, a comprehensive and independent comparison of these subtyping methodologies remains unexplored. This study introduces 'Themis' (Tumor HEterogeneity analysis on Molecular subtypIng System), an evaluation platform that encapsulates a few representative tumor molecular subtyping methods, including Stemness, Anoikis, Metabolism, and pathway-based classifications, utilizing 38 test datasets curated from The Cancer Genome Atlas (TCGA) and significant studies. Our self-designed quantitative analysis uncovers the relative strengths, limitations, and applicability of each method in different clinical contexts. Crucially, Themis serves as a vital tool in identifying the most appropriate subtyping methods for specific clinical scenarios. It also guides fine-tuning existing subtyping methods to achieve more accurate phenotype-associated results. To demonstrate the practical utility, we apply Themis to a breast cancer dataset, showcasing its efficacy in selecting the most suitable subtyping methods for personalized medicine in various clinical scenarios. This study bridges a crucial gap in cancer research and lays a foundation for future advancements in individualized cancer therapy and patient management.
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Affiliation(s)
- Yue Xi
- Department of Reproductive Medicine, Central Hospital Affiliated to Shandong First Medical University, Jinan, Shandong Province, 250013, China
- Institute of Clinical Science, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Kun Zheng
- Department of Urology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China
| | - Fulan Deng
- School of Materials Science and Engineering, Shanghai Institute of Technology, Shanghai 201418, China
| | - Yujun Liu
- Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, China
| | - Hourong Sun
- Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Department of Cardiovascular Surgery, Qilu Hospital of Shandong University, Jinan, Shandong, China
| | - Yingxia Zheng
- Department of Laboratory Medicine, Xin Hua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Henry H Y Tong
- Centre for Artificial Intelligence Driven Drug Discovery, Faculty of Applied Sciences, Macao Polytechnic University, Macao SAR, China
| | - Yuan Ji
- Molecular Pathology center, Dept. Pathology, Zhongshan Hospital, Fudan University
| | - Yingchun Zhang
- Department of Reproductive Medicine, Central Hospital Affiliated to Shandong First Medical University, Jinan, Shandong Province, 250013, China
| | - Wantao Chen
- Ninth People's Hospital, Shanghai Key Laboratory of Stomatology & Shanghai Research Institute of Stomatology, National Clinical Research Center of Stomatology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China
| | - Yiming Zhang
- Department of Reproductive Medicine, Central Hospital Affiliated to Shandong First Medical University, Jinan, Shandong Province, 250013, China
| | - Xin Zou
- National Engineering Center for Biochip at Shanghai, China
| | - Jie Hao
- Institute of Clinical Science, Zhongshan Hospital, Fudan University, Shanghai, China
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5
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Gao ZJ, Fang H, Sun S, Liu SQ, Fang Z, Liu Z, Li B, Wang P, Sun SR, Meng XY, Wu Q, Chen CS. Single-cell analyses reveal evolution mimicry during the specification of breast cancer subtype. Theranostics 2024; 14:3104-3126. [PMID: 38855191 PMCID: PMC11155410 DOI: 10.7150/thno.96163] [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: 03/11/2024] [Accepted: 05/12/2024] [Indexed: 06/11/2024] Open
Abstract
Background: The stem or progenitor antecedents confer developmental plasticity and unique cell identities to cancer cells via genetic and epigenetic programs. A comprehensive characterization and mapping of the cell-of-origin of breast cancer using novel technologies to unveil novel subtype-specific therapeutic targets is still absent. Methods: We integrated 195,144 high-quality cells from normal breast tissues and 406,501 high-quality cells from primary breast cancer samples to create a large-scale single-cell atlas of human normal and cancerous breasts. Potential heterogeneous origin of malignant cells was explored by contrasting cancer cells against reference normal epithelial cells. Multi-omics analyses and both in vitro and in vivo experiments were performed to screen and validate potential subtype-specific treatment targets. Novel biomarkers of identified immune and stromal cell subpopulations were validated by immunohistochemistry in our cohort. Results: Tumor stratification based on cancer cell-of-origin patterns correlated with clinical outcomes, genomic aberrations and diverse microenvironment constitutions. We found that the luminal progenitor (LP) subtype was robustly associated with poor prognosis, genomic instability and dysfunctional immune microenvironment. However, the LP subtype patients were sensitive to neoadjuvant chemotherapy (NAC), PARP inhibitors (PARPi) and immunotherapy. The LP subtype-specific target PLK1 was investigated by both in vitro and in vivo experiments. Besides, large-scale single-cell profiling of breast cancer inspired us to identify a range of clinically relevant immune and stromal cell subpopulations, including subsets of innate lymphoid cells (ILCs), macrophages and endothelial cells. Conclusion: The present single-cell study revealed the cellular repertoire and cell-of-origin patterns of breast cancer. Combining single-cell and bulk transcriptome data, we elucidated the evolution mimicry from normal to malignant subtypes and expounded the LP subtype with vital clinical implications. Novel immune and stromal cell subpopulations of breast cancer identified in our study could be potential therapeutic targets. Taken together, Our findings lay the foundation for the precise prognostic and therapeutic stratification of breast cancer.
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Affiliation(s)
- Zhi-Jie Gao
- Department of Breast and Thyroid Surgery, Renmin Hospital of Wuhan University, Wuhan, Hubei, China
| | - Huan Fang
- Kunming Institute of Zoology, Chinese Academy of Sciences. Kunming, Yunnan, China
- Kunming College of Life Sciences, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Si Sun
- Department of Clinical Laboratory, Renmin Hospital of Wuhan University, Wuhan, Hubei, China
| | - Si-Qing Liu
- Department of Breast and Thyroid Surgery, Renmin Hospital of Wuhan University, Wuhan, Hubei, China
| | - Zhou Fang
- Department of Breast and Thyroid Surgery, Renmin Hospital of Wuhan University, Wuhan, Hubei, China
| | - Zhou Liu
- Breast Tumor Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Bei Li
- Department of Pathology, Renmin Hospital of Wuhan University, Wuhan, Hubei. China
| | - Ping Wang
- Medical College, Anhui University of Science and Technology, Huainan, AnHui. China
- Tongji University Cancer Center, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Sheng-Rong Sun
- Department of Breast and Thyroid Surgery, Renmin Hospital of Wuhan University, Wuhan, Hubei, China
| | - Xiang-Yu Meng
- Health Science Center, Hubei Minzu University, Enshi, Hubei, China
| | - Qi Wu
- Tongji University Cancer Center, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Ce-Shi Chen
- Kunming Institute of Zoology, Chinese Academy of Sciences. Kunming, Yunnan, China
- Academy of Biomedical Engineering, Kunming Medical University, Kunming, Yunnan, China
- The Third Affiliated Hospital, Kunming Medical University, Kunming, Yunnan, China
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6
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Magbanua MJM, Li W, van ’t Veer LJ. Integrating Imaging and Circulating Tumor DNA Features for Predicting Patient Outcomes. Cancers (Basel) 2024; 16:1879. [PMID: 38791958 PMCID: PMC11120531 DOI: 10.3390/cancers16101879] [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: 04/15/2024] [Revised: 05/06/2024] [Accepted: 05/10/2024] [Indexed: 05/26/2024] Open
Abstract
Biomarkers for evaluating tumor response to therapy and estimating the risk of disease relapse represent tremendous areas of clinical need. To evaluate treatment efficacy, tumor response is routinely assessed using different imaging modalities like positron emission tomography/computed tomography or magnetic resonance imaging. More recently, the development of circulating tumor DNA detection assays has provided a minimally invasive approach to evaluate tumor response and prognosis through a blood test (liquid biopsy). Integrating imaging- and circulating tumor DNA-based biomarkers may lead to improvements in the prediction of patient outcomes. For this mini-review, we searched the scientific literature to find original articles that combined quantitative imaging and circulating tumor DNA biomarkers to build prediction models. Seven studies reported building prognostic models to predict distant recurrence-free, progression-free, or overall survival. Three discussed building models to predict treatment response using tumor volume, pathologic complete response, or objective response as endpoints. The limited number of articles and the modest cohort sizes reported in these studies attest to the infancy of this field of study. Nonetheless, these studies demonstrate the feasibility of developing multivariable response-predictive and prognostic models using regression and machine learning approaches. Larger studies are warranted to facilitate the building of highly accurate response-predictive and prognostic models that are generalizable to other datasets and clinical settings.
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Affiliation(s)
- Mark Jesus M. Magbanua
- Department of Laboratory Medicine, University of California San Francisco, San Francisco, CA 94115, USA;
| | - Wen Li
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94115, USA;
| | - Laura J. van ’t Veer
- Department of Laboratory Medicine, University of California San Francisco, San Francisco, CA 94115, USA;
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7
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Fang Z, Han YL, Gao ZJ, Yao F. Cancer-associated fibroblast-derived gene signature discriminates distinct prognoses by integrated single-cell and bulk RNA-seq analyses in breast cancer. Aging (Albany NY) 2024; 16:8279-8305. [PMID: 38728370 PMCID: PMC11132004 DOI: 10.18632/aging.205817] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Accepted: 04/10/2024] [Indexed: 05/12/2024]
Abstract
BACKGROUND Cancer-associated fibroblasts (CAFs) are one of the most predominant cellular subpopulations in the tumor stroma and play an integral role in cancer occurrence and progression. However, the prognostic role of CAFs in breast cancer remains poorly understood. METHODS We identified a number of CAF-related biomarkers in breast cancer by combining single-cell and bulk RNA-seq analyses. Based on univariate Cox regression as well as Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis, a novel CAF-associated prognostic model was developed. Breast cancer patients were grouped according to the median risk score and further analyzed for outcome, clinical characteristic, pathway activity, genomic feature, immune landscape, and drug sensitivity. RESULTS A total of 341 CAF-related biomarkers were identified from single-cell and bulk RNA-seq analyses. We eventually screened eight candidate prognostic genes, including CERCAM, EMP1, SDC1, PRKG1, XG, TNN, WLS, and PDLIM4, and constructed the novel CAF-related prognostic model. Grouped by the median risk score, high-risk patients showed a significantly worse prognosis and exhibited distinct pathway activities such as uncontrolled cell cycle progression, angiogenesis, and activation of glycolysis. In addition, the combined risk score and tumor mutation burden significantly improved the ability to predict patient prognosis. Importantly, patients in the high-risk group had a higher infiltration of M2 macrophages and a lower infiltration of CD8+ T cells and activated NK cells. Finally, we calculated the IC50 for a range of anticancer drugs and personalized the treatment regimen for each patient. CONCLUSION Integrating single-cell and bulk RNA-seq analyses, we identified a list of compositive CAF-associated biomarkers and developed a novel CAF-related prognostic model for breast cancer. This robust CAF-derived gene signature acts as an excellent predictor of patient outcomes and treatment responses in breast cancer.
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Affiliation(s)
- Zhou Fang
- Department of Breast and Thyroid Surgery, Renmin Hospital of Wuhan University, Wuhan, Hubei, P. R. China
| | - Yi-Ling Han
- Center for Reproductive Medicine, Renmin Hospital of Wuhan University, Wuhan, Hubei, P. R. China
| | - Zhi-Jie Gao
- Department of Breast and Thyroid Surgery, Renmin Hospital of Wuhan University, Wuhan, Hubei, P. R. China
| | - Feng Yao
- Department of Breast and Thyroid Surgery, Renmin Hospital of Wuhan University, Wuhan, Hubei, P. R. China
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8
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Wang K, Zerdes I, Johansson HJ, Sarhan D, Sun Y, Kanellis DC, Sifakis EG, Mezheyeuski A, Liu X, Loman N, Hedenfalk I, Bergh J, Bartek J, Hatschek T, Lehtiö J, Matikas A, Foukakis T. Longitudinal molecular profiling elucidates immunometabolism dynamics in breast cancer. Nat Commun 2024; 15:3837. [PMID: 38714665 PMCID: PMC11076527 DOI: 10.1038/s41467-024-47932-y] [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: 05/08/2023] [Accepted: 04/12/2024] [Indexed: 05/10/2024] Open
Abstract
Although metabolic reprogramming within tumor cells and tumor microenvironment (TME) is well described in breast cancer, little is known about how the interplay of immune state and cancer metabolism evolves during treatment. Here, we characterize the immunometabolic profiles of tumor tissue samples longitudinally collected from individuals with breast cancer before, during and after neoadjuvant chemotherapy (NAC) using proteomics, genomics and histopathology. We show that the pre-, on-treatment and dynamic changes of the immune state, tumor metabolic proteins and tumor cell gene expression profiling-based metabolic phenotype are associated with treatment response. Single-cell/nucleus RNA sequencing revealed distinct tumor and immune cell states in metabolism between cold and hot tumors. Potential drivers of NAC based on above analyses were validated in vitro. In summary, the study shows that the interaction of tumor-intrinsic metabolic states and TME is associated with treatment outcome, supporting the concept of targeting tumor metabolism for immunoregulation.
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Affiliation(s)
- Kang Wang
- Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden
| | - Ioannis Zerdes
- Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden
- Theme Cancer, Karolinska University Hospital and Karolinska Comprehensive Cancer Center, Stockholm, Sweden
| | - Henrik J Johansson
- Department of Oncology-Pathology, Karolinska Institutet, and Science for Life Laboratory, Stockholm, Sweden
| | - Dhifaf Sarhan
- Department of Laboratory Medicine, Division of Pathology, Karolinska Institutet, Stockholm, Sweden
| | - Yizhe Sun
- Department of Laboratory Medicine, Division of Pathology, Karolinska Institutet, Stockholm, Sweden
| | - Dimitris C Kanellis
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | | | - Artur Mezheyeuski
- Department of Immunology, Genetics and Pathology, Uppsala University, Rudbeck Laboratory, Uppsala, Sweden
- Molecular Oncology Group, Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Spain
| | - Xingrong Liu
- Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden
| | - Niklas Loman
- Department of Hematology, Oncology and Radiation Physics, Lund University Hospital, Lund, Sweden
- Division of Oncology, Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Ingrid Hedenfalk
- Division of Oncology, Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Jonas Bergh
- Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden
- Breast Center, Theme Cancer, Karolinska University Hospital and Karolinska Comprehensive Cancer Center, Stockholm, Sweden
| | - Jiri Bartek
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
- Danish Cancer Institute, DK-2100, Copenhagen, Denmark
| | - Thomas Hatschek
- Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden
- Breast Center, Theme Cancer, Karolinska University Hospital and Karolinska Comprehensive Cancer Center, Stockholm, Sweden
| | - Janne Lehtiö
- Department of Oncology-Pathology, Karolinska Institutet, and Science for Life Laboratory, Stockholm, Sweden
- Division of Pathology, Karolinska University Hospital and Karolinska Comprehensive Cancer Center, Stockholm, Sweden
| | - Alexios Matikas
- Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden
- Breast Center, Theme Cancer, Karolinska University Hospital and Karolinska Comprehensive Cancer Center, Stockholm, Sweden
| | - Theodoros Foukakis
- Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden.
- Breast Center, Theme Cancer, Karolinska University Hospital and Karolinska Comprehensive Cancer Center, Stockholm, Sweden.
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9
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Gedik ME, Saatci O, Oberholtzer N, Uner M, Akbulut Caliskan O, Cetin M, Aras M, Ibis K, Caliskan B, Banoglu E, Wiemann S, Üner A, Aksoy S, Mehrotra S, Sahin O. Targeting TACC3 Induces Immunogenic Cell Death and Enhances T-DM1 Response in HER2-Positive Breast Cancer. Cancer Res 2024; 84:1475-1490. [PMID: 38319231 PMCID: PMC11063689 DOI: 10.1158/0008-5472.can-23-2812] [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: 09/14/2023] [Revised: 12/27/2023] [Accepted: 01/25/2024] [Indexed: 02/07/2024]
Abstract
Trastuzumab emtansine (T-DM1) was the first and one of the most successful antibody-drug conjugates (ADC) approved for treating refractory HER2-positive breast cancer. Despite its initial clinical efficacy, resistance is unfortunately common, necessitating approaches to improve response. Here, we found that in sensitive cells, T-DM1 induced spindle assembly checkpoint (SAC)-dependent immunogenic cell death (ICD), an immune-priming form of cell death. The payload of T-DM1 mediated ICD by inducing eIF2α phosphorylation, surface exposure of calreticulin, ATP and HMGB1 release, and secretion of ICD-related cytokines, all of which were lost in resistance. Accordingly, ICD-related gene signatures in pretreatment samples correlated with clinical response to T-DM1-containing therapy, and increased infiltration of antitumor CD8+ T cells in posttreatment samples was correlated with better T-DM1 response. Transforming acidic coiled-coil containing 3 (TACC3) was overexpressed in T-DM1-resistant cells, and T-DM1 responsive patients had reduced TACC3 protein expression whereas nonresponders exhibited increased TACC3 expression during T-DM1 treatment. Notably, genetic or pharmacologic inhibition of TACC3 restored T-DM1-induced SAC activation and induction of ICD markers in vitro. Finally, TACC3 inhibition in vivo elicited ICD in a vaccination assay and potentiated the antitumor efficacy of T-DM1 by inducing dendritic cell maturation and enhancing intratumoral infiltration of cytotoxic T cells. Together, these results illustrate that ICD is a key mechanism of action of T-DM1 that is lost in resistance and that targeting TACC3 can restore T-DM1-mediated ICD and overcome resistance. SIGNIFICANCE Loss of induction of immunogenic cell death in response to T-DM1 leads to resistance that can be overcome by targeting TACC3, providing an attractive strategy to improve the efficacy of T-DM1.
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Affiliation(s)
- Mustafa Emre Gedik
- Department of Biochemistry and Molecular Biology, Hollings Cancer Center, Medical University of South Carolina, Charleston, South Carolina
| | - Ozge Saatci
- Department of Biochemistry and Molecular Biology, Hollings Cancer Center, Medical University of South Carolina, Charleston, South Carolina
- Department of Drug Discovery and Biomedical Sciences, University of South Carolina, Columbia, South Carolina
| | - Nathaniel Oberholtzer
- Department of Surgery, Hollings Cancer Center, Medical University of South Carolina, Charleston, South Carolina
| | - Meral Uner
- Department of Pathology, Faculty of Medicine, Hacettepe University, Ankara, Turkey
| | | | - Metin Cetin
- Department of Biochemistry and Molecular Biology, Hollings Cancer Center, Medical University of South Carolina, Charleston, South Carolina
- Department of Drug Discovery and Biomedical Sciences, University of South Carolina, Columbia, South Carolina
| | - Mertkaya Aras
- Department of Drug Discovery and Biomedical Sciences, University of South Carolina, Columbia, South Carolina
| | - Kubra Ibis
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Gazi University, Ankara, Turkey
| | - Burcu Caliskan
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Gazi University, Ankara, Turkey
| | - Erden Banoglu
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Gazi University, Ankara, Turkey
| | - Stefan Wiemann
- Division of Molecular Genome Analysis, German Cancer Research Center (DKFZ), INF580, Heidelberg, Germany
| | - Ayşegül Üner
- Department of Pathology, Faculty of Medicine, Hacettepe University, Ankara, Turkey
| | - Sercan Aksoy
- Department of Medical Oncology, Hacettepe University Cancer Institute, Ankara, Turkey
| | - Shikhar Mehrotra
- Department of Surgery, Hollings Cancer Center, Medical University of South Carolina, Charleston, South Carolina
| | - Ozgur Sahin
- Department of Biochemistry and Molecular Biology, Hollings Cancer Center, Medical University of South Carolina, Charleston, South Carolina
- Department of Drug Discovery and Biomedical Sciences, University of South Carolina, Columbia, South Carolina
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10
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An M, Mehta A, Min BH, Heo YJ, Wright SJ, Parikh M, Bi L, Lee H, Kim TJ, Lee SY, Moon J, Park RJ, Strickland MR, Park WY, Kang WK, Kim KM, Kim ST, Klempner SJ, Lee J. Early Immune Remodeling Steers Clinical Response to First-Line Chemoimmunotherapy in Advanced Gastric Cancer. Cancer Discov 2024; 14:766-785. [PMID: 38319303 PMCID: PMC11061611 DOI: 10.1158/2159-8290.cd-23-0857] [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: 08/01/2023] [Revised: 11/28/2023] [Accepted: 02/02/2024] [Indexed: 02/07/2024]
Abstract
Adding anti-programmed cell death protein 1 (anti-PD-1) to 5-fluorouracil (5-FU)/platinum improves survival in some advanced gastroesophageal adenocarcinomas (GEA). To understand the effects of chemotherapy and immunotherapy, we conducted a phase II first-line trial (n = 47) sequentially adding pembrolizumab to 5-FU/platinum in advanced GEA. Using serial biopsy of the primary tumor at baseline, after one cycle of 5-FU/platinum, and after the addition of pembrolizumab, we transcriptionally profiled 358,067 single cells to identify evolving multicellular tumor microenvironment (TME) networks. Chemotherapy induced early on-treatment multicellular hubs with tumor-reactive T-cell and M1-like macrophage interactions in slow progressors. Faster progression featured increased MUC5A and MSLN containing treatment resistance programs in tumor cells and M2-like macrophages with immunosuppressive stromal interactions. After pembrolizumab, we observed increased CD8 T-cell infiltration and development of an immunity hub involving tumor-reactive CXCL13 T-cell program and epithelial interferon-stimulated gene programs. Strategies to drive increases in antitumor immune hub formation could expand the portion of patients benefiting from anti-PD-1 approaches. SIGNIFICANCE The benefit of 5-FU/platinum with anti-PD-1 in first-line advanced gastric cancer is limited to patient subgroups. Using a trial with sequential anti-PD-1, we show coordinated induction of multicellular TME hubs informs the ability of anti-PD-1 to potentiate T cell-driven responses. Differential TME hub development highlights features that underlie clinical outcomes. This article is featured in Selected Articles from This Issue, p. 695.
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Affiliation(s)
- Minae An
- Experimental Therapeutics Development Center, Samsung Medical Center, Seoul, Korea
- Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Arnav Mehta
- The Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Department of Medicine, Division of Hematology-Oncology, Massachusetts General Hospital, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Byung Hoon Min
- Department of Medicine, Division of Gastroenterology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | | | - Samuel J. Wright
- The Broad Institute of MIT and Harvard, Cambridge, Massachusetts
| | - Milan Parikh
- The Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Department of Medicine, Division of Hematology-Oncology, Massachusetts General Hospital, Boston, Massachusetts
| | - Lynn Bi
- The Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Department of Medicine, Division of Hematology-Oncology, Massachusetts General Hospital, Boston, Massachusetts
| | - Hyuk Lee
- Department of Medicine, Division of Gastroenterology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Tae Jun Kim
- Department of Medicine, Division of Gastroenterology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Song-Yi Lee
- Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Jeonghyeon Moon
- Departments of Neurology and Immunology, Yale School of Medicine, New Haven, Connecticut
| | - Ryan J. Park
- The Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Division of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts
| | - Matthew R. Strickland
- Department of Medicine, Division of Hematology-Oncology, Massachusetts General Hospital, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | | | - Won Ki Kang
- Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Kyoung-Mee Kim
- Department of Pathology and Translational Genomics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Seung Tae Kim
- Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Samuel J. Klempner
- Department of Medicine, Division of Hematology-Oncology, Massachusetts General Hospital, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Jeeyun Lee
- Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
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11
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Mei J, Cai Y, Xu R, Li Q, Chu J, Luo Z, Sun Y, Shi Y, Xu J, Li D, Liang S, Jiang Y, Liu J, Qian Z, Zhou J, Wan M, Yang Y, Zhu Y, Zhang Y, Yin Y. Conserved immuno-collagenic subtypes predict response to immune checkpoint blockade. Cancer Commun (Lond) 2024; 44:554-575. [PMID: 38507505 PMCID: PMC11110954 DOI: 10.1002/cac2.12538] [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: 10/05/2023] [Revised: 03/06/2024] [Accepted: 03/10/2024] [Indexed: 03/22/2024] Open
Abstract
BACKGROUND Immune checkpoint blockade (ICB) has revolutionized the treatment of various cancer types. Despite significant preclinical advancements in understanding mechanisms, identifying the molecular basis and predictive biomarkers for clinical ICB responses remains challenging. Recent evidence, both preclinical and clinical, underscores the pivotal role of the extracellular matrix (ECM) in modulating immune cell infiltration and behaviors. This study aimed to create an innovative classifier that leverages ECM characteristics to enhance the effectiveness of ICB therapy. METHODS We analyzed transcriptomic collagen activity and immune signatures in 649 patients with cancer undergoing ICB therapy. This analysis led to the identification of three distinct immuno-collagenic subtypes predictive of ICB responses. We validated these subtypes using the transcriptome data from 9,363 cancer patients from The Cancer Genome Atlas (TCGA) dataset and 1,084 in-house samples. Additionally, novel therapeutic targets were identified based on these established immuno-collagenic subtypes. RESULTS Our categorization divided tumors into three subtypes: "soft & hot" (low collagen activity and high immune infiltration), "armored & cold" (high collagen activity and low immune infiltration), and "quiescent" (low collagen activity and immune infiltration). Notably, "soft & hot" tumors exhibited the most robust response to ICB therapy across various cancer types. Mechanistically, inhibiting collagen augmented the response to ICB in preclinical models. Furthermore, these subtypes demonstrated associations with immune activity and prognostic predictive potential across multiple cancer types. Additionally, an unbiased approach identified B7 homolog 3 (B7-H3), an available drug target, as strongly expressed in "armored & cold" tumors, relating with poor prognosis. CONCLUSION This study introduces histopathology-based universal immuno-collagenic subtypes capable of predicting ICB responses across diverse cancer types. These findings offer insights that could contribute to tailoring personalized immunotherapeutic strategies for patients with cancer.
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Affiliation(s)
- Jie Mei
- Department of OncologyThe First Affiliated Hospital of Nanjing Medical UniversityNanjingJiangsuP. R. China
- The First Clinical Medicine CollegeNanjing Medical UniversityNanjingJiangsuP. R. China
| | - Yun Cai
- Departments of GynecologyWuxi Maternal and Child Health Care Hospital, Wuxi Medical Center, Nanjing Medical UniversityWuxiJiangsuP. R. China
| | - Rui Xu
- Department of OncologyThe First Affiliated Hospital of Nanjing Medical UniversityNanjingJiangsuP. R. China
- The First Clinical Medicine CollegeNanjing Medical UniversityNanjingJiangsuP. R. China
| | - Qing Li
- Departments of OncologyXuzhou Central HospitalThe Xuzhou School of Clinical Medicine of Nanjing Medical UniversityXuzhouJiangsuP. R. China
| | - Jiahui Chu
- Department of OncologyThe First Affiliated Hospital of Nanjing Medical UniversityNanjingJiangsuP. R. China
- The First Clinical Medicine CollegeNanjing Medical UniversityNanjingJiangsuP. R. China
| | - Zhiwen Luo
- Department of Sports MedicineHuashan Hospital Affiliated to Fudan UniversityShanghaiP. R. China
| | - Yaying Sun
- Department of Sports MedicineShanghai General HospitalShanghai Jiao Tong University School of MedicineShanghaiP. R. China
| | - Yuxin Shi
- Departments of OncologyThe Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi Medical Center, Nanjing Medical UniversityWuxiJiangsuP. R. China
| | - Junying Xu
- Departments of OncologyThe Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi Medical Center, Nanjing Medical UniversityWuxiJiangsuP. R. China
| | - Di Li
- Shanghai Outdo Biotech Co., Ltd., National Engineering Center for BiochipShanghaiP. R. China
| | - Shuai Liang
- Departments of OncologyThe Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi Medical Center, Nanjing Medical UniversityWuxiJiangsuP. R. China
| | - Ying Jiang
- Departments of GynecologyWuxi Maternity and Child Health Care HospitalAffiliated Women's Hospital of Jiangnan UniversityWuxiJiangsuP. R. China
| | - Jiayu Liu
- Departments of GynecologyWuxi Maternity and Child Health Care HospitalAffiliated Women's Hospital of Jiangnan UniversityWuxiJiangsuP. R. China
| | - Zhiwen Qian
- Departments of GynecologyWuxi Maternal and Child Health Care Hospital, Wuxi Medical Center, Nanjing Medical UniversityWuxiJiangsuP. R. China
| | - Jiaofeng Zhou
- Department of PhysiologySchool of Basic Medical SciencesNanjing Medical UniversityNanjingJiangsuP. R. China
| | - Mengyun Wan
- Department of PhysiologySchool of Basic Medical SciencesNanjing Medical UniversityNanjingJiangsuP. R. China
| | - Yunlong Yang
- Department of Cellular and Genetic MedicineSchool of Basic Medical Sciences, Fudan UniversityShanghaiP. R. China
| | - Yichao Zhu
- Department of PhysiologySchool of Basic Medical SciencesNanjing Medical UniversityNanjingJiangsuP. R. China
| | - Yan Zhang
- Departments of GynecologyWuxi Maternal and Child Health Care Hospital, Wuxi Medical Center, Nanjing Medical UniversityWuxiJiangsuP. R. China
- Departments of GynecologyWuxi Maternity and Child Health Care HospitalAffiliated Women's Hospital of Jiangnan UniversityWuxiJiangsuP. R. China
| | - Yongmei Yin
- Department of OncologyThe First Affiliated Hospital of Nanjing Medical UniversityNanjingJiangsuP. R. China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Personalized Cancer Medicine, Nanjing Medical UniversityNanjingJiangsuP. R. China
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12
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van der Voort A, Louis FM, van Ramshorst MS, Kessels R, Mandjes IA, Kemper I, Agterof MJ, van der Steeg WA, Heijns JB, van Bekkum ML, Siemerink EJ, Kuijer PM, Scholten A, Wesseling J, Vrancken Peeters MJTFD, Mann RM, Sonke GS. MRI-guided optimisation of neoadjuvant chemotherapy duration in stage II-III HER2-positive breast cancer (TRAIN-3): a multicentre, single-arm, phase 2 study. Lancet Oncol 2024; 25:603-613. [PMID: 38588682 DOI: 10.1016/s1470-2045(24)00104-9] [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: 10/30/2023] [Revised: 02/12/2024] [Accepted: 02/16/2024] [Indexed: 04/10/2024]
Abstract
BACKGROUND Patients with stage II-III HER2-positive breast cancer have good outcomes with the combination of neoadjuvant chemotherapy and HER2-targeted agents. Although increasing the number of chemotherapy cycles improves pathological complete response rates, early complete responses are common. We investigated whether the duration of chemotherapy could be tailored on the basis of radiological response. METHODS TRAIN-3 is a single-arm, phase 2 study in 43 hospitals in the Netherlands. Patients with stage II-III HER2-positive breast cancer aged 18 years or older and a WHO performance status of 0 or 1 were enrolled. Patients received neoadjuvant chemotherapy consisting of paclitaxel (80 mg/m2 of body surface area on day 1 and 8 of each 21 day cycle), trastuzumab (loading dose on day 1 of cycle 1 of 8 mg/kg bodyweight, and then 6 mg/kg on day 1 on all subsequent cycles), and carboplatin (area under the concentration time curve 6 mg/mL per min on day 1 of each 3 week cycle) and pertuzumab (loading dose on day 1 of cycle 1 of 840 mg, and then 420 mg on day 1 of each subsequent cycle), all given intravenously. The response was monitored by breast MRI every three cycles and lymph node biopsy. Patients underwent surgery when a complete radiological response was observed or after a maximum of nine cycles of treatment. The primary endpoint was event-free survival at 3 years; however, follow-up for the primary endpoint is ongoing. Here, we present the radiological and pathological response rates (secondary endpoints) of all patients who underwent surgery and the toxicity data for all patients who received at least one cycle of treatment. Analyses were done in hormone receptor-positive and hormone receptor-negative patients separately. This trial is registered with ClinicalTrials.gov, number NCT03820063, recruitment is closed, and the follow-up for the primary endpoint is ongoing. FINDINGS Between April 1, 2019, and May 12, 2021, 235 patients with hormone receptor-negative cancer and 232 with hormone receptor-positive cancer were enrolled. Median follow-up was 26·4 months (IQR 22·9-32·9) for patients who were hormone receptor-negative and 31·6 months (25·6-35·7) for patients who were hormone receptor-positive. Overall, the median age was 51 years (IQR 43-59). In 233 patients with hormone receptor-negative tumours, radiological complete response was seen in 84 (36%; 95% CI 30-43) patients after one to three cycles, 140 (60%; 53-66) patients after one to six cycles, and 169 (73%; 66-78) patients after one to nine cycles. In 232 patients with hormone receptor-positive tumours, radiological complete response was seen in 68 (29%; 24-36) patients after one to three cycles, 118 (51%; 44-57) patients after one to six cycles, and 138 (59%; 53-66) patients after one to nine cycles. Among patients with a radiological complete response after one to nine cycles, a pathological complete response was seen in 147 (87%; 95% CI 81-92) of 169 patients with hormone receptor-negative tumours and was seen in 73 (53%; 44-61) of 138 patients with hormone receptor-positive tumours. The most common grade 3-4 adverse events were neutropenia (175 [37%] of 467), anaemia (75 [16%]), and diarrhoea (57 [12%]). No treatment-related deaths were reported. INTERPRETATION In our study, a third of patients with stage II-III hormone receptor-negative and HER2-positive breast cancer had a complete pathological response after only three cycles of neoadjuvant systemic therapy. A complete response on breast MRI could help identify early complete responders in patients who had hormone receptor negative tumours. An imaging-based strategy might limit the duration of chemotherapy in these patients, reduce side-effects, and maintain quality of life if confirmed by the analysis of the 3-year event-free survival primary endpoint. Better monitoring tools are needed for patients with hormone receptor-positive and HER2-positive breast cancer. FUNDING Roche Netherlands.
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Affiliation(s)
- Anna van der Voort
- Department of Medical Oncology, Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Fleur M Louis
- Department of Medical Oncology, Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Mette S van Ramshorst
- Department of Medical Oncology, Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Rob Kessels
- Department of Biometrics, Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Ingrid A Mandjes
- Department of Biometrics, Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Inge Kemper
- Department of Medical Oncology, Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Mariette J Agterof
- Department of Medical Oncology, St Antonius Hospital, Nieuwegein, Netherlands
| | | | - Joan B Heijns
- Department of Medical Oncology, Amphia, Breda, Netherlands
| | | | - Ester J Siemerink
- Department of Medical Oncology, Ziekenhuisgroep Twente, Hengelo, Netherlands
| | | | - Astrid Scholten
- Department of Radiation, Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Jelle Wesseling
- Division of Molecular Pathology and Department of Pathology, Netherlands Cancer Institute, Amsterdam, Netherlands; Department of Pathology, University Medical Centre, Leiden, Netherlands
| | - Marie-Jeanne T F D Vrancken Peeters
- Department of Surgery, Netherlands Cancer Institute, Amsterdam, Netherlands; Department of Surgery, Amsterdam University Medical Centre, Amsterdam, Netherlands
| | - Ritse M Mann
- Department of Radiology, Netherlands Cancer Institute, Amsterdam, Netherlands; Department of Medical Imaging, Radboud University Medical Center, Amsterdam, Netherlands
| | - Gabe S Sonke
- Department of Medical Oncology, Netherlands Cancer Institute, Amsterdam, Netherlands; Department of Medical Oncology, Amsterdam University Medical Centre, Amsterdam, Netherlands.
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13
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Masuda M, Nakagawa R, Kondo T. Harnessing the potential of reverse-phase protein array technology: Advancing precision oncology strategies. Cancer Sci 2024; 115:1378-1387. [PMID: 38409909 DOI: 10.1111/cas.16123] [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: 10/04/2023] [Revised: 02/04/2024] [Accepted: 02/13/2024] [Indexed: 02/28/2024] Open
Abstract
The last few decades have seen remarkable strides in the field of cancer therapy. Precision oncology coupled with comprehensive genomic profiling has become routine clinical practice for solid tumors, the advent of immune checkpoint inhibitors has transformed the landscape of oncology treatment, and the number of cancer drug approvals has continued to increase. Nevertheless, the application of genomics-driven precision oncology has thus far benefited only 10%-20% of cancer patients, leaving the majority without matched treatment options. This limitation underscores the need to explore alternative avenues with regard to selecting patients for targeted therapies. In contrast with genomics-based approaches, proteomics-based strategies offer a more precise understanding of the intricate biological processes driving cancer pathogenesis. This perspective underscores the importance of integrating complementary proteomic analyses into the next phase of precision oncology to establish robust biomarker-drug associations and surmount challenges related to drug resistance. One promising technology in this regard is the reverse-phase protein array (RPPA), which excels in quantitatively detecting protein modifications, even with limited amounts of sample. Its cost-effectiveness and rapid turnaround time further bolster its appeal for application in clinical settings. Here, we review the current status of genomics-driven precision oncology, as well as its limitations, with an emphasis on drug resistance. Subsequently, we explore the application of RPPA technology as a catalyst for advancing precision oncology. Through illustrative examples drawn from clinical trials, we demonstrate its utility for unraveling the molecular mechanisms underlying drug responses and resistance.
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Affiliation(s)
- Mari Masuda
- Department of Proteomics, National Cancer Center Research Institute, Tokyo, Japan
| | - Riko Nakagawa
- Department of Proteomics, National Cancer Center Research Institute, Tokyo, Japan
| | - Tadashi Kondo
- Division of Rare Cancer Research, National Cancer Center Research Institute, Tokyo, Japan
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14
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Papakyriacou I, Kutkaite G, Rúbies Bedós M, Nagarajan D, Alford LP, Menden MP, Mao Y. Loss of NEDD8 in cancer cells causes vulnerability to immune checkpoint blockade in triple-negative breast cancer. Nat Commun 2024; 15:3581. [PMID: 38678024 PMCID: PMC11055868 DOI: 10.1038/s41467-024-47987-x] [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: 03/22/2023] [Accepted: 04/17/2024] [Indexed: 04/29/2024] Open
Abstract
Immune checkpoint blockade therapy aims to activate the immune system to eliminate cancer cells. However, clinical benefits are only recorded in a subset of patients. Here, we leverage genome-wide CRISPR/Cas9 screens in a Tumor-Immune co-Culture System focusing on triple-negative breast cancer (TNBC). We reveal that NEDD8 loss in cancer cells causes a vulnerability to nivolumab (anti-PD-1). Genetic deletion of NEDD8 only delays cell division initially but cell proliferation is unaffected after recovery. Since the NEDD8 gene is commonly essential, we validate this observation with additional CRISPR screens and uncover enhanced immunogenicity in NEDD8 deficient cells using proteomics. In female immunocompetent mice, PD-1 blockade lacks efficacy against established EO771 breast cancer tumors. In contrast, we observe tumor regression mediated by CD8+ T cells against Nedd8 deficient EO771 tumors after PD-1 blockade. In essence, we provide evidence that NEDD8 is conditionally essential in TNBC and presents as a synergistic drug target for PD-1/L1 blockade therapy.
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Affiliation(s)
- Irineos Papakyriacou
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Ginte Kutkaite
- Computational Health Center, Helmholtz Munich, Neuherberg, Germany
- Department of Biology, Ludwig-Maximilians University Munich, Martinsried, Germany
| | - Marta Rúbies Bedós
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Divya Nagarajan
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Liam P Alford
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Michael P Menden
- Computational Health Center, Helmholtz Munich, Neuherberg, Germany
- Department of Biochemistry and Pharmacology, University of Melbourne, Parkville, VIC, Australia
| | - Yumeng Mao
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
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15
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Wescott EC, Sun X, Gonzalez-Ericsson P, Hanna A, Taylor BC, Sanchez V, Bronzini J, Opalenik SR, Sanders ME, Wulfkuhle J, Gallagher RI, Gomez H, Isaacs C, Bharti V, Wilson JT, Ballinger TJ, Santa-Maria CA, Shah PD, Dees EC, Lehmann BD, Abramson VG, Hirst GL, Brown Swigart L, van ˈt Veer LJ, Esserman LJ, Petricoin EF, Pietenpol JA, Balko JM. Epithelial Expressed B7-H4 Drives Differential Immunotherapy Response in Murine and Human Breast Cancer. CANCER RESEARCH COMMUNICATIONS 2024; 4:1120-1134. [PMID: 38687247 PMCID: PMC11041871 DOI: 10.1158/2767-9764.crc-23-0468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 01/30/2024] [Accepted: 03/29/2024] [Indexed: 05/02/2024]
Abstract
Combinations of immune checkpoint inhibitors (ICI, including anti-PD-1/PD-L1) and chemotherapy have been FDA approved for metastatic and early-stage triple-negative breast cancer (TNBC), but most patients do not benefit. B7-H4 is a B7 family ligand with proposed immunosuppressive functions being explored as a cancer immunotherapy target and may be associated with anti-PD-L1 resistance. However, little is known about its regulation and effect on immune cell function in breast cancers. We assessed murine and human breast cancer cells to identify regulation mechanisms of B7-H4 in vitro. We used an immunocompetent anti-PD-L1-sensitive orthotopic mammary cancer model and induced ectopic expression of B7-H4. We assessed therapy response and transcriptional changes at baseline and under treatment with anti-PD-L1. We observed B7-H4 was highly associated with epithelial cell status and transcription factors and found to be regulated by PI3K activity. EMT6 tumors with cell-surface B7-H4 expression were more resistant to immunotherapy. In addition, tumor-infiltrating immune cells had reduced immune activation signaling based on transcriptomic analysis. Paradoxically, in human breast cancer, B7-H4 expression was associated with survival benefit for patients with metastatic TNBC treated with carboplatin plus anti-PD-L1 and was associated with no change in response or survival for patients with early breast cancer receiving chemotherapy plus anti-PD-1. While B7-H4 induces tumor resistance to anti-PD-L1 in murine models, there are alternative mechanisms of signaling and function in human cancers. In addition, the strong correlation of B7-H4 to epithelial cell markers suggests a potential regulatory mechanism of B7-H4 independent of PD-L1. SIGNIFICANCE This translational study confirms the association of B7-H4 expression with a cold immune microenvironment in breast cancer and offers preclinical studies demonstrating a potential role for B7-H4 in suppressing response to checkpoint therapy. However, analysis of two clinical trials with checkpoint inhibitors in the early and metastatic settings argue against B7-H4 as being a mechanism of clinical resistance to checkpoints, with clear implications for its candidacy as a therapeutic target.
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Affiliation(s)
- Elizabeth C. Wescott
- Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Xiaopeng Sun
- Breast Cancer Research Program, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Paula Gonzalez-Ericsson
- Breast Cancer Research Program, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Ann Hanna
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Brandie C. Taylor
- Breast Cancer Research Program, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Violeta Sanchez
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Juliana Bronzini
- Department of Biological Sciences, Vanderbilt University, Nashville, Tennessee
| | - Susan R. Opalenik
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Melinda E. Sanders
- Breast Cancer Research Program, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Julia Wulfkuhle
- Center for Applied Proteomics and Molecular Medicine, George Mason University, Manassas, Virginia
| | - Rosa I. Gallagher
- Center for Applied Proteomics and Molecular Medicine, George Mason University, Manassas, Virginia
| | - Henry Gomez
- Department of Medical Oncology, Instituto Nacional de Enfermedades Neoplásicas, Lima, Perú
| | - Claudine Isaacs
- Division of Hematology-Oncology, Department of Medicine, Georgetown University, Washington, District of Columbia
| | - Vijaya Bharti
- Department of Chemical and Biomolecular Engineering, Vanderbilt University, Nashville, Tennessee
| | - John T. Wilson
- Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Chemical and Biomolecular Engineering, Vanderbilt University, Nashville, Tennessee
| | - Tarah J. Ballinger
- Division of Hematology and Oncology, Indiana University School of Medicine, Indianapolis, Indiana
| | | | - Payal D. Shah
- Abramson Cancer Center, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Elizabeth C. Dees
- Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill, North Carolina
| | - Brian D. Lehmann
- Breast Cancer Research Program, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Vandana G. Abramson
- Breast Cancer Research Program, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Gillian L. Hirst
- Department of Surgery, University of California San Francisco, San Francisco, California
| | - Lamorna Brown Swigart
- Department of Laboratory Medicine, University of California San Francisco, San Francisco, California
| | - Laura J. van ˈt Veer
- Department of Laboratory Medicine, University of California San Francisco, San Francisco, California
| | - Laura J. Esserman
- Department of Surgery, University of California San Francisco, San Francisco, California
| | - Emanuel F. Petricoin
- Center for Applied Proteomics and Molecular Medicine, George Mason University, Manassas, Virginia
| | - Jennifer A. Pietenpol
- Breast Cancer Research Program, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
- Johns Hopkins Sidney Kimmel Comprehensive Cancer Center, Baltimore, Maryland
- Department of Biochemistry, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Justin M. Balko
- Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, Tennessee
- Breast Cancer Research Program, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
- Cancer Biology Program, Vanderbilt University, Nashville, Tennessee
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16
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Xiong G, Shan J, Chong Q, Cui Y. Tertiary lymphoid structures associated with enhanced anti-tumor immunity and favorable prognosis in cervical squamous carcinoma. Aging (Albany NY) 2024; 16:6898-6920. [PMID: 38709170 PMCID: PMC11087108 DOI: 10.18632/aging.205733] [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: 11/01/2023] [Accepted: 02/13/2024] [Indexed: 05/07/2024]
Abstract
BACKGROUND Cervical squamous carcinoma (CESC) is the main subtype of cervical cancer. Unfortunately, there are presently no effective treatment options for advanced and recurrent CESC. Tertiary lymphoid structures (TLSs) are clusters of lymphoid cells that resemble secondary lymphoid organs; nevertheless, there is no summary of the clinical importance of TLS in CESC. METHODS A large set of transcriptomic and single-cell RNA-sequencing (scRNA-seq) datasets were used to analyze the pattern of TLS and its immuno-correlations in CESC. Additionally, an independent in-house cohort was collected to validate the correlation between TLS and TME features. RESULTS In the current study, we found that the presence of TLS could predict better prognosis in CESC and was correlated with the activation of immunological signaling pathways and enrichment of immune cell subpopulations. In addition, TLS was associated with reduced proliferation activity in tumor cells, indicating the negative correlation between TLS and the degree of malignancy. Last but not least, in two independent immunotherapy cohorts, tumors with the presence of TLS were more sensitive to immunotherapy. CONCLUSION Overall, TLS is related to an inflamed TME and identified immune-hot tumors, which could be an indicator for the identification of immunological features in CESC.
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Affiliation(s)
- Guohai Xiong
- Department of Gynaecology, Yancheng Third People’s Hospital, Yancheng 224008, China
- Department of Gynaecology, The Yancheng School of Clinical Medicine of Nanjing Medical University, Yancheng 224008, China
| | - Jinmei Shan
- Department of Gynaecology, Yancheng Third People’s Hospital, Yancheng 224008, China
- Department of Gynaecology, The Yancheng School of Clinical Medicine of Nanjing Medical University, Yancheng 224008, China
| | - Qingguo Chong
- Department of Gynaecology, Yancheng Third People’s Hospital, Yancheng 224008, China
- Department of Gynaecology, The Yancheng School of Clinical Medicine of Nanjing Medical University, Yancheng 224008, China
| | - Yueqing Cui
- Department of Gynaecology, Yancheng Third People’s Hospital, Yancheng 224008, China
- Department of Gynaecology, The Yancheng School of Clinical Medicine of Nanjing Medical University, Yancheng 224008, China
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17
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Zheng K, Hai Y, Chen H, Zhang Y, Hu X, Ni K. Tumor immune dysfunction and exclusion subtypes in bladder cancer and pan-cancer: a novel molecular subtyping strategy and immunotherapeutic prediction model. J Transl Med 2024; 22:365. [PMID: 38632658 PMCID: PMC11025237 DOI: 10.1186/s12967-024-05186-8] [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: 12/31/2023] [Accepted: 04/09/2024] [Indexed: 04/19/2024] Open
Abstract
BACKGROUND Molecular subtyping is expected to enable precise treatment. However, reliable subtyping strategies for clinical application remains defective and controversial. Given the significance of tumor immune dysfunction and exclusion (TIDE), we aimed to develop a novel TIDE-based subtyping strategy to guide personalized immunotherapy in the bladder cancer (BC). METHODS Transcriptome data of BC was used to evaluate the heterogeneity and the status of TIDE patterns. Subsequently, consensus clustering was applied to classify BC patients based on TIDE marker-genes. Patients' clinicopathological, molecular features and signaling pathways of the different TIDE subtypes were well characterized. We also utilize the deconvolution algorithms to analyze the tumor microenvironment, and further explore the sensitivity and mechanisms of each subtype to immunotherapy. Furthermore, BC patient clinical information, real-world BC samples and urine samples were collected for the validation of our findings, which were used for RNA-seq analysis, H&E staining, immunohistochemistry and immunofluorescence staining, and enzyme-linked immunosorbent assay. Finally, we also explored the conservation of our novel TIDE subtypes in pan-cancers. RESULTS We identified 69 TIDE biomarker genes and classified BC samples into three subtypes using consensus clustering. Subtype I showed the lowest TIDE status and malignancy with the best prognosis and highest sensitivity to immune checkpoint blockade (ICB) treatment, which was enriched of metabolic related signaling pathways. Subtype III represented the highest TIDE status and malignancy with the poorest prognosis and resistance to ICB treatment, resulting from its inhibitory immune microenvironment and T cell terminal exhaustion. Subtype II was in a transitional state with intermediate TIDE level, malignancy, and prognosis. We further confirmed the existence and characteristics of our novel TIDE subtypes using real-world BC samples and collected patient clinical data. This subtyping method was proved to be more efficient than previous known methods in identifying non-responders to immunotherapy. We also propose that combining our TIDE subtypes with known biomarkers can potentially improve the sensitivity and specificity of these biomarkers. Moreover, besides guiding ICB treatment, this classification approach can assist in selecting the frontline or recommended drugs. Finally, we confirmed that the TIDE subtypes are conserved across the pan-tumors. CONCLUSIONS Our novel TIDE-based subtyping method can serve as a powerful clinical tool for BC and pan-cancer patients, and potentially guiding personalized therapy decisions for selecting potential beneficiaries and excluding resistant patients of ICB therapy.
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Affiliation(s)
- Kun Zheng
- Department of Urology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China
| | - Youlong Hai
- Department of Urology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China
| | - Hongqi Chen
- Department of Urology, The Affiliated Jiangsu Shengze Hospital of Nanjing Medical University, Suzhou, 215200, Jiangsu, China
| | - Yukun Zhang
- Beijing University of Chinese Medicine East Hospital, Zaozhuang Hospital, Zaozhuang, 277000, Shandong, China
| | - Xiaoyong Hu
- Department of Urology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China.
| | - Kai Ni
- Department of Urology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China.
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18
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Li Y, Xu Y, Lin C, Jin X, Ma D, Shao Z. Calcification-associated molecular traits and therapeutic strategies in hormone receptor-positive HER2-negative breast cancer. Cancer Biol Med 2024; 21:j.issn.2095-3941.2023.0492. [PMID: 38605478 PMCID: PMC11131048 DOI: 10.20892/j.issn.2095-3941.2023.0492] [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: 12/15/2023] [Accepted: 02/19/2024] [Indexed: 04/13/2024] Open
Abstract
OBJECTIVE Mammographic calcifications are a common feature of breast cancer, but their molecular characteristics and treatment implications in hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-) breast cancer remain unclear. METHODS We retrospectively collected mammography records of an HR+/HER2- breast cancer cohort (n = 316) with matched clinicopathological, genomic, transcriptomic, and metabolomic data. On the basis of mammographic images, we grouped tumors by calcification status into calcification-negative tumors, tumors with probably benign calcifications, tumors with calcification of low-moderate suspicion for maligancy and tumors with calcification of high suspicion for maligancy. We then explored the molecular characteristics associated with each calcification status across multiple dimensions. RESULTS Among the different statuses, tumors with probably benign calcifications exhibited elevated hormone receptor immunohistochemical staining scores, estrogen receptor (ER) pathway activation, lipid metabolism, and sensitivity to endocrine therapy. Tumors with calcifications of high suspicion for malignancy had relatively larger tumor sizes, elevated lymph node metastasis incidence, Ki-67 staining scores, genomic instability, cell cycle pathway activation, and may benefit from cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitors. CONCLUSIONS Our research established links between tumor calcifications and molecular features, thus proposing potential precision treatment strategies for HR+/HER2- breast cancer.
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Affiliation(s)
- Yuwei Li
- Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai 200032, China
- Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Shanghai 200032, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Yuzheng Xu
- Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai 200032, China
- Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Shanghai 200032, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Caijin Lin
- Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai 200032, China
- Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Shanghai 200032, China
| | - Xi Jin
- Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai 200032, China
- Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Shanghai 200032, China
| | - Ding Ma
- Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai 200032, China
- Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Shanghai 200032, China
| | - Zhiming Shao
- Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai 200032, China
- Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Shanghai 200032, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
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19
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Abbasi AB, Wu V, Lang JE, Esserman LJ. Precision Oncology in Breast Cancer Surgery. Surg Oncol Clin N Am 2024; 33:293-310. [PMID: 38401911 DOI: 10.1016/j.soc.2023.12.011] [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] [Indexed: 02/26/2024]
Abstract
Outcomes for patients with breast cancer have improved over time due to increased screening and the availability of more effective therapies. It is important to recognize that breast cancer is a heterogeneous disease that requires treatment based on molecular characteristics. Early endpoints such as pathologic complete response correlate with event-free survival, allowing the opportunity to consider de-escalation of certain cancer treatments to avoid overtreatment. This article discusses clinical trials of tailoring treatment (eg, I-SPY2) and screening (eg, WISDOM) to individual patients based on their unique risk features.
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Affiliation(s)
- Ali Benjamin Abbasi
- Department of Surgery, San Francisco Breast Care Center, University of California, Box 1710, UCSF, San Francisco, CA 94143, USA
| | - Vincent Wu
- Department of Surgery, Cleveland Clinic Breast Services, 9500 Euclid Avenue, A80, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Julie E Lang
- Department of Surgery, Cleveland Clinic Breast Services, 9500 Euclid Avenue, A80, Cleveland Clinic, Cleveland, OH 44195, USA.
| | - Laura J Esserman
- Department of Surgery, San Francisco Breast Care Center, University of California, Box 1710, UCSF, San Francisco, CA 94143, USA
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20
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Shi R, Chang L, Shi L, Zhang Z, Zhang L, Li X. Development and validation of a prognostic model for cervical cancer by combination of machine learning and high-throughput sequencing. EUROPEAN JOURNAL OF SURGICAL ONCOLOGY 2024; 50:108241. [PMID: 38452717 DOI: 10.1016/j.ejso.2024.108241] [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: 09/02/2023] [Revised: 01/02/2024] [Accepted: 02/29/2024] [Indexed: 03/09/2024]
Abstract
BACKGROUND Cervical cancer holds the highest morbidity and mortality rates among female reproductive tract tumors. However, the curative outcomes for patients with persistent, recurrent, or metastatic cervical cancer remain unsatisfactory. There is a lack of comprehensive prognostic indicators for cervical cancer. This study aims to develop a model that evaluates the prognosis of cervical cancer in combination of high-throughput sequencing and various machine learning algorithms. METHODS In this study, we combined two single-cell RNA sequencing (scRNA-seq) projects and TCGA data for cervical cancer to obtain shared differentially expressed genes (DEGs). A LASSO regression and several learners were applied for signature feature selection. Six machine learning algorithms including Linear Discriminant Analysis, Naive Bayes, K Nearest Neighbors, Decision Tree, Random Forest, and eXtreme Gradient Boosting were utilized to construct a prognostic model for cervical cancer. External validation was conducted using the CGCI-HTMCP-CC dataset, and the accuracy of the model was assessed through ROC curve analysis. RESULTS The results demonstrated the successful construction of a prognostic model based on DEGs from bulk- and scRNA-seq data. Ten genes CXCL8, DLC1, GRN, MPLKIP, PRDX1, RUNX1, SNX3, TFRC, UBE2V2, and UQCRC1 were screened by feature selection and applied for model construction. Random Forest exhibited the best performance in predicting the risk of cervical cancer. Patients in the high-risk group presented worse overall survival compared to those in the low-risk group. CONCLUSION Conclusively, our model based on DEGs from bulk-seq and scRNA-seq data effectively evaluates the prognosis of cervical cancer and provides valuable insights for comprehensive clinical management.
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Affiliation(s)
- Rui Shi
- Department of Obstetrics and Gynecology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, 200120, China
| | - Linlin Chang
- Department of Obstetrics and Gynecology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, 200120, China
| | - Liya Shi
- Department of Reproductive Medicine Center, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, 200120, China
| | - Zhouxiang Zhang
- Department of Obstetrics and Gynecology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, 200120, China
| | - Limin Zhang
- Department of Obstetrics and Gynecology, The First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, China; Department of Obstetrics and Gynecology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350212, China.
| | - Xiaona Li
- Department of Obstetrics and Gynecology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, 200120, China.
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21
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Jiang YZ, Ma D, Jin X, Xiao Y, Yu Y, Shi J, Zhou YF, Fu T, Lin CJ, Dai LJ, Liu CL, Zhao S, Su GH, Hou W, Liu Y, Chen Q, Yang J, Zhang N, Zhang WJ, Liu W, Ge W, Yang WT, You C, Gu Y, Kaklamani V, Bertucci F, Verschraegen C, Daemen A, Shah NM, Wang T, Guo T, Shi L, Perou CM, Zheng Y, Huang W, Shao ZM. Integrated multiomic profiling of breast cancer in the Chinese population reveals patient stratification and therapeutic vulnerabilities. NATURE CANCER 2024; 5:673-690. [PMID: 38347143 DOI: 10.1038/s43018-024-00725-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Accepted: 01/04/2024] [Indexed: 04/30/2024]
Abstract
Molecular profiling guides precision treatment of breast cancer; however, Asian patients are underrepresented in publicly available large-scale studies. We established a comprehensive multiomics cohort of 773 Chinese patients with breast cancer and systematically analyzed their genomic, transcriptomic, proteomic, metabolomic, radiomic and digital pathology characteristics. Here we show that compared to breast cancers in white individuals, Asian individuals had more targetable AKT1 mutations. Integrated analysis revealed a higher proportion of HER2-enriched subtype and correspondingly more frequent ERBB2 amplification and higher HER2 protein abundance in the Chinese HR+HER2+ cohort, stressing anti-HER2 therapy for these individuals. Furthermore, comprehensive metabolomic and proteomic analyses revealed ferroptosis as a potential therapeutic target for basal-like tumors. The integration of clinical, transcriptomic, metabolomic, radiomic and pathological features allowed for efficient stratification of patients into groups with varying recurrence risks. Our study provides a public resource and new insights into the biology and ancestry specificity of breast cancer in the Asian population, offering potential for further precision treatment approaches.
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Affiliation(s)
- Yi-Zhou Jiang
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
| | - Ding Ma
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Xi Jin
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yi Xiao
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ying Yu
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute and Shanghai Cancer Center, Fudan University, Shanghai, China
| | - Jinxiu Shi
- Shanghai-MOST Key Laboratory of Health and Disease Genomics, Shanghai Institute for Biomedical and Pharmaceutical Technologies (SIBPT), Shanghai, China
| | - Yi-Fan Zhou
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Tong Fu
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Cai-Jin Lin
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Lei-Jie Dai
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Cheng-Lin Liu
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Shen Zhao
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Guan-Hua Su
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Wanwan Hou
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute and Shanghai Cancer Center, Fudan University, Shanghai, China
| | - Yaqing Liu
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute and Shanghai Cancer Center, Fudan University, Shanghai, China
| | - Qingwang Chen
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute and Shanghai Cancer Center, Fudan University, Shanghai, China
| | - Jingcheng Yang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute and Shanghai Cancer Center, Fudan University, Shanghai, China
- Greater Bay Area Institute of Precision Medicine, Guangzhou, China
| | - Naixin Zhang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute and Shanghai Cancer Center, Fudan University, Shanghai, China
| | - Wen-Juan Zhang
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Wei Liu
- Westlake Omics (Hangzhou) Biotechnology, Hangzhou, China
| | - Weigang Ge
- Westlake Omics (Hangzhou) Biotechnology, Hangzhou, China
| | - Wen-Tao Yang
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Chao You
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Yajia Gu
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Virginia Kaklamani
- Division Haematology/Oncology, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - François Bertucci
- Predictive Oncology Laboratory and Department of Medical Oncology, CRCM, Institut Paoli-Calmettes, Inserm UMR1068, CNRS UMR7258, Aix-Marseille Université, Marseille, France
| | | | - Anneleen Daemen
- Department of Bioinformatics and Computational Biology, Genentech, South San Francisco, CA, USA
| | - Nakul M Shah
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO, USA
| | - Ting Wang
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO, USA
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Tiannan Guo
- Westlake Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China
- School of Medicine, School of Life Sciences, Westlake University, Hangzhou, China
- Research Center for Industries of the Future, Westlake University, Hangzhou, China
| | - Leming Shi
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute and Shanghai Cancer Center, Fudan University, Shanghai, China
- International Human Phenome Institutes (Shanghai), Shanghai, China
| | - Charles M Perou
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Yuanting Zheng
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute and Shanghai Cancer Center, Fudan University, Shanghai, China.
| | - Wei Huang
- Shanghai-MOST Key Laboratory of Health and Disease Genomics, Shanghai Institute for Biomedical and Pharmaceutical Technologies (SIBPT), Shanghai, China.
| | - Zhi-Ming Shao
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
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22
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Ma T, Wang J. GraphPath: a graph attention model for molecular stratification with interpretability based on the pathway-pathway interaction network. Bioinformatics 2024; 40:btae165. [PMID: 38530778 PMCID: PMC11007237 DOI: 10.1093/bioinformatics/btae165] [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: 09/22/2023] [Revised: 02/22/2024] [Accepted: 03/22/2024] [Indexed: 03/28/2024] Open
Abstract
MOTIVATION Studying the molecular heterogeneity of cancer is essential for achieving personalized therapy. At the same time, understanding the biological processes that drive cancer development can lead to the identification of valuable therapeutic targets. Therefore, achieving accurate and interpretable clinical predictions requires paramount attention to thoroughly characterizing patients at both the molecular and biological pathway levels. RESULTS Here, we present GraphPath, a biological knowledge-driven graph neural network with multi-head self-attention mechanism that implements the pathway-pathway interaction network. We train GraphPath to classify the cancer status of patients with prostate cancer based on their multi-omics profiling. Experiment results show that our method outperforms P-NET and other baseline methods. Besides, two external cohorts are used to validate that the model can be generalized to unseen samples with adequate predictive performance. We reduce the dimensionality of latent pathway embeddings and visualize corresponding classes to further demonstrate the optimal performance of the model. Additionally, since GraphPath's predictions are interpretable, we identify target cancer-associated pathways that significantly contribute to the model's predictions. Such a robust and interpretable model has the potential to greatly enhance our understanding of cancer's biological mechanisms and accelerate the development of targeted therapies. AVAILABILITY AND IMPLEMENTATION https://github.com/amazingma/GraphPath.
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Affiliation(s)
- Teng Ma
- Hunan Provincial Key Lab on Bioinformatics, School of Computer Science and Engineering, Central South University, Changsha 41083, Hunan, China
| | - Jianxin Wang
- Hunan Provincial Key Lab on Bioinformatics, School of Computer Science and Engineering, Central South University, Changsha 41083, Hunan, China
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23
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Tzetzo SL, Kramer ED, Mohammadpour H, Kim M, Rosario SR, Yu H, Dolan MR, Oturkar CC, Morreale BG, Bogner PN, Stablewski AB, Benavides FJ, Brackett CM, Ebos JM, Das GM, Opyrchal M, Nemeth MJ, Evans SS, Abrams SI. Downregulation of IRF8 in alveolar macrophages by G-CSF promotes metastatic tumor progression. iScience 2024; 27:109187. [PMID: 38420590 PMCID: PMC10901102 DOI: 10.1016/j.isci.2024.109187] [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: 01/30/2023] [Revised: 01/16/2024] [Accepted: 02/06/2024] [Indexed: 03/02/2024] Open
Abstract
Tissue-resident macrophages (TRMs) are abundant immune cells within pre-metastatic sites, yet their functional contributions to metastasis remain incompletely understood. Here, we show that alveolar macrophages (AMs), the main TRMs of the lung, are susceptible to downregulation of the immune stimulatory transcription factor IRF8, impairing anti-metastatic activity in models of metastatic breast cancer. G-CSF is a key tumor-associated factor (TAF) that acts upon AMs to reduce IRF8 levels and facilitate metastasis. Translational relevance of IRF8 downregulation was observed among macrophage precursors in breast cancer and a CD68hiIRF8loG-CSFhi gene signature suggests poorer prognosis in triple-negative breast cancer (TNBC), a G-CSF-expressing subtype. Our data highlight the underappreciated, pro-metastatic roles of AMs in response to G-CSF and identify the contribution of IRF8-deficient AMs to metastatic burden. AMs are an attractive target of local neoadjuvant G-CSF blockade to recover anti-metastatic activity.
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Affiliation(s)
- Stephanie L. Tzetzo
- Department of Immunology, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14263, USA
| | - Elliot D. Kramer
- Department of Immunology, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14263, USA
| | - Hemn Mohammadpour
- Department of Cell Stress Biology, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14263, USA
| | - Minhyung Kim
- Department of Surgical Oncology, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14263, USA
| | - Spencer R. Rosario
- Department of Biostatistics and Bioinformatics, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14263, USA
| | - Han Yu
- Department of Biostatistics and Bioinformatics, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14263, USA
| | - Melissa R. Dolan
- Department of Pharmacology and Therapeutics, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14263, USA
| | - Chetan C. Oturkar
- Department of Pharmacology and Therapeutics, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14263, USA
| | - Brian G. Morreale
- Department of Immunology, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14263, USA
| | - Paul N. Bogner
- Department of Pathology, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14263, USA
| | - Aimee B. Stablewski
- Department of Molecular and Cellular Biology, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14263, USA
| | - Fernando J. Benavides
- Department of Epigenetics and Molecular Carcinogenesis, MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Craig M. Brackett
- Department of Cell Stress Biology, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14263, USA
| | - John M.L. Ebos
- Department of Cancer Genetics and Genomics, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14263, USA
- Department of Medicine, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14263, USA
| | - Gokul M. Das
- Department of Pharmacology and Therapeutics, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14263, USA
| | - Mateusz Opyrchal
- Department of Medicine, Indiana University, Indianapolis, IN 46202, USA
| | - Michael J. Nemeth
- Department of Immunology, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14263, USA
| | - Sharon S. Evans
- Department of Immunology, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14263, USA
| | - Scott I. Abrams
- Department of Immunology, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14263, USA
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Duan XP, Qin BD, Jiao XD, Liu K, Wang Z, Zang YS. New clinical trial design in precision medicine: discovery, development and direction. Signal Transduct Target Ther 2024; 9:57. [PMID: 38438349 PMCID: PMC10912713 DOI: 10.1038/s41392-024-01760-0] [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: 11/30/2023] [Revised: 01/25/2024] [Accepted: 01/29/2024] [Indexed: 03/06/2024] Open
Abstract
In the era of precision medicine, it has been increasingly recognized that individuals with a certain disease are complex and different from each other. Due to the underestimation of the significant heterogeneity across participants in traditional "one-size-fits-all" trials, patient-centered trials that could provide optimal therapy customization to individuals with specific biomarkers were developed including the basket, umbrella, and platform trial designs under the master protocol framework. In recent years, the successive FDA approval of indications based on biomarker-guided master protocol designs has demonstrated that these new clinical trials are ushering in tremendous opportunities. Despite the rapid increase in the number of basket, umbrella, and platform trials, the current clinical and research understanding of these new trial designs, as compared with traditional trial designs, remains limited. The majority of the research focuses on methodologies, and there is a lack of in-depth insight concerning the underlying biological logic of these new clinical trial designs. Therefore, we provide this comprehensive review of the discovery and development of basket, umbrella, and platform trials and their underlying logic from the perspective of precision medicine. Meanwhile, we discuss future directions on the potential development of these new clinical design in view of the "Precision Pro", "Dynamic Precision", and "Intelligent Precision". This review would assist trial-related researchers to enhance the innovation and feasibility of clinical trial designs by expounding the underlying logic, which be essential to accelerate the progression of precision medicine.
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Affiliation(s)
- Xiao-Peng Duan
- Department of Medical Oncology, Changzheng Hospital, Naval Medical University, Shanghai, China
| | - Bao-Dong Qin
- Department of Medical Oncology, Changzheng Hospital, Naval Medical University, Shanghai, China
| | - Xiao-Dong Jiao
- Department of Medical Oncology, Changzheng Hospital, Naval Medical University, Shanghai, China
| | - Ke Liu
- Department of Medical Oncology, Changzheng Hospital, Naval Medical University, Shanghai, China
| | - Zhan Wang
- Department of Medical Oncology, Changzheng Hospital, Naval Medical University, Shanghai, China
| | - Yuan-Sheng Zang
- Department of Medical Oncology, Changzheng Hospital, Naval Medical University, Shanghai, China.
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Lee S, Kang BH, Lee HB, Jang BS, Han W, Kim IA. B-Cell-Mediated Immunity Predicts Survival of Patients With Estrogen Receptor-Positive Breast Cancer. JCO Precis Oncol 2024; 8:e2300263. [PMID: 38452311 DOI: 10.1200/po.23.00263] [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: 05/25/2023] [Revised: 12/21/2023] [Accepted: 01/11/2024] [Indexed: 03/09/2024] Open
Abstract
PURPOSE The estrogen receptor-positive (ER+) breast cancer (BC), which constitutes the majority of BC cases, exhibits highly heterogeneous clinical behavior. To aid precision treatments, we aimed to find molecular subtypes of ER+ BC representing the tumor microenvironment and prognosis. METHODS We analyzed RNA-seq data of 113 patients with BC and classified them according to the PAM50 intrinsic subtypes using gene expression profiles. Among them, we further focused on 44 patients with luminal-type (ER+) BC for subclassification. The Cancer Genome Atlas (TCGA) data of patients with BC were used as a validation data set to verify the new classification. We estimated the immune cell composition using CIBERSORT and further analyzed its association with clinical or molecular parameters. RESULTS Principal component analysis clearly divided the patients into two subgroups separately from the luminal A and B classification. The top differentially expressed genes between the subgroups were distinctly characterized by immunoglobulin and B-cell-related genes. We could also cluster a separate cohort of patients with luminal-type BC from TCGA into two subgroups on the basis of the expression of a B-cell-specific gene set, and patients who were predicted to have high B-cell immune activity had better prognoses than other patients. CONCLUSION Our transcriptomic approach emphasize a molecular phenotype of B-cell immunity in ER+ BC that may help to predict disease prognosis. Although further researches are required, B-cell immunity for patients with ER+ BC may be helpful for identifying patients who are good responders to chemotherapy or immunotherapy.
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Affiliation(s)
- Seungbok Lee
- Department of Genomic Medicine, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Republic of Korea
| | - Byung-Hee Kang
- Department of Radiation Oncology, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
- Department of Radiation Oncology, Ewha Womans University Seoul Hospital, Seoul, Republic of Korea
| | - Han-Byoel Lee
- Department of Surgery, Seoul National University College of Medicine, Seoul, Republic of Korea
- Biomedical Research Institute, Seoul National University Hospital, Seoul, Republic of Korea
- Cancer Research Institute, Seoul National University, Seoul, Republic of Korea
| | - Bum-Sup Jang
- Department of Radiation Oncology, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Republic of Korea
| | - Wonshik Han
- Department of Surgery, Seoul National University College of Medicine, Seoul, Republic of Korea
- Biomedical Research Institute, Seoul National University Hospital, Seoul, Republic of Korea
- Cancer Research Institute, Seoul National University, Seoul, Republic of Korea
| | - In Ah Kim
- Department of Radiation Oncology, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
- Department of Radiation Oncology and Cancer Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea
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Wu WQ, Zou CD, Wu D, Fu HX, Wang XD, Yao F. Construction of molecular subtype model of osteosarcoma based on endoplasmic reticulum stress and tumor metastasis-related genes. Heliyon 2024; 10:e25691. [PMID: 38371978 PMCID: PMC10873750 DOI: 10.1016/j.heliyon.2024.e25691] [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: 02/08/2023] [Revised: 01/24/2024] [Accepted: 01/31/2024] [Indexed: 02/20/2024] Open
Abstract
Introduction Osteosarcoma, the prevailing primary bone malignancy among children and adolescents, is frequently associated with treatment failure primarily due to its pronounced metastatic nature. Methods This study aimed to establish potential associations between hub genes and subtypes for the treatment of metastatic osteosarcoma. Differentially expressed genes were extracted from patients diagnosed with metastatic osteosarcoma and a control group of non-metastatic patients, using the publicly available gene expression profile (GSE21257). The intersection of these gene sets was determined by focusing on endoplasmic reticulum (ER) stress-related genes sourced from the GeneCards database. We conducted various analytical techniques, including functional and pathway enrichment analysis, WGCNA analysis, protein-protein interaction (PPI) network construction, and assessment of immune cell infiltration, using the intersecting genes. Through this analysis, we identified potential hub genes. Results Osteosarcoma subtype models were developed using molecular consensus clustering analysis, followed by an examination of the associations between each subtype and hub genes. A total of 138 potential differentially expressed genes related to endoplasmic reticulum (ER) stress were identified. These genes were further investigated using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) pathways. Additionally, the PPI interaction network revealed 38 interaction relationships among the top ten hub genes. The findings of the analysis revealed a strong correlation between the extent of immune cell infiltration and both osteosarcoma metastasis and the expression of hub genes. Notably, the differential expression of the top ten hub genes was observed in osteosarcoma clusters 1 and 4, signifying their significant association with the disease. Conclusion The identification of ten key genes linked to osteosarcoma metastasis and endoplasmic reticulum stress bears potential clinical significance. Additionally, exploring the molecular subtype of osteosarcoma has the capacity to guide clinical treatment decisions, necessitating further investigations and subsequent clinical validations.
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Affiliation(s)
- Wang-Qiang Wu
- Department of Orthopaedics, Children's Hospital of Soochow University, 92# Zhongnan Street, Suzhou, Jiangsu 215025, China
| | - Cheng-Da Zou
- Children's Hospital of Soochow University, Children's Hospital of Wujiang District, China
| | - Di Wu
- Department of Orthopaedics, Children's Hospital of Soochow University, 92# Zhongnan Street, Suzhou, Jiangsu 215025, China
| | - Hou-Xin Fu
- Department of Orthopaedics, Children's Hospital of Soochow University, 92# Zhongnan Street, Suzhou, Jiangsu 215025, China
| | - Xiao-Dong Wang
- Department of Orthopaedics, Children's Hospital of Soochow University, 92# Zhongnan Street, Suzhou, Jiangsu 215025, China
| | - Feng Yao
- Department of Orthopaedics, Children's Hospital of Soochow University, 92# Zhongnan Street, Suzhou, Jiangsu 215025, China
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Okines A, Turner N. Developing therapies for triple-negative breast cancer subtypes. Lancet Oncol 2024; 25:149-151. [PMID: 38211607 DOI: 10.1016/s1470-2045(23)00639-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2023] [Accepted: 12/06/2023] [Indexed: 01/13/2024]
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Ribeiro JM, Dixon-Douglas J, André F. Moving to ultra-short therapy to cure patients with cancer: a solution for sustainable cancer care. ESMO Open 2024; 9:102238. [PMID: 38350339 PMCID: PMC10875333 DOI: 10.1016/j.esmoop.2024.102238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 12/27/2023] [Accepted: 01/03/2024] [Indexed: 02/15/2024] Open
Affiliation(s)
- J M Ribeiro
- Département de Médecine Oncologique, Gustave Roussy, Villejuif; Gustave Roussy, INSERM U981, PRISM Center, Villejuif, France.
| | - J Dixon-Douglas
- Sir Peter MacCallum Department of Medical Oncology, University of Melbourne, Melbourne, Australia
| | - F André
- Département de Médecine Oncologique, Gustave Roussy, Villejuif; Gustave Roussy, INSERM U981, PRISM Center, Villejuif, France
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Cantini L, Trapani D, Guidi L, Boscolo Bielo L, Scafetta R, Koziej M, Vidal L, Saini KS, Curigliano G. Neoadjuvant therapy in hormone Receptor-Positive/HER2-Negative breast cancer. Cancer Treat Rev 2024; 123:102669. [PMID: 38141462 DOI: 10.1016/j.ctrv.2023.102669] [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: 09/20/2023] [Revised: 12/05/2023] [Accepted: 12/07/2023] [Indexed: 12/25/2023]
Abstract
Neoadjuvant therapy is commonly used in patients with locally advanced or inoperable breast cancer (BC). Neoadjuvant chemotherapy (NACT) represents an established treatment modality able to downstage tumours, facilitate breast-conserving surgery, yet also achieve considerable pathologic complete response (pCR) rates in HER2-positive and triple-negative BC. For patients with HR+/HER2- BC, the choice between NACT and neoadjuvant endocrine therapy (NET) is still based on clinical and pathological features and not guided by biomarkers of defined clinical utility, differently from the adjuvant setting where gene-expression signatures have been widely adopted to drive decision-making. In this review, we summarize the evidence supporting the choice of NACT vs NET in HR+/HER2- BC, discussing the issues surrounding clinical trial design and proper selection of patients for every treatment. It is time to question the binary paradigm of responder vs non-responders as well as the "one size fits all" approach in luminal BC, supporting the utilization of continuous endpoints and the adoption of tissue and plasma-based biomarkers at multiple timepoints. This will eventually unleash the full potential of neoadjuvant therapy which is to modulate patient treatment based on treatment sensitivity and surgical outcomes. We also reviewed the current landscape of neoadjuvant studies for HR+/HER2- BC, focusing on antibody-drug conjugates (ADCs) and immunotherapy combinations. Finally, we proposed a roadmap for future neoadjuvant approaches in HR+/HER2- BC, which should be based on a staggered biomarker-driven treatment selection aiming at impacting long-term relevant endpoints.
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Affiliation(s)
| | - Dario Trapani
- Department of Oncology and Hemato-Oncology, University of Milan, 20122 Milan, Italy; Division of New Drugs and Early Drug Development, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
| | - Lorenzo Guidi
- Department of Oncology and Hemato-Oncology, University of Milan, 20122 Milan, Italy; Division of New Drugs and Early Drug Development, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
| | - Luca Boscolo Bielo
- Department of Oncology and Hemato-Oncology, University of Milan, 20122 Milan, Italy; Division of New Drugs and Early Drug Development, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
| | - Roberta Scafetta
- Department of Oncology and Hemato-Oncology, University of Milan, 20122 Milan, Italy; Division of New Drugs and Early Drug Development, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy; Department of medical oncology, Campus Bio-Medico, University of Rome, Rome, Italy
| | | | | | | | - Giuseppe Curigliano
- Department of Oncology and Hemato-Oncology, University of Milan, 20122 Milan, Italy; Division of New Drugs and Early Drug Development, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy.
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30
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Fan L, Wang ZH, Ma LX, Wu SY, Wu J, Yu KD, Sui XY, Xu Y, Liu XY, Chen L, Zhang WJ, Jin X, Xiao Q, Shui RH, Xiao Y, Wang H, Yang YS, Huang XY, Cao AY, Li JJ, Di GH, Liu GY, Yang WT, Hu X, Xia Y, Liang QN, Jiang YZ, Shao ZM. Optimising first-line subtyping-based therapy in triple-negative breast cancer (FUTURE-SUPER): a multi-cohort, randomised, phase 2 trial. Lancet Oncol 2024; 25:184-197. [PMID: 38211606 DOI: 10.1016/s1470-2045(23)00579-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 11/03/2023] [Accepted: 11/06/2023] [Indexed: 01/13/2024]
Abstract
BACKGROUND Triple-negative breast cancers display heterogeneity in molecular drivers and immune traits. We previously classified triple-negative breast cancers into four subtypes: luminal androgen receptor (LAR), immunomodulatory, basal-like immune-suppressed (BLIS), and mesenchymal-like (MES). Here, we aimed to evaluate the efficacy and safety of subtyping-based therapy in the first-line treatment of triple-negative breast cancer. METHODS FUTURE-SUPER is an ongoing, open-label, randomised, controlled phase 2 trial being conducted at Fudan University Shanghai Cancer Center (FUSCC), Shanghai, China. Eligible participants were females aged 18-70 years, with an Eastern Cooperative Oncology Group performance status of 0-1, and histologically confirmed, untreated metastatic or recurrent triple-negative breast cancer. After categorising participants into five cohorts according to molecular subtype and genomic biomarkers, participants were randomly assigned (1:1) with a block size of 4, stratified by subtype, to receive, in 28-day cycles, nab-paclitaxel (100 mg/m2, intravenously on days 1, 8, and 15) alone (control group) or with a subtyping-based regimen (subtyping-based group): pyrotinib (400 mg orally daily) for the LAR-HER2mut subtype, everolimus (10 mg orally daily) for the LAR-PI3K/AKTmut and MES-PI3K/AKTmut subtypes, camrelizumab (200 mg intravenously on days 1 and 15) and famitinib (20 mg orally daily) for the immunomodulatory subtype, and bevacizumab (10 mg/kg intravenously on days 1 and 15) for the BLIS/MES-PI3K/AKTWT subtype. The primary endpoint was investigator-assessed progression-free survival for the pooled subtyping-based group versus the control group in the intention-to-treat population (all randomly assigned participants). Safety was analysed in all patients with safety records who received at least one dose of study drug. This study is registered with ClinicalTrials.gov (NCT04395989). FINDINGS Between July 28, 2020, and Oct 16, 2022, 139 female participants were enrolled and randomly assigned to the subtyping-based group (n=69) or control group (n=70). At the data cutoff (May 31, 2023), the median follow-up was 22·5 months (IQR 15·2-29·0). Median progression-free survival was significantly longer in the pooled subtyping-based group (11·3 months [95% CI 8·6-15·2]) than in the control group (5·8 months [4·0-6·7]; hazard ratio 0·44 [95% CI 0·30-0·65]; p<0·0001). The most common grade 3-4 treatment-related adverse events were neutropenia (21 [30%] of 69 in the pooled subtyping-based group vs 16 [23%] of 70 in the control group), anaemia (five [7%] vs none), and increased alanine aminotransferase (four [6%] vs one [1%]). Treatment-related serious adverse events were reported for seven (10%) of 69 patients in the subtyping-based group and none in the control group. No treatment-related deaths were reported in either group. INTERPRETATION These findings highlight the potential clinical benefits of using molecular subtype-based treatment optimisation in patients with triple-negative breast cancer, suggesting a path for further clinical investigation. Phase 3 randomised clinical trials assessing the efficacy of subtyping-based regimens are now underway. FUNDING National Natural Science Foundation of China, Natural Science Foundation of Shanghai, Shanghai Hospital Development Center, and Jiangsu Hengrui Pharmaceuticals. TRANSLATION For the Chinese translation of the abstract see Supplementary Materials section.
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Affiliation(s)
- Lei Fan
- Department of Breast Surgery, Fudan University Shanghai Cancer Center and Key Laboratory of Breast Cancer in Shanghai, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Zhong-Hua Wang
- Department of Breast Surgery, Fudan University Shanghai Cancer Center and Key Laboratory of Breast Cancer in Shanghai, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Lin-Xiaoxi Ma
- Department of Breast Surgery, Fudan University Shanghai Cancer Center and Key Laboratory of Breast Cancer in Shanghai, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Song-Yang Wu
- Department of Breast Surgery, Fudan University Shanghai Cancer Center and Key Laboratory of Breast Cancer in Shanghai, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jiong Wu
- Department of Breast Surgery, Fudan University Shanghai Cancer Center and Key Laboratory of Breast Cancer in Shanghai, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ke-Da Yu
- Department of Breast Surgery, Fudan University Shanghai Cancer Center and Key Laboratory of Breast Cancer in Shanghai, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Xin-Yi Sui
- Department of Breast Surgery, Fudan University Shanghai Cancer Center and Key Laboratory of Breast Cancer in Shanghai, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ying Xu
- Department of Breast Surgery, Fudan University Shanghai Cancer Center and Key Laboratory of Breast Cancer in Shanghai, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Xi-Yu Liu
- Department of Breast Surgery, Fudan University Shanghai Cancer Center and Key Laboratory of Breast Cancer in Shanghai, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Li Chen
- Department of Breast Surgery, Fudan University Shanghai Cancer Center and Key Laboratory of Breast Cancer in Shanghai, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Wen-Juan Zhang
- Department of Breast Surgery, Fudan University Shanghai Cancer Center and Key Laboratory of Breast Cancer in Shanghai, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Xi Jin
- Department of Breast Surgery, Fudan University Shanghai Cancer Center and Key Laboratory of Breast Cancer in Shanghai, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Qin Xiao
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Ruo-Hong Shui
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Yi Xiao
- Department of Breast Surgery, Fudan University Shanghai Cancer Center and Key Laboratory of Breast Cancer in Shanghai, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Han Wang
- Department of Breast Surgery, Fudan University Shanghai Cancer Center and Key Laboratory of Breast Cancer in Shanghai, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yun-Song Yang
- Department of Breast Surgery, Fudan University Shanghai Cancer Center and Key Laboratory of Breast Cancer in Shanghai, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Xiao-Yan Huang
- Department of Breast Surgery, Fudan University Shanghai Cancer Center and Key Laboratory of Breast Cancer in Shanghai, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - A-Yong Cao
- Department of Breast Surgery, Fudan University Shanghai Cancer Center and Key Laboratory of Breast Cancer in Shanghai, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jun-Jie Li
- Department of Breast Surgery, Fudan University Shanghai Cancer Center and Key Laboratory of Breast Cancer in Shanghai, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Gen-Hong Di
- Department of Breast Surgery, Fudan University Shanghai Cancer Center and Key Laboratory of Breast Cancer in Shanghai, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Guang-Yu Liu
- Department of Breast Surgery, Fudan University Shanghai Cancer Center and Key Laboratory of Breast Cancer in Shanghai, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Wen-Tao Yang
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Xin Hu
- Department of Breast Surgery, Fudan University Shanghai Cancer Center and Key Laboratory of Breast Cancer in Shanghai, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yan Xia
- Department of Clinical Research & Development, Jiangsu Hengrui Pharmaceuticals, Shanghai, China
| | - Qian-Nan Liang
- Department of Clinical Research & Development, Jiangsu Hengrui Pharmaceuticals, Shanghai, China
| | - Yi-Zhou Jiang
- Department of Breast Surgery, Fudan University Shanghai Cancer Center and Key Laboratory of Breast Cancer in Shanghai, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
| | - Zhi-Ming Shao
- Department of Breast Surgery, Fudan University Shanghai Cancer Center and Key Laboratory of Breast Cancer in Shanghai, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
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Liang Y, Zhang P, Li F, Lai H, Qi T, Wang Y. Advances in the study of marketed antibody-drug Conjugates (ADCs) for the treatment of breast cancer. Front Pharmacol 2024; 14:1332539. [PMID: 38352694 PMCID: PMC10862125 DOI: 10.3389/fphar.2023.1332539] [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: 11/03/2023] [Accepted: 12/21/2023] [Indexed: 02/16/2024] Open
Abstract
Breast cancer continues to have a high incidence rate among female malignancies. Despite significant advancements in treatment modalities, the heterogeneous nature of breast cancer and its resistance to various therapeutic approaches pose considerable challenges. Antibody-drug conjugates (ADCs) effectively merge the specificity of antibodies with the cytotoxicity of chemotherapeutic agents, offering a novel strategy for precision treatment of breast cancer. Notably, trastuzumab emtansine (T-DM1) has provided a new therapeutic option for HER2-positive breast cancer patients globally, especially those resistant to conventional treatments. The development of trastuzumab deruxtecan (T-DXd) and sacituzumab govitecan (SG) has further broadened the applicability of ADCs in breast cancer therapy, presenting new hopes for patients with low HER2 expression and triple-negative breast cancer. However, the application of ADCs presents certain challenges. For instance, their treatment may lead to adverse reactions such as interstitial lung disease, thrombocytopenia, and diarrhea. Moreover, prolonged treatment could result in ADCs resistance, complicating the therapeutic process. Economically, the high costs of ADCs might hinder their accessibility in low-income regions. This article reviews the structure, mechanism of action, and clinical trials of commercially available ADCs for breast cancer treatment, with a focus on the clinical trials of the three drugs, aiming to provide insights for clinical applications and future research.
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Affiliation(s)
- Yan Liang
- Sichuan Cancer Hospital, Cancer Hospital Affiliate University of Electronic Science and Technology, Chengdu, China
- School of Medicine, University of Electronic Science and Technology, Chengdu, China
| | - Purong Zhang
- Sichuan Cancer Hospital, Cancer Hospital Affiliate University of Electronic Science and Technology, Chengdu, China
| | - Feng Li
- Sichuan Cancer Hospital, Cancer Hospital Affiliate University of Electronic Science and Technology, Chengdu, China
- School of Medicine, University of Electronic Science and Technology, Chengdu, China
| | - Houyun Lai
- Sichuan Cancer Hospital, Cancer Hospital Affiliate University of Electronic Science and Technology, Chengdu, China
- School of Medicine, University of Electronic Science and Technology, Chengdu, China
| | - Tingting Qi
- Sichuan Cancer Hospital, Cancer Hospital Affiliate University of Electronic Science and Technology, Chengdu, China
| | - Yixin Wang
- Sichuan Cancer Hospital, Cancer Hospital Affiliate University of Electronic Science and Technology, Chengdu, China
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Mei J, Cai Y, Zhu H, Jiang Y, Fu Z, Xu J, Chen L, Yang K, Zhao J, Song C, Zhang Y, Mao W, Yin Y. High B7-H3 expression with low PD-L1 expression identifies armored-cold tumors in triple-negative breast cancer. NPJ Breast Cancer 2024; 10:11. [PMID: 38280882 PMCID: PMC10821876 DOI: 10.1038/s41523-024-00618-6] [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: 04/22/2023] [Accepted: 01/06/2024] [Indexed: 01/29/2024] Open
Abstract
Triple-negative breast cancer (TNBC) is generally regarded as the most aggressive subtype among breast cancers, but exhibits higher chemotherapeutic and immunotherapeutic responses due to its unique immunogenicity. Thus, appropriate discrimination of subtypes is critical for guiding therapeutic options in clinical practice. In this research, using multiple in-house and public cohorts, we investigated the expression features and immuno-correlations of B7-H3 in breast cancer and checked the anti-tumor effect of the B7-H3 monoclonal antibody in a mouse model. We also developed a novel classifier combining B7-H3 and PD-L1 expression in TNBC. B7-H3 was revealed to be related to immuno-cold features and accumulated collagen in TNBC. In addition, targeting B7-H3 using the monoclonal antibody significantly suppressed mouse TNBC growth, reversed the armored-cold phenotype, and also boosted anti-PD-1 immunotherapy. In addition, patients with B7-H3 high and PD-L1 low expression showed the lowest anti-tumor immune infiltration, the highest collagen level, and the lowest therapeutic responses to multiple therapies, which mostly belong to armored-cold tumors. Overall, this research provides a novel subtyping strategy based on the combination of B7-H3/PD-L1 expression, which leads to a novel approach for the management of TNBC.
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Affiliation(s)
- Jie Mei
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 211166, China
- The First Clinical Medicine College, Nanjing Medical University, Wuxi, 214023, China
- Department of Oncology, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi, 214023, China
| | - Yun Cai
- Wuxi Maternal and Child Health Care Hospital, Wuxi Medical Center of Nanjing Medical University, Wuxi, 214023, China
| | - Hongjun Zhu
- Department of Oncology, Nantong Third People's Hospital Affiliated to Nantong University, Nantong, 226006, China
| | - Ying Jiang
- Department of Gynecology, The Obstetrics and Gynecology Hospital Affiliated to Jiangnan University, Wuxi, 214023, China
| | - Ziyi Fu
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 211166, China
| | - Junying Xu
- Department of Oncology, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi, 214023, China
| | - Lingyan Chen
- Wuxi Maternal and Child Health Care Hospital, Wuxi Medical Center of Nanjing Medical University, Wuxi, 214023, China
| | - Kai Yang
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 211166, China
- The First Clinical Medicine College, Nanjing Medical University, Wuxi, 214023, China
- Department of Oncology, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi, 214023, China
| | - Jinlu Zhao
- Department of General Surgery, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, 150001, China
| | - Chenghu Song
- Department of Thoracic Surgery, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi, 214023, China
| | - Yan Zhang
- Wuxi Maternal and Child Health Care Hospital, Wuxi Medical Center of Nanjing Medical University, Wuxi, 214023, China.
- Department of Gynecology, The Obstetrics and Gynecology Hospital Affiliated to Jiangnan University, Wuxi, 214023, China.
| | - Wenjun Mao
- Department of Thoracic Surgery, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi, 214023, China.
| | - Yongmei Yin
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 211166, China.
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Personalized Cancer Medicine, Nanjing Medical University, Nanjing, 211166, China.
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Krop IE, Mittempergher L, Paulson JN, Andre F, Bonnefoi H, Loi S, Loibl S, Gelber RD, Caballero C, Bhaskaran R, Dreezen C, Menicucci AR, Bernards R, van 't Veer LJ, Piccart MJ. Prediction of Benefit From Adjuvant Pertuzumab by 80-Gene Signature in the APHINITY (BIG 4-11) Trial. JCO Precis Oncol 2024; 8:e2200667. [PMID: 38237097 DOI: 10.1200/po.22.00667] [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: 12/06/2022] [Revised: 03/30/2023] [Accepted: 05/04/2023] [Indexed: 01/23/2024] Open
Abstract
PURPOSE At the primary analysis, the APHINITY trial reported a statistically significant but modest benefit of adding pertuzumab to standard adjuvant chemotherapy plus trastuzumab in patients with histologically confirmed human epidermal growth factor receptor 2 (HER2)-positive early-stage breast cancer. This study evaluated whether the 80-gene molecular subtyping signature (80-GS) could identify patients within the APHINITY population who derive the most benefit from dual anti-HER2 therapy. METHODS In a nested case-control study design of 1,023 patients (matched event to control ratio of 3:1), the 80-GS classified breast tumors into functional luminal type, HER2 type, or basal type. Additionally, 80-GS distinguished tumor subtypes that exhibited a single-dominant functional pathway versus tumors with multiple activated pathways. The primary end point was invasive disease-free survival (IDFS). Hazard ratios (HRs) were evaluated by Cox regression. After excluding patients without appropriate consent and those with missing data, 964 patients were included. RESULTS The 80-GS classified 50% (n = 479) of tumors as luminal type, 28% (n = 275) as HER2 type, and 22% (n = 209) as basal type. Most luminal-type tumors (86%) displayed a single-activated pathway, whereas 49% of HER2-type and 42% of basal-type tumors were dual activated. There was no significant difference in IDFS among different conventional 80-GS subtypes (single- and dual-activated subtypes combined). However, basal single-subtype tumors were significantly more likely to have an IDFS event (hazard ratio, 1.69 [95% CI, 1.12 to 2.54]) compared with other subtypes. HER2 single-subtype tumors displayed a trend toward greater beneficial effect on the addition of pertuzumab (hazard ratio, 0.56 [95% CI, 0.27 to 1.16]) compared with all other subtypes. CONCLUSION The 80-GS identified subgroups of histologically confirmed HER2-positive tumors with distinct biological characteristics. Basal single-subtype tumors exhibit an inferior prognosis compared with other subgroups and may be candidates for additional therapeutic strategies. Preliminary results suggest patients with HER2-positive, genomically HER2 single-subtype tumors may particularly benefit from added pertuzumab, which warrants further investigation.
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Affiliation(s)
| | | | | | | | | | - Sherene Loi
- Peter MacCallum Cancer Centre, Melbourne, Australia
| | | | - Richard D Gelber
- Dana-Farber Cancer Institute, Harvard Medical School, Harvard TH Chan School of Public Health, and Frontier Science Foundation, Boston, MA
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Zahavi DJ, Erbe R, Zhang YW, Guo T, Malchiodi ZX, Maynard R, Lekan A, Gallagher R, Wulfkuhle J, Petricoin E, Jablonski SA, Fertig EJ, Weiner LM. Antibody dependent cell-mediated cytotoxicity selection pressure induces diverse mechanisms of resistance. Cancer Biol Ther 2023; 24:2269637. [PMID: 37878417 PMCID: PMC10601508 DOI: 10.1080/15384047.2023.2269637] [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: 07/14/2023] [Accepted: 10/07/2023] [Indexed: 10/27/2023] Open
Abstract
Targeted monoclonal antibody therapy has emerged as a powerful therapeutic strategy for cancer. However, only a minority of patients have durable responses and the development of resistance remains a major clinical obstacle. Antibody-dependent cell-mediated cytotoxicity (ADCC) represents a crucial therapeutic mechanism of action; however, few studies have explored ADCC resistance. Using multiple in vitro models of ADCC selection pressure, we have uncovered both shared and distinct resistance mechanisms. Persistent ADCC selection pressure yielded ADCC-resistant cells that are characterized by a loss of NK cell conjugation and this shared resistance phenotype is associated with cell-line dependent modulation of cell surface proteins that contribute to immune synapse formation and NK cell function. We employed single-cell RNA sequencing and proteomic screens to interrogate molecular mechanisms of resistance. We demonstrate that ADCC resistance involves upregulation of interferon/STAT1 and DNA damage response signaling as well as activation of the immunoproteasome. Here, we identify pathways that modulate ADCC sensitivity and report strategies to enhance ADCC-mediated elimination of cancer cells. ADCC resistance could not be reversed with combinatorial treatment approaches. Hence, our findings indicate that tumor cells utilize multiple strategies to inhibit NK cell mediated-ADCC. Future research and development of NK cell-based immunotherapies must incorporate plans to address or potentially prevent the induction of resistance.
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Affiliation(s)
- David J. Zahavi
- Department of Oncology and Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, USA
| | - Rossin Erbe
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, USA
| | - Yong-Wei Zhang
- Department of Oncology and Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, USA
| | - Theresa Guo
- Department of Oncology, UC San Diego School of Medicine, San Diego, USA
| | - Zoe X. Malchiodi
- Department of Oncology and Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, USA
| | - Rachael Maynard
- Department of Oncology and Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, USA
| | - Alexander Lekan
- Department of Oncology and Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, USA
| | - Rosa Gallagher
- Center for Applied Proteomics and Molecular Medicine, George Mason University, Fairfax, USA
| | - Julia Wulfkuhle
- Center for Applied Proteomics and Molecular Medicine, George Mason University, Fairfax, USA
| | - Emanuel Petricoin
- Center for Applied Proteomics and Molecular Medicine, George Mason University, Fairfax, USA
| | - Sandra A. Jablonski
- Department of Oncology and Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, USA
| | - Elana J. Fertig
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, USA
| | - Louis M. Weiner
- Department of Oncology and Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, USA
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Wang S, Böhnert V, Joseph AJ, Sudaryo V, Skariah G, Swinderman JT, Yu FB, Subramanyam V, Wolf DM, Lyu X, Gilbert LA, van’t Veer LJ, Goodarzi H, Li L. ENPP1 is an innate immune checkpoint of the anticancer cGAMP-STING pathway in breast cancer. Proc Natl Acad Sci U S A 2023; 120:e2313693120. [PMID: 38117852 PMCID: PMC10756298 DOI: 10.1073/pnas.2313693120] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Accepted: 11/10/2023] [Indexed: 12/22/2023] Open
Abstract
Ectonucleotide pyrophosphatase/phosphodiesterase 1 (ENPP1) expression correlates with poor prognosis in many cancers, and we previously discovered that ENPP1 is the dominant hydrolase of extracellular cGAMP: a cancer-cell-produced immunotransmitter that activates the anticancer stimulator of interferon genes (STING) pathway. However, ENPP1 has other catalytic activities and the molecular and cellular mechanisms contributing to its tumorigenic effects remain unclear. Here, using single-cell RNA-seq, we show that ENPP1 in both cancer and normal tissues drives primary breast tumor growth and metastasis by dampening extracellular 2'3'-cyclic-GMP-AMP (cGAMP)-STING-mediated antitumoral immunity. ENPP1 loss-of-function in both cancer cells and normal tissues slowed primary tumor growth and abolished metastasis. Selectively abolishing the cGAMP hydrolysis activity of ENPP1 phenocopied ENPP1 knockout in a STING-dependent manner, demonstrating that restoration of paracrine cGAMP-STING signaling is the dominant anti-cancer mechanism of ENPP1 inhibition. Finally, ENPP1 expression in breast tumors deterministically predicated whether patients would remain free of distant metastasis after pembrolizumab (anti-PD-1) treatment followed by surgery. Altogether, ENPP1 blockade represents a strategy to exploit cancer-produced extracellular cGAMP for controlled local activation of STING and is therefore a promising therapeutic approach against breast cancer.
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Affiliation(s)
- Songnan Wang
- Department of Biochemistry, Stanford University, Stanford, CA94305
- ChEM-H Institute, Stanford University, Stanford, CA94305
- Arc Institute, Palo Alto, CA94304
| | - Volker Böhnert
- Department of Biochemistry, Stanford University, Stanford, CA94305
- ChEM-H Institute, Stanford University, Stanford, CA94305
| | - Alby J. Joseph
- Department of Biochemistry, Stanford University, Stanford, CA94305
- ChEM-H Institute, Stanford University, Stanford, CA94305
- Arc Institute, Palo Alto, CA94304
| | - Valentino Sudaryo
- Department of Biochemistry, Stanford University, Stanford, CA94305
- ChEM-H Institute, Stanford University, Stanford, CA94305
- Arc Institute, Palo Alto, CA94304
| | - Gemini Skariah
- Department of Biochemistry, Stanford University, Stanford, CA94305
- ChEM-H Institute, Stanford University, Stanford, CA94305
| | - Jason T. Swinderman
- Arc Institute, Palo Alto, CA94304
- Department of Urology, University of California, San Francisco, CA94143
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA94158
| | | | - Vishvak Subramanyam
- Department of Urology, University of California, San Francisco, CA94143
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA94158
- Department of Biophysics & Biochemistry, University of California, San Francisco, CA94143
- Baker Computational Health Science Institute, University of California, San Francisco, CA94143
| | - Denise M. Wolf
- Department of Laboratory Medicine, University of California, San Francisco, CA94115
| | - Xuchao Lyu
- ChEM-H Institute, Stanford University, Stanford, CA94305
- Department of Pathology, Stanford University School of Medicine, Stanford, CA94305
| | - Luke A. Gilbert
- Arc Institute, Palo Alto, CA94304
- Department of Urology, University of California, San Francisco, CA94143
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA94158
| | - Laura J. van’t Veer
- Department of Laboratory Medicine, University of California, San Francisco, CA94115
| | - Hani Goodarzi
- Department of Urology, University of California, San Francisco, CA94143
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA94158
- Department of Biophysics & Biochemistry, University of California, San Francisco, CA94143
- Baker Computational Health Science Institute, University of California, San Francisco, CA94143
| | - Lingyin Li
- Department of Biochemistry, Stanford University, Stanford, CA94305
- ChEM-H Institute, Stanford University, Stanford, CA94305
- Arc Institute, Palo Alto, CA94304
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36
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Gallagher RI, Wulfkuhle J, Wolf DM, Brown-Swigart L, Yau C, O'Grady N, Basu A, Lu R, Campbell MJ, Magbanua MJ, Coppé JP, Asare SM, Sit L, Matthews JB, Perlmutter J, Hylton N, Liu MC, Symmans WF, Rugo HS, Isaacs C, DeMichele AM, Yee D, Pohlmann PR, Hirst GL, Esserman LJ, van 't Veer LJ, Petricoin EF. Protein signaling and drug target activation signatures to guide therapy prioritization: Therapeutic resistance and sensitivity in the I-SPY 2 Trial. Cell Rep Med 2023; 4:101312. [PMID: 38086377 PMCID: PMC10772394 DOI: 10.1016/j.xcrm.2023.101312] [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: 12/07/2022] [Revised: 07/03/2023] [Accepted: 11/14/2023] [Indexed: 12/22/2023]
Abstract
Molecular subtyping of breast cancer is based mostly on HR/HER2 and gene expression-based immune, DNA repair deficiency, and luminal signatures. We extend this description via functional protein pathway activation mapping using pre-treatment, quantitative expression data from 139 proteins/phosphoproteins from 736 patients across 8 treatment arms of the I-SPY 2 Trial (ClinicalTrials.gov: NCT01042379). We identify predictive fit-for-purpose, mechanism-of-action-based signatures and individual predictive protein biomarker candidates by evaluating associations with pathologic complete response. Elevated levels of cyclin D1, estrogen receptor alpha, and androgen receptor S650 associate with non-response and are biomarkers for global resistance. We uncover protein/phosphoprotein-based signatures that can be utilized both for molecularly rationalized therapeutic selection and for response prediction. We introduce a dichotomous HER2 activation response predictive signature for stratifying triple-negative breast cancer patients to either HER2 or immune checkpoint therapy response as a model for how protein activation signatures provide a different lens to view the molecular landscape of breast cancer and synergize with transcriptomic-defined signatures.
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Affiliation(s)
- Rosa I Gallagher
- Center for Applied Proteomics and Molecular Medicine, George Mason University, Manassas, VA 20110, USA.
| | - Julia Wulfkuhle
- Center for Applied Proteomics and Molecular Medicine, George Mason University, Manassas, VA 20110, USA.
| | - Denise M Wolf
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Lamorna Brown-Swigart
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Christina Yau
- Department of Surgery, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Nicholas O'Grady
- Department of Surgery, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Amrita Basu
- Department of Surgery, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Ruixiao Lu
- Quantum Leap Healthcare Collaborative, San Francisco, CA 94118, USA
| | - Michael J Campbell
- Department of Surgery, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Mark J Magbanua
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Jean-Philippe Coppé
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Smita M Asare
- Quantum Leap Healthcare Collaborative, San Francisco, CA 94118, USA
| | - Laura Sit
- Department of Surgery, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Jeffrey B Matthews
- Department of Surgery, University of California, San Francisco, San Francisco, CA 94143, USA
| | | | - Nola Hylton
- Department of Radiology, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Minetta C Liu
- Department of Surgery, Mayo Clinic, Rochester, MN 55905, USA
| | - W Fraser Symmans
- Department of Pathology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Hope S Rugo
- Division of Hematology/Oncology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Claudine Isaacs
- Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC 20007, USA
| | - Angela M DeMichele
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Douglas Yee
- Department of Medicine, University of Minnesota, Minneapolis, MN 55455, USA
| | - Paula R Pohlmann
- Department of Breast Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Gillian L Hirst
- Department of Surgery, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Laura J Esserman
- Department of Surgery, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Laura J van 't Veer
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Emanuel F Petricoin
- Center for Applied Proteomics and Molecular Medicine, George Mason University, Manassas, VA 20110, USA.
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Wang H, Wang W, Wang Z, Li X. Transcriptomic correlates of cell cycle checkpoints with distinct prognosis, molecular characteristics, immunological regulation, and therapeutic response in colorectal adenocarcinoma. Front Immunol 2023; 14:1291859. [PMID: 38143740 PMCID: PMC10749195 DOI: 10.3389/fimmu.2023.1291859] [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: 09/10/2023] [Accepted: 11/22/2023] [Indexed: 12/26/2023] Open
Abstract
Backgrounds Colorectal adenocarcinoma (COAD), accounting for the most common subtype of colorectal cancer (CRC), is a kind of malignant digestive tumor. Some cell cycle checkpoints (CCCs) have been found to contribute to CRC progression, whereas the functional roles of a lot of CCCs, especially the integrated role of checkpoint mechanism in the cell cycle, remain unclear. Materials and methods The Genomic Data Commons (GDC) The Cancer Genome Atlas (TCGA) COAD cohort was retrieved as the training dataset, and GSE24551 and GSE29623 were downloaded from Gene Expression Omnibus (GEO) as the validation datasets. A total of 209 CCC-related genes were derived from the Gene Ontology Consortium and were subsequently enrolled in the univariate, multivariate, and least absolute shrinkage and selection operator (LASSO) Cox regression analyses, finally defining a CCC signature. Cell proliferation and Transwell assay analyses were utilized to evaluate the functional roles of signature-related CCCs. The underlying CCC signature, molecular characteristics, immune-related features, and therapeutic response were finally estimated. The Genomics of Drug Sensitivity in Cancer (GDSC) database was employed for the evaluation of chemotherapeutic responses. Results The aberrant gene expression of CCCs greatly contributed to COAD development and progression. Univariate Cox regression analysis identified 27 CCC-related genes significantly affecting the overall survival (OS) of COAD patients; subsequently, LASSO analysis determined a novel CCC signature. Noticeably, CDK5RAP2, MAD1L1, NBN, RGCC, and ZNF207 were first identified to be correlated with the prognosis of COAD, and it was proven that all of them were significantly correlated with the proliferation and invasion of HCT116 and SW480 cells. In TCGA COAD cohort, CCC signature robustly stratified COAD patients into high and low CCC score groups (median OS: 57.24 months vs. unreached, p< 0.0001), simultaneously, with the good AUC values for OS prediction at 1, 2, and 3 years were 0.74, 0.78, and 0.77. Furthermore, the prognostic capacity of the CCC signature was verified in the GSE24551 and GSE29623 datasets, and the CCC signature was independent of clinical features. Moreover, a higher CCC score always indicated worse OS, regardless of clinical features, histological subtypes, or molecular subgroups. Intriguingly, functional enrichment analysis confirmed the CCC score was markedly associated with extracellular, matrix and immune (chemokine)-related signaling, cell cycle-related signaling, and metabolisms. Impressively, a higher CCC score was positively correlated with a majority of chemokines, receptors, immunostimulators, and anticancer immunity, indicating a relatively immune-promoting microenvironment. In addition, GSE173839, GSE25066, GSE41998, and GSE194040 dataset analyses of the underlying CCC signature suggested that durvalumab with olaparib and paclitaxel, taxane-anthracycline chemotherapy, neoadjuvant cyclophosphamide/doxorubicin with ixabepilone or paclitaxel, and immunotherapeutic strategies might be suitable for COAD patients with higher CCC score. Eventually, the GDSC database analysis showed that lower CCC scores were likely to be more sensitive to 5-fluorouracil, bosutinib, gemcitabine, gefitinib, methotrexate, mitomycin C, and temozolomide, while patients with higher CCC score seemed to have a higher level of sensitivity to bortezomib and elesclomol. Conclusion The novel CCC signature exhibited a good ability for prognosis prediction for COAD patients, and the CCC score was found to be highly correlated with molecular features, immune-related characteristics, and therapeutic responses, which would greatly promote clinical management and precision medicine for COAD.
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Affiliation(s)
- Heng Wang
- Department of Colorectal Surgery, Shanghai Yangpu Hospital of Traditional Chinese Medicine, Shanghai, China
| | - Wei Wang
- Department of Colorectal Surgery, The First Affiliated Hospital of Naval Medical University, Shanghai, China
| | - Zhen Wang
- Department of Colorectal Surgery, The First Affiliated Hospital of Naval Medical University, Shanghai, China
| | - Xu Li
- Department of Colorectal Surgery, The First Affiliated Hospital of Naval Medical University, Shanghai, China
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Wang H, Ding XH, Liu CL, Xiao Y, Shui RH, Li YP, Chen C, Yang WT, Liu S, Chen CS, Shao ZM, Jiang YZ. Genomic alterations affecting tumor-infiltrating lymphocytes and PD-L1 expression patterns in triple-negative breast cancer. J Natl Cancer Inst 2023; 115:1586-1596. [PMID: 37549066 DOI: 10.1093/jnci/djad154] [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: 12/22/2022] [Revised: 06/14/2023] [Accepted: 08/02/2023] [Indexed: 08/09/2023] Open
Abstract
BACKGROUND Tumor-infiltrating lymphocytes (TILs) and programmed cell death 1 ligand 1 (PD-L1) remain imperfect in predicting clinical outcomes of triple-negative breast cancer because outcomes do not always correlate with the expression of these biomarkers. Genomic and transcriptomic alterations that may contribute to the expression of these biomarkers remain incompletely uncovered. METHODS We evaluated PD-L1 immunohistochemistry scores (SP142 and 28-8 assays) and TILs in our triple-negative breast cancer multiomics dataset and 2 immunotherapy clinical trial cohorts. Then, we analyzed genomic and transcriptomic alterations correlated with TILs, PD-L1 expression, and patient outcomes. RESULTS Despite TILs serving as a decent predictor for triple-negative breast cancer clinical outcomes, exceptions remained. Our study revealed that several genomic alterations were correlated with unexpected events. In particular, PD-L1 expression may cause a paradoxical relationship between TILs and prognosis in certain patients. Consequently, we classified triple-negative breast cancers into 4 groups based on PD-L1 and TIL levels. The TIL-negative PD-L1-positive and TIL-positive PD-L1-negative groups were not typical "hot" tumors; both were associated with worse prognoses and lower immunotherapy efficacy than TIL-positive PD-L1-positive tumors. Copy number variation of PD-L1 and oncogenic signaling activation were correlated with PD-L1 expression in the TIL-negative PD-L1-positive group, whereas GSK3B-induced degradation may cause undetectable PD-L1 expression in the TIL-positive PD-L1-negative group. These factors have the potential to affect the predictive function of both PD-L1 and TILs. CONCLUSIONS Several genomic and transcriptomic alterations may cause paradoxical effects among TILs, PD-L1 expression, and prognosis in triple-negative breast cancer. Investigating and targeting these factors will advance precision immunotherapy for patients with this disease.
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Affiliation(s)
- Han Wang
- Key Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Xiao-Hong Ding
- Key Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Cheng-Lin Liu
- Key Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Yi Xiao
- Key Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ruo-Hong Shui
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Yan-Ping Li
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Chen Chen
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Wen-Tao Yang
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Suling Liu
- Key Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, China
- Institutes of Biomedical Sciences, Cancer Institutes, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ce-Shi Chen
- Academy of Biomedical Engineering, Kunming Medical University, Kunming, China
- The Third Affiliated Hospital, Kunming Medical University, Kunming, China
| | - Zhi-Ming Shao
- Key Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yi-Zhou Jiang
- Key Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
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39
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De Caluwe A, Romano E, Poortmans P, Gombos A, Agostinetto E, Marta GN, Denis Z, Drisis S, Vandekerkhove C, Desmet A, Philippson C, Craciun L, Veys I, Larsimont D, Paesmans M, Van Gestel D, Salgado R, Sotiriou C, Piccart-Gebhart M, Ignatiadis M, Buisseret L. First-in-human study of SBRT and adenosine pathway blockade to potentiate the benefit of immunochemotherapy in early-stage luminal B breast cancer: results of the safety run-in phase of the Neo-CheckRay trial. J Immunother Cancer 2023; 11:e007279. [PMID: 38056900 PMCID: PMC10711977 DOI: 10.1136/jitc-2023-007279] [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] [Accepted: 10/20/2023] [Indexed: 12/08/2023] Open
Abstract
BACKGROUND Luminal B breast cancer (BC) presents a worse prognosis when compared with luminal A BC and exhibits a lower sensitivity to chemotherapy and a lower immunogenicity in contrast to non-luminal BC subtypes. The Neo-CheckRay clinical trial investigates the use of stereotactic body radiation therapy (SBRT) directed to the primary tumor in combination with the adenosine pathway inhibitor oleclumab to improve the response to neo-adjuvant immuno-chemotherapy in luminal B BC. The trial consists of a safety run-in followed by a randomized phase II trial. Here, we present the results of the first-in-human safety run-in. METHODS The safety run-in was an open-label, single-arm trial in which six patients with early-stage luminal B BC received the following neo-adjuvant regimen: paclitaxel q1w×12 → doxorubicin/cyclophosphamide q2w×4; durvalumab (anti-programmed cell death receptor ligand 1 (PD-L1)) q4w×5; oleclumab (anti-CD73) q2w×4 → q4w×3 and 3×8 Gy SBRT to the primary tumor at week 5. Surgery must be performed 2-6 weeks after primary systemic treatment and adjuvant therapy was given per local guidelines, RT boost to the tumor bed was not allowed. Key inclusion criteria were: luminal BC, Ki67≥15% or histological grade 3, MammaPrint high risk, tumor size≥1.5 cm. Primary tumor tissue samples were collected at three timepoints: baseline, 1 week after SBRT and at surgery. Tumor-infiltrating lymphocytes, PD-L1 and CD73 were evaluated at each timepoint, and residual cancer burden (RCB) was calculated at surgery. RESULTS Six patients were included between November 2019 and March 2020. Median age was 53 years, range 37-69. All patients received SBRT and underwent surgery 2-4 weeks after the last treatment. After a median follow-up time of 2 years after surgery, one grade 3 adverse event (AE) was reported: pericarditis with rapid resolution under corticosteroids. No grade 4-5 AE were documented. Overall cosmetical breast evaluation after surgery was 'excellent' in four patients and 'good' in two patients. RCB results were 2/6 RCB 0; 2/6 RCB 1; 1/6 RCB 2 and 1/6 RCB 3. CONCLUSIONS This novel treatment combination was considered safe and is worth further investigation in a randomized phase II trial. TRIAL REGISTRATION NUMBER NCT03875573.
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Affiliation(s)
- Alex De Caluwe
- Radiation Oncology, Université libre de Bruxelles (ULB), Hôpital Universitaire de Bruxelles (H.U.B), Institut Jules Bordet, Bruxelles, Belgium
| | - Emanuela Romano
- Medical Oncology, Center for Cancer Immunotherapy, Institut Curie, Paris, France
| | - Philip Poortmans
- Radiation Oncology, Iridium Network and University of Antwerp, Antwerpen, Belgium
| | - Andrea Gombos
- Medical Oncology, Université libre de Bruxelles (ULB), Hôpital Universitaire de Bruxelles (H.U.B), Institut Jules Bordet, Bruxelles, Belgium
| | - Elisa Agostinetto
- Clinical Trials Support Unit (CTSU), Université libre de Bruxelles (ULB), Hôpital Universitaire de Bruxelles (H.U.B), Institut Jules Bordet, Bruxelles, Bruxelles, Belgium
| | - Guilherme Nader Marta
- Clinical Trials Support Unit (CTSU), Université libre de Bruxelles (ULB), Hôpital Universitaire de Bruxelles (H.U.B), Institut Jules Bordet, Bruxelles, Bruxelles, Belgium
| | - Zoe Denis
- Université Libre de Bruxelles (ULB), Hôpital Universitaire de Bruxelles (HUB), Institut Jules Bordet, Bruxelles, Belgium
| | - Stylianos Drisis
- Radiology, Université libre de Bruxelles (ULB), Hôpital Universitaire de Bruxelles (H.U.B), Institut Jules Bordet, Bruxelles, Belgium
| | - Christophe Vandekerkhove
- Medical Physics, Université libre de Bruxelles (ULB), Hôpital Universitaire de Bruxelles (H.U.B), Institut Jules Bordet, Bruxelles, Belgium
| | - Antoine Desmet
- Radiation Oncology, Université libre de Bruxelles (ULB), Hôpital Universitaire de Bruxelles (H.U.B), Institut Jules Bordet, Bruxelles, Belgium
| | - Catherine Philippson
- Radiation Oncology, Université libre de Bruxelles (ULB), Hôpital Universitaire de Bruxelles (H.U.B), Institut Jules Bordet, Bruxelles, Belgium
| | - Ligia Craciun
- Pathology, Université libre de Bruxelles (ULB), Hôpital Universitaire de Bruxelles (H.U.B), Institut Jules Bordet, Bruxelles, Belgium
| | - Isabelle Veys
- Surgery, Université libre de Bruxelles (ULB), Hôpital Universitaire de Bruxelles (H.U.B), Institut Jules Bordet, Bruxelles, Belgium
| | - Denis Larsimont
- Pathology, Université libre de Bruxelles (ULB), Hôpital Universitaire de Bruxelles (H.U.B), Institut Jules Bordet, Bruxelles, Belgium
| | - Marianne Paesmans
- Clinical Trials Support Unit (CTSU), Université libre de Bruxelles (ULB), Hôpital Universitaire de Bruxelles (H.U.B), Institut Jules Bordet, Bruxelles, Bruxelles, Belgium
| | - Dirk Van Gestel
- Radiation Oncology, Université libre de Bruxelles (ULB), Hôpital Universitaire de Bruxelles (H.U.B), Institut Jules Bordet, Bruxelles, Belgium
| | | | - Christos Sotiriou
- Medical Oncology, Université libre de Bruxelles (ULB), Hôpital Universitaire de Bruxelles (H.U.B), Institut Jules Bordet, Bruxelles, Belgium
| | - Martine Piccart-Gebhart
- Medical Oncology, Université libre de Bruxelles (ULB), Hôpital Universitaire de Bruxelles (H.U.B), Institut Jules Bordet, Bruxelles, Belgium
| | - Michail Ignatiadis
- Medical Oncology, Université libre de Bruxelles (ULB), Hôpital Universitaire de Bruxelles (H.U.B), Institut Jules Bordet, Bruxelles, Belgium
| | - Laurence Buisseret
- Medical Oncology, Université libre de Bruxelles (ULB), Hôpital Universitaire de Bruxelles (H.U.B), Institut Jules Bordet, Bruxelles, Belgium
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Zhou J, Wan F, Wang L, Peng C, Huang R, Peng F. STAT4 facilitates PD-L1 level via IL-12R/JAK2/STAT3 axis and predicts immunotherapy response in breast cancer. MedComm (Beijing) 2023; 4:e464. [PMID: 38107057 PMCID: PMC10724500 DOI: 10.1002/mco2.464] [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: 06/04/2023] [Revised: 11/26/2023] [Accepted: 12/04/2023] [Indexed: 12/19/2023] Open
Abstract
Signal transducer and activator of transcription 4 (STAT4) is a critical transcription factor for T helper cell differentiation and tumor cells. Although its prognostic role and gene function have been reported in several carcinomas, the role of STAT4 in vitro and in vivo in breast cancer remains poorly understood. The effect of STAT4 in immunotherapy is also unclear. Therefore, we integrated bulk transcriptomics, experiments, and single-cell transcriptomics to systematically analyze its function in prognosis and signaling pathway. Several clinical breast cancer cohorts confirmed STAT4 as a T-cell relevant prognostic biomarker. Overexpressed STAT4 increased programmed cell death ligand 1 (PD-L1) and major histocompatibility complex class II levels in breast cancer cells. In molecular mechanism, transcriptional synergy between STAT4 and STAT3 transactivated interleukin (IL)-12R and involved a positive feedback loop: STAT4/IL-12R/JAK2-STAT3-STAT4, which contributed to the upregulation of PD-L1 expression. The above signaling axis was defined as the STAT4-related pathway and its score was used to predict T-cell expansion and anti-PD1 treatment response. These findings highlight a novel molecular mechanism indirectly regulating PD-L1 through the STAT4-related pathway: IL-12R/JAK2-STAT3-STAT4/PD-L1, and it has potential application in predicting anti-PD-1 immunotherapy response, which may pave the way for stratified immunotherapy in breast cancer.
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Affiliation(s)
- Jianbo Zhou
- West China School of PharmacySichuan UniversityChengduChina
| | - Feng Wan
- State Key Laboratory of Southwestern Chinese Medicine ResourcesChengdu University of Traditional Chinese MedicineChengduChina
| | - Li Wang
- West China School of PharmacySichuan UniversityChengduChina
| | - Cheng Peng
- State Key Laboratory of Southwestern Chinese Medicine ResourcesChengdu University of Traditional Chinese MedicineChengduChina
| | - Ruizhen Huang
- Department of CardiovascularHospital of Chengdu University of Traditional Chinese MedicineChengduChina
| | - Fu Peng
- West China School of PharmacySichuan UniversityChengduChina
- Key Laboratory of Drug‐Targeting and Drug Delivery System of the Education Ministry and Sichuan ProvinceSichuan Engineering Laboratory for Plant‐Sourced Drug and Sichuan Research Center for Drug Precision Industrial TechnologySichuan UniversityChengduChina
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Zheng X, Zhao D, Liu Y, Jin Y, Liu T, Li H, Liu D. Regeneration and anti-inflammatory effects of stem cells and their extracellular vesicles in gynecological diseases. Biomed Pharmacother 2023; 168:115739. [PMID: 37862976 DOI: 10.1016/j.biopha.2023.115739] [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: 08/25/2023] [Revised: 10/10/2023] [Accepted: 10/16/2023] [Indexed: 10/22/2023] Open
Abstract
There are many gynecological diseases, among which breast cancer (BC), cervical cancer (CC), endometriosis (EMs), and polycystic ovary syndrome (PCOS) are common and difficult to cure. Stem cells (SCs) are a focus of regenerative medicine. They are commonly used to treat organ damage and difficult diseases because of their potential for self-renewal and multidirectional differentiation. SCs are also commonly used for difficult-to-treat gynecological diseases because of their strong directional differentiation ability with unlimited possibilities, their tendency to adhere to the diseased tissue site, and their use as carriers for drug delivery. SCs can produce exosomes in a paracrine manner. Exosomes can be produced in large quantities and have the advantage of easy storage. Their safety and efficacy are superior to those of SCs, which have considerable potential in gynecological treatment, such as inhibiting endometrial senescence, promoting vascular reconstruction, and improving anti-inflammatory and immune functions. In this paper, we review the mechanisms of the regenerative and anti-inflammatory capacity of SCs and exosomes in incurable gynecological diseases and the current progress in their application in genetic engineering to provide a foundation for further research.
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Affiliation(s)
- Xu Zheng
- Changchun University of Chinese Medicine, Changchun 130117, China
| | - Dan Zhao
- Affiliated Hospital of Changchun University of Traditional Chinese Medicine, Changchun 130000, China
| | - Yang Liu
- Affiliated Hospital of Changchun University of Traditional Chinese Medicine, Changchun 130000, China
| | - Ye Jin
- Changchun University of Chinese Medicine, Changchun 130117, China
| | - Tianjia Liu
- Changchun University of Chinese Medicine, Changchun 130117, China; Baicheng Medical College, Baicheng 137000, China.
| | - Huijing Li
- Changchun University of Chinese Medicine, Changchun 130117, China.
| | - Da Liu
- Changchun University of Chinese Medicine, Changchun 130117, China.
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Kyalwazi B, Yau C, Campbell MJ, Yoshimatsu TF, Chien AJ, Wallace AM, Forero-Torres A, Pusztai L, Ellis ED, Albain KS, Blaes AH, Haley BB, Boughey JC, Elias AD, Clark AS, Isaacs CJ, Nanda R, Han HS, Yung RL, Tripathy D, Edmiston KK, Viscusi RK, Northfelt DW, Khan QJ, Asare SM, Wilson A, Hirst GL, Lu R, Symmans WF, Yee D, DeMichele AM, van ’t Veer LJ, Esserman LJ, Olopade OI. Race, Gene Expression Signatures, and Clinical Outcomes of Patients With High-Risk Early Breast Cancer. JAMA Netw Open 2023; 6:e2349646. [PMID: 38153734 PMCID: PMC10755617 DOI: 10.1001/jamanetworkopen.2023.49646] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 10/26/2023] [Indexed: 12/29/2023] Open
Abstract
Importance There has been little consideration of genomic risk of recurrence by breast cancer subtype despite evidence of racial disparities in breast cancer outcomes. Objective To evaluate associations between clinical trial end points, namely pathologic complete response (pCR) and distant recurrence-free survival (DRFS), and race and examine whether gene expression signatures are associated with outcomes by race. Design, Setting, and Participants This retrospective cohort study used data from the Investigation of Serial Studies to Predict Your Therapeutic Response With Imaging and Molecular Analysis 2 (I-SPY 2) multicenter clinical trial of neoadjuvant chemotherapy with novel agents and combinations for patients with previously untreated stage II/III breast cancer. Analyses were conducted of associations between race and short- and long-term outcomes, overall and by receptor subtypes, and their association with 28 expression biomarkers. The trial enrolled 990 female patients between March 30, 2010, and November 5, 2016, with a primary tumor size of 2.5 cm or greater and clinical or molecular high risk based on MammaPrint or hormone receptor (HR)-negative/ERBB2 (formerly HER2 or HER2/neu)-positive subtyping across 9 arms. This data analysis was performed between June 10, 2021, and October 20, 2022. Exposure Race, tumor receptor subtypes, and genomic biomarker expression of early breast cancer. Main Outcomes and Measures The primary outcomes were pCR and DRFS assessed by race, overall, and by tumor subtype using logistic regression and Cox proportional hazards regression models. The interaction between 28 expression biomarkers and race, considering pCR and DRFS overall and within subtypes, was also evaluated. Results The analytic sample included 974 participants (excluding 16 self-reporting as American Indian or Alaska Native, Native Hawaiian or Other Pacific Islander, or multiple races due to small sample sizes), including 68 Asian (7%), 120 Black (12%), and 786 White (81%) patients. Median (range) age at diagnosis was 47 (25-71) years for Asian, 49 (25-77) for Black, and 49 (23-73) years for White patients. The pCR rates were 32% (n = 22) for Asian, 30% for Black (n = 36), and 32% for White (n = 255) patients (P = .87). Black patients with HR-positive/ERBB2-negative tumors not achieving pCR had significantly worse DRFS than their White counterparts (hazard ratio, 2.28; 95% CI, 1.24-4.21; P = .01), with 5-year DRFS rates of 55% (n = 32) and 77% (n = 247), respectively. Black patients with HR-positive/ERBB2-negative tumors, compared with White patients, had higher expression of an interferon signature (mean [SD], 0.39 [0.87] and -0.10 [0.99]; P = .007) and, compared with Asian patients, had a higher mitotic score (mean [SD], 0.07 [1.08] and -0.69 [1.06]; P = .01) and lower estrogen receptor/progesterone receptor signature (mean [SD], 0.31 [0.90] and 1.08 [0.95]; P = .008). A transforming growth factor β signature had a significant association with race relative to pCR and DRFS, with a higher signature associated with lower pCR and worse DRFS outcomes among Black patients only. Conclusions and Relevance The findings show that women with early high-risk breast cancer who achieve pCR have similarly good outcomes regardless of race, but Black women with HR-positive/ERBB2-negative tumors without pCR may have worse DRFS than White women, highlighting the need to develop and test novel biomarker-informed therapies in diverse populations.
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Affiliation(s)
- Beverly Kyalwazi
- Center for Clinical Cancer Genetics and Global Health, The University of Chicago, Chicago, Illinois
- Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas
| | - Christina Yau
- Department of Surgery, University of California, San Francisco
| | | | - Toshio F. Yoshimatsu
- Center for Clinical Cancer Genetics and Global Health, The University of Chicago, Chicago, Illinois
- Department of Medicine, Section of Hematology/Oncology, The University of Chicago, Chicago, Illinois
| | - A. Jo Chien
- Department of Hematology Oncology and Surgery, University of California, San Francisco Helen Diller Comprehensive Cancer Center, San Francisco
| | - Anne M. Wallace
- Division of Breast Surgery and the Comprehensive Breast Health Center, University of California San Diego, La Jolla
| | | | - Lajos Pusztai
- Department of Medical Oncology, Yale School of Medicine, Yale University, New Haven, Connecticut
| | | | - Kathy S. Albain
- Division of Hematology-Oncology, Department of Medicine, University of Minnesota, Minneapolis
| | - Anne H. Blaes
- Division of Hematology-Oncology, Department of Medicine, University of Minnesota, Minneapolis
| | - Barbara B. Haley
- Division of Hematology-Oncology, University of Texas Southwestern Medical Center, Dallas
| | | | | | - Amy S. Clark
- Division of Hematology and Oncology, Department of Medicine, University of Pennsylvania, Perelman School of Medicine, Philadelphia
| | | | - Rita Nanda
- Department of Medicine, Section of Hematology/Oncology, The University of Chicago, Chicago, Illinois
| | - Hyo S. Han
- Department of Breast Oncology, Moffitt Cancer Center, Tampa, Florida
| | - Rachel L. Yung
- Department of Medicine, School of Medicine, University of Washington, Seattle
| | - Debasish Tripathy
- Division of Cancer Medicine, Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston
| | | | - Rebecca K. Viscusi
- Department of Surgery, University of Arizona College of Medicine, Tucson
| | | | - Qamar J. Khan
- Division of Medical Oncology, Department of Internal Medicine, University of Kansas Medical Center, Kansas City
| | - Smita M. Asare
- Quantum Leap Healthcare Collaborative, San Francisco, California
| | - Amy Wilson
- Quantum Leap Healthcare Collaborative, San Francisco, California
| | | | - Ruixiao Lu
- Quantum Leap Healthcare Collaborative, San Francisco, California
| | - William Fraser Symmans
- Division of Pathology and Laboratory Medicine, Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston
| | - Douglas Yee
- Division of Hematology-Oncology, Department of Medicine, University of Minnesota, Minneapolis
| | - Angela M. DeMichele
- Division of Hematology and Oncology, Department of Medicine, University of Pennsylvania, Perelman School of Medicine, Philadelphia
| | - Laura J. van ’t Veer
- Department of Laboratory Medicine, University of California, San Francisco Helen Diller Family Comprehensive Cancer Center, San Francisco
| | | | - Olufunmilayo I. Olopade
- Center for Clinical Cancer Genetics and Global Health, The University of Chicago, Chicago, Illinois
- Department of Medicine, Section of Hematology/Oncology, The University of Chicago, Chicago, Illinois
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Yang T, Li W, Huang T, Zhou J. Genetic Testing Enhances the Precision Diagnosis and Treatment of Breast Cancer. Int J Mol Sci 2023; 24:16607. [PMID: 38068930 PMCID: PMC10706486 DOI: 10.3390/ijms242316607] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Revised: 11/14/2023] [Accepted: 11/20/2023] [Indexed: 12/18/2023] Open
Abstract
The contemporary comprehension of breast cancer has progressed to the molecular level. As a heterogeneous malignancy, conventional pathological diagnosis and histological classification could no longer meet the needs of precisely managing breast cancer. Genetic testing based on gene expression profiles and gene mutations has emerged and substantially contributed to the precise diagnosis and treatment of breast cancer. Multigene assays (MGAs) are explored for early-stage breast cancer patients, aiding the selection of adjuvant therapy and predicting prognosis. For metastatic breast cancer patients, testing specific genes indicates potentially effective antitumor agents. In this review, genetic testing in early-stage and metastatic breast cancer is summarized, as well as the advantages and challenges of genetic testing in breast cancer.
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Affiliation(s)
| | | | - Tao Huang
- Department of Breast and Thyroid Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China (W.L.)
| | - Jun Zhou
- Department of Breast and Thyroid Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China (W.L.)
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Zou X, Liu Y, Wang M, Zou J, Shi Y, Su X, Xu J, Tong HHY, Ji Y, Gui L, Hao J. scCURE identifies cell types responding to immunotherapy and enables outcome prediction. CELL REPORTS METHODS 2023; 3:100643. [PMID: 37989083 PMCID: PMC10694528 DOI: 10.1016/j.crmeth.2023.100643] [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: 01/17/2023] [Revised: 07/17/2023] [Accepted: 10/23/2023] [Indexed: 11/23/2023]
Abstract
A deep understanding of immunotherapy response/resistance mechanisms and a highly reliable therapy response prediction are vital for cancer treatment. Here, we developed scCURE (single-cell RNA sequencing [scRNA-seq] data-based Changed and Unchanged cell Recognition during immunotherapy). Based on Gaussian mixture modeling, Kullback-Leibler (KL) divergence, and mutual nearest-neighbors criteria, scCURE can faithfully discriminate between cells affected or unaffected by immunotherapy intervention. By conducting scCURE analyses in melanoma and breast cancer immunotherapy scRNA-seq data, we found that the baseline profiles of specific CD8+ T and macrophage cells (identified by scCURE) can determine the way in which tumor microenvironment immune cells respond to immunotherapy, e.g., antitumor immunity activation or de-activation; therefore, these cells could be predictive factors for treatment response. In this work, we demonstrated that the immunotherapy-associated cell-cell heterogeneities revealed by scCURE can be utilized to integrate the therapy response mechanism study and prediction model construction.
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Affiliation(s)
- Xin Zou
- Center for Tumor Diagnosis & Therapy, Jinshan Hospital, Fudan University, Shanghai 201508, China; Department of Pathology, Jinshan Hospital, Fudan University, Shanghai 201508, China.
| | - Yujun Liu
- Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, China
| | - Miaochen Wang
- Department of Oral and Maxillofacial-Head & Neck Oncology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine; College of Stomatology, Shanghai Jiao Tong University; National Center for Stomatology; National Clinical Research Center for Oral Diseases; Shanghai Key Laboratory of Stomatology, Shanghai, China
| | - Jiawei Zou
- Institute of Clinical Science, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Yi Shi
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
| | - Xianbin Su
- Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai JiaoTong University, Shanghai, China
| | - Juan Xu
- Department of Stomatology, Sijing Hospital, Shanghai 201601, China
| | - Henry H Y Tong
- Centre for Artificial Intelligence Driven Drug Discovery, Faculty of Applied Sciences, Macao Polytechnic University, Macao SAR, China
| | - Yuan Ji
- Molecular Pathology Center, Department Pathology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Lv Gui
- Department of Pathology, Jinshan Hospital, Fudan University, Shanghai 201508, China.
| | - Jie Hao
- Institute of Clinical Science, Zhongshan Hospital, Fudan University, Shanghai 200032, China.
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Huang C, Deng M, Leng D, Sun B, Zheng P, Zhang XD. MIRS: An AI scoring system for predicting the prognosis and therapy of breast cancer. iScience 2023; 26:108322. [PMID: 38026206 PMCID: PMC10665820 DOI: 10.1016/j.isci.2023.108322] [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: 10/22/2022] [Revised: 09/25/2023] [Accepted: 10/20/2023] [Indexed: 12/01/2023] Open
Abstract
Tumor-infiltrating immune cells (TIICs) and metastasis are crucial characteristics for tumorigenesis. However, the potential role of their combination in breast cancer (BRCA) remains elusive. Herein, on the basis of quantifying TIICs and tumor metastasis together, we established a precise prognostic scoring system named metastatic and immunogenomic risk score (MIRS) using a neural network model. MIRS showed better performance when compared with other published signatures. MIRS stratifies patients into a high risk subtype (MIRShigh) and a low risk subtype (MIRSlow). The MIRShigh patients exhibit significantly lower survival rate compared with MIRSlow patients (P < 0.0001 ), higher response to chemotherapy, but lower response to immunotherapy. Conversely, higher infiltration level of TIICs and significantly prolonged survival (P = 0.029 ) are observed in MIRSlow patients, indicating sensitive response in immunotherapy. This work presents a promising indicator to guide treatment options of the BRCA population and provides a predicted webtool that is almost universally applicable to BRCA patients.
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Affiliation(s)
- Chen Huang
- Dr. Neher’s Biophysics Laboratory for Innovative Drug Discovery, Macau University of Science and Technology, Macau SAR 999078, China
- State Key laboratory of Quality Research in Chinese Medicine, Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, Macau SAR 999078, China
| | - Min Deng
- CRDA, Faculty of Health Sciences, University of Macau, Taipa, Macau SAR 999078, China
| | - Dongliang Leng
- CRDA, Faculty of Health Sciences, University of Macau, Taipa, Macau SAR 999078, China
| | - Baoqing Sun
- Department of Allergy and Clinical Immunology, State Key Laboratory of Respiratory Disease, National Clinical Research Center of Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou 511436, China
| | - Peiyan Zheng
- Department of Allergy and Clinical Immunology, State Key Laboratory of Respiratory Disease, National Clinical Research Center of Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou 511436, China
| | - Xiaohua Douglas Zhang
- Department of Biostatistics, College of Public Health, University of Kentucky, Lexington, KY 40536, USA
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Zheng K, Hai Y, Xi Y, Zhang Y, Liu Z, Chen W, Hu X, Zou X, Hao J. Integrative multi-omics analysis unveils stemness-associated molecular subtypes in prostate cancer and pan-cancer: prognostic and therapeutic significance. J Transl Med 2023; 21:789. [PMID: 37936202 PMCID: PMC10629187 DOI: 10.1186/s12967-023-04683-6] [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: 08/21/2023] [Accepted: 10/29/2023] [Indexed: 11/09/2023] Open
Abstract
BACKGROUND Prostate cancer (PCA) is the fifth leading cause of cancer-related deaths worldwide, with limited treatment options in the advanced stages. The immunosuppressive tumor microenvironment (TME) of PCA results in lower sensitivity to immunotherapy. Although molecular subtyping is expected to offer important clues for precision treatment of PCA, there is currently a shortage of dependable and effective molecular typing methods available for clinical practice. Therefore, we aim to propose a novel stemness-based classification approach to guide personalized clinical treatments, including immunotherapy. METHODS An integrative multi-omics analysis of PCA was performed to evaluate stemness-level heterogeneities. Unsupervised hierarchical clustering was used to classify PCAs based on stemness signature genes. To make stemness-based patient classification more clinically applicable, a stemness subtype predictor was jointly developed by using four PCA datasets and 76 machine learning algorithms. RESULTS We identified stemness signatures of PCA comprising 18 signaling pathways, by which we classified PCA samples into three stemness subtypes via unsupervised hierarchical clustering: low stemness (LS), medium stemness (MS), and high stemness (HS) subtypes. HS patients are sensitive to androgen deprivation therapy, taxanes, and immunotherapy and have the highest stemness, malignancy, tumor mutation load (TMB) levels, worst prognosis, and immunosuppression. LS patients are sensitive to platinum-based chemotherapy but resistant to immunotherapy and have the lowest stemness, malignancy, and TMB levels, best prognosis, and the highest immune infiltration. MS patients represent an intermediate status of stemness, malignancy, and TMB levels with a moderate prognosis. We further demonstrated that these three stemness subtypes are conserved across pan-tumor. Additionally, the 9-gene stemness subtype predictor we developed has a comparable capability to 18 signaling pathways to make tumor diagnosis and to predict tumor recurrence, metastasis, progression, prognosis, and efficacy of different treatments. CONCLUSIONS The three stemness subtypes we identified have the potential to be a powerful tool for clinical tumor molecular classification in PCA and pan-cancer, and to guide the selection of immunotherapy or other sensitive treatments for tumor patients.
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Affiliation(s)
- Kun Zheng
- Department of Urology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China
| | - Youlong Hai
- Department of Urology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China
| | - Yue Xi
- Department of Reproductive Medicine, Central Hospital Affiliated to Shandong First Medical University, Jinan, 250013, Shandong, China
| | - Yukun Zhang
- Beijing University of Chinese Medicine East Hospital, Zaozhuang Hospital, Zaozhuang, 277000, Shandong, China
| | - Zheqi Liu
- Department of Oral and Maxillofacial Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Wantao Chen
- Shanghai Key Laboratory of Stomatology & Shanghai Research Institute of Stomatology, National Clinical Research Center of Stomatology, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China
| | - Xiaoyong Hu
- Department of Urology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China.
| | - Xin Zou
- Jinshan Hospital Center for Tumor Diagnosis & Therapy, Jinshan Hospital, Fudan University, Shanghai, 201508, China.
- Department of Pathology, Jinshan Hospital, Fudan University, Shanghai, 201508, China.
| | - Jie Hao
- Institute of Clinical Science, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
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Castellano G, Giugliano F, Curigliano G, Marra A. Clinical utility of genomic signatures for the management of early and metastatic triple-negative breast cancer. Curr Opin Oncol 2023; 35:479-490. [PMID: 37621170 DOI: 10.1097/cco.0000000000000989] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/26/2023]
Abstract
PURPOSE OF REVIEW This comprehensive review aims to provide timely and relevant insights into the current therapeutic landscape for triple-negative breast cancer (TNBC) and the molecular features underlying this subtype. It emphasizes the need for more reliable biomarkers to refine prognostication and optimize therapy, considering the aggressive nature of TNBC and its limited targeted treatment options. RECENT FINDINGS The review explores the multidisciplinary management of early TNBC, which typically involves systemic chemotherapy, surgery, and radiotherapy. It highlights the emergence of immune checkpoint inhibitors (ICIs), poly(ADP-ribose) polymerase (PARP) inhibitors, and antibody-drug conjugates (ADCs) as promising therapeutic strategies for TNBC. Recent clinical trials investigating the use of ICIs in combination with chemotherapy and the approval of pembrolizumab and atezolizumab for PD-L1-positive metastatic TNBC are discussed. The efficacy of PARP inhibitors and ADCs in treating TNBC patients with specific genetic alterations is also highlighted. SUMMARY The findings discussed in this review have significant implications for clinical practice and research in TNBC. The identification of distinct molecular subtypes through gene expression profiling has enabled a better understanding of TNBC heterogeneity and its clinical implications. This knowledge has the potential to guide treatment decisions, as different subtypes display varying responses to neoadjuvant chemotherapy. Furthermore, the review emphasizes the importance of developing reliable genomic and transcriptomic signatures as biomarkers to refine patient prognostication and optimize therapy selection in TNBC. Integrating these signatures into clinical practice may lead to more personalized treatment approaches, improving outcomes for TNBC patients.
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Affiliation(s)
- Grazia Castellano
- Division of New Drugs and Early Drug Development, European Institute of Oncology IRCCS
- Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
| | - Federica Giugliano
- Division of New Drugs and Early Drug Development, European Institute of Oncology IRCCS
- Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
| | - Giuseppe Curigliano
- Division of New Drugs and Early Drug Development, European Institute of Oncology IRCCS
- Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
| | - Antonio Marra
- Division of New Drugs and Early Drug Development, European Institute of Oncology IRCCS
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48
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Zhang J, Teng X, Zhang X, Lam SK, Lin Z, Liang Y, Yu H, Siu SWK, Chang ATY, Zhang H, Kong FM, Yang R, Cai J. Comparing effectiveness of image perturbation and test retest imaging in improving radiomic model reliability. Sci Rep 2023; 13:18263. [PMID: 37880324 PMCID: PMC10600245 DOI: 10.1038/s41598-023-45477-6] [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: 03/13/2023] [Accepted: 10/19/2023] [Indexed: 10/27/2023] Open
Abstract
Image perturbation is a promising technique to assess radiomic feature repeatability, but whether it can achieve the same effect as test-retest imaging on model reliability is unknown. This study aimed to compare radiomic model reliability based on repeatable features determined by the two methods using four different classifiers. A 191-patient public breast cancer dataset with 71 test-retest scans was used with pre-determined 117 training and 74 testing samples. We collected apparent diffusion coefficient images and manual tumor segmentations for radiomic feature extraction. Random translations, rotations, and contour randomizations were performed on the training images, and intra-class correlation coefficient (ICC) was used to filter high repeatable features. We evaluated model reliability in both internal generalizability and robustness, which were quantified by training and testing AUC and prediction ICC. Higher testing performance was found at higher feature ICC thresholds, but it dropped significantly at ICC = 0.95 for the test-retest model. Similar optimal reliability can be achieved with testing AUC = 0.7-0.8 and prediction ICC > 0.9 at the ICC threshold of 0.9. It is recommended to include feature repeatability analysis using image perturbation in any radiomic study when test-retest is not feasible, but care should be taken when deciding the optimal feature repeatability criteria.
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Affiliation(s)
- Jiang Zhang
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Y920, Lee Shau Kee Building, Hung Hom, Kowloon, Hong Kong, China
| | - Xinzhi Teng
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Y920, Lee Shau Kee Building, Hung Hom, Kowloon, Hong Kong, China
| | - Xinyu Zhang
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Y920, Lee Shau Kee Building, Hung Hom, Kowloon, Hong Kong, China
| | - Sai-Kit Lam
- Department of Biomedical Engineering, Faculty of Engineering, The Hong Kong Polytechnic University, Hong Kong, China
- Research Institute for Smart Ageing, The Hong Kong Polytechnic University, Hong Kong, China
| | - Zhongshi Lin
- Shenzhen Institute for Drug Control (Shenzhen Testing Center of Medical Devices), Shenzhen, China
| | - Yongyi Liang
- Shenzhen Institute for Drug Control (Shenzhen Testing Center of Medical Devices), Shenzhen, China
| | - Hao Yu
- Institute of Biomedical and Health Engineering, Chinese Academy of Sciences Shenzhen Institutes of Advanced Technology, Shenzhen, China
| | - Steven Wai Kwan Siu
- Department of Clinical Oncology, The University of Hong Kong, Hong Kong, China
| | - Amy Tien Yee Chang
- Department of Clinical Oncology, The University of Hong Kong, Hong Kong, China
| | - Hua Zhang
- Beijing Linking Medical Technology Co., Ltd., Beijing, China
| | - Feng-Ming Kong
- Department of Clinical Oncology, The University of Hong Kong, Hong Kong, China
- Department of Clinical Oncology, The University of Hong Kong-Shenzhen Hospital, Shenzhen, China
| | - Ruijie Yang
- Department of Radiation Oncology, Cancer Center, Peking University Third Hospital, Beijing, China
| | - Jing Cai
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Y920, Lee Shau Kee Building, Hung Hom, Kowloon, Hong Kong, China.
- Research Institute for Smart Ageing, The Hong Kong Polytechnic University, Hong Kong, China.
- The Hong Kong Polytechnic University Shenzhen Research Institute, Shenzhen, China.
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49
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Zhao S, Chen DP, Fu T, Yang JC, Ma D, Zhu XZ, Wang XX, Jiao YP, Jin X, Xiao Y, Xiao WX, Zhang HY, Lv H, Madabhushi A, Yang WT, Jiang YZ, Xu J, Shao ZM. Single-cell morphological and topological atlas reveals the ecosystem diversity of human breast cancer. Nat Commun 2023; 14:6796. [PMID: 37880211 PMCID: PMC10600153 DOI: 10.1038/s41467-023-42504-y] [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: 12/15/2022] [Accepted: 10/12/2023] [Indexed: 10/27/2023] Open
Abstract
Digital pathology allows computerized analysis of tumor ecosystem using whole slide images (WSIs). Here, we present single-cell morphological and topological profiling (sc-MTOP) to characterize tumor ecosystem by extracting the features of nuclear morphology and intercellular spatial relationship for individual cells. We construct a single-cell atlas comprising 410 million cells from 637 breast cancer WSIs and dissect the phenotypic diversity within tumor, inflammatory and stroma cells respectively. Spatially-resolved analysis identifies recurrent micro-ecological modules representing locoregional multicellular structures and reveals four breast cancer ecotypes correlating with distinct molecular features and patient prognosis. Further analysis with multiomics data uncovers clinically relevant ecosystem features. High abundance of locally-aggregated inflammatory cells indicates immune-activated tumor microenvironment and favorable immunotherapy response in triple-negative breast cancers. Morphological intratumor heterogeneity of tumor nuclei correlates with cell cycle pathway activation and CDK inhibitors responsiveness in hormone receptor-positive cases. sc-MTOP enables using WSIs to characterize tumor ecosystems at the single-cell level.
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Affiliation(s)
- Shen Zhao
- Key Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, China
| | - De-Pin Chen
- Institute for Artificial Intelligence in Medicine, School of Artificial Intelligence, Nanjing University of Information Science and Technology, Nanjing, China
| | - Tong Fu
- Key Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Jing-Cheng Yang
- Key Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, China
- Greater Bay Area Institute of Precision Medicine, Guangzhou, China
| | - Ding Ma
- Key Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Xiu-Zhi Zhu
- Key Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Xiang-Xue Wang
- Institute for Artificial Intelligence in Medicine, School of Artificial Intelligence, Nanjing University of Information Science and Technology, Nanjing, China
| | - Yi-Ping Jiao
- Institute for Artificial Intelligence in Medicine, School of Artificial Intelligence, Nanjing University of Information Science and Technology, Nanjing, China
| | - Xi Jin
- Key Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Yi Xiao
- Key Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Wen-Xuan Xiao
- Key Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Hu-Yunlong Zhang
- Key Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Hong Lv
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Anant Madabhushi
- Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA
- Atlanta Veterans Affairs Medical Center, Atlanta, GA, USA
| | - Wen-Tao Yang
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China.
| | - Yi-Zhou Jiang
- Key Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.
| | - Jun Xu
- Institute for Artificial Intelligence in Medicine, School of Artificial Intelligence, Nanjing University of Information Science and Technology, Nanjing, China.
| | - Zhi-Ming Shao
- Key Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.
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50
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Debets DO, Stecker KE, Piskopou A, Liefaard MC, Wesseling J, Sonke GS, Lips EH, Altelaar M. Deep (phospho)proteomics profiling of pre- treatment needle biopsies identifies signatures of treatment resistance in HER2 + breast cancer. Cell Rep Med 2023; 4:101203. [PMID: 37794585 PMCID: PMC10591042 DOI: 10.1016/j.xcrm.2023.101203] [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: 12/21/2022] [Revised: 07/06/2023] [Accepted: 08/31/2023] [Indexed: 10/06/2023]
Abstract
Patients with early-stage HER2-overexpressing breast cancer struggle with treatment resistance in 20%-40% of cases. More information is needed to predict HER2 therapy response and resistance in vivo. In this study, we perform (phospho)proteomics analysis of pre-treatment HER2+ needle biopsies of early-stage invasive breast cancer to identify molecular signatures predictive of treatment response to trastuzumab, pertuzumab, and chemotherapy. Our data show that accurate quantification of the estrogen receptor (ER) and HER2 biomarkers, combined with the assessment of associated biological features, has the potential to enable better treatment outcome prediction. In addition, we identify cellular mechanisms that potentially precondition tumors to resist therapy. We find proteins with expression changes that correlate with resistance and constitute to a strong predictive signature for treatment success in our patient cohort. Our results highlight the multifactorial nature of drug resistance in vivo and demonstrate the necessity of deep tumor profiling.
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Affiliation(s)
- Donna O Debets
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, 3584 Utrecht, the Netherlands
| | - Kelly E Stecker
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, 3584 Utrecht, the Netherlands
| | - Anastasia Piskopou
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, 3584 Utrecht, the Netherlands
| | - Marte C Liefaard
- Department of Molecular Pathology, The Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Jelle Wesseling
- Department of Molecular Pathology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Department of Pathology, Leiden University Medical Center, Leiden, the Netherlands
| | - Gabe S Sonke
- Department of Medical Oncology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Department of Medical Oncology, University of Amsterdam, Amsterdam, the Netherlands
| | - Esther H Lips
- Department of Molecular Pathology, The Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Maarten Altelaar
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, 3584 Utrecht, the Netherlands.
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