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Mo Y, Liu J, Hu Y, Peng X, Liu H. Development and Validation of a Predictive Model for Resistance to Platinum-Based Chemotherapy in Patients with Ovarian Cancer through Proteomic Analysis. J Proteome Res 2024; 23:4648-4657. [PMID: 39253780 DOI: 10.1021/acs.jproteome.4c00558] [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: 09/11/2024]
Abstract
Platinum resistance in ovarian cancer poses a significant challenge, substantially impacting patient outcomes. Developing an accurate predictive model is crucial for improving clinical decision-making and guiding treatment strategies. Proteomic data from 217 high-grade serous ovarian cancer (HGSOC) biospecimens obtained from JHU, PNNL, and PTRC were used to construct a prediction model for identifying individuals who are resistant to platinum-based chemotherapy. A total of 6437 common proteins were detected across all data sets, with 26 proteins overlapping between the development cohorts JHU and PNNL. Using LASSO and logistic regression analysis, a six-protein model (P31323_PRKAR2B, Q13309_SKP2, Q14997_PSME4, Q6ZRP7_QSOX2, Q7LGA3_HS2ST1, and Q7Z2Z2_EFL1) was developed, which accurately predicted platinum resistance, with an AUC of 0.964 (95% CI, 0.929-0.999). Internal validation by resampling resulted in a C-index of 0.972 (95% CI 0.894-0.988). External validation performed on the PTRC cohort achieved an AUC of 0.855 (95% CI 0.748-0.963). Calibration curves showed good consistency, and DCA indicated superior clinical utility. The model also performed well in predicting PFS and OS at various time points. Based on these proteins, our predictive model can precisely predict platinum response and survival outcomes in HGSOC patients, which can assist clinicians in promptly identifying potentially platinum-resistant individuals.
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Affiliation(s)
- Yanqun Mo
- Department of Gynecology and Obstetrics, XiangYa Hospital Central South University, No. 87 XiangYa Road, Changsha, Hunan 410008, China
| | - Junliang Liu
- Department of Gynecology and Obstetrics, XiangYa Hospital Central South University, No. 87 XiangYa Road, Changsha, Hunan 410008, China
| | - Yi Hu
- Department of Gynecology and Obstetrics, XiangYa Hospital Central South University, No. 87 XiangYa Road, Changsha, Hunan 410008, China
| | - Xiaotong Peng
- Shanghai Key Laboratory of Maternal-Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, No. 2699, Gaoke West Road, Shanghai 200092, China
| | - Huining Liu
- Department of Gynecology and Obstetrics, XiangYa Hospital Central South University, No. 87 XiangYa Road, Changsha, Hunan 410008, China
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De Silva S, Alli-Shaik A, Gunaratne J. Machine Learning-Enhanced Extraction of Biomarkers for High-Grade Serous Ovarian Cancer from Proteomics Data. Sci Data 2024; 11:685. [PMID: 38918474 PMCID: PMC11199488 DOI: 10.1038/s41597-024-03536-1] [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: 11/27/2023] [Accepted: 06/17/2024] [Indexed: 06/27/2024] Open
Abstract
Comprehensive biomedical proteomic datasets are accumulating exponentially, warranting robust analytics to deconvolute them for identifying novel biological insights. Here, we report a strategic machine learning (ML)-based feature extraction workflow that was applied to unveil high-performing protein markers for high-grade serous ovarian carcinoma (HGSOC) from publicly available ovarian cancer tissue and serum proteomics datasets. Diagnosis of HGSOC, an aggressive form of ovarian cancer, currently relies on diagnostic methods based on tissue biopsy and/or non-specific biomarkers such as the cancer antigen 125 (CA125) and human epididymis protein 4 (HE4). Our newly developed ML-based approach enabled the identification of new serum proteomic biomarkers for HGSOC. The performance verification of these marker combinations using two independent cohorts affirmed their outperformance against known biomarkers for ovarian cancer including clinically used serum markers with >97% AUC. Our analysis also added novel biological insights such as enriched cancer-related processes associated with HGSOC.
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Affiliation(s)
- Senuri De Silva
- Institute of Molecular and Cell Biology (IMCB), Agency for Science, Technology and Research (A*STAR), Singapore, 138673, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 117594, Singapore
| | - Asfa Alli-Shaik
- Institute of Molecular and Cell Biology (IMCB), Agency for Science, Technology and Research (A*STAR), Singapore, 138673, Singapore
| | - Jayantha Gunaratne
- Institute of Molecular and Cell Biology (IMCB), Agency for Science, Technology and Research (A*STAR), Singapore, 138673, Singapore.
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 117594, Singapore.
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3
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Yang J, Wang C, Zhang Y, Cheng S, Wu M, Gu S, Xu S, Wu Y, Sheng J, Voon DCC, Wang Y. Clinical significance and immune infiltration analyses of a novel coagulation-related signature in ovarian cancer. Cancer Cell Int 2023; 23:232. [PMID: 37803446 PMCID: PMC10559580 DOI: 10.1186/s12935-023-03040-3] [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: 06/12/2023] [Accepted: 08/25/2023] [Indexed: 10/08/2023] Open
Abstract
Ovarian cancer (OV) is the most lethal gynecological malignancies worldwide. The coagulation cascade could induce tumor cell infiltration and contribute to OV progression. However, coagulation-related gene (CRG) signature for OV prognosis hasn't been determined yet. In this study, we evaluated the prognostic value of coagulation scores through receiver operating characteristics (ROC) analysis and K-M curves, among OV patients at our institution. Based on the transcriptome data of TCGA-OV cohort, we stratified two coagulation-related subtypes with distinct differences in prognosis and tumor immune microenvironment (p < 0.05). Moreover, from the 6406 differentially-expressed genes (DEGs) between the GTEx (n = 180) and TCGA-OV cohorts (n = 376), we identified 138 potential CRGs. Through LASSO-Cox algorithm, we finally distinguished a 3-gene signature (SERPINA10, CD38, and ZBTB16), with promising prognostic ability in both TCGA (p < 0.001) and ICGC cohorts (p = 0.040). Stepwise, we constructed a nomogram based on the clinical features and coagulation-related signature for overall survival prediction, with the C-index of 0.6761, which was evaluated by calibration curves. Especially, based on tissue microarrays analysis, Quantitative real-time fluorescence PCR (qRT-PCR), and Western Blot, we found that aberrant upregulation of CRGs was related to poor prognosis in OV at both mRNA and protein level (p < 0.05). Collectively, the coagulation-related signature was a robust prognostic biomarker, which could provide therapeutic benefits for chemotherapy/immunotherapy and assist clinical decision in OV patients.
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Affiliation(s)
- Jiani Yang
- Department of Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, 200092 China
| | - Chao Wang
- Department of Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, 200092 China
| | - Yue Zhang
- Department of Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, 200092 China
| | - Shanshan Cheng
- Department of Obstetrics and Gynecology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
| | - Meixuan Wu
- Department of Obstetrics and Gynecology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
| | - Sijia Gu
- Department of Obstetrics and Gynecology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
| | - Shilin Xu
- Department of Obstetrics and Gynecology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
| | - Yongsong Wu
- Department of Obstetrics and Gynecology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
| | - Jindan Sheng
- Department of Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, 200092 China
| | - Dominic Chih-Cheng Voon
- Cancer Research Institute, Kanazawa University, Kanazawa, Ishikawa 9201192 Japan
- Institute of Frontier Sciences Initiative, Kanazawa University, Kanazawa, Ishikawa 9201192 Japan
| | - Yu Wang
- Department of Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, 200092 China
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4
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Nelson L, Barnes BM, Tighe A, Littler S, Coulson-Gilmer C, Golder A, Desai S, Morgan RD, McGrail JC, Taylor SS. Exploiting a living biobank to delineate mechanisms underlying disease-specific chromosome instability. Chromosome Res 2023; 31:21. [PMID: 37592171 PMCID: PMC10435626 DOI: 10.1007/s10577-023-09731-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 07/25/2023] [Accepted: 07/30/2023] [Indexed: 08/19/2023]
Abstract
Chromosome instability (CIN) is a cancer hallmark that drives tumour heterogeneity, phenotypic adaptation, drug resistance and poor prognosis. High-grade serous ovarian cancer (HGSOC), one of the most chromosomally unstable tumour types, has a 5-year survival rate of only ~30% - largely due to late diagnosis and rapid development of drug resistance, e.g., via CIN-driven ABCB1 translocations. However, CIN is also a cell cycle vulnerability that can be exploited to specifically target tumour cells, illustrated by the success of PARP inhibitors to target homologous recombination deficiency (HRD). However, a lack of appropriate models with ongoing CIN has been a barrier to fully exploiting disease-specific CIN mechanisms. This barrier is now being overcome with the development of patient-derived cell cultures and organoids. In this review, we describe our progress building a Living Biobank of over 120 patient-derived ovarian cancer models (OCMs), predominantly from HGSOC. OCMs are highly purified tumour fractions with extensive proliferative potential that can be analysed at early passage. OCMs have diverse karyotypes, display intra- and inter-patient heterogeneity and mitotic abnormality rates far higher than established cell lines. OCMs encompass a broad-spectrum of HGSOC hallmarks, including a range of p53 alterations and BRCA1/2 mutations, and display drug resistance mechanisms seen in the clinic, e.g., ABCB1 translocations and BRCA2 reversion. OCMs are amenable to functional analysis, drug-sensitivity profiling, and multi-omics, including single-cell next-generation sequencing, and thus represent a platform for delineating HGSOC-specific CIN mechanisms. In turn, our vision is that this understanding will inform the design of new therapeutic strategies.
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Affiliation(s)
- Louisa Nelson
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Cancer Research Centre, Wilmslow Road, Manchester, M20 4GJ, UK
| | - Bethany M Barnes
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Cancer Research Centre, Wilmslow Road, Manchester, M20 4GJ, UK
| | - Anthony Tighe
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Cancer Research Centre, Wilmslow Road, Manchester, M20 4GJ, UK
| | - Samantha Littler
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Cancer Research Centre, Wilmslow Road, Manchester, M20 4GJ, UK
| | - Camilla Coulson-Gilmer
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Cancer Research Centre, Wilmslow Road, Manchester, M20 4GJ, UK
| | - Anya Golder
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Cancer Research Centre, Wilmslow Road, Manchester, M20 4GJ, UK
| | - Sudha Desai
- Department of Histopathology, The Christie NHS Foundation Trust, Wilmslow Rd, Manchester, M20 4BX, UK
| | - Robert D Morgan
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Cancer Research Centre, Wilmslow Road, Manchester, M20 4GJ, UK
- Department of Medical Oncology, The Christie NHS Foundation Trust, Wilmslow Road, Manchester, M20 4BX, UK
| | - Joanne C McGrail
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Cancer Research Centre, Wilmslow Road, Manchester, M20 4GJ, UK
| | - Stephen S Taylor
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Cancer Research Centre, Wilmslow Road, Manchester, M20 4GJ, UK.
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Proteomic landscape of the extracellular matrix in the fibrotic kidney. Kidney Int 2023; 103:1063-1076. [PMID: 36805449 DOI: 10.1016/j.kint.2023.01.021] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Revised: 01/14/2023] [Accepted: 01/20/2023] [Indexed: 02/19/2023]
Abstract
The extracellular matrix (ECM) is a complex three-dimensional network of proteins surrounding cells, forming a niche that controls cell adhesion, proliferation, migration and differentiation. The ECM network provides an architectural scaffold for surrounding cells and undergoes dynamic changes in composition and contents during the evolution of chronic kidney disease (CKD). Here, we unveiled the proteomic landscape of the ECM by delineating proteome-wide and ECM-specific alterations in normal and fibrotic kidneys. Decellularized kidney tissue scaffolds were made and subjected to proteomic profiling by liquid chromatography with tandem mass spectrometry. A total of 172 differentially expressed proteins were identified in these scaffolds from mice with CKD. Through bioinformatics analysis and experimental validation, we identified a core set of nine signature proteins, which could play a role in establishing an oxidatively stressed, profibrotic, proinflammatory and antiangiogenetic microenvironment. Among these nine proteins, glutathione peroxidase 3 (GPX3) was the only protein with downregulated expression during CKD. Knockdown of GPX3 in vivo augmented ECM expression and aggravated kidney fibrotic lesions after obstructive injury. Transcriptomic profiling revealed that GPX3 depletion resulted in an altered expression of the genes enriched in hypoxia pathway. Knockdown of GPX3 induced NADPH oxidase 2 expression, promoted kidney generation of reactive oxygen species and activated p38 mitogen-activated protein kinase. Conversely, overexpression of exogenous GPX3 alleviated kidney fibrosis, inhibited NADPH oxidase 2 and p38 mitogen-activated protein kinase. These findings suggest that oxidative stress is a pivotal element of the fibrogenic microenvironment. Thus, our studies represent a comprehensive proteomic characterization of the ECM in the fibrotic kidney and provide novel insights into molecular composition of the fibrogenic microenvironment.
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Brown Y, Hua S, Tanwar PS. Extracellular Matrix in High-Grade Serous Ovarian Cancer: Advances in Understanding of Carcinogenesis and Cancer Biology. Matrix Biol 2023; 118:16-46. [PMID: 36781087 DOI: 10.1016/j.matbio.2023.02.004] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2022] [Revised: 01/20/2023] [Accepted: 02/08/2023] [Indexed: 02/13/2023]
Abstract
High-grade serous ovarian cancer (HGSOC) is notoriously known as the "silent killer" of post-menopausal women as it has an insidious progression and is the deadliest gynaecological cancer. Although a dual origin of HGSOC is now widely accepted, there is growing evidence that most cases of HGSOC originate from the fallopian tube epithelium. In this review, we will address the fallopian tube origin and involvement of the extracellular matrix (ECM) in HGSOC development. There is limited research on the role of ECM at the earliest stages of HGSOC carcinogenesis. Here we aim to synthesise current understanding on the contribution of ECM to each stage of HGSOC development and progression, beginning at serous tubal intraepithelial carcinoma (STIC) precursor lesions and proceeding across key events including dissemination of tumourigenic fallopian tube epithelial cells to the ovary, survival of these cells in peritoneal fluid as multicellular aggregates, and colonisation of the ovary. Likewise, as part of the metastatic series of events, serous ovarian cancer cells survive travel in peritoneal fluid, attach to, migrate across the mesothelium and invade into the sub-mesothelial matrix of secondary sites in the peritoneal cavity. Halting cancer at the pre-metastatic stage and finding ways to stop the dissemination of ovarian cancer cells from the primary site is critical for improving patient survival. The development of drug resistance also contributes to poor survival statistics in HGSOC. In this review, we provide an update on the involvement of the ECM in metastasis and drug resistance in HGSOC. Interplay between different cell-types, growth factor gradients as well as evolving ECM composition and organisation, creates microenvironment conditions that promote metastatic progression and drug resistance of ovarian cancer cells. By understanding ECM involvement in the carcinogenesis and chemoresistance of HGSOC, this may prompt ideas for further research for developing new early diagnostic tests and therapeutic strategies for HGSOC with the end goal of improving patient health outcomes.
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Affiliation(s)
- Yazmin Brown
- Global Centre for Gynaecological Diseases, School of Biomedical Sciences and Pharmacy, University of Newcastle, Callaghan, New South Wales, Australia.; Cancer Detection and Therapy Research Program, Hunter Medical Research Institute, New Lambton Heights, NSW, Australia..
| | - Susan Hua
- Therapeutic Targeting Research Group, School of Biomedical Sciences and Pharmacy, University of Newcastle, Callaghan, NSW, Australia.; Precision Medicine Research Program, Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
| | - Pradeep S Tanwar
- Global Centre for Gynaecological Diseases, School of Biomedical Sciences and Pharmacy, University of Newcastle, Callaghan, New South Wales, Australia.; Cancer Detection and Therapy Research Program, Hunter Medical Research Institute, New Lambton Heights, NSW, Australia..
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7
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Li W, Li M, Zhang X, Yue S, Xu Y, Jian W, Qin Y, Lin L, Liu W. Improved profiling of low molecular weight serum proteome for gastric carcinoma by data-independent acquisition. Anal Bioanal Chem 2022; 414:6403-6417. [PMID: 35773495 DOI: 10.1007/s00216-022-04196-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Revised: 06/06/2022] [Accepted: 06/22/2022] [Indexed: 11/27/2022]
Abstract
Low molecular weight proteins (LMWPs) in the bloodstream participate in various biological processes and are closely associated with disease status, whereas identification of serous LMWPs remains a great technical challenge due to the wide dynamic range of protein components. In this study, we constructed an integrated LMWP library by combining the LMWPs obtained by three enrichment methods (50% ACN, 20% ACN + 20 mM ABC, and 30 kDa) and their fractions identified by the data-dependent acquisition method. With this newly constructed library, we comprehensively profiled LMWPs in serum using data-independent acquisition and reliably achieved quantitative results for 75% serous LMWPs. When applying this strategy to quantify LMWPs in human serum samples, we could identify 405 proteins on average per sample, of which 136 proteins were with a MW less than 30 kDa and 293 proteins were with a MW less than 65 kDa. Of note, pre- and post-operative gastric carcinoma (GC) patients showed differentially expressed serous LWMPs, which was also different from the pattern of LWMP expression in healthy controls. In conclusion, our results showed that LMWPs could efficiently distinguish GC patients from healthy controls as well as between pre- and post-operative statuses, and more importantly, our newly developed LMWP profiling platform could be used to discover candidate LMWP biomarkers for disease diagnosis and status monitoring.
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Affiliation(s)
- Weifeng Li
- The Central Laboratory, Shenzhen Second People's Hospital/the First Affiliated Hospital of Shenzhen University, Shenzhen, 518035, China
| | - Mengna Li
- The Central Laboratory, Shenzhen Second People's Hospital/the First Affiliated Hospital of Shenzhen University, Shenzhen, 518035, China
| | - Xiaoli Zhang
- The Central Laboratory, Shenzhen Second People's Hospital/the First Affiliated Hospital of Shenzhen University, Shenzhen, 518035, China
| | - Siqin Yue
- The Central Laboratory, Shenzhen Second People's Hospital/the First Affiliated Hospital of Shenzhen University, Shenzhen, 518035, China
| | - Yun Xu
- The Central Laboratory, Shenzhen Second People's Hospital/the First Affiliated Hospital of Shenzhen University, Shenzhen, 518035, China
| | - Wenjing Jian
- The Central Laboratory, Shenzhen Second People's Hospital/the First Affiliated Hospital of Shenzhen University, Shenzhen, 518035, China
| | - Yin Qin
- Department of Gastrointestinal Surgery, Shenzhen Second People's Hospital/the First Affiliated Hospital of Shenzhen University, Shenzhen, 518035, China.
| | - Lin Lin
- Sustech Core Research Facilities, Southern University of Science and Technology, Shenzhen, 518055, China.
| | - Wenlan Liu
- The Central Laboratory, Shenzhen Second People's Hospital/the First Affiliated Hospital of Shenzhen University, Shenzhen, 518035, China.
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Belotti Y, Lim EH, Lim CT. The Role of the Extracellular Matrix and Tumor-Infiltrating Immune Cells in the Prognostication of High-Grade Serous Ovarian Cancer. Cancers (Basel) 2022; 14:404. [PMID: 35053566 PMCID: PMC8773831 DOI: 10.3390/cancers14020404] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 01/05/2022] [Accepted: 01/11/2022] [Indexed: 12/12/2022] Open
Abstract
Ovarian cancer is the eighth global leading cause of cancer-related death among women. The most common form is the high-grade serous ovarian carcinoma (HGSOC). No further improvements in the 5-year overall survival have been seen over the last 40 years since the adoption of platinum- and taxane-based chemotherapy. Hence, a better understanding of the mechanisms governing this aggressive phenotype would help identify better therapeutic strategies. Recent research linked onset, progression, and response to treatment with dysregulated components of the tumor microenvironment (TME) in many types of cancer. In this study, using bioinformatic approaches, we identified a 19-gene TME-related HGSOC prognostic genetic panel (19 prognostic genes (PLXNB2, HMCN2, NDNF, NTN1, TGFBI, CHAD, CLEC5A, PLXNA1, CST9, LOXL4, MMP17, PI3, PRSS1, SERPINA10, TLL1, CBLN2, IL26, NRG4, and WNT9A) by assessing the RNA sequencing data of 342 tumors available in the TCGA database. Using machine learning, we found that specific patterns of infiltrating immune cells characterized each risk group. Furthermore, we demonstrated the predictive potential of our risk score across different platforms and its improved prognostic performance compared with other gene panels.
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Affiliation(s)
- Yuri Belotti
- Institute for Health Innovation and Technology, National University of Singapore, 14 Medical Drive, Singapore 117599, Singapore;
| | - Elaine Hsuen Lim
- Division of Medical Oncology, National Cancer Center Singapore, 11 Hospital Drive, Singapore 169610, Singapore;
| | - Chwee Teck Lim
- Institute for Health Innovation and Technology, National University of Singapore, 14 Medical Drive, Singapore 117599, Singapore;
- Department of Biomedical Engineering, National University of Singapore, 4 Engineering Drive 3, Singapore 117583, Singapore
- Mechanobiology Institute, National University of Singapore, 5A Engineering Drive 1, Singapore 117411, Singapore
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