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Guo Y, Zhou Q, Wei M, Fan J, Huang H. Association of TNFRSF19 with a TNF family-based prognostic model and subtypes in gliomas using machine learning. Heliyon 2024; 10:e28445. [PMID: 38560169 PMCID: PMC10979244 DOI: 10.1016/j.heliyon.2024.e28445] [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: 08/13/2023] [Revised: 03/18/2024] [Accepted: 03/19/2024] [Indexed: 04/04/2024] Open
Abstract
Purpose TNF family members (TFMs) play a crucial role in different types of cancers, with TNF Receptor Superfamily Member 19 (TNFRSF19) standing out as a particularly important member in this category. Further research is necessary to investigate the potential impact of TFMs on prognosis prediction and to elucidate the function and potential therapeutic targets linked to TNFRSF19 expression in gliomas. Methods Three databases provided the data on gene expression and clinical information. Fourteen prognostic members were found through univariate Cox analysis and subsequently utilized to construct TFMs-based model in LASSO and multivariate Cox analyses. TFMs-based subtypes based on the expression profile were identified using an unsupervised clustering method. Machine learning algorithm identified key genes linked to prognostic model and subtype. A sequence of immune infiltrations was evaluated using the ssGSEA and ESTIMATE algorithms. Immunohistochemistry was used to examine the patterns of expression and the clinical significance of TNFRSF19. Results Our development of a prognostic model and subtypes based on the TNF family was successful, resulting in accurate predictions of prognosis. The findings indicate that TNFRSF19 exhibited strong performance. Upregulation of TNFRSF19 was correlated with malignant phenotypes and poor prognosis, which was confirmed through immunohistochemistry. TNFRSF19 played a role in reshaping the immunosuppressive microenvironment in gliomas, and multiple drug-targeted TNFRSF19 molecules were identified. Conclusions The TMF-based prognostic model and subtype can facilitate treatment decisions for glioma. TNFRSF19 is an outstanding representative of a predictor of prognosis and immunotherapy effect in gliomas.
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Affiliation(s)
- Youwei Guo
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan Province, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Quanwei Zhou
- The National Key Clinical Specialty, The Engineering Technology Research Center of Education Ministry of China, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Department of Neurosurgery, Zhujiang Hospital, Southern Medical University, Guangzhou, 510282, China
| | - Min Wei
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan Province, China
| | - Jianfeng Fan
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan Province, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - He Huang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan Province, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
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2
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Fang Y, Xiao X, Wang J, Dasari S, Pepin D, Nephew KP, Zamarin D, Mitra AK. Cancer associated fibroblasts serve as an ovarian cancer stem cell niche through noncanonical Wnt5a signaling. NPJ Precis Oncol 2024; 8:7. [PMID: 38191909 PMCID: PMC10774407 DOI: 10.1038/s41698-023-00495-5] [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: 03/28/2023] [Accepted: 12/05/2023] [Indexed: 01/10/2024] Open
Abstract
Frequent relapse and chemoresistance cause poor outcome in ovarian cancer (OC) and cancer stem cells (CSCs) are important contributors. While most studies focus exclusively on CSCs, the role of the microenvironment in providing optimal conditions to maintain their tumor-initiating potential remains poorly understood. Cancer associated fibroblasts (CAFs) are a major constituent of the OC tumor microenvironment and we show that CAFs and CSCs are enriched following chemotherapy in patient tumors. CAFs significantly increase OC cell resistance to carboplatin. Using heterotypic CAF-OC cocultures and in vivo limiting dilution assay, we confirm that the CAFs act by enriching the CSC population. CAFs increase the symmetric division of CSCs as well as the dedifferentiation of bulk OC cells into CSCs. The effect of CAFs is limited to OC cells in their immediate neighborhood, which can be prevented by inhibiting Wnt. Analysis of single cell RNA-seq data from OC patients reveal Wnt5a as the highest expressed Wnt in CAFs and that certain subpopulations of CAFs express higher levels of Wnt5a. Our findings demonstrate that Wnt5a from CAFs activate a noncanonical Wnt signaling pathway involving the ROR2/PKC/CREB1 axis in the neighboring CSCs. While canonical Wnt signaling is found to be predominant in interactions between cancer cells in patients, non-canonical Wnt pathway is activated by the CAF-OC crosstalk. Treatment with a Wnt5a inhibitor sensitizes tumors to carboplatin in vivo. Together, our results demonstrate a novel mechanism of CSC maintenance by signals from the microenvironmental CAFs, which can be targeted to treat OC chemoresistance and relapse.
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Affiliation(s)
- Yiming Fang
- Indiana University School of Medicine-Bloomington, Indiana University, Bloomington, IN, USA
- Indiana University Simon Comprehensive Cancer Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Xue Xiao
- Indiana University School of Medicine-Bloomington, Indiana University, Bloomington, IN, USA
- Indiana University Simon Comprehensive Cancer Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Ji Wang
- Indiana University School of Medicine-Bloomington, Indiana University, Bloomington, IN, USA
- Indiana University Simon Comprehensive Cancer Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Subramanyam Dasari
- Indiana University School of Medicine-Bloomington, Indiana University, Bloomington, IN, USA
- Indiana University Simon Comprehensive Cancer Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - David Pepin
- Pediatric Surgical Research Laboratories, Massachusetts General Hospital; Department of Surgery, Harvard Medical School, Boston, MA, USA
| | - Kenneth P Nephew
- Indiana University School of Medicine-Bloomington, Indiana University, Bloomington, IN, USA
- Indiana University Simon Comprehensive Cancer Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Dmitriy Zamarin
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Anirban K Mitra
- Indiana University School of Medicine-Bloomington, Indiana University, Bloomington, IN, USA.
- Indiana University Simon Comprehensive Cancer Center, Indiana University School of Medicine, Indianapolis, IN, USA.
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Li YR, Ochoa CJ, Zhu Y, Kramer A, Wilson M, Fang Y, Chen Y, Singh T, Di Bernardo G, Zhu E, Lee D, Moatamed NA, Bando J, Zhou JJ, Memarzadeh S, Yang L. Profiling ovarian cancer tumor and microenvironment during disease progression for cell-based immunotherapy design. iScience 2023; 26:107952. [PMID: 37810241 PMCID: PMC10558812 DOI: 10.1016/j.isci.2023.107952] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 08/28/2023] [Accepted: 09/14/2023] [Indexed: 10/10/2023] Open
Abstract
Ovarian cancer (OC) is highly lethal due to late detection and frequent recurrence. Initial treatments, comprising surgery and chemotherapy, lead to disease remission but are invariably associated with subsequent relapse. The identification of novel therapies and an improved understanding of the molecular and cellular characteristics of OC are urgently needed. Here, we conducted a comprehensive analysis of primary tumor cells and their microenvironment from 16 chemonaive and 10 recurrent OC patient samples. Profiling OC tumor biomarkers allowed for the identification of potential molecular targets for developing immunotherapies, while profiling the microenvironment yielded insights into its cellular composition and property changes between chemonaive and recurrent samples. Notably, we identified CD1d as a biomarker of the OC microenvironment and demonstrated its targeting by invariant natural killer T (iNKT) cells. Overall, our study presents a comprehensive immuno-profiling of OC tumor and microenvironment during disease progression, guiding the development of immunotherapies for OC treatment, especially for recurrent disease.
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Affiliation(s)
- Yan-Ruide Li
- Department of Microbiology, Immunology & Molecular Genetics, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Christopher J Ochoa
- Department of Obstetrics and Gynecology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
- Molecular Biology Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Yichen Zhu
- Department of Microbiology, Immunology & Molecular Genetics, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Adam Kramer
- Department of Microbiology, Immunology & Molecular Genetics, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Matthew Wilson
- Department of Microbiology, Immunology & Molecular Genetics, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Ying Fang
- Department of Microbiology, Immunology & Molecular Genetics, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Yuning Chen
- Department of Microbiology, Immunology & Molecular Genetics, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Tanya Singh
- Department of Obstetrics and Gynecology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Jonsson Comprehensive Cancer Center, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Gabriella Di Bernardo
- Department of Obstetrics and Gynecology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Jonsson Comprehensive Cancer Center, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Enbo Zhu
- Department of Microbiology, Immunology & Molecular Genetics, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Derek Lee
- Department of Microbiology, Immunology & Molecular Genetics, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Neda A Moatamed
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Joanne Bando
- Department of Medicine, Division of Pulmonary and Critical Care, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Jin J Zhou
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Sanaz Memarzadeh
- Department of Obstetrics and Gynecology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
- Molecular Biology Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Jonsson Comprehensive Cancer Center, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- The VA Greater Los Angeles Healthcare System, Los Angeles, CA 90073, USA
| | - Lili Yang
- Department of Microbiology, Immunology & Molecular Genetics, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Molecular Biology Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Jonsson Comprehensive Cancer Center, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
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Gertych A, Walts AE, Cheng K, Liu M, John J, Lester J, Karlan BY, Orsulic S. Dynamic Changes in the Extracellular Matrix in Primary, Metastatic, and Recurrent Ovarian Cancers. Cells 2022; 11:3769. [PMID: 36497028 PMCID: PMC9736731 DOI: 10.3390/cells11233769] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Revised: 11/21/2022] [Accepted: 11/24/2022] [Indexed: 11/29/2022] Open
Abstract
Cancer-associated fibroblasts (CAFs) and their extracellular matrix are active participants in cancer progression. While it is known that functionally different subpopulations of CAFs co-exist in ovarian cancer, it is unclear whether certain CAF subsets are enriched during metastatic progression and/or chemotherapy. Using computational image analyses of patient-matched primary high-grade serous ovarian carcinomas, synchronous pre-chemotherapy metastases, and metachronous post-chemotherapy metastases from 42 patients, we documented the dynamic spatiotemporal changes in the extracellular matrix, fibroblasts, epithelial cells, immune cells, and CAF subsets expressing different extracellular matrix components. Among the different CAF subsets, COL11A1+ CAFs were associated with linearized collagen fibers and exhibited the greatest enrichment in pre- and post-chemotherapy metastases compared to matched primary tumors. Although pre- and post-chemotherapy metastases were associated with increased CD8+ T cell infiltration, the infiltrate was not always evenly distributed between the stroma and cancer cells, leading to an increased frequency of the immune-excluded phenotype where the majority of CD8+ T cells are present in the tumor stroma but absent from the tumor parenchyma. Overall, most of the differences in the tumor microenvironment were observed between primary tumors and metastases, while fewer differences were observed between pre- and post-treatment metastases. These data suggest that the tumor microenvironment is largely determined by the primary vs. metastatic location of the tumor while chemotherapy does not have a significant impact on the host microenvironment.
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Affiliation(s)
- Arkadiusz Gertych
- Department of Pathology and Laboratory Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
- Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
- Faculty of Biomedical Engineering, Silesian University of Technology, 44-100 Zabrze, Poland
| | - Ann E. Walts
- Department of Pathology and Laboratory Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Keyi Cheng
- Department of Mathematics, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Manyun Liu
- Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, GA 30458, USA
| | - Joshi John
- Department of Veterans Affairs, Greater Los Angeles Healthcare System, Los Angeles, CA 90095, USA
| | - Jenny Lester
- Department of Obstetrics and Gynecology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Beth Y. Karlan
- Department of Obstetrics and Gynecology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
- Jonsson Comprehensive Cancer Center, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Sandra Orsulic
- Department of Veterans Affairs, Greater Los Angeles Healthcare System, Los Angeles, CA 90095, USA
- Department of Obstetrics and Gynecology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
- Jonsson Comprehensive Cancer Center, University of California Los Angeles, Los Angeles, CA 90095, USA
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5
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Huang H, Yu H, Li X, Li Y, Zhu G, Su L, Li M, Chen C, Gao M, Wu D, Zhang R, Cao P, Liu H, Chen J. Genomic analysis of TNF-related genes with prognosis and characterization of the tumor immune microenvironment in lung adenocarcinoma. Front Immunol 2022; 13:993890. [PMID: 36505472 PMCID: PMC9732939 DOI: 10.3389/fimmu.2022.993890] [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: 07/14/2022] [Accepted: 11/11/2022] [Indexed: 11/27/2022] Open
Abstract
Background The tumor necrosis factor (TNF) family plays a role in modulating cellular functions that regulate cellular differentiation, survival, apoptosis, and especially cellular immune functions. The TNF family members also play important roles in oncogenesis and progression. However, the potential role of the TNF family members in lung adenocarcinoma (LUAD) is yet to be explored. Methods The expression of TNF-related genes (TNFRGs) in 1,093 LUAD samples was investigated using The Cancer Genome Atlas and Gene Expression Omnibus datasets. The characteristic patterns of TNFRGs in LUAD were systematically probed and three distinct molecular subtypes were identified. Furthermore, a correlation was found between the different subtypes and their clinical characteristics. A TNF scoring system was created to predict overall survival (OS) and therapeutic responses in patients with LUAD. Subsequently, the predictive accuracy of the score was verified and a nomogram was used to optimize the clinical applicability range of the TNF score. Results A high TNF score, involving the immune and stromal scores, indicated negative odds of OS. Moreover, the TNF score was associated with immune checkpoints and chemotherapeutic drug sensitivity. Collectively, our comprehensive TNFRGs analysis of patients with LUAD revealed that TNF could be involved in forming the diverse and complex tumor microenvironment, its clinicopathological features, and its prognosis. Conclusions A TNF-related prognostic model was constructed, and a TNF score was developed. These findings are expected to improve our knowledge regarding the function of TNFRGs in LUAD, pave a new path for assessing the disease prognosis, and assist in developing personalized therapeutic strategies for patients with LUAD.
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Affiliation(s)
- Hua Huang
- Department of Lung Cancer Surgery, Tianjin Medical University General Hospital, Tianjin, China
| | - Haochuan Yu
- Department of Lung Cancer Surgery, Tianjin Medical University General Hospital, Tianjin, China
| | - Xuanguang Li
- Department of Lung Cancer Surgery, Tianjin Medical University General Hospital, Tianjin, China
| | - Yongwen Li
- Tianjin Key Laboratory of Lung Cancer Metastasis and Tumor Microenvironment, Tianjin Lung Cancer Institute, Tianjin Medical University General Hospital, Tianjin, China
| | - Guangsheng Zhu
- Department of Lung Cancer Surgery, Tianjin Medical University General Hospital, Tianjin, China
| | - Lianchun Su
- Department of Thoracic Surgery, First Affiliated Hospital, School of Medicine, Shihezi University, Shihezi, Xinjiang, China
| | - Mingbiao Li
- Tianjin Key Laboratory of Lung Cancer Metastasis and Tumor Microenvironment, Tianjin Lung Cancer Institute, Tianjin Medical University General Hospital, Tianjin, China
| | - Chen Chen
- Tianjin Key Laboratory of Lung Cancer Metastasis and Tumor Microenvironment, Tianjin Lung Cancer Institute, Tianjin Medical University General Hospital, Tianjin, China
| | - Min Gao
- Department of Thoracic Surgery, the Affiliated Hospital of Inner Mongolia Medical University, Hohhot, China
| | - Di Wu
- Department of Lung Cancer Surgery, Tianjin Medical University General Hospital, Tianjin, China
| | - Ruihao Zhang
- Department of Lung Cancer Surgery, Tianjin Medical University General Hospital, Tianjin, China
| | - Peijun Cao
- Department of Lung Cancer Surgery, Tianjin Medical University General Hospital, Tianjin, China
| | - Hongyu Liu
- Tianjin Key Laboratory of Lung Cancer Metastasis and Tumor Microenvironment, Tianjin Lung Cancer Institute, Tianjin Medical University General Hospital, Tianjin, China,Quantitative Biomedical Research Center, Department of Population and Data Sciences, University of Texas Southwestern Medical Center, Dallas, TX, United States,*Correspondence: Jun Chen, ; Hongyu Liu,
| | - Jun Chen
- Department of Lung Cancer Surgery, Tianjin Medical University General Hospital, Tianjin, China,Tianjin Key Laboratory of Lung Cancer Metastasis and Tumor Microenvironment, Tianjin Lung Cancer Institute, Tianjin Medical University General Hospital, Tianjin, China,Department of Thoracic Surgery, First Affiliated Hospital, School of Medicine, Shihezi University, Shihezi, Xinjiang, China,*Correspondence: Jun Chen, ; Hongyu Liu,
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6
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Spheroid Formation and Peritoneal Metastasis in Ovarian Cancer: The Role of Stromal and Immune Components. Int J Mol Sci 2022; 23:ijms23116215. [PMID: 35682890 PMCID: PMC9181487 DOI: 10.3390/ijms23116215] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 05/25/2022] [Accepted: 05/30/2022] [Indexed: 12/13/2022] Open
Abstract
Ovarian cancer (OC) is one of the most common gynecological cancers, with the worst prognosis and the highest mortality rate. Peritoneal dissemination (or carcinomatosis) accompanied by ascites formation is the most unfavorable factor in the progression and recurrence of OC. Tumor cells in ascites are present as either separate cells or, more often, as cell aggregates, i.e., spheroids which promote implantation on the surface of nearby organs and, at later stages, metastases to distant organs. Malignant ascites comprises a unique tumor microenvironment; this fact may be of relevance in the search for new prognostic and predictive factors that would make it possible to personalize the treatment of patients with OC. However, the precise mechanisms of spheroid formation and carcinomatosis are still under investigation. Here, we summarize data on ascites composition as well as the activity of fibroblasts and macrophages, the key stromal and immune components, in OC ascites. We describe current knowledge about the role of fibroblasts and macrophages in tumor spheroid formation, and discuss the specific functions of fibroblasts, macrophages and T cells in tumor peritoneal dissemination and implantation.
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Tian J, Liang X, Wang D, Tian J, Liang H, Lei T, Yan Z, Wu D, Liu X, Liu S, Yang Y. TBC1D2 Promotes Ovarian Cancer Metastasis via Inducing E-Cadherin Degradation. Front Oncol 2022; 12:766077. [PMID: 35574392 PMCID: PMC9091366 DOI: 10.3389/fonc.2022.766077] [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: 08/28/2021] [Accepted: 03/28/2022] [Indexed: 11/16/2022] Open
Abstract
Background Ovarian cancer (OC) is the most lethal gynecological malignancy worldwide. Increasing evidence indicates that TBC domain family is implicated in various cellular events contributing to initiation and development of different cancers, including OC. However, the role of TBC1D2, a crucial member of TBC domain family, remains unclear in OC. Methods IHC and qRT-PCR were employed to determine TBC1D2 expression in OC tissues and cells. In vitro and in vivo assays involving proliferation, migration, invasion were performed to explore the role of TBC1D2 in OC development. The underlying mechanism by which TBC1D2 promotes OC metastasis were elucidated using bioinformatics analysis, western blotting and co-immunoprecipitation. Results Upregulation of TBC1D2 was found in OC and was associated with a poor prognosis. Meanwhile, TBC1D2 promoted OC cell proliferation, migration, and invasion in vitro and facilitated tumor growth and metastasis in vivo. Moreover, TBC1D2 contributed to OC cell invasion by E-cadherin degradation via disassembling Rac1-IQGAP1 complex. In addition, miR-373-3p was screened out and identified to inhibit OVCAR3 invasion via negative regulation of TBC1D2. Conclusion Our findings indicated that TBC1D2 is overexpressed in OC and contributes to tumor metastasis via E-cadherin degradation. This study suggests that TBC1D2 may be an underlying therapeutic target for OC.
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Affiliation(s)
- Jiming Tian
- The First Clinical Medical College of Lanzhou University, Lanzhou, China.,Department of Obstetrics and Gynecology, Key Laboratory for Gynecologic Oncology Gansu Province, The First Hospital of Lanzhou University, Lanzhou, China
| | - Xiaolei Liang
- Department of Obstetrics and Gynecology, Key Laboratory for Gynecologic Oncology Gansu Province, The First Hospital of Lanzhou University, Lanzhou, China
| | - Dalin Wang
- State Key Laboratory of Cancer Biology and Department of Physiology and Pathophysiology, Fourth Military Medical University, Xi'an, China
| | - Jinglin Tian
- The First Clinical Medical College of Lanzhou University, Lanzhou, China
| | - Haiping Liang
- The First Clinical Medical College of Lanzhou University, Lanzhou, China
| | - Ting Lei
- The First Clinical Medical College of Lanzhou University, Lanzhou, China
| | - Zeyu Yan
- State Key Laboratory of Cancer Biology and Department of Physiology and Pathophysiology, Fourth Military Medical University, Xi'an, China
| | - Dan Wu
- State Key Laboratory of Cancer Biology and Department of Physiology and Pathophysiology, Fourth Military Medical University, Xi'an, China
| | - Xiaoli Liu
- State Key Laboratory of Cancer Biology and Department of Physiology and Pathophysiology, Fourth Military Medical University, Xi'an, China
| | - Shujuan Liu
- Department of Gynecology and Obstetrics, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Yongxiu Yang
- Department of Obstetrics and Gynecology, Key Laboratory for Gynecologic Oncology Gansu Province, The First Hospital of Lanzhou University, Lanzhou, China
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Ma Y, Zhang X, Yang J, Jin Y, Xu Y, Qiu J. Comprehensive Molecular Analyses of a TNF Family-Based Gene Signature as a Potentially Novel Prognostic Biomarker for Cervical Cancer. Front Oncol 2022; 12:854615. [PMID: 35392242 PMCID: PMC8980547 DOI: 10.3389/fonc.2022.854615] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Accepted: 02/28/2022] [Indexed: 12/14/2022] Open
Abstract
Background Increasing evidence suggests that tumour necrosis factor (TNF) family genes play important roles in cervical cancer (CC). However, whether TNF family genes can be used as prognostic biomarkers of CC and the molecular mechanisms of TNF family genes remain unclear. Methods A total of 306 CC and 13 normal samples were obtained from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. We identified differentially expressed TNF family genes between CC and normal samples and subjected them to univariate Cox regression analysis for selecting prognostic TNF family genes. Least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analyses were performed to screen genes to establish a TNF family gene signature. Gene set enrichment analysis (GSEA) was performed to investigate the biological functions of the TNF family gene signature. Finally, methylation and copy number variation data of CC were used to analyse the potential molecular mechanisms of TNF family genes. Results A total of 26 differentially expressed TNF family genes were identified between the CC and normal samples. Next, a TNF family gene signature, including CD27, EDA, TNF, TNFRSF12A, TNFRSF13C, and TNFRSF9 was constructed based on univariate Cox, LASSO, and multivariate Cox regression analyses. The TNF family gene signature was related to age, pathological stages M and N, and could predict patient survival independently of clinical factors. Moreover, KEGG enrichment analysis suggested that the TNF family gene signature was mainly involved in the TGF-β signaling pathway, and the TNF family gene signature could affect the immunotherapy response. Finally, we confirmed that the mRNA expressions of CD27, TNF, TNFRSF12A, TNFRSF13C, and TNFRSF9 were upregulated in CC, while that of EDA was downregulated. The mRNA expressions of CD27, EDA, TNF, TNFRSF12A, TNFRSF13C, and TNFRSF9 might be influenced by gene methylation and copy number variation. Conclusion Our study is the first to demonstrate that CD27, EDA, TNF, TNFRSF12A, TNFRSF13C, and TNFRSF9 might be used as prognostic biomarkers of CC and are associated with the immunotherapy response of CC.
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Affiliation(s)
- Yan Ma
- Department of Gynecology and Obstetrics, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Xiaoyan Zhang
- Department of Gynecology and Obstetrics, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Jiancheng Yang
- Department of Gynecology and Obstetrics, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Yanping Jin
- Department of Gynecology and Obstetrics, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Ying Xu
- Department of Gynecology and Obstetrics, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Jianping Qiu
- Department of Gynecology and Obstetrics, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
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Development and Validation of a TNF Family-Based Signature for Predicting Prognosis, Tumor Immune Characteristics, and Immunotherapy Response in Colorectal Cancer Patients. J Immunol Res 2021; 2021:6439975. [PMID: 34541005 PMCID: PMC8448595 DOI: 10.1155/2021/6439975] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Revised: 07/10/2021] [Accepted: 08/03/2021] [Indexed: 12/12/2022] Open
Abstract
In this study, a comprehensive analysis of TNF family members in colorectal cancer (CRC) was conducted and a TNF family-based signature (TFS) was generated to predict prognosis and immunotherapy response. Using the expression data of 516 CRC patients from The Cancer Genome Atlas (TCGA) database, TNF family members were screened to construct a TFS by using the univariate Cox proportional hazards regression and the least absolute shrinkage and selection operator- (LASSO-) Cox proportional hazards regression method. The TFS was then validated in a meta-Gene Expression Omnibus (GEO) cohort (n = 1162) from the GEO database. Additionally, the tumor immune characteristics and predicted responses to immune checkpoint blockade in TFS-based risk subgroups were analyzed. Eight genes (TNFRSF11A, TNFRSF10C, TNFRSF10B, TNFSF11, TNFRSF25, TNFRSF19, LTBR, and NGFR) were used to construct the TFS. Compared to the high-risk patients, the low-risk patients had better overall survival, which was verified by the GEO data. In addition, a high TFS risk score was associated with high infiltration of regulatory T cells (Tregs), nonactivated macrophages (M0), natural killer cells, immune escape phenotypes, poor immunotherapy response, and tumorigenic and metastasis-related pathways. Conversely, a low TFS risk score was related to high infiltration of resting CD4 memory T cells and resting dendritic cells, few immune escape phenotypes, and high sensitivity to immunotherapy. Thus, the eight gene-based TFS is a promising index to predict the prognosis, immune characteristics, and immunotherapy response in CRC, and our results also provide new understanding of the role of the TNF family members in the prognosis and treatment of CRC.
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Li DF, Tulahong A, Uddin MN, Zhao H, Zhang H. Meta-analysis identifying epithelial-derived transcriptomes predicts poor clinical outcome and immune infiltrations in ovarian cancer. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2021; 18:6527-6551. [PMID: 34517544 DOI: 10.3934/mbe.2021324] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
BACKGROUND Previous studies revealed that the epithelial component is associated with the modulation of the ovarian tumor microenvironment (TME). However, the identification of key transcriptional signatures of laser capture microdissected human ovarian cancer epithelia remains lacking. METHODS We identified the differentially expressed transcriptional signatures of human ovarian cancer epithelia by meta-analysis of GSE14407, GSE2765, GSE38666, GSE40595, and GSE54388. Then we investigated the enrichment of KEGG pathways that are associated with epithelia-derived transcriptomes. Finally, we investigated the correlation of key epithelia-hub genes with the survival prognosis and immune infiltrations. Finally, we investigated the genetic alterations of key prognostic hub genes and their diagnostic efficacy in ovarian cancer epithelia. RESULTS We identified 1339 differentially expressed genes (DEGs) in ovarian cancer epithelia including 541upregulated and 798 downregulated genes. We identified 21 (such as E2F4, FOXM1, TFDP1, E2F1, and SIN3A) and 11 (such as JUN, DDX4, FOSL1, NOC2L, and HMGA1) master transcriptional regulators (MTRs) that are interacted with upregulated and the downregulated genes in ovarian tumor epithelium, respectively. The STRING-based analysis identified hub genes (such as CDK1, CCNB1, AURKA, CDC20, and CCNA2) in ovarian cancer epithelia. The significant clusters of identified hub genes are associated with the enrichment of KEGG pathways including cell cycle, DNA replication, cytokine-cytokine receptor interaction, pathways in cancer, and focal adhesion. The upregulation of SCNN1A and CDCA3 and the downregulation of SOX6 are correlated with a shorter survival prognosis in ovarian cancer (OV). The expression level of SOX6 is negatively correlated with immune score and positively correlated with tumor purity in OV. Moreover, SOX6 is negatively correlated with the infiltration of TILs, CD8+ T cells, CD4+ Regulatory T cells, cytolytic activity, T cell activation, pDC, neutrophils, and macrophages in OV. Also, SOX6 is negatively correlated with various immune markers including CD8A, PRF1, GZMA, GZMB, NKG7, CCL3, and CCL4, indicating the immune regulatory efficiency of SOX6 in the TME of OV. Furthermore, SCNN1A, CDCA3, and SOX6 genes are genetically altered in OV and the expression levels of SCNN1A and SOX6 genes showed diagnostic efficacy in ovarian cancer epithelia. CONCLUSIONS The identified ovarian cancer epithelial-derived key transcriptional signatures are significantly correlated with survival prognosis and immune infiltrations, and may provide new insight into the diagnosis and treatment of epithelial ovarian cancer.
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Affiliation(s)
- Dong-Feng Li
- Department of Pharmacy, First Affiliated Hospital of Xinjiang Medical University, Urumqi 830011, China
| | - Aisikeer Tulahong
- Department of Oncology, First Affiliated Hospital of Xinjiang Medical University, Urumqi 830011, China
| | - Md Nazim Uddin
- School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing 211198, China
| | - Huan Zhao
- Department of Pharmacy, First Affiliated Hospital of Xinjiang Medical University, Urumqi 830011, China
| | - Hua Zhang
- Department of Oncology, First Affiliated Hospital of Xinjiang Medical University, Urumqi 830011, China
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Chang X, Dong Y. CACNA1C is a prognostic predictor for patients with ovarian cancer. J Ovarian Res 2021; 14:88. [PMID: 34210324 PMCID: PMC8252246 DOI: 10.1186/s13048-021-00830-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Accepted: 05/28/2021] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND CACNA1C, as a type of voltage-dependent calcium ion transmembrane channel, played regulatory roles in the development and progress of multiple tumors. This study was aimed to analyze the roles of CACNA1C in ovarian cancer (OC) of overall survival (OS) and to explore its relationships with immunity. METHODS Single gene mRNA sequencing data and corresponding clinical information were obtained from The Cancer Genome Atlas Database (TCGA) and the International Cancer Genome Consortium (ICGC) datasets. Gene set enrichment analysis (GSEA) was used to identify CACNA1C-related signal pathways. Univariate and multivariate Cox regression analyses were applied to evaluate independent prognostic factors. Besides, associations between CACNA1C and immunity were also explored. RESULTS CACNA1C had a lower expression in OC tumor tissues than in normal tissues (P < 0.001), with significant OS (P = 0.013) and a low diagnostic efficiency. We further validated the expression levels of CACNA1C in OC by means of the ICGC dataset (P = 0.01), qRT-PCR results (P < 0.001) and the HPA database. Univariate and multivariate Cox hazard regression analyses indicated that CACNA1C could be an independent risk factor of OS for OC patients (both P < 0.001). Five significant CACNA1C-related signaling pathways were identified by means of GSEA. As for genetic alteration analysis, altered CACNA1C groups were significantly associated with OS (P = 0.0169), progression-free survival (P = 0.0404), disease-free survival (P = 0.0417) and disease-specific survival (P = 9.280e-3), compared with unaltered groups in OC. Besides, CACNA1C was dramatically associated with microsatellite instability (MSI) and immunity. CONCLUSIONS Our results shed light on that CACNA1C could be a prognostic predictor of OS in OC and it was closely related to immunity.
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Affiliation(s)
- Xiaohan Chang
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, No. 36 Sanhao street, Liaoning Province, 110004, Shenyang, P.R. China
| | - Yunxia Dong
- Department of Anesthesiology, Shengjing Hospital of China Medical University, No. 36 Sanhao street, Liaoning Province, 110004, Shenyang, P.R. China.
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Yin W, Zhu H, Tan J, Xin Z, Zhou Q, Cao Y, Wu Z, Wang L, Zhao M, Jiang X, Ren C, Tang G. Identification of collagen genes related to immune infiltration and epithelial-mesenchymal transition in glioma. Cancer Cell Int 2021; 21:276. [PMID: 34034744 PMCID: PMC8147444 DOI: 10.1186/s12935-021-01982-0] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2020] [Accepted: 05/13/2021] [Indexed: 01/05/2023] Open
Abstract
Background Gliomas account for the majority of fatal primary brain tumors, and there is much room for research in the underlying pathogenesis, the multistep progression of glioma, and how to improve survival. In our study, we aimed to identify potential biomarkers or therapeutic targets of glioma and study the mechanism underlying the tumor progression. Methods We downloaded the microarray datasets (GSE43378 and GSE7696) from the Gene Expression Omnibus (GEO) database. Then, we used weighted gene co-expression network analysis (WGCNA) to screen potential biomarkers or therapeutic targets related to the tumor progression. ESTIMATE (Estimation of STromal and Immune cells in MAlignant Tumors using Expression data) algorithm and TIMER (Tumor Immune Estimation Resource) database were used to analyze the correlation between the selected genes and the tumor microenvironment. Real-time reverse transcription polymerase chain reaction was used to measure the selected gene. Transwell and wound healing assays were used to measure the cell migration and invasion capacity. Western blotting was used to test the expression of epithelial-mesenchymal transition (EMT) related markers. Results We identified specific module genes that were positively correlated with the WHO grade but negatively correlated with OS of glioma. Importantly, we identified that 6 collagen genes (COL1A1, COL1A2, COL3A1, COL4A1, COL4A2, and COL5A2) could regulate the immunosuppressive microenvironment of glioma. Moreover, we found that these collagen genes were significantly involved in the EMT process of glioma. Finally, taking COL3A1 as a further research object, the results showed that knockdown of COL3A1 significantly inhibited the migration, invasion, and EMT process of SHG44 and A172 cells. Conclusions In summary, our study demonstrated that collagen genes play an important role in regulating the immunosuppressive microenvironment and EMT process of glioma and could serve as potential therapeutic targets for glioma management. Supplementary Information The online version contains supplementary material available at 10.1186/s12935-021-01982-0.
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Affiliation(s)
- Wen Yin
- Department of Neurosurgery, Xiangya Hospital of Central South University, Changsha, Hunan Province, 410008, China
| | - Hecheng Zhu
- Changsha Kexin Cancer Hospital, Changsha, Hunan, 410205, China
| | - Jun Tan
- Department of Neurosurgery, Xiangya Hospital of Central South University, Changsha, Hunan Province, 410008, China
| | - Zhaoqi Xin
- Department of Neurosurgery, Xiangya Hospital of Central South University, Changsha, Hunan Province, 410008, China
| | - Quanwei Zhou
- Department of Neurosurgery, Xiangya Hospital of Central South University, Changsha, Hunan Province, 410008, China
| | - Yudong Cao
- Department of Neurosurgery, Xiangya Hospital of Central South University, Changsha, Hunan Province, 410008, China
| | - Zhaoping Wu
- Department of Neurosurgery, Xiangya Hospital of Central South University, Changsha, Hunan Province, 410008, China
| | - Lei Wang
- Cancer Research Institute, Collaborative Innovation Center for Cancer Medicine, The Key Laboratory for Carcinogenesis of Chinese Ministry of Health and the Key Laboratory of Carcinogenesis and Cancer Invasion of the Chinese Ministry of Education, School of Basic Medical Science, Central South University, Changsha, Hunan, People's Republic of China
| | - Ming Zhao
- Changsha Kexin Cancer Hospital, Changsha, Hunan, 410205, China
| | - Xingjun Jiang
- Department of Neurosurgery, Xiangya Hospital of Central South University, Changsha, Hunan Province, 410008, China.
| | - Caiping Ren
- Cancer Research Institute, Collaborative Innovation Center for Cancer Medicine, The Key Laboratory for Carcinogenesis of Chinese Ministry of Health and the Key Laboratory of Carcinogenesis and Cancer Invasion of the Chinese Ministry of Education, School of Basic Medical Science, Central South University, Changsha, Hunan, People's Republic of China.
| | - Guihua Tang
- Department of Clinical Laboratory, Hunan Provincial People's Hospital (The first affiliated hospital of Hunan Normal University, The college of clinical medicine of Human Normal University), Changsha, Hunan Province, 410005, China.
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