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Nair NU, Schäffer AA, Gertz EM, Cheng K, Zerbib J, Sahu AD, Leor G, Shulman ED, Aldape KD, Ben-David U, Ruppin E. Chromosome 7 Gain Compensates for Chromosome 10 Loss in Glioma. Cancer Res 2024; 84:3464-3477. [PMID: 39078448 PMCID: PMC11479827 DOI: 10.1158/0008-5472.can-24-1366] [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: 04/24/2024] [Revised: 07/23/2024] [Accepted: 07/25/2024] [Indexed: 07/31/2024]
Abstract
The co-occurrence of chromosome 10 loss and chromosome 7 gain in gliomas is the most frequent loss-gain co-aneuploidy pair in human cancers. This phenomenon has been investigated since the late 1980s without resolution. Expanding beyond previous gene-centric studies, we investigated the co-occurrence in a genome-wide manner, taking an evolutionary perspective. Mining of large-scale tumor aneuploidy data confirmed the previous finding of a small-scale longitudinal study that the most likely order is chromosome 10 loss, followed by chromosome 7 gain. Extensive analysis of genomic and transcriptomic data from both patients and cell lines revealed that this co-occurrence can be explained by functional rescue interactions that are highly enriched on chromosome 7, which could potentially compensate for any detrimental consequences arising from the loss of chromosome 10. Transcriptomic data from various normal, noncancerous human brain tissues were analyzed to assess which tissues may be most predisposed to tolerate compensation of chromosome 10 loss by chromosome 7 gain. The analysis indicated that the preexisting transcriptomic states in the cortex and frontal cortex, where gliomas arise, are more favorable than other brain regions for compensation by rescuer genes that are active on chromosome 7. Collectively, these findings suggest that the phenomenon of chromosome 10 loss and chromosome 7 gain in gliomas is orchestrated by a complex interaction of many genes residing within these two chromosomes and provide a plausible reason why this co-occurrence happens preferentially in cancers originating in certain regions of the brain. Significance: Increased expression of multiple rescuer genes on the gained chromosome 7 could compensate for the downregulation of several vulnerable genes on the lost chromosome 10, resolving the long-standing mystery of this frequent co-occurrence in gliomas.
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Affiliation(s)
- Nishanth Ulhas Nair
- Computational Precision Oncology Section, Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Alejandro A. Schäffer
- Computational Precision Oncology Section, Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - E. Michael Gertz
- Computational Precision Oncology Section, Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Kuoyuan Cheng
- Computational Precision Oncology Section, Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
- MSD, Beijing, China
| | - Johanna Zerbib
- Department of Human Molecular Genetics and Biochemistry, Faculty of Medicine, Tel Aviv University, Tel Aviv-Yafo, Israel
| | - Avinash Das Sahu
- The University of New Mexico, Comprehensive Cancer Center, Albuquerque, NM, USA
| | - Gil Leor
- Department of Human Molecular Genetics and Biochemistry, Faculty of Medicine, Tel Aviv University, Tel Aviv-Yafo, Israel
| | - Eldad D. Shulman
- Computational Precision Oncology Section, Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Kenneth D. Aldape
- Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Uri Ben-David
- Department of Human Molecular Genetics and Biochemistry, Faculty of Medicine, Tel Aviv University, Tel Aviv-Yafo, Israel
| | - Eytan Ruppin
- Computational Precision Oncology Section, Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
- Lead contact
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Bai Y, Han T, Dong Y, Liang C, Gao L, Liu Y, Zhou J, Guo J, Ge D, Wu J, Hu D. GPX8 + cancer-associated fibroblast, as a cancer-promoting factor in lung adenocarcinoma, is related to the immunosuppressive microenvironment. BMC Med Genomics 2024; 17:77. [PMID: 38515109 PMCID: PMC10958965 DOI: 10.1186/s12920-024-01832-8] [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: 11/28/2023] [Accepted: 02/11/2024] [Indexed: 03/23/2024] Open
Abstract
BACKGROUND Cancer-associated fibroblasts (CAFs) play a crucial role in the tumor microenvironment of lung adenocarcinoma (LUAD) and are often associated with poorer clinical outcomes. This study aimed to screen for CAF-specific genes that could serve as promising therapeutic targets for LUAD. METHODS We established a single-cell transcriptional profile of LUAD, focusing on genetic changes in fibroblasts. Next, we identified key genes associated with fibroblasts through weighted gene co-expression network analysis (WGCNA) and univariate Cox analysis. Then, we evaluated the relationship between glutathione peroxidase 8 (GPX8) and clinical features in multiple independent LUAD cohorts. Furthermore, we analyzed immune infiltration to shed light on the relationship between GPX8 immune microenvironment remodeling. For clinical treatment, we used the tumor immune dysfunction and exclusion (TIDE) algorithm to assess the immunotherapy prediction efficiency of GPX8. After that, we screened potential therapeutic drugs for LUAD by the connectivity map (cMAP). Finally, we conducted a cell trajectory analysis of GPX8+ CAFs to show their unique function. RESULTS Fibroblasts were found to be enriched in tumor tissues. Then we identified GPX8 as a key gene associated with CAFs through comprehensive bioinformatics analysis. Further analysis across multiple LUAD cohorts demonstrated the relationship between GPX8 and poor prognosis. Additionally, we found that GPX8 played a role in inducing the formation of an immunosuppressive microenvironment. The TIDE method indicated that patients with low GPX8 expression were more likely to be responsive to immunotherapy. Using the cMAP, we identified beta-CCP as a potential drug-related to GPX8. Finally, cell trajectory analysis provided insights into the dynamic process of GPX8+ CAFs formation. CONCLUSIONS This study elucidates the association between GPX8+ CAFs and poor prognosis, as well as the induction of immunosuppressive formation in LUAD. These findings suggest that targeting GPX8+ CAFs could potentially serve as a therapeutic strategy for the treatment of LUAD.
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Affiliation(s)
- Ying Bai
- Key Laboratory of Industrial Dust Prevention and Control & Occupational Safety and Health of the Ministry of Education, Anhui University of Science and Technology, Huainan, Anhui, China
- School of Medicine, Anhui University of Science and Technology, Huainan, Anhui, China
- Anhui Occupational Health and Safety Engineering Laboratory, Huainan, Anhui, China
| | - Tao Han
- School of Medicine, Anhui University of Science and Technology, Huainan, Anhui, China
- Anhui Occupational Health and Safety Engineering Laboratory, Huainan, Anhui, China
| | - Yunjia Dong
- School of Medicine, Anhui University of Science and Technology, Huainan, Anhui, China
- Anhui Occupational Health and Safety Engineering Laboratory, Huainan, Anhui, China
| | - Chao Liang
- School of Medicine, Anhui University of Science and Technology, Huainan, Anhui, China
- Anhui Occupational Health and Safety Engineering Laboratory, Huainan, Anhui, China
| | - Lu Gao
- School of Medicine, Anhui University of Science and Technology, Huainan, Anhui, China
- Anhui Occupational Health and Safety Engineering Laboratory, Huainan, Anhui, China
| | - Yafeng Liu
- School of Medicine, Anhui University of Science and Technology, Huainan, Anhui, China
- Anhui Occupational Health and Safety Engineering Laboratory, Huainan, Anhui, China
| | - Jiawei Zhou
- School of Medicine, Anhui University of Science and Technology, Huainan, Anhui, China
- Anhui Occupational Health and Safety Engineering Laboratory, Huainan, Anhui, China
| | - Jianqiang Guo
- School of Medicine, Anhui University of Science and Technology, Huainan, Anhui, China
- Anhui Occupational Health and Safety Engineering Laboratory, Huainan, Anhui, China
| | - Deyong Ge
- Key Laboratory of Industrial Dust Prevention and Control & Occupational Safety and Health of the Ministry of Education, Anhui University of Science and Technology, Huainan, Anhui, China.
- School of Medicine, Anhui University of Science and Technology, Huainan, Anhui, China.
- Anhui Occupational Health and Safety Engineering Laboratory, Huainan, Anhui, China.
| | - Jing Wu
- Key Laboratory of Industrial Dust Prevention and Control & Occupational Safety and Health of the Ministry of Education, Anhui University of Science and Technology, Huainan, Anhui, China.
- School of Medicine, Anhui University of Science and Technology, Huainan, Anhui, China.
- Anhui Occupational Health and Safety Engineering Laboratory, Huainan, Anhui, China.
- Key Laboratory of Industrial Dust Deep Reduction and Occupational Health and Safety of Anhui Higher Education Institute, Huainan, Anhui, China.
| | - Dong Hu
- Key Laboratory of Industrial Dust Prevention and Control & Occupational Safety and Health of the Ministry of Education, Anhui University of Science and Technology, Huainan, Anhui, China.
- School of Medicine, Anhui University of Science and Technology, Huainan, Anhui, China.
- Anhui Occupational Health and Safety Engineering Laboratory, Huainan, Anhui, China.
- Key Laboratory of Industrial Dust Deep Reduction and Occupational Health and Safety of Anhui Higher Education Institute, Huainan, Anhui, China.
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Nair NU, Schäffer AA, Gertz EM, Cheng K, Zerbib J, Sahu AD, Leor G, Shulman ED, Aldape KD, Ben-David U, Ruppin E. Chromosome 7 to the rescue: overcoming chromosome 10 loss in gliomas. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.17.576103. [PMID: 38313282 PMCID: PMC10836086 DOI: 10.1101/2024.01.17.576103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2024]
Abstract
The co-occurrence of chromosome 10 loss and chromosome 7 gain in gliomas is the most frequent loss-gain co-aneuploidy pair in human cancers, a phenomenon that has been investigated without resolution since the late 1980s. Expanding beyond previous gene-centric studies, we investigate the co-occurrence in a genome-wide manner taking an evolutionary perspective. First, by mining large tumor aneuploidy data, we predict that the more likely order is 10 loss followed by 7 gain. Second, by analyzing extensive genomic and transcriptomic data from both patients and cell lines, we find that this co-occurrence can be explained by functional rescue interactions that are highly enriched on 7, which can possibly compensate for any detrimental consequences arising from the loss of 10. Finally, by analyzing transcriptomic data from normal, non-cancerous, human brain tissues, we provide a plausible reason why this co-occurrence happens preferentially in cancers originating in certain regions of the brain.
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Lee H, Ha S, Choi S, Do S, Yoon S, Kim YK, Kim WY. Oncogenic Impact of TONSL, a Homologous Recombination Repair Protein at the Replication Fork, in Cancer Stem Cells. Int J Mol Sci 2023; 24:ijms24119530. [PMID: 37298484 DOI: 10.3390/ijms24119530] [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: 03/18/2023] [Revised: 05/15/2023] [Accepted: 05/18/2023] [Indexed: 06/12/2023] Open
Abstract
We investigated the role of TONSL, a mediator of homologous recombination repair (HRR), in stalled replication fork double-strand breaks (DSBs) in cancer. Publicly available clinical data (tumors from the ovary, breast, stomach and lung) were analyzed through KM Plotter, cBioPortal and Qomics. Cancer stem cell (CSC)-enriched cultures and bulk/general mixed cell cultures (BCCs) with RNAi were employed to determine the effect of TONSL loss in cancer cell lines from the ovary, breast, stomach, lung, colon and brain. Limited dilution assays and ALDH assays were used to quantify the loss of CSCs. Western blotting and cell-based homologous recombination assays were used to identify DNA damage derived from TONSL loss. TONSL was expressed at higher levels in cancer tissues than in normal tissues, and higher expression was an unfavorable prognostic marker for lung, stomach, breast and ovarian cancers. Higher expression of TONSL is partly associated with the coamplification of TONSL and MYC, suggesting its oncogenic role. The suppression of TONSL using RNAi revealed that it is required in the survival of CSCs in cancer cells, while BCCs could frequently survive without TONSL. TONSL dependency occurs through accumulated DNA damage-induced senescence and apoptosis in TONSL-suppressed CSCs. The expression of several other major mediators of HRR was also associated with worse prognosis, whereas the expression of error-prone nonhomologous end joining molecules was associated with better survival in lung adenocarcinoma. Collectively, these results suggest that TONSL-mediated HRR at the replication fork is critical for CSC survival; targeting TONSL may lead to the effective eradication of CSCs.
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Affiliation(s)
- Hani Lee
- College of Pharmacy, Sookmyung Women's University, Seoul 04310, Republic of Korea
| | - Sojung Ha
- College of Pharmacy, Sookmyung Women's University, Seoul 04310, Republic of Korea
- Muscle Physiome Research Center, Sookmyung Women's University, Seoul 04310, Republic of Korea
| | - SeokGyeong Choi
- College of Pharmacy, Sookmyung Women's University, Seoul 04310, Republic of Korea
| | - Soomin Do
- College of Pharmacy, Sookmyung Women's University, Seoul 04310, Republic of Korea
| | - Sukjoon Yoon
- Department of Biological Sciences, Sookmyung Women's University, Seoul 04310, Republic of Korea
| | - Yong Kee Kim
- College of Pharmacy, Sookmyung Women's University, Seoul 04310, Republic of Korea
- Muscle Physiome Research Center, Sookmyung Women's University, Seoul 04310, Republic of Korea
- Research Institute of Pharmacal Research, Sookmyung Women's University, Seoul 04310, Republic of Korea
| | - Woo-Young Kim
- College of Pharmacy, Sookmyung Women's University, Seoul 04310, Republic of Korea
- Research Institute of Pharmacal Research, Sookmyung Women's University, Seoul 04310, Republic of Korea
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Huang Q, Carrio-Cordo P, Gao B, Paloots R, Baudis M. The Progenetix oncogenomic resource in 2021. Database (Oxford) 2021; 2021:baab043. [PMID: 34272855 PMCID: PMC8285936 DOI: 10.1093/database/baab043] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Revised: 06/16/2021] [Accepted: 06/30/2021] [Indexed: 12/02/2022]
Abstract
In cancer, copy number aberrations (CNAs) represent a type of nearly ubiquitous and frequently extensive structural genome variations. To disentangle the molecular mechanisms underlying tumorigenesis as well as identify and characterize molecular subtypes, the comparative and meta-analysis of large genomic variant collections can be of immense importance. Over the last decades, cancer genomic profiling projects have resulted in a large amount of somatic genome variation profiles, however segregated in a multitude of individual studies and datasets. The Progenetix project, initiated in 2001, curates individual cancer CNA profiles and associated metadata from published oncogenomic studies and data repositories with the aim to empower integrative analyses spanning all different cancer biologies. During the last few years, the fields of genomics and cancer research have seen significant advancement in terms of molecular genetics technology, disease concepts, data standard harmonization as well as data availability, in an increasingly structured and systematic manner. For the Progenetix resource, continuous data integration, curation and maintenance have resulted in the most comprehensive representation of cancer genome CNA profiling data with 138 663 (including 115 357 tumor) copy number variation (CNV) profiles. In this article, we report a 4.5-fold increase in sample number since 2013, improvements in data quality, ontology representation with a CNV landscape summary over 51 distinctive National Cancer Institute Thesaurus cancer terms as well as updates in database schemas, and data access including new web front-end and programmatic data access. Database URL: progenetix.org.
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Affiliation(s)
- Qingyao Huang
- Department of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190, Zurich 8057, Switzerland
- Swiss Institute of Bioinformatics, Winterthurerstrasse 190, Zurich 8057, Switzerland
| | - Paula Carrio-Cordo
- Department of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190, Zurich 8057, Switzerland
- Swiss Institute of Bioinformatics, Winterthurerstrasse 190, Zurich 8057, Switzerland
| | - Bo Gao
- Department of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190, Zurich 8057, Switzerland
- Swiss Institute of Bioinformatics, Winterthurerstrasse 190, Zurich 8057, Switzerland
| | - Rahel Paloots
- Department of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190, Zurich 8057, Switzerland
- Swiss Institute of Bioinformatics, Winterthurerstrasse 190, Zurich 8057, Switzerland
| | - Michael Baudis
- Department of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190, Zurich 8057, Switzerland
- Swiss Institute of Bioinformatics, Winterthurerstrasse 190, Zurich 8057, Switzerland
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