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Paloots R, Baudis M. cancercelllines.org-a novel resource for genomic variants in cancer cell lines. Database (Oxford) 2024; 2024:baae030. [PMID: 38687868 PMCID: PMC11060486 DOI: 10.1093/database/baae030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 02/19/2024] [Accepted: 03/27/2024] [Indexed: 05/02/2024]
Abstract
Cancer cell lines are an important component in biological and medical research, enabling studies of cellular mechanisms as well as the development and testing of pharmaceuticals. Genomic alterations in cancer cell lines are widely studied as models for oncogenetic events and are represented in a wide range of primary resources. We have created a comprehensive, curated knowledge resource-cancercelllines.org-with the aim to enable easy access to genomic profiling data in cancer cell lines, curated from a variety of resources and integrating both copy number and single nucleotide variants data. We have gathered over 5600 copy number profiles as well as single nucleotide variant annotations for 16 000 cell lines and provide these data with mappings to the GRCh38 reference genome. Both genomic variations and associated curated metadata can be queried through the GA4GH Beacon v2 Application Programming Interface (API) and a graphical user interface with extensive data retrieval enabled using GA4GH data schemas under a permissive licensing scheme. Database URL: https://cancercelllines.org.
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Affiliation(s)
- Rahel Paloots
- Institute of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190, Zurich 8057, Switzerland
- Swiss Institute of Bioinformatics, Winterthurerstrasse 190, Zurich 8057, Switzerland
| | - Michael Baudis
- Institute 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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Wang L, Cai M, Song Y, Bai J, Sun W, Yu J, Du S, Lu J, Fu S. Multidimensional difference analysis in gastric cancer patients between high and low latitude. Front Genet 2022; 13:944492. [PMID: 35957688 PMCID: PMC9360553 DOI: 10.3389/fgene.2022.944492] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2022] [Accepted: 06/27/2022] [Indexed: 12/24/2022] Open
Abstract
Genetic variation has been shown to affect tumor growth and progression, and the temperature at different latitudes may promote the evolution of genetic variation. Geographical data with latitudinal information is of importance to understand the interplay between genetic variants and environmental influence, such as the temperature, in gastric cancer (GC). In this study, we classified the GC samples from The Cancer Genome Atlas database into two groups based on the latitudinal information of patients and found that GC samples with low-latitude had better clinical outcomes. Further analyses revealed significant differences in other clinical factors such as disease stage and grade between high and low latitudes GC samples. Then, we analyzed the genomic and transcriptomic differences between the two groups. Furthermore, we evaluated the activity score of metabolic pathways and infiltrating immune cells in GC samples with different latitudes using the single-sample gene set enrichment analysis algorithm. These results showed that GC samples at low-latitude had lower tumor mutation burden and subclones as well as higher DNA repair activities. Meanwhile, we found that most immune cells were associated with the prognosis of low-latitude GC patients. At last, we constructed and validated an immune-related prognostic model to evaluate the prognosis of GC samples at different latitudes. This study has provided a further understanding of the geographical contribution to GC at the multiomic level and may benefit the individualized treatment of GC patients at different latitudes.
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Affiliation(s)
- Liqiang Wang
- Key Laboratory of Preservation of Human Genetic Resources and Disease Control in China (Harbin Medical University), Ministry of Education, Harbin, China
- Laboratory of Medical Genetics, Harbin Medical University, Harbin, China
| | - Mengdi Cai
- Key Laboratory of Preservation of Human Genetic Resources and Disease Control in China (Harbin Medical University), Ministry of Education, Harbin, China
- Laboratory of Medical Genetics, Harbin Medical University, Harbin, China
| | - Ying Song
- Key Laboratory of Preservation of Human Genetic Resources and Disease Control in China (Harbin Medical University), Ministry of Education, Harbin, China
- Laboratory of Medical Genetics, Harbin Medical University, Harbin, China
| | - Jing Bai
- Key Laboratory of Preservation of Human Genetic Resources and Disease Control in China (Harbin Medical University), Ministry of Education, Harbin, China
- Laboratory of Medical Genetics, Harbin Medical University, Harbin, China
| | - Wenjing Sun
- Key Laboratory of Preservation of Human Genetic Resources and Disease Control in China (Harbin Medical University), Ministry of Education, Harbin, China
- Laboratory of Medical Genetics, Harbin Medical University, Harbin, China
| | - Jingcui Yu
- Key Laboratory of Preservation of Human Genetic Resources and Disease Control in China (Harbin Medical University), Ministry of Education, Harbin, China
- Scientific Research Centre, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Shuomeng Du
- Key Laboratory of Preservation of Human Genetic Resources and Disease Control in China (Harbin Medical University), Ministry of Education, Harbin, China
- Laboratory of Medical Genetics, Harbin Medical University, Harbin, China
| | - Jianping Lu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
- *Correspondence: Songbin Fu, ; Jianping Lu,
| | - Songbin Fu
- Key Laboratory of Preservation of Human Genetic Resources and Disease Control in China (Harbin Medical University), Ministry of Education, Harbin, China
- Laboratory of Medical Genetics, Harbin Medical University, Harbin, China
- *Correspondence: Songbin Fu, ; Jianping Lu,
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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: 3.3] [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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