ReviewCancer research2019
An Interactive Resource to Probe Genetic Diversity and Estimated Ancestry in Cancer Cell Lines.
Review in Cancer research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
51 citing papers in PubMed.
- Epithelial YPEL3 Modulates CD8Cancer science · 2026Article
- Article
- Multi-omics evaluation of cell lines as models for metastatic prostate cancer.Communications biology · 2026Article
- AML Disparities Across Racial Ancestry Groups: A Spotlight on the NPM1 Mutations.International journal of molecular sciences · 2026Review
- Strengthening Biomedical Research and Healthcare in Africa Through Localized Reagent Production.BioMed research international · 2026Review
- Integrated Multi-Omics Analysis Constructs an Intratumoral Heterogeneity-Corrected Prognostic Signature for Cervical Cancer.International journal of general medicine · 2026Article
- Inhibition of RNA-binding proteins enhances immunotherapy in ovarian cancer.Signal transduction and targeted therapy · 2025Article
- Review
- Artificial intelligence in cancer: applications, challenges, and future perspectives.Molecular cancer · 2025Review
- Reconstructing the hepatocellular carcinoma microenvironment: the current status and challenges of 3D culture technology.Discover oncology · 2025Review
- Equitable machine learning counteracts ancestral bias in precision medicine.Nature communications · 2025Article
- Dissecting the molecular landscape of Parkinson's disease and Parkinson's disease dementia using highly efficient snRNA-seq (HIF-snRNA-seq).bioRxiv : the preprint server for biology · 2025Article
- Strategies for the drug development of cancer therapeutics.Frontiers in pharmacology · 2025Review
- Optimization of computational ancestry inference for use in cancer cell lines.Biology methods & protocols · 2025Article
- Review
- Regulation of volume-regulated anion channels alters sensitivity to platinum chemotherapy.Science advances · 2024Article
- Particles and Prejudice: Nanomedicine Approaches to Reducing Health Disparities in Endometrial Cancer.Small (Weinheim an der Bergstrasse, Germany) · 2024Review
- Genetic diversity among the present Japanese population: evidence from genotyping of human cell lines established in Japan.Human cell · 2024Article
- Germline variation contributes to false negatives in CRISPR-based experiments with varying burden across ancestries.Nature communications · 2024Article
- Regulation of respiratory complex I assembly by FMN cofactor targeting.Redox biology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Recent work points to a lack of diversity in genomics studies from genome-wide association studies to somatic (tumor) genome analyses. Yet, population-specific genetic variation has been shown to contribute to health disparities in cancer risk and outcomes. Immortalized cancer cell lines are widely used in cancer research, from mechanistic studies to drug screening. Larger collections of cancer cell lines better represent the genomic heterogeneity found in primary tumors. Yet, the genetic ancestral origin of cancer cell lines is rarely acknowledged and often unknown. Using genome-wide genotyping data from 1,393 cancer cell lines from the Catalogue of Somatic Mutations in Cancer (COSMIC) and Cancer Cell Line Encyclopedia (CCLE), we estimated the genetic ancestral origin for each cell line. Our data indicate that cancer cell line collections are not representative of the diverse ancestry and admixture characterizing human populations. We discuss the implications of genetic ancestry and diversity of cellular models for cancer research and present an interactive tool, Estimated Cell Line Ancestry (ECLA), where ancestry can be visualized with reference populations of the 1000 Genomes Project. Cancer researchers can use this resource to identify cell line models for their studies by taking ancestral origins into consideration.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.