ArticleCancer letters2024
PCTA, a pan-cancer cell line transcriptome atlas.
Article in Cancer letters, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The organ-specific modulation of malignant processes by opioids: a systematic review of cell culture studies.British journal of cancer · 2025Pooled it
- Article
- ATHENA: A deep learning-based AI for functional prediction of genomic mutations and synergistic vulnerabilities in prostate cancer.bioRxiv : the preprint server for biology · 2025Article
- The Comparative Effect of Morphine on Proliferation of Cancer Cell Lines Originating from Different Organs: An In Vitro Study.Pharmaceuticals (Basel, Switzerland) · 2024Article
- Unveiling novel double-negative prostate cancer subtypes through single-cell RNA sequencing analysis.NPJ precision oncology · 2024Article
- Systematic Multi-Omics Investigation of Androgen Receptor Driven Gene Expression and Epigenetics changes in Prostate Cancer.bioRxiv : the preprint server for biology · 2024Article
- Unveiling Novel Double-Negative Prostate Cancer Subtypes Through Single-Cell RNA Sequencing Analysis.bioRxiv : the preprint server for biology · 2024Article
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Abstract
A substantial volume of RNA sequencing data have been generated from cancer cell lines. However, it requires specific bioinformatics skills to compare gene expression levels across cell lines. This has hindered non-bioinformaticians from fully utilizing these valuable datasets in their research. To bridge this gap, we established a curated Pan-cancer Cell Line Transcriptome Atlas (PCTA) dataset. This resource aims to provide a user-friendly platform, allowing researchers without extensive bioinformatics expertise to access and leverage the wealth of information within the dataset for their studies. The PCTA dataset encompasses the expression matrix of 24,965 genes, featuring data from 84,385 samples derived from 5677 studies. This comprehensive compilation spans 535 cell lines, representing a spectrum of 114 cancer types originating from 30 diverse tissue types. On UMAP plots, cell lines originating from the same type of tissue tend to cluster together, illustrating the dataset's ability to capture biological relationships. Additionally, an interactive and user-friendly web application (https://pcatools.shinyapps.io/PCTA_app/) was developed for researchers to explore the PCTA dataset. This platform allows users to examine the expression of their genes of interest across a diverse array of samples.
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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 OpenQuestion graph.