ArticleNature communications2021
Global computational alignment of tumor and cell line transcriptional profiles.
Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 89 papers.
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Who cites it
89 citing papers in PubMed.
- Hierarchical modeling of tumor subtypes in cell lines using large-scale genomic datasets.iScience · 2026Article
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- Decoding cellular vulnerabilities for interpretable drug response prediction.Briefings in bioinformatics · 2026Article
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- Systematic pathway-level analysis defines conserved transcriptional divergence between primary lung tumors and cell line models.Animal models and experimental medicine · 2026Article
- Predicting gene essentiality and drug response from preclinical perturbation screens with layered ensemble of autoencoders and predictors.Scientific reports · 2026Article
- Transcriptional states define dependencies and therapeutic vulnerabilities in head and neck cancer.NPJ precision oncology · 2026Article
- Targeting Neuropeptide Y/DPP4 Signalling Suppresses Ewing Sarcoma Survival and Improves Monocyte Viability.International journal of molecular sciences · 2026Article
- A self-adaptive and versatile tool for eliminating multiple undesirable variations from large-scale transcriptomes.Nature biomedical engineering · 2026Article
- Discovery of predictive biomarkers for cancer therapy through computational approaches.Nature reviews. Clinical oncology · 2026Review
- A Pan-Cancer Single-Cell Atlas to Evaluate Tumor Identity, Cell Line Concordance, and Dependency Mapping.bioRxiv : the preprint server for biology · 2026Article
- Multi-omic integration identifies broad drug resistance mechanisms and strategies to therapeutically reprogram cancer cells.iScience · 2026Article
- KCTD10 as a selective cancer dependency from transcription-replication conflicts (TRCs).Ageing and cancer research & treatment · 2026Article
- EPI-SauriCas9-based mouse ovarian cancer models recapitulating pten deletion in patients.Communications biology · 2025Article
- Advances and Challenges in Drug Screening for Cancer Therapy: A Comprehensive Review.Bioengineering (Basel, Switzerland) · 2025Review
- Generative Design of Cell Type-Specific RNA Splicing Elements for Programmable Gene Regulation.bioRxiv : the preprint server for biology · 2025Article
- Investigation of the heterogeneity of cancer cells using single cell CaCell communication and signaling : CCS · 2025Article
- Cell-intrinsic platinum response and associated genetic and gene expression signatures in ovarian cancer.Cancer gene therapy · 2025Article
- Scalable, compressed phenotypic screening using pooled perturbations.Nature biotechnology · 2025Article
- CellHit: a web server to predict and analyze cancer patients' drug responsiveness.Nucleic acids research · 2025Article
29 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
Cell lines are key tools for preclinical cancer research, but it remains unclear how well they represent patient tumor samples. Direct comparisons of tumor and cell line transcriptional profiles are complicated by several factors, including the variable presence of normal cells in tumor samples. We thus develop an unsupervised alignment method (Celligner) and apply it to integrate several large-scale cell line and tumor RNA-Seq datasets. Although our method aligns the majority of cell lines with tumor samples of the same cancer type, it also reveals large differences in tumor similarity across cell lines. Using this approach, we identify several hundred cell lines from diverse lineages that present a more mesenchymal and undifferentiated transcriptional state and that exhibit distinct chemical and genetic dependencies. Celligner could be used to guide the selection of cell lines that more closely resemble patient tumors and improve the clinical translation of insights gained from cell lines.
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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 OpenQuestion graph.