ArticleCell2016
A Landscape of Pharmacogenomic Interactions in Cancer.
Article in Cell, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1,251 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
1,251 citing papers in PubMed, 2,211 citations in OpenAlex.
- Biologically-informed integration of drug representations for breast cancer treatment using deep learning.Nature communications · 2025Trial
- A predictive endocrine resistance index accurately stratifies luminal breast cancer treatment responders and nonresponders.The Journal of clinical investigation · 2025Trial
- GATRSyn: Advancing Anticancer Drug Synergy Prediction Through Graph Attention Networks and Transformer-based Feature Re-embedding.Interdisciplinary sciences, computational life sciences · 2026Article
- Decomposition-driven biomarker identification enhances non-invasive early cancer detection.iScience · 2026Article
- Interpretable neural networks prioritize cancer driver genes from genome-wide dependency landscapes.PLoS computational biology · 2026Article
- Integrative Transcriptomic and Proteomic Profiling Identifies S100P as a Potential Functional Biomarker for Sessile Serrated Lesions.Digestive diseases and sciences · 2026Article
- A phosphoproteome atlas of human cell lines reveals the landscape of kinase activity.Nature structural & molecular biology · 2026Article
- Epithelial interferon-stimulated gene programs modulate chemotherapy sensitivity in colorectal cancer via EPSTI1.Oncogene · 2026Article
- Transcriptome-Based Synthetic Lethality Predictions to Improve Targeted Therapy/Immunotherapy Treatment Prioritization in Nonmetastatic Breast Cancer: BC-SELECT.Cancer research communications · 2026Article
- AI-enabled multi-omics pharmacogenomic modeling guides resistance-aware multitarget optimization of venetoclax therapy in acute myeloid leukemia.NPJ precision oncology · 2026Article
- A Systematic Machine Learning Framework for Evaluating and Ranking Omics Layers in Cancer Drug Response Prediction.Current issues in molecular biology · 2026Article
- Article
- Lipid droplet-associated gene signatures classify metabolic subtypes and identify PLIN3 as a key driver in hepatocellular carcinoma.Genes & diseases · 2026Article
- Decoding cellular vulnerabilities for interpretable drug response prediction.Briefings in bioinformatics · 2026Article
- Article
- Virtual cells: progress and challenges from mechanistic modeling to data-driven integration.Briefings in bioinformatics · 2026Review
- DECANT: decoupling mechanism from context in single-cell drug perturbation representation.Bioinformatics (Oxford, England) · 2026Article
- OX40 (TNFRSF4) Tracks Immune Infiltration in Small Cell Lung Cancer and Shows a Cohort-Specific, Non-Replicated Association with the POU2F3/SCLC-P Subtype: A Multi-Source In Silico Analysis.International journal of molecular sciences · 2026Article
- Article
- Exceptional treatment responses and molecular markers among 103 colorectal cancer cell lines.Molecular biomedicine · 2026Article
1,191 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
39 authors at 16 institutions in 5 countries.
Funding
Abstract
Systematic studies of cancer genomes have provided unprecedented insights into the molecular nature of cancer. Using this information to guide the development and application of therapies in the clinic is challenging. Here, we report how cancer-driven alterations identified in 11,289 tumors from 29 tissues (integrating somatic mutations, copy number alterations, DNA methylation, and gene expression) can be mapped onto 1,001 molecularly annotated human cancer cell lines and correlated with sensitivity to 265 drugs. We find that cell lines faithfully recapitulate oncogenic alterations identified in tumors, find that many of these associate with drug sensitivity/resistance, and highlight the importance of tissue lineage in mediating drug response. Logic-based modeling uncovers combinations of alterations that sensitize to drugs, while machine learning demonstrates the relative importance of different data types in predicting drug response. Our analysis and datasets are rich resources to link genotypes with cellular phenotypes and to identify therapeutic options for selected cancer sub-populations.
Indexed as
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What OpenQuestion 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 OpenQuestion graph.