ArticleCell systems2018
Genome-Scale Signatures of Gene Interaction from Compound Screens Predict Clinical Efficacy of Targeted Cancer Therapies.
Article in Cell systems, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
What it found
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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.
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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
32 citing papers in PubMed, 67 citations in OpenAlex.
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- Comparative analyses of gene networks mediating cancer metastatic potentials across lineage types.Briefings in bioinformatics · 2024Article
- Integrated single-cell and bulk sequencing analyses with experimental validation identify the prognostic and immunological implications of CD226 in pan-cancer.Journal of cancer research and clinical oncology · 2023Article
- Comprehensive bioinformatic analysis of the expression and prognostic significance of TSC22D domain family genes in adult acute myeloid leukemia.BMC medical genomics · 2023Article
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- Identification of a venetoclax-resistance prognostic signature base on 6-senescence genes and its clinical significance for acute myeloid leukemia.Frontiers in oncology · 2023Article
- Six-Transmembrane Epithelial Antigen of Prostate 4: An Indicator of Prognosis and Tumor Immunity in Hepatocellular Carcinoma.Journal of hepatocellular carcinoma · 2023Article
- EZH2 as a Prognostic Factor and Its Immune Implication with Molecular Characterization in Prostate Cancer: An Integrated Multi-Omics in Silico Analysis.Biomolecules · 2022Article
- ATG101-related signature predicts prognosis and therapeutic option in hepatocellular carcinoma.Scientific reports · 2022Article
- TET1 mutations as a predictive biomarker for immune checkpoint inhibitors in colon adenocarcinoma.World journal of surgical oncology · 2022Article
- Selective inference for effect modification via the lasso.Journal of the Royal Statistical Society. Series B, Statistical methodology · 2022Article
- Integrative Bioinformatics Analysis Reveals CHEK1 and UBE2C as Luminal A Breast Cancer Subtype Biomarkers.Frontiers in genetics · 2022Article
- KIF2C is a Biomarker Correlated With Prognosis and Immunosuppressive Microenvironment in Human Tumors.Frontiers in genetics · 2022Article
- Methylation-Mediated Silencing ofJournal of oncology · 2022Article
- The established chemokine-related prognostic gene signature in prostate cancer: Implications for anti-androgen and immunotherapies.Frontiers in immunology · 2022Article
- Article
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 2 countries.
Funding
Abstract
Identifying reliable drug response biomarkers is a significant challenge in cancer research. We present computational analysis of resistance (CARE), a computational method focused on targeted therapies, to infer genome-wide transcriptomic signatures of drug efficacy from cell line compound screens. CARE outputs genome-scale scores to measure how the drug target gene interacts with other genes to affect the inhibitor efficacy in the compound screens. Such statistical interactions between drug targets and other genes were not considered in previous studies but are critical in identifying predictive biomarkers. When evaluated using transcriptome data from clinical studies, CARE can predict the therapy outcome better than signatures from other computational methods and genomics experiments. Moreover, the CARE signatures for the PLX4720 BRAF inhibitor are associated with an anti-programmed death 1 clinical response, suggesting a common efficacy signature between a targeted therapy and immunotherapy. When searching for genes related to lapatinib resistance, CARE identified PRKD3 as the top candidate. PRKD3 inhibition, by both small interfering RNA and compounds, significantly sensitized breast cancer cells to lapatinib. Thus, CARE should enable large-scale inference of response biomarkers and drug combinations for targeted therapies using compound screen data.
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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.