ArticleiScience2019
Perturbational Gene-Expression Signatures for Combinatorial Drug Discovery.
Article in iScience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 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
21 citing papers in PubMed, 33 citations in OpenAlex.
- DRIVE: a comprehensive resource deciphering drug-induced transcriptomic and splicing response in cancer cell.Neoplasia (New York, N.Y.) · 2026Article
- Review
- Quantitative Proteomics Unveils the Synergistic Effects of Combination Drugs on Cytoskeleton Composition and Autophagy-Mediated Cell Death in Neuroblastoma.Journal of proteome research · 2025Article
- iDOMO: identification of drug combinations via multi-set operations for treating diseases.Briefings in bioinformatics · 2024Article
- Article
- Article
- DrSim: Similarity Learning for Transcriptional Phenotypic Drug Discovery.Genomics, proteomics & bioinformatics · 2022Article
- BI-2536 Promotes Neuroblastoma Cell Death via Minichromosome Maintenance Complex Components 2 and 10.Pharmaceuticals (Basel, Switzerland) · 2021Article
- Predicting candidate therapeutic drugs for sepsis-induced acute respiratory distress syndrome based on transcriptome profiling.Bioengineered · 2021Article
- Reconciling multiple connectivity scores for drug repurposing.Briefings in bioinformatics · 2021Article
- On the robustness of generalization of drug-drug interaction models.BMC bioinformatics · 2021Article
- DeepCellState: An autoencoder-based framework for predicting cell type specific transcriptional states induced by drug treatment.PLoS computational biology · 2021Article
- Prediction and identification of synergistic compound combinations against pancreatic cancer cells.iScience · 2021Article
- Systems Medicine Design for Triple-Negative Breast Cancer and Non-Triple-Negative Breast Cancer Based on Systems Identification and Carcinogenic Mechanisms.International journal of molecular sciences · 2021Article
- Prediction of Synergistic Drug Combinations for Prostate Cancer by Transcriptomic and Network Characteristics.Frontiers in pharmacology · 2021Article
- Enhancement of the IFN-β-induced host signature informs repurposed drugs for COVID-19.Heliyon · 2020Article
- The Clinical Kinase Index: A Method to Prioritize Understudied Kinases as Drug Targets for the Treatment of Cancer.Cell reports. Medicine · 2020Article
- Article
- Universal Nature of Drug Treatment Responses in Drug-Tissue-Wide Model-Animal Experiments Using Tensor Decomposition-Based Unsupervised Feature Extraction.Frontiers in genetics · 2020Article
- Transcriptomics predicts compound synergy in drug and natural product treated glioblastoma cells.PloS one · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cancer is a complex disease that relies on both oncogenic mutations and non-mutated genes for survival, and therefore coined as oncogene and non-oncogene addictions. The need for more effective combination therapies to overcome drug resistance in oncology has been increasingly recognized, but the identification of potentially synergistic drugs at scale remains challenging. Here we propose a gene-expression-based approach, which uses the recurrent perturbation-transcript regulatory relationships inferred from a large compendium of chemical and genetic perturbation experiments across multiple cell lines, to engender a testable hypothesis for combination therapies. These transcript-level recurrences were distinct from known compound-protein target counterparts, were reproducible in external datasets, and correlated with small-molecule sensitivity. We applied these recurrent relationships to predict synergistic drug pairs for cancer and experimentally confirmed two unexpected drug combinations in vitro. Our results corroborate a gene-expression-based strategy for combinatorial drug screening as a way to target non-mutated genes in complex diseases.
Indexed as
Identifiers
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.