ArticleNature communications2024
Network-based elucidation of colon cancer drug resistance mechanisms by phosphoproteomic time-series analysis.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed.
- Targeting GLUTs in Cancer: Mechanisms, Combination Strategies, and Translational Challenges.Current medical science · 2026Review
- Mechanisms and advances of drug resistance in colorectal cancer: A systematic overview of multi-layered regulatory networks.Translational oncology · 2026Review
- Complex assembly and activity states as multifaceted protein attributes explaining phenotypic variability.Molecular systems biology · 2026Article
- Virtual cell: Current perspectives and future prospects.The Journal of international medical research · 2026Review
- Epigenetic modifications in cancer drug resistance: molecular mechanisms and therapeutic interventions.Molecular biomedicine · 2026Review
- Complex Assembly and Activity States as Multifaceted Protein Attributes Explaining Phenotypic Variability.bioRxiv : the preprint server for biology · 2025Article
- Increased CDKN2A expression correlates with resistance to platinum-based therapy and decreased infiltration of B lymphocytes in colon adenocarcinoma.Functional & integrative genomics · 2025Article
- Elucidating the role of artificial intelligence in drug development from the perspective of drug-target interactions.Journal of pharmaceutical analysis · 2025Review
- Advances in Precision Medicine Approaches for Colorectal Cancer: From Molecular Profiling to Targeted Therapies.ACS pharmacology & translational science · 2024Review
- Dysregulated Signalling Pathways Driving Anticancer Drug Resistance.International journal of molecular sciences · 2023Review
- Integrating Multi-Omics Mendelian Randomization and Functional Validation to Identify Novel Apoptosis Regulators in Follicular Lymphoma.Technology in cancer research & treatmentArticle
Corrections and comments
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Authors and funding
13 authors.
Funding
Abstract
Aberrant signaling pathway activity is a hallmark of tumorigenesis and progression, which has guided targeted inhibitor design for over 30 years. Yet, adaptive resistance mechanisms, induced by rapid, context-specific signaling network rewiring, continue to challenge therapeutic efficacy. Leveraging progress in proteomic technologies and network-based methodologies, we introduce Virtual Enrichment-based Signaling Protein-activity Analysis (VESPA)-an algorithm designed to elucidate mechanisms of cell response and adaptation to drug perturbations-and use it to analyze 7-point phosphoproteomic time series from colorectal cancer cells treated with clinically-relevant inhibitors and control media. Interrogating tumor-specific enzyme/substrate interactions accurately infers kinase and phosphatase activity, based on their substrate phosphorylation state, effectively accounting for signal crosstalk and sparse phosphoproteome coverage. The analysis elucidates time-dependent signaling pathway response to each drug perturbation and, more importantly, cell adaptive response and rewiring, experimentally confirmed by CRISPR knock-out assays, suggesting broad applicability to cancer and other diseases.
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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.