ArticleNature genetics2024
A combinatorial genetic strategy for exploring complex genotype-phenotype associations in cancer.
Article in Nature genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- NetG2P: Network-based genotype-to-phenotype transformation identifies key signaling crosstalk for prognosis in pan-cancer study.BMC biology · 2026Article
- Integrated in vivo combinatorial functional genomics and spatial transcriptomics of tumours to decode genotype-to-phenotype relationships.Nature biomedical engineering · 2026Article
- The Reg gene family: roles in gastric and colorectal cancer progression and its potential for targeted therapy.Discover oncology · 2025Review
- Therapeutic Potential of Glucose Oxidase-Loaded Biogenic Mesoporous Silica Nanoparticles in Ovarian Cancer.Pharmaceuticals (Basel, Switzerland) · 2025Article
- Defined cellular reprogramming of androgen receptor-active prostate cancer to neuroendocrine prostate cancer.bioRxiv : the preprint server for biology · 2025Article
- N7-methylguanosine modification in cancers: from mechanisms to therapeutic potential.Journal of hematology & oncology · 2025Review
- CRISPR/Cas9 technology in tumor research and drug development application progress and future prospects.Frontiers in pharmacology · 2025Review
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14 authors.
Funding
Abstract
Available genetically defined cancer models are limited in genotypic and phenotypic complexity and underrepresent the heterogeneity of human cancer. Here, we describe a combinatorial genetic strategy applied to an organoid transformation assay to rapidly generate diverse, clinically relevant bladder and prostate cancer models. Importantly, the clonal architecture of the resultant tumors can be resolved using single-cell or spatially resolved next-generation sequencing to uncover polygenic drivers of cancer phenotypes.
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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.