ArticleCancer research2023
The Genetic, Pharmacogenomic, and Immune Landscapes Associated with Protein Expression across Human Cancers.
Article in Cancer research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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.
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.
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Who cites it
7 citing papers in PubMed, 9 citations in OpenAlex.
- Functional, Pharmacogenomic, and Immune Landscapes of Long Non-Coding RNAs in Cancer.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Characterization of Tumor Antigens from Multi-omics Data: Computational Approaches and Resources.Genomics, proteomics & bioinformatics · 2025Review
- Comprehensive characterization of the transcriptional landscape in Alzheimer's disease (AD) brains.Science advances · 2025Article
- Applications and advances of multi-omics technologies in gastrointestinal tumors.Frontiers in medicine · 2025Review
- A pan-cancer analysis of the core pre-mRNA 3' end processing factors, and their association with prognosis, tumor microenvironment, and potential targets.Scientific reports · 2024Article
- Genomic hallmarks and therapeutic targets of ribosome biogenesis in cancer.Briefings in bioinformatics · 2024Article
- PancanQTLv2.0: a comprehensive resource for expression quantitative trait loci across human cancers.Nucleic acids research · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 1 country.
Funding
Abstract
Proteomics is a powerful approach that can rapidly enhance our understanding of cancer development. Detailed characterization of the genetic, pharmacogenomic, and immune landscape in relation to protein expression in patients with cancer could provide new insights into the functional roles of proteins in cancer. By taking advantage of the genotype data from The Cancer Genome Atlas and protein expression data from The Cancer Proteome Atlas, we characterized the effects of genetic variants on protein expression across 31 cancer types and identified approximately 100,000 protein quantitative trait loci (pQTL). Among these, over 8000 pQTLs were associated with patient overall survival. Furthermore, characterization of the impact of protein expression on more than 350 imputed anticancer drug responses in patients revealed nearly 230,000 significant associations. In addition, approximately 21,000 significant associations were identified between protein expression and immune cell abundance. Finally, a user-friendly data portal, GPIP (https://hanlaboratory.com/GPIP), was developed featuring multiple modules that enable researchers to explore, visualize, and browse multidimensional data. This detailed analysis reveals the associations between the proteomic landscape and genetic variation, patient outcome, the immune microenvironment, and drug response across cancer types, providing a resource that may offer valuable clinical insights and encourage further functional investigations of proteins in cancer. SIGNIFICANCE: Comprehensive characterization of the relationship between protein expression and the genetic, pharmacogenomic, and immune landscape of tumors across cancer types provides a foundation for investigating the role of protein expression in cancer development and treatment.
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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.