ArticleJCO clinical cancer informatics2022
Shared Nearest Neighbors Approach and Interactive Browser for Network Analysis of a Comprehensive Non-Small-Cell Lung Cancer Data Set.
Article in JCO clinical cancer informatics, 2022. 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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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.
- Concordance analysis of DNA and RNA profiling: The MD Anderson IMPACT2 study in precision oncology.Signal transduction and targeted therapy · 2026Trial
- FOXM1-Specific TCR-Engineered T Cells Target Non-Small Cell Lung Cancer.Cancer immunology research · 2026Article
- Article
- Synthetic PET from CT improves diagnosis and prognosis for lung cancer: Proof of concept.Cell reports. Medicine · 2024Article
- ATM Mutations Associate with Distinct Co-Mutational Patterns and Therapeutic Vulnerabilities in NSCLC.Clinical cancer research : an official journal of the American Association for Cancer Research · 2023Article
- Autotaxin suppresses cytotoxic T cells via LPAR5 to promote anti-PD-1 resistance in non-small cell lung cancer.The Journal of clinical investigation · 2023Article
- EMT activates exocytotic Rabs to coordinate invasion and immunosuppression in lung cancer.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
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Authors and funding
35 authors.
Funding
Abstract
purposeAdvances in biological measurement technologies are enabling large-scale studies of patient cohorts across multiple omics platforms. Holistic analysis of these data can generate actionable insights for translational research and necessitate new approaches for data integration and mining.
methodsWe present a novel approach for integrating data across platforms on the basis of the shared nearest neighbors algorithm and use it to create a network of multiplatform data from the immunogenomic profiling of non-small-cell lung cancer project.
resultsBenchmarking demonstrates that the shared nearest neighbors-based network approach outperforms a traditional gene-gene network in capturing established interactions while providing new ones on the basis of the interplay between measurements from different platforms. When used to examine patient characteristics of interest, our approach provided signatures associated with and new leads related to recurrence and TP53 oncogenotype.
conclusionThe network developed offers an unprecedented, holistic view into immunogenomic profiling of non-small-cell lung cancer, which can be explored through the accompanying interactive browser that we built.
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