ArticlePloS one2007
Identification of key processes underlying cancer phenotypes using biologic pathway analysis.
Article in PloS one, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 75 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.
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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
75 citing papers in PubMed.
- Article
- Biopsy and Blood Gene Expression Distinguish Injury, Subclinical and Clinical Rejection in Kidney Transplant Recipients.Transplantation direct · 2026Article
- Sex-specific skeletal muscle gene expression responses to exercise reveal novel direct mediators of insulin sensitivity change.NAR molecular medicine · 2025Article
- Pathway metrics accurately stratify T cells to their cells states.BioData mining · 2024Article
- A high-dimensional omnibus test for set-based association analysis.Briefings in bioinformatics · 2024Article
- Robustness evaluations of pathway activity inference methods on gene expression data.BMC bioinformatics · 2024Article
- Functional Profiling of Soft Tissue Sarcoma Using Mechanistic Models.International journal of molecular sciences · 2023Article
- Discovering potential interactions between rare diseases and COVID-19 by combining mechanistic models of viral infection with statistical modeling.Human molecular genetics · 2022Article
- Sample-Specific Perturbation of Gene Interactions Identifies Pancreatic Cancer Subtypes.International journal of molecular sciences · 2022Article
- Computational prediction of intracellular targets of wild-type or mutant vesicular stomatitis matrix protein.PloS one · 2022Article
- Pathway-Based Personalized Analysis of Pan-Cancer Transcriptomic Data.Biomedicines · 2021Article
- Sample-specific perturbation of gene interactions identifies breast cancer subtypes.Briefings in bioinformatics · 2021Article
- Popularity and performance of bioinformatics software: the case of gene set analysis.BMC bioinformatics · 2021Article
- Genome-scale mechanistic modeling of signaling pathways made easy: A bioconductor/cytoscape/web server framework for the analysis of omic data.Computational and structural biotechnology journal · 2021Article
- Predicting and affecting response to cancer therapy based on pathway-level biomarkers.Nature communications · 2020Article
- Article
- Using mechanistic models for the clinical interpretation of complex genomic variation.Scientific reports · 2019Article
- High GILT Expression and an Active and Intact MHC Class II Antigen Presentation Pathway Are Associated with Improved Survival in Melanoma.Journal of immunology (Baltimore, Md. : 1950) · 2019Article
- Topologically inferring active miRNA-mediated subpathways toward precise cancer classification by directed random walk.Molecular oncology · 2019Article
- Astrocyte-specific transcriptome analysis using the ALDH1L1 bacTRAP mouse reveals novel biomarkers of astrogliosis in response to neurotoxicity.Journal of neurochemistry · 2019Article
15 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Cancer is recognized to be a family of gene-based diseases whose causes are to be found in disruptions of basic biologic processes. An increasingly deep catalogue of canonical networks details the specific molecular interaction of genes and their products. However, mapping of disease phenotypes to alterations of these networks of interactions is accomplished indirectly and non-systematically. Here we objectively identify pathways associated with malignancy, staging, and outcome in cancer through application of an analytic approach that systematically evaluates differences in the activity and consistency of interactions within canonical biologic processes. Using large collections of publicly accessible genome-wide gene expression, we identify small, common sets of pathways - Trka Receptor, Apoptosis response to DNA Damage, Ceramide, Telomerase, CD40L and Calcineurin - whose differences robustly distinguish diverse tumor types from corresponding normal samples, predict tumor grade, and distinguish phenotypes such as estrogen receptor status and p53 mutation state. Pathways identified through this analysis perform as well or better than phenotypes used in the original studies in predicting cancer outcome. This approach provides a means to use genome-wide characterizations to map key biological processes to important clinical features in disease.
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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.