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Cited by 6,086Gene expression and cancer classificationBioinformatics and Genomic NetworksCancer Genomics and Diagnostics

UALCAN: A Portal for Facilitating Tumor Subgroup Gene Expression and Survival Analyses

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Chandrashekar, Darshan S., Bashel, Bhuwan, Balasubramanya, Sai Akshaya Hodigere, Creighton, Chad J., Ponce-Rodriguez, Israel, Chakravarthi, Balabhadrapatruni V.S.K., Varambally, Sooryanarayana·2017·Neoplasia
DOI 10.1016/j.neo.2017.05.002PMC PMC5516091
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Abstract

Genomics data from The Cancer Genome Atlas (TCGA) project has led to the comprehensive molecular characterization of multiple cancer types. The large sample numbers in TCGA offer an excellent opportunity to address questions associated with tumo heterogeneity. Exploration of the data by cancer researchers and clinicians is imperative to unearth novel therapeutic/diagnostic biomarkers. Various computational tools have been developed to aid researchers in carrying out specific TCGA data analyses; however there is need for resources to facilitate the study of gene expression variations and survival associations across tumors. Here, we report UALCAN, an easy to use, interactive web-portal to perform to in-depth analyses of TCGA gene expression data. UALCAN uses TCGA level 3 RNA-seq and clinical data from 31 cancer types. The portal's user-friendly features allow to perform: 1) analyze relative expression of a query gene(s) across tumor and normal samples, as well as in various tumor sub-groups based on individual cancer stages, tumor grade, race, body weight or other clinicopathologic features, 2) estimate the effect of gene expression level and clinicopathologic features on patient survival; and 3) identify the top over- and under-expressed (up and down-regulated) genes in individual cancer types. This resource serves as a platform for in silico validation of target genes and for identifying tumor sub-group specific candidate biomarkers. Thus, UALCAN web-portal could be extremely helpful in accelerating cancer research. UALCAN is publicly available at http://ualcan.path.uab.edu.

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  • In human HCCs, higher expression of GSTM3 was associated with shorter survival.

    “In human HCCs, higher expression of GSTM3 was associated with shorter survival (fig. S7E) (44, 45).”

    From The origin of hepatocellular carcinoma depends on metabolic zonation (2026) · cites this paper as [44]

    The Methods (Data Analyses; page unavailable) describe survival analyses by gene expression, and the Results (Usage of UALCAN; page unavailable) discuss liver hepatocellular carcinoma. Neither reports a GSTM3 survival result or says whether higher GSTM3 expression is associated with shorter survival. Searches for GSTM3 and its full gene name found no such passage in our copy. (LLM, conf=0.76)

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Authors
Chandrashekar, D. S., Bashel, B., Balasubramanya, S. A. H., Creighton, C. J., Ponce-Rodriguez, I., Chakravarthi, B. V. S. K., & Varambally, S.
Affiliations
  • University of Alabama at Birmingham (US)
  • Baylor College of Medicine (US)
Corresponding author
Varambally, Sooryanarayana
ORCID
Venue
Neoplasia
Publisher
Elsevier BV
Published
2017-08
Volume
19
Issue
8
Pages
649-658
ISSN
1476-5586 (ISSN-L)
DOI
10.1016/j.neo.2017.05.002
PMC
PMC5516091
OpenAlex
W2736730167
Cited by
6,086
References
7
Citations by year
2026: 271 · 2025: 534 · 2024: 676 · 2023: 938 · 2022: 1326 · 2021: 1192 · 2020: 769 · 2019: 282 · 2018: 84 · 2017: 6 · 2013: 1
FWCI
127.73
Type
journal article
Language
en
Open access
Licence
Locations
  • Neoplasia (publishedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • Breast Cancer Research Foundation
  • University of Alabama
  • National Institutes of Health (CA125123)
  • National Cancer Institute (R01CA154980, CA125123, R01CA157845, P30CA125123)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
Keywords
web portal, TCGA, tumor heterogeneity, tumor subtypes, gene expression, survival analysis, RNA-seq, biomarker discovery, tumor stage, tumor grade, clinicopathological features, up- and down-regulated genes, in silico validation
MeSH terms
Humans, Neoplasms, Prognosis, Software, User-Computer Interface, Gene Expression Regulation, Neoplastic, Survival Analysis, Computational Biology, Gene Expression Profiling, Databases, Genetic, Kaplan-Meier Estimate, Web Browser

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