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Cited by 2,473Gene expression and cancer classificationBioinformatics and Genomic NetworksCancer Genomics and Diagnostics

UALCAN: An update to the integrated cancer data analysis platform

Open access
Chandrashekar, Darshan Shimoga, Karthikeyan, Santhosh Kumar, Korla, Praveen Kumar, Patel, Henalben, Shovon, Ahmedur Rahman, Athar, Mohammad, Netto, George J., Qin, Zhaohui S. +4 more·2022·Neoplasia
DOI 10.1016/j.neo.2022.01.001PMC PMC8788199
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Abstract

Cancer genomic, transcriptomic, and proteomic profiling has generated extensive data that necessitate the development of tools for its analysis and dissemination. We developed UALCAN to provide a portal for easy exploring, analyzing, and visualizing these data, allowing users to integrate the data to better understand the gene, proteins, and pathways perturbed in cancer and make discoveries. UALCAN web portal enables analyzing and delivering cancer transcriptome, proteomics, and patient survival data to the cancer research community. With data obtained from The Cancer Genome Atlas (TCGA) project, UALCAN has enabled users to evaluate protein-coding gene expression and its impact on patient survival across 33 types of cancers. The web portal has been used extensively since its release and received immense popularity, underlined by its usage from cancer researchers in more than 100 countries. The present manuscript highlights the task we have undertaken and updates that we have made to UALCAN since its release in 2017. Extensive user feedback motivated us to expand the resource by including data on a) microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and promoter DNA methylation from TCGA and b) mass spectrometry-based proteomics from the Clinical Proteomic Tumor Analysis Consortium (CPTAC). UALCAN provides easy access to pre-computed, tumor subgroup-based gene/protein expression, promoter DNA methylation status, and Kaplan-Meier survival analyses. It also provides new visualization features to comprehend and integrate observations and aids in generating hypotheses for testing. UALCAN is accessible 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 [45]

    The Methods section (Survival analyses; page not provided) describes how UALCAN compares survival by expression level. Searches for GSTM3 and HCC found no passage in our copy reporting whether higher GSTM3 expression is associated with shorter survival in human HCCs. (LLM, conf=0.75)

    Experimental — accuracy not yet measured

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Research works printed but not linked: 23

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Cited by

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Authors
Chandrashekar, D. S., Karthikeyan, S. K., Korla, P. K., Patel, H., Shovon, A. R., Athar, M., Netto, G. J., Qin, Z. S., Kumar, S., Manne, U., Creighton, C. J., & Varambally, S.
Affiliations
  • University of Alabama at Birmingham (US)
  • Emory University (US)
  • Baylor College of Medicine (US)
  • University of Michigan (US)
Corresponding author
Chandrashekar, Darshan Shimoga
ORCID
Venue
Neoplasia
Publisher
Elsevier BV
Published
2022-03
Volume
25
Pages
18-27
ISSN
1476-5586 (ISSN-L)
DOI
10.1016/j.neo.2022.01.001
PMC
PMC8788199
OpenAlex
W4206965224
Cited by
2,473
References
1
Citations by year
2026: 439 · 2025: 675 · 2024: 737 · 2023: 495 · 2022: 124
FWCI
170.71
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
  • U.S. Department of Defense (W81XWH-19-1-0588, CA125123)
  • National Institutes of Health (U54 CA118948)
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
cancer transcriptomics, cancer proteomics, gene expression, protein expression, promoter methylation, microRNA, long non-coding RNA, TCGA, CPTAC, tumor subtypes, data visualization, web portal
MeSH terms
Data Analysis, Humans, Neoplasms, DNA Methylation, Gene Expression Profiling, Genomics, Proteomics

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