ArticleCancer informatics2026
iCRCexp: An Integrative Database for Colorectal Cancer-Associated Gene Expression Profiles.
Article in Cancer informatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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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Authors and funding
9 authors.
Funding
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Abstract
Background: Colorectal cancer (CRC) is a leading cause of tumor-related mortality. Recent studies have shown that the transcriptome plays an important role in the development and occurrence of CRC. However, a comprehensive repository of CRC transcriptome sequencing data is unavailable. In the present study, we constructed a colorectal database (iCRCexp; http://icrcexp.omicsbio.info/). Method: We collected CRC-related transcriptome datasets from The Cancer Genome Atlas (TCGA) and National Center for Biotechnology Information (NCBI) Gene Ontology Omnibus (GEO) databases up to 2022. The sequencing data were preprocessed through a unified pipeline and subsequently analyzed. CRC-related genes and drugs were identified via text mining of the PubMed abstracts. Results: A total of 18 466 tissue samples from 231 studies, 2429 CRC-related genes, and 1852 CRC-related drugs were collected and integrated into iCRCexp. Among these studies, 251 CRC-related datasets were identified with abundant characteristic information, including tissue source, baseline characteristics, therapeutic responses, recurrence and metastasis, and survival. We conducted differential correlation and survival analyses. We predicted potential target drugs for CRC-related genes by calculating connectivity scores. Consequently, we integrated these analysis results through network construction and presented them in a CRC database. Conclusion: A comprehensive resource, including CRC-related gene and medication information and an expression analysis platform, was constructed for the CRC community.
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Registered trials
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