Data in Brief (Jun 2023)

Transcriptomic data of bevacizumab-adapted colorectal adenocarcinoma cells HCT-116

  • Sala Cesare,
  • Lottini Tiziano,
  • Lastraioli Elena,
  • Ruffinatti Federico Alessandro,
  • Visentin Luca,
  • Arcangeli Annarosa

Journal volume & issue
Vol. 48
p. 109069

Abstract

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A bioinformatic approach was applied to evaluate the effect of treatment with Bevacizumab on the gene expression profile of colorectal adenocarcinoma cells. The transcriptomic profile of Bevacizumab-adapted HCT-116 (Bev/A) colorectal adenocarcinoma cells was determined and compared with that of the corresponding control cell line by Agilent microarray analysis. Raw data were preprocessed, normalized, filtered, and subjected to a differential expression analysis using standard R/Bioconductor packages (i.e., limma, RankProd). As consequence of Bevacizumab adaptation, 166 differentially expressed genes (DEGs) emerged, most of them (123) resulted downregulated and 43 overexpressed. The list of statistically significant dysregulated genes was used as an input for functional overrepresentation analysis using ToppFun web tool. Such analysis pointed at cell adhesion, cell migration, extracellular matrix organization and angiogenesis as the main dysregulated biological process involved in Bevacizumab-adaptation of HCT116 cells. In addition, gene set enrichment analysis was performed using GSEA, searching for enriched terms within the Hallmarks (H), Canonical Pathways (CP), and Gene Ontology (GO) gene sets. GO terms that showed significant enrichment included: transportome, vascularization, cell adhesion and cytoskeleton, extra cellular matrix (ECM), differentiation and epithelial–mesenchymal transition (EMT), inflammation and immune response. Raw and normalized microarray data were deposited in the Gene Expression Omnibus (GEO) public repository with accession number GSE221948.

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