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

Articolo
Data di Pubblicazione:
2023
Abstract:
A bioinformatic approach was applied to evaluate the effect of treatment with Bevacizumab on the gene expression pro-file 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 microar-ray analysis. Raw data were preprocessed, normalized, fil-tered, and subjected to a differential expression analysis us-ing standard R/Bioconductor packages (i.e., limma, RankProd). As consequence of Bevacizumab adaptation, 166 differentially expressed genes (DEGs) emerged, most of them (123) re-sulted downregulated and 43 overexpressed. The list of sta-tistically significant dysregulated genes was used as an in-put for functional overrepresentation analysis using Topp-Fun web tool. Such analysis pointed at cell adhesion, cell migration, extracellular matrix organization and angiogene-sis as the main dysregulated biological process involved in Bevacizumab-adaptation of HCT116 cells. In addition, gene set enrichment analysis was performed using GSEA, search-ing 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 cellu-lar 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.(c) 2023 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
Tipologia CRIS:
03A-Articolo su Rivista
Keywords:
Bevacizumab; Bioinformatic analysis; Gene expression; HCT116
Elenco autori:
Cesare, Sala; Tiziano, Lottini; Elena, Lastraioli; Alessandro, Ruffinatti Federico; Luca, Visentin; Annarosa, Arcangeli
Autori di Ateneo:
RUFFINATTI Federico Alessandro
Link alla scheda completa:
https://iris.unito.it/handle/2318/1950690
Link al Full Text:
https://iris.unito.it/retrieve/handle/2318/1950690/1225933/1-s2.0-S2352340923001877-main.pdf
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Settori (17)


LS2_8 - Transcriptomics - (2020)

LS4_1 - Organ and tissue physiology and pathophysiology - (2022)

LS4_12 - Cancer - (2022)

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