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Microarray analysis reveals ONC201 mediated differential mechanisms of CHOP gene regulation in metastatic and nonmetastatic colorectal cancer cells.

ABSTRACT: The imipramine ONC201 has antiproliferative effects in several cancer cell types and activates integrated stress response pathway associated with the induction of Damage Inducible Transcript 3 (DDIT3, also known as C/EBP homologous protein or CHOP). We investigated the signaling pathways through which ONC201/CHOP crosstalk is regulated in ONC201-treated nonmetastatic and metastatic cancer cell lines (Dukes' type B colorectal adenocarcinoma nonmetastatic SW480 and metastatic LS-174T cells, respectively). Cell proliferation and apoptosis were evaluated by MTT assays and flow cytometry, gene expression was assessed by Affymetrix microarray, signaling pathway perturbations were assessed in silico, and key regulatory proteins were validated by Western blotting. Unlike LS-174T cells, SW480 cells were resistant to ONC201 treatment; Gene Ontology analysis of differentially expressed genes showed that cellular responsiveness to ONC201 treatment also differed substantially. In both ONC201-treated cell lines, CHOP expression was upregulated; however, its upstream regulatory mechanisms were perturbed. Although, PERK, ATF6 and IRE1 ER-stress pathways upregulated CHOP in both cell types, the Bak/Bax pathway regulated CHOP only LS-174T cells. Additionally, CHOP RNA splicing profiles varied between cell lines; these were further modified by ONC201 treatment. In conclusion, we delineated the signaling mechanisms by which CHOP expression is regulated in ONC201-treated non-metastatic and metastatic colorectal cell lines. The observed differences could be related to cellular plasticity and metabolic reprogramming, nevertheless, detailed mechanistic studies are required for further validations.

SUBMITTER: Al Madhoun A

PROVIDER: S-EPMC8178367 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundTo utilize the large volume of gene expression information generated from different microarray experiments, several meta-analysis techniques have been developed. Despite these efforts, there remain significant challenges to effectively increasing the statistical power and decreasing the Type I error rate while pooling the heterogeneous datasets from public resources. The objective of this study is to develop a novel meta-analysis approach, Consistent Differential Expression Pattern (CDEP), to identify genes with common differential expression patterns across different datasets.ResultsWe combined False Discovery Rate (FDR) estimation and the non-parametric RankProd approach to estimate the Type I error rate in each microarray dataset of the meta-analysis. These Type I error rates from all datasets were then used to identify genes with common differential expression patterns. Our simulation study showed that CDEP achieved higher statistical power and maintained low Type I error rate when compared with two recently proposed meta-analysis approaches. We applied CDEP to analyze microarray data from different laboratories that compared transcription profiles between metastatic and primary cancer of different types. Many genes identified as differentially expressed consistently across different cancer types are in pathways related to metastatic behavior, such as ECM-receptor interaction, focal adhesion, and blood vessel development. We also identified novel genes such as AMIGO2, Gem, and CXCL11 that have not been shown to associate with, but may play roles in, metastasis.ConclusionsCDEP is a flexible approach that borrows information from each dataset in a meta-analysis in order to identify genes being differentially expressed consistently. We have shown that CDEP can gain higher statistical power than other existing approaches under a variety of settings considered in the simulation study, suggesting its robustness and insensitivity to data variation commonly associated with microarray experiments.AvailabilityCDEP is implemented in R and freely available at: http://genomebioinfo.musc.edu/CDEP/.Contactzhengw@musc.edu.

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Microarray analysis reveals ONC201 mediated differential mechanisms of CHOP gene regulation in metastatic and nonmetastatic colorectal cancer cells.

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