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Identification of colorectal cancer associated biomarkers: an integrated analysis of miRNA expression.

ABSTRACT: Colorectal cancer is one of the leading causes of cancer-related deaths worldwide. This complex disease still holds severe problems concerning diagnosis due to the high invasiveness nature of colonoscopy and the low accuracy of the alternative diagnostic methods. Additionally, patient heterogeneity even within the same stage is not properly reflected in the current stratification system. This scenario highlights the need for new biomarkers to improve non-invasive screenings and clinical management of patients. MicroRNAs (miRNAs) have emerged as good candidate biomarkers in cancer as they are stable molecules, easily measurable and detected in body fluids thus allowing for non-invasive diagnosis and/or prognosis. In this study, we performed an integrated analysis first using 4 different datasets (discovery cohorts) to identify miRNAs associated with colorectal cancer development, unveil their role in this disease by identifying putative targets and regulatory networks and investigate their ability to serve as biomarkers. We have identified 26 differentially expressed miRNAs which interact with frequently deregulated genes known to participate in commonly altered pathways in colorectal cancer. Most of these miRNAs have high diagnostic power, and their prognostic potential is evidenced by panels of 5 miRNAs able to predict the outcome of stage II and III colorectal cancer patients. Notably, 8 miRNAs were validated in three additional independent cohorts (validation cohorts) including a plasma cohort thus reinforcing the value of miRNAs as non-invasive biomarkers.

SUBMITTER: Fonseca A

PROVIDER: S-EPMC8507258 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:An increasing number of studies suggest the implication of microRNAs (miRNAs) in colorectal (CRC) carcinogenesis and disease progression. Nevertheless, the basic mechanism is not yet clear. We determined plasma miRNA expression levels using Agilent microarray technology followed by overlapping with The Cancer Genome Atlas (TCGA) tissue data and a qRT-PCR validation step and analysis of the altered miRNA signatures to emphasize new mechanistic insights. For TGCA dataset, we identified 156 altered miRNAs (79 downregulated and 77 upregulated) in colorectal tissue samples versus normal tissue. The microarray experiment is based on 16 control samples, 38 CRC plasma samples from colorectal cancer patients who have not undergone chemotherapy, and 17 chemo-treated samples. In the case of the analysis of CRC cancer versus healthy control we identified 359 altered miRNAs (214 downregulated and 60 upregulated), considering as the cutoff value a fold-change of ±1.5 and p < 0.01. An additional microarray analysis was performed on plasma from untreated colorectal cancer (n = 38) and chemotherapy-treated colorectal cancer patients (n = 17), which revealed 15 downregulated miRNAs and 53 upregulated miRNAs, demonstrating that the plasma miRNA pattern is affected by chemotherapy and emphasizing important regulators of drug resistance mechanisms. For the validation of the microarray data, we selected a panel of 4 miRNAs from the common miRNA signatures for colon and rectal cancer (miR-642b-3p, miR-195-5p and miR-4741). At the tissue level, the expression levels were in agreement with those observed in colorectal plasma. miR-1228-3p, the top upregulated miRNA in CRC, was chosen to be validated on tissue and plasma samples, as it was demonstrated to be downregulated at tissue level in our patient cohort. This was confirmed by TCGA data and was one example of ta ranscript that has a different expression level between tumor tissue and plasma. Developing more efficient investigation methods will help explain the mechanisms responsible for miRNAs released in biofluids, which is the most upregulated transcript in colorectal plasma samples and which can function as a prediction tool within the oncological field.

Project description:Background Small cell lung cancer (SCLC) is an aggressive and recalcitrant cancer. In recent years, studies focused on the abnormal expression of microRNA which has proven valuable in terms of prognosis, diagnosis and treatment in SCLC. To address the limitations of independent studies data, a meta-analysis seems necessary for further exploration of microRNA as biological target and regulatory factor in SCLC. Methods We performed comprehensive literature retrieval in GEO database and EBI ArrayExpress database. The microRNA expression data was extracted from 4 related researches (GSE15008, GSE74190, GSE19945, GSE77380), which was obtained from GEO database. In each included study, the R. Affymetrix Expression Console’s Limma package and RMA algorithms were used to screen for raw data for gene chip quality control, standardization, log2 conversion and differential expression of the gene chip, respectively. Significant microRNA meta-signatures were identified by Robust Rank Aggregation method. Subsequently, gene ontology (GO) enrichment analysis and pathway analysis were performed using bioinformatics tools. Results We found a significant microRNA meta-signature of six up-regulated (hsa-miR-182-5p, hsa-miR-96-5p, hsa-miR-7-5p, hsa-miR-301b-3p, hsa-miR-130b-3p, hsa-miR-210-3p) and four down-regulated (hsa-miR-126-3p, hsa-miR-451a, hsa-miR-145-5p, hsa-miR-486-5p) microRNA s in meta-analysis approaches. GO analysis showed that target gene of meta-signatures microRNA was mainly enriched in endosome, chordate embryonic development and transforming growth factor beta receptor. The related functional gene of microRNA meta signature synergistically targeting SCLC signaling pathway was confirmed by enrichment analysis. In particular, neurotrophin and TGF-beta signaling pathway play the most important roles in the pathway network. Conclusions Our study identified 10 highly significant and consistently dysregulated microRNA s from 4 datasets, which offering convincing molecular targets and regulatory factors in future research of SCLC.

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Identification of colorectal cancer associated biomarkers: an integrated analysis of miRNA expression.

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