Plasma and Tissue Specific miRNA Expression Pattern and Functional Analysis Associated to Colorectal Cancer Patients

Abstract

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.

Identification of a Potentially Functional microRNA–mRNA Regulatory Network in Lung Adenocarcinoma Using a Bioinformatics Analysis

“…The isoform expressions of the DEmiRNAs were identified using the R package miRNAmeConverter . The common consistently and differentially expressed (Co-DE) miRNAs were obtained using intersected analyses comparing TCGA and microarray datasets ( Cojocneanu et al, 2020 ). The targeted mRNAs of the Co-DEmiRNAs were predicted using three online analytical software tools including miRDB 2 , TargetScanHuman (version 7.2) 3 , and miRWalk ( Agarwal et al, 2015 ; Dweep and Gretz, 2015 ; Chen and Wang, 2020 ) 4 .…”

“…et al, 2019 ; Wu S.G. et al, 2019 ; Condrat et al, 2020 ). miRNAs could be readily detected in circulation and carry information regarding the origin of a neoplasm, thus serving as diagnostic and prognostic biomarkers in the development of tumors ( Hummel et al, 2010 ; Blondal et al, 2013 ; Qi et al, 2013 ; Zhang et al, 2016 ; Liu et al, 2017 ; Świtlik et al, 2019 ; Cojocneanu et al, 2020 ; Wang et al, 2020 ). An increasing number of studies have reported various expression levels of miRNAs in LUAD ( Cazzoli et al, 2013 ; Zhong et al, 2018 ), although findings remain inconsistent.…”

“…Microarray analysis has been widely used in the evaluation of miRNA in cancers to understand the complexity and heterogeneity of malignant disease ( Jurj et al, 2017 ; Cojocneanu et al, 2020 ), but has not been fully elucidated in LUAD. A public dataset from the Cancer Genome Atlas (TCGA) is widely used in LUAD analyses, although cases primarily originate from a non-Asian population, yet include primary tissue samples.…”

Fecal microRNAs as Innovative Biomarkers of Intestinal Diseases and Effective Players in Host-Microbiome Interactions

“…Several studies have shown that miRNAs can be identified in a variety of body fluids, including plasma, saliva, urine, seminal fluids, breast milk, cerebrospinal fluid and more recently also in feces, leading to the definition of circulating miRNAs [70][71][72][73][74]. Every miRNA has a unique nucleotide sequence and expression pattern in a certain cell type; however, although miRNAs show a high tissue specificity, body fluids can contain different or unique circulating miRNAs, that can putatively have several hundred gene targets, thereby generating an intricate picture [75]. Circulating miRNAs have been found associated with EVs, with high-density lipoproteins or with proteins involved in their processing such as the argonaute protein.…”

Cancer-Associated Stemness and Epithelial-to-Mesenchymal Transition Signatures Related to Breast Invasive Carcinoma Prognostic

“…Therefore, patient care management remains an important clinical challenge due to the lack of availability of prognostic markers that could stratify a patient’s risk. In the past few years, there has been an increased interest in verifying the clinical utility of coding and noncoding genes as important biomarkers for prognostic, diagnostic, and therapeutic targets [ 2 , 4 , 5 , 6 , 7 , 8 ].…”