A Circulating miRNA-Based Scoring System Established by WGCNA to Predict Colon Cancer

Expression Analysis of hsa-miR-181a-5p, hsa-miR-143-3p, hsa-miR-132-3p and hsa-miR-23a-3p as Biomarkers in Colorectal Cancer-Relationship to the Body Mass Index

This work aims to investigate the expression levels of four preselected miRNAs previously linked to cancer and/or obesity, with the purpose of finding potential biomarkers in the clinical management of CRC developed by patients showing different BMI values. We analyzed samples from a total of 65 subjects: 43 affected by CRC and 22 without cancer. Serum and both subcutaneous and omental adipose tissues (SAT and OAT) were investigated, as well as tumor and non-tumor colorectal tissues in the case of the CRC patients. The relative expression (2^-∆∆Ct) levels of 4 miRNAs (hsa-miR-181a-5p, hsa-miR-143-3p, has-miR-132-3p and hsa-miR-23a-3p) were measured by RT-qPCR. Serum, SAT and OAT expression levels of these miRNAs showed significant differences between subjects with and without CRC, especially in the group of overweight/obese subjects. In CRC, serum levels of hsa-miR-143-3p clearly correlated with their levels in both SAT and OAT, independently of the BMI group. Moreover, hsa-miR-181a-5p could be considered as a biomarker in CRC patients with BMI ≥ 25 Kg/m² and emerges as a tumor location marker. We conclude that both adiposity and CRC induce changes in the expression of the miRNAs investigated, and hsa-miR-143-3p and hsa-miR-181a-5p expression analysis could be useful in the clinical management of CRC.

Network analysis identifies DAPK3 as a potential biomarker for lymphatic invasion and colon adenocarcinoma prognosis

Colon adenocarcinoma is a prevalent malignancy with significant mortality. Hence, the identification of molecular biomarkers with prognostic significance is important for improved treatment and patient outcomes. Clinical traits and RNA-Seq of 551 patient samples in the UCSC Toil Recompute Compendium of The Cancer Genome Atlas TARGET and Genotype Tissue Expression project datasets (primary_site = colon) were used for weighted gene co-expression network analysis to reveal the association between gene networks and cancer cell invasion. One module, containing 151 genes, was significantly correlated with lymphatic invasion, a histopathological feature of higher risk colon cancer. DAPK3 (death-associated protein kinase 3) was identified as the pseudohub of the module. Gene ontology identified gene enrichment related to cytoskeletal organization and apoptotic signaling processes, suggesting modular involvement in tumor cell survival, migration, and epithelial-mesenchymal transformation. Although DAPK3 expression was reduced in patients with colon cancer, high expression of DAPK3 was significantly correlated with greater lymphatic invasion and poor overall survival.

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WCGNA reveals a gene module linked to lymphatic invasion in colon adenocarcinoma

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DAPK3 is a pseudohub gene with differential expression in colon cancer

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Gene ontology identified relationships to cytoskeletal organization and apoptosis

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DAPK3 was correlated with lymphatic invasion and poor overall survival

Weighted miRNA co-expression networks analysis identifies circulating miRNA predicting overall survival in hepatocellular carcinoma patients

The weighted gene co-expression network analysis (WGCNA) has been used to explore gene expression datasets by constructing biological networks based on the likelihood expression profile among genes. In recent years, WGCNA found application in biomarker discovery studies, including miRNA. Serum samples from 20 patients with hepatocellular carcinoma (HCC) were profiled through miRNA 3.0 gene array and miRNAs biomarker candidates were identified through WGCNA. Results were validated by qRT-PCR in 102 HCC serum samples collected at diagnosis. WGCNA identified 16 miRNA modules, nine of them were significantly associated with the clinical characteristics of the patient. The Red module had a significant negative correlation with patients Survival (− 0.59, p = 0.007) and albumin (− 0.52, p = 0.02), and a positive correlation with PCR (0.61, p = 0.004) and alpha-fetoprotein (0.51, p = 0.02). In the red module, 16 circulating miRNAs were significantly associated with patient survival. MiR-3185 and miR-4507 were identified as predictors of patient survival after the validation phase. At diagnosis, high expression of circulating miR-3185 and miR-4507 identifies patients with longer survival (HR 2.02, 95% CI 1.10–3.73, p = 0.0086, and HR of 1.75, 95% CI 1.02–3.02, p = 0.037, respectively). Thought a WGCNA we identified miR-3185 and miR-4507 as promising candidate biomarkers predicting a longer survival in HCC patients.

Weighted correlation network bioinformatics uncovers a key molecular biosignature driving the left-sided heart failure

BACKGROUND

Left-sided heart failure (HF) is documented as a key prognostic factor in HF. However, the relative molecular mechanisms underlying left-sided HF is unknown. The purpose of this study is to unearth significant modules, pivotal genes and candidate regulatory components governing the progression of left-sided HF by bioinformatical analysis.

METHODS

A total of 319 samples in GSE57345 dataset were used for weighted gene correlation network analysis (WGCNA). ClusterProfiler package in R was used to conduct functional enrichment for genes uncovered from the modules of interest. Regulatory networks of genes were built using Cytoscape while Enrichr database was used for identification of transcription factors (TFs). The MCODE plugin was used for identifying hub genes in the modules of interest and their validation was performed based on GSE1869 dataset.

RESULTS

A total of six significant modules were identified. Notably, the blue module was confirmed as the most crucially associated with left-sided HF, ischemic heart disease (ISCH) and dilated cardiomyopathy (CMP). Functional enrichment conveyed that genes belonging to this module were mainly those driving the extracellular matrix-associated processes such as extracellular matrix structural constituent and collagen binding. A total of seven transcriptional factors, including Suppressor of Zeste 12 Protein Homolog (SUZ12) and nuclear factor erythroid 2 like 2 (NFE2L2), adrenergic receptor (AR), were identified as possible regulators of coexpression genes identified in the blue module. A total of three key genes (OGN, HTRA1 and MXRA5) were retained after validation of their prognostic value in left-sided HF. The results of functional enrichment confirmed that these key genes were primarily involved in response to transforming growth factor beta and extracellular matrix.

CONCLUSION

We uncovered a candidate gene signature correlated with HF, ISCH and CMP in the left ventricle, which may help provide better prognosis and therapeutic decisions and in HF, ISCH and CMP patients.