A miR-205-Associated Target-Gene Expression Signature in Breast Cancer Tissue and Circulation
Description
This dataset was generated as part of a case-control study investigating the relationship between miR-205 and selected target genes in breast cancer. The central hypothesis was that miR-205, a microRNA previously implicated in tumour suppression and epithelial differentiation, would be downregulated in breast cancer, while selected candidate target genes (NFIB, YAP1, ZEB1, RUNX2, and AMOT) would show reciprocal increases in expression. We further hypothesised that these molecular changes would be associated with clinicopathological characteristics of disease severity and could be detected in both tissue and peripheral blood compartments. The dataset includes clinical, pathological, and quantitative real-time PCR (qRT-PCR) data from 150 women with histologically confirmed breast cancer and 150 healthy female controls recruited in Lahore, Pakistan. Breast cancer patients contributed tumour tissue, paired adjacent non-cancerous tissue, peripheral blood, and serum samples, while controls contributed peripheral blood and serum samples. Expression levels were quantified using qRT-PCR and reported as relative expression values calculated using the 2^-ΔΔCt method. miR-205 expression was normalised to RNU6, while mRNA expression of NFIB, YAP1, ZEB1, RUNX2, and AMOT was normalised to GAPDH. The data show significantly lower miR-205 expression in breast cancer tissue and serum compared with corresponding control samples. In contrast, NFIB, YAP1, ZEB1, RUNX2, and AMOT expression was significantly increased in breast cancer tissue and blood. Several biomarkers were associated with tumour stage, grade, receptor status, molecular subtype, tumour size, and metastatic status. Correlation analyses demonstrated inverse relationships between miR-205 and multiple target genes, particularly within tumour tissue. Exploratory receiver operating characteristic analyses suggested potential diagnostic utility for miR-205 and selected target genes, although these findings require independent validation. The dataset also includes outputs from complementary bioinformatic analyses, including target prediction, public transcriptomic dataset validation, pathway enrichment, and protein-protein interaction analyses. These resources were used to place the experimental findings within broader molecular networks relevant to breast cancer biology. Researchers may use this dataset for biomarker validation, comparative expression analyses, meta-analyses, machine-learning model development, pathway investigations, and studies examining microRNA–mRNA regulatory relationships in breast cancer. Because the study is observational and expression-based, the data should not be interpreted as evidence of direct causal regulation between miR-205 and the selected target genes without further functional validation.
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This dataset was generated through a case-control study conducted in Lahore, Pakistan. Breast cancer patients contributed tumour tissue, paired adjacent non-cancerous tissue, peripheral blood, and serum samples. Healthy controls contributed peripheral blood and serum samples. Fresh tissue specimens were snap-frozen and stored at −80°C. Peripheral blood was collected into EDTA tubes for mRNA analysis and clot-activator tubes for serum separation and circulating miRNA analysis. Serum samples underwent sequential centrifugation steps to remove cellular debris before storage at −80°C. Total RNA was extracted from tissue and whole-blood samples using TRIzol reagent (Invitrogen, USA). Circulating miRNA was isolated from serum using the FavorPrep miRNA Isolation Kit. RNA concentration and purity were assessed using NanoDrop spectrophotometry, and only samples meeting predefined quality criteria were used for downstream analyses. For miR-205 analysis, cDNA synthesis was performed using a modified poly(A)-tail reverse-transcription protocol based on sRNAPrimerDB. Expression of miR-205 was quantified by quantitative real-time PCR (qRT-PCR) using Maxima SYBR Green/ROX chemistry on a QuantStudio 5 Real-Time PCR System (Applied Biosystems). RNU6 served as the endogenous control. For mRNA analysis, cDNA was synthesised using the RevertAid First Strand cDNA Synthesis Kit. Expression of NFIB, YAP1, ZEB1, RUNX2, and AMOT was measured by qRT-PCR using gene-specific primers and Maxima SYBR Green/ROX Master Mix. GAPDH was used as the endogenous control. All reactions were performed in duplicate, and melt-curve analysis and no-template controls were used to assess amplification specificity. Raw cycle-threshold (Ct) values were processed using QuantStudio Design and Analysis Software v2. Relative expression was calculated using the 2^-ΔΔCt method. Statistical analyses were performed using IBM SPSS Statistics v24.0 and GraphPad Prism v9.0. Group comparisons, correlation analyses, clinicopathological association analyses, and exploratory receiver operating characteristic (ROC) analyses were conducted using standard statistical procedures with two-sided significance testing (p ≤ 0.05). Bioinformatic analyses included miR-205 target prediction using miRWalk, TargetScan Human v8.0, and miRDB; public-dataset validation using TCGA-BRCA (via UALCAN) and GEO datasets GSE45827 and GSE65216; protein–protein interaction analysis using STRING v12.0; network visualisation using Cytoscape v3.10.0; and pathway enrichment analyses using Gene Ontology and KEGG resources. These workflows were used to validate and contextualise the experimental expression findings within broader breast cancer molecular networks.
Institutions
- University of LahorePunjab, Lahore