Identification of MicroRNAs as Novel Biomarkers for Esophageal Squamous Cell Carcinoma: A Study Based on The Cancer Genome Atlas (TCGA) and Bioinformatics
Esophageal squamous cell carcinoma (ESCC) is a highly aggressive and fatal malignancy, accounting for a significant proportion of cancer-related deaths worldwide. Despite advancements in diagnostic and therapeutic strategies, the prognosis for ESCC patients remains poor, primarily due to the lack of reliable biomarkers for early detection and prognosis. MicroRNAs (miRNAs), small non-coding RNAs that regulate gene expression, have emerged as promising biomarkers in various cancers. This study aims to identify key miRNAs associated with ESCC by leveraging The Cancer Genome Atlas (TCGA) database and employing comprehensive bioinformatics analyses.
The study utilized RNA sequencing data from TCGA, which included 161 ESCC tumor samples and 11 normal esophageal tissue samples. The primary objective was to identify differentially expressed miRNAs in ESCC and explore their potential roles in tumor progression, clinical characteristics, and patient survival. The methodology involved several steps, including data preprocessing, identification of differentially expressed miRNAs, construction of miRNA-mRNA co-expression networks, and validation of selected miRNAs using quantitative real-time PCR (qRT-PCR).
In the initial phase, the researchers identified 232 miRNAs that were significantly differentially expressed between ESCC tumor tissues and normal esophageal tissues. Further analysis revealed 35 key miRNAs that were consistently dysregulated across different stages of ESCC, including those with and without lymphatic metastasis. Among these, 25 miRNAs were upregulated, and 10 were downregulated. These miRNAs were selected for further investigation due to their potential involvement in ESCC pathogenesis.
To understand the regulatory functions of these miRNAs, a miRNA-mRNA co-expression network was constructed. This network included 28 miRNAs and 72 mRNAs, with the miRNAs predicted to negatively regulate the expression of their target mRNAs. The network revealed several key genes involved in cancer development, such as E2F2, FGF2, COL4A3, ERBB4, FGFR1, RELN, and TCF3. Gene Ontology (GO) and pathway analyses indicated that these mRNAs were enriched in critical biological processes and pathways, including regulation of cellular processes, protein binding, and cancer-related signaling pathways such as PI3K-AKT and MAPK.
The study also explored the correlation between the expression levels of these miRNAs and various clinical characteristics of ESCC patients. Seventeen miRNAs were found to be significantly associated with tumor grade, TNM stage, and lymphatic metastasis. For instance, miR-32-5p, miR-330-5p, miR-135b-5p, miR-195-5p, and miR-145-5p were linked to tumor grade, while miR-16-5p, miR-32-5p, miR-93-5p, miR-185-5p, miR-15b-5p, miR-135b-5p, miR133a-3p, miR-28-5p, and miR-195-5p were associated with TNM stages. Additionally, miR-32-5p, miR-93-5p, miR-15b-5p, miR-135b-5p, miR-330-5p, miR-106b-5p, miR-182-5p, miR-20b-5p, miR-141-3p, miR-28-5p, miR-195-5p, and miR-320a were related to lymphatic metastasis.
Kaplan-Meier survival analysis was performed to assess the prognostic value of these miRNAs. Six miRNAs (miR-200b-3p, miR-31-5p, miR-15b-5p, miR-141-3p, miR-135b-5p, and miR-195-5p) were significantly correlated with overall survival in ESCC patients. Among these, miR-200b-3p, miR-31-5p, miR-15b-5p, miR-141-3p, and miR-135b-5p were negatively associated with survival, while miR-195-5p showed a positive correlation.
To validate the bioinformatics findings, the expression levels of three selected miRNAs (miR-135b-5p, miR-15b-5p, and miR-195-5p) were measured using qRT-PCR in 51 newly diagnosed ESCC patients’ tissue samples. The results confirmed the consistency of miRNA expression patterns between the TCGA data and the qRT-PCR analysis. Specifically, miR-135b-5p and miR-15b-5p were upregulated, while miR-195-5p was downregulated in ESCC tumor tissues compared to normal tissues. Furthermore, these miRNAs were significantly associated with tumor differentiation degree, TNM stage, and lymph-node metastasis, aligning with the TCGA bioinformatics analysis.
The study’s findings underscore the potential of miRNAs as biomarkers for ESCC diagnosis, classification, and prognosis. The identified miRNAs, particularly those associated with clinical characteristics and patient survival, warrant further investigation to elucidate their roles in ESCC pathogenesis and to explore their therapeutic potential. The integration of large-scale genomic data from TCGA with comprehensive bioinformatics analyses provides a robust framework for identifying and validating cancer biomarkers, offering new avenues for improving the management of ESCC.
In conclusion, this study successfully identified key miRNAs associated with ESCC using TCGA data and bioinformatics tools. The findings highlight the potential of miRNAs as novel biomarkers for ESCC, offering insights into their roles in tumor progression and patient outcomes. Future research should focus on validating these miRNAs in larger cohorts and exploring their mechanistic roles in ESCC, paving the way for the development of targeted therapies and improved diagnostic strategies.
doi.org/10.1097/CM9.0000000000000427
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