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Identification of miR-203a, mir-10a, and miR-194 as predictors for risk of lymphovascular invasion in head and neck cancers.

ABSTRACT: Lymphovascular invasion (LVI) is an important prognostic indicator of lymph node metastasis and disease aggressiveness but clear molecular mechanisms mediating this in head and neck cancers (HNSC) remain undefined. To identify important microRNAs (miRNAs) in HNSC that associate with and are also predictive of increased risk of LVI, we used a combination of clustering algorithms, multiple regression analyses and machine learning approaches and analyzed miRNA expression profiles in the TCGA HNSC database. As the first step, we identified miRNAs with increased association with LVI as a binary variable. In order to determine whether the identified miRNAs would show functional clusters that are also indicative of increased risk for LVI, we carried out unsupervised as well as supervised clustering. Our results identified distinct clusters of miRNAs that are predictive of increased LVI. We further refined these findings using a Random forest approach, and miR-203a-3p, mir-10a-5p, and miR-194-5p to be most strongly associated with LVI. Pathway enrichment analysis showed these miRNAs targeted genes involved in Hippo signaling and fatty acid oxidation pathways that are mediators of lymph node metastasis. Specific association was also identified between the miRNAs associated with LVI and expression of several lymphangiogenic genes that could be critical for determination of therapeutic strategies.

SUBMITTER: Karmakar M

PROVIDER: S-EPMC8310671 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundLymphovascular invasion (LOI), a key pathological feature of head and neck squamous cell carcinoma (HNSCC), is predictive of poor survival; however, the associated clinical characteristics and underlying molecular mechanisms remain largely unknown.MethodsWe performed weighted gene co-expression network analysis to construct gene co-expression networks and investigate the relationship between key modules and the LOI clinical phenotype. Functional enrichment and KEGG pathway analyses were performed with differentially expressed genes. A protein-protein interaction network was constructed using Cytoscape, and module analysis was performed using MCODE. Prognostic value, expression analysis, and survival analysis were conducted using hub genes; GEPIA and the Human Protein Atlas database were used to determine the mRNA and protein expression levels of hub genes, respectively. Multivariable Cox regression analysis was used to establish a prognostic risk formula and the areas under the receiver operating characteristic curve (AUCs) were used to evaluate prediction efficiency. Finally, potential small molecular agents that could target LOI were identified with DrugBank.ResultsTen co-expression modules in two key modules (turquoise and pink) associated with LOI were identified. Functional enrichment and KEGG pathway analysis revealed that turquoise and pink modules played significant roles in HNSCC progression. Seven hub genes (CNFN, KIF18B, KIF23, PRC1, CCNA2, DEPDC1, and TTK) in the two modules were identified and validated by survival and expression analyses, and the following prognostic risk formula was established: [risk score = EXPDEPDC1 * 0.32636 + EXPCNFN * (- 0.07544)]. The low-risk group showed better overall survival than the high-risk group (P < 0.0001), and the AUCs for 1-, 3-, and 5-year overall survival were 0.582, 0.634, and 0.636, respectively. Eight small molecular agents, namely XL844, AT7519, AT9283, alvocidib, nelarabine, benzamidine, L-glutamine, and zinc, were identified as novel candidates for controlling LOI in HNSCC (P < 0.05).ConclusionsThe two-mRNA signature (CNFN and DEPDC1) could serve as an independent biomarker to predict LOI risk and provide new insights into the mechanisms underlying LOI in HNSCC. In addition, the small molecular agents appear promising for LOI treatment.

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Identification of miR-203a, mir-10a, and miR-194 as predictors for risk of lymphovascular invasion in head and neck cancers.

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