Abstract C048: Computational pathway analysis of differentially expressed miRNAs in Black compared with White laryngeal squamous cell carcinoma

Abstract

Abstract Background: Black patients have maintained higher burden of laryngeal squamous cell carcinoma (LSCC), despite there being an overall decline in the rates of incidence and mortality across the U.S. population. A molecular basis for this disparity remains elusive. In recent years, studies have addressed head and neck disparities via protein coding genes, while ignoring the potential impact of non-coding RNA. Here we explore the manner in which differential expression of miRNAs in Black compared with White LSCC patients may influence the activation of various different downstream molecular pathways. Methods: Differential expression analysis was performed on a dataset generated from small RNA-sequencing of 32 LSCC tumors (16 derived from Black patients, 16 derived from White patients) using the R package DESeq2. For miRNAs identified as differentially expressed between Black and White patient tumors (-log2FC < -1 or log2FC > 1; p adjusted > 0.05) we generated a list of predicted mRNA targets using the R package miRNAtap. For miRNAs with significantly higher or lower expression in Black tumors compared with White tumors, we respectively combined their mRNA targets and performed KEGG pathway enrichment analysis on the lists of genes using the R package clusterProfiler. Results: From our dataset, we profiled 2051 miRNAs. Unsupervised clustering revealed a subset of 14 miRNAs that were significantly lower in expression in Black LSCCs compared to White LSCCs. KEGG pathway analysis showed that human immunodeficiency virus 1 pathway was significantly enriched for these miRNAs (p < 0.005). The GeneRatio for this pathway is greater than 0.60, indicating that around 60% of all genes in the human immunodeficiency virus 1 pathway are targeted by these lower expressed miRNAs. Significant gene targets identified are those involving the inflammatory signaling pathway including Raf-1, NFκB, and TNFR2. Conversely, we identified 7 miRNAs that were significantly higher in expression in Black LSCC compared to White LSCC. KEGG pathway analysis found the autophagy pathway to be significantly enriched for these miRNAs (p < 0.005). The GeneRatio for this pathway is greater than 0.40, indicating that over 40% of all genes in the autophagy pathway are targeted by these higher expressed miRNAs. Significant gene targets identified are those involved in cell survival signaling pathways including PI3K, AKT, JNK1, and PTEN. Conclusion: In summary, our computational findings highlight differential cell signaling pathways that may play a role in LSCC tumorigenesis in a race-dependent manner. Future directions for this work will involve additional pathway characterization through further computational analyses and biochemical studies. Citation Format: Chayil C. Lattimore, Heather Kates, Tongjun Gu, Jinmai Jiang, Thomas Schmittgen, Kristianna M. Fredenburg. Computational pathway analysis of differentially expressed miRNAs in Black compared with White laryngeal squamous cell carcinoma [abstract]. In: Proceedings of the 15th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2022 Sep 16-19; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr C048.