Dataset Information

Identifying Susceptibility Loci for Cutaneous Squamous Cell Carcinoma Using a Fast Sequence Kernel Association Test.

ABSTRACT: Cutaneous squamous cell carcinoma (cSCC) accounts for about 20% of all skin cancers, the most common type of malignancy in the United States. Genome-wide association studies (GWAS) have successfully identified multiple genetic variants associated with the risk of cSCC. Most of these studies were single-locus-based, testing genetic variants one-at-a-time. In this article, we performed gene-based association tests to evaluate the joint effect of multiple variants, especially rare variants, on the risk of cSCC by using a fast sequence kernel association test (fastSKAT). The study included 1,710 cSCC cases and 24,304 cancer-free controls from the Nurses' Health Study, the Nurses' Health Study II and the Health Professionals Follow-up Study. We used UCSC Genome Browser to define gene units as candidate loci, and further evaluated the association between all variants within each gene unit and disease outcome. Four genes HP1BP3, DAG1, SEPT7P2, and SLFN12 were identified using Bonferroni adjusted significance level. Our study is complementary to the existing GWASs, and our findings may provide additional insights into the etiology of cSCC. Further studies are needed to validate these findings.

SUBMITTER: Huang M

PROVIDER: S-EPMC8141858 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:A cutaneous squamous cell carcinoma (cSCC) derived from keratinocytes is the second most common cause of non-melanoma skin cancer. The accumulation of the mutational burden of genes and cellular DNA damage caused by the risk factors (e.g., exposure to ultraviolet radiation) contribute to the aberrant proliferation of keratinocytes and the formation of a cSCC. A cSCC encompasses a spectrum of diseases that range from recursor actinic keratosis (AK) and squamous cell carcinoma (SCC) in situ (SCCIS) to invasive cSCCs and further metastatic SCCs. Emerging evidence has revealed that lncRNAs are involved in the biological process of a cSCC. According to the ceRNA regulatory theory, lncRNAs act as natural miRNA sponges and interact with miRNA response elements, thereby regulating the mRNA expression of their down-stream targets. This study was designed to search for the potential lncRNAs that may become potential therapeutic targets or biomarkers of a cSCC. Considering the spirit of the study to be adequately justified, we collected microarray-based datasets of 19 cSCC tissues and 12 normal skin samples from the GEO database (GSE42677 and GSE45164). After screening the differentially expressed genes via a limma package, we identified 24 differentially expressed lncRNAs (DElncRNAs) and 3221 differentially expressed mRNAs (DEmRNAs). The miRcode, miRTarBase, miRDB and TargetScan databases were used to predict miRNAs that could interact with DElncRNAs and DEmRNAs. A total of 137 miRNA-lncRNA and 221 miRNA-mRNA pairs were retained in the ceRNA network, consisting of 31 miRNAs, 11 DElncRNAs and 155 DEmRNAs. For the functional analysis, the top enriched biological process was enhancer sequence-specific DNA binding in Gene Ontology (GO) terms. The FoxO signaling pathway, autophagy and cellular senescence were the top enrichment terms based on a Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The combination of a STRING tool and Cytoscape software (plug-in MCODE) identified five core mRNAs and built a core mRNA-associated ceRNA network. The expression for five identified core mRNAs and their related nine lncRNAs was validated using the external dataset GSE7553. Finally, one lncRNA HLA-F-AS1 and three mRNAs named AGO4, E2F1 and CCND1 were validated with the same expression patterns. We speculate that lncRNA HLA-F-AS1 may sponge miR-17-5p or miR-20b-5p to regulate the expression of CCND1 and E2F1 in the cSCC. The present study may provide potential diagnostic and therapeutic targets for cSCC patients.

Dataset Information

Identifying Susceptibility Loci for Cutaneous Squamous Cell Carcinoma Using a Fast Sequence Kernel Association Test.

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