Dataset Information

Survival-Based Biomarker Module Identification Associated with Oral Squamous Cell Carcinoma (OSCC).

ABSTRACT: Head and neck squamous cell carcinoma (HNSC) is one of the most common malignant tumors worldwide with a high rate of morbidity and mortality, with 90% of predilections occurring for oral squamous cell carcinoma (OSCC). Cancers of the mouth account for 40% of head and neck cancers, including squamous cell carcinomas of the tongue, floor of the mouth, buccal mucosa, lips, hard and soft palate, and gingival. OSCC is the most devastating and commonly occurring oral malignancy, with a mortality rate of 500,000 deaths per year. This has imposed a strong necessity to discover driver genes responsible for its progression and malignancy. In the present study we filtered oral squamous cell carcinoma tissue samples from TCGA-HNSC cohort, which we followed by constructing a weighted PPI network based on the survival of patients and the expression profiles of samples collected from them. We found a total of 46 modules, with 18 modules having more than five edges. The KM and ME analyses revealed a single module (with 12 genes) as significant in the training and test datasets. The genes from this significant module were subjected to pathway enrichment analysis for identification of significant pathways and involved genes. Finally, the overlapping genes between gene sets ranked on the basis of weighted PPI module centralities (i.e., degree and eigenvector), significant pathway genes, and DEGs from a microarray OSCC dataset were considered as OSCC-specific hub genes. These hub genes were clinically validated using the IHC images available from the Human Protein Atlas (HPA) database.

SUBMITTER: Singh P

PROVIDER: S-EPMC8389591 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundOral squamous cell carcinoma (OSCC) is one of the common cancers worldwide. The lack of specific biomarkers and therapeutic targets leads to delayed diagnosis and hence the poor prognosis of OSCC patients. Thus, it is urgent to identify effective biomarkers and therapeutic targets for OSCC.MethodsWe established the golden hamster carcinogenic model of OSCC induced by 7,12-dimethylbenz(a) anthrancene (DMBA) and used mRNA microarrays to detect the differentially expressed genes (DEGs). DEGs were validated in OSCC clinical tissue microarrays using immunohistochemistry method. Whole transcriptome sequencing was performed to obtain an overview of biological functions of Lsm12. PCR assay and sequencing were employed to investigate the alternative splicing of genes regulated by Lsm12. Cell proliferation, colony formation, Transwell migration and invasion assay and in vivo tumor formation assay were performed to investigate the roles of Lsm12 and two transcript variants of USO1 in OSCC cells.ResultsLsm12 was identified to be significantly up-regulated in the animal model of OSCC tumorigenesis, which was validated in the clinical OSCC samples. In the paired normal tissues, Lsm12 staining was negative (91%, 92/101) or weak, while in OSCC tissues, positive rate is 100% and strong staining spread over the whole tissues in 93 (93/101, 92%) cases. Lsm12 overexpression significantly promoted OSCC cell growth, colony formation, migration and invasion abilities, while Lsm12 knockdown showed the opposite trends on these phenotypes and obviously inhibited the tumor formation in vivo. Furthermore, Lsm12 overexpression caused the inclusion of USO1 exon 15 and Lsm12 knockdown induced exon 15 skipping. Exon 15-retained USO1 significantly promoted the malignant phenotypes of OSCC cells when compared with the exon 15-deleted USO1.ConclusionsWe identified Lsm12, a novel tumorigenesis-related gene, as an important regulator involved in OSCC tumorigenesis. Lsm12 is a novel RNA-splicing related gene and can regulate the alternative splicing of USO1 exon 15 which was associated closely with OSCC carcinogenesis. Our findings thus provide that Lsm12 might be a potent biomarker and potential therapeutic target for OSCC.

Dataset Information

Survival-Based Biomarker Module Identification Associated with Oral Squamous Cell Carcinoma (OSCC).

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets