Affiliation:
1. Second Clinical Medical College of ShanXi Medical University
2. Second Hospital of ShanXi Medical University
3. Sun Yat-sen University Cancer Center
Abstract
Abstract
Background
Oropharyngeal squamous cell carcinoma (OSCC) has been a common malignancy in head and neck region. Despite the improved understanding of the cancer development attributing to the revealing of significant epidemiological risk factors, the genetic information of the cancer is still lacking and the patients prognosis remains challenging. The study is to explore the transcriptome data of OSCC and to identify promising cancer development responsible genes thus aiding more precise understanding of the disease and screening promising drug targets for clinical medical therapy.
Methods
Multiple bioinformatic serves were used to interpret the genetic events in OSCC development. Firstly, based on GEO OSCC transcriptome data, the genes with changed expression in cancer comparing to normal oral tissues were identified, followed by being grouped according to the changing level. Then, GO/KEGG interpretation, protein-protein interaction (PPI) network construction and modules analysis were in succession performed to interpret the multiple gene groups for selecting promising hub gene clusters, which were next step proceeded by risk score assessment, Kaplan-Meier survival and Cox Regression analysis to scale down the cluster of candidate genes and select credible prognosis relating key genes. Further, detailed information of the key genes including their physicochemical properties, predicted cellular locations, the expression in human cancers, association with immune cells infiltration, relation with OSCC clinical pathological features and the probable signaling pathways involved in the gene’s regulation on cancer development were explored.
Results
A total of 30054 genes were identified to express abnormally in OSCC cancer versus normal oral epithelium. Of the genes, the expression difference of 607/30054 genes were indicated to be over 8-fold, and further module analysis of the 607 genes highlighted a 33-genes containing module which was supported by SurvExpress risk score assessment to be associated with OSCC survival. Moreover, Kaplan-Meier survival and Cox-regression analysis were performed continually to analyze all the 33 genes one by one, and the result revealed SPP1 and PLAU as two independent prognostic indicators in OSCC development. After the validation of changed expression of SPP1 and PLAU in OSCC versus normal tissues using local hospital biobank samples and exploration of the genes’ association with patients clinical pathological features including the relation with HPV infection, detailed information for instance their physicochemical properties, their expression and variation ratio in human cancers, their relation with immune cells infiltration, as well as the probable signaling pathways involved in the genes’ regulation on OSCC development were explored.
Conclusions
Based on online bioinformatic serves as well as local hospital samples validation, we identified SPP1 and PLAU as two independent prognostic indicators in OSCC and preliminary explored their biological features and clinical significance. Although further experiments and rigorous clinical trials are needed to reveal the genes’ potential drug-target role in clinical medical use, the results shall provide inspiring insights into current understanding of the genetic events in OSCC development and provoke next step deeply exploration of the disease.
Publisher
Research Square Platform LLC