Identification of a polyamine-related signature and six novel prognostic biomarkers in oral squamous cell carcinoma

Abstract

Elevated polyamine levels are required for tumor transformation and development; however, expression patterns of polyamines and their diagnostic potential have not been investigated in oral squamous cell carcinoma (OSCC), and its impact on prognosis has yet to be determined. A total of 440 OSCC samples and clinical data were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Consensus clustering was conducted to classify OSCC patients into two subgroups based on the expression of the 17 polyamine regulators. Polyamine-related differentially expressed genes (PARDEGs) among distinct polyamine clusters were determined. To create a prognostic model, PARDEGs were examined in the training cohorts using univariate-Lasso-multivariate Cox regression analyses. Six prognostic genes, namely, “CKS2,” “RIMS3,” “TRAC,” “FMOD,” CALML5,” and “SPINK7,” were identified and applied to develop a predictive model for OSCC. According to the median risk score, the patients were split into high-risk and low-risk groups. The predictive performance of the six gene models was proven by the ROC curve analysis of the training and validation cohorts. Kaplan–Meier curves revealed that the high-risk group had poorer prognosis. Furthermore, the low-risk group was more susceptible to four chemotherapy drugs according to the IC50 of the samples computed by the “pRRophetic” package. The correlation between the risk scores and the proportion of immune cells was calculated. Meanwhile, the tumor mutational burden (TMB) value of the high-risk group was higher. Real-time quantitative polymerase chain reaction was applied to verify the genes constructing the model. The possible connections of the six genes with various immune cell infiltration and therapeutic markers were anticipated. In conclusion, we identified a polyamine-related prognostic signature, and six novel biomarkers in OSCC, which may provide insights to identify new treatment targets for OSCC.

Baicalin induces ferroptosis in oral squamous cell carcinoma by suppressing the activity of FTH1

“…Oral squamous cell carcinoma is one of the most common malignancies worldwide, 24 and its morbidity and mortality in China are increasing annually. 25 HNSCC patients. 28 However, many patients are either intrinsically resistant to these regimens (chemotherapy, targeted therapy or immunotherapy) or develop acquired resistance.…”

“…Oral squamous cell carcinoma is one of the most common malignancies worldwide, 24 and its morbidity and mortality in China are increasing annually 25 . Surgery or definitive radiotherapy (RT) is used to treat OSCC patients at the early stages, and the majority of the patients have a good prognosis.…”

A novel sphingolipid metabolism-related long noncoding RNA signature predicts the prognosis, immune landscape and therapeutic response in pancreatic adenocarcinoma

“…Although risk stratification based on the SMLs can better predict the survival and clinical outcomes of patients with PAAD, it cannot distinguish populations with different TIME characteristics. Studies have shown that tumor subgroups derived from consensus clustering analysis have different TIME characteristics and impact immunotherapy response [ [66] , [67] , [68] ]. Accordingly, we performed a consensus clustering analysis based on the constructed SMLs, dividing the TCGA-PAAD cohort into two clusters to further explore the differences in clinical outcomes and the TIME of patients in different subtypes.…”