A transcriptional metabolic gene-set based prognostic signature is associated with clinical and mutational features in head and neck squamous cell carcinoma

Abstract

Purpose: Head and neck squamous cell carcinoma (HNSCC) is a common cancer with high mortality and poor prognosis partially owing to lack of application of predictive markers. Increasing evidence has suggested that metabolic dysregulation plays an important part in tumorigenesis. We aim to identify a prognostic metabolic pathway (MP) signature in HNSCC.

Methods: Single sample gene-set enrichment analysis (ssGSEA) was used in metabolic gene sets to develop a metabolism-based prognostic risk score (MPRS) for HNSCC using Cox regression analysis (univariate, LASSO, and stepwise multiple cox analysis), which was then validated in different subgroups, and association with clinical and mutational features was analyzed.

Results: Seventy-two dysregulated metabolic pathways were identified, and a six-MP signature (6MPS) was constructed which can effectively distinguish between the high- and low-risk patients in both training and testing sets, accompanied with high sensitivity and specificity (AUC = 0.7) in prognosis prediction. 6MPS was also applicable to patients of different subgroups. Furthermore, 6MPS is not only an independent prognostic predictor but also associated with clinicopathological and mutational features. Higher tumor stage and tumor mutation burden (TMB) have a higher MPRS.

Conclusion: 6MPS functions not only as a promising predictor of prognosis and survival but also as potential marker for therapeutic schedule monitoring.

Keywords: Biomarker; Head and neck squamous cell carcinoma; Metabolic pathway; Prognosis; Survival.

Fig. 1

Construction of 6MPS and its prognostic value. a LASSO coefficient profiles of the 21 survival-related MPs. A coefficient profile plot was produced against the log lambda sequence. b Tuning parameter (lambda) selection in the LASSO model used tenfold cross-validation via minimum criteria. A lambda value of 0.01485 was chosen (minimum criteria). Dotted vertical lines were drawn at the optimal values using the minimum criteria and the 1 standard error of the minimum criteria (the 1-SE criteria). c The Kaplan–Meier estimates of the OS for high-risk and low-risk patient cohorts grouping by the 6MPS in the training set (N = 346). The OS differences between the two groups were determined by the two-sided log-rank test. It can be concluded that higher MPRS are significantly associated with worse OS (p < 0.0001). d ROC analysis of sensitivity and specificity for the 6MPS in predicting the OS of patients for 1, 3, and 5 years in training set. e The distribution of MPRS, patients’ survival status and five MP enrichment scores in the training set were presented. As the risk score rising, the patients had a shorter survival time, more dead events, and a higher MP enrichment score. f, g The Kaplan–Meier estimates of the OS for high-risk and low-risk patients grouping by the 6MPS in the testing set (N = 148) and whole set (N = 494). The OS differences between the two groups were determined by the two-sided log-rank test. It can be concluded that higher MPRS are significantly associated with worse OS (p < 0.05). MP: metabolic pathway, MPRS: metabolism-based prognostic risk score, 6MPS: 6-MP signature, hsa00290: valine, leucine, and isoleucine biosynthesis, hsa01230: biosynthesis of amino acids, hsa00430: taurine and hypotaurine metabolism, hsa00380: tryptophan metabolism, hsa00232: caffeine metabolism, hsa00534: glycosaminoglycan biosynthesis—heparan sulfate/heparin

Fig. 2

The clinical association of MPRS. a The heatmap shows the MPRS level of the five metabolic pathways in low- and high-risk HNSCC. The distribution of clinical features was compared between the low- and high-risk groups. b Distribution of MPRS in different subgroups was compared, which stratified by gender, age, anatomic subdivision, grade, stage, and margin status. MP: metabolic pathway, MPRS: metabolism-based prognostic risk score, 6MPS: 6-MP signature, hsa00290: valine, leucine, and isoleucine biosynthesis, hsa01230: biosynthesis of amino acids, hsa00430: taurine and hypotaurine metabolism, hsa00380: tryptophan metabolism, hsa00232: caffeine metabolism, hsa00534: glycosaminoglycan biosynthesis—heparan sulfate / heparin. *p < 0.05, **p < 0.01

Fig. 3.

6MPS is an independent prognostic factor. a Univariate and b multivariate Cox regression analyses of the association between clinical factors (including the MPRS) and overall survival of patients in the HNSCC. The 6MPS is an independent prognostic factor (p value < 0.001). c Kaplan–Meier analyses of patients with HNSCC in different clinical subgroups, grouping based on their gender, age, anatomic subdivision, grade, stage, and margin status. Kaplan–Meier analysis with two-sided log-rank test was performed to estimate the differences in OS between the low-risk and high-risk patients. MPRS: metabolism-based prognostic risk score, 6MPS: 6-MP signature, *p < 0.05, **p < 0.001, ***p < 0.0001

Fig. 4

Associations between MPRS and mutation. a The overall summary of mutation information in HNSCC cohort by mutect2. b The oncoplot shows the top ten mutated genes in HNSCC cohort and their mutation information. c Distribution of MPRS in high-TMB and low-TMB groups was compared, The MPRS is higher in high-TMB group than low-TMB groups. d The Kaplan–Meier estimates of the OS for groups using combinations of MRPS and TMB. The OS differences between the four groups were determined by the two-sided log-rank test. TMB: Tumor mutation burden. e The heatmap shows the MP enrichment score of the five metabolic pathways in low- and high-risk HNSCC. The distributions of top ten mutation genes status were compared between the low- and high-risk groups. MP metabolic pathway, MPRS metabolism-based prognostic risk score, 6MPS 6-MP signature, hsa00290: valine, leucine, and isoleucine biosynthesis, hsa01230: biosynthesis of amino acids, hsa00430: taurine and hypotaurine metabolism, hsa00380: tryptophan metabolism, hsa00232: caffeine metabolism, hsa00534: glycosaminoglycan biosynthesis—heparan sulfate/heparin. **p < 0.01, *p < 0.05