# Construction of a risk model associated with tryptophan metabolism and identification of related molecular subtypes in laryngeal squamous cell carcinoma

## TL;DR

This study builds a risk model based on tryptophan metabolism genes to predict laryngeal cancer prognosis and treatment response.

## Contribution

A novel risk model using tryptophan metabolism-related genes to predict prognosis and drug sensitivity in laryngeal squamous cell carcinoma.

## Key findings

- Five prognostic genes (SERPINA1, TMC8, RENBP, SDS, FAM107A) were identified for laryngeal squamous cell carcinoma.
- High-risk patients showed higher immune dysfunction and lower immunotherapy responsiveness.
- Low-risk patients were more sensitive to Salubrinal, Lenalidomide, and Metformin.

## Abstract

Catabolic metabolites of tryptophan (Trp) are considered to be important microenvironmental factors by suppressing anti-tumor immune responses in cancers. Nevertheless, the effect of Trp metabolism (Trp metabolism)-related genes Trp metabolism-related genes on laryngeal squamous cell carcinoma (LSCC) progression is not yet clear. So, in this study, the TCGA-LSCC, GSE27020, and 40 TMRGs were extracted via public databases to explore the effects of TMRGs on laryngeal squamous cell carcinoma. Firstly, Weighted Gene Co-expression Network Analysis (WGCNA) was adopted with LSCC samples in TCGA-LSCC to acquire key module, and differentially expressed genes between LSCC and normal samples from TCGA-LSCC were yielded via differential expression analysis. Next, differentially expressed TMRGs (DE-TMRGs) was obtained in key model and DEGs, and prognostic genes were identifde through multiple algorithms. Five prognostic genes, namely SERPINA1, TMC8, RENBP, SDS and FAM107A were finally identified. A risk model was established based on the expressions of prognostic genes and survival information of LSCC samples while that were divided into high and low risk groups. Obviously, the LSCC immune dysfunction and exclusion score of high-risk patients was dramatically higher than that in low-risk patients, indicating that patients in the high-risk subgroup exhibited reduced responsiveness to immunotherapy. Besides, the drug sensitivity analysis showed that the low -risk subgroup was notably sensitive to Salubrinal, Lenalidomide, Metformin, while high -risk subgroup was more responsive to Docetaxel, AUY922, Embelin. Eventually, two clusters of LSCC samples had notable correlations with LSCC prognosis. The above results indicated that the risk model consisted of TMRGs (SERPINA1, TMC8, RENBP, SDS and FAM107A) was constructed in LSCC, contributing to studies related to the prognosis and treatment of LSCC.