# Construction of circadian clock signature for tumor microenvironment in predicting survival of esophageal squamous cell carcinoma

## TL;DR

This study identifies seven circadian clock genes linked to esophageal cancer prognosis and immune response, suggesting CST3 as a potential biomarker and treatment target.

## Contribution

A novel ESCC-specific circadian clock gene signature is developed for prognosis prediction and immune infiltration analysis.

## Key findings

- Seven DE-CCGs (CST3, C1QBP, TTF2, EGFR, CDKN2A, PFAS, TRRAP) correlate with poor ESCC prognosis.
- High-risk ESCC patients show increased tumor infiltration and CST3 expression linked to tumor growth.
- CST3 combined with PD-L1 may serve as a prognostic marker for ESCC patients.

## Abstract

Esophageal squamous cell carcinoma (ESCC) is a distinct subtype of esophageal cancer (EC). Research indicates that circadian clock genes (CCGs) in human ESCC are dysregulated. However, the significance of CCGs in ESCC prognosis remains ambiguous. This study sought to establish a complete signature of ESCC-specific differentially expressed CCGs (DE-CCGs) associated with prognosis, tumor growth, and immunological infiltration.

Differentially expressed genes (DEGs) between normal and ESCC samples in TCGA database and the GSE23400 dataset were intersected with CCGs to obtain DE-CCGs. The prognosis-related DE-CCGs were discerned to develop a risk model using univariate Cox regression and LASSO regression analyses in TCGA-ESCC. The accuracy of the model was validated using risk and overall survival profiles.

Seven DE-CCGs (CST3, C1QBP, TTF2, EGFR, CDKN2A, PFAS, TRRAP) were identified in TCGA-ESCC, which were correlated with unfavorable ESCC prognosis. The immune infiltration analysis revealed that High-risk ESCC patients displayed enhanced tumor infiltration. And the combination of CST3 and PD-L1 expression may serve as a potential marker for predicting prognosis of ESCC patients. Moreover, in Vitro experimental models, CST3 expression was markedly elevated in tumor cells and associated with ESCC growth.

This research illustrated the prognostic significance of seven DE-CCGs for ESCC patients based on tumor progression and immune infiltration. And the CST3 may serve as an independent prognostic biomarker and a potential therapeutic target for ESCC.

Flowchart depicting a study process on esophageal squamous cell carcinoma (ESCC). It begins with data from TCGA-ESCC and GSE23400 cohorts, leading to the identification of ESCC-DE-CCGs. Lasso regression is applied to construct a seven-feature gene prognostic model, which is validated through ROC and predictive nomogram. Correlation analysis between the risk model and clinical features includes GESA and TME analysis. High-risk group analysis leads to immune cell infiltration, drug sensitivity studies, and CST3 verification.