A Novel Lysosome-Related Gene Signature Predicts Lung Cancer Prognosis: A Bioinformatics-Driven Study.

BACKGROUND AND AIMS

The biological function of lysosomes has been increasingly appreciated in cancer. However, the relationship between lysosome and lung adenocarcinoma (LUAD) was not well understood. In this study, a lysosome-related signature was developed for LUAD risk stratification and prognosis prediction.

METHODS

Download RNA-seq data of LUAD and clinical information of corresponding samples from the UCSC-Xena platform. GSE31210 databases is used as a validation cohort. The lysosome-related genes was obtained from molecular signature database. The differentially expressed genes (DEGs) as well as lysosome-associated prognosis signatures were identified by using univariate, multivariate cox, and Lasso regression. A nomogram was constructed and evaluated using ROC and DCA.

RESULTS

A total of 109 lysosome-related DEGs were identified and 30 prognostic related DEGs were subsequently screened. Cluster analysis further divides the TCGA cohort into clusters 1 and 2. Patients in cluster 2 had a worse prognosis ( = 0.016), lower LYSOSOME score. Enrichment analysis showed that 21 significantly enriched gene sets in the cluster 2 were activated. And 10 pathways, such as E2F_TARGETS, G2M_CHECKPOINT were upregulated. Multivariate Cox regression analysis identified 17 best prognostic genes as risk signature. An independent prognostic factor, the risk signature, was identified. A prognostic nomogram including risk signature, age, TNM stage, and gender was constructed, and ROC and DCA curves proved its excellent performance. We examined CTSZ and AP3S2 protein expression in 48 stage 3-4 NSCLC samples. Low AP3S2 expression was associated with better prognosis (median overall survival: 37.87 vs. 8.53 months,  = 0.0211). Increased CTSZ expression also indicated better prognosis (median overall survival: 6.77 vs. 30.50 months,  = 0.0306).

CONCLUSION

We identified molecular subtypes and lysosomal-based prognostic signatures for LUAD patients, as well as 17 genes that serve as a biomarker for evaluating the prognosis of LUAD patients.