Expression-based, consistent biomarkers for prognosis and diagnosis in lung cancer

Lung cancer is one of the deadliest cancers in the world. Its histological classification depends on early diagnosis and successful treatment. Therefore, having specific biomarkers for a quick sorting widens the successful output of lung cancer treatment.

High-throughput sequencing (RNA-seq) was performed of small cohorts of BioBanco samples from healthy and tumour cells from lung adenocarcinoma (LUAD) and squamous cell carcinoma of the lung (lSCC). RNA-seq samples from small cell lung cancer (SCLC) were downloaded from databases. A bioinformatic workflow has been programmed for the identification of differentially expressed genes (DEGs).

A total of 4777 DEGs were differentially expressed in SCLC, 3676 DEGs were in lSCC, while the lowest number of DEGs, 2819, appeared in LUAD. Among them, 945 DEGs were common to the three histological types. Once validated their expression profile and their survival predictive capacity in large, public cohorts, three DEGs can be exclusively considered as diagnostic biomarkers, three as prognosis biomarkers, and other three exhibit both diagnosis and prognosis capabilities.

This prospective study presents evidences for the diagnostic and prognostic capabilities of expression changes in CAPN8-2, TMC5 and MUC1 in LUAD, while they are non-significant in SCLC and lSCC. Their translation to clinical practice is proposed.