Abstract
Background
Lung cancer is a major contributor to cancer rates and deaths worldwide. Due to its complexity and variability, lung cancer progresses quickly and has a grim outlook, making early and precise diagnosis imperative. Despite numerous clinical methods available to aid doctors in detecting lung cancer, there is still a need for a non-invasive biomarker for cancer development.
Methods
We examine the levels of TREML1 mRNA and protein expression in exosomes derived from tumors in both normal and cancerous lung tissues of humans, utilizing information from TCGA, GTEx, HPA databases, as well as samples obtained from clinical settings. Validation experiments were performed on tissue microarrays obtained from lung cancer samples. We examined targeted next-generation sequencing data from the TCGA database to gain insight into the frequency of TREML1 mutations and the collection of genes that are co-altered in tumors with TREML1 mutations.
Results
Our findings reveal that TREML1 is highly expressed in lung cancer, and could be one valueable predictor which may be applied in clinic in the future. Analysis of survival data from the TCGA and GTEx database suggests that high levels of TREML1 expression are associated with poor clinical prognosis in lung cancer. Analysis of gene mutations revealed that TTN (53.7%) is the most frequent alteration associated with TREML1 overexpression in LUAD, while APOB is the most common alteration in LUSC.
Conclusions
It can be concluded that TREML1 is a suitable target for prognosis and treatment markers. Additional research is required to comprehensively grasp how TREML1 interacts with these signaling pathways, which will be the primary focus of our upcoming studies.