Identification of potential cachexia biomarkers in the secretome of pulmonary adenocarcinoma

Abstract

Cachexia is multifactorial metabolical syndrome that is very common in advanced malignant neoplasms. Its main characteristic is the significant loss of muscle mass (with concomitant loss of fat or not), which can not be reversed by nutritional support, leading to progressive dysfunctions. This condition has been vastly considered as a paraneoplastic syndrome, in which tumor derived factors induce global alterations in the genetic expression or metabolic flux, resulting in the liberation of molecules that could be used in the growth and expansion of the tumor. Recent advances in genomic, transcriptomic and proteomic studies on cancer have been useful in the identification of sets of molecules secreted by tumor cells (the secretome). The components of the secretome of the tumorigenic environment includes pro-inflammatory cytokines, which are fundamental in metabolic alterations that lead to muscle loss in cachectic patients. Among the list of cancers that cause cachexia we have lung cancer, which has a very high incidence in the world. The loss of muscle mass is considered a powerful prognostic factor for lung cancer patients, and thus the analysis of the pectoral muscle mass through computerized tomographies (CT) has been utilized with great efficacy to determine the presence of cachexia. Considering that there still isn't an effective treatment for cachexia and that the viability of "omic" tools for the identification of molecular alterations in this condition, it is important to evaluate how the tumor secretome relates to the incidence of cachexia. Therefore, the objective of this project is to integrate clinical data such as the area of the pectoralis muscle, obtained through CT to the tumorigenic transcriptional profile to identify potential cachexia biomarkers in the secretome of pulmonary adenocarcinoma. For that, 69 CTs from pulmonary adenocarcinoma patients, available on The Cancer Imaging Archive data base (TCIA, http://www.cancerimagingarchive.net/) will be used to dichotomize cachectic and non-cachectic patients, based on their muscle areas. Then, the transcriptomic data from their tumors, available at The Cancer Genome Atlas (TCGA, http://www.cancergenome.nih.gov/) will be analyzed to identify transcripts with elevated expression in cachectic patients. These transcripts will then be selected based on their probability of being in the secretome, such as being an extracellular RNA or vesicle communication transcript. Additionally, this data will be correlated to other clinical data of these patients through the oncogenomic websites UCSC Cancer Genomics Browser, ICGC Data Portal, COSMIC, cBioPortal, IntOGen and BioProfiling.de. The results will be used as basis for the identification of potential cachexia biomarkers in the secretome of pulmonary adenocarcinoma. These potential biomarkers could also be used in the development of future therapies to reduce the loss of muscle mass, increasing the life expectancy and life quality of cachectic patients. (AU)