Locally advanced rectal cancer transcriptomic-based secretome analysis reveals novel biomarkers useful to identify patients according to neoadjuvant chemoradiotherapy response

Nenhuma Miniatura disponível

Data

2019-12-01

Autores

Canto, Luisa Matos do
Cury, Sarah Santiloni [UNESP]
Barros-Filho, Mateus Camargo
Kupper, Bruna Elisa Catin
Begnami, Maria Dirlei Ferreira de Souza
Scapulatempo-Neto, Cristovam
Carvalho, Robson Francisco [UNESP]
Marchi, Fabio Albuquerque
Olsen, Dorte Aalund
Madsen, Jonna Skov

Título da Revista

ISSN da Revista

Título de Volume

Editor

Resumo

Most patients with locally advanced rectal cancer (LARC) present incomplete pathological response (pIR) to neoadjuvant chemoradiotherapy (nCRT). Despite the efforts to predict treatment response using tumor-molecular features, as differentially expressed genes, no molecule has proved to be a strong biomarker. The tumor secretome analysis is a promising strategy for biomarkers identification, which can be assessed using transcriptomic data. We performed transcriptomic-based secretome analysis to select potentially secreted proteins using an in silico approach. The tumor expression profile of 28 LARC biopsies collected before nCRT was compared with normal rectal tissues (NT). The expression profile showed no significant differences between complete (pCR) and incomplete responders to nCRT. Genes with increased expression (pCR = 106 and pIR = 357) were used for secretome analysis based on public databases (Vesiclepedia, Human Cancer Secretome, and Plasma Proteome). Seventeen potentially secreted candidates (pCR = 1, pIR = 13 and 3 in both groups) were further investigated in two independent datasets (TCGA and GSE68204) confirming their over-expression in LARC and association with nCRT response (GSE68204). The expression of circulating amphiregulin and cMET proteins was confirmed in serum from 14 LARC patients. Future studies in liquid biopsies could confirm the utility of these proteins for personalized treatment in LARC patients.

Descrição

Palavras-chave

Como citar

Scientific Reports, v. 9, n. 1, 2019.