Dados do Trabalho


A diagnostic and prognostic value of a 77-gene set for patients with lung adenocarcinoma


Lung cancer remains a significant global health concern due to its high mortality rate. Therapeutic options for lung adenocarcinoma (LUAD) have increased, but challenges persist in late diagnosis and prognostic stratification. Differentially expressed genes (DEG) may be employed as biomarkers for LUAD management.


To identify potential biomarkers for diagnosis and prognosis of LUAD.


We evaluated fresh-frozen tumoral tissues from patients with LUAD (n=53) from a single cancer center (Project 1139/2016 – CAAE: 55631316.2.0000.5437). Gene expression analysis was conducted using the nCounter® PanCancer Pathways panel (NanoString Technologies). Upregulated and downregulated genes were selected according to fold-change (FC ≥ |2|) and p-value (p ≤ 0.01) using the ROSALIND software. DEG were in silico validated using The Cancer Genome Atlas Lung Adenocarcinoma dataset. Enrichment analysis was performed using STRING platform, incorporating Wikipathways and Kyoto Encyclopedia of Genes and Genomes databases. Median normalized counts were used as cut-off for stratification of genes for overall survival analysis.


We identified a 78-gene signature distinguishing tumoral tissues from histopathological normal lung tissue. Seventy-seven out of the 78-gene signature were validated in public datasets (p<0.05) and demonstrated strong biological connectivity (PPIp-value=1.0e-16). The patients were further stratified into two groups based on gene expression levels using the Partition Around Medoids (PAM) clustering algorithm. An association with survival was noted (p<0.001), whereas the cluster II displaying a hazard ratio (HR) of 3.28 (95% CI: 1.49-7.19; p=0.003) compared to cluster I. Remarkably, lower expression of CD19 and APH1B showed HRs of 2.37 (95% CI: 1.05-5.08; p=0.036) and 3.82 (95% CI: 1.63-8.91; p=0.002), respectively, highlighting their prognostic value.


We identified a 77-gene signature with promising potential to enhance the accuracy of diagnosing lung adenocarcinoma and aid in prognostic stratification for these patients.


Lung adenocarcinoma; diagnosis and prognosis stratification; NanoString.

Financiador do resumo

Barretos Cancer Hospital; Coordination for the Improvement of Higher Education Personnel (CAPES); Public Ministry of Labor Campinas (MPT).


Estudo Clínico - Tumores de Pulmão e Tórax


ISABELLA LEMUQUI TEGAMI, Luciane Sussuchi da Silva, Rodrigo de Oliveira Cavagna, Maria Fernanda Gonçalves, Flávio Augusto Ferreira da Silva, Eduardo Caetano Albino da Silva, Vinicius Duval da Silva, Pedro De Marchi, Rui Manuel Reis, Letícia Ferro Leal