Dados do Resumo
Título
Key Gene Networks and Hub Genes in Gastric Adenocarcinoma
Introdução
Gastric cancer (GC) ranks as the fifth most common cancer and the fourth leading cause of cancer deaths. Although incidence and mortality rates have decreased due to early diagnosis and Helicobacter pylori eradication, GC remains a major global health issue with a 5-year survival rate below 30%. The heterogeneous nature of GC and its complex gene expression profiles present ongoing treatment challenges. Recent advances in systems biology, including weighted gene coexpression networks, offer new insights into gene modules linked to GC, revealing potential therapeutic targets.
Objetivo
This study aims to construct and analyze gene coexpression networks derived from Gastric Adenocarcinoma (GAC) and adjacent peritumoral tissues. By utilizing a scale-free topology approach, we delineated distinct coexpression networks and investigated their correlations with tumor characteristics.
Métodos
We analyzed 119 tumor and peritumoral tissue samples from gastric adenocarcinoma patients at João de Barros Barreto University Hospital, Belém, Brazil, with ethical approval (No. 47580121.9.0000.5634) and informed consent. Clinical data from 81 patients included GC presence, histological subtype, chemotherapy regimens, and molecular markers (EBV, HER, hPSM2, hMLH1, p53), along with survival information. RNA was extracted using TRIZOL® from 50-100 ng tissue, and quality was assessed with Qubit, NanoDrop, and TapeStation, meeting criteria of A260/A280 ratio 1.8-2.2, A260/A230 >1.8, and RIN ≥ 5. cDNA libraries were prepared with TruSeq Stranded Total RNA Library Prep Kit and sequenced on Illumina NextSeq® 500. Weighted gene co-expression network analysis (WGCNA) included 11,620 genes, using β = 10 for network construction, and modules were correlated with clinical data. Functional enrichment was analyzed using ClusterProfile, and ROC curves for gene expression were plotted with pROC v1.18. Networks were vizualized in Cytoscape.
Resultados
We analyzed gene expression in GAC tumor tissues (n=65) versus peritumoral tissues (n=54) using weighted gene co-expression network analysis (WGCNA). We identified 10 co-expression modules (or networks) with distinct patterns. The MEmagenta, MEbrown, MEgreen, and MEturquoise modules were positively correlated with tumor tissues, while MEblack and MEblue showed negative correlations. Hub genes like COL3A1 and SPARC in MEmagenta, RPL36 and COX6A1 in MEbrown, and PSAP and RPL18 in MEgreen were notably expressed in tumor tissues. Conversely, MEblack and MEblue hubs were upregulated in peritumoral tissues. Functional enrichment highlighted roles in extracellular matrix organization, protein metabolism, and energy regulation. Correlation analyses revealed links between gene expression and clinical features, such as Laurén classification and neoadjuvance, providing insights into the complex interactions in GAC.
Conclusões
Our GAC gene expression analysis reveals co-expression patterns with key genes in tumor progression. COL3A1 and SPARC are crucial for ECM remodeling and tissue invasion, while RPL10A and EEF1A1 are important for protein synthesis and proliferation. Limitations include a small sample size and the need for functional validation of identified genes.
Financiador do resumo
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
Fundação Amazônia de Amparo a Estudos e Pesquisas (FAPESPA)
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
Palavras Chave
Gene Coexpression Networks; Gastric Adenocarcinoma; Hub Genes
Área
7.Pesquisa básica/translacional
Autores
RONALD MATHEUS DA SILVA MOURAO, Jéssica Costa Silva, Daniel de Souza Avelar Costa, Valéria Cristiane Santos da Silva, Ana Karyssa Anaissi, Samia Demachki, Williams Fernandes Barra, Geraldo Ishak Ishak, Paulo Pimentel Assumpção, Fabiano Cordeiro Moreira