Ronald Matheus da Silva Mourão

This study identifies ANPEP as upregulated in gastric adenocarcinoma and associated with immune suppression and tumor progression, suggesting its potential as a biomarker and therapeutic target.

This study compares microbial diversity, immune cell composition, and gene expression in gastric adenocarcinoma and peritumoral tissue to identify functional differences in their microenvironments.

The paper identifies a 138-gene transcriptional signature in gastric cancer peritumoral tissue that is conserved in tumors and associated with poor prognosis.

This study analyzes mutational profiles in gastric adenocarcinoma samples from northern Brazil using NGS, identifying key mutations and patterns associated with replication damage and DNA repair.

This study identifies molecular subtypes of gastric adenocarcinoma that correlate with prognosis but find that neither histology nor a derived signature alone reliably stratifies survival.

This study examines how the FLOT chemotherapy regimen affects the gastric tumor microenvironment, revealing subtype-specific microbiome-host interactions that influence tumor behavior.

This study analyzes the expression of C-MYC and its associated pathways in gastric adenocarcinoma, identifying dysregulated genes and their correlation with clinicopathological factors.

This study identifies distinct ferroptosis gene signatures in gastric adenocarcinoma and adjacent tissues, revealing transcriptional heterogeneity and regulatory imbalances.

This study identifies differentially expressed transcription factors in gastric adenocarcinoma using NGS and bioinformatics, revealing potential biomarkers for prognosis and treatment.

This study characterizes HERV expression in gastric cancer tissues and finds differential expression in tumor samples, particularly those with H. pylori infection.

The paper identifies viral species in gastric tumor and peritumoral tissues, finding enriched viruses and comparable diversity between tissue types.

The paper uses coexpression network analysis on RNA-seq data to identify key hub genes and modules associated with gastric adenocarcinoma, revealing potential diagnostic biomarkers and tumor microenvironment interactions.

This study uses RNA-seq to analyze gene expression in EBV-positive and EBV-negative gastric cancer samples, identifying differentially expressed genes and viral gene activity associated with tumor progression.