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Biology subjects

Vidal, A. F.

Publications and source records attributed to Vidal, A. F..

4 recordsLinked to original sources

Transcriptomic Mutational Profiling of Gastric Adenocarcinoma in Northern Brazil

Gastric cancer (GC) remains among the neoplasms with the worst prognosis, partly due to its biological heterogeneity and the scarcity of robust biomarkers. The characterization of mutational profiles from transcripts can reveal specific tumor signatures and point to therapeutic targets. This study investigated the landscape of mutations expressed in 102 samples of gastric adenocarcinoma from northern Brazil, which were sequenced using NGS. Readings were aligned to the reference genome using STAR (two-pass mode), and variants were called with GATK and VarDict. Annotations and impact predictions were generated using VEP, SIFT, and PolyPhen. We identified >90,000 variants; among the most frequently mutated genes, FTH1 stood out. The mutational profile was described using maftools, and signatures were inferred with MutationalPatterns. We observed a predominant distribution of SNVs, with C>T transitions as the most common event, in addition to patterns compatible with signatures related to replication damage and DNA repair. To mitigate biases inherent to RNA-seq, we applied filters for coverage, strand bias, and RNA editing hotspots. Together, the data outline a regional landscape of mutations expressed in GC and reinforce the usefulness of the transcriptome for prioritizing biomarkers and functional hypotheses that may guide genomic validations and subsequent clinical studies.

bioinformatics↗

EXPRESSION INSIGHTS INTO GASTRIC ADENOCARCINOMA: NETWORK ANALYSIS REVEALS KEY HUB GENES AND FUNCTIONAL MODULES

Gastric cancer remains a leading cause of cancer-related mortality worldwide, with poor survival rates. To uncover its molecular basis, we performed weighted gene coexpression network analysis on RNA-seq data from 119 gastric adenocarcinoma (GAC) and peritumoral tissue (PTT) samples. We identified six key coexpression modules: MEmagenta, MEbrown, MEgreen, and MEturquoise showed strong positive correlations with GAC, whereas MEblack and MEblue were negatively correlated. Hub genes such as COL3A1, PGAM1, and CFL1 were among the most highly expressed in GAC samples compared to PTT. ROC analyses of selected hub genes yielded AUC values exceeding 0.80 for distinguishing GAC from PTT, underscoring their diagnostic potential. Integrating cellular deconvolution with module expression revealed that MEblack hub genes (TFF1, TFF2, GKN1, GKN2 and MUCL3) correlated positively with B-cell abundance and negatively with resting mast cells and neutrophils. Conversely, MEturquoise hub genes (COL1A2, COL3A1, TAGLN and SPARC) correlated strongly with Cance Associated Fibroblasts and inversely with B-cells, reflecting a collagen-rich stroma. We also observed overlapping expression profiles between GAC and PTT, indicating tumor heterogeneity and a molecular continuum between normal and neoplastic tissues. These integrated insights highlight candidate biomarkers and in GAC.

genomics↗

Unmasking Epstein-Barr Role in Gastric Carcinogenesis: A Gene Expression Approach to Virus-Positive Tumors

Human gammaherpesvirus 4 or Epstein-Barr virus (EBV) is an oncogenic virus linked to malignancies like gastric adenocarcinoma. Notably, EBV infection induces genetic and epigenetic modifications that play a crucial role in oncogenesis and tumor progression, underscoring the importance of analyzing viral gene expression in the context of gastric cancer (GC) to elucidate its unique characteristics. This study aimed to perform a molecular characterization of EBV gene expression using next-generation sequencing (NGS). The analysis included human gene expression patterns in EBV-positive and EBV-negative samples and the expression of viral genes in EBV-positive samples. The study received approval from the Ethics and Research Committee of Joao de Barros Barreto University Hospital under reference number 47580121.9.0000.5634. It utilized 76 tumor tissue samples from patients with gastric cancer who had undergone surgical resection, and both fresh and paraffin-embedded samples were gathered for total RNA sequencing (RNA-seq) and in situ hybridization (ISH). The RNA-seq was conducted in a pair-end manner on the NextSeq(R) platform (Illumina(R), US). The NextSeq(R) 500 MID Output V2 kit - 150 cycles (Illumina(R)) were utilized following the manufacturers instructions. ISH targeting RNA-1 of EBER1 (Y5200, DAKO, Carpinteria) was performed using the automated Dako system. Molecular characterization was conducted using the Kraken2 software. Subsequently, to elucidate the mechanisms through which EBV may influence gastric cancer, we analyzed the patterns of human gene expression in EBV-positive and EBV-negative samples. Of the 76 samples, 8 were classified as EBV-positive according to the applied methodology. Our analysis identified approximately 834 differentially expressed genes, 92 of which exhibited an AUC > 0.85. These genes are implicated in tumor progression, cellular metabolism, and both innate and adaptive immune responses. Additionally, viral genes expressed in the positive samples were evaluated, and we found manifestations of both lytic phase and latent phase genes. Finally, our study presents an efficient strategy for molecular classification of EBV-positive gastric cancer based on NGS and shows the effects of EBV on human gene expression. Author summaryIn our study, we explored how EBV influences the development of stomach cancer. EBV is a virus known to be linked to various cancers, including gastric cancer, and it can alter the behavior of both human and viral genes within infected cells. To investigate this, we analyzed tissue samples from 76 patients with stomach cancer, focusing on differences between samples with and without EBV. Using advanced sequencing technology, we identified over 800 genes that behave differently in EBV-positive cancers. These genes are involved in critical processes like how cells grow, how the immune system responds, and how energy is produced within cells. We also examined which EBV genes were active in the cancer samples and found evidence of both dormant and active phases of the virus. Our work demonstrated how EBV may contribute to stomach cancer and suggests new ways to classify and understand this disease. By uncovering these details, we hope to pave the way for more targeted treatments in the future.

cancer biology↗

Characterization and analysis of the transcriptome in Arapaima gigas using multi-tissue RNA-sequencing

Arapaima gigas is a giant bony tongue air-breathing fish, and a promising species for aquaculture due to its particular features. However, there is still a lack of information on its biology and few transcriptome studies are available. Our aim was to characterize the transcriptome of arapaima in order to shed light on molecular networks contributing to its unique traits. Through RNA-sequencing, we generated a transcriptome from eight tissues (brain, pituitary, heart, muscle, kidney, lung, ovary, and testis) collected from arapaima adults specimens. Using a genome-guided strategy associated with homologous protein evidence, 57,706 transcripts were assembled, which aligned to 23,353 high confidence protein-coding genes. The analysis revealed a global view of expression patterns, as well as it allowed us to identify tissue-specific gene clusters, transcription factors within the clusters, and to compare expression patterns between male and female. These analyses has generated tissue-specific and sex-biased transcriptome profiles, which will be helpful to understand its molecular biology, evolution, and also guide future functional studies of the arapaima.

genomics↗