Gastric Cancer Microbiome

Identifying a microbiome pattern in gastric cancer (GC) is hugely debatable due to the variation resulting from the diversity of the studied populations, clinical scenarios, and metagenomic approach. H. pylori remains the main microorganism impacting gastric carcinogenesis and seems necessary for the initial steps of the process. Nevertheless, an additional non-H. pylori microbiome pattern is also described, mainly at the final steps of the carcinogenesis. Unfortunately, most of the presented results are not reproducible, and there are no consensual candidates to share the H. pylori protagonists. Limitations to reach a consistent interpretation of metagenomic data include contamination along every step of the process, which might cause relevant misinterpretations. In addition, the functional consequences of an altered microbiome might be addressed. Aiming to minimize methodological bias and limitations due to small sample size and the lack of standardization of bioinformatics assessment and interpretation, we carried out a comprehensive analysis of the publicly available metagenomic data from various conditions relevant to gastric carcinogenesis. Mainly, instead of just analyzing the results of each available publication, a new approach was launched, allowing the comprehensive analysis of the total sample amount, aiming to produce a reliable interpretation due to using a significant number of samples, from different origins, in a standard protocol. Among the main results, Helicobacter and Prevotella figured in the "top 6" genera of every group. Helicobacter was the first one in chronic gastritis (CG), gastric cancer (GC), and adjacent (ADJ) groups, while Prevotella was the leader among healthy control (HC) samples. Groups of bacteria are differently abundant in each clinical situation, and bacterial metabolic pathways also diverge along the carcinogenesis cascade. This information may support future microbiome interventions aiming to face the carcinogenesis process and/or reduce GC risk.

Identifying novel genetic alterations in pediatric acute lymphoblastic leukemia based on copy number analysis

Copy number variations (CNVs) analysis may reveal molecular biomarkers and provide information on the pathogenesis of acute lymphoblastic leukemia (ALL). We investigated the gene copy number in childhood ALL by microarray and select three new recurrent CNVs to evaluate by real-time PCR assay: DMBT1, KIAA0125 and PRDM16 were selected due to high frequency of CNVs in ALL samples and based on their potential biological functions in carcinogenesis described in the literature. DBMT1 deletion was associated with patients with chromosomal translocations and is a potential tumor suppressor; KIAA0125 and PRDM16 may act as an oncogene despite having a paradoxical behavior in carcinogenesis. This study reinforces that microarrays/aCGH is it is a powerful tool for detection of genomic aberrations, which may be used in the risk stratification.

Effect of American genomic ancestry on severe toxicities in children with acute lymphoblastic leukemia in the Amazon region

BACKGROUND

Acute Lymphoblastic Leukemia (ALL) is a neoplasm of the hematopoietic system characterized by a clonal expansion of abnormal lymphocyte precursor cells. ALL is the most common form of cancer in children, but despite advances in treatment, it can still be fatal. Ethnic differences influence survival rates, and genomic ancestry plays an important role, especially in mixed-race populations such as Latin America. This study aims to analyze the influence of genomic ancestry on toxicity in children with ALL in the Amazon region.

METHODS

The study included 171 patients (protocol number 119,649/2012-Ethics Committee) with ALL treated at a pediatric treatment center in Belém do Pará, in the Brazilian Amazon. The patients were submitted to the BFM protocol of induction therapy for ALL. Toxicity was assessed based on laboratory tests and adverse events, classified according to the CTC-NCI guide. Genomic ancestry was determined using autosomal informative markers.

RESULTS

The majority of children (94.74%) developed some type of toxicity during treatment, 87.04% of which were severe. Infectious toxicity was the most common, present in 84.8% of cases, 77.24% of which were severe. Amerindian ancestry showed an association with the risk of severe general toxicity and severe infectious toxicity, with a contribution of 35.0% demonstrating a significant increase in risk. In addition, post-induction refractoriness and relapse were also associated with an increased risk of death.

CONCLUSION

This study highlights the influence of Amerindian genomic ancestry on response to therapy and toxicity in children with ALL in the Amazon region. Understanding these associations can contribute to personalizing treatment and improving clinical outcomes.