Introduction: Gastric cancer (GC) is a heterogenous disease with clinicopathologic variations due to a complex interplay of environmental and biological factors, which may affect disparities in oncologic outcomes. Here, we characterize differences in the genetic and microbial profiles of GC in patients of African, European, and Asian ancestry. Methods: We identified 1,042 GC patients with next-generation sequencing (NGS) data from an institutional Integrated Mutation Profiling of Actionable Cancer Targets (IMPACT) assay and the Cancer Genomic Atlas (TCGA) group. Genetic ancestry was inferred from markers captured by the IMPACT and TCGA whole exome sequencing panels. Tumor microbial profiles were inferred from sequencing data using a validated microbiome bioinformatics pipeline. Genomic alterations and microbial profiles were compared between GC patients of different ancestries. Results: We assessed 8,023 genomic alterations. The most frequently altered genes were TP53, ARID1A, KRAS, ERBB2, and CDH1. Patients of African ancestry had a significantly higher rate of CCNE1 alterations and a lower rate of KRAS alterations (P<0.05), and patients of East Asian ancestry had a significantly lower rate of PI3K pathway alterations (P<0.05) compared to other ancestries. Microbial diversity and enrichment did not differ significantly across ancestry groups (P>0.05). Discussion: Distinct patterns of genomic alterations and variations in microbial profiles were identified in GC patients of African, European, and Asian ancestry. Our findings of variation in the prevalence of clinically actionable tumor alterations among ancestry groups suggest that precision medicine can mitigate oncologic disparities.
Objective: The microbiome is associated with the pathogenesis and progression of disease in gastric cancer (GC). Eradication of Helicobacter pylori has reduced overall GC incidence, however, gastroesophageal cancer (GEJC) continues to increase. While there are oncologic differences between GEJC and GC, distinctions based on microbial profiles are unknown. In this study, we characterize differences in the microbial profiles of GEJC and GC. Methods: 562 patients with microsatellite stable GC (n=303) and GEJC (n=259) who had an institutional Integrated Mutation Profiling of Actionable Cancer Targets assay on the primary tumor were included in the study. A validated microbiome bioinformatics pipeline that is generalizable across multiple next generation sequencing platforms was utilized to compare microbial enrichment and alpha diversity between GC and GEJC, defined by type 1-3 Siewert classification. Results: Over 20 unique microbial species were enriched in GC when compared to GEJC, including Helicobacter and Lymphocryptovirus (Table 1). Prevotella had increased incidence in GEJC (OR:1.57,95%CI:1.02,2.41). Siewert type 2 and 3 GEJC had a significantly lower alpha diversity compared to GC. There was no significant difference in alpha diversity between GC and Siewert type 1 GEJC. Conclusion: There are distinct differences in microbial enrichment and alpha diversity between GEJC and GC. Helicobacter and Lymphocryptovirus, the genus family for Epstein Bar Virus, were noted to have the highest odds ratios in the GC group. Our findings showing the reduced incidence of microbes in GEJC which are the current targets of GC screening, prevention, and therapy, have implications in evaluating optimal preventative and treatment strategies in GEJC. Table 1. Microbes with enrichment in gastric cancer (GC) when compared to gastroesophageal cancer (GEJC) Microbes OR (95% Confidence Interval) p-value Helicobacter 85.40 (5.191, 1404.81) 0.002 Lymphocryptovirus 6.83 (2.3120,.17) 0.001 Pelagibacterium 6.01 (1.71, 21.06) 0.005 Gluconacetobacter 5.14 (1.70, 15.53) 0.004 Myxococcus 5.14 (1.70, 15.53) 0.004 Kribbella 4.48 (1.46, 13.74) 0.009 Celeribacter 3.46 (1.43, 8.37) 0.006 Halomonas 3.46 (1.43, 8.37) 0.006 Nakamurella 3.35 (1.46, 7.71) 0.004 Nitrobacter 2.91 (1.40, 6.05) 0.004 Pseudogulbenkiania 2.80 (1.30, 6.03) 0.009 Mycobacteroides 2.78 (1.33, 5.81) 0.006 Polaromonas 2.70 (1.49, 4.90) 0.001 Meiothermus 2.54 (1.41, 4.57) 0.002 Sphingopyxis 2.44 (1.33, 4.46) 0.004 Mesorhizobium 2.38 (1.32, 4.30) 0.004 Staphylococcus 2.23 (1.37, 3.62) 0.001 Thermus 2.13 (1.22, 3.70) 0.008 Mycolicibacterium 1.99 (1.29, 3.07) 0.002 Mycobacterium 1.95 (1.23, 3.08) 0.005 Lactobacillus 1.94 (1.17, 3.22) 0.01 Citation Format: Miseker Abate, Harrison Drebin, Shoji Shimada, Santosh Vardhana, Smita Sihag, Vivian E. Strong, Chad Vanderbilt. Distinct differences in microbial enrichment and diversity identified between gastric and gastroesophageal junction adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5890.
Identification of locally advanced gastric cancer (GC) patients who might potentially benefit from immune-based strategies is limited by both the poor predictive quality of existing biomarkers, including molecular subtypes, tumor mutational burden, and PD-L1 expression, as well as inadequate understanding of the gastric cancer immune microenvironment. Here, we leveraged high-dimensional spectral cytometry to re-classify locally advanced gastric tumors based on immune composition. The gastric cancer microenvironment was comprised of a diverse immune infiltrate including high proportions of plasmablasts, macrophages, and myeloid-derived suppressor cells. Computational cell typing and sample clustering based on tiered broad immune and T-cell focused phenotyping identified three distinct immune subtypes. The most immunogenic subtype exhibited high proportions of activated CD4+ T-cells and plasmablasts and included tumors that would have been classified as non-immunogenic based on prior classifications. Analysis of gastric cancer patients treated with immune checkpoint blockade indicates that patients who responded to immunotherapy had a pre-treatment tumor composition that corresponded to higher immune scores from our analysis. This work establishes a novel immunological classification of gastric cancer including identification of patients and immune networks likely to benefit from immune-based therapies.
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