Three biomarkers (HER2, PD-L1, and microsatellite status) in a large cohort of metastatic gastroesophageal adenocarcinomas: The MD Anderson Cancer Center experience.

Human epidermal growth factor receptor-2 (HER2), programmed death-ligand 1 (PD-L1), and microsatellite (MS) status are well-established biomarkers in gastroesophageal adenocarcinomas (GEAs). However, it is unclear how the combination of these biomarkers is associated with clinicopathological factors and prognosis. This retrospective study included baseline metastatic GEA patients who were tested for all three biomarkers (HER2, PD-L1, and MS status) at the MD Anderson Cancer Center between 2012 and 2022. Stratification was performed according to the combination of biomarker profiles: triple negative (TN), single positive (SP), and multiple positive (MP). Comparative analyses of clinicopathological factors and survival using combinations of biomarkers were performed. Among the 698 GEA patients analyzed, 251 (36.0%) were classified as TN, 334 (47.9%) as SP, and 113 (16.1%) as MP. The MP group showed a significant association with tumors located in the esophagus (p < .001), well to moderate differentiation (p < .001), and the absence of signet ring cells (p < .001). In the survival analysis, MP group had a significantly longer overall survival (OS) compared to the other groups (MP vs. TN, p < .001 and MP vs. SP, p < .001). Multivariate Cox regression analysis revealed that MP serves as an independent positive prognostic indicator for OS (hazard ratio = 0.63, p < .01). Our findings indicate that MP biomarkers are associated with a favorable prognosis in metastatic GEA. These results are reflective of clinical practice and offer valuable insights into how therapeutics and future biomarkers could influence therapy/prognosis.

E-cadherin loss drives diffuse-type gastric tumorigenesis via EZH2-mediated reprogramming.

Diffuse-type gastric adenocarcinoma (DGAC) is a deadly cancer often diagnosed late and resistant to treatment. While hereditary DGAC is linked to CDH1 mutations, the role of CDH1/E-cadherin inactivation in sporadic DGAC tumorigenesis remains elusive. We discovered CDH1 inactivation in a subset of DGAC patient tumors. Analyzing single-cell transcriptomes in malignant ascites, we identified two DGAC subtypes: DGAC1 (CDH1 loss) and DGAC2 (lacking immune response). DGAC1 displayed distinct molecular signatures, activated DGAC-related pathways, and an abundance of exhausted T cells in ascites. Genetically engineered murine gastric organoids showed that Cdh1 knock-out (KO), KrasG12D, Trp53 KO (EKP) accelerates tumorigenesis with immune evasion compared with KrasG12D, Trp53 KO (KP). We also identified EZH2 as a key mediator promoting CDH1 loss-associated DGAC tumorigenesis. These findings highlight DGAC's molecular diversity and potential for personalized treatment in CDH1-inactivated patients.

CDH1 loss promotes diffuse-type gastric cancer tumorigenesis via epigenetic reprogramming and immune evasion.

Diffuse-type gastric adenocarcinoma (DGAC) is a deadly cancer often diagnosed late and resistant to treatment. While hereditary DGAC is linked to CDH1 gene mutations, causing E-Cadherin loss, its role in sporadic DGAC is unclear. We discovered CDH1 inactivation in a subset of DGAC patient tumors. Analyzing single-cell transcriptomes in malignant ascites, we identified two DGAC subtypes: DGAC1 (CDH1 loss) and DGAC2 (lacking immune response). DGAC1 displayed distinct molecular signatures, activated DGAC-related pathways, and an abundance of exhausted T cells in ascites. Genetically engineered murine gastric organoids showed that Cdh1 knock-out (KO), KrasG12D, Trp53 KO (EKP) accelerates tumorigenesis with immune evasion compared to KrasG12D, Trp53 KO (KP). We also identified EZH2 as a key mediator promoting CDH1 loss-associated DGAC tumorigenesis. These findings highlight DGAC's molecular diversity and potential for personalized treatment in CDH1-inactivated patients.

Pan-cancer T cell atlas links a cellular stress response state to immunotherapy resistance.

Tumor-infiltrating T cells offer a promising avenue for cancer treatment, yet their states remain to be fully characterized. Here we present a single-cell atlas of T cells from 308,048 transcriptomes across 16 cancer types, uncovering previously undescribed T cell states and heterogeneous subpopulations of follicular helper, regulatory and proliferative T cells. We identified a unique stress response state, TSTR, characterized by heat shock gene expression. TSTR cells are detectable in situ in the tumor microenvironment across various cancer types, mostly within lymphocyte aggregates or potential tertiary lymphoid structures in tumor beds or surrounding tumor edges. T cell states/compositions correlated with genomic, pathological and clinical features in 375 patients from 23 cohorts, including 171 patients who received immune checkpoint blockade therapy. We also found significantly upregulated heat shock gene expression in intratumoral CD4/CD8+ cells following immune checkpoint blockade treatment, particularly in nonresponsive tumors, suggesting a potential role of TSTR cells in immunotherapy resistance. Our well-annotated T cell reference maps, web portal and automatic alignment/annotation tool could provide valuable resources for T cell therapy optimization and biomarker discovery.

A total transcriptome profiling method for plasma-derived extracellular vesicles: applications for liquid biopsies.

Extracellular vesicles (EVs) are key mediators of intercellular communication. Part of their biological effects can be attributed to the transfer of cargos of diverse types of RNAs, which are promising diagnostic and prognostic biomarkers. EVs found in human biofluids are a valuable source for the development of minimally invasive assays. However, the total transcriptional landscape of EVs is still largely unknown. Here we develop a new method for total transcriptome profiling of plasma-derived EVs by next generation sequencing (NGS) from limited quantities of patient-derived clinical samples, which enables the unbiased characterization of the complete RNA cargo, including both small- and long-RNAs, in a single library preparation step. This approach was applied to RNA extracted from EVs isolated by ultracentrifugation from the plasma of five healthy volunteers. Among the most abundant RNAs identified we found small RNAs such as tRNAs, miRNAs and miscellaneous RNAs, which have largely unknown functions. We also identified protein-coding and long noncoding transcripts, as well as circular RNA species that were also experimentally validated. This method enables, for the first time, the full spectrum of transcriptome data to be obtained from minute patient-derived samples, and will therefore potentially allow the identification of cell-to-cell communication mechanisms and biomarkers.