Biology subjects

So, J. B.-Y.

Publications and source records attributed to So, J. B.-Y..

3 recordsLinked to original sources

bioRxiv2026

TIM3+ Tumor Associated M2 Macrophages Impair Antitumor T Cell Immunity and Promote Gastric Cancer Progression and Peritoneal Metastasis

Peritoneal metastases (PM) are the leading cause of cancer-related death in gastric cancer (GC) patients with survival typically < 9 months. Here, we demonstrate that TIM3 and its ligands are increased along the GC continuum and associated with poor survival. Integrated omics analyses and functional studies revealed highly enriched TIM3 in CD163+ tumor associated M2 immunosuppressive macrophages significantly promote tumor cell invasion and tumor growth in vivo, while TIM3 depletion in macrophages reduced tumor cell malignant attributes and increased T cell immunity from PBMCs or CD45+ immune cells of malignant ascites in co-culture system. By cytokine and kinase arrays, we discovered that depletion of TIM3 in macrophages reduced the production of notable secretome of cytokines/chemokines from M2 macrophages; and the protumor function of TIM3+ macrophages rely on the p90RSK1/2/CCL20 axis. Finally, we reveal that TIM3 blockage or genetic KO had superior antitumor activity in combination with anti-PD1 immunotherapy and mitomycin C (MMC) chemotherapy. Together, this study uncovers an important role for TIM3 in tumor associated M2 macrophages and underscores the potential of TIM3 blockage in GC patients with PM. Statement of significanceIn this study, we show TIM3 increases along GC continuum, and highly enriched on tumor associated M2 macrophages that fuel tumor growth; and suppress T cell function via p90RSK1/2/CCL20 axis. TIM3 depletion restores T-cell immunity and curbs tumor growth. TIM3 blockade combined with anti-PD1 and mitomycin C provide a novel therapeutic strategy for GC patients with PM.

immunology↗

bioRxiv2025

Single-Cell Pharmacogenomic Landscapes of Epigenetic Therapy in Gastric Cancer

Gene expression signatures ("molecular phenotypes") are extensively utilized in cancer research. To study how gastric cancer (GC) molecular phenotypes are shaped by cell-intrinsic genetic alterations interacting with cell-extrinsic therapeutic pressures, we performed direct capture Perturb-seq (dcPerturb-seq) to interrogate >200 GC-related genes across 4 distinct epigenetic drug classes in multiple gastric lines. We captured 17.7 million pharmocogenomic expression interactions in 625,866 cells representing baseline and post-therapeutic molecular phenotypes. This single-cell pharmacogenomic compendium confirmed previously known gene-driven molecular phenotypes, elucidated poorly characterized genes, and uncovered novel gene dosage-molecular phenotype relationships. Molecular phenotypes in post-therapeutic surviving cells revealed diverse gene perturbation-associated pathways causing convergent drug resistance (EMT plasticity, cell cycle alterations, metabolic reprogramming), highlighting combinatorial strategies for restoring sensitivity. Mapping of in vitro molecular phenotypes to primary human GCs imparted prognostic information and insights into spatial heterogeneity. Comparative analysis of gene perturbations across therapies and lines revealed both conserved and context-specific molecular alterations. Our results illustrate how Perturb-seq approaches can systematically map diverse cancer-associated molecular phenotypes across multiple gene/drug/cell line interactions, yielding translational insights.

cancer biology↗

bioRxiv2020

"3G" Trial: An RNA Editing Signature for Guiding Gastric Cancer Chemotherapy

Background & AimsGastric cancer (GC) cases are often diagnosed at an advanced stage with poor prognosis. Platinum-based chemotherapy has been internationally accepted as first-line therapy for inoperable or metastatic GC. To achieve greater benefits, it is critical to select patients who are eligible for the treatment. Albeit gene expression profiling has been widely used as a genomic classifier to identify molecular subtypes of GC and stratify patients for different chemotherapy regimens, the prediction accuracy remains to be improved. More recently, adenosine-to-inosine (A-to-I) RNA editing has emerged as a new player contributing to GC development and progression, offering potential clinical utility for diagnosis and treatment. MethodsWe conducted a transcriptome-wide RNA editing analysis of a cohort of 104 patients with advanced GC and identified an RNA editing (GCRE) signature to guide GC chemotherapy, using a systematic computational approach followed by both in vitro validations and in silico validations in TCGA. ResultsWe found that RNA editing events alone stand as a prognostic and predictive biomarker in advanced GC. We developed a GCRE score based on the GCRE signature consisting of 50 editing sites associated with 29 genes and achieved a high accuracy (84%) of predicting patient response to chemotherapy. Of note, patients demonstrating higher editing levels of this panel of sites present a better overall response. Consistently, GC cell lines with higher editing levels showed higher chemosensitivity. Applying the GCRE score on TCGA dataset confirmed that responders had significantly higher levels of editing in advanced GC. ConclusionsOverall, the GCRE signature reliably stratifies patients with advanced GC and predicts response from chemotherapy. SignificanceDespite the increasing documentation of RNA editing and its functional regulation, the translational potential of RNA editome in cancer remains largely under-investigated. This study reports for the first time an RNA editing signature in advanced GC, to reliably stratify patients with advanced disease to predict response from chemotherapy independently of gene expression profiling and other genomic and epigenetic changes. For this purpose, a bioinformatics approach was used to develop a GCRE score based on a panel of 50 editing sites from 29 unique genes (GCRE signature), followed by an experimental evaluation of their clinical utility as predictive biomarker in GC cell lines and in silico validation in using RNA sequencing (RNA-Seq) datasets from TCGA. The applied methodology provides a robust means of an RNA editing signature to be investigated in patients with advanced GC. Overall, this study provides insights into the translation of RNA editing process into predictive clinical applications to direct chemotherapy against GC.

cancer biology↗