Usage Information
Abstract
Based on the observation that loss-of-function mutations of KMT2C and KMT2D (KMT2C/D) are enriched and co-occur in gastric adenocarcinoma, we developed genetically engineered mouse model (GEMM) to conditionally knock out Kmt2c and Kmt2d in gastric epithelial cells. We observed that Kmt2c/d loss led to nuclear dysplasia, cellular crowding, and expansion of cells with mixed gastric lineage markers. When combined with Pten deletion, Kmt2c/d loss drove rapid development of muscle-invasive gastric adenocarcinoma as early as 3 weeks post Cre-mediated gene deletion. The adenocarcinoma exhibited decreased expression of gastric lineage markers and increased expression of intestinal differentiation markers, phenocopying human intestinal type gastric adenocarcinoma. Bioinformatic integration of single cell RNA-seq of our GEMMs and human gastric cancer datasets shows co-clustering of normal and of cancerous gastric epithelial cells. Kmt2c/d knockout in gastric epithelium reduced protein synthesis but upregulated transcription of ribosomal proteins, rendering the cells to be hypersensitive to mTORC1 inhibitors. Additionally, Kmt2c/d knockout increased MHC-I molecule expression and enhanced antigen presentation. Combination of mTORC1 inhibition and anti-PD1 immunotherapy markedly suppressed tumor growth in immune-competent mice. Together, these findings reveal the role of Kmt2c/d loss in gastric cancer initiation and suggest the potential therapeutic strategies for KMT2C/D-deficient gastric cancer.
Authors
Naitao Wang, Dan Li, Tao Zhang, Mohini R. Pachai, Dana M. Schoeps, Yudi Bao, Woo Hyun Cho, Makhzuna N. Khudoynazarova, Kae Kristoff, Marion Liu, Laura Tang, Yelena Y. Janjigian, Ping Chi, Yu Chen
Usage data is cumulative from May 2026 through June 2026.
| Usage | JCI | PMC |
|---|---|---|
| Text version | 746 | 0 |
| 395 | 0 | |
| Supplemental data | 214 | 0 |
| Citation downloads | 58 | 0 |
| Totals | 1,413 | 0 |
| Total Views | 1,413 | |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.
Copyright © 2026 American Society for Clinical Investigation
ISSN: 0021-9738 (print), 1558-8238 (online)