Divergent lineage trajectories and genetic landscapes in human gastric intestinal metaplasia organoids associated with early neoplastic progression
Bibliographic record
Abstract
ABSTRACT Objective Gastric intestinal metaplasia (IM) is a pre-cancerous stage spanning a morphological spectrum that is poorly represented by human cell line models. We aim to establish and characterize human IM cell models to better understand IM progression along the cancer spectrum. Design A large human gastric IM organoid (IMO) cohort (n=28) was established, along with normal gastric organoids (n=42) for comparison, and comprehensive multi-omics profiling and functional characterization were performed. Results Single-cell transcriptomes revealed IMO cells spanning a spectrum from hybrid gastric/intestinal to advanced intestinal differentiation, and unveiled lineage trajectories that connected different cycling and quiescent stem and progenitors, highlighting their differences in gastric to IM transition. The hybrid IMO cells showed impaired differentiation potential, high lineage plasticity beyond gastric or intestinal fates, and reactivation of a fetal gene program. Cell populations in gastric IM and cancer tissues were found to be highly similar to those derived from IMOs and exhibited fetal signature. Genomically, IMOs showed an elevated mutation burden, frequent chromosome 20 gain, and epigenetic de-regulation of many intestinal and gastric genes. Functionally, IMOs downregulated FGFR2 and became independent of FGF10 for survival. Several IMOs exhibited a cell-matrix adhesion independent (CMi) subpopulation that displayed chromosome 20 gain but lacked key cancer driver mutations, which could represent the earliest neoplastic precursor of IM-induced gastric cancer. Conclusions Overall, our IM organoid biobank captured the heterogeneous nature of IM, revealing mechanistic insights on IM pathogenesis and its neoplastic progression, offering an ideal platform for studying early gastric neoplastic transformation and chemoprevention.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".