Comprehensive characterization of pseudomyxoma peritonei.
Bibliographic record
Abstract
e15701 Background: Pseudomyxoma peritonei (PMP) is a rare malignant tumor characterized by the infiltration of the peritoneum by mucus-secreting tumor cells. The genetic landscape of these tumors and correlation with clinico-pathological tumor features is unclear to date. Methods: We performed whole-exome sequencing (WES) on 8 PMPs and matched normal. We then validated our finding using ultra-deep sequencing of hotspot mutations (~82.270 x) in 45 clinically annotated samples. In addition, bulk RNAseq was performed on 10 samples and MCP-counter was used to infer absolute abundance of eight immune and two stromal cell populations. Results: Overall, 323 somatic mutations were identified through WES with most frequent mutations involving GNAS (R186H) (50%), KRAS (G12D) (50%), AHNAK2 (25%) and ATXN1 (25%). Furthermore, ultra-deep sequencing uncovered KRAS, GNAS and IDH1/2 hotspots mutations in 16 (35.5%), 11 (24.4%) and 2 (4.4%) PMPs, respectively. Strikingly, KRAS mutations were enriched in females (79% vs 39%, p = 0.03) while GNAS in males (67% vs 28%, p = 0.04). No other significant associations were identified between mutations and other clinico-pathological features. Using MCP-counter, fibroblasts, endothelial cells and moncoytic cells were the most frequent inferred cells. Unsupervised clustering using expression of most variable cells identified two PMP clusters, namely C1 (n = 4) and C2 (n = 6). C2 cluster displayed higher T cells as compared to C1 (p < 0.0001), consistent with increased cytotoxic lymphocytes (p = 0.04). Notably, C2 was enriched for tumors with higher grade as compared to C1 (80% vs 0%; p = 0.04). Conclusions: Our study represents the largest study to data exploring genetic and immune alterations in PMPs. We uncovered puzzling associations between genetic landscape of PMPs and patients gender, which deserve further validation in an independent cohort. The association of high-grade tumors with increased tumor infiltrating lymphocytes suggests the existence of an immunogenic microenvironment; PD-1/PD-L1 blockade might represent a therapeutic option for these patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".