Redefinition of familial intestinal gastric cancer: clinical and genetic perspectives
Bibliographic record
Abstract
Background Familial intestinal gastric cancer (FIGC) remains genetically unexplained and without testing/clinical criteria. Herein, we characterised the age of onset and disease spectrum of 50 FIGC families and searched for genetic causes potentially underlying a monogenic or an oligogenic/polygenic inheritance pattern. Methods Normal and tumour DNA from 50 FIGC probands were sequenced using Illumina custom panels on MiSeq, and their respective germline and somatic landscapes were compared with corresponding landscapes from sporadic intestinal gastric cancer (SIGC) and hereditary diffuse gastric cancer cohorts. Results The most prevalent phenotype in FIGC families was gastric cancer, detected in 138 of 208 patients (50 intestinal gastric cancer probands and 88 unknown gastric cancer histology relatives), followed by colorectal and breast cancers. After excluding benign and intronic variants lacking impact in splicing, 12 rare high-quality variants were found exclusively in 11 FIGC probands. Only two probands carried potentially deleterious variants, but lacked somatic second-hits, weakly supporting the monogenic hypothesis for FIGC. However, FIGC probands developed gastric cancer at least 10 years earlier and carried more TP53 germline common variants than SIGC (p=4.5E-03); FIGC and SIGC could be distinguished by specific germline and somatic variant profiles; there was an excess of FIGC tumours presenting microsatellite instability (38%); and FIGC tumours displayed significantly more somatic common variants than SIGC tumours (p=4.2E-06). Conclusion This study proposed the first data-driven testing criteria for FIGC families, and supported FIGC as a genetically determined, likely polygenic, gastric cancer-predisposing disease, with earlier onset and distinct from patients with SIGC at the germline and somatic levels.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".