Germline mutations of the <i>E-cadherin(CDH1)</i> and <i>TP53</i> genes, rather than of <i>RUNX3</i> and <i>HPP1</i>, contribute to genetic predisposition in German gastric cancer patients
Bibliographic record
Abstract
Germline mutations of the cell adhesion molecule E-cadherin have been shown for the first time to underlie a hereditary diffuse type gastric cancer syndrome (HDGC) in Maori families,1 and subsequently have been reported in HDGC patients of various ethnic origins.2–9 Gastric cancer may also be associated with other hereditary tumour syndromes, which are mainly characterised by carcinomas of other organs. One of these syndromes is the HNPCC syndrome (hereditary nonpolyposis colorectal cancer syndrome), which is caused by germline mutations in DNA mismatch repair genes.10 Furthermore, gastric cancer has been observed in the context of the Li Fraumeni syndrome, a rare cancer syndrome due to germline mutations of the TP53 tumour suppressor gene,11–14 as well as in association with the FAP and Peutz–Jeghers syndrome.15 Despite known molecular genetic causes, contributing to a genetic predisposition to gastric cancer, a considerable number of familial cases have been reported that were not attributable to one of this hereditary syndromes, suggesting that unknown susceptibility genes for gastric cancer might exist. Putative tumour suppressor genes that are commonly inactivated in sporadic gastric cancers, such as the RUNX3 or HPP1 genes, are potential candidate susceptibility genes.16,17 In a previous study, we identified one E-cadherin germline mutation among seven diffuse type familial gastric cancer patients, indicating that in addition to E-cadherin , other genes might be involved in genetic predisposition to the disease in this patient group.4 There were three goals of the present study. First, we aimed to extend our analysis of E-cadherin germline mutations to a higher number of patients, to evaluate the contribution of germline mutations in this gene to German familial and early onset gastric cancer patients and to characterise identified missense mutations for their functional relevance. Secondly, we wished to analyse the role …
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".