A clinical case of multiple primary cancers in a carrier of rare SDK2 and NOTCH2 gene mutations
Bibliographic record
Abstract
Abstract Background Genetic predisposition is one of the risk factors for the development of multiple primary cancers (MPCs), the frequency of which increases and ranges from 2 to 17%. This study describes a combination of rare mutations, rs746551843 in the NOTCH2 gene and rs144933006 in the SDK2 gene, in a woman with breast cancer and leiomyosarcoma without a clearly burdened family history. Case presentation A 55-year-old Caucasian woman received complex treatment on the basis of the National Medical Research Centre for Oncology for left breast cancer and leiomyosarcoma of soft tissues of the left thigh. The patient was referred for consultation with a geneticist. Among direct relatives, a maternal aunt with a history of kidney cancer was not a carrier of the studied single nucleotide polymorphisms (SNPs). The healthy son of the patient inherited both mutations. Conclusion Thus, perhaps in the described case, there is a synergistic effect of two alleles of moderate and low penetrance, which led to the phenotype of multiple primary cancers.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".