Building a hereditary cancer program in Colombia: analysis of germline pathogenic and likely pathogenic variants spectrum in a high-risk cohort
Bibliographic record
Abstract
Genetic studies in Latin America have expanded, but further efforts are needed to understand cancer susceptibility genes beyond BRCA1 and BRCA2, especially by characterizing the prevalence and spectrum of pathogenic or likely pathogenic variants (PVs) in the region. This study aimed to determine the frequency of hereditary cancer syndromes (HCS) in Colombians with solid tumors and to characterize the spectrum of PVs. Using data from the Colombia's largest Institutional Hereditary Cancer Program, we included patients aged ≥18 years with solid tumors who met HCS criteria and were offered genetic testing with a 105-cancer gene panel. We calculated the prevalence of PVs and HCS by cancer type (beyond breast) and gene. For patients with breast cancer, we examined genotype-phenotype correlations with molecular subtypes and stratified positivity rates by different genetic testing criteria. Among 769 patients, we identified 216 PVs in 43 genes in 197 patients (26%). Thirty-three PVs were recurrent. Autosomal HCS was found in 21% (160/769) of patients (159 dominant, one recessive), while 5% (37/769) were heterozygous carriers of PVs in autosomal recessive genes. In 42% (321/769) of the cases, only one or more variants of uncertain significance (VUS) were identified, whereas 33% (251/769) had neither PVs nor VUS detected (negative results). HCS prevalence varied by cancer type (11-26%). The triple-negative subtype and bilateral presentation were strong predictors of inherited breast cancer. Our study reveals a significant presence of PVs among high-risk Colombian patients with solid tumors, underscoring the importance of genetic counseling and testing in the region.
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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 | 0.001 | 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 | 0.000 | 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".