Comparative Genomic and Microenvironmental Profiles of Hereditary and Sporadic TNBC in Colombian Women
Bibliographic record
Abstract
Breast cancer (BC) is a heterogeneous disease, and triple-negative breast cancer (TNBC) is the most aggressive and immunogenic subtype. A significant proportion of TNBC cases are linked to hereditary cancer syndromes involving pathogenic germline variants, most commonly in BRCA1/2. However, few studies have compared hereditary and sporadic TNBC in admixed populations. In this study, molecular and immunological features were analyzed through the analysis of 62 Colombian TNBC samples (20 hereditary and 42 sporadic cases) by RNA sequencing to identify molecular and immune differences. We used an external validation cohort of 16 TCGA TNBC cases (8 BRCA-mutated and 8 non-mutated) to replicate our findings. Results: We found a set of 921 differentially expressed genes (DEGs) between hereditary and sporadic TNBC. Hereditary tumors were enriched for pathways related to extracellular matrix (ECM) remodeling, structural components, and DNA damage response and exhibited a more immunologically active tumor microenvironment compared to sporadic tumors. LASSO logistic regression identified 23 genes with discriminatory potential, showing that hereditary tumors are characterized by complex immune regulation, inflammatory processes, and activation of key oncogenic pathways. Conclusions: Hereditary TNBC is characterized by molecular and biological functions linked to ECM remodeling and its constituents and an active immune microenvironment. This integrated molecular–immune profile provides insight into the distinct biology of hereditary tumors in admixed populations.
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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) | 0.000 | 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".