Current and new frontiers in hereditary cancer surveillance: Opportunities for liquid biopsy
Bibliographic record
Abstract
At least 5% of cancer diagnoses are attributed to a causal pathogenic or likely pathogenic germline genetic variant (hereditary cancer syndrome-HCS). These individuals are burdened with lifelong surveillance monitoring organs for a wide spectrum of cancers. This is associated with substantial uncertainty and anxiety in the time between screening tests and while the individuals are awaiting results. Cell-free DNA (cfDNA) sequencing has recently shown potential as a non-invasive strategy for monitoring cancer. There is an opportunity for high-yield cancer early detection in HCS. To assess clinical validity of cfDNA in individuals with HCS, representatives from eight genetics centers from across Canada founded the CHARM (cfDNA in Hereditary and High-Risk Malignancies) Consortium in 2017. In this perspective, we discuss operationalization of this consortium and early data emerging from the most common and well-characterized HCSs: hereditary breast and ovarian cancer, Lynch syndrome, Li-Fraumeni syndrome, and Neurofibromatosis type 1. We identify opportunities for the incorporation of cfDNA sequencing into surveillance protocols; these opportunities are backed by examples of earlier cancer detection efficacy in HCSs from the CHARM Consortium. We seek to establish a paradigm shift in early cancer surveillance in individuals with HCSs, away from highly centralized, regimented medical screening visits and toward more accessible, frequent, and proactive care for these high-risk individuals.
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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".