Germline Variants in Targeted Tumor Sequencing Using Matched Normal DNA
Bibliographic record
Abstract
IMPORTANCE: Tumor genetic sequencing identifies potentially targetable genetic alterations with therapeutic implications. Analysis has concentrated on detecting tumor-specific variants, but recognition of germline variants may prove valuable as well. OBJECTIVE: To estimate the burden of germline variants identified through routine clinical tumor sequencing. DESIGN, SETTING, AND PARTICIPANTS: Patients with advanced cancer diagnoses eligible for studies of targeted agents at Memorial Sloan Kettering Cancer Center are offered tumor-normal sequencing with MSK-IMPACT, a 341-gene panel. We surveyed the germline variants seen in 187 overlapping genes with Mendelian disease associations in 1566 patients who had undergone tumor profiling between March and October 2014. MAIN OUTCOMES AND MEASURES: The number of presumed pathogenic germline variants (PPGVs) and variants of uncertain significance per person in 187 genes associated with single-gene disorders and the proportions of individuals with PPGVs in clinically relevant gene subsets, in genes consistent with known tumor phenotypes, and in genes with evidence of second somatic hits in their tumors. RESULTS: The mean age of the 1566 patients was 58 years, and 54% were women. Presumed pathogenic germline variants in known Mendelian disease-associated genes were identified in 246 of 1566 patients (15.7%; 95% CI, 14.0%-17.6%), including 198 individuals with mutations in genes associated with cancer susceptibility. Germline findings in cancer susceptibility genes were concordant with the individual's cancer type in only 81 of 198 cases (40.9%; 95% CI, 34.3%-47.9%). In individuals with PPGVs retained in the tumor, somatic alteration of the other allele was seen in 39 of 182 cases (21.4%; 95% CI, 16.1%-28.0%), of which 13 cases did not show a known correlation of the germline mutation and a known syndrome. Mutations in non-cancer-related Mendelian disease genes were seen in 55 of 1566 cases (3.5%; 95% CI, 27.1%-45.4%). Almost every individual had more than 1 variant of uncertain significance (1565 of 1566 patients; 99.9%; 95% CI, 99.6%-99.9%). CONCLUSIONS AND RELEVANCE: Germline variants are common in individuals undergoing tumor-normal sequencing and may reveal otherwise unsuspected syndromic associations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.008 |
| 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) | 0.002 | 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 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".