Reply to Evans and Woodward
Bibliographic record
Abstract
We thank Drs Evans and Woodward for their correspondence (1) in which the following points related to our publication entitled “Heterozygous BRCA1 and BRCA2 and mismatch repair gene pathogenic variants in children and adolescents with cancer” are raised. Point 1: The frequency of pathogenic and/or likely pathogenic variants (PVs) in the German control group is lower than the frequency observed in published series. We agree with this point, and for this reason, we included an analysis of a cancer-free Genome Aggregation Database (gnomAD) control group. The enrichment of PVs in BRCA1 and 2 and mismatch repair (MMR) genes was reproduced—with borderline statistical significance for PVs in BRCA1 and 2 combined—when we used the gnomAD control group. Similar results were reproduced in a supplementary analysis including 17 studies. In addition, analysis of a validation patient cohort confirmed an enrichment of PVs in BRCA2 and MSH2—but not in PMS2—compared with a gnomAD control group. Notably, there are other independent recent publications (2-5) including one study focusing on the somatic mutation landscape (2) supporting the association between Lynch syndrome and childhood cancer. Other recent papers have demonstrated an enrichment of PVs in BRCA2 in children with cancer (6,7). Together, these studies suggest that these syndromes have a low penetrant pediatric spectrum. Point 2: Variants may have been missed (eg, in PMS2), and copy number variants were not included. Different sequencing pipelines and differences in pathogenicity assessment can confound burden testing. Therefore, we restricted our meta-analysis that included studies employing different pipelines to ClinVar PVs. This led to the intentional exclusion of copy number variants not included in ClinVar; however, this factor affects both cases and controls. We agree that difficulties in detecting variants are likely to influence the reported PV frequencies of our study, however, this factor affects both cases and controls. Future studies should analyze cases and controls employing the same pipeline and pathogenicity assessment strategy and should include copy number variants. Point 3: Biallelic gene variants were not ruled out. This point cannot be addressed because of the retrospective nature of our study. Based on our results, we now recommend functional assays (eg, chromosomal breakage test) to rule out Fanconi anemia in children with cancer who are found to have a heterozygous PV in BRCA1, BRCA2, or PALB2. It is possible that a second germline PV on the other allele is missed when sequencing is employed alone. We recommend a similar procedure in children with cancer who are found to harbor a heterozygous germline PV in a MMR gene to rule out constitutional MMR deficiency because of biallelic PVs in one of the MMR genes. Despite these limitations, our data provide evidence supporting the hypothesis that heterozygous PVs in BRCA and MMR genes (with the strongest signal observed for MSH2) are associated with pediatric cancer with a low penetrance not necessitating changes to current predictive testing recommendations. Prospective studies are needed to independently confirm these findings and to define the pediatric cancer spectra, tumor risks, and somatic mutation landscapes associated with PVs in these genes. CPK and SMP have been supported by the Deutsche Kinderkrebsstiftung (DKS2019.13) and Federal Ministry of Education and Research (BMBF) ADDRess (01GM1909A and 01GM1909E). RA is supported by the Everest Centre for Low-Grade Paediatric Brain Tumours (the Brain Tumour Charity, UK; GN-000382). SMW is supported by the Research Council of Norway (187615), the South-Eastern Norway Regional Health Authority, and the University of Oslo. TR has been supported by BMBF MyPred (01GM1911B). DM is supported by grants from the Canadian Institutes for Health Research (FDN-143234) and the Terry Fox Research Institute (TFRI #1081). DS and HP have been supported by BMBF (01GM1906B). Role of the funder: The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Author disclosures: None exist. Author contributions: Conceptualization: CPK; Writing—review & editing: all authors. No new data were generated or analyzed for this response.
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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 | 0.005 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.095 | 0.070 |
| Insufficient payload (model declined to judge) | 0.009 | 0.008 |
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".