RESPONSE: Re: Population-Based Study of BRCA1 and BRCA2 Mutations in 1035 Unselected Finnish Breast Cancer Patients
Bibliographic record
Abstract
In our recent survey of BRCA1 and BRCA2 mutations in 1035 unselected Finnish breast cancer patients (1), 15 of the 19 mutation carriers identified belonged to a group defined by three simple criteria (i.e., family history of ovarian cancer, index case patient diagnosed with breast cancer at ≤40 years, or two or more relatives diagnosed with breast cancer). However, better predictive factors for germline mutations are required. Here, we evaluate the possibility raised by Chappuis et al. that immunohistologic features of the tumor tissues could help in identifying patients for mutation testing. Of the 1035 patients (1036 tumors), the histologic type was available in 998 (96.3%) tumors, the World Health Organization histologic grade (of 741 ductal carcinomas) was available in 706 (95.3%) tumors, the estrogen receptor (ER) status was available in 937 (90.5%) tumors, and the progesterone receptor (PR) status was available in 935 (90.3%) tumors. Table 1 compares the distribution of these four parameters in tumors from BRCA1 mutation carriers (“BRCA1”) and BRCA2 mutation carriers (“BRCA2”) and in noncarriers (“control”). All four BRCA1 tumors were invasive ductal carcinomas. Three of these were poorly differentiated, two were ER negative, and one was PR negative. High grade and lack of ER have been shown to be typical of tumors from BRCA1-linked breast cancer families (2,3). Medullary histology has also been found to be overrepresented among BRCA1 tumors (2). However, most BRCA1 tumors are of ductal histology (2). BRCA2 tumors had a similar distribution of histologic subtypes as the controls. An association between BRCA2 status and tumor grade was observed, attributable to the absence of grade 1 tumors in the BRCA2 carriers. Loss of PR tended to be more common in the BRCA2 tumors than in the controls. ER positivity among the BRCA2 tumors was similar to that among the controls. We also determined the frequency of ER-positive lobular carcinomas among BRCA2 carriers, as suggested by Chappuis et al. Two such tumors (15.4%) were found among 13 BRCA2 tumors, a prevalence similar to that of control cancers (130 [14.4%] of 903 controls). In our study, the cases came from a prospective mutation screening among unselected, newly diagnosed breast cancers, providing an unbiased, population-based tumor material. Our study was based on histology reports obtained in the context of clinical pathologic diagnosis, which reflects the kind of information available to a physician who needs to decide whether germline BRCA1 and BRCA2 mutation testing is appropriate for a particular patient. In retrospective reviews by expert pathologists, specific histologic features have been linked with BRCA1 and BRCA2 tumors (4). If such features were to be used in defining putative mutation carriers, they should be routinely included in pathology reports, and the reproducibility of defining such features should be assessed. Although differences in histologic and biologic features exist between BRCA1 tumors and to some extent between BRCA2 tumors and sporadic tumors (2–5), it remains to be determined whether such differences translate to better criteria for defining putative mutation carriers. Because of the interrelationships of the predictive features, large studies are required to test their independent value in the context of germline mutation screening. We expect that improved immunohistologic or molecular classifiers for both BRCA1 and BRCA2 tumors will arise from surveys of genetic alterations (6) and global gene expression changes (7) in hereditary breast cancers. Association of germline genotype of breast cancer patients with histologic and biologic features of the tumor tissues* We thank Dr. Päivi Heikkilä for critical reading of the manuscript.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.008 | 0.002 |
| Insufficient payload (model declined to judge) | 0.027 | 0.016 |
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".