Data from Lynch Syndrome–Associated Breast Cancers: Clinicopathologic Characteristics of a Case Series from the Colon Cancer Family Registry
Bibliographic record
Abstract
Abstract Purpose: The recognition of breast cancer as a spectrum tumor in Lynch syndrome remains controversial. The aim of this study was to explore features of breast cancers arising in Lynch syndrome families. Experimental Design: This observational study involved 107 cases of breast cancer identified from the Colorectal Cancer Family Registry (Colon CFR) from 90 families in which (a) both breast and colon cancer co-occurred, (b) families met either modified Amsterdam criteria, or had at least one early-onset (<50 years) colorectal cancer, and (c) breast tissue was available within the biospecimen repository for mismatch repair (MMR) testing. Eligibility criteria for enrollment in the Colon CFR are available online. Breast cancers were reviewed by one pathologist. Tumor sections were stained for MLH1, PMS2, MSH2, and MSH6, and underwent microsatellite instability testing. Results: Breast cancer arose in 35 mutation carriers, and of these, 18 (51%) showed immunohistochemical absence of MMR protein corresponding to the MMR gene mutation segregating the family. MMR-deficient breast cancers were more likely to be poorly differentiated (P = 0.005) with a high mitotic index (P = 0.002), steroid hormone receptor–negative (estrogen receptor, P = 0.031; progesterone receptor, P = 0.022), and to have peritumoral lymphocytes (P = 0.015), confluent necrosis (P = 0.002), and growth in solid sheets (P < 0.001) similar to their colorectal counterparts. No difference in age of onset was noted between the MMR-deficient and MMR-intact groups. Conclusions: MMR deficiency was identified in 51% of breast cancers arising in known mutation carriers. Breast cancer therefore may represent a valid tissue option for the detection of MMR deficiency in which spectrum tumors are lacking. Clin Cancer Res; 16(7); 2214–24. ©2010 AACR.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".