Molecular Alterations Between the Primary Breast Cancer and the Subsequent Locoregional/Metastatic Tumor
Bibliographic record
Abstract
Abstract Learning Objectives: After completing this course, the reader will be able to: Describe the rate of discordance of predictive marker phenotype (i.e., ER/PR, HER2) between the primary and the relapsed/metastatic breast cancer lesion.Explain the impact of a change in predictive marker phenotype between the primary and relapsed/metastatic lesion on treatment options for these patients. This article is available for continuing medical education credit at CME.TheOncologist.com Background. Metastatic breast cancers have historically been presumed to have the same predictive biomarkers as the initial primary tumor. We compared the expression of these biomarkers in a large paired tissue microarray (TMA) series of primary and subsequent relapsed tumors. Methods. Using the British Columbia Cancer Agency Breast Cancer Outcomes Unit database, patients with biopsy-proven relapses were identified and linked to a large TMA series of primary breast cancers from 1986–1992. Charts were reviewed, and tissue blocks of the metastatic cancer were collected to create a separate TMA. Immunohistochemical assessment with the same antibodies and conditions was performed for estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor (HER)-2 on both the primary and relapsed tumors. Results. One hundred sixty cases were received that had tumor adequate for analyses. Of these, 71.9% had no changes in either the ER or PR status or HER-2 status. Of the 45 (28.1%; 95% confidence interval [CI], 21.2%–35.1%) tumors that did have changes in receptor status, 7.5% were in-breast recurrences or new breast primaries, 4.4% had changes in PR status only and were therefore deemed clinically irrelevant, and 19.4% (95% CI, 13.3%–25.5%) had changes in either the ER or HER-2 status from regional or distant relapses. Five percent of tumors had a receptor status change going from ER+ or PR+ to ER− or PR−; 9.4% went from ER− or PR− to ER+ or PR+. With regard to HER-2 status, 3.8% of tumors went from positive to negative and 1.3% went from negative to positive. For all discordant cases, biopsies of the relapsed lesion were obtained prior to initiation of first-line treatment for metastatic disease. In the primary tumors that were ER+, time to relapse was significantly shorter in the discordant relapsed cases than in the concordant ones (p = .0002). Changes in loss or gain of either biomarker were seen across the discordant cases. Conclusions. A significant proportion of relapsed tumors had changes in either ER or HER-2 status, which would dramatically alter treatment recommendations and clinical behavior. This study suggests that biopsies of relapsed and metastatic breast cancers should be performed routinely in clinical practice.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".