Abstract P2-11-03: Predictive significance of an optimized immunohistochemical panel for basal-like breast cancer on the CCTG MA.12 phase III randomized clinical trial
Bibliographic record
Abstract
Abstract Background: Tamoxifen and aromatase inhibitors constitute the backbone of treatment for estrogen receptor positive early stage breast cancers based on immunohistochemical (IHC) results. While these therapies significantly reduce the risk of relapse of breast cancer, they have toxicities and add to costs. Gene expression profiling assays are widely used to quantify risk and support targeted therapies for luminal breast cancers treated with adjuvant endocrine therapy. In a prospective-retrospective analysis of the phase III CCTG MA.12 clinical trial (randomizing premenopausal women treated with adjuvant chemotherapy, to either tamoxifen or placebo for 5 years), luminal subtype by PAM50 was significantly predictive for tamoxifen benefit. However, IHC classification (as estrogen receptor positive) could not demonstrate a statistically significant benefit from tamoxifen over placebo. More accurate IHC biomarkers incorporating nestin positivity or loss of inositol polyphosphate-4-phosphate (INPP4B) have recently been optimized to identify the basal-like intrinsic subtype of breast cancer regardless of ER/PR/HER2 status. In this study, we examined the capacity of these basal biomarkers to identify intrinsic subtype and predict benefit from adjuvant tamoxifen vs. placebo in the CCTG MA.12 clinical trial Methods:492 formalin-fixed paraffin embedded blocks of primary tumor from patients randomized in the CCTG MA.12 trial were used to build tissue microarrays. IHC staining for nestin and INPP4B was done according to published methods, and interpretation was performed by pathologists with no access to molecular data. The performance of the nestin and INPP4B panel was assessed against PAM50 gene expression assay as a standard reference. A prespecified statistical plan was executed independently by the Canadian Cancer Trials Group, testing the primary hypothesis that patients with basal breast cancer, when defined as “positive for nestin or negative for INPP4B,” would not benefit from tamoxifen (primary endpoint: disease-free survival).Results: 366 primary tumor samples from the CCTG MA.12 had a full dataset available for IHCbiomarker evaluation, PAM50 subtype and clinical outcomes. Positive staining of nestin or loss of INPP4B was observed in 47 (13%) of the total cases and was significantly associated with poor prognostic factors including high grade, younger age, ER negativity, triple negative and core basal IHC status (p<0.01). “Nestin+ or INPP4B-” status was significantly associated with basal-like PAM50 gene expression subtype, while the other cases (nestin- and INPP4B+) were significantly associated with PAM50 luminal subtype. Patients assigned as basals by “nestin+ or INPP4B-” IHC status did not demonstrate a benefit from adjuvant tamoxifen vs. placebo (HR=1.39, 95%CI [0.37-5.26], p=0.63), whereas “nestin- and INPP4B+” cases displayed a significantly higher benefit from adjuvant tamoxifen vs. placebo (HR=0.67, 95% CI [0.45-0.98], p=0.04), (p-interaction=0.87). While, in this trial, ER clinical status as determined in community hospitals or centrally by single biomarker IHC was not significantly predictive for tamoxifen benefit, patients classified as IHC non-basal “nestin- and INPP4B+” within the ER+ subgroup did benefit from addition of tamoxifen (HR=0.62, 95%CI [0.38-1.01], p=0.05).Conclusions:The nestin/INPP4B IHC panel offers a feasible and inexpensive methodology to accurately identify intrinsic subtype of breast cancer. Patients assigned as IHC basal by this panel did not display a superior survival when treated with tamoxifen vs. placebo in the adjuvant setting. Within the ER+ subgroup, these cases could potentially be spared the side effects of currently recommended endocrine therapies that do not benefit this group of patients. Citation Format: Karama Asleh, Dongxia Gao, Vivien H Bramwell, Dongsheng Tu, Lois E Shepherd, Torsten O Nielsen. Predictive significance of an optimized immunohistochemical panel for basal-like breast cancer on the CCTG MA.12 phase III randomized clinical trial [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P2-11-03.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".