Abstract C1: BRCA1 protein levels and PI3KA mutations as predictive biomarkers for response to neoadjuvant chemotherapy in locally advanced breast cancer: An exploratory analysis.
Bibliographic record
Abstract
Abstract Background: Locally advanced breast cancer (LABC) is treated with neoadjuvant chemotherapy, with a goal of achieving a pathologic complete response (pCR) and a better outcome. Given the role of breast cancer 1 (BRCA1) overexpression and PI 3-kinase (PI3K) activation in the resistance to DNA damaging agents, we hypothesize that BRCA1 protein expression and activating PI3K mutations are potential tumor biomarkers for chemotherapy response in LABC. Methods: For this exploratory study, informed consent was requested from 136 eligible patients identified between 2006 and 2008. Participants had demographic and response data collected and the pathologic characteristics of the tumor specimens before and after chemotherapy were evaluated. BRCA1 protein expression levels were assessed by immunohistochemistry of archival tissue. Specimens were evaluated by two separate pathologists for both staining intensity and distribution. BRCA1 protein levels were then tested for correlation with pCR and a partial response or better using a Chi Square Test and logistic regression analysis. PI3KA mutation status was assessed by isolating DNA from pathology sample sections followed by nested PCR amplification and DNA sequencing. PI3KA mutation status was then tested for correlation with pCR and a partial response or better using a Fisher Exact Test and a logistic regression analysis. Results: Of the 136 eligible participants, 65 agreed to participate, with analyzable samples available in 59. Of these 59 patients, the median age was 51.6 years, 20.3% had inflammatory disease, 72.8% were ER positive, 61.0% were PR positive, 28.8% were HER2 positive and the median tumor grade was 2/3. All participants received 4 cycles of doxorubicin/cyclophosphamide and 4 cycles of docetaxel followed by 1 year of trastuzumab initiated with docetaxel if HER2 positive, except for one participant who received 6 cycles of carboplatin/taxotere due to a pre-existing cardiac dysfunction. 78.3% of participants had ≥30% response to therapy, with 23.7% achieving a pCR. BRCA1 protein expression was scored between 0–9. A minimal p-value approach established that samples scored ≤4 have relatively low levels of protein expression, while samples scored >4 have high levels. Low levels of BRCA1 protein had an Odds ratio (OR) = 1.74 of achieving a pCR compared to high levels, although this was not statistically significant (p-value=0.437). PI3KA mutations were not statistically associated with a likelihood of pCR (OR=0.977; p=0.971). Neither BRCA1 protein levels (OR=1.18; p=0.818) nor PI3KA mutations (OR=1.03; p=0.971) appeared to be associated with the likelihood of achieving a partial response or better to neoadjuvant chemotherapy. A mutation in PI3KA showed a trend towards an increased likelihood of not presenting with inflammatory disease (OR=5.34), although this result did not reach statistical significance (p=0.101). Conclusions: In this exploratory study in LABC, neither BRCA1 protein expression levels nor the presence of PI3KA mutations appear to be associated with chemotherapy response. However, the relatively small sample size limits the overall interpretation. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2011 Nov 12-16; San Francisco, CA. Philadelphia (PA): AACR; Mol Cancer Ther 2011;10(11 Suppl):Abstract nr C1.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".