NSABP B-41, a randomized neoadjuvant trial: Genes and signatures associated with pathologic complete response (pCR).
Bibliographic record
Abstract
511 Background: NSABP B-41 randomly assigned 529 patients (pts) with HER2 positive breast cancer to neoadjuvant trastuzumab (T), lapatinib (L), or combination (T+L), with weekly paclitaxel following doxorubicin and cyclophosphamide. No significant differences in pCR were found, but overall survival was significantly increased for pCR. Methods: RNA was extracted from FFPE tumor specimens, run on the NanoString Breast Cancer 360 Plus panel. Gene counts were normalized to include housekeeping genes, 33 biological signatures from 776 genes across 23 pathways and transformed into logarithm scale with base two. Univariate logistic regression was used to screen candidate genes and signatures that are prognostic of pCR, with false discovery rate controlled at 0.1. Multivariable logistic regression with lasso regularization was used for model selection. Results: 194 core biopsy samples were available; 69 treated with T, 64 with L and 61 with T+L. 20 prognostic genes are selected for trastuzumab-based regimens (TBR), including the epithelial-mesenchymal transition (HEMK1, GRB7, ERBB2, TMPRSS4), adhesion and migration (ITGB6, COL27A1, NRCAM), JAK-STAT (SOCS2), Hedgehog (LRP2), ER signaling (ELOVL2, MAPT), DNA damage and repair (NPEPPS, PRKDC), MAPK (DUSP6, PRKCB), Apoptosis (BCL2), proliferation (TFDP1). ERBB2 expression are associated with pCR in patients on TBR (OR = 1.73), but not for patients on L (interaction p = 0.01). HER2-Enriched correlation (p < 0.001), ESR1 (OR = 0.78, 95% CI = 0.69-0.88, p < 0.001), PD1 (OR = 1.68, 95% CI = 1.12-2.52, p = 0.01) and Tumor Inflammation Score (OR = 1.58, 95% CI = 1.18-2.11, p = 0.002) are associated with pCR in TBR. No genes or signatures were found to be predictive of treatment benefit from L added to T. Conclusions: BC360 highlighted tumor progression and signaling genes prognostic for TBR. HER2-Enriched correlation, ERBB2 and PD1 expression, and immune activation signatures were associated with pCR in TBR and may provide personalized treatment guidance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".