Abstract 3940: Baseline molecular markers and risk of distant relapse in the NeoSphere study
Bibliographic record
Abstract
Abstract Background We investigated the association between gene-expression (GEP) based markers and distant event free survival (DEFS) in HER2+ breast cancer patients (pts) in the NeoSphere study. Methods In NeoSphere HER2+ pts were randomized to neoadjuvant HD, PHD, PH or PD (H = trastuzumab, P = pertuzumab, D = docetaxel). Affymetrix-based GEPs were generated in 367/417 pts (88%). We evaluated the association with DEFS of 10 biomarkers in all patients with arms pooled and by each arm, and separately by ER status: six immune-related metagenes (CD8, IGG and MHC2, related to T cells, plasma cells and antigen presenting cells, respectively; MHC1, STAT1 and IF.I related to HLA cass I genes, and to genes modulated by interferons), ESR1 and an ER-related score (ERS), a proliferation marker (MKS) and ERBB2 expression. We re-assessed findings in GEPs derived from ER-/HER2+ pts of the NOAH trial treated with neoadjuvant chemotherapy (CT) or CT and trastuzumab (CTH). Results Median follow-up was 5 years. Overall none of the markers was significant, but an interaction test for biomarkers and ER status was significant for MHC1, MHC2, STAT1, and marginally for MKS. In ER+/HER2+ tumors, immune markers were not significant, but higher proliferation (MKS; HR 2.12 [1.07-4.19], p = 0.03) was linked to higher risk, with a similar trend for low ERS (p = 0.097). In ER-/HER2+ tumors higher MHC2 (HR 0.53 [0.36-0.79]; p = 0.002), MHC1 (HR 0.41 [0.22-0.77], p = 0.005) and STAT1 (HR 0.69 [0.49-0.97], p = 0.036) were linked to better DEFS. Outcome for high MHC1 tertile was excellent and similar in all treatment arms. Low/int MHC1 pts treated with PHD had a trend for better DEFS compared to other treatments (HR 0.41 (0.14-1.21), p = 0.11). In cases reaching pCR higher MHC1 (p = 0.009), MHC2 (p = 0.006), IGG (p = 0.027) and STAT1 (p = 0.008) were linked to better DEFS. For instance, the 5 yrs DEFS for high and low MHC1 tertiles was 100% and 74.6%, respectively. Similarly, in ER-/HER2+ pts from NOAH, the 5-yrs DEFS in high, int and low MHC1 tertiles was 88.1%, 68.4% and 48.1%, respectively (p = 0.015). Prognosis was similar and good in patients with high MHC1 receiving CT or CTH (p = 0.674). Instead, in low/int MHC1 groups, CTH compared to CT significantly improved DEFS (HR 0.39 [0.16-0.93], p = 0.035). Also in NOAH, the 5 yrs DEFS of pCR cases was influenced by baseline MCH1 (100% and 76.2% with high and low/int MHC1, respectively). Conclusions In this exploratory analysis of NeoSphere, different biological functions were linked to DEFS in ER+ (proliferation and ER-related genes) and ER- (immune related) cases. In particular outcome of ER-/HER2+ with high MHC1 was good. However, in this group the benefit from adding trastuzumab to CT or pertuzumab in the PHD regimen was relatively small. Instead, the benefit seemed significant and large in cases of low/int MHC1, who had higher relapse risk. Of note, baseline immune markers of ER-/HER2+ tumors were linked to different DEFS also for cases achieving pCR. Citation Format: Giampaolo Bianchini, Tadeusz Pienkowski, Young-Hyuck Im, Giulia Valeria Bianchi, Ling-Ming Tseng, Mei-Ching Liu, Ana Lluch, Vladimir Semiglazov, Juan de la Haba-Rodríguez, Do-Youn Oh, Brigitte Poirier, Jose Luiz Pedrini, Pinuccia Valagussa, Luca Gianni. Baseline molecular markers and risk of distant relapse in the NeoSphere study. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3940.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".