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Abstract HER2-06: HER2-06 Outcome analysis of HER2-zero or HER2-low hormone receptor-positive (HR+) breast cancer patients - characterization of the molecular phenotype in combination with molecular subtyping

2023· article· en· W4322774011 on OpenAlexaff
Carsten Denkert, Michael Untch, Hervé Bonnefoi, Erik S. Knudsen, Seock‐Ah Im, Angela DeMichele, Agnieszka K. Witkiewicz, Laura van ‘t Veer, Sung‐Bae Kim, Harry D. Bear, Nicole McCarthy, Karen Gelmon, Frederik Marmé, José Á. García-Sáenz, Nicholas Turner, Federico Rojo, Martin Filipits, Lesley‐Ann Martin, Peter A. Fasching, Christian Schem, Catherine M. Kelly, Toralf Reimer, Masakazu Toi, Hope Rugo, Michael Gnant, Andreas Makris, Yuan Liu, Karsten E. Weber, Sivaramakrishna Rachakonda, Sibylle Loibl

Bibliographic record

VenueCancer Research · 2023
Typearticle
Languageen
FieldMedicine
TopicAdvanced Breast Cancer Therapies
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsBreast cancerMedicineOncologyInternal medicineCancerNeoadjuvant therapyBiomarkerHormone receptorStage (stratigraphy)TrastuzumabBiopsyPathologyBiology

Abstract

fetched live from OpenAlex

Abstract Background: Breast cancer with low HER2 expression (HER2-low) is of high clinical relevance because of new therapeutic options with antibody-drug conjugates. We have recently shown in a large cohort from neoadjuvant clinical trials that HER2-low breast cancer has different molecular characteristics as well as different clinical outcomes compared to HER2-zero. Considering the positive correlation between HER2-low expression and hormone receptor positivity observed consistently in many investigations, we have extended our analysis to HR+ tumors from the post-neoadjuvant PenelopeB trial. In PenelopeB, patients with HR+ breast cancer and residual disease after neoadjuvant chemotherapy (NACT) were randomized to post-neoadjuvant palbociclib versus placebo in addition to endocrine therapy. We evaluated the molecular phenotype and clinical outcomes of HER2-low compared to HER2-zero patients. Methods: A total of 1250 patients were randomized, HER2 status was available for 1151 tumors from pretherapeutic core biopsy, determined mainly by local pathology, and from 1213 tumors from the post-NACT sample, determined as part of central pathology. For 1119 patients a paired HER2-status was both available. HER2-zero was defined as IHC0 and HER2-low-positive was defined as IHC1+ or IHC2+/ISH-. Gene expression analysis of 2549 genes using the HTG oncology biomarker panel was performed in 620 pretherapeutic biopsies and 780 post-NACT residual tumor samples, with 539 paired gene expression samples. Breast cancer subtypes were determined using the AIMS approach. Results: In pretherapeutic biopsies, 695 tumors (60%) were HER2-low and 457 (40%) were HER2-zero. A HER2-low status in the biopsy was significantly linked to improved iDFS (HR 0.76 (0.60-0.96; p=0.02). In residual tumors, 632 tumors (60%) were HER2-low and 581 (40%) were HER2-zero, without any prognostic impact of HER2 low status. In addition, a shift of HER2-low-status comparing core biopsy and residual tumor was observed in 415 (37%) of 1119 tumors. 161 (14%) had a shift from HER2-zero to HER2-low and 254 (23%) shifted from HER2-low to HER2-zero. A shift from HER2-zero to HER2-low in the post-NACT samples was significantly linked to reduced iDFS (HR 1.43 [95%CI 1.01-2.01]), p=0.04), compared to HER2-low group, while a shift from HER2-low to HER2-zero was associated with better iDFS compared to HER2-zero group, although not statistically significant (p=0.17). We did not observe a significant correlation of HER2-low status and AIMS molecular subtypes. In particular, the HER2-enriched (HER2E) subtype was assigned to only 4.3% of HER2-zero and 3.1% of HER2-low tumors. Significant iDFS differences were observed for HER2-low-status in combination with AIMS subtypes (lumB/basal/HER2E vs. lumA/normL; overall p-value < 0.0001) for both pretherapeutic biopsies and residual tumor. Patients with post-NACT HER2-low tumors had an improved survival in the subgroups of aggressive AIMS subtypes (lumB/basal/HER2E), but not in the less aggressive AIMs subtypes (lumA/normL), with a positive test for interaction (p=0.02). For the pre-NACT samples a similar, but non-significant trend was observed. We evaluated a total of 620 core biopsies for differences in gene expression comparing HER2-low and HER2-zero tumors. A total of 417 genes were statistically significantly different, but in a hierarchical clustering there was no clear separation of HER2-low and HER2-zero tumors. Conclusions: In the PenelopeB cohort of HR+ tumors, a HER2-low status in pretherapeutic core biopsies is related to improved disease-free survival, especially for those tumors that have a more aggressive intrinsic subtype. A shift of HER2-low status was observed before and after chemotherapy, indicating an adaptation of the pathway activity to therapy-induced stress, which might become relevant for future diagnostic and therapeutic approaches. Citation Format: Carsten Denkert, Miguel Martín, Michael Untch, Hervé R. Bonnefoi, Erik S. Knudsen, Seock-Ah Im, Angela DeMichele, Agnieszka Witkiewicz, Laura Van ’t Veer, Sung-Bae Kim, Harry D. Bear, Nicole McCarthy, Karen Gelmon, Frederik Marmé, José Ángel García-Sáenz, Nicholas Turner, Federico Rojo, Martin Filipits, Lesley-Ann Martin, Peter A. Fasching, Christian Schem, Catherine M. Kelly, Toralf Reimer, Masakazu Toi, Hope Rugo, Michael Gnant, Andreas Makris, Yuan Liu, Karsten Weber, Sivaramakrishna Rachakonda, Sibylle Loibl. HER2-06 Outcome analysis of HER2-zero or HER2-low hormone receptor-positive (HR+) breast cancer patients - characterization of the molecular phenotype in combination with molecular subtyping [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr HER2-06.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.576
Threshold uncertainty score0.979

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.006
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.027
GPT teacher head0.353
Teacher spread0.326 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations5
Published2023
Admission routes1
Has abstractyes

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