A Multiparameter Molecular Classifier to Predict Response to Neoadjuvant Lapatinib plus Trastuzumab without Chemotherapy in HER2+ Breast Cancer
dc.contributor.author | Veeraraghavan, Jamunarani | |
dc.contributor.author | Gutierrez, Carolina | |
dc.contributor.author | De Angelis, Carmine | |
dc.contributor.author | Davis, Robert | |
dc.contributor.author | Wang, Tao | |
dc.contributor.author | Pascual, Tomas | |
dc.contributor.author | Selenica, Pier | |
dc.contributor.author | Sanchez, Katherine | |
dc.contributor.author | Nitta, Hiroaki | |
dc.contributor.author | Kapadia, Monesh | |
dc.contributor.author | Pavlick, Anne C. | |
dc.contributor.author | Galvan, Patricia | |
dc.contributor.author | Rexer, Brent | |
dc.contributor.author | Forero-Torres, Andres | |
dc.contributor.author | Nanda, Rita | |
dc.contributor.author | Storniolo, Anna M. | |
dc.contributor.author | Krop, Ian E. | |
dc.contributor.author | Goetz, Matthew P. | |
dc.contributor.author | Nangia, Julie R. | |
dc.contributor.author | Wolff, Antonio C. | |
dc.contributor.author | Weigelt, Britta | |
dc.contributor.author | Reis-Filho, Jorge S. | |
dc.contributor.author | Hilsenbeck, Susan G. | |
dc.contributor.author | Prat, Aleix | |
dc.contributor.author | Osborne, C. Kent | |
dc.contributor.author | Schiff, Rachel | |
dc.contributor.author | Rimawi, Mothaffar F. | |
dc.contributor.department | Medicine, School of Medicine | |
dc.date.accessioned | 2024-06-27T09:39:52Z | |
dc.date.available | 2024-06-27T09:39:52Z | |
dc.date.issued | 2023 | |
dc.description.abstract | Purpose: Clinical trials reported 25% to 30% pathologic complete response (pCR) rates in HER2+ patients with breast cancer treated with anti-HER2 therapies without chemotherapy. We hypothesize that a multiparameter classifier can identify patients with HER2-"addicted" tumors who may benefit from a chemotherapy-sparing strategy. Experimental design: Baseline HER2+ breast cancer specimens from the TBCRC023 and PAMELA trials, which included neoadjuvant treatment with lapatinib and trastuzumab, were used. In the case of estrogen receptor-positive (ER+) tumors, endocrine therapy was also administered. HER2 protein and gene amplification (ratio), HER2-enriched (HER2-E), and PIK3CA mutation status were assessed by dual gene protein assay (GPA), research-based PAM50, and targeted DNA-sequencing. GPA cutoffs and classifier of response were constructed in TBCRC023 using a decision tree algorithm, then validated in PAMELA. Results: In TBCRC023, 72 breast cancer specimens had GPA, PAM50, and sequencing data, of which 15 had pCR. Recursive partitioning identified cutoffs of HER2 ratio ≥ 4.6 and %3+ IHC staining ≥ 97.5%. With PAM50 and sequencing data, the model added HER2-E and PIK3CA wild-type (WT). For clinical implementation, the classifier was locked as HER2 ratio ≥ 4.5, %3+ IHC staining ≥ 90%, and PIK3CA-WT and HER2-E, yielding 55% and 94% positive (PPV) and negative (NPV) predictive values, respectively. Independent validation using 44 PAMELA cases with all three biomarkers yielded 47% PPV and 82% NPV. Importantly, our classifier's high NPV signifies its strength in accurately identifying patients who may not be good candidates for treatment deescalation. Conclusions: Our multiparameter classifier differentially identifies patients who may benefit from HER2-targeted therapy alone from those who need chemotherapy and predicts pCR to anti-HER2 therapy alone comparable with chemotherapy plus dual anti-HER2 therapy in unselected patients. | |
dc.eprint.version | Author's manuscript | |
dc.identifier.citation | Veeraraghavan J, Gutierrez C, De Angelis C, et al. A Multiparameter Molecular Classifier to Predict Response to Neoadjuvant Lapatinib plus Trastuzumab without Chemotherapy in HER2+ Breast Cancer. Clin Cancer Res. 2023;29(16):3101-3109. doi:10.1158/1078-0432.CCR-22-3753 | |
dc.identifier.uri | https://hdl.handle.net/1805/41941 | |
dc.language.iso | en_US | |
dc.publisher | American Association for Cancer Research | |
dc.relation.isversionof | 10.1158/1078-0432.CCR-22-3753 | |
dc.relation.journal | Clinical Cancer Research | |
dc.rights | Publisher Policy | |
dc.source | PMC | |
dc.subject | HER2-positive breast cancer | |
dc.subject | HER2 levels and heterogeneity | |
dc.subject | PIK3CA mutations | |
dc.subject | PAM50 subtype | |
dc.subject | Treatment de-escalation | |
dc.subject | Molecular predictor | |
dc.title | A Multiparameter Molecular Classifier to Predict Response to Neoadjuvant Lapatinib plus Trastuzumab without Chemotherapy in HER2+ Breast Cancer | |
dc.type | Article |