A Multiparameter Molecular Classifier to Predict Response to Neoadjuvant Lapatinib plus Trastuzumab without Chemotherapy in HER2+ Breast Cancer

dc.contributor.authorVeeraraghavan, Jamunarani
dc.contributor.authorGutierrez, Carolina
dc.contributor.authorDe Angelis, Carmine
dc.contributor.authorDavis, Robert
dc.contributor.authorWang, Tao
dc.contributor.authorPascual, Tomas
dc.contributor.authorSelenica, Pier
dc.contributor.authorSanchez, Katherine
dc.contributor.authorNitta, Hiroaki
dc.contributor.authorKapadia, Monesh
dc.contributor.authorPavlick, Anne C.
dc.contributor.authorGalvan, Patricia
dc.contributor.authorRexer, Brent
dc.contributor.authorForero-Torres, Andres
dc.contributor.authorNanda, Rita
dc.contributor.authorStorniolo, Anna M.
dc.contributor.authorKrop, Ian E.
dc.contributor.authorGoetz, Matthew P.
dc.contributor.authorNangia, Julie R.
dc.contributor.authorWolff, Antonio C.
dc.contributor.authorWeigelt, Britta
dc.contributor.authorReis-Filho, Jorge S.
dc.contributor.authorHilsenbeck, Susan G.
dc.contributor.authorPrat, Aleix
dc.contributor.authorOsborne, C. Kent
dc.contributor.authorSchiff, Rachel
dc.contributor.authorRimawi, Mothaffar F.
dc.contributor.departmentMedicine, School of Medicine
dc.date.accessioned2024-06-27T09:39:52Z
dc.date.available2024-06-27T09:39:52Z
dc.date.issued2023
dc.description.abstractPurpose: 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.versionAuthor's manuscript
dc.identifier.citationVeeraraghavan 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.urihttps://hdl.handle.net/1805/41941
dc.language.isoen_US
dc.publisherAmerican Association for Cancer Research
dc.relation.isversionof10.1158/1078-0432.CCR-22-3753
dc.relation.journalClinical Cancer Research
dc.rightsPublisher Policy
dc.sourcePMC
dc.subjectHER2-positive breast cancer
dc.subjectHER2 levels and heterogeneity
dc.subjectPIK3CA mutations
dc.subjectPAM50 subtype
dc.subjectTreatment de-escalation
dc.subjectMolecular predictor
dc.titleA Multiparameter Molecular Classifier to Predict Response to Neoadjuvant Lapatinib plus Trastuzumab without Chemotherapy in HER2+ Breast Cancer
dc.typeArticle
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