TY - JOUR
T1 - A Multiparameter Molecular Classifier to Predict Response to Neoadjuvant Lapatinib plus Trastuzumab without Chemotherapy in HER2þ Breast Cancer
AU - Veeraraghavan, Jamunarani
AU - Gutierrez, Carolina
AU - De Angelis, Carmine
AU - Davis, Robert
AU - Wang, Tao
AU - Pascual, Tomas
AU - Selenica, Pier
AU - Sanchez, Katherine
AU - Nitta, Hiroaki
AU - Kapadia, Monesh
AU - Pavlick, Anne C.
AU - Galvan, Patricia
AU - Rexer, Brent
AU - Forero-Torres, Andres
AU - Nanda, Rita
AU - Storniolo, Anna M.
AU - Krop, Ian E.
AU - Goetz, Matthew P.
AU - Nangia, Julie R.
AU - Wolff, Antonio C.
AU - Weigelt, Britta
AU - Reis-Filho, Jorge S.
AU - Hilsenbeck, Susan G.
AU - Prat, Aleix
AU - Osborne, C. Kent
AU - Schiff, Rachel
AU - Rimawi, Mothaffar F.
N1 - Publisher Copyright:
© 2023 American Association for Cancer Research Inc.. All rights reserved.
PY - 2023/8/15
Y1 - 2023/8/15
N2 - Purpose: Clinical trials reported 25% to 30% pathologic Results: In TBCRC023, 72 breast cancer specimens had GPA, complete response (pCR) rates in HER2þ patients with breast PAM50, and sequencing data, of which 15 had pCR. Recursive cancer treated with anti-HER2 therapies without chemotherpartitioning identified cutoffs of HER2 ratio ≥ 4.6 and %3þ IHC apy. We hypothesize that a multiparameter classifier can staining ≥ 97.5%. With PAM50 and sequencing data, the model identify patients with HER2-“addicted” tumors who may benadded HER2-E and PIK3CA wild-type (WT). For clinical impleefit from a chemotherapy-sparing strategy. mentation, the classifier was locked as HER2 ratio ≥ 4.5, %3þ IHC Experimental Design: Baseline HER2þ breast cancer speci-staining ≥ 90%, and PIK3CA-WT and HER2-E, yielding 55% and mens from the TBCRC023 and PAMELA trials, which included 94% positive (PPV) and negative (NPV) predictive values, respecneoadjuvant treatment with lapatinib and trastuzumab, were tively. Independent validation using 44 PAMELA cases with all three used. In the case of estrogen receptor–positive (ERþ) tumors, biomarkers yielded 47% PPV and 82% NPV. Importantly, our endocrine therapy was also administered. HER2 protein and classifier’s high NPV signifies its strength in accurately identifying gene amplification (ratio), HER2-enriched (HER2-E), and patients who may not be good candidates for treatment deescalation. PIK3CA mutation status were assessed by dual gene protein Conclusions: Our multiparameter classifier differentially idenassay (GPA), research-based PAM50, and targeted DNAtifies patients who may benefit from HER2-targeted therapy alone sequencing. GPA cutoffs and classifier of response were con-from those who need chemotherapy and predicts pCR to anti-HER2 structed in TBCRC023 using a decision tree algorithm, then therapy alone comparable with chemotherapy plus dual anti-HER2 validated in PAMELA. therapy in unselected patients.
AB - Purpose: Clinical trials reported 25% to 30% pathologic Results: In TBCRC023, 72 breast cancer specimens had GPA, complete response (pCR) rates in HER2þ patients with breast PAM50, and sequencing data, of which 15 had pCR. Recursive cancer treated with anti-HER2 therapies without chemotherpartitioning identified cutoffs of HER2 ratio ≥ 4.6 and %3þ IHC apy. We hypothesize that a multiparameter classifier can staining ≥ 97.5%. With PAM50 and sequencing data, the model identify patients with HER2-“addicted” tumors who may benadded HER2-E and PIK3CA wild-type (WT). For clinical impleefit from a chemotherapy-sparing strategy. mentation, the classifier was locked as HER2 ratio ≥ 4.5, %3þ IHC Experimental Design: Baseline HER2þ breast cancer speci-staining ≥ 90%, and PIK3CA-WT and HER2-E, yielding 55% and mens from the TBCRC023 and PAMELA trials, which included 94% positive (PPV) and negative (NPV) predictive values, respecneoadjuvant treatment with lapatinib and trastuzumab, were tively. Independent validation using 44 PAMELA cases with all three used. In the case of estrogen receptor–positive (ERþ) tumors, biomarkers yielded 47% PPV and 82% NPV. Importantly, our endocrine therapy was also administered. HER2 protein and classifier’s high NPV signifies its strength in accurately identifying gene amplification (ratio), HER2-enriched (HER2-E), and patients who may not be good candidates for treatment deescalation. PIK3CA mutation status were assessed by dual gene protein Conclusions: Our multiparameter classifier differentially idenassay (GPA), research-based PAM50, and targeted DNAtifies patients who may benefit from HER2-targeted therapy alone sequencing. GPA cutoffs and classifier of response were con-from those who need chemotherapy and predicts pCR to anti-HER2 structed in TBCRC023 using a decision tree algorithm, then therapy alone comparable with chemotherapy plus dual anti-HER2 validated in PAMELA. therapy in unselected patients.
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U2 - 10.1158/1078-0432.CCR-22-3753
DO - 10.1158/1078-0432.CCR-22-3753
M3 - Article
C2 - 37195235
AN - SCOPUS:85170416586
SN - 1078-0432
VL - 29
SP - 3101
EP - 3109
JO - Clinical Cancer Research
JF - Clinical Cancer Research
IS - 16
ER -