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

Author:

Veeraraghavan Jamunarani123ORCID,Gutierrez Carolina124ORCID,De Angelis Carmine123ORCID,Davis Robert123ORCID,Wang Tao123ORCID,Pascual Tomas56ORCID,Selenica Pier7ORCID,Sanchez Katherine13ORCID,Nitta Hiroaki8ORCID,Kapadia Monesh8ORCID,Pavlick Anne C.12ORCID,Galvan Patricia6ORCID,Rexer Brent9ORCID,Forero-Torres Andres10ORCID,Nanda Rita11ORCID,Storniolo Anna M.12ORCID,Krop Ian E.13ORCID,Goetz Matthew P.14ORCID,Nangia Julie R.2ORCID,Wolff Antonio C.15ORCID,Weigelt Britta7ORCID,Reis-Filho Jorge S.7ORCID,Hilsenbeck Susan G.123ORCID,Prat Aleix56ORCID,Osborne C. Kent12316ORCID,Schiff Rachel12316ORCID,Rimawi Mothaffar F.123ORCID

Affiliation:

1. 1Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, Texas.

2. 2Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas.

3. 3Department of Medicine, Baylor College of Medicine, Houston, Texas.

4. 4Department of Pathology, Baylor College of Medicine, Houston, Texas.

5. 5Translational Genomics and Targeted Therapies in Solid Tumors, IDIBAPS, Hospital Clinic de Barcelona, Barcelona, Spain.

6. 6SOLTI Cancer Research Group, Barcelona, Spain.

7. 7Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, Manhattan, New York.

8. 8Roche Tissue Diagnostics, Tucson, Arizona.

9. 9Vanderbilt University, Nashville, Tennesse.

10. 10University of Alabama-Birmingham, Birmingham, Alabama.

11. 11University of Chicago, Chicago, Illinois.

12. 12Indiana University School of Medicine, Indianapolis, Indiana.

13. 13Dana Farber Cancer Institute, Boston, Massachusetts.

14. 14Mayo Clinic, Rochester, Minnesota.

15. 15Johns Hopkins University, Baltimore, Maryland.

16. 16Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas.

Abstract

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.

Funder

U.S. Department of Defense

Breast Cancer Research Foundation

National Cancer Institute

Publisher

American Association for Cancer Research (AACR)

Subject

Cancer Research,Oncology

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