Quantitative pre-treatment assessment of trastuzumab deruxtecan (T-DXd) antibody target (HER2) and payload target (topoisomerase 1, Topo1) to predict outcomes in metastatic breast cancer (MBC).

P Paolo Tarantino (Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA) S Se Eun Kim M Melissa E. Hughes A Ashka Patel K Kalie Smith (Dana-Farber Cancer Institute, Boston, MA) F Fara Brasó-Maristany L Laia Paré J Justin Davis (Department of Biological Sciences, Rutgers University − Newark, 195 University Avenue, Newark, New Jersey 07102, United States) C Claudius Mueller B Brian Corgiat (Ignite Proteomics, Golden, CO) M Mercedes Marín-Aguilera F Francisco Pardo O Olivia D'Amico (Dana-Farber Cancer Institute, Boston, MA) A Alba Martini (1Dana Farber Cancer Institute, Boston, United States) R Ross J. Kusmick (Dana-Farber Cancer Institute, Boston, MA) N Nabihah Tayob E Emanuel Petricoin (George Mason University, Manassas, VA) A Aleix Prat N Nancy U. Lin S Sara M. Tolaney (Department of Medical Oncology, Dana-Farber Cancer Institute)

Abstract

1032 Background: The antitumor activity of T-DXd for MBC is sub-optimally predicted by HER2 immunohistochemistry (IHC). We evaluated novel assays to quantify the expression of T-DXd antibody and payload targets and their association with outcomes. Methods: We retrieved pre-treatment FFPE tumor samples for patients (pts) with MBC receiving T-DXd at Dana-Farber Cancer Institute between 2017 and 2023. Patients were categorized by HER2 IHC status at start of T-DXd. The RPPA-based protein assessment of HER2 and Topo1 was performed in a CLIA lab after laser capture microdissection enrichment of tumor epithelium. The HER2DX standardized assay was performed after RNA extraction. We evaluated the association of each marker, continuously and by tertiles/quartiles, with time to next treatment (TTNT) with T-DXd. Cox proportional hazards models were utilized to estimate hazard ratios and log-rank test p-values were reported. The Kaplan-Meier method was used to calculate median estimates. Results: HER2DX and RPPA testing were conducted for 41 (25 with HER2+, 16 with HER2- MBC) and 38 pts (24 with HER2+, 14 with HER2- MBC), respectively.Both HER2DX and RPPA HER2 quantitative testing significantly predicted outcomes with T-DXd (Table). The HER2DX HER2 amplicon mRNA signature was significantly associated with TTNT with T-DXd (p=0.001), including when divided into tertiles, with a range of 4.7 months in the lowest vs 12.03 months in the highest tertile (p=0.02). Similarly, the RPPA-based HER2 protein expression was significantly associated with TTNT when divided into quartiles (p=0.02). Pre-treatment Topo1 protein expression was significantly associated with outcomes in pts with HER2-negative MBC (n=14), with higher expression of TOPO1 associated with worse TTNT with T-DXd (p=0.04). Conclusions: Higher pre-treatment HER2 mRNA signature (HER2DX) and protein (RPPA) expression predicted improved outcomes with T-DXd for MBC, whereas higher Topo1 expression was associated with worse outcomes with T-DXd among pts with HER2- MBC. Association of pre-treatment HER2 amplicon mRNA signature, HER2 RPPA and Topo1 RPPA expression with outcomes among patients receiving T-DXd. Group Median TTNT (months) 95% CI HR 95% CI p-value HER2 amplicon mRNA expressionn=41 1 unit increase - - 0.70 0.56-0.87 0.001 HER2 amplicon tertilesn=41 Low (ref)MedHigh 4.705.3312.03 3.27-NA4.7-NA7.37-NA 0.710.23 0.33-1.550.08-0.69 Log-Rank p= 0.019 HER2 RPPA protein expressionn=38 10 unit increase - - 0.95 0.90-1.01 0.083 HER2 RPPA quartiles n=38 ≤ 25% (ref)>25%-50%>50%-75%>75% 4.035.838.009.07 2.87-NA2.13-NA5.33-NA5.83-NA 0.640.280.30 0.25-1.610.10-0.740.12-0.75 Log-Rank p= 0.019 Topo1 RPPA expression (HER2- only)n=14 < median (ref)≥ median 5.872.70 4.90-NA2.47-NA 3.49 1.02-11.96 Log-Rank p= 0.036

Article Details

Volume / Issue Vol. 43, Issue 16_suppl
Published June 01, 2025
Pages 1032-1032
ISSN 0732-183X
Publisher Lippincott Williams & Wilkins

Journal Info

Journal of Clinical Oncology

Lippincott Williams & Wilkins

ISSN: 0732-183X Health Sciences

Authors (20)

P

Paolo Tarantino

Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA

S

Se Eun Kim

M

Melissa E. Hughes

A

Ashka Patel

K

Kalie Smith

Dana-Farber Cancer Institute, Boston, MA

F

Fara Brasó-Maristany

L

Laia Paré

J

Justin Davis

Department of Biological Sciences, Rutgers University − Newark, 195 University Avenue, Newark, New Jersey 07102, United States

C

Claudius Mueller

B

Brian Corgiat

Ignite Proteomics, Golden, CO

M

Mercedes Marín-Aguilera

F

Francisco Pardo

O

Olivia D'Amico

Dana-Farber Cancer Institute, Boston, MA

A

Alba Martini

1Dana Farber Cancer Institute, Boston, United States

R

Ross J. Kusmick

Dana-Farber Cancer Institute, Boston, MA

N

Nabihah Tayob

E

Emanuel Petricoin

George Mason University, Manassas, VA

A

Aleix Prat

N

Nancy U. Lin

S

Sara M. Tolaney

Department of Medical Oncology, Dana-Farber Cancer Institute