Biomarkers for Antibody-Drug Conjugates in Breast Cancer

Educational Objectives

The goal of this program is to improve biomarker-guided management of antibody drug conjugates (ADCs) in breast cancer. After hearing and assimilating this program, the clinician will be better able to:

1. Identify antigen- and payload-related biomarkers that predict ADC resistance.
2. Apply appropriate ADC sequencing strategies after development of payload-related resistance.

Summary

Antibody-drug conjugates (ADC) in metastatic breast cancer: 4 ADCs are Food and Drug Administration (FDA)-approved; sacituzumab govotecan (eg, Trodelvy) and trastuzumab deruxtecan (T-DXd; eg, Enhertu), both targeting TROP2 and HER2 antigens respectively with TOP1 inhibitor payloads, plus trastuzumab emtansine (T-DM1) that targets HER2 with a tubulin inhibitor payload; despite improved clinical outcomes, emerging resistance poses significant challenges; resistance patterns include primary resistance (no initial response) and acquired resistance (initial response followed by treatment failure); mechanisms occur at multiple pathway steps, including antigen binding, ADC internalization and processing, payload-related effects, and drug efflux pump activity

Antigen-related resistance mechanisms: HER2 expression and outcomes—Caris study analyzed 379 samples using multi-omic molecular profiling in patients treated with T-DXd; highest HER2 expression quartile correlated with median overall survival (OS) of 25 mo vs 13.2 mo in lowest quartile; HER2-positive disease demonstrated significantly longer median OS compared with HER2-null disease; decreased HER2 expression was more pronounced in post-treatment samples from patients progressing on T-DM1; TEMPEST database analysis—compares pretreatment samples (collected ≤1 yr before or 15 days after ADC initiation) with post-treatment samples (collected ≤3 mo after progression); decreased HER2 expression was more pronounced in post-treatment samples from patients progressing on T-DM1, although signals not significant for trastuzumab deruxtecan or sacituzumab govotecan, potentially due to small sample size; TROP2-related resistance—case study identifies defective plasma membrane localization and reduced cell surface binding to HRS7 antibody (used in sacituzumab govotecan), combined with TOP1 mutation, demonstrating multifactorial resistance mechanisms

Payload-related resistance and cross-ADC implications: TOP1 mutations—Mass General study identified TOP1 mutations in 4 of 31 patients with metastatic breast cancer treated with ADCs; 4 different TOP1 mutation subtypes were characterized; mutant allele frequency increases over time after first ADC exposure, correlating with shorter duration of treatment on second ADC when both target TOP1; decreased TOP1 enzymatic activity was identified in 3 mutation categories, conferring resistance to both SN-38 (sacituzumab govotecan) and deruxtecan (trastuzumab deruxtecan); clinical sequencing outcomes—study examines outcomes post-T-DXd treatment across breast cancer subtypes; HER2-positive disease shows longer median progression-free survival (PFS) and OS compared with hormone receptor (HR)-positive/HER2-negative and triple-negative breast cancer; patients receiving sacituzumab govotecan immediately after T-DXd have significantly shorter median PFS compared with other therapies; in HER2-positive disease, patients receiving T-DM1 post-T-DXd have longer median PFS, potentially due to different payload target (tubulin vs TOP1); shorter real-world PFS was observed in HR-positive/HER2-negative disease when sacituzumab govotecan was used after T-DXd; findings emphasize avoiding sequential use of ADCs with same payload target

Drug efflux pump upregulation as resistance mechanism: ABCC1 expression—CARIS study post-treatment samples show highest ABCC1 expression quartile correlates with median OS of 14.2 mo vs 22 mo in lowest quartile; in HER2-low or HER2-null disease, higher ABCC1 expression was associated with shorter median OS; combined biomarkers—patients with highest ERBB2 expression and lowest ABCC1 expression achieved median OS of ≈28 mo, compared with poorest outcomes in patients with lowest ERBB2 and highest ABCC1 expression; TEMPEST biomarker analysis—at RNA expression level, higher ABCC1 and ABCB1 expression in patients treated with T-DXd correlated with shorter treatment duration; ABCB1 expression in T-DXd correlated with worse OS; in sacituzumab govotecan, ABCC2 and ABCB4 expression correlated with worse OS; trend toward higher drug efflux pump expression was seen in post-treatment compared with pretreatment samples across all 3 ADCs (not statistically significant due to sample size); trend toward higher expression of ABCB1 was seen in primary resistance cohort for T-DXd

Cathepsins and other resistance mechanisms: cathepsin expression—cathepsins are proteolytic enzymes involved in extracellular matrix remodeling; preclinical studies show higher cathepsin expression decreases T-DXd efficacy; Tempest analysis finds that higher cathepsin B and L expression leads to worse OS in HER2-positive disease, whereas higher expression correlates with better OS in HR-positive/HER2-negative disease; hypothesis for HER2-positive findings involves premature extracellular payload release that negatively impacts efficacy, while premature release may have positive effect in HR-positive/HER2-negative disease since T-DXd efficacy is less dependent on HER2 binding and endocytosis; additional mutations—CARIS study identifies evolution of ESR1, NFE2L2, and mTOR mutations after T-DXd treatment, although findings require validation in larger cohorts; extracellular mechanisms—include poor intratumoral penetration due to physical barriers, activation of alternative pathways (eg, leukemia inhibitor factor receptor and PIK3 pathway), and tumor microenvironment changes, including increased cancer-associated fibroblasts and enrichment in cancer stem cells

Clinical implications for ADC sequencing: antigen-related mutations suggest using same antigen-targeting ADC may not improve outcomes; payload-related mutations warrant switching to ADC with completely different payload target; avoiding sequential TOP1 inhibitor-based ADCs (T-DXd followed by sacituzumab govotecan or vice versa) appears prudent based on cross-resistance data; T-DM1 may provide benefit after T-DXd in HER2-positive disease due to different payload mechanism (tubulin inhibitor); 5 ongoing prospective phase 2 trials are evaluating ADC sequencing strategies after progression on first-line ADC across different metastatic breast cancer subtypes

Strategies to overcome resistance: combination approaches—ongoing phase 3 trials are evaluating ADCs combined with immune checkpoint inhibitors (durvalumab, atezolizumab, and pembrolizumab), PARP inhibitors (olaparib, talazoparib), anti-VEGF agents, and PIK3CA inhibitors; novel ADC designs—next-generation ADCs under development include immune stimulator-antibody conjugates, antibody-oligonucleotide conjugates, multiple payload platforms, and innovative linker technologies; focus is on identifying new antigens exclusively expressed on cancer cells rather than normal tissue; multiple phase 3 trials of investigational ADCs are ongoing; transporter inhibition—CARIS preclinical study using HER2-resistant cell lines shows MK571 transporter inhibitor combined with T-DXd significantly decreases tumor cell viability, suggesting potential strategy to overcome drug efflux pump-mediated resistance

Future directions and biomarker development: prospective molecular profiling—need for longitudinal studies obtaining tumor biopsies before ADC initiation and at progression to identify predictive and acquired resistance biomarkers; liquid biopsy via circulating tumor DNA (ctDNA) is emerging as a tool for real-time assessment of resistance mutations, addressing challenges of obtaining tissue biopsies from metastatic sites; planned prospective work includes following patients on ADC therapy with serial molecular profiling to identify baseline mutations conferring primary resistance or acquired mutations developing during treatment; clinical trial landscape—5 prospective trials currently evaluating ADC sequencing strategies after prior ADC exposure; multiple combination therapy trials in various phases; need for biomarker-driven personalization of therapy selection based on antigen expression, payload target status, and drug efflux pump profiles

Readings

Disclosures

For this program, members of the faculty and planning committee reported nothing relevant to disclose.

Acknowledgements

Dr. Alkassis was recorded at the 13th Annual USC Multidisciplinary Breast Cancer Symposium, held on January 17, 2026, in Los Angeles, CA, and presented by Keck School of Medicine of USC. For information about upcoming CME activities from this presenter, please visit keck.usc.edu/cme. Audio Digest thanks Dr. Alkassis and Keck School of Medicine of USC for their cooperation in the production of this program.

CME/CE INFO

Accreditation:

Lecture ID:

ON170902

Qualifies for:

ABIM MOC, Clinical Pharmacology

Expiration:

This CME course qualifies for AMA PRA Category 1 Credits™ for 3 years from the date of publication.

Instructions:

To earn CME/CE credit for this course, you must complete all the following components in the order recommended: (1) Review introductory course content, including Educational Objectives and Faculty/Planner Disclosures; (2) Listen to the audio program and review accompanying learning materials; (3) Complete posttest (only after completing Step 2) and earn a passing score of at least 80%. Taking the course Pretest and completing the Evaluation Survey are strongly recommended (but not mandatory) components of completing this CME/CE course.

Estimated time to complete this CME/CE course:

Approximately 2x the length of the recorded lecture to account for time spent studying accompanying learning materials and completing tests.