Efficacy and omics-based insights of TROP2 ADC in non–small cell lung cancer with or without actionable genomic alterations (AGAs).

A Anlin Li (Department of Medical Oncology, Sun Yat-Sen University Cancer Center, Guangzhou, China) H Hong Lin Zhu (Sun Yat-sen University Cancer Center, Guangzhou, China) K Kai Wu (BNLMS, College of Chemistry and Molecular Engineering) Z Zhixin Yu S Sitong Liu (Computational Biology Department, School of Computer Science) X Xuan Yang L Li Zhang Y Yi-xin Zhou (Sun Yat-sen University Cancer Center, Guangzhou, China) S Shaodong Hong (Department of Medical Oncology, Sun Yat-Sen University Cancer Center, Guangzhou, China)

Abstract

8637 Background: TROP2 antibody–drug conjugate (ADC) has emerged as a promising strategy for advanced non-small cell lung cancer (NSCLC). A trend of enhanced efficacy has been observed in patients with actionable genomic alterations (AGAs), but the validity of AGA status for patient selection remains controversial. Current evidence suggests that endocytosis is a key factor in TROP2 ADC activity. However, systematic analyses of clinicopathological and genetic associations with endocytosis are lacking. This study combined a meta-analysis and omics analyses to identify potential NSCLC populations that respond or are resistant to TROP2 ADC. Methods: For the meta-analysis, we searched for trials of TROP2 ADC in advanced or metastatic NSCLC. Overall survival (OS), progression-free survival (PFS), and objective response rate (ORR) were pooled in the overall population and AGA subgroups. For the omics analysis, given that STK11/KEAP1 mutations are generally mutually exclusive with AGAs and define special subsets, we assessed TROP2 expression and endocytosis activity in three NSCLC categories: AGA-positive (AGA+), AGA–negative/STK11 or KEAP1-mutated (AGA–/SK+), and AGA-negative/STK11 and KEAP1-wild-type (AGA–/SK–). Each NSCLC AGA and key tumor suppressor driver mutation was also evaluated independently. Results: A total of 1,387 NSCLC patients from two randomized clinical trials (TROPION-Lung01 and EVOKE-01) and two single-arm trials (TROPION-Lung05 and KL264-01) were meta-analyzed. TROP2 ADC did not significantly improve OS (HR = 0.89, P = 0.12), PFS (HR = 0.90, P = 0.25), or ORR (OR = 1.68, P = 0.39) compared to docetaxel. The pooled ORR for the TROP2 ADC arm was 30% [18%-42%], with higher rates in AGA+ (43% [35–50%]) and EGFR-mutant subsets (45% [37–54%]). However, there was no significant difference in the advantage of TROP2 ADC over docetaxel between patients with and without AGAs ( P interaction =0.11, 0.51, and 0.79 for OS, PFS, and ORR, respectively). AGA+ tumors exhibited significantly higher TROP2 expression (FDR=0.01) and endocytosis activity (FDR=0.001) than AGA–/SK+ tumors, but no differences were observed between AGA+ and AGA–/SK– tumors. Within AGA– populations, SK– tumors had evidently higher TROP2 expression (FDR=0.0001) and endocytosis activity (FDR=0.01) than SK+ tumors. Among common NSCLC mutations, STK11 mutations showed the lowest levels of both TROP2 expression and endocytosis activity. Conclusions: AGA+ NSCLC tends to be more responsive to TROP2 ADC, but AGA status is not a reliable predictive biomarker for patient selection, likely due to heterogeneity within AGA– population. AGA–/SK+ defines a subgroup with the low TROP2 expression and endocytosis activity that may confer primary resistance to TROP2 ADC. We'll present in vitro experiments and clinical data regarding the primary resistance to TROP2 ADC in SK+ NSCLC at ASCO.

Article Details

Volume / Issue Vol. 43, Issue 16_suppl
Published June 01, 2025
Pages 8637-8637
ISSN 0732-183X
Publisher Lippincott Williams & Wilkins

Journal Info

Journal of Clinical Oncology

Lippincott Williams & Wilkins

ISSN: 0732-183X Health Sciences

Authors (9)

A

Anlin Li

Department of Medical Oncology, Sun Yat-Sen University Cancer Center, Guangzhou, China

H

Hong Lin Zhu

Sun Yat-sen University Cancer Center, Guangzhou, China

K

Kai Wu

BNLMS, College of Chemistry and Molecular Engineering

Z

Zhixin Yu

S

Sitong Liu

Computational Biology Department, School of Computer Science

X

Xuan Yang

L

Li Zhang

Y

Yi-xin Zhou

Sun Yat-sen University Cancer Center, Guangzhou, China

S

Shaodong Hong

Department of Medical Oncology, Sun Yat-Sen University Cancer Center, Guangzhou, China