Features of tumor-microenvironment images predict targeted therapy survival benefit in patients with EGFR-mutant lung cancer

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Abstract

Tyrosine kinase inhibitors (TKIs) targeting epidermal growth factor receptor (EGFR) are effective for many patients with lung cancer with EGFR mutations. However, not all patients are responsive to EGFR TKIs, including even those harboring EGFR-sensitizing mutations. In this study, we quantified the cells and cellular interaction features of the tumor microenvironment (TME) using routine H&E-stained biopsy sections. These TME features were used to develop a prediction model for survival benefit from EGFR TKI therapy in patients with lung adenocarcinoma and EGFR-sensitizing mutations in the Lung Cancer Mutation Consortium 1 (LCMC1) and validated in an independent LCMC2 cohort. In the validation data set, EGFR TKI treatment prolonged survival in the predicted-to-benefit group but not in the predicted-not-to-benefit group. Among patients treated with EGFR TKIs, the predicted-to-benefit group had prolonged survival outcomes compared with the predicted not-to-benefit group. The EGFR TKI survival benefit positively correlated with tumor-tumor interaction image features and negatively correlated with tumor-stroma interaction. Moreover, the tumor-stroma interaction was associated with higher activation of the hepatocyte growth factor/MET-mediated PI3K/AKT signaling pathway and epithelial-mesenchymal transition process, supporting the hypothesis of fibroblast-involved resistance to EGFR TKI treatment.

Authors

Shidan Wang, Ruichen Rong, Donghan M. Yang, Junya Fujimoto, Justin A. Bishop, Shirley Yan, Ling Cai, Carmen Behrens, Lynne D. Berry, Clare Wilhelm, Dara Aisner, Lynette Sholl, Bruce E. Johnson, David J. Kwiatkowski, Ignacio I. Wistuba, Paul A. Bunn Jr., John Minna, Guanghua Xiao, Mark G. Kris, Yang Xie