Prospective analysis of adoptive TIL therapy in patients with metastatic melanoma: Response, impact of anti-CTLA4, and biomarkers to predict clinical outcome

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Abstract

Purpose: Adoptive cell therapy (ACT) using tumor-infiltrating lymphocytes (TIL) has consistently demonstrated clinical efficacy in metastatic melanoma. Recent widespread use of checkpoint blockade has shifted the treatment landscape, raising questions regarding impact of these therapies on response to TIL and appropriate immunotherapy sequence. Patients and Methods: Seventy-four metastatic melanoma patients were treated with autologous TIL and evaluated for clinical response according to irRC, overall survival, and progression-free survival. Immunologic factors associated with response were also evaluated. Results: Best overall response for the entire cohort was 42%; 47% in 43 checkpoint-na€ve patients, 38% when patients were exposed to anti-CTLA4 alone (21 patients) and 33% if also exposed to anti-PD1 (9 patients) prior to TIL ACT. Median overall survival was 17.3 months; 24.6 months in CTLA4-na€ve patients and 8.6 months in patients with prior CTLA4 blockade. The latter patients were infused with fewer TIL and experienced a shorter duration of response. Infusion of higher numbers of TIL with CD8 predominance and expression of BTLA correlated with improved response in anti-CTLA4 na€ve patients, but not in anti-CTLA4 refractory patients. Baseline serum levels of IL9 predicted response to TIL ACT, while TIL persistence, tumor recognition, and mutation burden did not correlate with outcome. Conclusions: This study demonstrates the deleterious effects of prior exposure to anti-CTLA4 on TIL ACT response and shows that baseline IL9 levels can potentially serve as a predictive tool to select the appropriate sequence of immunotherapies.

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Forget, M. A., Haymaker, C., Hess, K. R., Meng, Y. J., Creasy, C., Karpinets, T., … Bernatchez, C. (2018). Prospective analysis of adoptive TIL therapy in patients with metastatic melanoma: Response, impact of anti-CTLA4, and biomarkers to predict clinical outcome. Clinical Cancer Research, 24(18), 4416–4428. https://doi.org/10.1158/1078-0432.CCR-17-3649

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