Abstract
BACKGROUND: Adoptive T cell therapy (ACT) has shown great promise in melanoma, with over 50 % response rate in patients where autologous tumor-reactive tumor-infiltrating lymphocytes (TIL) can be cultured and expanded. A major limitation of ACT is the inability to generate or expand autologous tumor-reactive TIL in 25-45 % of patients tested. Methods that successfully identify tumors that are not suitable for TIL generation by standard methods would eliminate the costs of fruitless expansion and enable these patients to receive alternate therapy immediately. METHODS: Multispectral fluorescent immunohistochemistry with a panel including CD3, CD8, FoxP3, CD163, PD-L1 was used to analyze the tumor microenvironment in 17 patients with melanoma among our 36-patient cohort to predict successful TIL generation. Additionally, we compared tumor fragments and enzymatic digestion of tumor samples for efficiency in generating tumor-reactive TIL. RESULTS: Tumor-reactive TIL were generated from 21/36 (58 %) of melanomas and for 12/13 (92 %) tumors where both enzymatic and fragment methods were compared. TIL generation was successful in 10/13 enzymatic preparations and in 10/13 fragment cultures; combination of both methods resulted in successful generation of autologous tumor-reactive TIL in 12/13 patients. In 17 patients for whom tissue blocks were available, IHC analysis identified that while the presence of CD8(+) T cells alone was insufficient to predict successful TIL generation, the CD8(+) to FoxP3(+) ratio was predictive with a positive-predictive value (PPV) of 91 % and negative-predictive value (NPV) of 86 %. Incorporation of CD163+ macrophage numbers and CD8:PD-L1 ratio did not improve the PPV. However, the NPV could be improved to 100 % by including the ratio of CD8(+):PD-L1(+) expressing cells. CONCLUSION: This is the first study to apply 7-color multispectral immunohistochemistry to analyze the immune environment of tumors from patients with melanoma. Assessment of the data using unsupervised hierarchical clustering identified tumors from which we were unable to generate TIL. If substantiated, this immune profile could be applied to select patients for TIL generation. Additionally, this biomarker profile may also indicate a pre-existing immune response, and serve as a predictive biomarker of patients who will respond to checkpoint blockade. We postulate that expanding the spectrum of inhibitory cells and molecules assessed using this technique could guide combination immunotherapy treatments and improve response rates.