Abstract

Optimizing immune checkpoint inhibitor (ICI) therapy may require identification of co-targetable checkpoint pathways via immune profiling. Herein, we analyzed the transcriptomic expression and clinical correlates of V-domain immunoglobulin suppressor of T-cell activation (VISTA), a promising targetable checkpoint. RNA sequencing was carried out on 514 tissues reflecting diverse advanced/metastatic cancers. Expression of eight immune checkpoint markers [lymphocyte-activation gene 3 (LAG-3), tumor necrosis factor receptor superfamily 14 (TNFRSF14), programmed cell death protein 1 (PD-1), programmed death-ligand 1 (PD-L1), programmed death-ligand 2 (PD-L2), B- and T-lymphocyte attenuator (BTLA), T-cell immunoglobulin and mucin domain-containing protein 3 (TIM-3), cytotoxic T-lymphocyte antigen 4 (CTLA-4)], in addition to VISTA, was analyzed, along with clinical outcomes. High VISTA RNA expression was observed in 32% of tumors (66/514) and was the most common highly expressed checkpoint among the nine assessed. High VISTA expression was independently correlated with high BTLA, TIM-3, and TNFRSF14, and with a diagnosis of pancreatic, small intestine, and stomach cancer. VISTA transcript levels did not correlate with overall survival (OS) from metastatic/advanced disease in the pan-cancer cohort or with immunotherapy outcome (progression-free survival and OS from the start of ICI) in 217 ICI-treated patients. However, in ICI-treated pancreatic cancer patients (n = 16), median OS was significantly shorter (from immunotherapy initiation) for the high- versus not-high-VISTA groups (0.28 versus 1.21 years) (P= 0.047); in contrast, VISTA levels were not correlated with OS in 36 pancreatic cancer patients who did not receive ICI. High VISTA expression correlates with high BTLA, TIM-3, and TNFRSF14 checkpoint-related molecules and with poorer post-immunotherapy survival in pancreatic cancer, consistent with prior literature indicating that VISTA is prominently expressed on CD68+ macrophages in pancreatic cancers and requiring validation in larger prospective studies. Immunomic analysis may be important for individualized precision immunotherapy.

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