VISTA and PD-L1 synergistically predict poor prognosis in patients with extranodal natural killer/T-cell lymphoma

Oncoimmunology. 2021 Apr 7;10(1):1907059. doi: 10.1080/2162402X.2021.1907059.

Abstract

Although PD-1/PD-L1 blockade therapy confers salutary effects across cancer types, their efficacy in Extranodal Natural killer/T-cell lymphoma (ENKTCL) patients is limited and unpredictable. Here, we comprehensively evaluated the expression profile of a panel of immune-regulatory makers to identify novel prognostic biomarkers and/or therapeutic targets for this malignancy. Using immunohistochemistry and multiplex immunofluorescence, we found that the expression of VISTA (88.1%) was predominantly in CD68+ macrophages and much higher than PD-L1 expression (68.7%) in ENKTCL. B7-H4 and HHLA2 proteins were not detected in ENKTCL. B7-H3 was expressed in minority of ENKTCL patients (13.7%) and mainly colocalized with CD31. A close correlation was detected between VISTA and PD-L1, but they were not co-expressed in the same cells. High expressions of VISTA or PD-L1 were significantly associated with detrimental clinicopathological characteristics, dismal prognosis, and high density of CD8+ TILs, and high VISTA expression was also significantly associated with high density of Foxp3+ TILs. VISTA combined with PD-L1 was an independent prognostic factor for PFS and OS. Moreover, the patients with high VISTA showed a poor response to PD-1 blockades in ENKTCL. In conclusion, these findings provide a rationale for VISTA as an ideal immunotherapeutic target next to PD-L1 for ENKTCL.

Keywords: Natural killer/t-cell lymphoma; PD-L1; antitumor immunity; immune checkpoint; ✚-vista.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • B7 Antigens
  • B7-H1 Antigen*
  • Biomarkers, Tumor
  • Humans
  • Immunoglobulins
  • Killer Cells, Natural
  • Lymphoma, T-Cell*
  • Prognosis

Substances

  • B7 Antigens
  • B7-H1 Antigen
  • Biomarkers, Tumor
  • HHLA2 protein, human
  • Immunoglobulins
  • VSIR protein, human

Grants and funding

This study was supported by the National Science & Technology Major Project (2017ZX09304021), the National Science Foundation of China (81970176 and 82072827) and Guangdong Basic and Applied Basic Research Foundation (2021B1515020009 and 2020A1515010888); National Natural Science Foundation of China [82072827]; National Natural Science Foundation of China [81970176].