Clinicopathological relevance of tumor expression of NK group 2 member D ligands in resected non-small cell lung cancer

// Riki Okita 1 , Ai Maeda 1 , Katsuhiko Shimizu 1 , Yuji Nojima 1 , Shinsuke Saisho 1 and Masao Nakata 1 1 Department of General Thoracic Surgery, Kawasaki Medical School, Kurashiki, Japan Correspondence to: Riki Okita, email: riki0716okita@yahoo.co.jp Keywords: non-small cell lung cancer (NSCLC); UL16-binding protein (ULBP); prognostic factor; MICA/B (MHC class I chain-related molecule A and B); NK cell Received: June 17, 2019     Accepted: September 24, 2019     Published: November 26, 2019 ABSTRACT UL16-binding protein (ULBP) 1-6 and MHC class I chain-related molecule A and B (MICA/B) are NK group 2, member D (NKG2D) ligands, which are specifically expressed in infected or transformed cells and are recognized by NK cells via NKG2D-NKG2D ligand interactions. We previously reported that MICA/B overexpression predicted improved clinical outcomes in patients with resected non-small cell lung cancer (NSCLC). However, the clinicopathological features and prognostic significance of ULBPs in NSCLC remain unclear. Here,ULBP1-6 expression was evaluated based on immunohistochemistry of 91 NSCLC samples from patients following radical surgery. ULBPs were expressed by the majority of NSCLC. Either ULBP1 or ULBP2/5/6 overexpression was associated with squamous-cell carcinoma histology, whereas ULBP4 overexpression was associated with younger age and adenocarcinoma histology. Although overexpression of ULBP1-6 did not impact clinical outcomes in NSCLC patients, integrative profiling with cluster analysis classified patients into 3 subgroups based on the expression pattern of NKG2D ligands. The subgroup characterized by ULBP1 or ULBP2/5/6 high expressing but ULBP4 low expressing tumors showed poor overall survival. Taken together with previous results, NSCLC histological subtype strongly correlates with NKG2D ligands expression pattern. NKG2D ligands expression levels assessed by multiple immune parameters could predict clinical outcomes of patients with NSCLC.