Major Histocompatibility Complex Class I-Related Chain A (MICA) allelic variants associate with susceptibility and prognosis of gastric cancer

Abstract

Gastric cancer (GC) is the fifth most prevalent type of cancer worldwide. Gastric tumor cells express MICA protein, a ligand to NKG2D receptor that triggers natural killer (NK) cells effector functions for early tumor elimination. MICA gene is highly polymorphic, thus originating alleles that encode protein variants with a controversial role in cancer. The main goal of this work was to study MICA gene polymorphisms and their relationship with the susceptibility and prognosis of GC. Fifty patients with GC and 50 healthy volunteers were included in this study. MICA alleles were identified using Sanger sequencing methods. The analysis of MICA gene sequence revealed 13 MICA sequences and 5 MICA-short tandem repeats (STR) alleles in the studied cohorts We identified MICA*002 (*A9) as the most frequent allele in both, patients and controls, followed by MICA*008 allele (*A5.1). MICA*009/049 allele was significantly associated with increased risk of GC (OR: 5.11 [95% CI: 1.39-18.74], p = 0.014). The analysis of MICA-STR alleles revealed a higher frequency of MICA*A5 in healthy individuals than GC patients (OR = 0.34 [95% CI: 0.12-0.98], p = 0.046). Survival analysis after gastrectomy showed that patients with MICA*002/002 or MICA*002/004 alleles had significantly higher survival rates than those patients bearing MICA*002/008 (p = 0.014) or MICA*002/009 (MICA*002/049) alleles (p = 0.040). The presence of threonine in the position MICA-181 (MICA*009/049 allele) was more frequent in GC patients than controls (p = 0.023). Molecular analysis of MICA-181 showed that the presence of threonine provides greater mobility to the protein than arginine in the same position (MICA*004), which could explain, at least in part, some immune evasion mechanisms developed by the tumor. In conclusion, our findings suggest that the study of MICA alleles is crucial to search for new therapeutic approaches and may be useful for the evaluation of risk and prognosis of GC and personalized therapy.