Abstract
Somatostatin receptor 2 (SSTR2), the most abundant receptor of somatostatin (SST), possesses immunoreactivity and is altered in many cancers. However, the association between SSTR2 and efficacy of immune checkpoint inhibitors (ICIs) has not yet been reported. Immunohistochemistry (IHC) information across 20 cancers was collected from the Human Protein Atlas (HPA) and used to analyze the expression of SSTR2. Immune signatures collected from public databases, such as BioCarta or Reactome, were used to investigate the association between SSTR2 and the tumor microenviroment in the Cancer Genome Atlas (TCGA). Data from cohorts treated with ICIs were collected to assess whether SSTR2 is associated with benefits from ICIs treatment. In the HPA, we found the SSTR2 IHC-positive rate of 13 cancers to be above 50%. Five types of cancer express SSTR2 mildly (positive rate: 25%–50%), while the remaining two types of cancer barely stained SSTR2-positive (positive rate: 0%–24%). In TCGA analysis, immune cell signatures and immune function pathways were enriched in high SSTR2 expression groups in most cancers. In each ICIs treated cohort, patients with high SSTR2 expression experienced numerically superior objective response rate (Braun: 14.8% vs 13.4%, p = 0.85; Gide: 69.4% vs 40.5%, p = 0.025; Mariathasan: 22.4% vs 16.7%, p = 0.233; Miao: 37.5% vs 11.8%; Riaz: 32.0% vs 7.7%, p = 0.067) and overall survival (Braun: HR (95%CI): 0.80 [0.62–1.04], p = 0.80; Gide: HR (95%CI): 0.61 [0.29–1.30], p = 0.20; Mariathasan: HR (95%CI): 0.83 [0.64–1.08], p = 0.16; Miao: HR (95%CI): 0.24 [0.086–0.65], p = 0.0028; Nathanson cohort: HR (95%CI): 0 [0-inf], p = 0.18; Riaz: HR (95%CI): 0.24 [0.086–0.65], p = 0.028) than patients with low SSTR2 expression. In pooled cohort, we found these differences were significant (Pool: 24.6% vs 16.7%, p = 0.0077; HR (95% CI): 0.77 [0.65–0.91], p = 0.0018). Our results suggest that SSTR2 is a potential predictive biomarker for response to ICIs.
Highlights
Immune checkpoint inhibitors (ICIs), which are mainly comprised of anti-programmed cell death-1 (PD-1/ PD-L1) and anti-cytotoxic T lymphocyte-associated antigen 4 (CTLA-4) drugs, have revolutionized the therapeutic landscape for many advanced cancers [1,2,3,4]
By using collected RNA-seq data and clinical information of patients treated with ICIs, we further investigated the association between SSTR2 and the efficacy of ICIs treatment
The clinical use of ICIs has been proven to result in a better prognosis than conventional treatments in multiple types of cancer
Summary
Immune checkpoint inhibitors (ICIs), which are mainly comprised of anti-programmed cell death (ligand)-1 (PD-1/ PD-L1) and anti-cytotoxic T lymphocyte-associated antigen 4 (CTLA-4) drugs, have revolutionized the therapeutic landscape for many advanced cancers [1,2,3,4]. Limited response rate and occasional adverse reactions make it difficult to implement ICIs in clinical practice [5, 6]. Biomarkers are helpful in identifying ICIs-sensitive patients, protecting them from unnecessary adverse reactions and reducing financial burden. Further research regarding predictive biomarkers for ICIs is urgently needed [7, 8]. Recent studies have discovered various predictive biomarkers for ICIs, including PD-L1 immunohistochemistry (IHC), microsatellite instability (MSI), tumor mutation burden (TMB) and multiple gene signatures [9,10,11,12,13,14]. There are limitations to their use in clinical practice. Finding novel predictive biomarkers is beneficial for the clinical practice of ICIs
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
