Emerging role of non-coding RNAs in regulation of t-lymphocyte function

T-lymphocytes (T cells) play a major role in adaptive immunity and current immune checkpoint inhibitor-based cancer treatments. The regulation of their function is complex, and in addition to cytokines, receptors and transcription factors, several non-coding RNAs (ncRNAs) have been shown to affect differentiation and function of T cells. Among these non-coding RNAs, certain small microRNAs (miRNAs) including miR-15a/16-1, miR-125b-5p, miR-99a-5p, miR-128-3p, let-7 family, miR-210, miR-182-5p, miR-181, miR-155 and miR-10a have been well recognized. Meanwhile, IFNG-AS1, lnc-ITSN1-2, lncRNA-CD160, NEAT1, MEG3, GAS5, NKILA, lnc-EGFR and PVT1 are among long non-coding RNAs (lncRNAs) that efficiently influence the function of T cells. Recent studies have underscored the effects of a number of circular RNAs, namely circ_0001806, hsa_circ_0045272, hsa_circ_0012919, hsa_circ_0005519 and circHIPK3 in the modulation of T-cell apoptosis, differentiation and secretion of cytokines. This review summarizes the latest news and regulatory roles of these ncRNAs on the function of T cells, with widespread implications on the pathophysiology of autoimmune disorders and cancer

Evaluation of autoantibodies as predictors of treatment response and immune‐related adverse events during the treatment with immune checkpoint inhibitors: a prospective longitudinal pan‐cancer study

BACKGROUND: The presence of autoantibodies in the serum of cancer patients has been associated with immune‐checkpoint inhibitor (ICI) therapy response and immune‐related adverse events (irAEs). A prospective evaluation of different autoantibodies in different cancer entities is missing. MATERIALS AND METHODS: In this prospective cohort study, we included a pan‐cancer cohort of patients undergoing ICI treatment and measured a comprehensive panel of autoantibodies at treatment start and at the time point of first response evaluation. The presence and induction of autoantibodies (ANA, ENA, myositis, hepatopathy, rheumatoid arthritis) in different cancer entities were assessed and the association between autoantibodies and disease control rate (DCR), objective response rate (ORR), and progression‐free survival (PFS), as well as the development of grade 3 or higher irAEs were evaluated by logistic regression models, cox proportional hazard models, and Kaplan–Meier estimators. RESULTS: Of 44 patients with various cancer entities, neither the presence of any positive autoantibody measurement nor the presence of positive antinuclear antibodies (ANA) [≥1:80] at baseline was associated with the examined clinical endpoints (DCR, ORR, PFS) in univariable and multivariable analyses. After 8–12 weeks of ICI treatment, DCR, ORR, and PFS did not significantly differ between patients with and without any positive autoantibody measurement or positive ANA titers. The frequency of irAEs did not differ depending on autoantibody status of the patients. CONCLUSION: Autoantibodies at treatment initiation or induction after 8–12 weeks of ICI treatment are not associated with treatment efficacy as indicated by DCR, ORR, and PFS or higher grade irAEs

Patterns of peripheral blood B-cell subtypes are associated with treatment response in patients treated with immune checkpoint inhibitors: a prospective longitudinal pan-cancer study

BACKGROUND: Immune checkpoint inhibitors (ICIs) have revolutionized systemic anti-tumor treatments across different types of cancer. Nevertheless, predictive biomarkers regarding treatment response are not routinely established yet. Apart from T-lymphocytes, the humoral immunity of B-lymphocytes is studied to a substantially lesser extent in the respective setting. Thus, the aim of this study was to evaluate peripheral blood B-cell subtypes as potential predictors of ICI treatment response. METHODS: Thirty-nine cancer patients receiving ICI therapy were included into this prospective single-center cohort study. All had a first blood draw at the date before treatment initiation and a second at the time of first response evaluation (after 8-12 weeks). Seven different B-cell subtypes were quantified by fluorescence-activated cell sorting (FACS). Disease control- (DCR) and objective response rate (ORR) were co-primary study endpoints. RESULTS: Overall, DCR was 48.7% and ORR was 25.6%, respectively. At baseline, there was no significant association of any B-cell subtype with neither DCR nor ORR. At the first response evaluation, an increase in the frequency of CD21(-) B-cells was a statistically significant negative predictor of response, both regarding DCR (OR=0.05, 95%CI=0.00-0.67, p=0.024) and ORR (OR=0.09, 95%CI=0.01-0.96, p=0.046). An increase of the frequency of switched memory B-cells was significantly associated with reduced odds for DCR (OR=0.06, 95%CI=0.01-0.70, p=0.025). Patients with an increased frequency of naïve B-cells were more likely to benefit from ICI therapy as indicated by an improved DCR (OR=12.31, 95%CI=1.13-134.22, p=0.039). CONCLUSION: In this study, certain B-cell subpopulations were associated with ICI treatment response in various human cancer types