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Abstract Background Immunotherapy, especially immune checkpoint inhibition, has provided powerful tools against cancer. We aimed to detect the expression of common immune checkpoints and evaluate their prognostic values in nasopharyngeal carcinoma (NPC). Methods The expression of 9 immune checkpoints consistent with 13 features was detected in the training cohort (n = 208) by immunohistochemistry and quantified by computational pathology. Then, the LASSO cox regression model was used to construct an immune checkpoint-based signature (ICS), which was validated in a validation cohort containing 125 patients. Results High positive expression of PD-L1 and B7-H4 was observed in tumour cells (TCs), whereas PD-L1, B7-H3, B7-H4, IDO-1, VISTA, ICOS and OX40 were highly expressed in tumour-associated immune cells (TAICs). Eight of the 13 immune features were associated with patient overall survival, and an ICS classifier consisting of 5 features (B7-H3TAIC, IDO-1TAIC, VISTATAIC, ICOSTAIC, and LAG3TAIC) was established. Patients with high-risk scores in the training cohort had shorter overall (P

Abstract Recent phase 1–2 trials reported manageable safety profiles and promising antitumor activities of anti-PD-1 drugs (pembrolizumab, nivolumab, camrelizumab and JS001) with/without chemotherapy in recurrent/metastatic nasopharyngeal carcinoma (RM-NPC), however head-to-head comparison among these regimens is lacking. We aimed to comprehensively compare the efficacy and safety of different anti-PD-1 drugs, standard chemotherapy, and their combination therapy in RM-NPC. Adverse event (AE) and objective response rate (ORR) were assessed. The pooled incidence rates of grade 1–5/3–5 AEs were 74.1%/29.6, 54.2%/17.4, 92.3%/24.5, 96.8%/16.1, 91.2%/42.8, and 100%/87.9% for pembrolizumab, nivolumab, JS001, camrelizumab, chemotherapy and camrelizumab+chemotherapy, respectively, which suggested that nivolumab and pembrolizumab exhibited the optimal safety regarding grade 1–5 AEs whereas camrelizumab and nivolumab regarding grade 3–5 AEs. As second- or later-line therapy, ORR was higher with camrelizumab (34.1%), followed by pembrolizumab (26.3%), JS001 (23.3%), and nivolumab (19.0%); whereas ORR with first-line nivolumab reached 40%. Additionally, first-line camrelizumab+chemotherapy achieved a dramatically higher ORR than that with chemotherapy alone (90.9% vs. 64.1%). Pooled ORR was 28.4 and 17.4% for PD-L1–positive and PD-L1–negative patients, respectively (P = 0.11). Here, we represent preliminary evidence for the comparative safety and efficacy of existing anti-PD-1 agents with/without chemotherapy in RM-NPC, which indicated that camrelizumab has the least toxicity profile and merits future investigation. Our findings might provide insights into the future design of immunotherapy trials in RM-NPC.

Background Metabolomics has the characteristics of terminal effects and reflects the physiological state of biological diseases more directly. Several current biomarkers of multiple omics were revealed to be associated with immune-related adverse events (irAEs) occurrence. However, there is a lack of reliable metabolic biomarkers to predict irAEs. This study aims to explore the potential metabolic biomarkers to predict risk of irAEs and to investigate the association of plasma metabolites level with survival in patients with lung cancer receiving PD-1/PD-L1 inhibitor treatment.Methods The study collected 170 plasmas of 85 patients with lung cancer who received immune checkpoint inhibitors (ICIs) treatment. 58 plasma samples of 29 patients with irAEs were collected before ICIs treatment and at the onset of irAEs. 112 plasma samples of 56 patients who did not develop irAEs were collected before ICIs treatment and plasma matched by treatment cycles to onset of irAEs patients. Untargeted metabolomics analysis was used to identify the differential metabolites before initiating ICIs treatment and during the process that development of irAEs. Kaplan-Meier curves analysis was used to detect the associations of plasma metabolites level with survival of patients with lung cancer.Results A total of 24 differential metabolites were identified to predict the occurrence of irAEs. Baseline acylcarnitines and steroids levels are significantly higher in patients with irAEs, and the model of eight acylcarnitine and six steroid metabolites baseline level predicts irAEs occurrence with area under the curve of 0.91. Patients with lower concentration of baseline decenoylcarnitine(AcCa(10:1) 2, decenoylcarnitine(AcCa(10:1) 3 and hexanoylcarnitine(AcCa(6:0) in plasma would have better overall survival (OS). Moreover, 52 differential metabolites were identified related to irAEs during ICIs treatment, dehydroepiandrosterone sulfate, corticoserone, cortisol, thyroxine and sphinganine 1-phaosphate were significantly decreased in irAEs group while oxoglutaric acid and taurocholic acid were significantly increased in irAEs group.Conclusions High levels of acylcarnitines and steroid hormone metabolites might be risk factor to development of irAEs, and levels of decenoylcarnitine (AcCa(10:1) 2, decenoylcarnitine (AcCa(10:1) 3 and hexanoylcarnitine (AcCa(6:0) could be used to predict OS for patients with lung cancer received ICIs treatment.