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Background: Immunotherapy provides new hope to individuals with small cell lung cancer (SCLC). Predicting biomarkers for clinical effects is crucial for SCLC patients receiving programed death-ligand 1 (PD-L1) inhibitor treatment., Aim: The aim of this study was to clarify the value of serum lipids as predictors of immune related adverse events (irAEs) and the anti-tumour effects in SCLC patients who received PD-L1 inhibitors as first-line treatment., Method: This study included patients with SCLC who received at least one cycle of PD-L1inhibitors at Shanghai Pulmonary Hospital from August 2020 to December 2023. We collected the clinical data of the SCLC patients, including basic information and serum lipid levels, before immunotherapy., Results: The irAEs rate was 16.1% of 124 enrolled patients. In multivariate analysis, the triglyceride (TG)/high-density lipoprotein cholesterol (HDL-C) ratio was an independent predictor of irAEs (p = 0.045). Tumour response analysis indicated that the objective response rate (ORR) was 43.4% and the disease control rate (DCR) was 79.5%. Seventy-seven patients experienced any progression-free survival (PFS) event. The median PFS was longer in the HDL-C-high group (10.03 months) than in the HDL-C-low group (6.67 months) (p = 0.043). In Cox regression analysis, the serum HDL-C level was an independent predictor of PFS (p = 0.002). For patients of the high TG/HDL-C ratio, the ORR significantly differed between patients who suffered from any irAEs and those who did not (p = 0.0139)., Conclusion: This study found that serum lipid levels might predict the responses to anti-PD-L1 as first-line treatment for SCLC., Competing Interests: Conflicts of interest All authors declare no conflicts of interest associated with this manuscript., (© 2024. The Author(s).)

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., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Immune checkpoint inhibitors (ICIs) targeting programmed cell death 1/programmed cell death ligand-1 (PD-1/PD-L1) have significantly prolonged the survival of advanced/metastatic patients with lung cancer. However, only a small proportion of patients can benefit from ICIs, and clinical management of the treatment process remains challenging. Glycosylation has added a new dimension to advance our understanding of tumor immunity and immunotherapy. To systematically characterize anti-PD-1/PD-L1 immunotherapy-related changes in serum glycoproteins, a series of serum samples from 12 patients with metastatic lung squamous cell carcinoma (SCC) and lung adenocarcinoma (ADC), collected before and during ICIs treatment, are firstly analyzed with mass-spectrometry-based label-free quantification method. Second, a stratification analysis is performed among anti-PD-1/PD-L1 responders and non-responders, with serum levels of glycopeptides correlated with treatment response. In addition, in an independent validation cohort, a large-scale site-specific profiling strategy based on chemical labeling is employed to confirm the unusual characteristics of IgG N-glycosylation associated with anti-PD-1/PD-L1 treatment. Unbiased label-free quantitative glycoproteomics reveals serum levels' alterations related to anti-PD-1/PD-L1 treatment in 27 out of 337 quantified glycopeptides. The intact glycopeptide EEQFN 177 STYR (H3N4) corresponding to IgG4 is significantly increased during anti-PD-1/PD-L1 treatment (FC=2.65, P =0.0083) and has the highest increase in anti-PD-1/PD-L1 responders (FC=5.84, P =0.0190). Quantitative glycoproteomics based on protein purification and chemical labeling confirms this observation. Furthermore, obvious associations between the two intact glycopeptides (EEQFN 177 STYR (H3N4) of IgG4, EEQYN 227 STFR (H3N4F1) of IgG3) and response to treatment are observed, which may play a guiding role in cancer immunotherapy. Our findings could benefit future clinical disease management.

Background: Receptor activator of nuclear factor kappa-B ligand (RANKL) can directly promote tumor growth and indirectly support tumor immune evasion by altering the tumor microenvironment and immune cell responses. This study aimed to assess the prognostic significance of soluble RANKL in patients with advanced non-small cell lung cancer (NSCLC) receiving programmed cell death 1 (PD1)/programmed death-ligand 1 (PDL1) checkpoint inhibitor therapy., Methods: Plasma RANKL levels were measured in 100 patients with advanced NSCLC without bone metastases undergoing monotherapy with PD1/PDL1 checkpoint inhibitors. To establish the optimal cut-off value, we used the Cutoff Finder package in R. Survival curves for four distinct patient groups, according to their RANKL and PDL1 levels (high or low), were generated using the Kaplan-Meier method and compared with the log-rank test. The Cox regression model calculated HRs and 95% CIs for overall survival (OS) and progression-free survival (PFS)., Results: The optimal RANKL cut-off was established at 280.4 pg/mL, categorizing patients into groups with high or low RANKL levels. A significant association was observed between increased RANKL concentrations and decreased survival rates at 24 months, only within the subgroup expressing high levels of PDL1 (p=0.002). Additionally, low RANKL levels in conjunction with elevated PDL1 expression correlated with improved PFS (median 22 months, 95% CI 6.70 to 50 vs median 4 months, 95% CI 3.0 to 7.30, p=0.009) and OS (median 26 months, 95% CI 20 to not reached vs median 7 months, 95% CI 6 to 13, p=0.003), indicating RANKL's potential as an indicator of adverse prognosis in these patients. Multivariate analysis identified RANKL as an independent negative prognostic factor for both PFS and OS, regardless of other clinicopathological features., Conclusion: These results highlight the prognostic and predictive value of RANKL specifically in patients with high PDL1 expression., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Immune checkpoint inhibitors (ICIs) are effective for non-small cell lung cancer (NSCLC) treatment, but the response rate remains low. Programmed cell death ligand 1 (PD-L1) in peripheral blood, including soluble form (sPD-L1), expression on circulating tumor cells (CTCs PD-L1) and exosomes (exoPD-L1), are minimally invasive and promising markers for patient selection and management, but their prognostic significance remains inconclusive. Here, we performed a meta-analysis for the prognostic value of PD-L1 blood markers in NSCLC patients treated with ICIs., Methods: Eligible studies were obtained by searching PubMed, EMBAS, Web of Science, and Cochrane Library prior to November 30, 2023. The associations between pre-treatment, post-treatment and dynamic changes of blood PD-L1 levels and progression-free survival (PFS)/over survival (OS) were analyzed by estimating hazard ratio (HR) and 95% confidence interval (CI)., Results: A total of 26 studies comprising 1606 patients were included. High pre- or post-treatment sPD-L1 levels were significantly associated with worse PFS (pre-treatment: HR=1.49, 95%CI 1.13-1.95; post-treatment: HR=2.09, 95%CI 1.40-3.12) and OS (pre-treatment: HR=1.83, 95%CI 1.25-2.67; post-treatment: HR=2.60, 95%CI 1.09-6.20, P=0.032). High pre-treatment exoPD-L1 levels predicted a worse PFS (HR=4.24, 95%CI 2.82-6.38, P<0.001). Pre-treatment PD-L1 + CTCs tended to be correlated with prolonged PFS (HR=0.63, 95%CI 0.39-1.02) and OS (HR=0.58, 95%CI 0.36-0.93). Patients with up-regulated exoPD-L1 levels, but not sPD-L1, after ICIs treatment had significantly favorable PFS (HR=0.36, 95%CI 0.23-0.55) and OS (HR=0.24, 95%CI 0.08-0.68)., Conclusion: PD-L1 blood markers, including sPD-L1, CTCs PD-L1 and exoPD-L1, can effectively predict prognosis, and may be potentially utilized for patient selection and treatment management for NSCLC patients receiving ICIs., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Zhang, Chang, Liu, Tian and Yu.)

Immune checkpoint inhibitors (ICIs) bring prognostic benefits to patients with malignancies. However, there is a substantial number of patients whose lesions are not improved by ICIs. In addition, ICIs may cause immune-related adverse events (irAEs), which could lead to an unfavorable prognosis with fatal consequences. Therefore, we conducted a retrospective study to evaluate the utility of circulating sPD-L1 (soluble programmed cell death 1 ligand 1) as a biomarker in patients with advanced melanoma treated with anti-PD-1 (programmed cell death 1 protein) antibodies. Sera from 31 consecutive patients were prospectively collected before and after anti-PD-1 antibody treatment and the serum level of sPD-L1 was evaluated. We found that high sPD-L1 levels before treatment were associated with better prognosis, and this association was observed only in patients with a low tumor burden. We also found that sPD-L1 levels were elevated in patients who developed severe irAEs after treatment, and the patients with severe irAEs had significantly higher fluctuations in sPD-L1 (delta sPD-L1) than those without severe irAEs. Our study suggests that serum sPD-L1 level is a useful biomarker to predict tumor response and irAE development in patients with advanced melanoma treated with anti-PD-1 antibodies., (© 2024 Japanese Dermatological Association.)

Objective: Immune checkpoint inhibitors (ICIs), specifically targeting the programmed cell death protein-1 or its ligand (PD-1/PD-L1), have been extensively used in the treatment of a spectrum of malignancies, although the predictive biomarkers remain to be elucidated. This study aims to investigate the association between baseline circulating levels of cytokines and the creatinine/cystatin C ratio (CCR) with the treatment outcomes of ICIs in patients with advanced cancer., Methods: The pre-treatment circulating levels of 10 cytokines (PD-L1, CTLA4, CXCL10, LAG3, HGF, CCL2, MIG, GRANB, IL-18, and IL-6) were measured via automated capillary-based immunoassay platform in the serum of 65 advanced cancer patients treated with anti-PD-1/PD-L1-based systemic therapy and 10 healthy volunteers. The levels of cytokines and CCR were quantified and categorized into high and low groups based on the median value. The associations of serum cytokines and CCR with response to treatment, survival, and immune-related adverse events were assessed., Results: Elevated circulating levels of 6 cytokines (PD-L1, CXCL10, HGF, CCL2, MIG, and IL-6) were observed in cancer patients compared with that in healthy volunteers. The correlation coefficients between cytokines, CCR and nutritional risk index were also calculated. In the cancer cohort (N = 65), low circulating HGF (P = 0.023, P = 0.029), low IL-6 (P = 0.002, P < 0.001), and high CCR (P = 0.031, P = 0.008) were associated with significantly improved progression-free survival (PFS) and overall survival (OS). Multi-variable COX analyses adjusted for clinicopathological factors revealed that low HGF, low IL-6, and high CCR were independent favorable prognostic factors for PFS (P = 0.028, P = 0.010, and P = 0.015, respectively) and OS (P = 0.043, P = 0.003, and P = 0.026, respectively). Grade 2 irAEs occurred more frequently in patients with low levels of circulating CCL2 and LAG3., Conclusions: Pre-treatment circulating levels of serum IL-6, HGF, and CCR may serve as independent predictive and prognostic biomarkers in advanced cancer patients treated with ICIs-based systemic therapy. These findings might help to identify potential patients who would benefit from these therapies., (© 2024. The Author(s).)

Immune checkpoints inhibitors (ICIs) have markedly improved the therapeutic management of advanced NSCLC and, more recently, they have demonstrated efficacy also in the early-stage disease. Despite better survival outcomes with ICIs compared to standard chemotherapy, a large proportion of patients can derive limited clinical benefit from these agents. So far, few predictive biomarkers, including the programmed death-ligand 1 (PD-L1), have been introduced in clinical practice. Therefore, there is an urgent need to identify novel biomarkers to select patients for immunotherapy, to improve efficacy and avoid unnecessary toxicity. A deeper understanding of the mechanisms involved in antitumor immunity and advances in the field of liquid biopsy have led to the identification of a wide range of circulating biomarkers that could potentially predict response to immunotherapy. Herein, we provide an updated overview of these circulating biomarkers, focusing on emerging data from clinical studies and describing modern technologies used for their detection., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Umberto Malapelle has received personal fees, as consultant and/or speaker bureau, from Boehringer Ingelheim, Roche, MSD, Amgen, Thermo Fisher Scientific, Eli Lilly, Diaceutics, GSK, Merck and AstraZeneca, Janssen, Diatech, Novartis and Hedera, unrelated to the current work. Francesco Pepe has received personal fees, as consultant and/or speaker bureau, from Menarini, unrelated to the current work. Nicola Silvestris: advisory board for AstraZeneca, Eisai, Roche, Sanitanova, unrelated to the current work. Mariacarmela Santarpia has received advisory board and/or speaker bureau honoraria from AstraZeneca, BMS, Novartis, unrelated to the current work. The other authors have no disclosures to declare., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Introduction: Anti-PD-1/PD-L1 inhibitors therapy has become a promising treatment for hepatocellular carcinoma (HCC), while the therapeutic efficacy varies significantly among effects for individual patients are significant difference. Unfortunately, specific predictive biomarkers indicating the degree of benefit for patients and thus guiding the selection of suitable candidates for immune therapy remain elusive.no specific predictive biomarkers are available indicating the degree of benefit for patients and thus screening the preferred population suitable for the immune therapy., Methods: Ultra-high-pressure liquid chromatography-mass spectrometry (UHPLC-MS) considered is an important method for analyzing biological samples, since it has the advantages of high rapid, high sensitivity, and high specificity. Ultra-high-pressure liquid chromatography-mass spectrometry (UHPLC-MS) has emerged as a pivotal method for analyzing biological samples due to its inherent advantages of rapidity, sensitivity, and specificity. In this study, potential metabolite biomarkers that can predict the therapeutic effect of HCC patients receiving immune therapy were identified by UHPLC-MS., Results: A partial least-squares discriminant analysis (PLS-DA) model was established using 14 glycerophospholipid metabolites mentioned above, and good prediction parameters (R2 = 0.823, Q2 = 0.615, prediction accuracy = 0.880 and p < 0.001) were obtained. The relative abundance of glycerophospholipid metabolite ions is closely related to the survival benefit of HCC patients who received immune therapy., Discussion: This study reveals that glycerophospholipid metabolites play a crucial role in predicting the efficacy of immune therapy for HCC., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Liu, Shi, Su, Zheng, Xing, Zhang, Wang, Chen and Feng.)

Immune checkpoint therapy targeting the PD-1/PD-L1 axis is a potentially novel development in anticancer therapy and has been applied to clinical medicine. However, there are still some problems, including a relatively low response rate, innate mechanisms of resistance against immune checkpoint blockades, and the absence of reliable biomarkers to predict responsiveness. In this study of in vitro and in vivo models, we demonstrate that PD-L1-vInt4, a splicing variant of PD-L1, plays a role as a decoy in anti-PD-L1 antibody treatment. First, we showed that PD-L1-vInt4 was detectable in clinical samples and that it was possible to visualize the secreting variants with IHC. By overexpressing the PD-L1-secreted splicing variant on MC38 cells, we observed that an immune-suppressing effect was not induced by their secretion alone. We then demonstrated that PD-L1-vInt4 secretion resisted anti-PD-L1 antibody treatment, compared with WT PD-L1, which was explicable by the PD-L1-vInt4's decoying of the anti-PD-L1 antibody. The decoying function of PD-L1 splicing variants may be one of the reasons for cancers being resistant to anti-PD-L1 therapy. Measuring serum PD-L1 levels might be helpful in deciding the therapeutic strategy.

Background: We performed a meta-analysis to evaluate the association between soluble PD-L1 (sPD-L1) and survival outcomes and treatment response in lung cancer. Methods & methods: Eligible studies were obtained by searching PubMed, EMBASE and Web of Science. Pooled effect estimates were calculated for overall survival (OS), progression-free survival (PFS) and objective response rate (ORR). Results: Twelve eligible studies with 1188 lung cancer patients were included. High sPD-L1 was significantly associated with worse OS (hazard ratio [HR] = 2.20; 95% CI: 1.59-3.05; p < 0.001) and PFS (HR = 2.42; 95% CI: 1.72-3.42; p < 0.001) in patients treated with immune checkpoint inhibitors (ICIs). Meanwhile, high sPD-L1 predicted worse OS (HR = 1.60; 95% CI: 1.31-1.96; p < 0.001) and lower ORR (odds ratio = 0.52; 95% CI: 0.35-0.80; p = 0.002) in patients treated with non-ICI therapies. Conclusion: sPD-L1 is a potential predictive biomarker of lung cancer.

Circulating soluble programmed death-1 ligand (sPD-L1) is measurable in the serum of cancer patients. This study aimed to investigate the significance of sPD-L1 in cancer patients receiving immune checkpoint inhibitor therapy. Blood samples were obtained before and after immune checkpoint inhibitor therapy (January 2015 to January 2019). The study cohort consisted of 128 patients who were diagnosed with non-small cell lung cancer (n = 50), melanoma (n = 31), small cell lung cancer (n = 14), urothelial carcinoma (n = 13), and other cancers (n = 20). Patients with a high level (> 11.0 pg/μL) of sPD-L1 were more likely to exhibit progressive disease compared with those with a low level (41.8% versus 20.7%, p = 0.013). High sPD-L1 was also associated with worse prognosis; the median PFS was 2.9 (95% confidence interval [CI] 2.1-3.7) months versus 6.3 (95% CI 3.0-9.6) months (p = 0.023), and the median OS was 7.4 (95% CI 6.3-8.5) months versus 13.3 (95% CI 9.2-17.4) months (p = 0.005). In the multivariate analyses, high sPD-L1 was an independent prognostic factor for both decreased PFS (HR 1.928, p = 0.038) and OS (HR 1.788, p = 0.004). sPD-L1 levels did not correlate with tissue PD-L1 expression. However, sPD-L1 levels were positively correlated with neutrophil to lymphocyte ratios and negatively correlated with both the proportion and the total number of lymphocytes. We found that high pretreatment sPD-L1 levels were associated with progressive disease and were an independent prognostic factor predicting lower PFS and OS in these patients., (© 2021. The Author(s).)

Immunotherapy has markedly improved the survival rate of patients with non-small cell lung cancer (NSCLC) and has introduced a new era in lung cancer treatment. Although some patients achieve durable responses to checkpoint blockade, not all experience such benefits, and some suffer from significant immunotoxicities. Thus, it is crucial to identify potential biomarkers suitable for screening the population that may benefit from immunotherapy. Based on the current clinical trials, the aim of the present study was to review the biomarkers for immune checkpoint inhibition that may have the potential to predict the response to immunotherapy in patients with lung cancer. A non-systematic literature review was done. We searched for eligible randomized controlled trials (RCTs) from PubMed, Embase, and the Cochrane Central Register of Controlled Trials from January 2015 to January 2021. The keywords included biomarkers, immunotherapy, immune checkpoint inhibition, programmed death ligand 1 (PD-L1), and non-small cell lung cancer. Additional biomarkers beyond PD-L1 that have been shown to have predictive capacity include tumor mutational burden, microsatellite instability, lung immune prognostic index, gut microbiome, and certain alterations in genes (eg, STK11 deletion, LKB1 kinase mutation, MDM2/4 amplification) that confer immunoresistance. The biomarkers reviewed in this article could help us better select the appropriate immunotherapy treatment for patients with NSCLC., (Copyright © 2021. Published by Elsevier Inc.)

Background: Immune checkpoint inhibitors (ICIs) have become a high-profile regimen for malignancy recently. However, only a small subpopulation obtains long-term clinical benefit. How to select optimal patients by reasonable biomarkers remains a hot topic., Methods: Paired tissue samples and blood samples from 51 patients with advanced malignancies were collected for correlation analysis. Dynamic changes in blood PD-L1 (bPD-L1) expression, including PD-L1 mRNA, exosomal PD-L1 (exoPD-L1) protein and soluble PD-L1 (sPD-L1), were detected after 2 months of ICIs treatment in advanced non-small-cell lung cancer (NSCLC) patients. The best cutoff values for progression-free survival (PFS) and overall survival (OS) of all three biomarkers were calculated with R software., Results: In 51 cases of various malignancies, those with positive tissue PD-L1 (tPD-L1) had significantly higher PD-L1 mRNA than those with negative tPD-L1. In 40 advanced NSCLC patients, those with a fold change of PD-L1 mRNA ≥ 2.04 had better PFS, OS and best objective response (bOR) rate. In addition, a fold change of exoPD-L1 ≥ 1.86 was also found to be associated with better efficacy and OS in a cohort of 21 advanced NSCLC cases. The dynamic change of sPD-L1 was not associated with efficacy and OS. Furthermore, the combination of PD-L1 mRNA and exoPD-L1 could screen better patients for potential benefit from ICIs treatment., Conclusion: There was a positive correlation between bPD-L1 and tPD-L1 expression. Increased expression of PD-L1 mRNA, exoPD-L1, or both in early stage of ICIs treatment could serve as positive biomarkers of efficacy and OS in advanced NSCLC patients., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Yang, Chen, Gu, Niu, Zhao, Zheng, Xu, Yu, Li, Meng, Chen, Zhuo, Zhang and Sun.)

PD-L1 expression is the most useful predictive biomarker for immunotherapy efficacy on non-small cell lung cancer (NSCLC), and CD8+ tumor-infiltrating lymphocytes (CD8+ TILs) play an essential role in the clinical activity of immunotherapy. PD-L1 is found on the exosome's surface, and PD-L1 expressing exosomes can inhibit antitumor immune responses. This study aimed to analyze tumor PD-L1 expression, serum exosomal PD-L1, and CD8+ TILs to investigate anti-PD-1 response and clinicopathological outcomes in NSCLC. One hundred twenty patients with stage I-III NSCLC were enrolled, and serum samples collected during the initial surgery were pooled. The Human CD274/PD-L1 ELISA kit was used to quantify the exosomal PD-L1. Exosomal PD-L1 levels were significantly correlated with tumor PD-L1 levels (p < 0.001) and the number of CD8+ TILs (p = 0.001). Patients with exosomal PD-L1 ≥ 166 pg/mL tended to have a worse RFS than those with < 166 pg/mL in all stage (p = 0.163) and stage I patients (p = 0.116). Seventeen patients exhibited postoperative recurrences and received anti-PD-1 treatment. The disease control rate of patients with exosomal PD-L1 ≥ 166 pg/mL was 100%. The measurement of serum exosomal PD-L1 as a quantitative factor with tumor PD-L1 status may help predict anti-PD-1 response and clinical outcomes in patients with NSCLC.

Purpose: Tryptophan metabolites have immunomodulatory functions, suggesting possible roles in cancer immunity., Methods: Plasma tryptophan metabolites were measured using liquid chromatography/mass spectrometry before immune checkpoint inhibitors (ICIs) in patients with non-small cell lung cancer (NSCLC)., Results: The 19 patients with NSCLC had significantly lower levels of tryptophan (p = 0.002) and xanthurenic acid (p = 0.032), and a significantly higher level of 3-hydroxyanthranilic acid (3-HAA) (p = 0.028) compared with the 10 healthy volunteers. The patients achieving objective responses had significantly lower levels of 3-HAA than those who did not (p = 0.045). Receiver operating characteristic analyses determined that the cutoff value of 3-HAA for objective response was 35.4 pmol/mL (sensitivity: 87.5% and specificity: 83.3%). The patients with 3-HAA < 35.4 pmol/mL had significantly longer median progression-free survival (7.0 months) than those without (1.6 months, p = 0.022)., Conclusions: Tryptophan metabolites may have a potential for predicting the efficacy of ICIs., Registration Number: University Hospital Medical Information Network Clinical Trial Registry 000026140.

Purpose: Pretreatment selection of patients with non-small cell lung cancer (NSCLC) who would derive clinical benefit from treatment with immune checkpoint inhibitors (CPIs) would fulfill an unmet clinical need by reducing unnecessary toxicities from treatment and result in substantial health care savings., Experimental Design: In a retrospective study, mass spectrometry (MS)-based proteomic analysis was performed on pretreatment sera derived from patients with advanced NSCLC treated with nivolumab as part of routine clinical care ( n = 289). Machine learning combined spectral and clinical data to stratify patients into three groups with good ("sensitive"), intermediate, and poor ("resistant") outcomes following treatment in the second-line setting. The test was applied to three independent patient cohorts and its biology was investigated using protein set enrichment analyses (PSEA)., Results: A signature consisting of 274 MS features derived from a development set of 116 patients was associated with progression-free survival (PFS) and overall survival (OS) across two validation cohorts ( N = 98 and N = 75). In pooled analysis, significantly better OS was demonstrated for "sensitive" relative to "not sensitive" patients treated with nivolumab; HR, 0.58 (95% confidence interval, 0.38-0-87; P = 0.009). There was no significant association with clinical factors including PD-L1 expression, available from 133 of 289 patients. The test demonstrated no significant association with PFS or OS in a historical cohort ( n = 68) of second-line NSCLC patients treated with docetaxel. PSEA revealed proteomic classification to be significantly associated with complement and wound-healing cascades., Conclusions: This serum-derived protein signature successfully stratified outcomes in cohorts of patients with advanced NSCLC treated with second-line PD-1 CPIs and deserves further prospective study., (©2020 American Association for Cancer Research.)

Currently, only a small subset of cancer patients can benefit from anti-PD-1/PD-L1 monotherapy, indicating that further predictive biomarkers are needed. In the retrospective study, plasma samples were collected before anti-PD-L1/PD-L1 treatment in two subsets of patients. A total of 59 immunological factors, including cytokines, chemokines, and soluble immune checkpoints, were measured by using a multiplex immunoassay kit. Moreover, multiplex immunohistochemistry (mIHC) was performed in a subgroup of patients. In the discovery cohort, multiplex immunoassay profiling data revealed that both soluble PD-L1 and C-C motif chemokine 5 (CCL5/RANTES) showed rising trends across the three subgroups PD, SD and CR/PR. Further investigation demonstrated the predictive and prognostic value of the pre-treatment levels of PD-L1, CCL5/RANTES, and their combinatorial signature the "2-cytokine signature". As expected, the signature-high patients displayed a remarkably increased disease control rate (DCR) and prolonged survival versus that of the lower subgroup. More importantly, the relevance between the three signatures and the efficiency of immunotherapy was confirmed in the pan-cancer validation cohort. Notably, the significant association between the "2-cytokine signature" and longer survival was validated. Further quantitative analyses of the tumor microenvironment composition suggested a link between the "2-cytokine signature" and NK cell infiltration. In conclusion, a combined peripheral signature comprising CCL5/RANTES and soluble PD-L1 appears to be an effective biomarker to predict benefit from anti-PD-1/PD-L1 monotherapy. Our study underscores that peripheral immunological features may play an essential role in guiding patient selection and are worthy of future prospective investigations., (Copyright © 2020. Published by Elsevier Masson SAS.)