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Instead of “2Tianjin Medical University Cancer Institute and Hospital, Tianjin China, 3National Clinical Research Center for Cancer, Tianjin, China, 4Key Laboratory of Cancer Prevention and Therapy, Tianjin China, 5Tianjin’s Clinical Research Center for Cancer, Tianjin China, 6Key Laboratory of Cancer Immunology and Biotherapy, Tianjin, China, 7Department of Immunology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, 8Wenzhou Central Hospital, Wenzhou, Zhejiang, China, 9Department of Head and Neck Surgery, Shanxi Province Cancer Hospital/ Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, Shanxi, China, 10Department of Pathology, Shanxi Bethune Hospital, Taiyuan, Shanxi, China, 11General Surgery Department, Shanxi Bethune Hospital, Taiyuan, Shanxi, China, 12Haihe Laboratory of Cell Ecosystem, Tianjin, China, 13Department of Biotherapy, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.”, it should be:” 2National Clinical Research Center for Cancer, Tianjin, China, 3Key Laboratory of Cancer Prevention and Therapy, Tianjin, China, 4Tianjin’s Clinical Research Center for Cancer, Tianjin, China, 5Key Laboratory of Cancer Immunology and Biotherapy, Tianjin, China, 6Department of Immunology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, 7Wenzhou Central Hospital, Wenzhou, Zhejiang, China, 8Department of head and neck surgery, Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, Shanxi, China, 9Department of Pathology, Shanxi Bethune Hospital, Taiyuan, Shanxi, China, 10General Surgery Department, Shanxi Bethune Hospital, Taiyuan, Shanxi, China, 11Haihe Laboratory of Cell Ecosystem, Tianjin, China, 12Department of Biotherapy, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.” The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. In the published article, there was an error regarding the affiliation(s) for Siyuan Zhang, Qiuru Zhou, Fei Han, Gang Du, Lin Wang, Xuena Yang, Xiying Zhang, Wenwen Yu, Feng Wei, Xishan Hao, Xiubao Ren and Hua Zhao.

BackgroundAntibodies targeting programmed cell death-1(PD1) and its ligand (PDL1) have revolutionized cancer therapy. However, little is known about the preexisted anti-PD1/PDL1 autoantibodies (AAbs) distribution in multiple cancer types, nor is their potential biomarker role for anti-PD1 therapy.MethodPlasma anti-PD1/PDL1 AAb IgG and subclasses (IgG1-4) were detected by enzyme-linked immune sorbent assay (ELISA) in 190 cancer patients, covering 10 cancer types (lung, breast, esophageal, colorectal, liver, prostatic, cervical, ovarian, gastric cancers and lymphoma), the comprehensive correlation of AAbs with multiple clinical parameters was analyzed. We further tested these AAbs in 76 non-small cell lung cancer (NSCLC) samples receiving anti-PD1 therapy, the association of AAbs level with survival was analyzed and validated in an independent cohort (n = 32).ResultsAnti-PD1/PDL1 AAb IgG were globally detected in 10 types of cancer patients. IgG1 and IgG2 were the major subtypes for anti-PD1/PDL1 AAbs. Correlation analysis revealed a distinct landscape between various cancer types. The random forest model indicated that IgG4 subtype was mostly associated with cancer. In discovery cohort of 76 NSCLC patients, high anti-PD1 IgG4 was associated with a reduced overall survival (OS, p = 0.019), not progression-free survival (PFS, p = 0.088). The negative association of anti-PD1 IgG4 with OS was validated in 32 NSCLC patients (p = 0.032).ConclusionThis study reports for the first time the distribution of preexisted anti-PD1/PDL1 AAb IgG and subclasses across 10 cancer types. Moreover, the anti-PD1 AAb IgG4 subclass was identified to associate with OS, which may serve as a potential biomarker for anti-PD1 therapeutic survival benefit in NSCLC patients.

Background Clinical drawback in checkpoint inhibitors immunotherapy (ICI) of metastatic melanoma (MM) is monitoring clinical benefit. Soluble forms of PD1(sPD1) and PD-L1(sPD-L1) and extracellular vesicles (EVs) expressing PD1 and PD-L1 have recently emerged as predictive biomarkers of response. As factors released in the blood, EVs and soluble forms could be relevant in monitoring treatment efficacy and adaptive resistance to ICI. Methods We used pre-therapy plasma samples of 110 MM patients and longitudinal samples of 46 patients. Elisa assay and flow cytometry (FCM) were used to measure sPD-L1 and sPD1 concentrations and the percentage of PD1 + EVs and PD-L1 + EVs, released from tumor and immune cells in patients subsets. Transwell assays were conducted to investigate the impact of EVs of each patient subset on MM cells invasion and interaction between tumor cells and macrophages or dendritic cells. Viability assays were performed to assess EVs effect on MM cells and organoids sensitivity to anti-PD1. FCM was used to investigate immunosuppressive markers in EVs and immune cells. Results The concentrations of sPD1 and sPD-L1 in pre-treatment and longitudinal samples did not correlate with anti-PD1 response, instead only tumor-derived PD1 + EVs decreased in long responders while increased during disease progression in responders. Notably, we observed reduction of T cell derived EVs expressing LAG3 + and PD1 + in long responders and their increase in responders experiencing progression. By investigating the impact of EVs on disease progression, we found that those isolated from non-responders and from patients with progression disease accelerated tumor cells invasiveness and migration towards macrophages, while EVs of long responders reduced the metastatic potential of MM cells and neo-angiogenesis. Additionally, the EVs of non-responders and of progression disease patients subset reduced the sensitivity of MM cells and organoids of responder to anti-PD1 and the recruitment of dendritic cells, while the EVs of progression disease subset skewed macrophages to express higher level of PDL-1. Conclusion Collectively, we suggest that the detection of tumor-derived PD1 + EVs may represent a useful tool for monitoring the response to anti-PD1 and a role for EVs shed by tumor and immune cells in promoting tumor progression and immune dysfunction. Graphical Abstract

Background Circular RNAs (circRNAs) can be encapsulated into exosomes to participate in intercellular communication, affecting the malignant progression of a variety of tumors. Dysfunction of CD8 + T cells is the main factor in immune escape from hepatocellular carcinoma (HCC). Nevertheless, the effect of exosome-derived circRNAs on CD8 + T-cell dysfunction needs further exploration. Methods The effect of circCCAR1 on the tumorigenesis and metastasis of HCC was assessed by in vitro and in vivo functional experiments. The function of circCCAR1 in CD8 + T-cell dysfunction was measured by enzyme-linked immunosorbent assay (ELISA), western blotting and flow cytometry. Chromatin immunoprecipitation, biotinylated RNA pull-down, RNA immunoprecipitation, and MS2 pull-down assays were used to the exploration of mechanism. A mouse model with reconstituted human immune system components (huNSG mice) was constructed to explore the role of exosomal circCCAR1 in the resistance to anti-PD1 therapy in HCC. Results Increased circCCAR1 levels existed in tumor tissues and exosomes in the plasma of HCC patients, in the culture supernatant and HCC cells. CircCCAR1 accelerated the growth and metastasis of HCC in vitro and in vivo. E1A binding protein p300 (EP300) and eukaryotic translation initiation factor 4A3 (EIF4A3) promoted the biogenesis of circCCAR1, and Wilms tumor 1-associated protein (WTAP)-mediated m6A modification enhanced circCCAR1 stability by binding insulin-like growth factor 2 mRNA-binding protein 3 (IGF2BP3). CircCCAR1 acted as a sponge for miR-127-5p to upregulate its target WTAP and a feedback loop comprising circCCAR1/miR-127-5p/WTAP axis was formed. CircCCAR1 is secreted by HCC cells in a heterogeneous nuclear ribonucleoprotein A2/B1 (hnRNPA2B1)-dependent manner. Exosomal circCCAR1 was taken in by CD8 + T cells and caused dysfunction of CD8 + T cells by stabilizing the PD-1 protein. CircCCAR1 promoted resistance to anti-PD1 immunotherapy. Furthermore, increased cell division cycle and apoptosis regulator 1 (CCAR1) induced by EP300 promoted the binding of CCAR1 and β-catenin protein, which further enhanced the transcription of PD-L1. Conclusions The circCCAR1/miR-127-5p/WTAP feedback loop enhances the growth and metastasis of HCC. Exosomal circCCAR1 released by HCC cells contributes to immunosuppression by facilitating CD8 + T-cell dysfunction in HCC. CircCCAR1 induces resistance to anti-PD1 immunotherapy, providing a potential therapeutic strategy for HCC patients.

Anti-PD1/PD-L1 immunotherapy has emerged as a standard of care for stage III-IV non-small cell lung cancer (NSCLC) over the past decade. Patient selection is usually based on PD-L1 expression by tumor cells and/or tumor mutational burden. However, mutations in oncogenic drivers such as EGFR, ALK, BRAF, or MET modify the immune tumor microenvironment and may promote anti-PD1/PD-L1 resistance. In this review, we discuss the molecular mechanisms associated with these mutations, which shape the immune tumor microenvironment and may impede anti-PD1/PD-L1 efficacy. We provide an overview of the current clinical data on anti-PD1/PD-L1 efficacy in NSCLC with oncogenic driver mutation.

Background CD8 + T cells play a critical role in the innate antitumour immune response. Recently, CD8 + T cell dysfunction has been verified in various malignant cancers, including non-small cell lung cancer (NSCLC). However, the molecular biological mechanisms of CD8 + T cell dysfunction in human NSCLC are still unclear. Methods The expression of circular ubiquitin-specific protease-7 (circUSP7) in NSCLC tissues, exosomes, and cell lines was detected by quantitative real-time polymerase chain reaction (qRT-PCR). Exosomes were isolated from the culture medium of NSCLC cells and the plasma of NSCLC patients using an ultracentrifugation method and the ExoQuick Exosome Precipitation Solution kit. The exosomes were then characterized by transmission electronic microscopy (TEM), NanoSight and western blotting. The role of circUSP7 in CD8 + T cell dysfunction was assessed by enzyme-linked immunosorbent assay (ELISA). In vivo circular RNA (circRNA) precipitation (circRIP), RNA immunoprecipitation (RIP), and luciferase reporter assays were performed to explore the molecular mechanisms of circUSP7 in CD8 + T cells. In a retrospective study, the clinical characteristics and prognostic significance of circUSP7 in NSCLC tissues were determined. Results The expression levels of circUSP7 were higher in human NSCLC tissues than in matched adjacent nontumour tissues. Increased levels of circUSP7 indicate poor clinical prognosis and CD8 + T cell dysfunction in patients with NSCLC. The circUSP7 found in NSCLC patient plasma is predominantly secreted by NSCLC cells in an exosomal manner, and circUSP7 inhibits IFN-γ, TNF-α, Granzyme-B and Perforin secretion by CD8 + T cells. Furthermore, circUSP7 inhibits CD8 + T cell function by upregulating the expression of Src homology region 2 (SH2)-containing protein tyrosine phosphatase 2 (SHP2) via sponging miR-934. Finally, we show that circUSP7 may promote resistance to anti-PD1 immunotherapy in NSCLC patients. Conclusions Exosomal circUSP7 is predominantly secreted by NSCLC cells and contributes to immunosuppression by promoting CD8 + T cell dysfunction in NSCLC. CircUSP7 induces resistance to anti-PD1 immunotherapy, providing a potential therapeutic strategy for NSCLC patients.

Background The immunotherapy with immune checkpoints inhibitors (ICI) has changed the life expectancy in metastatic melanoma (MM) patients. Nevertheless, several patients do not respond hence, the identification and validation of novel biomarkers of response to ICI is of crucial importance. Circulating extracellular vesicles (EVs) such as PD-L1 + EV mediate resistance to anti-PD1, instead the role of PD1 + EV is not fully understood. Methods We isolated the circulating EVs from the plasma of an observational cohort study of 71 metastatic melanoma patients and correlated the amount of PD-L1 + EVs and PD1 +  EVs with the response to ICI. The analysis was performed according to the origin of EVs from the tumor and the immune cells. Subsequently, we analysed the data in a validation cohort of 22 MM patients to assess the reliability of identified EV-based biomarkers. Additionally we assessed the involvement of PD1 + EVs in the seizure of nivolumab and in the perturbation of immune cells-mediated killing of melanoma spheroids. Results The level of PD-L1 + EVs released from melanoma and CD8 +  T cells and that of PD1 + EVs irrespective of the cellular origin were higher in non-responders. The Kaplan-Meier curves indicated that higher levels of PD1+ EVs were significantly correlated with poorer progression-free survival (PFS) and overall survival (OS). Significant correlations were found for PD-L1 + EVs only when released from melanoma and T cells. The multivariate analysis showed that high level of PD1 + EVs, from T cells and B cells, and high level of PD-L1 + EVs from melanoma cells, are independent biomarkers of response. The reliability of PD-L1 + EVs from melanoma and PD1 + EVs from T cells in predicting PFS was confirmed in the validation cohort through the univariate Cox-hazard regression analysis. Moreover we discovered that the circulating EVs captured nivolumab and reduced the T cells trafficking and tumor spheroids killing. Conclusion Our study identified circulating PD1 + EVs as driver of resistance to anti-PD1, and highlighted that the analysis of single EV population by liquid biopsy is a promising tool to stratify MM patients for immunotherapy.

Major efforts are underway to identify agents that can potentiate effects of immune checkpoint inhibition. Here, we show that ascorbic acid (AA) treatment caused genomewide demethylation and enhanced expression of endogenous retroviral elements in lymphoma cells. AA also increased 5-hydroxymethylcytosine (5hmC) levels of CD8+ T cells and enhanced their cytotoxic activity in a lymphoma coculture system. High-dose AA treatment synergized with anti-PD1 therapy in a syngeneic lymphoma mouse model, resulting in marked inhibition of tumor growth compared with either agent alone. Analysis of the intratumoral epigenome revealed increased 5hmC with AA treatment, consistent with in vitro findings. Analysis of the tumor immune microenvironment revealed that AA strikingly increased intratumoral infiltration of CD8+ T cells and macrophages, suggesting enhanced tumor immune recognition. The combination treatment markedly enhanced intratumoral infiltration of macrophages and CD8+ T lymphocytes, granzyme B production by cytotoxic cells (cytotoxic T cells and natural killer cells), and interleukin 12 production by antigen-presenting cells compared with single-agent anti-PD1. These data indicate that AA potentiates anti-PD1 checkpoint inhibition through synergistic mechanisms. The study provides compelling rationale for testing combinations of high-dose AA and anti-PD1 agents in patients with aggressive B cell lymphoma as well as in preclinical models of other malignancies.

BackgroundTherapeutic chances for metastatic melanoma have consistently changed over the last years with the advent of antibodies targeting the programmed cell death protein-1 (PD-1). Onset of immune-related adverse events (irAEs) during treatment can be a source of concern, and the association with survival outcome is yet to be defined.Patients and methodsData of consecutive patients treated with anti-PD1 (nivolumab or pembrolizumab) for metastatic melanoma between July 2013 and January 2018 were retrospectively reviewed. Baseline factors, together with onset of irAEs and vitiligo during treatment, were evaluated to identify predictors of progression-free (PFS) and overall (OS) survival. PFS and OS were assessed using Kaplan–Meier and Cox models.ResultsOverall, 173 patients were included in the present analysis, and 102 patients (59%) experienced irAEs. Disease control rate was 51%. Median (interquartile range) PFS and OS were 4.9 (2.6–13.3) and 8.6 (3.5–18.3) months, respectively. At multivariate analysis, irAEs occurrence was independently associated with improved PFS [HR 0.47 (95% CI 0.26, 0.86); p = 0.016], and correlated with better OS [HR 0.39 (95% CI 0.18, 0.81); p = 0.007]. Among various irAEs, the occurrence of vitiligo was associated with a trend toward a non-significant improved OS in comparison with other irAEs (p = 0.061). Median OS was undefined for patients experiencing vitiligo vs. 21.9 months for patients with other irAEs vs. 9.7 months for patients who had no irAEs (p = 0.003).ConclusionsOur study underlines the association between irAEs and survival outcomes from anti-PD1 therapy. Careful management of treatment-related toxicity can lead to achieve maximum clinical benefit from this therapy.

Background Despite the high response rate to PD-1 blockade therapy in metastatic melanoma (MM) patients, a significant proportion of patients do not respond. Identifying biomarkers to predict patient response is crucial, ideally through non-invasive methods such as liquid biopsy. Methods Soluble forms of PD1, PD-L1, LAG-3, CTLA-4, CD4, CD73, and CD74 were quantified using ELISA assay in plasma of a cohort of 110 MM patients, at baseline, to investigate possible correlations with clinical outcomes. A clinical risk prediction model was applied and validated in pilot studies. Results No biomarker showed statistically significant differences between responders and non-responders. However, high number of significant correlations were observed among certain biomarkers in non-responders. Through univariate and multivariate Cox analyses, we identified sPD-L1, sCTLA-4, sCD73, and sCD74 as independent biomarkers predicting progression-free survival and overall survival. According to ROC analysis we discovered that, except for sCD73, values of sPD-L1, sCTLA-4, and sCD74 lower than the cut-off predicted lower disease progression and reduced mortality. A comprehensive risk score for predicting progression-free survival was developed by incorporating the values ​​of the two identified independent factors, sCTLA-4 and sCD74, which significantly improved the accuracy of outcome prediction. Pilot validations highlighted the potential use of the risk score in treatment-naive individuals and long responders. Conclusion In summary, risk score based on circulating sCTLA-4 and sCD74 reflects the response to immune checkpoint inhibitor (ICI) therapy in MM patients. If confirmed, through further validation, these findings could assist in recommending therapy to patients likely to experience a long-lasting response.