Cancer Immunology, Immunotherapy最新文献

Intraperitoneal cellular immunotherapy with CAR-redirected lymphocytes is an intriguing approach to target peritoneal carcinomatosis (PC) from ovarian cancer (OC), which is currently evaluated in clinical trials. PC displays a composite structure with floating tumor cells within ascites and solid-like masses invading the peritoneum. Therefore, a comprehensive experimental model is crucial to optimize CAR-cell therapies in such a peculiar environment. Here, we explored the activity of cytokine-induced killer lymphocytes (CIK), redirected by CAR against mesothelin (MSLN-CAR.CIK), within reductionistic 3D models resembling the structural complexity of both liquid and solid components of PC. MSLN-CAR.CIK effectively killed and were functionally efficient against OC targets. In a "floating-like" 3D context with floating OC spheroids, both tumor localization and killing by MSLN-CAR.CIK were significantly boosted by fluid flow. In a "solid-like" context, MSLN-CAR.CIK were recruited through the extracellular matrix on embedded tumor aggregates, with variable kinetics depending on the effector-target distance. Furthermore, MSLN-CAR.CIK penetrated the inner levels of OC spheroids exerting effective tumor killing. Our findings provide currently unknown therapeutically relevant information on intraperitoneal approaches with CAR.CIK, supporting further developments and improvements for clinical studies in the context of locoregional cell therapy approaches for patients with PC from OC.

Background: Lymphocyte antigen 6 complex, locus E (Ly6E) has been initially demonstrated to involve in T cell activity and impair viral infectivity. Recently, high expression levels of Ly6E have been reported in tumor microenvironment (TME) of various types of cancers. However, the immunoregulatory mechanism of Ly6E manipulating TME remains unknown.

Methods: TCGA database and Kaplan-Meier plotter database were used to evaluate the correlation between Ly6E expression levels and cancer patient survival. After analyzing Ly6E expression levels in human breast cancer tissues and tumor cell lines, we generated Ly6E knockout (KO) and overexpression (OE) mouse cell lines. Cell proliferation ability in vitro and the ability of growth and metastasis in mouse tumor models were compared between KO/OE and wild-type tumor cells. On day 7 after tumor implantation, tumor tissues were separated for flow cytometric assay, bulk RNA sequencing and single-cell RNA sequencing (ScRNA-seq). The role of Ly6E-expressing tumor cell on macrophage was analyzed in vitro.

Results: Our result surprisingly found that high Ly6E expression levels were associated with CD8⁺ T cell exclusion in tumor tissues and resistance to immunotherapy. Our data showed that knockout of Ly6E in tumor cells prompts tumor regression and inhibits tumor metastases, and Ly6E-OE tumor cells vice versa. The enhanced anti-tumor effect of Ly6E knockout in tumor cells was dependent on T cell response and formed long-lasting memory. The increase in the CD8⁺ T-cell infiltration into the tumor islet of Ly6E-KO tumors confirmed the role of Ly6E on T cell exclusion. ScRNA-seq analysis showed that M2 macrophages are particularly abundant in the Ly6E-expressing tumor tissues, especially M2-4 macrophage cluster identified by high levels of Arg-1, indicates that Ly6E-expressing tumor cells might restrict T cell infiltration via M2 macrophages. Moreover, in vitro assay showed that cell culture media derived from Ly6E-positive tumor cells promoted macrophage migration and M2 polarization.

Conclusion: Our study illuminated that Ly6E-expressing tumor cells facilitated the accumulation of M2 macrophages in TME, which contributes to CD8⁺ T cell exclusion and provides new insights for improving efficacy of cancer immunotherapy.

Immune checkpoint inhibitor (ICI) therapies effectively treat a broadening spectrum of cancer entities but induce various immune-related side effects (irAEs). Recent reports suggest a correlation between ICI-induced systemic inflammation and thromboembolic events as well as an increased effectiveness by coadministration of anticoagulants. With cancer patients having a higher risk of thrombotic events per se, it is crucial to dissect and characterize the mechanisms that cause pro-coagulative effects induced by systemic tumor therapies and their potential interplay with anti-tumor response. A total of 31 patients with advanced skin cancer treated with either ICIs (n = 24) or BRAF/MEK inhibitors (n = 7) were longitudinally assessed for blood and coagulation parameters before as well as 7, 20 and 40 days after initiation of systemic tumor therapy. Changes were analyzed and compared between both groups. In addition, the influence of coagulation parameters on progression-free, recurrence-free and overall survival was investigated. The ICI cohort presented significantly increased factor VIII activity after one week of therapy (p 0.0225); while, protein S activity was reduced during the whole observation period. Additionally, von Willebrand factor activity and tissue factor concentrations increased under immunotherapy. Similar changes occurred under BRAF/MEK inhibitor therapy (BRAF/MEKi). Increased baseline levels of von Willebrand factor antigen and factor VIII:C before the start of ICI therapy correlated with a significantly higher risk of recurrence for patients receiving adjuvant immunotherapy. The findings suggest the induction of a pro-coagulant state under ICI and BRAF/MEKi and a role of coagulation parameters in the efficacy of ICI therapies.

Introduction: Several trials of perioperative immunotherapy for resectable non-small cell lung cancer (NSCLC) reported positive results. They were designed to adjuvant, neoadjuvant and sandwich (neoadjuvant plus adjuvant) immunotherapy with immune checkpoint inhibitors and chemotherapy (CT). The differences between neoadjuvant and sandwich modalities were unclear.

Method: We performed a systematic review and Bayesian network meta-analysis by retrieving relevant literature from PubMed, EMBASE, Cochrane Library, Web of Science, ClinicalTrials.gov, WHO ICTRP and major international conferences.

Results: We analyzed 8 studies involving 3429 patients, including 6 neoadjuvant plus adjuvant (Neo-Adj) and 2 neoadjuvant (Neo) trials. Neo-Adj had better event-free survival (EFS) (hazard ratio [HR] = 0.57, 95% confidence interval [CI]: 0.45-0.71) than CT. There existed no difference between Neo-Adj and Neo in EFS (HR = 0.87, 95% CI: 0.53-1.46) and overall survival (OS) (HR = 1.04, 95% CI: 0.38-2.57). Neo might have lower incidence of treatment-related adverse events (TRAEs) (relative risk [RR] = 0.96, 95% CI: 0.87-1.12) than Neo-Adj. Subgroup analysis of PD-L1 ≥ 50% suggested that EFS of Neo-Adj (HR = 0.46, 95% CI: 0.27-0.76) and Neo (HR = 0.24, 95% CI: 0.06-0.89) was better than CT, and Neo-Adj potentially caused shorter EFS than Neo (HR = 1.92, 95% CI: 0.46-7.84).

Conclusions: Our results suggest that Neo-Adj and Neo have similar EFS for patients with PD-L1 < 1% or 1-49%. However, patients with PD-L1 ≥ 50% may obtain more EFS benefit from Neo than Neo-Adj. Neo might present a more favorable assessment than Neo-Adj when evaluating OS. Moreover, adding adjuvant immunotherapy may increase toxicity.

Thyroid immune-related adverse events (irAEs) are associated with programmed cell death protein 1 (PD-1) blockade efficacy in non-small cell lung cancer (NSCLC). However, their independence from PD-L1 expression and quantitative impact on predicting PD-1 blockade efficacy remain unexplored. This multicenter, retrospective, longitudinal study from Korea included 71 metastatic NSCLC patients who underwent PD-L1 expression and thyroid function testing during PD-1 blockade. Disease progression by the Response Evaluation Criteria for Solid Tumors was the main outcome. Three-stage analyses were performed: (1) multivariate Cox regression models adjusted for PD-L1 expression according to thyroid irAEs; (2) subgroup analyses; (3) regrouping and comparing predictivity of current and alternative staging. Patients with thyroid irAE + exhibited a longer progression-free survival [7/20 vs. 34/51, adjusted HR 0.19 (0.07-0.47); P < 0.001] than those with thyroid irAE-, independent of PD-L1 expression; the results remained across most subgroups without interaction. The three groups showed different adjusted HR for disease progression (Group 1: PD L1 + and thyroid irAE + ; Group 2: PD-L1 + or thyroid irAE + : 5.08 [1.48-17.34]; Group 3: PD-L1- and thyroid irAE- : 30.49 [6.60-140.78]). Alternative staging (Group 1 in stage IVB → stage IVA; Group 3 in stage IVA → stage IVB) improved the prognostic value (PVE: 21.7% vs. 6.44%; C-index: 0.706 vs. 0.617) compared with the 8th Tumor-Node-Metastasis staging. Our study suggests thyroid irAEs and PD-L1 expression are independent biomarkers that improve predicting PD-1 blockade efficacy in NSCLC. Thyroid irAEs would be helpful to identify NSCLC patients who benefit from PD-1 blockade in early course of treatment.

The identification of relevant biomarkers from high-dimensional cancer data remains a significant challenge due to the complexity and heterogeneity inherent in various cancer types. Conventional feature selection methods often struggle to effectively navigate the vast solution space while maintaining high predictive accuracy. In response to these challenges, we introduce a novel feature selection approach that integrates Random Drift Optimization (RDO) with XGBoost, specifically designed to enhance the performance of cancer classification tasks. Our proposed framework not only improves classification accuracy but also offers valuable insights into the underlying biological mechanisms driving cancer progression. Through comprehensive experiments conducted on real-world cancer datasets, including Central Nervous System (CNS), Leukemia, Breast, and Ovarian cancers, we demonstrate the efficacy of our method in identifying a smaller subset of unique and relevant genes. This selection results in significantly improved classification efficiency and accuracy. When compared with popular classifiers such as Support Vector Machine, K-Nearest Neighbor, and Naive Bayes, our approach consistently outperforms these models in terms of both accuracy and F-measure metrics. For instance, our framework achieved an accuracy of 97.24% in the CNS dataset, 99.14% in Leukemia, 95.21% in Ovarian, and 87.62% in Breast cancer, showcasing its robustness and effectiveness across different types of cancer data. These results underline the potential of our RDO-XGBoost framework as a promising solution for feature selection in cancer data analysis, offering enhanced predictive performance and valuable biological insights.

Background: Immune checkpoint inhibitor (ICI)-mediated myocarditis results in significant morbidity and mortality. At our institution, we noted an increased incidence of ICI-mediated myocarditis cases, leading to further investigation in our database of advanced melanoma patients treated with ICI therapy.

Methods: A single-center, retrospective cohort analysis of patients with advanced melanoma identified cases of ICI-mediated myocarditis and myositis.

Results: 366 patients with advanced melanoma received a dose of ICI from September 2014 to October 2019. Of these patients, there were 0 cases of ICI-mediated myocarditis (0%, 95% CI 0%-1.0%) and 2 cases of ICI-mediated myositis (0.55%, 95% CI 0.07%-1.96%). From November 2019 to December 2021, an additional 246 patients with advanced melanoma were identified. Of these patients, 10 (4.1%, 95% CI 1.97%-7.35%) developed ICI-mediated myocarditis and 10 developed ICI-mediated myositis.

Conclusion: Our study suggests an increase in prevalence of ICI-mediated muscle damage including myositis and myocarditis in the COVID-19 era. Differentiation of these patients and further risk stratification may allow for development of guidelines for nuanced management of this serious complication.

Background: Glioblastoma multiforme (GBM) is the most lethal primary brain tumor for which novel therapies are needed. Recently, chimeric antigen receptor (CAR) T cell therapy has been shown to be effective against GBM, but it is a personalized medicine and requires high cost and long time for the cell production. CAR-transduced natural killer (NK) cells can be used for "off-the-shelf" cellular immunotherapy because they do not induce graft-versus-host disease. Therefore, we aimed to analyze the anti-GBM effect of CAR-T or NK cells targeting B7-H3, which is known to be highly expressed in GBM.

Methods: CAR-T cells targeting B7-H3 were generated using previously reported anti-B7-H3 scFv sequences. Cord blood (CB)-derived NK cells transduced with the B7-H3 CAR were also generated. Their anti-GBM effect was analyzed in vitro. The antitumor effect of intracranial injection of the B7-H3 CAR-T or NK cells was investigated in an in vivo xenograft model with patient-derived GBM cells.

Results: Both B7-H3 CAR-T cells and CAR-NK cells exhibited marked cytotoxicity against patient-derived GBM cells in vitro. Furthermore, intracranial injection of CAR-T cells and CAR-NK cells targeting B7-H3 resulted in a significant antitumor effect against patient-derived GBM xenografts.

Conclusion: Not only CAR-T cells but also CB-derived CAR-NK cells targeting B7-H3 may have the potential to eliminate GBM cells.

Neoadjuvant chemoimmunotherapy (NACI) has significant implications for the treatment of esophageal cancer. However, its clinical efficacy varies considerably among patients, necessitating further investigation into the underlying mechanisms. The rapid advancement of single-cell RNA sequencing (scRNA-seq) technology facilitates the analysis of patient heterogeneity at the cellular level, particularly regarding treatment outcomes. In this study, we first analyzed scRNA-seq data of esophageal squamous cell carcinoma (ESCC) following NACI, obtained from the Gene Expression Omnibus (GEO) database. After performing dimensionality reduction, clustering, and annotation on the scRNA-seq data, we employed CellChat to investigate differences in cell-cell communication among samples from distinct efficacy groups. The results indicated that macrophages in the non-responder exhibited stronger cell communication intensity compared to those in responders, with SPP1 and GALECTIN signals showing the most significant differences between the two groups. This finding underscores the crucial role of macrophages in the efficacy of NACI. Subsequently, reclustering of macrophages revealed that Mac-SPP1 may be primarily responsible for treatment resistance, while Mac-C1QC appears to promote T cell activation. Finally, we conducted transcriptome sequencing on ESCC tissues obtained from 32 patients who underwent surgery following NACI. Utilizing CIBERSORT, CIBERSORTx, and WGCNA, we analyzed the heterogeneity of tumor microenvironment among different efficacy groups and validated the correlation between SPP1⁺ macrophages and resistance to NACI in ESCC using publicly available transcriptome sequencing datasets. These findings suggest that SPP1⁺ macrophages may represent a key factor contributing to resistance against NACI in ESCC.