Journal of Immunotherapy最新文献

Adenylate uridylate-rich element genes (AREGs) are crucial in modulating gene expression following transcription. However, the comprehensive role of AREGs in lung squamous carcinoma (LUSC) remains inadequately understood. Transcriptome data from TCGA and GTEx databases to identify differentially expressed AREGs. Clustering algorithms were used to identify AREGs-related subtypes, and a prognostic model was developed through univariate/multivariate and LASSO regression analyses. Following this, we created a nomogram integrating clinical pathologic characteristics and the risk model. The immune microenvironment was evaluated using CIBERSORT, ESTIMATE, and MCPcounter analyses. We examined the mRNA expression of the signature genes in normal and lung squamous carcinoma cells using RT-qPCR. Finally, we assessed the sensitivity to drugs based on the signature genes in risk patients. Patients with the 2 identified molecular subtypes exhibit distinct prognoses and immune microenvironments. We identified 5 genes with prognostic significance that can serve as independent predictors in clinical practice. The low-risk patients demonstrates more favorable prognostic outcomes, while the high-risk patients show elevated immune scores and increased immune cell infiltration, suggesting a favorable response to immunotherapy. RT-qPCR results showed upregulation of FAM83A and TINAGL1 and downregulation of FGG and ADH1C in LUSC. In addition, the low-risk patients show increased sensitivity to vinorelbine. The molecular subtypes and prognostic model based on AREGs demonstrate reliable clinical prognostic value. This finding may contribute to personalized and precise treatment for patients with LUSC, offering new insights for improving patient outcomes.

We present a rare case of aortitis in a 65-year-old male diagnosed with p16-positive, metastatic oropharyngeal squamous cell carcinoma on pembrolizumab therapy. The patient has a history of rheumatoid arthritis. Patient presented to the emergency room with cough, sudden onset pleuritic chest pain, and low-grade fever. Extensive infectious and rheumatological work up for the patient's symptoms yielded no significant findings. Radiologic workup suggested aortic inflammation. Because of the temporal relationship of onset of symptoms with immune checkpoint inhibitor therapy, a diagnosis of immune checkpoint related adverse effect (IrAE) associated vasculitis was established. To our knowledge, this is the first case of this unusual side effect of pembrolizumab presenting in the unique context of underlying autoimmune disease.

Metformin has the potential to synergistically enhance the effect of immune checkpoint inhibitors (ICI) in nonsmall cell lung cancer (NSCLC). We evaluated the association between metformin use before ICI initiation and cancer-specific and all-cause mortality among NSCLC patients. We conducted a retrospective cohort study using the Surveillance, Epidemiology, and End Results (SEER)-Medicare data (2013-2019), including NSCLC patients with type 2 diabetes who newly initiated ICI therapy and had prior antidiabetic medication use. The exposure was metformin monotherapy versus sulfonylurea and/or dipeptidyl peptidase-4 (DPP-4) inhibitors. The primary outcome was cancer-specific mortality, and the secondary outcome was all-cause mortality. We used stabilized inverse probability of treatment weighting (sIPTW) to adjust for confounders. Fine-Gray competing risk model estimated cancer-specific mortality, while Cox proportional hazards model evaluated all-cause mortality. We included 1123 metformin users and 362 sulfonylurea/DPP-4 users. Although baseline characteristics differed, groups were well balanced after weighting. The adjusted incidence rate (aIR) of cancer-specific mortality was 82 versus 81 (aIR difference=1, 95% CI: -13 to 16), and all-cause mortality was 71 versus 67 (aIR difference=4, 95% CI: -6 to 15) per 100 person-years for metformin and sulfonylurea/DPP-4 users, respectively. Metformin use was not significantly associated with cancer-specific mortality (adjusted hazard ratio (aHR)=1.08, 95% CI: 0.88-1.33) and all-cause mortality (aHR=1.07, 95% CI: 0.90-1.26). In this large, diverse cohort of individuals with NSCLC using ICI, there was no statistically significant association between metformin use and cancer-specific or all-cause mortality.

This study aims to explore the common immune-related gene characteristics of cholangiocarcinoma (CHOL) and inflammatory bowel disease (IBD) to predict disease prognosis. By analyzing the gene expression data from the TCGA, GEO, and NGDC databases, differentially expressed immune-related genes (DE-IRGs) were screened, and a prognostic model was constructed. The results showed that CCR7, OSM, S100P, ACVR1C, OSMR, SPP1, and PIK3R3 were key immune-related genes, and their expressions were closely related to the occurrence and development of CHOL and IBD. Patients in the low immune risk score (IRS) group had more abundant antitumor immune cell infiltration, while those in the high IRS group had more macrophage infiltration. In addition, the model based on these genes had good predictive ability for the diagnosis and prognosis of CHOL and IBD, with an area under the ROC curve (AUC) value exceeding 0.7. This study also predicted potential small molecule drugs that might be effective for the treatment of CHOL, such as Umbralisib and Tamoxifen. In conclusion, this study provides new biomarkers and potential targets for diagnosis, prognosis assessment, and treatment of CHOL and IBD.

Abstract: A highly suppressive tumor immune microenvironment and nonspecific target endow malignant tumors with CAR-T cells. CSF1R is highly expressed on pancreatic cancer tissues compares with normal tissues in GEPIA database and M2 macrophages mainly contributing to the suppressive tumor microenvironment (TME), suggesting that CSF1R is a suitable antigen. CSF1 is the natural ligand of CSF1R, so we constructed a CSF1-CAR and tested its cytotoxic effect on tumor cells and macrophages in vitro. Our results demonstrated that CSF1-CAR-T cells can lyse tumor cells dependent on CSF1R expression. Meanwhile, CSF1-CAR-T also lyse CSF1R + M2 macrophages, suggesting that CSF1-CAR-T cells play a role in eliminating tumor cells and remodeling the TME.

Calmodulin (CALM) has a bearing on the prognosis of various cancers. However, the prognostic value of CALM in esophageal squamous cell carcinoma (ESCC) remains unelucidated. Differentially expressed genes (DEGs) were screened between normal and tumor groups of TCGA-ESCC sets. The intersection of DEGs with calmodulin-related genes (CRGs) yielded differentially expressed CRGs (DE-CRGs). A prognostic model was established using LASSO Cox regression analysis and multivariate Cox regression analysis. qPCR validated the expression of prognostic feature genes. Analysis of gene expression patterns of different cellular clusters was based on single-cell sequencing data. Lastly, GSEA enrichment, immune infiltration, mutational profiling, drug sensitivity, and molecular docking as well as cellular thermal shift assay (CETSA) were conducted for ESCC patients. A prognosis model with excellent predictive capability was created based on 4 feature genes (ATP2B3, CALB1, KCNQ1, and MYO1G). The qPCR results demonstrated that ATP2B3 and KCNQ1 were significantly downregulated in human ESCC cells, whereas CALB1 and MYO1G were upregulated ( P <0.05). Single-cell analysis uncovered that MYO1G and KCNQ1 were mainly expressed in different cell clusters. Furthermore, this risk model was strongly associated with functional pathway enrichment, immune cell infiltration, and somatic mutations. We also identified AZD-8055 may be potential therapy for ESCC patients. The CETSA experiment demonstrated the existence of a favorable binding thermal stability between AZD-8055 and MYO1G. This research may identify potential biomarkers for predicting the prognosis of ESCC patients.

Abstract: Ovarian cancer (OV) remains the most lethal gynecological malignancy. The aim of this study was to identify molecular subtypes of OV through integrative multi-omics analysis and construct machine learning-based prognostic models for predicting the efficacy of immunotherapy. In here, the mutation, copy number variation, RNA sequencing expression profiles, and clinical information were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Multi-omics data were stratified using the MOVICS package, identifying different molecular subtypes. Our analysis identified 2 molecular subtypes (CS1 and CS2) with significant survival differences. Transcriptional regulatory network analysis revealed differential activation of transcription factors such as FOXA1 and GATA3 in CS1, whereas AR and ESR2 were enriched in CS2. A robust prognostic signature comprising 5 key genes was developed through the integration of 10 machine learning algorithms, demonstrating high predictive power across data sets. Immune cell infiltration analysis revealed that anti-tumor immune cells were more abundant in low-risk groups, whereas pro-tumor immune cells predominated in high-risk groups. Furthermore, low-risk patients exhibited better immunotherapy responses and higher tumor mutational burden (TMB). In conclusion, our findings underscore the potential of multi-omics integration in unveiling novel OV subtypes and constructing predictive models that inform personalized treatment strategies. Future research should focus on validating these findings in larger cohorts to enhance OV management through targeted therapeutic approaches.

Abstract: Lung squamous cell carcinoma (LUSC) remains a major clinical challenge due to its aggressive nature and poor prognosis. Enhancer of zeste homolog 2 (EZH2), a key epigenetic regulator within the polycomb repressive complex 2 (PRC2), has emerged as a critical player in cancer progression. This study investigates the dual role of EZH2 in driving tumor proliferation and modulating the immune microenvironment in LUSC. Bioinformatics analysis revealed significant upregulation of EZH2 in LUSC tissues compared with normal counterparts, with high EZH2 expression correlating with improved overall survival in early-stage patients. Functional assays in EZH2 knockout LUSC cell lines demonstrated reduced tumor cell proliferation, migration, and invasion alongside enhanced apoptosis and cell cycle arrest. Furthermore, in vivo studies using an EZH2 knockout mouse model showed decreased tumor growth and increased immune cell infiltration, including CD8+ T cells, macrophages, and neutrophils. These findings highlight the pivotal role of EZH2 in promoting tumor progression and orchestrating immune evasion mechanisms in LUSC. Given its multifaceted influence on tumor biology and the immune landscape, EZH2 represents a promising therapeutic target for improving outcomes in LUSC patients. Future studies should explore the therapeutic potential of targeting EZH2 to enhance immune responses and overcome resistance to current treatments.

Immunotherapy combined with chemotherapy has become the first-line treatment for recurrent or metastatic nasopharyngeal carcinoma (RM-NPC). However, the impact of antibiotic (ATB) use on the efficacy of immunotherapy in RM-NPC remains unclear. A total of 200 patients with RM-NPC who started first-line immunotherapy between October 2021 and September 2023 were included. Forty-six patients received ATB within 60 days before and 42 days after the first infusion of immunotherapy (group ATB+), and the remaining 154 patients were in group ATB-. The median progression-free survival (PFS) times of the ATB+ and ATB- groups were 11.20 and 19.87 months, respectively ( P = 0.061). The 2-year overall survival (OS) rates of the ATB+ and ATB- groups were 52.6% and 76.7%, respectively ( P = 0.001). In multivariate analysis, ATB use was significantly associated with worse OS (hazard ratio = 2.549, P = 0.002). No significant differences were observed between the 2 groups in terms of grade 3+ treatment-related adverse events. ATB use in RM-NPC may reduce the effectiveness of first-line immunotherapy.

This project aims to explore the clustering value of polyamine metabolism-related genes (PMRGs) in breast cancer (BC) to assist treatment. ConsensusClusterPlus R package was employed to cluster BC patients based on the expression of PMRGs. Using the edgeR R package, we analyzed differentially expressed genes (DEGs) of different molecular clusters. Core genes were screened and enriched by the PPI network. Univariate COX was applied to determine genes tightly linked with survival. ConsensusClusterPlus R package was employed to cluster PMRGs. Differences in immune infiltration and expression of immune checkpoints between 2 subgroups were analyzed. Response to immunotherapy was assessed based on the expression level of immunophenoscore (IPS). Drug sensitivity of different PMRG clusters was assessed by pRRophitic R package. We clustered BC patients into 2 different subtypes with different survival rates and biological functions based on the expression of 16 PMRGs. Application of univariate COX analysis identified genes greatly associated with survival and divided BC patients into 2 different PMRG clusters. Patients in the 2 clusters exhibited differences in overall survival rate and immune cell infiltration levels, with multiple immune cells displaying higher immune levels in PMRG cluster 2. PMRG cluster 2 demonstrated higher expression of HLA and IC as well as IPS. Cluster 1 exhibited higher sensitivity to (5Z)-7-Oxozeaenol, 5-Fluorouracil, and 681640, while cluster 2 exhibited higher sensitivity to A-443654 and A-770041. We identified 2 clusters of PMRG with significant differences in the immune microenvironment in BC and predicted potential drugs, aiming to find new directions for clinical treatment of BC.