Introduction: Psoriasis is a chronic inflammatory disease of the skin. A few studies have shown that psoriasis is an immune-mediated disease in which multiple immune cells play crucial roles. However, the association between circulating immune cells and psoriasis remains elusive.Methods: To explore the role of circulating immune cells in psoriasis, 361,322 individuals from the UK Biobank (UKB) and 3,971 patients with psoriasis from China were included to investigate the association between white blood cells and psoriasis via an observational study. Genome-wide association studies (GWAS) and Mendelian randomization (MR) were used to evaluate the causal relationship between circulating leukocytes and psoriasis.Results: The risk of psoriasis increased with high levels of monocytes, neutrophils, and eosinophils (relative risks and 95% confidence intervals, respectively: 1.430 (1.291–1.584) for monocytes, 1.527 (1.379–1.692) for neutrophils, and 1.417 (1.294–1.551) for eosinophils). Upon further MR analysis, eosinophils showed a definite causal relationship with psoriasis (odds ratio of inverse-variance weighted: 1.386, 95% confidence intervals: 1.092–1.759) and a positive correlation with the psoriasis area and severity index (PASI) score (P = 6.6 × 10^-5). The roles of the neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), and lymphocyte-monocyte ratio (LMR) in psoriasis were also assessed. More than 20,000 genetic variations associated with NLR, PLR, and LMR were discovered in a GWAS analysis using the UKB data. Following adjustment for covariates in the observational study, NLR and PLR were shown to be risk factors for psoriasis, whereas LMR was a protective factor. MR results indicated that there was no causal relationship between these three indicators and psoriasis; however, NLR, PLR, and LMR correlated with the PASI score (NLR: rho = 0.244, P = 2.1 × 10^-21; PLR: rho = 0.113, P = 1.4 × 10^-5; LMR: rho = -0.242, P = 3.5×10^-21).Discussion: Our findings revealed an important association between circulating leukocytes and psoriasis, which is instructive for the clinical practice of psoriasis treatment.

Alternative polyadenylation (APA) is an important posttranscriptional modification commonly involved in tumor development. However, the functional roles of APA in tumor immunity remain largely unknown. Here, we performed an in-depth analysis of the 3′UTR usage of protein-coding genes and tumor immune response in 10,303 tumor samples across 31 cancer types to develop the immune-related APA event (ImmAPA) score pipeline, an integrated algorithm to characterize the regulatory landscape of APA events in cancer immunity–related pathways. Tumor-specific ImmAPAs that strongly correlate with immune cell infiltration and immune checkpoint blockade (ICB) treatment–related biomarkers were identified. Among these ImmAPAs, the top-ranking COL1A1 3′UTR usage was strongly associated with worse prognosis and tumor immune evasion. Furthermore, a machine learning approach to construct an ICB-related ImmAPA score model predicted immunotherapy efficacy. Overall, the characterization of immune-related APA that corresponds to tumor progression and tumor immunity highlights the clinical utility of APA events as potential biomarkers in cancer immunotherapy. Significance: Elucidation of the landscape of immune-related alternative polyadenylation in cancer identifies alternative polyadenylation events that may play a role in immune modulation and immunotherapy efficacy.

Background: Pyroptosis, mediated by gasdermins with the release of multiple inflammatory cytokines, has emerged as playing an important role in targeted therapy and immunotherapy due to its effectiveness at inhibiting tumor growth. Melanoma is one of the most commonly used models for immunotherapy development, though an inadequate immune response can occur. Moreover, the development of pyroptosis-related therapy and combinations with other therapeutic strategies is limited due to insufficient understanding of the role of pyroptosis in the context of different tumor immune microenvironments (TMEs).Methods: Here, we present a computational model (pyroptosis-related gene score, PScore) to assess the pyroptosis status. We applied PScore to 1388 melanoma samples in our in-house cohort and eight other publicly available independent cohorts and then calculated its prognostic power of and potential as a predictive marker of immunotherapy efficacy. Furthermore, we performed association analysis for PScore and the characteristics of the TME by using bulk, single-cell, and spatial transcriptomics and assessed the association of PScore with mutation status, which contributes to targeted therapy.Results: Pyroptosis-related genes (PRGs) showed distinct expression patterns and prognostic predictive ability in melanoma. Most PRGs were associated with better survival in metastatic melanoma. Our PScore model based on genes associated with prognosis exhibits robust performance in survival prediction in multiple metastatic melanoma cohorts. We also found PScore to be associated withBRAFmutation and correlate positively with multiple molecular signatures, such as KRAS signaling and the IFN gamma response pathway. Based on our data, melanoma with an immune-enriched TME had a higher PScore than melanoma with an immune-depleted or fibrotic TME. Additionally, monocytes had the highest PScore and malignant cells and fibroblasts the lowest PScore based on single-cell and spatial transcriptome analyses. Finally, a higher PScore was associated with better therapeutic efficacy of immune checkpoint blockade, suggesting the potential of pyroptosis to serve as a marker of immunotherapy response.Conclusions: Collectively, our findings indicate that pyroptosis is a prognostic factor and is associated with the immune response in metastatic melanoma, as based on multiomics data. Our results provide a theoretical basis for drug combination and reveal potential immunotherapy response markers.

Ferroptosis is a type of regulated cell death catalyzed by the iron‐dependent accumulation of lipid hydroperoxides to lethal levels. Chronic lymphocytic leukemia (CLL) is a chronic lymphoproliferative disorder. However, the understanding of ferroptosis in CLL remains largely poor. In this study, we investigated the stratification and prognostic role of ferroptosis‐related genes in CLL patients of ICGC cohort. We obtained fourteen genes with prognostic value by screening 110 ferroptosis‐related genes (FRGs). Based on the expression profiles of these 14 genes, we classified CLL patients into two clusters. Most of the FRGs were highly expressed in cluster 1, and cluster 1 was associated with better overall survival (OS). Subsequently, we developed an eight‐gene signature (TP63, STEAP3, NQO1, ELAVL1, PRKAA1, HELLS, FANCD2, and CDKN2A) by using LASSO analysis. This risk signature divided CLL patients into high‐ and low‐risk groups. We used Cox regression analysis and ROC analysis demonstrated the risk signature was reliable and robust. And we validated the risk model in an external cohort (GSE22762). We also conducted enrichment analysis and genomic mutation analysis. Finally, we explored the potential effect of chemotherapy between the two risk groups. Our study contributed to understanding the role of ferroptosis in CLL and facilitated personalized and precision treatment.

Extracellular adenosine is extensively involved in regulating the tumor microenvironment. Given the disappointing results of adenosine-targeted therapy trials, personalized treatment might be necessary, tailored to the microenvironment status of individual patients. Here, we introduce the adenosine signaling score (ADO-score) model using non-negative matrix fraction identified patient subtypes using publicly available melanoma dataset, which aimed to profile adenosine signaling-related genes and construct a model to predict prognosis. We analyzed 580 malignant melanoma samples and demonstrated its robust value for prognosis. Further investigation in immune checkpoint inhibitor dataset suggests its potential as a stratified factor of immune checkpoint inhibitor efficacy. We validated the power of the ADO-score at the protein level immunofluorescence in a melanoma cohort from Xiangya Hospital. More importantly, single-cell and spatial transcriptomic data highlighted the cell-specific expression patterns of adenosine signaling-related genes and the existence of adenosine signaling-mediated crosstalk between tumor cells and immune cells in melanoma. Our study reveals a robust connection between adenosine signaling and clinical benefits in melanoma patients and proposes a universally applicable adenosine signaling model, the ADO-score, in gene expression profiles and histological sections. This model enables us to more precisely and conveniently select patients who are likely to benefit from immunotherapy.