Influence of Malignant Pleural Fluid from Lung Adenocarcinoma Patients on Neutrophil Response

Dendritic Cell-Related Immune Marker CD1C for Predicting Prognosis and Immunotherapy Opportunities of Lung Adenocarcinoma Patients

Lung adenocarcinoma (LUAD) is the most frequent type of lung cancer with a high mortality rate. Here, we aim to explore novel immune-related biomarkers for LUAD patients. Datasets, mRNA expression profiles, and clinical data concerned with LUAD were obtained from Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA), respectively. Differential expression analysis was performed to obtain differentially expressed genes (DEGs). Based on DEGs, we conducted functional enrichment analyses. Subsequently, Kaplan‑Meier (KM) was performed to analyze survival differences among different groups. Furthermore, immune cell infiltration proportion was calculated by CIBERSORT and TIMER. The relationship between gene and immune response was analyzed using Tumor Immune System Interactions (TISIDB) database. Finally, Pearson correlation analysis was performed between CD1C and six immune checkpoints. We identified dendritic cells (DCs)-related expression profiles from four LUAD samples. DCs' immune marker CD1C in LUAD was selected by univariate Cox regression analysis. Low CD1C expression patients had a poor prognosis. A total of 332 DEGs were identified in high and low CD1C expression groups, which primarily enriched in 348 GO terms and 30 KEGG pathways. There were significant differences in the infiltration proportion of 17 immune cells between high and low CD1C expression groups. Most immunomodulators, chemokines, and chemokine receptors were positively associated with CD1C expression. Six immune checkpoints were also positively correlated with CD1C expression. DCs related immunomarker CD1C probably plays a pivotal part in prognosis and immunotherapy of LUAD via a joint analysis of single-cell and bulk sequencing data.

Novel serous effusion-related risk models and biomarkers for predicting prognosis in T-cell lymphoma patients

T-cell lymphomas (TCLs) are a cluster of lymphoproliferative diseases with high heterogeneity, which lack accurate prognostic models and standard treatment regimen at present. Serous effusion (SE) is a relatively common manifestation and poses more challenges for risk stratification in TCLs. In this study, entire of 518 newly diagnosed TCLs patients were included. SE was found to be tightly correlated to clinical characteristics and prognosis in TCL patients, and SE volume (SEV) > 1000 ml was identified as a potential prognostic factor. Novel AEBS risk model, including age > 60, ECOG PS > 1, β2-microglobulin (BMG) > 3.0 mg/L and SEV > 1000 ml, which exerted superior efficacy for risk stratification compared to the current risk systems in TCL patients with SE. Besides, multiple RNA-seq datasets were used for the identification and function analysis of SE-related genes (SERGs). TCL patients in different SERGs-associated subgroups exhibited discrepancy in the infiltration of immunocytes and the expression of immune checkpoints. SERGs signature, including HIF1A, FERMT2, NFATC1 and COL1A1, was established and demonstrated to have distinguishing capacity for predicting prognosis in TCL patients. Moreover, immunohistochemistry revealed that SE-related molecule HIF1A was reductively expressed and related to inferior prognosis in TCL patients, especially in SE group. Pan-cancer analysis found HIF1A expression was decreased in several tumors, and chemosensitivity analysis revealed that HIF1A was associated with sensitivity of several anti-tumor drugs, such as Sorafenib, Navitoclax, and Venetoclax. Our findings provide evidence for identifying high-risk population and facilitating individualized treatment in TCL patients with SE.

Dysregulated neutrophil extracellular traps formation in sepsis

The migration and antimicrobial functions of neutrophils seem to be impaired during sepsis and contribute to the dysregulation of immune responses and disease pathogenesis. However, the role of neutrophil extracellular traps (NETs) remains to be clarified. The study aimed to analyse sequential phenotypic and functional changes of neutrophils during the time following the diagnosis of sepsis. We prospectively enrolled 49 septic and 18 non-septic patients from the intensive care unit (ICU) and emergency room (ER) and 20 healthy volunteers (HV). Baseline blood samples from septic and non-septic patients were collected within 12 h of admission to the hospital. Additional septic samples were drawn at 24, 48 and 72 h after baseline. Neutrophil phenotype and degranulation capacity were assessed by flow cytometry and NET formation was quantified by fluorescence. Neutrophils from septic patients exhibited increased CD66b, CD11b and CD177 expression but displayed reduced NET formation at baseline compared with non-septic patients and HV controls. Neutrophils expressing CD177 interacted less with platelets, were related to reduced NETosis and tended to indicate a worse sepsis outcome. In vitro experiments revealed that neutrophil function is compromised by the origin of sepsis, including the pathogen type and the affected organ. Assessing a decision tree model, our study showed that CD11b expression and NETosis values are useful variables to discriminate septic from non-septic patients. We conclude that sepsis induces changes in neutrophil phenotype and function that may compromise the effective capacity of the host to eliminate pathogens.