Specific immunoglobulin G4 correlates with Th2 cytokine reduction in patients with allergic asthma treated by Dermatophagoides pteronyssinus subcutaneous immunotherapy.

Background: The modulations of lymphocyte subsets and cytokine production due to subcutaneous allergen immunotherapy (SCIT) are not fully clarified. Objective: We investigated the changes in T-lymphocyte subsets and serum Dermatophagoides pteronyssinus-specific immunoglobulin G4 (Der-p sIgG4), as well as cytokine production during Der-p SCIT, in patients with allergic asthma. Methods: This study involved 20 patients with allergic asthma who were receiving 156-week Der-p SCIT and 20 patients without SCIT (non-SCIT). We measured symptom and medication scores (SMS), serum Der-p sIgG4 levels, CD4+CD25+Foxp3+ T regulatory (Treg), CD4+IL-4-IFN-γ+ T-helper (Th) 1, and CD4+IL-4+IFN-γ- Th2 lymphocyte percentages in peripheral blood mononuclear cells (PBMCs) with/without Der-p extract stimulation at weeks 0, 4, 12, 16, 52, 104, and 156. Cytokine release inhibition assays were performed by incubation with serum from SCIT and non-SCIT patients, Der-p allergen, and PBMCs. Levels of interleukin (IL)-4, IL-5, IL-10, IL-13, IL-17, interferon (IFN)-γ, tumor necrosis factor (TNF)-α, and transforming growth factor (TGF)-ß1 were evaluated in supernatant. Results: We found that SCIT patients had significantly lower SMS after week 52. Der-p sIgG4 levels in SCIT patients significantly increased at week 16 compared with non-SCIT subjects. CD4+IL-4+IFN-γ- Th2% in SCIT patients showed a significant decrease from weeks 104-156 compared with week 0, while no change was observed in CD4+CD25+Foxp3+ Treg and CD4+IL-4-IFN-γ+ Th1 percentages. IL-5, IL-13, IL-4, IL-17, and TNF-α levels in supernatant of PBMCs cultured with serum of SCIT patients after 16 weeks showed significant lower levels compared with non-SCIT patients, and showed significant reverse associations with Der-p sIgG4 levels. Conclusion: SCIT induced Dep-p sIgG4 may be involved in downregulating Th2 cytokine production in Der-p allergic asthma patients.

Identification of seven-gene marker to predict the survival of patients with lung adenocarcinoma using integrated multi-omics data analysis.

BACKGROUND: The mechanism of cancer occurrence and development could be understood with multi-omics data analysis. Discovering genetic markers is highly necessary for predicting clinical outcome of lung adenocarcinoma (LUAD). METHODS: Clinical follow-up information, copy number variation (CNV) data, single nucleotide polymorphism (SNP), and RNA-Seq were acquired from The Cancer Genome Atlas (TCGA). To obtain robust biomarkers, prognostic-related genes, genes with SNP variation, and copy number differential genes in the training set were selected and further subjected to feature selection using random forests. Finally, a gene-based prediction model for LUAD was validated in validation datasets. RESULTS: The study filtered 2071 prognostic-related genes and 230 genomic variants, 1878 copy deletions, and 438 significant mutations. 218 candidate genes were screened through integrating genomic variation genes and prognosis-related genes. 7 characteristic genes (RHOV, CSMD3, FBN2, MAGEL2, SMIM4, BCKDHB, and GANC) were identified by random forest feature selection, and many genes were found to be tumor progression-related. A 7-gene signature constructed by Cox regression analysis was an independent prognostic factor for LUAD patients, and at the same time a risk factor in the test set, external validation set, and training set. Noticeably, the 5-year AUC of survival in the validation set and training set was all ˃ 0.67. Similar results were obtained from multi-omics validation datasets. CONCLUSIONS: The study builds a novel 7-gene signature as a prognostic marker for the survival prediction of patients with LUAD. The current findings provided a set of new prognostic and diagnostic biomarkers and therapeutic targets.