11,

(1.85) = 12.71,

 < .01; Depersonalization

 = .07,

(1.85) = 6.73,

 = .01; Low Personal Accomplishment

 = .11,

(1.85) = 11.29,

 < .01).

Burnout is prevalent in the sample, yet self-compassion may be a possible protective factor.

Burnout is prevalent in the sample, yet self-compassion may be a possible protective factor.Rationale The clinical application of biomarkers reflecting tumor immune microenvironment is hurdled by the invasiveness of obtaining tissues despite its importance in immunotherapy. We developed a deep learning-based biomarker which noninvasively estimates a tumor immune profile with fluorodeoxyglucose positron emission tomography (FDG-PET) in lung adenocarcinoma (LUAD). Methods A deep learning model to predict cytolytic activity score (CytAct) using semi-automatically segmented tumors on FDG-PET trained by a publicly available dataset paired with tissue RNA sequencing (n = 93). This model was validated in two independent cohorts of LUAD SNUH (n = 43) and The Cancer Genome Atlas (TCGA) cohort (n = 16). The model was applied to the immune checkpoint blockade (ICB) cohort, which consists of patients with metastatic LUAD who underwent ICB treatment (n = 29). Results The predicted CytAct showed a positive correlation with CytAct of RNA sequencing in validation cohorts (Spearman rho = 0.32, p = 0.04 in SNUH cohort; spearman rho = 0.47, p = 0.07 in TCGA cohort). In ICB cohort, the higher predicted CytAct of individual lesion was associated with more decrement in tumor size after ICB treatment (Spearman rho = -0.54, p less then 0.001). Higher minimum predicted CytAct in each patient associated with significantly prolonged progression free survival and overall survival (Hazard ratio 0.25, p = 0.001 and 0.18, p = 0.004, respectively). In patients with multiple lesions, ICB responders had significantly lower variance of predicted CytActs (p = 0.005). Conclusion The deep learning model that predicts CytAct using FDG-PET of LUAD was validated in independent cohorts. Our approach may be used to noninvasively assess an immune profile and predict outcomes of LUAD patients treated with ICB.Rationale The forkhead box A1 (FOXA1) is a crucial transcription factor in initiation and development of breast, lung and prostate cancer. Previous studies about the FOXA1 transcriptional network were mainly focused on protein-coding genes. Its regulatory network of long non-coding RNAs (lncRNAs) and their role in FOXA1 oncogenic activity remains unknown. Methods The Cancer Genome Atlas (TCGA) data, RNA-seq and ChIP-seq data were used to analyze FOXA1 regulated lncRNAs. RT-qPCR was used to detect the expression of DSCAM-AS1, RT-qPCR and Western blotting were used to determine the expression of FOXA1, estrogen receptor α (ERα) and Y box binding protein 1 (YBX1). RNA pull-down and RIP-qPCR were employed to investigate the interaction between DSCAM-AS1 and YBX1. The effect of DSCAM-AS1 on malignant phenotypes was examined through in vitro and in vivo assays. Results In this study, we conducted a global analysis of FOXA1 regulated lncRNAs. For detailed analysis, we chose lncRNA DSCAM-AS1, which is specifically expressed in lung adenocarcinoma, breast and prostate cancer. selleck inhibitor The expression level of DSCAM-AS1 is regulated by two super-enhancers (SEs) driven by FOXA1. High expression levels of DSCAM-AS1 was associated with poor prognosis. Knockout experiments showed DSCAM-AS1 was essential for the growth of xenograft tumors. Moreover, we demonstrated DSCAM-AS1 can regulate the expression of the master transcriptional factor FOXA1. In breast cancer, DSCAM-AS1 was also found to regulate ERα. Mechanistically, DSCAM-AS1 interacts with YBX1 and influences the recruitment of YBX1 in the promoter regions of FOXA1 and ERα. Conclusion Our study demonstrated that lncRNA DSCAM-AS1 was transcriptionally activated by super-enhancers driven by FOXA1 and exhibited lineage-specific expression pattern. DSCAM-AS1 can promote cancer progression by interacting with YBX1 and regulating expression of FOXA1 and ERα.Rationale Anti-tumor necrosis factor (TNF) therapy is a very effective way to treat inflammatory bowel disease. However, systemic exposure to anti-TNF-α antibodies through current clinical systemic administration can cause serious adverse effects in many patients. Here, we report a facile prepared self-assembled supramolecular nanoparticle based on natural polyphenol tannic acid and poly(ethylene glycol) containing polymer for oral antibody delivery. Method This supramolecular nanoparticle was fabricated within minutes in aqueous solution and easily scaled up to gram level due to their pH-dependent reversible assembly. DSS-induced colitis model was prepared to evaluate the ability of inflammatory colon targeting ability and therapeutic efficacy of this antibody-loaded nanoparticles. Results This polyphenol-based nanoparticle can be aqueous assembly without organic solvent and thus scaled up easily. The oral administration of antibody loaded nanoparticle achieved high accumulation in the inflamed colon and low systemic exposure. The novel formulation of anti-TNF-α antibodies administrated orally achieved high efficacy in the treatment of colitis mice compared with free antibodies administered orally. The average weight, colon length, and inflammatory factors in colon and serum of colitis mice after the treatment of novel formulation of anti-TNF-α antibodies even reached the similar level to healthy controls. Conclusion This polyphenol-based supramolecular nanoparticle is a promising platform for oral delivery of antibodies for the treatment of inflammatory bowel diseases, which may have promising clinical translation prospects.Background Circular RNAs (circRNAs) are a new class of non-coding RNAs (ncRNAs) that are derived from exons or introns by special selective shearing. circRNAs have been shown to play critical roles in various human cancers. However, their roles in renal cell carcinoma (RCC) and the underlying mechanisms remain largely unknown. Methods A novel circRNA-circPTCH1, was identified from a microarray analysis of five paired RCC tissues. Then, we validated its expression and characterization through qRT-PCR, gel electrophoresis, RNase R digestion assays and Sanger sequencing. Functional experiments were performed to determine the effect of circPTCH1 on RCC progression both in vitro and in vivo. The interactions between circPTCH1 and miR-485-5p were clarified by RNA pull-down, luciferase reporter and RNA immunoprecipitation (RIP) assays. Results We observed that circPTCH1 was up-regulated in RCC cell lines and tumor samples, and higher levels of circPTCH1 were significantly correlated with worse patient survival, advanced Fuhrman grade and greater risk of metastases.