25-Hydroxycholesterol regulates lysosome AMP kinase activation and metabolic reprogramming to educate immunosuppressive macrophages.

Macrophages are critical to turn noninflamed "cold tumors" into inflamed "hot tumors". Emerging evidence indicates abnormal cholesterol metabolites in the tumor microenvironment (TME) with unclear function. Here, we uncovered the inducible expression of cholesterol-25-hydroxylase (Ch25h) by interleukin-4 (IL-4) and interleukin-13 (IL-13) via the transcription factor STAT6, causing 25-hydroxycholesterol (25HC) accumulation. scRNA-seq analysis confirmed that CH25Hhi subsets were enriched in immunosuppressive macrophage subsets and correlated to lower survival rates in pan-cancers. Targeting CH25H abrogated macrophage immunosuppressive function to enhance infiltrating T cell numbers and activation, which synergized with anti-PD-1 to improve anti-tumor efficacy. Mechanically, lysosome-accumulated 25HC competed with cholesterol for GPR155 binding to inhibit the kinase mTORC1, leading to AMPKα activation and metabolic reprogramming. AMPKα also phosphorylated STAT6 Ser564 to enhance STAT6 activation and ARG1 production. Together, we propose CH25H as an immunometabolic checkpoint, which manipulates macrophage fate to reshape CD8+ T cell surveillance and anti-tumor response.

Targeting 7-Dehydrocholesterol Reductase Integrates Cholesterol Metabolism and IRF3 Activation to Eliminate Infection.

Recent work suggests that cholesterol metabolism impacts innate immune responses against infection. However, the key enzymes or the natural products and mechanisms involved are not well elucidated. Here, we have shown that upon DNA and RNA viral infection, macrophages reduced 7-dehydrocholesterol reductase (DHCR7) expression. DHCR7 deficiency or treatment with the natural product 7-dehydrocholesterol (7-DHC) could specifically promote phosphorylation of IRF3 (not TBK1) and enhance type I interferon (IFN-I) production in macrophages. We further elucidated that viral infection or 7-DHC treatment enhanced AKT3 expression and activation. AKT3 directly bound and phosphorylated IRF3 at Ser385, together with TBK1-induced phosphorylation of IRF3 Ser386, to achieve IRF3 dimerization. Deletion of DHCR7 and the DHCR7 inhibitors including AY9944 and the chemotherapy drug tamoxifen promoted clearance of Zika virus and multiple viruses in vitro or in vivo. Taken together, we propose that the DHCR7 inhibitors and 7-DHC are potential therapeutics against emerging or highly pathogenic viruses.

AKT2 reduces IFNß1 production to modulate antiviral responses and systemic lupus erythematosus.

Interferon regulatory factor 3 (IRF3)-induced type I interferon (I-IFN) production plays key roles in both antiviral and autoimmune responses. IRF3 phosphorylation, dimerization, and nuclear localization are needed for its activation and function, but the precise regulatory mechanisms remain to be explored. Here, we show that the serine/threonine kinase AKT2 interacts with IRF3 and phosphorylates it on Thr207, thereby attenuating IRF3 nuclear translocation in a 14-3-3ε-dependent manner and reducing I-IFN production. We further find that AKT2 expression is downregulated in viral-infected macrophages or in monocytes and tissue samples from systemic lupus erythematosus (SLE) patients and mouse models. Akt2-deficient mice exhibit increased I-IFN induction and reduced mortality in response to viral infection, but aggravated severity of SLE. Overexpression of AKT2 kinase-inactive or IRF3-T207A mutants in zebrafish supports that AKT2 negatively regulates I-IFN production and antiviral response in a kinase-dependent manner. This negative role of AKT2 in IRF3-induced I-IFN production suggests that AKT2 may be therapeutically targeted to differentially regulate antiviral infection and SLE.

Causal relationship between psoriasis vulgaris and dementia: Insights from Mendelian randomization analysis.

Many clinical studies have demonstrated a correlation between psoriasis vulgaris and dementia, yet this correlation remains controversial. Our study employed the Mendelian randomization (MR) method to investigate the causal relationship between psoriasis vulgaris and dementia. Data were obtained from the summary statistics of the genome-wide association studies from IEU-OpenGWAS project database. In univariate Mendelian randomization (UVMR) analysis, psoriasis vulgaris was used as exposure. Alzheimer disease (AD), vascular dementia (VaD), dementia with Lewy bodies (DLB), Parkinson's disease with dementia (PDD) and frontotemporal dementia (FTD) served as the outcomes. In multivariate Mendelian randomization (MVMR) analysis, VaD served as the outcome. The first MVMR analysis used psoriasis vulgaris, mean platelet volume (MPV), platelet distribution width (PDW) and platelet count (PLT) as exposures. The second MVMR analysis used psoriasis vulgaris, vitamin D level and 25 hydroxyvitamin D level as exposures. The main analysis employed the inverse variance weighted method, and the outcomes were evaluated by odds ratio (OR) and 95% confidence interval (95% CI). In UVMR analysis, the results depicted that psoriasis vulgaris was associated with VaD (OR: 0.903, 95% CI: 0.818-0.996, p = 0.041). The results revealed insignificant associations between psoriasis vulgaris and other dementia types. After adjusting the effects of MPV, PDW and PLT in MVMR analysis, the association between psoriasis vulgaris and VaD was no longer significant (p = 0.164). Similarly, after adjusting the effects of vitamin D level and 25 hydroxyvitamin D level in MVMR analysis, the association between psoriasis vulgaris and VaD was also no longer significant (p = 0.533). Our study suggests that psoriasis vulgaris may potentially decrease VaD incidence. However, the causal association between psoriasis vulgaris and VaD may be impeded by platelet-related indices, vitamin D level and 25 hydroxyvitamin D level.

CSNK1D-mediated phosphorylation of HNRNPA2B1 induces miR-25-3p/miR-93-5p maturation to promote prostate cancer cell proliferation and migration through m6A-dependent manner.

It has been reported that heterogeneous nuclear ribonucleoprotein A2/B1 (HNRNPA2B1) is highly expressed in prostate cancer (PCa) and associated with poor prognosis of patients with PCa. Nevertheless, the specific mechanism underlying HNRNPA2B1 functions in PCa remains not clear. In our study, we proved that HNRNPA2B1 promoted the progression of PCa through in vitro and in vivo experiments. Further, we found that HNRNPA2B1 induced the maturation of miR-25-3p/miR-93-5p by recognizing primary miR-25/93 (pri-miR-25/93) through N6-methyladenosine (m6A)-dependent manner. In addition, both miR-93-5p and miR-25-3p were proven as tumor promoters in PCa. Interestingly, by mass spectrometry analysis and mechanical experiments, we found that casein kinase 1 delta (CSNK1D) could mediate the phosphorylation of HNRNPA2B1 to enhance its stability. Moreover, we further proved that miR-93-5p targeted BMP and activin membrane-bound inhibitor (BAMBI) mRNA to reduce its expression, thereby activating transforming growth factor ß (TGF-ß) pathway. At the same time, miR-25-3p targeted forkhead box O3 (FOXO3) to inactivate FOXO pathway. These results collectively indicated that CSNK1D stabilized HNRNPA2B1 facilitates the processing of miR-25-3p/miR-93-5p to regulate TGF-ß and FOXO pathways, resulting in PCa progression. Our findings supported that HNRNPA2B1 might be a promising target for PCa treatment.

Polyoxometalates-Based Semi-flexible Metal-Semiconductor Triboelectric Nanogenerators for Low Frequency and Small Amplitude Mechanical Energy Harvesting.

The development of high-performance and low-cost durable triboelectric nanogenerators (TENGs) is essential for converting mechanical energy into electrical energy. Many organic polymer friction materials used widely have thermal stability problems, which makes TENGs with semiconductors as friction materials stand out. Here, we report a semi-flexible TENG based on metal and TiO2 modified by polyoxometalates (POMs) as pure inorganic friction materials. Six different POMs are firstly selected to modify the friction materials of TENGs, and the output performance of TENGs with different POMs-modified semiconductors and different metals as friction materials are tested. Compared with the unmodified TENGs, the open-circuit voltage (VOC ) of the optimal Ag-K6 P2 Mo18 O62 (P2 Mo18 )/TiO2 TENG device is increased by more than 4 times, which is mainly attributed to the strong electron-accepting and storage capabilities of POMs. This study has demonstrated that TENGs modified by POMs have potential application prospects and provided a new method for increasing the electrical output of TENGs.

Hua-Feng-Dan alleviates LPS-induced neuroinflammation by inhibiting the TLR4/Myd88/NF-κB pathway: Through Integrating Network Pharmacology and Experimental Validation.

BACKGROUND: Neuroinflammation is the pathological basis of many neurological diseases, including neurodegenerative diseases and stroke. Hua-Feng-Dan (HFD) is a well-established traditional Chinese medicine that has been used for centuries to treat stroke and various other brain-related ailments. OBJECTIVE: Our study aims to elucidate the molecular mechanism by which HFD mitigates neuroinflammation by combining network pharmacology and in vitro experiments. METHODS: TCMSP and SymMap databases were used to extract active compounds and their related targets. The neuroinflammation-related targets were obtained from the GeneCards database. The common targets of HFD and neuroinflammation were used to construct a protein-protein interaction (PPI) network. MCODE plug-in was used to find the hub module genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to dissect the hub module genes. The lipopolysaccharide (LPS)-induced BV2 microglial neuroinflammation model was utilized to assess the therapeutic effects of HFD on neuroin- flammation. Western blotting analysis was performed to examine the core target proteins in the TLR4/My- D88/NF-κB signaling pathway, potentially implicated in HFD's therapeutic effects on neuroinflammation. Hoechst 33342 staining and JC-1 staining were employed to evaluate neuronal apoptosis. RESULTS: Through network pharmacology, 73 active compounds were identified, with quercetin, beta-sitos- terol, luteolin, and (-)-Epigallocatechin-3-Gallate recognized as important compounds. Meanwhile, 115 com- mon targets of HFD and neuroinflammation were identified, and 61 targets were selected as the hub targets uti- lizing the MCODE algorithm. The results of in vitro experiments demonstrated that HFD significantly inhibit- ed microglial-mediated neuronal inflammation induced by LPS. Integrating the predictions from network phar- macology with the in vitro experiment results, it was determined that the mechanism of HFD in mitigating neu- roinflammation is closely related to the TLR4/MyD88/NF-κB pathway. Furthermore, HFD demonstrated the capacity to shield neurons from apoptosis by curbing the secretion of pro-inflammatory factors subsequent to microglial activation. CONCLUSION: The findings demonstrated that HFD had an inhibitory effect on LPS-induced neuroinflammation in microglia and elucidated its underlying mechanism. These findings will offer a theoretical foundation for the clinical utilization of HFD in treating neurodegenerative diseases associated with neuroinflammation.

LncNAP1L6 activates MMP pathway by stabilizing the m6A-modified NAP1L2 to promote malignant progression in prostate cancer.

Malignant progression such as bone metastasis, which is associated with pathologic fractures, pain and reduced survival frequently occurs in prostate cancer (PCa) patients at advanced stages. Accumulating evidence has supported that long non-coding RNAs (lncRNAs) participate in multiple biological processes. Nevertheless, the functions of most lncRNAs in PCa malignant progression remain largely unclear. Our current study is to elucidate the influence of lncRNA lncNAP1L6 on PCa malignant progression and uncover the possible regulatory mechanism. Firstly, RT-qPCR analysis was to detect lncNAP1L6 expression and suggested that lncNAP1L6 was markedly upregulated in PCa cells. Functional assays manifested that silencing of lncNAP1L6 hampered cell migration, invasion, and epithelial-mesenchymal transition (EMT) while overexpression of lncNAP1L6 exacerbated cell migration, invasion and EMT. In addition, mechanism assays were to determine the latent regulatory mechanism of lncNAP1L6. It turned out that METTL14/METTL3 complex mediated m6A methylation of NAP1L2 mRNA. Besides, lncNAP1L6 recruited HNRNPC to m6A-modified NAP1L2, leading to stabilization of NAP1L2 mRNA. Moreover, NAP1L6 interacted with YY1 to promote the transcription of MMP2 and MMP9 and activate MMP signaling pathway. In summary, lncNAP1L6 was identified as an oncogene in PCa, which revealed that lncNAP1L6 might be used as potential therapeutic target in PCa.

Refined Qingkailing protects the in vitro neurovascular unit against oxygen-glucose deprivation and re-oxygenation-induced injury.

Since the proposal of the neurovascular unit (NVU) theory, it has become almost mandatory for neuroprotective medicines against ischaemic stroke (IS) to focus on this unit. Refined Qingkailing (RQKL) is a compound composed of hyodeoxycholic acid, geniposide, baicalin and cholic acid, which has shown great potential in the treatment of IS, but its effect on NVU has not been fully studied. The purpose of this study was to investigate the potential biological pathways that underlie the protective effects of RQKL against NVU damage induced by oxygen-glucose deprivation and re-oxygenation (OGD/R). Using in vitro OGD/R models, we looked into whether RQKL protects the NVU. In order to create an in vitro NVU that resembles IS, we created an OGD/R injury model using primary cultures of brain microvascular endothelial cells, neurons, and astrocytes. Based on our results, we present evidence, for the first time, that RQKL treatment of the injury caused by OGD/R significantly (1) kept the blood brain barrier (BBB) functioning and maintained the architecture of the neurons, (2) mitigated the oxidative stress damage, inflammatory cytokine release, and neuronal death, and (3) upregulated the expression of neurotrophic factors generated from glial cells and the brain in the in vitro model. Therefore, RQKL has a variety of preventive effects against NVU damage caused by OGD/R. RQKL may be a suitable medication for treating IS in a clinical setting.

Emerging effects of non-coding RNA in vascular endothelial cells during strokes.

Vascular and neurological damage are the typical outcomes of ischemic strokes. Vascular endothelial cells (VECs), a substantial component of the blood-brain barrier (BBB), are necessary for normal cerebrovascular physiology. During an ischemic stroke (IS), changes in the brain endothelium can lead to a BBB rupture, inflammation, and vasogenic brain edema, and VECs are essential for neurotrophic effects and angiogenesis. Non-coding RNAs (nc-RNAs) are endogenous molecules, and brain ischemia quickly changes the expression patterns of several non-coding RNA types, such as microRNA (miRNA/miR), long non-coding RNA (lncRNA), and circular RNA (circRNA). Furthermore, vascular endothelium-associated nc-RNAs are important mediators in the maintenance of healthy cerebrovascular function. In order to better understand how VECs are regulated epigenetically during an IS, in this review, we attempted to assemble the molecular functions of nc-RNAs that are linked with VECs during an IS.

Comprehensive Genomic Characterization of Tumor Microenvironment and Relevant Signature in Clear Cell Renal Cell Carcinoma.

Purpose: To systematically investigate the characterization of tumor microenvironment (TME) in clear cell renal cell carcinoma (ccRCC), we performed a comprehensive analysis incorporating genomic alterations, cellular interactions, infiltrating immune cells, and risk signature. Patients and Methods: Multi-omics data including RNA-seq, single-nucleotide variant (SNV) data, copy number variation (CNV) data, miRNA, and corresponding prognostic data were obtained from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) database. The CIBERSORT algorithm was utilized to identify prognostic TME subclusters, and TMEscore was further quantified. Moreover, the mutational landscape of TCGA-KIRC was explored. Lastly, TIDE resource was applied to assess the significance of TMEscore in predicting immunotherapeutic benefits. Results: We analyzed the TME infiltration patterns from 621 ccRCC patients and identified 5 specific TME subclusters associated with clinical outcomes. Then, we found that TMEcluster5 was significantly related to favorable prognosis and enriched memory B-cell infiltration. Accordingly, we depicted the clustering landscape of TMEclusters, TMEscore levels, tumor mutation burden (TMB), tumor grades, purity, and ploidy in all patients. Lastly, TIDE was used to assess the efficiency of immune checkpoint blockers (ICBs) and found that the TMEscore has superior predictive significance to TMB, making it an essential independent prognostic biomarker and drug indicator for clinical use. Conclusions: Our study depicted the clustering landscape of TMEclusters, TMEscore levels, TMB, tumor grades, purity, and ploidy in total ccRCC patients. The TMEscore was proved to have promising significance for predicting prognosis and ICB responses, in accordance with the goal of developing rationally individualized therapeutic interventions.

Comprehensive FGFR3 alteration-related transcriptomic characterization is involved in immune infiltration and correlated with prognosis and immunotherapy response of bladder cancer.

Background: Bladder cancer (BC) threatens the health of human beings worldwide because of its high recurrence rate and mortality. As an actionable biomarker, fibroblast growth factor receptor 3 (FGFR3) alterations have been revealed as a vital biomarker and associated with favorable outcomes in BC. However, the comprehensive relationship between the FGFR3 alteration associated gene expression profile and the prognosis of BC remains ambiguous. Materials and Methods: Genomic alteration profile, gene expression data, and related clinical information of BC patients were downloaded from The Cancer Genomics database (TCGA), as a training cohort. Subsequently, the Weighted Gene Co-expression Network Analysis (WGCNA) was conducted to identify the hub modules correlated with FGFR3 alteration. The univariate, multivariate, and least absolute shrinkage and selection operator (LASSO) Cox regression analyses were used to obtain an FGFR3 alteration-related gene (FARG) prognostic signature and FARG-based nomogram. The receiver operating characteristic (ROC) curve analysis was used for evaluation of the ability of prognosis prediction. The FARG signature was validated in four independent datasets, namely, GSE13507, GSE31684, GSE32548, and GSE48075, from Gene Expression Omnibus (GEO). Then, clinical feature association analysis, functional enrichment, genomic alteration enrichment, and tumor environment analysis were conducted to reveal differential clinical and molecular characterizations in different risk groups. Lastly, the treatment response was evaluated in the immunotherapy-related dataset of the IMvigor210 cohort and the frontline chemotherapy dataset of GSE48276, and the chemo-drug sensitivity was estimated via Genomics of Drug Sensitivity in Cancer (GDSC). Results: There were a total of eleven genes (CERCAM, TPST1, OSBPL10, EMP1, CYTH3, NCRNA00201, PCDH10, GAP43, COLQ, DGKB, and SETBP1) identified in the FARG signature, which divided BC patients from the TCGA cohort into high- and low-risk groups. The Kaplan-Meier curve analysis demonstrated that BC patients in the low-risk group have superior overall survival (OS) than those in the high-risk group (median OS: 27.06 months vs. 104.65 months, p < 0.0001). Moreover, the FARG signature not only showed a good performance in prognosis prediction, but also could distinguish patients with different neoplasm disease stages, notably whether patients presented with muscle invasive phenotype. Compared to clinicopathological features, the FARG signature was found to be the only independent prognostic factor, and subsequently, a FARG-based prognostic nomogram was constructed with better ability of prognosis prediction, indicated by area under ROC curve (AUC) values for 1-, 3-, and 5-year OS of 0.69, 0.71, and 0.79, respectively. Underlying the FARG signature, multiple kinds of metabolism- and immune-related signaling pathways were enriched. Genomic alteration enrichment further identified that FGFR3 alterations, especially c.746C>G (p.Ser249Cys), were more prevalent in the low-risk group. Additionally, FARG score was positively correlated with ESTIMATE and TIDE scores, and the low-risk group had abundant enrichment of plasma B cells, CD8+ T cells, CD4+ naive T cells, and helper follicular T cells, implying that patients in the low-risk group were likely to make significant responses to immunotherapy, which was further supported by the analysis in the IMvigor210 cohort as there was a significantly higher response rate among patients with lower FARG scores. The analysis of the GDSC database finally demonstrated that low-risk samples were more sensitive to methotrexate and tipifarnib, whereas those in the high-risk group had higher sensitivities in cisplatin, docetaxel, and paclitaxel, instead. Conclusion: The novel established FARG signature based on a comprehensive FGFR3 alteration-related transcriptomic profile performed well in prognosis prediction and was also correlated with immunotherapy and chemotherapy treatment responses, which had great potential in future clinical applications.

Targeting lysophospholipid acid receptor 1 and ROCK kinases promotes antiviral innate immunity.

Growing evidence indicates the vital role of lipid metabolites in innate immunity. The lipid lysophosphatidic acid (LPA) concentrations are enhanced in patients upon HCV or SARS-CoV-2 infection, but the function of LPA and its receptors in innate immunity is largely unknown. Here, we found that viral infection promoted the G protein­coupled receptor LPA1 expression, and LPA restrained type I/III interferon production through LPA1. Mechanistically, LPA1 signaling activated ROCK1/2, which phosphorylated IRF3 Ser97 to suppress IRF3 activation. Targeting LPA1 or ROCK in macrophages, fibroblasts, epithelial cells, and LPA1 conditional KO mice promoted interferon-induced clearance of multiple viruses. LPA1 was colocalized with the receptor ACE2 in lung and intestine. Together with previous findings that LPA1 and ROCK1/2 promoted vascular leaking or lung fibrosis, we propose that the current available preclinical drugs targeting the LPA1-ROCK module might protect from SARS-CoV-2 or various virus infections in the intestine or lung.

M-CSF, IL-6, and TGF-ß promote generation of a new subset of tissue repair macrophage for traumatic brain injury recovery.

Traumatic brain injury (TBI) leads to high mortality rate. We aimed to identify the key cytokines favoring TBI repair and found that patients with TBI with a better outcome robustly increased concentrations of macrophage colony-stimulating factor, interleukin-6, and transforming growth factor-ß (termed M6T) in cerebrospinal fluid or plasma. Using TBI mice, we identified that M2-like macrophage, microglia, and endothelial cell were major sources to produce M6T. Together with the in vivo tracking of mCherry+ macrophages in zebrafish models, we confirmed that M6T treatment accelerated blood-borne macrophage infiltration and polarization toward a subset of tissue repair macrophages that expressed similar genes as microglia for neuroprotection, angiogenesis and cell migration. M6T therapy in TBI mice and zebrafish improved neurological function while blocking M6T-exacerbated brain injury. Considering low concentrations of M6T in some patients with poor prognostic, M6T treatment might repair TBI via generating a previously unidentified subset of tissue repair macrophages.

Genome-wide screening of abberant methylated drivers combined with relative risk loci in bladder cancer.

BACKGROUND: To explore important methylation-driven genes (MDGs) and risk loci to construct risk model for prognosis of bladder cancer (BCa). METHODS: We utilized TCGA-Assembler package to download 450K methylation data and corresponding transcriptome profiles. MethylMix package was used for identifying methylation-driven genes and functional analysis was mainly performed based on ConsensusPathDB database. Then, Cox regression method was utilized to find prognostic MDGs, and we selected 17 hub genes via stepwise regression and multivariate Cox models. Kruskal-Wallis test was implemented for comparisons between risk with other clinical variables. Moreover, we constructed the risk model and validated it in GSE13507. Gene set enrichment analysis was performed using the levels of risk score as the phenotype. Additionally, we further screened out the relative methylation sites associated with the 17 hub genes. Cox regression and Survival analysis were conducted to find the specifically prognostic sites. RESULTS: Two hundred and twenty-eight MDGs were chosen by ConsensusPathDB database. Results revealed that most conspicuous pathways were transcriptional mis-regulation pathways in cancer and EMT. After Cox regression analysis, 17 hub epigenetic MDGs were identified. We calculated the risk score and found satisfactory predictive efficiency by ROC curve (AUC = 0.762). In the validation group from GSE13507, 17 hub genes remained higher predictive value with AUC = 0.723 and patients in high-risk group. Meanwhile, Kruskal-Wallis test revealed that higher risk score correlated with a higher level of TNM stage, tumor grade, and advanced pathological stages. Then, identified 38 risk methylated loci that highly associated with prognosis. Last, gene set enrichment analysis revealed that high-risk level of MDGs may correlate with several important pathways, including MAPK signaling pathway and so on. CONCLUSION: Our study indicated several hub-MDGs, calculated novel risk score and explored the prognostic value in BCa, which provided a promising approach to BCA prognosis assessment.

Nomograms to predict overall and cancer-specific survival in patients with upper tract urothelial carcinoma: a large population-based study.

BACKGROUND: To develop and validate survival nomograms for predicting the overall survival (OS) and cancer-specific survival (CSS) in upper tract urothelial carcinoma (UTUC) patients. METHOD: Patients diagnosed with UTUC from 2010 to 2015 in the Surveillance, Epidemiology, and End Results (SEER) database were retrospectively enrolled. Clinical characteristics and survival outcomes were respectively collected from the included patients. Then, eligible patients were divided into the training cohort and the validation cohort. Additionally, survival nomograms were developed based on the results of multivariate Cox analysis in the training cohort. Furthermore, Kaplan-Meier (KM) survival curves were generated to assess the actual effect of each variable. Lastly, the nomograms were validated using the concordance index (C-index), the area under the receiver operating characteristic (ROC) curve and calibration curves. RESULTS: Totally, 3,556 patients were included, with 2,492 in the training cohort and 1,064 in the validation cohort. No significant differences were detected in comparisons in clinical characteristics between two cohorts. Based on the results of uni- and multivariate Cox regression analysis, seven factors (age, TNM stage, use of surgery/radiation and marital status) for OS and six factors (age, TNM stage and use of surgery/radiation) for CSS were selected to develop the survival nomograms. The C-index for OS and CSS was 0.763 and 0.793 in the training cohort, and 0.759 and 0.784 in the validation cohort. Additionally, the 3- and 5-year AUCs for OS were 0.808 and 0.780 in the training cohort, and 0.785 and 0.778 in the validation group. As for CSS, it was 0.833 and 0.803 in the training cohort, and 0.815 and 0.810 in the validation cohort. Lastly, the calibration curves indicated a good consistency between the actual survival and the predictive survival. CONCLUSIONS: It was the first time to conduct survival models for UTUC patients with predictive performance. It might be valuable of clinical application and further exploration with more studies in the future.

Incidence trends and survival outcomes of penile squamous cell carcinoma: evidence from the Surveillance, Epidemiology and End Results population-based data.

BACKGROUND: To provide the latest incidence trends and explore survival outcomes of penile squamous cell carcinoma (PSCC) patients with or without a previous primary malignancy. METHODS: Patients diagnosed with PSCC between 1975 and 2016 in the Surveillance, Epidemiology, and End Results (SEER) database were retrospectively included. Then, we calculated the age-adjusted incidence rates (IRs) and annual percentage changes (APCs). Multivariate Cox analysis and Kaplan-Meier (KM) survival curves were conducted to investigate prognostic variables for cancer-specific survival (CSS). RESULTS: A total of 6,122 PSCC patients were enrolled, 1,137 of whom had a prior malignancy. The age-adjusted IR for the general population in men declined before 1987, fluctuated slightly between 1987 and 1997, and showed an upward trend after 1997, which was basically consistent with that in patients without a previous primary malignancy. The incidence trend of PSCC in the general population was similar with that in those without a previous malignancy. However, the IRs of PSCC in men with a previous malignancy have been increasing since 1975 regardless of race. Furthermore, age at diagnosis, pathological grade, extent of disease, marital status, the administration of surgery and presence of previous primary malignancy were identified to be significantly related to CSS. CONCLUSIONS: The IRs of PSCC have been increasing in recent years. Several independent prognostic factors for CSS were identified, allowing surgeons to assess the individualized risk in advance.

Comprehensive insights on pivotal prognostic signature involved in clear cell renal cell carcinoma microenvironment using the ESTIMATE algorithm.

Emerging evidence has highlighted that the immune and stromal cells formed the majority of tumor microenvironment (TME) which are served as important roles in tumor progression. In our study, we aimed to screen vital prognostic signature associated with TME in clear cell renal cell carcinoma (ccRCC). We obtained total 611 samples from TCGA database consisting of transcriptome profiles and clinical data. ESTIMATE algorithm was applied to estimate the infiltrating fractions of immune/stromal cells. We found that the immune scores revealed more prognostic significance in overall survival and positive associations with risk clinical factors than stromal scores. We carried out differential expression analysis between Immunescore and stromalscore groups to obtain the 72 intersect genes. Protein to protein interaction (PPI) network and functional analysis was performed to indicate potential altered pathways. Additionally, we further conducted multivariate Cox analysis to identify 12 hub genes associated highly with TME of ccRCC using a stepwise regression procedure. Accordingly, risk score was constructed from the multivariate Cox results and Receiver Operating Characteristic (ROC) curve was used to assess the predictive value (AUC = 0.781). The ccRCC patients with high risk scores suffered poor survival outcomes than that with low risk scores. In the validation cohort from GSE53757, TNFSF13B, CASP5, and GJB6 correlated positively with tumor stages, while FREM1 negatively correlated with tumor stages. Importantly, we further observed that TNFSF13B, CASP5 and XCR1 showed the remarkable correlations with tumor-infiltrating immune cells. Taken together, our research identified specific signatures that related to the infiltration of stromal and immune cells in TME of ccRCC using the transciptome profiles, which reached a comprehensive understanding of tumor microenvironment in ccRCC.

Screening TCGA database for prognostic genes in lower grade glioma microenvironment.

BACKGROUND: To identify prognostic hub genes which associated with tumor microenvironment (TME) in lower grade glioma (LGG) of central nervous system. METHODS: We downloaded LGG patients gene transcriptome profiles of the central nervous system in The Cancer Genome Atlas (TCGA) database. Clinical characteristics and survival data through the Genomic Data Commons (GDC) tool were extracted. We used limma package for normalization processing. Scores of immune, stromal and ESTIMATE were calculated using ESTIMATE algorithm. Then, box plots were applied to explore the association between immune scores, stromal scores, ESTIMATE scores and histological type, tumor grade. Kaplan-Meier (K-M) analysis was utilized to explore the prognostic value of scores. Furthermore, heatmaps and volcano plots were applied for visualizing expression of differential expressed-gene screening and cluster analysis. Venn plots were constructed to screen the intersected differentially expressed genes (DEGs). In addition, enrichment of functions and signaling pathways and Gene Set Enrichment Analysis (GESA) of the DEGs were performed. Then we used protein-protein interaction (PPI) network and Cytoscape software to identify hub genes. We evaluated the prognostic value of hub genes and risk score (RS) calculated based on multivariate cox regression analysis. Finally, relationships of hub genes with the TME of LGG patients were evaluated based on tumor immune estimation resource (TIMER) database. RESULTS: Gene expression profiles and clinical data of 514 LGG samples were extracted and the results revealed that higher scores were significantly related with histological types and higher tumor grade (P<0.0001, respectively). Besides, higher scores were associated with worse survival outcomes in immune scores (P=0.0167), stromal scores (P=0.0035) and ESTIMATE scores (P=0.0190). Then, 785 up-regulated intersected genes and 357 down-regulated intersected genes were revealed. Functional enrichment analysis revealed that intersected genes were associated with immune response, inflammatory response, plasma membrane and receptor activity. After PPI network construction and cytoHubba analysis, 25 tumor immune-related hub genes were identified and enriched pathways were identified by GSEA. Besides, receiver operating characteristic (ROC) curves showed significantly predictive accuracy [area under curve (AUC) =0.771] of RS. Furthermore, significant prognostic values of hub genes were observed, and the relationships between hub genes and LGG TME were demonstrated. CONCLUSIONS: We identified 25 TME-related genes which significantly associated with overall survival in patients with central nervous system LGG from TCGA database.

Identification of prognostic genes in adrenocortical carcinoma microenvironment based on bioinformatic methods.

BACKGROUND: To identify prognostic genes which were associated with adrenocortical carcinoma (ACC) tumor microenvironment (TME). METHODS AND MATERIALS: Transcriptome profiles and clinical data of ACC samples were collected from The Cancer Genome Atlas (TCGA) database. We use ESTIMATE (estimation of stromal and Immune cells in malignant tumor tissues using expression data) algorithm to calculate immune scores, stromal scores and estimate scores. Heatmap and volcano plots were applied for differential analysis. Venn plots were used for intersect genes selection. We used protein-protein interaction (PPI) networks and functional analysis to explore underlying pathways. After performing stepwise regression method and multivariate Cox analysis, we finally screened hub genes associated with ACC TME. We calculated risk scores (RS) for ACC cases based on multivariate Cox results and evaluated the prognostic value of RS shown by receiver operating characteristic curve (ROC). We investigated the association between hub genes with immune infiltrates supported by algorithm from online TIMER database. RESULTS: Gene expression profiles and clinical data were downloaded from TCGA. Lower immune scores were observed in disease with distant metastasis (DM) and locoregional recurrence (LR) than other cases (P = .0204). Kaplan-Meier analysis revealed that lower immune scores were significantly associated with poor overall survival (OS) (P = .0495). We screened 1649 differentially expressed genes (DEGs) and 1521 DEGs based on immune scores and stromal scores, respectively. Venn plots helped us find 1122 intersect genes. After analysing by cytoHubba from Cytoscape software, 18 hub genes were found. We calculated RS and ROC showed significantly predictive accuracy (area under curve (AUC) = 0.887). ACC patients with higher RS had worse survival outcomes (P < .0001). Results from TIMER (tumor immune estimation resource) database revealed that HLA-DOA was significantly related with immune cells infiltration. CONCLUSION: We screened a list of TME-related genes which predict poor survival outcomes in ACC patients from TCGA database.