Tumor microenvironment is associated with clinical and genetic properties of diffuse gliomas and predicts overall survival.

Tumor microenvironment (TME) is a complex and dynamic evolving environment which facilitates tumor proliferation and progression. We aimed at investigating the characteristics of tumor microenvironment and its prognostic value in gliomas. Transcriptome data of 702 glioma samples from The Cancer Genome Atlas were included as training dataset, while 325 samples from Chinese Glioma Genome Atlas database and 268 samples from GSE16011 database were used to validate. We found that the infiltration of stromal and immune cell varied in gliomas of different grades and pathological types, and was associated with poor prognosis. Based on the gene expression profile, we constructed a TME-related signature (TMERS), which was closely related to clinical features and genomic variation of gliomas. In TMERS-high group, specific gene mutations and increased copy number alternations were observed. Kaplan-Meier survival and Cox regression analysis showed that TMERS was an independent prognostic indicator. Then we developed a nomogram prognostic model to predict 1-year, 3-year and 5-year survival of patients. Functional analysis confirmed that TMERS could reflect the status of glioma microenvironment, and immunological analysis showed that macrophages were significantly enriched in the TMERS-high group. We established a novel TME-related signature for predicting prognosis and provided new insights into immunotherapy.

Comprehensive analysis of a TNF family based-signature in diffuse gliomas with regard to prognosis and immune significance.

BACKGROUND: Several studies have shown that members of the tumor necrosis factor (TNF) family play an important role in cancer immunoregulation, and trials targeting these molecules are already underway. Our study aimed to integrate and analyze the expression patterns and clinical significance of TNF family-related genes in gliomas. METHODS: A total of 1749 gliomas from 4 datasets were enrolled in our study, including the Cancer Genome Atlas (TCGA) dataset as the training cohort and the other three datasets (CGGA, GSE16011, and Rembrandt) as validation cohorts. Clinical information, RNA expression data, and genomic profile were collected for analysis. We screened the signature gene set by Cox proportional hazards modelling. We evaluated the prognostic value of the signature by Kaplan-Meier analysis and timeROC curve. Gene Ontology (GO) and Gene set enrichment analysis (GSEA) analysis were performed for functional annotation. CIBERSORT algorithm and inflammatory metagenes were used to reveal immune characteristics. RESULTS: In gliomas, the expression of most TNF family members was positively correlated. Univariate analysis showed that most TNF family members were related to the overall survival of patients. Then through the LASSO regression model, we developed a TNF family-based signature, which was related to clinical, molecular, and genetic characteristics of patients with glioma. Moreover, the signature was found to be an independent prognostic marker through survival curve analysis and Cox regression analysis. Furthermore, a nomogram prognostic model was constructed to predict individual survival rates at 1, 3 and 5 years. Functional annotation analysis revealed that the immune and inflammatory response pathways were enriched in the high-risk group. Immunological analysis showed the immunosuppressive status in the high-risk group. CONCLUSIONS: We developed a TNF family-based signature to predict the prognosis of patients with glioma. Video abstract.

Ethical issues of the research and practice in forensic genetics.

Forensic genetics mainly uses human biological samples as the objects, solves the identification of biological materials related to law by detecting genetic information, provides clues for investigation and evidences for trial, thus facing many ethical issues. This paper put forward the ethical principles in forensic genetics research and practice, and discussed the ethical issues in sample collection, forensic DNA phenotyping, forensic genetic genealogy analysis, forensic DNA database development, paternity and kinship testing, and research data sharing. We suggest that specific ethical requirements should be formulated, the ethical review system should be established for forensic genetics and ethical training for practitioners should be strengthened.

Experimental composable security decoy-state quantum key distribution using time-phase encoding.

Quantum key distribution (QKD) promises provably secure communications. In order to improve the secret key rate, combining a biased basis choice with the decoy-state method is proposed. Concomitantly, there is a basis-independent detection efficiency condition, which usually cannot be satisfied in a practical system, such as the time-phase encoding. Fortunately, this flaw has been recently removed theoretically and experimentally in the four-intensity decoy-state BB84 QKD protocol using the fact that the expected yields of single-photon states prepared in two bases stay the same for a given measurement basis. However, the security proofs do not fully consider the finite-key effects for general attacks. In this work, we provide the rigorous finite-key security bounds in the universally composable framework for the four-intensity decoy-state BB84 QKD protocol. We build a time-phase encoding system with 200 MHz clock to implement this protocol, in which the real-time secret key rate is more than 60 kbps over 50 km single-mode fiber.

Transcriptomic profiling identifies a nucleotide metabolism-related signature with prognostic power in gliomas.

OBJECTIVE: Nucleotide metabolic reprogramming as a hallmark of cancer is closely related to the occurrence and progression of cancer. We aimed to comprehensively analyze the nucleotide metabolism-related gene set and clinical significance in gliomas. METHODS: The RNA sequencing data of 702 gliomas from the Cancer Genome Atlas (TCGA) dataset were included as the training set, and the RNA sequencing data from the other three datasets (CGGA, GSE16011, and Rembrandt) were used as independent validation sets. Survival curve, Cox regression analysis, time-dependent ROC curve and nomogram model were performed to evaluate prognostic power of signature. R language was the main tool for bioinformatic analysis and graphical work. RESULTS: Based on the expression profiles of nucleotide metabolism-related genes, consensus clustering identified two robust clusters with different prognosis. We then developed a nucleotide metabolism-related signature that was closely related to clinical, pathological, and genomic characteristics of gliomas. And ROC curve showed that our signature was a potential biomarker for mesenchymal subtype. Survival curve and Cox regression analysis revealed signature as an independent prognostic factor for gliomas. In addition, we constructed a nomogram model to predict individual survival. Finally, functional analysis showed that nucleotide metabolism not only affected cell division and cell cycle, but also was associated with immune response in gliomas. CONCLUSION: We developed a nucleotide metabolism-related signature to predict prognosis and provided new insights into the role of nucleotide metabolism in gliomas.

Diagnostic performance evaluation of adult Chiari malformation type I based on convolutional neural networks.

PURPOSE: This study aimed to evaluate the diagnostic performance of convolutional neural network (CNN) models in Chiari malformation type I (CMI) and to verify whether CNNs can identify the morphological features of the craniocervical junction region between patients with CMI and healthy controls (HCs). To date, numerous indicators based on manual measurements are used for the diagnosis of CMI. However, the corresponding postoperative efficacy and prognostic evaluations have remained inconsistent. From a diagnostic perspective, CNN models may be used to explore the relationship between the clinical features and image morphological parameters. METHODS: This study included a total of 148 patients diagnosed with CMI at our institution and 205 HCs were included. T1-weighted sagittal magnetic resonance imaging (MRI) images were used for the analysis. A total of 220 and 355 slices were acquired from 98 patients with CMI and 155 HCs, respectively, to train and validate the CNN models. In addition, median sagittal images obtained from 50 patients with CMI and 50 HCs were selected to test the models. We applied original cervical MRI images (CI) and images of posterior cranial fossa and craniocervical junction area (CVI) to train the CI- and CVI-based CNN models. Transfer learning and data augmentation were used for model construction and each model was retrained 10 times. RESULTS: Both the CI- and CVI-based CNN models achieved high diagnostic accuracy. In the validation dataset, the models had diagnostic accuracy of 100% and 97% (p = 0.005), sensitivity of 100% and 98% (p = 0.016), and specificity of 100% (p = 0.929), respectively. In the test dataset, the accuracy was 97% and 96% (p = 0.25), sensitivity was 97% and 92% (p = 0.109), and specificity was 100% (p = 0.123), respectively. For patients with cerebellar subungual herniation less than 5 mm, three out of the 10 CVI-based retrained models reached 100% sensitivity. CONCLUSIONS: Our results revealed that the CNN models demonstrated excellent diagnostic performance for CMI. The models had higher sensitivity than the application of cerebellar tonsillar herniation alone and could identify features in the posterior cranial fossa and craniocervical junction area of patients. Our preliminary experiments provided a feasible method for the diagnosis and study of CMI using CNN models. However, further studies are needed to identify the morphologic characteristics of patients with different clinical outcomes, as well as patients who may benefit from surgery.

Comprehensive analysis of multi-omics data of recurrent gliomas identifies a recurrence-related signature as a novel prognostic marker.

Tumor recurrence is a common clinical dilemma in diffuse gliomas. We aimed to identify a recurrence-related signature to predict the prognosis for glioma patients. In the public Chinese Glioma Genome Atlas dataset, we enrolled multi-omics data including genome, epigenome and transcriptome across primary and recurrent gliomas. We included RNA sequencing data from the batch 1 patients (325 patients) as the training set, while RNA sequencing data from the batch 2 patients (693 patients) were selected as the validation set. The R language was used for subsequent analysis. Compared with primary gliomas, more somatic mutations and copy number alterations were revealed in recurrent gliomas. In recurrent gliomas, we identified 113 genes whose methylation levels were significantly different from those of the primary glioma. Through differential expression analysis between primary and recurrent gliomas, we screened 121 recurrence-related genes. Based on these 121 gene expression profiles, consensus clustering of 325 patients yielded two robust groups with different molecular and prognostic features. We developed a recurrence-related risk signature with the lasso regression algorithm. High-risk group had shorter survival and earlier tumor recurrence than the low-risk group. Compared with traditional indicators, the signature showed better prognostic value. In addition, we constructed a nomogram model to predict glioma survival. Functional characteristics analysis found that the signature was associated with cell division and cell cycle. Immune analysis suggested that immunosuppressive status and macrophages might promote glioma recurrence. We demonstrated a novel 18-gene signature that could effectively predict recurrence and prognosis for glioma patients.

MET overexpression contributes to STAT4-PD-L1 signaling activation associated with tumor-associated, macrophages-mediated immunosuppression in primary glioblastomas.

BACKGROUND: Dysregulated receptor tyrosine kinases, such as the mesenchymal-epidermal transition factor (MET), have pivotal role in gliomas. MET and its interaction with the tumor microenvironment have been previously implicated in secondary gliomas. However, the contribution of MET gene to tumor cells' ability to escape immunosurveillance checkpoints in primary gliomas, especially in glioblastoma (GBM), which is a WHO grade 4 glioma with the worst overall survival, is still poorly understood. METHODS: We investigated the relationship between MET expression and glioma microenvironment by using multiomics data and aimed to understand the potential implications of MET in clinical practice through survival analysis. RNA expression data from a total of 1243 primary glioma samples (WHO grades 2-4) were assembled, incorporating The Cancer Genome Atlas, Chinese Glioma Genome Atlas, and GSE16011 data sets. RESULTS: Pearson's correlation test from the three data sets indicated that MET showed a robust correlation with programmed death-ligand 1 (PD-L1) and STAT pathways. Western blot analysis revealed that in GBM cell lines (N33 and LN229), PD-L1 and phosphorylated STAT4 were upregulated by MET activation treatment with hepatocyte growth factor and were downregulated on MET suppression by PLB-1001. Tumor tissue microarray analysis indicated a positive correlation between MET and PD-L1 and macrophage-associated markers. Chromatin immunoprecipitation-PCR assay showed enrichment of STAT4 in the PD-L1 DNA. Transwell co-culture and chemotaxis assays revealed that knockdown of MET in GBM cells inhibited macrophage chemotaxis. Moreover, we performed CIBERSORTx and single-cell RNA sequencing data analysis which revealed an elevated number of macrophages in glioma samples with MET overexpression. Kaplan-Meier survival analysis indicated that activation of the MET/STAT4/PD-L1 pathway and upregulation of macrophages were associated with shorter survival time in patients with primary GBM. CONCLUSIONS: These data indicated that the MET-STAT4-PD-L1 axis and tumor-associated macrophages might enforce glioma immune evasion and were associated with poor prognosis in GBM samples, suggesting potential clinical strategies for targeted therapy combined with immunotherapy in patients with primary GBM.

Clinical and Molecular Characterization of Incidentally Discovered Lower-Grade Gliomas with Enrichment of Aerobic Respiration.

PURPOSE: Incidentally discovered diffusely infiltrating lower-grade gliomas (incidental LGGs, iLGGs) are defined as gliomas occasionally found in patients without tumor-related symptoms. At present, very few in-depth research studies on incidental LGGs were reported. We aimed to find out the inherent difference between iLGGs and LGGs with tumor-related symptoms. PATIENTS AND METHODS: We enrolled 2486 all-grade gliomas and screened 1594 lower-grade gliomas for further analysis. Medical records were retrospectively reviewed for iLGGs. Clinical and mRNA sequencing data were collected for in-depth analysis. RESULTS: We found that with increasing grade, the proportion of incidental glioma patients decreased obviously. In 1594 patients who underwent craniotomy for LGG, 80 (5%) patients were discovered incidentally. Grade II patients (88%) and patients bearing 1p/19q co-deletion in their tumors (23%) were more likely to be diagnosed as iLGGs. Regular radiological screening (48%) and trauma (24%) were the main complaint for brain imaging for iLGGs. Kaplan-Meier survival analysis indicated that iLGGs patients lived a significantly longer survival and Cox regression analysis revealed that iLGGs were an independent indicator of better prognosis. Subsequent gene set enrichment analysis and differential expression analysis based on the gene expression profile revealed that mitochondrial aerobic respiration process was enriched in iLGGs. Moreover, we found that iLGGs tended to generate energy by unique mitochondrial aerobic respiration. CONCLUSION: These results provided a primitive exploration of iLGGs, which may potentially assist clinical neurosurgeons with personalized management of iLGGs.

Prognostic Correlation of Autophagy-Related Gene Expression-Based Risk Signature in Patients with Glioblastoma.

PURPOSE: Autophagy plays a vital role in cancer initiation, malignant progression, and resistance to treatment; however, autophagy-related gene sets have rarely been analyzed in glioblastoma. The purpose of this study was to evaluate the prognostic significance of autophagy-related genes in patients with glioblastoma. PATIENTS AND METHODS: Here, we collected whole transcriptome expression data from the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) datasets to explore the relationship between autophagy-related gene expression and glioblastoma prognosis. R language was the primary analysis and drawing tool. RESULTS: We screened 531 autophagy-related genes and identified 14 associated with overall survival in data from 986 patients with glioblastoma. Patients could be clustered into two groups (high and low risk) using expression data from the 14 associated genes, based on significant differences in clinicopathology and prognosis. Next, we constructed a signature based on the 14 genes and found that most patients designated high risk using our gene signature were IDH wild-type, MGMT promoter non-methylated, and likely to have more malignant tumor subtypes (including classical and mesenchymal subtypes). Survival analysis indicated that patients in the high-risk group had dramatically shorter overall survival compared with their low-risk counterparts. Cox regression analysis further confirmed the independent prognostic value of our 14 gene signature. Moreover, functional and ESTIMATE analyses revealed enrichment of immune and inflammatory responses in the high-risk group. CONCLUSION: In this study, we identified a novel autophagy-related signature for the prediction of prognosis in patients with glioblastoma.

PD-L2 expression is correlated with the molecular and clinical features of glioma, and acts as an unfavorable prognostic factor.

Background: Gliomas are aggressive tumors with various molecular and clinical characteristics and exhibit strongly resistance to radio-chemotherapy. Programmed cell death 1 ligand 2 (PD-L2) is a cell surface protein, which was reported in many cancers, modulating cancer-associated immune responses, while the role of PD-L2 in gliomas remained unclear. Herein, we aimed to investigate the biological behaviors and clinical prognostic values of PD-L2 in gliomas. Methods: Totally, we enrolled RNA sequencing data of 325 glioma samples from Chinese Glioma Genome Atlas (CGGA) as training cohort and RNA expression data of 1032 samples from The Cancer Genome Atlas (TCGA) dataset as validation cohort in this research. Then, the clinical and molecular characteristics, and the prognostic value of PD-L2 were analyzed. Results: We found that PD-L2 expression level was significantly upregulated in higher grade glioma and IDH wild-type glioma. Receiver Operating Characteristic (ROC) analysis revealed that PD-L2 was a potential indicator of mesenchymal subtype. PD-L2 exhibited tight relationship with immune response and immune-modulating process in glioma. Moreover, PD-L2 expression level could predict unfavorable prognoses of patients independent of age, grade, IDH status and 1p/19q status. Conclusions: Our study revealed that PD-L2 was closely related with inflammation and immune response. Patients with lower PD-L2 expression level tended to experience improved survival. Targeting PD-L2 may become a valuable approach for the treatment of gliomas in clinical practice.

Immune Cytolytic Activity Is Associated With Genetic and Clinical Properties of Glioma.

Background: Immunotherapy provided unprecedented advances in the treatment of several previously untreated cancers. However, these immunomodulatory maneuvers showed limited response to patients with glioma in clinical trials. Our aim was to depict the immune characteristics of glioma with immune cytolytic activity at genetic and transcriptome levels. Methods: In total, 325 gliomas from CGGA dataset as training cohort and 699 gliomas from TCGA dataset as validation cohort were enrolled in our analysis. We calculated the immune cytolytic activity for 1,000 of gliomas. The characteristics of immune cytolytic activity in gliomas were interpreted by the corresponding clinical, molecular genetics and radiological information. Results: We found that immune cytolytic activity was highly associated with molecular, clinical, and edema extent. High cytolytic activity gliomas were more likely to be diagnosed as glioblastoma and might be a potential marker of mesenchymal subtype. Moreover, those gliomas exhibited significantly increased copy number alterations including recurrent focal amplifications of PDGFA and EGFR, as well as recurrent deletions of CDKN2A/B. Subsequent biological function analysis revealed that the immune response and immune checkpoints expression were significantly correlated with the cytolytic activity of gliomas. Immune cytolytic activity was significantly positively associated with the extent of peri-tumor edema and was independently correlated with reduced survival time. Conclusion: Our results highlighted the immunoregulatory mechanism heterogeneity of gliomas. Cytolytic activity, indirectly reflected by the extent of peri-tumor edema, may provide a potential index to evaluate the status of immune microenvironment and immune checkpoints in glioma, which should be fully valued for precision classification and immunotherapy.

A Novel DNA Methylation-Based Signature Can Predict the Responses of MGMT Promoter Unmethylated Glioblastomas to Temozolomide.

Glioblastoma (GBM) is the most malignant glioma, with a median overall survival (OS) of 14-16 months. Temozolomide (TMZ) is the first-line chemotherapy drug for glioma, but whether TMZ should be withheld from patients with GBMs that lack O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation is still under debate. DNA methylation profiling holds great promise for further stratifying the responses of MGMT promoter unmethylated GBMs to TMZ. In this study, we studied 147 TMZ-treated MGMT promoter unmethylated GBM, whose methylation information was obtained from the HumanMethylation27 (HM-27K) BeadChips (n = 107) and the HumanMethylation450 (HM-450K) BeadChips (n = 40) for training and validation, respectively. In the training set, we performed univariate Cox regression and identified that 3,565 CpGs were significantly associated with the OS of the TMZ-treated MGMT promoter unmethylated GBMs. Functional analysis indicated that the genes corresponding to these CpGs were enriched in the biological processes or pathways of mitochondrial translation, cell cycle, and DNA repair. Based on these CpGs, we developed a 31-CpGs methylation signature utilizing the least absolute shrinkage and selection operator (LASSO) Cox regression algorithm. In both training and validation datasets, the signature identified the TMZ-sensitive GBMs in the MGMT promoter unmethylated GBMs, and only the patients in the low-risk group appear to benefit from the TMZ treatment. Furthermore, these identified TMZ-sensitive MGMT promoter unmethylated GBMs have a similar OS when compared with the MGMT promoter methylated GBMs after TMZ treatment in both two datasets. Multivariate Cox regression demonstrated the independent prognostic value of the signature in TMZ-treated MGMT promoter unmethylated GBMs. Moreover, we also noticed that the hallmark of epithelial-mesenchymal transition, ECM related biological processes and pathways were highly enriched in the MGMT unmethylated GBMs with the high-risk score, indicating that enhanced ECM activities could be involved in the TMZ-resistance of GBM. In conclusion, our findings promote our understanding of the roles of DNA methylation in MGMT umethylated GBMs and offer a very promising TMZ-sensitivity predictive signature for these GBMs that could be tested prospectively.

Effects of azocyclotin on gene transcription and steroid metabolome of hypothalamic-pituitary-gonad axis, and their consequences on reproduction in zebrafish (Danio rerio).

The widely used organotins have the potential to disrupt the endocrine system, but little is known of underlying mechanisms of azocyclotin toxicity in fish. The objective of the present study was to investigate the impact of azocyclotin on reproduction in zebrafish. Adult zebrafish were exposed to 0.09 and 0.45µg/L azocyclotin for 21days, and effects on steroid hormones and mRNA expression of the genes belonging to the hypothalamic-pituitary-gonad (HPG) axis were investigated. Mass spectrometry methodology was developed to profile steroids within the metabolome of the gonads. They were disrupted as a result of azocyclotin exposure. Alterations in the expression of key genes associated with reproductive endocrine pathways in the pituitary (lhß), gonad (cyp19a1a, cyp17a1 and 17ß-hsd3), and liver (vtg1, vtg2, cyp1a1, comt, ugt1a and gstp1) were correlated with significant reductions in estrogen in both sexes and increased testosterone in females. Azocyclotin-induced down-regulation of cyp19a1a in males suggested a reduction in the rate of estrogen biosynthesis, while up-regulation of hepatic cyp1a1 and comt in both sexes suggested an increase in estrogen biotransformation and clearance. Azocyclotin also induced change in the expression of 17ß-hsd3, suggesting increased bioavailability of 11-ketotestosterone (11-KT) in the blood. Furthermore, the down-regulation of lhß expression in the brains of azocyclotin-exposed fish was associated with inhibition of oocyte maturation in females and retarded spermatogenesis in males. As a histological finding, retarded development of the ovaries was found to be an important cause for decreased fecundity, with down-regulation of vtg suspected to be a likely underlying mechanism. Additionally, relatively high concentrations of azocyclotin in the gonads may have directly caused toxicity, thereby impairing gametogenesis and reproduction. Embryonic or larval abnormalities occurred in the F1 generation along with accumulated burdens of azocyclotin in F1 eggs, following parental exposure. Overall, our results indicate that exposure to azocyclotin can impair reproduction in fish, and induce toxicity related abnormalities in non-exposed offspring.

Effects of tributyltin and benzo[a]pyrene on the immune-associated activities of hemocytes and recovery responses in the gastropod abalone, Haliotis diversicolor.

Our previous study reports that short-term exposure to sublethal concentrations of benzo[a]pyrene (BaP) induces immunomodulation in the gastropod abalone, Haliotis diversicolor. In the present study, it was further observed that long-term chronic exposure to sublethal concentrations of BaP modulated the immunocompetence of abalones in terms of the change in activity of the antioxidant and immune associated parameters tested. In addition, the effect of tributyltin (TBT), another important genotoxicant in the aquatic environment, was investigated. Exposure of abalones to sublethal concentrations of TBT and BaP for 21 days resulted in significant decrease of total hemocyte count, phagocytosis, membrane stability and lysozyme activity. Conversely induction of extra and intra cellular superoxide generation, nitric oxide, nitric oxide synthase and myeloperoxidase activity was present when the abalones were exposed to TBT and BaP. Most of the immune associated parameters tested showed clear time dependent response to both toxicants. Within 14 days after the 21 day exposure to BaP, recovery was observed as evidenced by most of the parameters returning to their normal level. However, no recovery was observed within 14 days after the 21 day exposure to TBT as evidenced by continued elevation of intra cellular superoxide and nitrite production and decrease in THC, membrane stability and lysozyme activity. This suggested a prolonged TBT-induced impact on the immune reaction and possibly more damage than that caused by BaP. Overall the results suggest that chronic exposure to sublethal concentrations of TBT or BaP causes modulations in the immunocompetence of abalones with most of the immune associated parameters tested being stimulated, and this might be harmful to the host.