Simpleaffy: a BioConductor package for Affymetrix Quality Control and data analysis

Polarized Macrophages Show Diverse Pro-Angiogenic Characteristics Under Normo- and Hyperglycemic Conditions

Angiogenesis plays a crucial role in solid tumor growth. Ischemia and inflammation induce various angiogenic mediators, and patient metabolic conditions importantly influence this process. Macrophages closely interact with the vascular system and regulate angiogenesis through pro/anti-angiogenic factors. Traditionally, pro-angiogenic activity has been attributed to M2-like macrophages. We question this, as recent evidence suggests that also M1-like macrophages can be pro-angiogenic. Therefore, the aim is to identify the pro/anti-angiogenic gene expression profiles of human polarized macrophages unbiasedly. We also examine the effect of hyperglycemia on angiogenic gene expression, reflecting its role in diabetes and other metabolic conditions. Bioinformatic analysis was performed on the angiogenesis-related gene expression profiles of CD14+ monocyte-derived M1(IFN-γ)- and M2(IL-4)-polarized macrophages. The top differentially expressed genes were selected for validation. Macrophages were generated in vitro and polarized to M1(IFN-γ) and M2(IL-4/IL-6) cells under standard/hyperglycemic conditions. After immunophenotypic confirmation, selected gene expression was quantified using qPCR. IL-4 and IL-6 induce distinct M2-like phenotypes with mixed pro/anti-angiogenic gene expression. Remarkably, IFN-γ stimulation also increases several pro-angiogenic genes. Hyperglycemia affects the angiogenic expression profile in both M1- and M2-like macrophages, although distinctive identities remain intact. The pro-angiogenic phenotype is not limited to M2-polarized macrophages. Both M1- and M2-like macrophages express complex pro/anti-angiogenic gene profiles, which are only mildly influenced by hyperglycemia.

Elevated Expression of Cell Adhesion, Metabolic, and Mucus Secretion Gene Clusters Associated with Tumorigenesis, Metastasis, and Poor Survival in Pancreatic Ductal Adenocarcinoma

OBJECTIVES

Technological advances in identifying gene expression profiles are being applied to study an array of cancers. The goal of this study was to identify differentially expressed genes in pancreatic ductal adenocarcinoma (PDAC) and examine their potential role in tumorigenesis and metastasis.

METHODS

The transcriptomic profiles of PDAC and non-tumorous tissue samples were derived from the gene expression omnibus (GEO), which is a public repository. The GEO2R tool was used to further derive differentially expressed genes from those profiles.

RESULTS

In this study, a total of 68 genes were derived from upregulated PDAC genes in three or more transcriptomic profiles and were considered PDAC gene sets. The identified PDAC gene sets were examined in the molecular signatures database (MSigDB) for ontological investigation, which revealed that these genes were involved in the extracellular matrix and associated with the cell adhesion process in PDAC tumorigenesis. The gene set enrichment analysis showed greater enrichment scores for the gene sets. Moreover, the identified gene sets were examined for protein-protein interaction using the STRING database. Based on functional k-means clustering, the following three functional cluster groups were identified in this study: extracellular matrix/cell adhesion, metabolic, and mucus secretion-related protein groups. The receiver operating characteristic (ROC) curve revealed greater specificity and sensitivity for these cluster genes in predicting PDAC tumorigenesis and metastases. In addition, the expression of the cluster genes affects the overall survival rate of PDAC patients. Using the cancer genome atlas (TCGA) database, the associations between expression levels and clinicopathological features were validated.

CONCLUSIONS

Overall, the genes identified in this study appear to be critical in PDAC development and can serve as potential diagnostic and prognostic targets for pancreatic cancer treatment.

Increased Expression and Prognostic Significance of BYSL in Melanoma

We evaluated the BYSL content and underlying mechanism in melanoma (SKCM) overall survival (OS). In this study, we used a comprehensive approach combining bioinformatics tools, including miRNA estimation, quantitative real-time polymerase chain reaction (qRT-PCR) of miRNAs, E3 ligase estimation, STRING analysis, TIMER analysis, examination of associated upstream modulators, protein-protein interaction (PPI) analysis, as well as retrospective and survival analyses, alongside clinical sample validation. These methods were used to investigate the content of BYSL, its methylation status, its relation to patient outcome, and its immunologic significance in tumors. Our findings revealed that BYSL expression is negatively regulated by BYSL methylation. Analysis of 468 cases of SKCM RNA sequencing samples demonstrated that enhanced BYSL expression was associated with higher tumor grade. We identified several miRNAs, namely hsa-miR-146b-3p, hsa-miR-342-3p, hsa-miR-511-5p, hsa-miR-3690, and hsa-miR-193a-5p, which showed a strong association with BYSL levels. Furthermore, we predicted the E3 ubiquitin ligase of BYSL and identified CBL, FBXW7, FZR1, KLHL3, and MARCH1 as potential modulators of BYSL. Through our investigation, we discovered that PNO1, RIOK2, TSR1, WDR3, and NOB1 proteins were strongly associated with BYSL expression. In addition, we found a close association between BYSL levels and certain immune cells, particularly dendritic cells (DCs). Notably, we observed a significant negative correlation between miR-146b-3p and BYSL mRNA expression in SKCM sera samples. Collectively, based on the previously shown evidences, BYSL can serve as a robust bioindicator of SKCM patient prognosis, and it potentially contributes to immune cell invasion in SKCM.

Signature Genes Selection and Functional Analysis of Astrocytoma Phenotypes: A Comparative Study

Novel cancer biomarkers discoveries are driven by the application of omics technologies. The vast quantity of highly dimensional data necessitates the implementation of feature selection. The mathematical basis of different selection methods varies considerably, which may influence subsequent inferences. In the study, feature selection and classification methods were employed to identify six signature gene sets of grade 2 and 3 astrocytoma samples from the Rembrandt repository. Subsequently, the impact of these variables on classification and further discovery of biological patterns was analysed. Principal component analysis (PCA), uniform manifold approximation and projection (UMAP), and hierarchical clustering revealed that the data set (10,096 genes) exhibited a high degree of noise, feature redundancy, and lack of distinct patterns. The application of feature selection methods resulted in a reduction in the number of genes to between 28 and 128. Notably, no single gene was selected by all of the methods tested. Selection led to an increase in classification accuracy and noise reduction. Significant differences in the Gene Ontology terms were discovered, with only 13 terms overlapping. One selection method did not result in any enriched terms. KEGG pathway analysis revealed only one pathway in common (cell cycle), while the two methods did not yield any enriched pathways. The results demonstrated a significant difference in outcomes when classification-type algorithms were utilised in comparison to mixed types (selection and classification). This may result in the inadvertent omission of biological phenomena, while simultaneously achieving enhanced classification outcomes.

Neutrophil extracellular trap genes predict immunotherapy response in gastric cancer

Background

Neutrophil extracellular trap (NET) is associated with host response, tumorigenesis, and immune dysfunction. However, the link between NET and the tumor microenvironment (TME) of gastric cancer (GC) remains unclear. Our study aims to characterize the expression patterns of NET-related genes and their relationships with clinicopathological characteristics, prognosis, TME features, and immunotherapy efficacy in GC cohorts.

Methods

Transcriptomic and single-cell RNA sequencing profiles of GC with annotated clinicopathological data were obtained from TCGA-STAD (n = 415), GSE62254 (n = 300), GSE15459 (n = 192), and GSE183904 (n = 26). The consensus cluster algorithm was used to classify tumor samples into different NET-related clusters. A NET-related signature was constructed using LASSO regression and verified in four immunotherapy cohorts. ROC and Kaplan-Meier analyses were conducted to evaluate the predictive and prognostic value of the model for immunotherapy efficacy.

Results

This study identified two NET-related clusters with distinct clinicopathological features, prognosis, and TME landscapes. The high NET-related cluster, characterized by increased NET-related gene expression, exhibited more aggressive behavior and a worse prognosis (HR = 1.63, P = 0.004) than the low NET-related cluster. DEGs were primarily involved in the chemokine/cytokine-associated pathways. Moreover, the high NET-related cluster had significantly higher levels of TME scores, immune infiltration, and immune effectors (all P < 0.001). The NET-related signature displayed a high predictive accuracy for immunotherapy response (AUC = 0.939, P < 0.001). Furthermore, patients with high NET-related scores consistently harbored a more favorable prognosis in different immunotherapy cohorts (all P < 0.05).

Conclusions

This study identified the NET-related signature as a robust model for predicting immunotherapy response in GC, which can help clinicians make appropriate immunotherapy decisions.

Amplified Cell Cycle Genes Identified in High-Grade Serous Ovarian Cancer

The objective of this study was to identify differentially expressed genes and their potential influence on the carcinogenesis of serous-type ovarian cancer tumors. Serous cancer is an epithelial ovarian cancer subtype and is the most common type of ovarian cancer. Transcriptomic profiles of serous cancer and non-cancerous datasets were obtained from the Gene Expression Omnibus (GEO-NCBI). Differentially expressed genes were then derived from those profiles; the identified genes were consistently upregulated in three or more transcriptomic profiles. These genes were considered as the serous ovarian cancer gene set for further study. The serous gene set derived from the transcriptomic profiles was then evaluated for ontological functional analysis using the Molecular Signatures Database. Next, we examined the mutational impact of this serous gene set on the transcriptomic profile of high-grade serous ovarian (HGSO) adenocarcinoma using the cBioPortal database. Results from OncoPrint revealed that 26 genes were amplified in more than 5% of HGSO cancer patients. Interestingly, several of these genes are involved in cell cycle processes, including genes ATPase family AAA domain containing 2 (ATAD2), recQ-like helicase 4 (RECQL4), cyclin E1 (CCNE1), anti-silencing function 1B histone chaperone (ASF1B), ribonuclease H2 subunit A (RNASEH2A), structural maintenance of chromosome 4 (SMC4), cell division cycle associated 20 (CDC20), and cell division cycle associated 8 (CDCA8). The receiver operating characteristic (ROC) curve results also revealed higher specificity and sensitivity for this subtype of tumors. Furthermore, these genes may affect the recurrence of serous ovarian carcinogenesis. Overall, our analytical study identifies cell cycle-related genes that can potentially be targeted as diagnostic and prognostic markers for serous ovarian cancer.

Amplification of Hippo Signaling Pathway Genes Is Governed and Implicated in the Serous Subtype-Specific Ovarian Carcino-Genesis

Among women, ovarian cancer ranks as the fifth most common cause of cancer-related deaths. This study examined the impact of Hippo signaling pathway on ovarian carcinogenesis. Therefore, the signatures related to Hippo signaling pathway were derived from the molecular signatures database (MSigDB) and were used for further analysis. The Z score-based pathway activation scoring method was employed to investigate the expression patterns of these signatures in the mRNA expression profiles of ovarian cancer cohorts. Compared to other subtype tumors, the results of this study show that the Hippo signaling pathway signatures are dysregulated prominently in serous subtype-specific ovarian carcinogenesis. A receiver operating characteristic (ROC) curve-based results of the Hippo gene set, yes-associated protein 1 (YAP1), and mammalian sterile 20-like kinases 1 (MST1) genes can predict the serous subtype tumors by higher specificity and sensitivity with significant areas under the curve values also further reconfirmed these signaling dysregulations. Moreover, these gene sets were studied further for mutation analysis in the profile of high-grade serous ovarian adenocarcinoma in the cBioPortal database. The OncoPrint results reveal that these Hippo signaling pathway genes are amplified highly during the grade three and stage third or fourth of serous type ovarian tumors. In addition, the results of the Dependency Map (DepMap) plot also clearly show that these genes are amplified significantly across the ovarian cancer cell lines. Finally, overall survival (OS) curve plot investigations also revealed that these gene expressions show poor survival patterns linked to highly expressed conditions in serous subtypes of ovarian cancer patients with significant p-values (p < 0.05). Thus, the current finding would help to develop the targeted therapies treatment for serous subtype ovarian carcinogenesis.

Root branching under high salinity requires auxin-independent modulation of LATERAL ORGAN BOUNDARY DOMAIN 16 function

Salinity stress constrains lateral root (LR) growth and severely affects plant growth. Auxin signaling regulates LR formation, but the molecular mechanism by which salinity affects root auxin signaling and whether salt induces other pathways that regulate LR development remains unknown. In Arabidopsis thaliana, the auxin-regulated transcription factor LATERAL ORGAN BOUNDARY DOMAIN 16 (LBD16) is an essential player in LR development under control conditions. Here, we show that under high-salt conditions, an alternative pathway regulates LBD16 expression. Salt represses auxin signaling but, in parallel, activates ZINC FINGER OF ARABIDOPSIS THALIANA 6 (ZAT6), a transcriptional activator of LBD16. ZAT6 activates LBD16 expression, thus contributing to downstream cell wall remodeling and promoting LR development under high-salt conditions. Our study thus shows that the integration of auxin-dependent repressive and salt-activated auxin-independent pathways converging on LBD16 modulates root branching under high-salt conditions.

ALKBH5 is a prognostic factor and promotes the angiogenesis of glioblastoma

Despite numerous reports indicating the significant impact of RNA modification on malignant glioblastoma (GBM) cell behaviors such as proliferation, invasion and therapy efficacy, its specific involvement in glioblastoma (GBM) angiogenesis is remains unclear and is currently under investigation. In this study, we aimed to investigate the relevance between RNA modification regulators and GBM angiogenesis. Our study employed bioinformatic analyses, including Gene Set Enrichment Analysis (GSEA), differential expression analysis, and Kaplan-Meier survival analysis, to identify regulators of angiogenesis-associated RNA modification (RM). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were applied to identify the enrichment of angiogenesis associated signatures in ALKBH5-high expression GBMs. We also utilized Western blot to verify the upregulation of ALKBH5 in clinical GBM samples. By a series of in vitro and in vivo assays, including plasmid transfection, wound healing, transwell invasion test, tube formation, RT-qPCR, ELISA assays and xenograft mice model, we validated the angiogenesis regulation ability of ALKBH5 in GBM. The N6-methyladenosine (m6A) modification "erase" ALKBH5 emerged as a candidate regulator associated with angiogenesis, demonstrating elevated expression and robust prognostic predictive ability in GBM patients. We also revealed enrichment of vasculature development biological process in GBMs with high ALKBH5 expression. Subsequently, we validated the elevated the expression of ALKBH5 in clinical GBM and paired adjacent tissues through western blot. Additionally, we knocked down the expression of ALKBH5 using sh-RNAs in U87 GBM cells to access the angiogenesis induction ability in U87 cells. In vitro experiments, Human Umbilical Vein Endothelial Cells (HUVECs) were used to perform wound healing, transwell migration and tube formation analysis, results indicated that ALKBH5 knock-down of U87 cells could decrease the pro-angiogenesis ability of U87 GBM cells. Further validation of our bioinformatic findings confirmed that ALKBH5 knockdown impaired VEGFA secretion in both in vitro and in vivo settings in U87 cells. These results comprehensively affirm the crucial role of ALKBH5 in regulating GBM-induced angiogenesis, both in vitro and in vivo. ALKBH5 not only emerges as a promising prognostic factor for GBM patients, but also plays a pivotal role in sustaining GBM progression by promoting angiogenesis.

Construction and evaluation of endometriosis diagnostic prediction model and immune infiltration based on efferocytosis-related genes

Background: Endometriosis (EM) is a long-lasting inflammatory disease that is difficult to treat and prevent. Existing research indicates the significance of immune infiltration in the progression of EM. Efferocytosis has an important immunomodulatory function. However, research on the identification and clinical significance of efferocytosis-related genes (EFRGs) in EM is sparse. Methods: The EFRDEGs (differentially expressed efferocytosis-related genes) linked to datasets associated with endometriosis were thoroughly examined utilizing the Gene Expression Omnibus (GEO) and GeneCards databases. The construction of the protein-protein interaction (PPI) and transcription factor (TF) regulatory network of EFRDEGs ensued. Subsequently, machine learning techniques including Univariate logistic regression, LASSO, and SVM classification were applied to filter and pinpoint diagnostic biomarkers. To establish and assess the diagnostic model, ROC analysis, multivariate regression analysis, nomogram, and calibration curve were employed. The CIBERSORT algorithm and single-cell RNA sequencing (scRNA-seq) were employed to explore immune cell infiltration, while the Comparative Toxicogenomics Database (CTD) was utilized for the identification of potential therapeutic drugs for endometriosis. Finally, immunohistochemistry (IHC) and reverse transcription quantitative polymerase chain reaction (RT-qPCR) were utilized to quantify the expression levels of biomarkers in clinical samples of endometriosis. Results: Our findings revealed 13 EFRDEGs associated with EM, and the LASSO and SVM regression model identified six hub genes (ARG2, GAS6, C3, PROS1, CLU, and FGL2). Among these, ARG2, GAS6, and C3 were confirmed as diagnostic biomarkers through multivariate logistic regression analysis. The ROC curve analysis of GSE37837 (AUC = 0.627) and GSE6374 (AUC = 0.635), along with calibration and DCA curve assessments, demonstrated that the nomogram built on these three biomarkers exhibited a commendable predictive capacity for the disease. Notably, the ratio of nine immune cell types exhibited significant differences between eutopic and ectopic endometrial samples, with scRNA-seq highlighting M0 Macrophages, Fibroblasts, and CD8 Tex cells as the cell populations undergoing the most substantial changes in the three biomarkers. Additionally, our study predicted seven potential medications for EM. Finally, the expression levels of the three biomarkers in clinical samples were validated through RT-qPCR and IHC, consistently aligning with the results obtained from the public database. Conclusion: we identified three biomarkers and constructed a diagnostic model for EM in this study, these findings provide valuable insights for subsequent mechanistic research and clinical applications in the field of endometriosis.

The Features of Shared Genes among Transcriptomes Probed in Atopic Dermatitis, Psoriasis, and Inflammatory Acne: S100A9 Selection as the Target Gene

BACKGROUND

Atopic dermatitis (AD), psoriasis (PS), and inflammatory acne (IA) are well-known as inflammatory skin diseases. Studies of the transcriptome with altered expression levels have reported a large number of dysregulated genes and gene clusters, particularly those involved in inflammatory skin diseases.

OBJECTIVE

To identify genes commonly shared in AD, PS, and IA that are potential therapeutic targets, we have identified consistently dysregulated genes and disease modules that overlap with AD, PS, and IA.

METHODS

Microarray data from AD, PS, and IA patients were downloaded from Gene Expression Omnibus (GEO), and identification of differentially expressed genes from microarrays of AD, PS, and IA was conducted. Subsequently, gene ontology and gene set enrichment analysis, detection of disease modules with known disease-associated genes, construction of the protein-protein interaction (PPI) network, and PPI sub-mapping analysis of shared genes were performed. Finally, the computational docking simulations between the selected target gene and inhibitors were conducted.

RESULTS

We identified 50 shared genes (36 up-regulated and 14 down-regulated) and disease modules for each disease. Among the shared genes, 20 common genes in PPI network were detected such as LCK, DLGAP5, SELL, CEP55, CDC20, RRM2, S100A7, S100A9, MCM10, AURKA, CCNB1, CHEK1, BTC, IL1F7, AGTR1, HABP4, SERPINB13, RPS6KA4, GZMB, and TRIP13. Finally, S100A9 was selected as the target gene for therapeutics. Docking simulations between S100A9 and known inhibitors indicated several key binding residues, and based on this result, we suggested several cannabinoids such as WIN-55212-2, JZL184, GP1a, Nabilone, Ajulemic acid, and JWH-122 could be potential candidates for a clinical study for AD, PS, and IA via inhibition of S100A9-related pathway.

CONCLUSION

Overall, our approach may become an effective strategy for discovering new disease candidate genes for inflammatory skin diseases with a reevaluation of clinical data.

The TiHoCL panel for canine lymphoma: a feasibility study integrating functional genomics and network biology approaches for comparative oncology targeted NGS panel design

Targeted next-generation sequencing (NGS) enables the identification of genomic variants in cancer patients with high sensitivity at relatively low costs, and has thus opened the era to personalized human oncology. Veterinary medicine tends to adopt new technologies at a slower pace compared to human medicine due to lower funding, nonetheless it embraces technological advancements over time. Hence, it is reasonable to assume that targeted NGS will be incorporated into routine veterinary practice in the foreseeable future. Many animal diseases have well-researched human counterparts and hence, insights gained from the latter might, in principle, be harnessed to elucidate the former. Here, we present the TiHoCL targeted NGS panel as a proof of concept, exemplifying how functional genomics and network approaches can be effectively used to leverage the wealth of information available for human diseases in the development of targeted sequencing panels for veterinary medicine. Specifically, the TiHoCL targeted NGS panel is a molecular tool for characterizing and stratifying canine lymphoma (CL) patients designed based on human non-Hodgkin lymphoma (NHL) research outputs. While various single nucleotide polymorphisms (SNPs) have been associated with high risk of developing NHL, poor prognosis and resistance to treatment in NHL patients, little is known about the genetics of CL. Thus, the ~100 SNPs featured in the TiHoCL targeted NGS panel were selected using functional genomics and network approaches following a literature and database search that shielded ~500 SNPs associated with, in nearly all cases, human hematologic malignancies. The TiHoCL targeted NGS panel underwent technical validation and preliminary functional assessment by sequencing DNA samples isolated from blood of 29 lymphoma dogs using an Ion Torrent™ PGM System achieving good sequencing run metrics. Our design framework holds new possibilities for the design of similar molecular tools applied to other diseases for which limited knowledge is available and will improve drug target discovery and patient care.

Identification of new potential downstream transcriptional targets of the strigolactone pathway including glucosinolate biosynthesis

Strigolactones regulate shoot branching and many aspects of plant growth, development, and allelopathy. Strigolactones are often discussed alongside auxin because they work together to inhibit shoot branching. However, the roles and mechanisms of strigolactones and how they act independently of auxin are still elusive. Additionally, there is still much in general to be discovered about the network of molecular regulators and their interactions in response to strigolactones. Here, we conducted an experiment in Arabidopsis with physiological treatments and strigolactone mutants to determine transcriptional pathways associated with strigolactones. The three physiological treatments included shoot tip removal with and without auxin treatment and treatment of intact plants with the auxin transport inhibitor, N-1-naphthylphthalamic acid (NPA). We identified the glucosinolate biosynthesis pathway as being upregulated across strigolactone mutants indicating strigolactone-glucosinolate crosstalk. Additionally, strigolactone application cannot restore the highly branched phenotype observed in glucosinolate biosynthesis mutants, placing glucosinolate biosynthesis downstream of strigolactone biosynthesis. Oxidative stress genes were enriched across the experiment suggesting that this process is mediated through multiple hormones. Here, we also provide evidence supporting non-auxin-mediated, negative feedback on strigolactone biosynthesis. Increases in strigolactone biosynthesis gene expression seen in strigolactone mutants could not be fully restored by auxin. By contrast, auxin could fully restore auxin-responsive gene expression increases, but not sugar signaling-related gene expression. Our data also point to alternative roles of the strigolactone biosynthesis genes and potential new signaling functions of strigolactone precursors. In this study, we identify a strigolactone-specific regulation of glucosinolate biosynthesis genes indicating that the two are linked and may work together in regulating stress and shoot ranching responses in Arabidopsis. Additionally, we provide evidence for non-auxinmediated feedback on strigolactone biosynthesis and discuss this in the context of sugar signaling.

Role of gene signature regulation in tumor immune microenvironment on the mechanism of uveal melanoma metastasis

BACKGROUND

Uveal melanoma (UM) is a rare but deadly cancer. The main cause of death from UM is liver metastasis. Though the metastasis mechanism remains unclear, it is closely related to the immune microenvironment and gene expression.

OBJECTIVE

This study aimed to identify the prognostic genes in primary and metastatic UM and their relationship with the immune microenvironment.

METHODS

Primary and metastatic UM data from the GEO database included GSE22138 and GSE44295 datasets. Kaplan-Meier analysis, Cox regression models, and ROC analysis were applied to screen genes in GSE22138. TIMER2.0 was employed to analyze the immune microenvironment from gene expression. Prognostic immune gene correlation was tested by Spearman. The results were validated in the independent dataset of cohort GSE44295.

RESULTS

Metastasis and primary differential gene analysis showed 107 significantly different genes associated with prognosis, and 11 of them were immune-related. ROC analysis demonstrated that our signature was predictive for UM prognosis (AUC > 0.8). Neutrophil and myeloid dendritic cells were closely associated with metastasis with scores that significantly divided patients into high-risk and low-risk groups (log-rank p< 0.05). Of these 11 genes, FABP5 and SHC4 were significantly associated with neutrophils in metastatic tumors, while ROBO1 expression was significantly correlated with myeloid dendritic cells in the primary tumors.

CONCLUSIONS

The present study constructed an 11-gene signature and established a model for risk stratification and prediction of overall survival in metastatic UM. Since FABP5 and SHC4 are related to neutrophil infiltration in metastatic UM, FABP5 and neutrophil regulation might be crucial in metastatic UM.

The miR-124-AMPAR pathway connects polygenic risks with behavioral changes shared between schizophrenia and bipolar disorder

Schizophrenia (SZ) and bipolar disorder (BP) are highly heritable major psychiatric disorders that share a substantial portion of genetic risk as well as their clinical manifestations. This raises a fundamental question of whether, and how, common neurobiological pathways translate their shared polygenic risks into shared clinical manifestations. This study shows the miR-124-3p-AMPAR pathway as a key common neurobiological mediator that connects polygenic risks with behavioral changes shared between these two psychotic disorders. We discovered the upregulation of miR-124-3p in neuronal cells and the postmortem prefrontal cortex from both SZ and BP patients. Intriguingly, the upregulation is associated with the polygenic risks shared between these two disorders. Seeking mechanistic dissection, we generated a mouse model that upregulates miR-124-3p in the medial prefrontal cortex. We demonstrated that the upregulation of miR-124-3p increases GRIA2-lacking calcium-permeable AMPARs and perturbs AMPAR-mediated excitatory synaptic transmission, leading to deficits in the behavioral dimensions shared between SZ and BP.

CD4+ T cells drive an inflammatory, TNF-α/IFN-rich tumor microenvironment responsive to chemotherapy

While chemotherapy remains the first-line treatment for many cancers, it is still unclear what distinguishes responders from non-responders. Here, we characterize the chemotherapy-responsive tumor microenvironment in mice, using RNA sequencing on tumors before and after cyclophosphamide, and compare the gene expression profiles of responders with progressors. Responsive tumors have an inflammatory and highly immune infiltrated pre-treatment tumor microenvironment characterized by the enrichment of pathways associated with CD4⁺ T cells, interferons (IFNs), and tumor necrosis factor alpha (TNF-α). The same gene expression profile is associated with response to cyclophosphamide-based chemotherapy in patients with breast cancer. Finally, we demonstrate that tumors can be sensitized to cyclophosphamide and 5-FU chemotherapy by pre-treatment with recombinant TNF-α, IFNγ, and poly(I:C). Thus, a CD4⁺ T cell-inflamed pre-treatment tumor microenvironment is necessary for response to chemotherapy, and this state can be therapeutically attained by targeted immunotherapy.

Expression of miRNA-Targeted and Not-Targeted Reporter Genes Shows Mutual Influence and Intercellular Specificity

The regulation of translation by RNA-induced silencing complexes (RISCs) composed of Argonaute proteins and micro-RNAs is well established; however, the mechanisms underlying specific cellular responses to miRNAs and how specific complexes arise are not completely clear. To explore these questions, we performed experiments with Renilla and firefly luciferase reporter genes transfected in a psiCHECK-2 plasmid into human HCT116 or Me45 cells, where only the Renilla gene contained sequences targeted by microRNAs (miRNAs) in the 3'UTR. The effects of targeting were miRNA-specific; miRNA-21-5p caused strong inhibition of translation, whereas miRNA-24-3p or Let-7 family caused no change or an increase in reporter Renilla luciferase synthesis. The mRNA-protein complexes formed by transcripts regulated by different miRNAs differed from each other and were different in different cell types, as shown by sucrose gradient centrifugation. Unexpectedly, the presence of miRNA targets on Renilla transcripts also affected the expression of the co-transfected but non-targeted firefly luciferase gene in both cell types. Renilla and firefly transcripts were found in the same sucrose gradient fractions and specific anti-miRNA oligoribonucleotides, which influenced the expression of the Renilla gene, and also influenced that of firefly gene. These results suggest that, in addition to targeted transcripts, miRNAs may also modulate the expression of non-targeted transcripts, and using the latter to normalize the results may cause bias. We discuss some hypothetical mechanisms which could explain the observed miRNA-induced effects.

Retinoic acid-induced 1 gene haploinsufficiency alters lipid metabolism and causes autophagy defects in Smith-Magenis syndrome

Smith-Magenis syndrome (SMS) is a neurodevelopmental disorder characterized by cognitive and behavioral symptoms, obesity, and sleep disturbance, and no therapy has been developed to alleviate its symptoms or delay disease onset. SMS occurs due to haploinsufficiency of the retinoic acid-induced-1 (RAI1) gene caused by either chromosomal deletion (SMS-del) or RAI1 missense/nonsense mutation. The molecular mechanisms underlying SMS are unknown. Here, we generated and characterized primary cells derived from four SMS patients (two with SMS-del and two carrying RAI1 point mutations) and four control subjects to investigate the pathogenetic processes underlying SMS. By combining transcriptomic and lipidomic analyses, we found altered expression of lipid and lysosomal genes, deregulation of lipid metabolism, accumulation of lipid droplets, and blocked autophagic flux. We also found that SMS cells exhibited increased cell death associated with the mitochondrial pathology and the production of reactive oxygen species. Treatment with N-acetylcysteine reduced cell death and lipid accumulation, which suggests a causative link between metabolic dyshomeostasis and cell viability. Our results highlight the pathological processes in human SMS cells involving lipid metabolism, autophagy defects and mitochondrial dysfunction and suggest new potential therapeutic targets for patient treatment.

Hepatocellular carcinoma stage: an almost loss of fatty acid metabolism and gain of glucose metabolic pathways dysregulation

Cancer cells rewire the metabolic processes beneficial for cancer cell proliferation, survival, and their progression. In this study, metabolic processes related to glucose, glutamine, and fatty acid metabolism signatures were collected from the molecular signatures database and investigated in the context of energy metabolic pathways through available genome-wide expression profiles of liver cancer cohorts by gene sets-based pathway activation scoring analysis. The outcomes of this study portray that the fatty acid metabolism, transport, and its storage related signatures are highly expressed across early stages of liver tumors and on the contrary, the gene sets related to glucose transport and glucose metabolism are prominently activated in the hepatocellular carcinoma (HCC) stage. Based on the results, these metabolic pathways are clearly dysregulated across specific stages of carcinogenesis. The identified dimorphic metabolic pathway dysregulation patterns are further reconfirmed by examining corresponding metabolic pathway genes expression patterns across various stages encompassing profiles. Recurrence is the primary concern in the carcinogenesis of liver tumors due to liver tissues regeneration. Hence, to further explore these dysregulation effects on recurrent cirrhosis and recurrent HCC sample containing profile GSE20140 was examined and interestingly, this result also reiterated these differential metabolic pathways dysregulation. In addition, a recently established metabolome profile for the massive panel of cancer cell-lines, including liver cancer cell-lines, was used for further exploration. These findings also reassured those differential metabolites abundance of the fatty acid and glucose metabolic pathways enlighten those dimorphic metabolic pathways dysregulation. Moreover, ROC curves of fatty acid metabolic pathway genes such as acetyl-CoA carboxylase (ACACB), acyl-CoA dehydrogenase long chain (ACADL), and acyl-CoA dehydrogenase medium chain (ACADM) as well as glucose metabolic pathway genes such as phosphoglycerate kinase (PGK1), pyruvate dehydrogenase (PDHA1), pyruvate dehydrogenase kinase (PDK1) demonstrated greater sensitivity and specificity in the corresponding stage-specific tumors with significant p-values (p < 0.05). Furthermore, overall survival (OS) and recurrence-free survival (RFS) studies also reconfirmed that the rate-limiting genes expression of fatty acid and glucose metabolic pathways reveal better and poor survival in HCC patient cohorts, respectively. In conclusion, all these results clearly show that metabolic rewiring and the existence of two diverse metabolic pathways dysregulation involving fatty acid and glucose metabolism across the stages of liver tumors have been identified. These findings might be useful for developing therapeutic target treatments in stage-specific tumors.

Intrinsic immune evasion patterns predict temozolomide sensitivity and immunotherapy response in lower-grade gliomas

BACKGROUND

Although intrinsic immune-evasion is important in cancer proliferation, metastasis and response to treatment, it is unclear whether intrinsic immune-evasion patterns of gliomas can aid in predicting clinical prognosis and determining treatment.

METHODS

A total of 182 immune-evasion genes intrinsic to cancer were subjected to consensus clustering to identify immune-evasion patterns in 1421 patients with lower-grade glioma (LGG). The levels of each cancer hallmark were determined by the Gene Set Variant Analysis (GSVA) method, and immune cell infiltrations were quantified using two algorithms, the single-sample Gene Set Enrichment Analysis (ssGSEA) and the Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) methods. IEVscore was determined by a method that combined univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO) regression and principal component analysis (PCA).

RESULTS

Transcriptional and genomic analysis showed that most immune evasion genes (IEVGs) were upregulated in LGGs, with aberrant expression driven by alterations in copy number variants (CNV). Based on the mRNA expression profiles of cancer-intrinsic IEVGs could be divided into three LGG subgroups with distinct prognosis, clinicopathological features and immune infiltrations. A combined scoring scheme designed to assess the immune-evasion levels of LGGs divided these 1421 patients into two subgroups that differed in IEVscores. LGG patients with low-IEVscore had a better prognosis, would be more likely to benefit from immune check-point inhibitors and would be more susceptible to temozolomide (TMZ) chemotherapy.

CONCLUSION

Intrinsic immune evasion in the tumor microenvironment (TME) has a crucial effect on glioma formation. Quantitatively assessing the IEV scores of individual LGG patients could enhance knowledge about the intra-glioma microenvironment and lead to the development of individualized therapeutic strategies for patients with LGG.

Integrated bioinformatics analysis uncovers characteristic genes and molecular subtyping system for endometriosis

Objective: Endometriosis is a chronic inflammatory estrogen-dependent disease with the growth of endometrial tissues outside the uterine cavity. Nevertheless, the etiology of endometriosis is still unclear. Integrated bioinformatics analysis was implemented to reveal the molecular mechanisms underlying this disease.

Methods: A total of four gene expression datasets (GSE7305, GSE11691, GSE23339, and GSE25628) were retrieved from the GEO, which were merged into a meta-dataset, followed by the removal of batch effects via the sva package. Weighted gene co-expression network analysis (WGCNA) was implemented, and endometriosis-related genes were screened under normal and endometriosis conditions. Thereafter, characteristic genes were determined via Lasso analysis. The diagnostic performance was estimated via receiver operating characteristic curves, and epigenetic and post-transcriptional modifications were analyzed. Small molecular compounds were predicted. Unsupervised clustering analysis was conducted via non-negative matrix factorization algorithm. The enriched pathways were analyzed via gene set enrichment analysis or GSVA. Immune features were evaluated according to immune-checkpoints, HLA, receptors, chemokines, and immune cells.

Results: In total, four characteristic genes (BGN, AQP1, ELMO1, and DDR2) were determined for endometriosis, all of which exhibited the favorable efficacy in diagnosing endometriosis. Their aberrant levels were modulated by epigenetic and post-transcriptional modifications. In total, 51 potential drugs were predicted against endometriosis. The characteristic genes exhibited remarkable associations with immunological function. Three subtypes were classified across endometriosis, with different mechanisms and immune features.

Conclusion: Our study reveals the characteristic genes and novel molecular subtyping of endometriosis, contributing to the early diagnosis and intervention in endometriosis.

Malic Enzyme 1 Absence in Synovial Sarcoma Shifts Antioxidant System Dependence and Increases Sensitivity to Ferroptosis Induction with ACXT-3102

PURPOSE

To investigate the metabolism of synovial sarcoma (SS) and elucidate the effect of malic enzyme 1 absence on SS redox homeostasis.

EXPERIMENTAL DESIGN

ME1 expression was measured in SS clinical samples, SS cell lines, and tumors from an SS mouse model. The effect of ME1 absence on glucose metabolism was evaluated utilizing Seahorse assays, metabolomics, and C13 tracings. The impact of ME1 absence on SS redox homeostasis was evaluated by metabolomics, cell death assays with inhibitors of antioxidant systems, and measurements of intracellular reactive oxygen species (ROS). The susceptibility of ME1-null SS to ferroptosis induction was interrogated in vitro and in vivo.

RESULTS

ME1 absence in SS was confirmed in clinical samples, SS cell lines, and an SS tumor model. Investigation of SS glucose metabolism revealed that ME1-null cells exhibit higher rates of glycolysis and higher flux of glucose into the pentose phosphate pathway (PPP), which is necessary to produce NADPH. Evaluation of cellular redox homeostasis demonstrated that ME1 absence shifts dependence from the glutathione system to the thioredoxin system. Concomitantly, ME1 absence drives the accumulation of ROS and labile iron. ROS and iron accumulation enhances the susceptibility of ME1-null cells to ferroptosis induction with inhibitors of xCT (erastin and ACXT-3102). In vivo xenograft models of ME1-null SS demonstrate significantly increased tumor response to ACXT-3102 compared with ME1-expressing controls.

CONCLUSIONS

These findings demonstrate the translational potential of targeting redox homeostasis in ME1-null cancers and establish the preclinical rationale for a phase I trial of ACXT-3102 in SS patients. See related commentary by Subbiah and Gan, p. 3408.

Construction and validation of a glioblastoma prognostic model based on immune-related genes

Background

Glioblastoma multiforme (GBM) is a common malignant brain tumor with high mortality. It is urgently necessary to develop a new treatment because traditional approaches have plateaued.

Purpose

Here, we identified an immune-related gene (IRG)-based prognostic signature to comprehensively define the prognosis of GBM.

Methods

Glioblastoma samples were selected from the Chinese Glioma Genome Atlas (CGGA). We retrieved IRGs from the ImmPort data resource. Univariate Cox regression and LASSO Cox regression analyses were used to develop our predictive model. In addition, we constructed a predictive nomogram integrating the independent predictive factors to determine the one-, two-, and 3-year overall survival (OS) probabilities of individuals with GBM. Additionally, the molecular and immune characteristics and benefits of ICI therapy were analyzed in subgroups defined based on our prognostic model. Finally, the proteins encoded by the selected genes were identified with liquid chromatography-tandem mass spectrometry and western blotting (WB).

Results

Six IRGs were used to construct the predictive model. The GBM patients were categorized into a high-risk group and a low-risk group. High-risk group patients had worse survival than low-risk group patients, and stronger positive associations with multiple tumor-related pathways, such as angiogenesis and hypoxia pathways, were found in the high-risk group. The high-risk group also had a low IDH1 mutation rate, high PTEN mutation rate, low 1p19q co-deletion rate and low MGMT promoter methylation rate. In addition, patients in the high-risk group showed increased immune cell infiltration, more aggressive immune activity, higher expression of immune checkpoint genes, and less benefit from immunotherapy than those in the low-risk group. Finally, the expression levels of TNC and SSTR2 were confirmed to be significantly associated with patient prognosis by protein mass spectrometry and WB.

Conclusion

Herein, a robust predictive model based on IRGs was developed to predict the OS of GBM patients and to aid future clinical research.

Cytokine Activation Reveals Tissue-Imprinted Gene Profiles of Mesenchymal Stromal Cells

Development of standardized metrics to support manufacturing and regulatory approval of mesenchymal stromal cell (MSC) products is confounded by heterogeneity of MSC populations. Many reports describe fundamental differences between MSCs from various tissues and compare unstimulated and activated counterparts. However, molecular information comparing biological profiles of activated MSCs across different origins and donors is limited. To better understand common and source-specific mechanisms of action, we compared the responses of 3 donor populations each of human umbilical cord (UC) and bone marrow (BM) MSCs to TNF-α, IL-1β or IFN-γ. Transcriptome profiles were analysed by microarray and select secretome profiles were assessed by multiplex immunoassay. Unstimulated (resting) UC and BM-MSCs differentially expressed (DE) 174 genes. Signatures of TNF-α-stimulated BM and UC-MSCs included 45 and 14 new DE genes, respectively, while all but 7 of the initial 174 DE genes were expressed at comparable levels after licensing. After IL-1β activation, only 5 of the 174 DE genes remained significantly different, while 6 new DE genes were identified. IFN-γ elicited a robust transcriptome response from both cell types, yet nearly all differences (171/174) between resting populations were attenuated. Nine DE genes predominantly corresponding to immunogenic cell surface proteins emerged as a BM-MSC signature of IFN-γ activation. Changes in protein synthesis of select analytes correlated modestly with transcript levels. The dynamic responses of licensed MSCs documented herein, which attenuated heterogeneity between unstimulated populations, provide new insight into common and source-imprinted responses to cytokine activation and can inform strategic development of meaningful, standardized assays.

An Immune-Related Gene Signature Can Predict Clinical Outcomes and Immunotherapeutic Response in Oral Squamous Cell Carcinoma

Objective: Immune landscape is a key feature that affects cancer progression, survival, and treatment response. Herein, this study sought to comprehensively characterize the immune-related genes (IRGs) in oral squamous cell carcinoma (OSCC) and conduct an immune-related risk score (IRS) model for prognosis and therapeutic response prediction.

Methods: Transcriptome profiles and follow-up data of OSCC cohorts were curated from TCGA, GSE41613, and IMvigor210 datasets. An IRS model was established through univariate Cox, Random Survival Forest, and multivariate Cox analyses. Prognostic significance was evaluated with Kaplan–Meier curves, ROC, uni- and multivariate Cox, and subgroup analyses. A nomogram was conducted and assessed with C-index, ROC, calibration curves, and decision curve analyses. Immune cell infiltration and immune response were estimated with ESTIMATE and ssGSEA methods.

Results: An IRS model was constructed for predicting the overall survival and disease-free survival of OSCC, containing MASP1, HBEGF, CCL22, CTSG, LBP, and PLAU. High-risk patients displayed undesirable prognosis, and the predictive efficacy of this model was more accurate than conventional clinicopathological indicators. Multivariate Cox analyses demonstrated that this model was an independent risk factor. The nomogram combining IRS, stage, and age possessed high clinical application values. The IRS was positively associated with a nonflamed tumor microenvironment. Moreover, this signature enabled to predict immunotherapeutic response and sensitivity to chemotherapeutic agents (methotrexate and paclitaxel).

Conclusion: Collectively, our study developed a robust IRS model with machine learning method to stratify OSCC patients into subgroups with distinct prognosis and benefits from immunotherapy, which might assist identify biomarkers and targets for immunotherapeutic schemes.

Identification of oncogenic signaling pathways associated with the dimorphic metabolic dysregulations in gastric cancer subtypes

Metabolic dysregulations have been identified as intrinsic hallmarks of cancer cells. Investigations of altered metabolic processes, in the context of the associated oncogenic signaling pathways are expected to pave way for the development of targeted cancer therapeutics. We have recently identified the enrichment of glucose and glutamine metabolism in a subset of intestinal subtype gastric tumors at the level of expression of genes, gene sets and the occurrence of metabolites. On the other hand, glucose transport, glucan and fatty acid metabolism were enriched in a subset of diffuse subtype gastric tumors. In the current study, along with glucose metabolism, mTOR, HSP90, MYC, E2F, P53 and proteasome pathways were found enriched in a subset of intestinal subtype and a part of MSI subtype gastric tumors. On the other hand, along with fatty acid metabolism, the oncogenic pathway KRAS was found to be enriched in a subset of GS tumors among diffuse subtype gastric tumors. Thus, oncogenic signaling pathways associated with two distinct metabolic rewiring which differentially occurs between major gastric cancer subtypes were identified. These pathways seem the potential targets to differentially target these gastric cancer subtypes. Exploratory integrative genomic analyses reveal HSP90 inhibitors, AKT/mTOR inhibitors, and cell cycle inhibitors as potential agents to target the gastric tumors with the rewired glucose metabolism and MEK/MAPK inhibitors as suitable drug candidates to target the diffuse subtype tumors with the dysregulated fatty acid metabolism. This observation would pave way for the selective and targeted use of signaling pathway modulators for targeted and stratified gastric cancer therapeutics.

exRNAdisease: An extracellular RNA transcriptome atlas in human diseases

Extracellular RNAs (exRNAs) are types of RNAs that present outside of the cells with highly stable features. exRNAs have been shown to play important roles in aiding intercellular communication and regulating cellular processes. In clinical settings, exRNAs have the potential to serve as biomarkers indicating the presence of a disease.Recently, the high-throughput technologies such as RNA sequencing (RNAseq) and microarray have generated abundant exRNA expression data about various diseases. Thus, it is highly desirable to have a comprehensive database for disease-related exRNA transcriptome data detected in diverse body fluids. Here, a total of 88 previously published exRNA transcriptome datasets were collected. We developed a web-accessible database, exRNADisease, which is designed as a central repository for exRNAs from body fluids in human diseases and healthy controls. In the current version, a total of 18,265 samples were collected, which includes 10 body fluids and 78 human disease types. Six different types of RNAs were included (messenger RNAs, circular RNAs, long noncoding RNAs, microRNAs, transfer RNA fragments and PIWI-interacting RNA). Literature is also included to provide the robust evidence about the relationship between exRNAs and diseases. A user-friendly interface was constructed to conveniently search and browse disease-related exRNAs. exRNADisease will become a useful platform to provide genome-wide view of exRNA deregulation in human diseases and help to identify novel biomarkers. Availability and implementation: exRNAdisease can be freely accessible at http://www.origin-gene.cn/database/exRNAdisease/.

Transcriptional Patterns of Lower-Grade Glioma Patients with Distinct Ferroptosis Levels, Immunotherapy Response, and Temozolomide Sensitivity

Background

Many studies have defined a critical role for ferroptosis in cancer progression and therapy, but it is unclear how ferroptosis regulates tumor immunity or tumor microenvironment (TME).

Methods

In this study, 24 ferroptosis-regulators were assessed by nonnegative matrix factorization (NMF) consensus clustering to identify ferroptosis patterns in lower-grade gliomas (LGGs). Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) method and single sample gene set enrichment analysis (ssGSEA) were used to quantify immune cell infiltrations. The PCA algorithm was used to develop the ferroptosis-related score (FRscore) to measure ferroptosis levels.

Results

Two LGG subgroups named ferroptosis-related clusters 1 (FRC1) and 2 (FRC2), with distinct ferroptosis levels, immune infiltrations, and clinical outcomes were determined in 1,407 LGG samples. A well-designed scoring system was developed to evaluate the ferroptosis levels in LGG patients based on the FRSig gene profile and divided patients into low- and high-FRscore subgroups. Patients with low FRscores had lower ferroptosis levels and prolonged survival time and were expected to benefit from immune checkpoint blockade (ICB) therapy and showed higher sensitivity to TMZ chemotherapy. Findings also showed that the PI3K-AKT-mTOR pathway is activated by ferroptosis induction in SW1088 cells.

Conclusions

This study highlights the critical role of ferroptosis in TME formation and shaping, and quantitatively assessing ferroptosis levels in individual tumors can help to define the intratumor microenvironment and formulate precise treatment strategies for LGG patients.

Molecular Characteristics, Oncogenic Roles, and Relevant Immune and Pharmacogenomic Features of EVA1B in Colorectal Cancer

OBJECTIVE

EVA1B, a protein coding gene, is a critical paralog of EVA1A gene. Herein, our study was conducted to investigate the role of EVA1B in colorectal cancer (CRC) progression and prognosis.

METHODS

Pan-cancer analysis was conducted to analyze expression, genetic and epigenetic alterations, and immunological characteristics of EVA1B. Especially, immunological characteristics and mutational landscape were compared between high and low EVA1B expression groups in the combined TCGA-COAD and TCGA-READ datasets. Through random survival forest analysis, an EVA1B-derived genomic model was developed, and its prognostic value was verified in the external datasets (GSE14333, GSE39582, and GSE87211). Drug sensitivity was compared between high- and low-risk subpopulations. A nomogram was conducted through integrating independent factors.

RESULTS

EVA1B expression presented a remarkable upregulation in most cancer types, especially CRC. EVA1B expression was significantly correlated to DNA methyltransferases, DNA mismatch repair genes, m⁶A regulators, TMB, and MSI across pan-cancer. High EVA1B expression indicated an undesirable CRC patients' prognosis. Additionally, its upregulation was correlated to enhanced immune cell infiltration, increased stromal and immune activation, and elevated activities of cancer immunity cycle. Higher frequencies of amplification and deletion were investigated in high EVA1B expression subpopulation. Following verification, the EVA1B-derived genomic model reliably predicted patients' prognosis and drug responses. The nomogram (age, stage, EVA1B-derived risk score) was conducted to quantify an individual's survival probability. Furthermore, our experimental validation based on immunohistochemistry indicated that EVA1B overexpression is correlated with CRC tumorigenesis and poor outcomes in our CRC patients' cohort.

CONCLUSION

Collectively, our findings provided valuable resource for guiding the mechanisms and therapeutic analysis of EVA1B in CRC.

Suppression of MYC by PI3K/AKT/mTOR pathway inhibition in combination with all-trans retinoic acid treatment for therapeutic gain in acute myeloid leukaemia

Aberrant activity of the phosphatidylinositol-3 kinase/protein kinase B/mammalian target of rapamycin (PI3K/AKT/mTOR [PAM]) pathway, as well as suppressed retinoic acid signalling, contribute to enhanced proliferation and the differentiation blockade of immature myeloid cells in acute myeloid leukaemia (AML). Inhibition of the PAM pathway was shown to affect especially mixed-lineage leukaemia-rearranged AML. Here, we sought to test a combined strategy using small molecule inhibitors against members of the PAM signalling pathway in conjunction with all-trans retinoic acid (ATRA) to target a larger group of different AML subtypes. We find that ATRA treatment in combination with inhibition of PI3K (ZSTK474), mTOR (WYE132) or PI3K/mTOR (BEZ235, dactolisib) drastically reduces protein levels of the proto-oncogene MYC. In combination with BEZ235, ATRA treatment led to almost complete eradication of cellular MYC, G1 arrest, loss of clonal capacity and terminal granulocytic differentiation. We demonstrate that PAM inhibitor/ATRA treatment targets MYC via independent mechanisms. While inhibition of the PAM pathway causes MYC phosphorylation at threonine 58 via glycogen synthase kinase 3 beta and subsequent degradation, ATRA reduces its expression. Here, we present an approach using a combination of known drugs to synergistically reduce aberrant MYC levels, thereby effectively blocking proliferation and enabling differentiation in various AML subtypes.

Measurement of activity of developmental signal transduction pathways to quantify stem cell pluripotency and phenotypically characterize differentiated cells

Important challenges in stem cell research and regenerative medicine are reliable assessment of pluripotency state and purity of differentiated cell populations. Pluripotency and differentiation are regulated and determined by activity of developmental signal transduction pathways (STPs). To date activity of these STPs could not be directly measured on a cell sample. Here we validate a novel assay platform for measurement of activity of developmental STPs (STP) for use in stem cells and stem cell derivatives. In addition to previously developed STP assays, we report development of an additional STP assay for the MAPK-AP1 pathway. Subsequently, activity of Notch, Hedgehog, TGFβ, Wnt, PI3K, MAPK-AP1, and NFκB signaling pathways was calculated from Affymetrix transcriptome data of human pluripotent embryonic (hES) and iPS cell lines under different culture conditions, organ-derived multipotent stem cells, and differentiated cell types, to generate quantitative STP activity profiles. Results show that the STP assay technology enables reliable and quantitative measurement of multiple STP activities simultaneously on any individual cell sample. Using the technology, we found that culture conditions dominantly influence the pluripotent stem cell STP activity profile, while the origin of the stem cell line was a minor variable. A pluripotency STP activity profile (Pluripotency qPAP) was defined (active PI3K, MAPK, Hedgehog, Notch, TGFβ, and NFκB pathway, inactive Wnt pathway). Differentiation of hES cells to intestinal progenitor cells resulted in an STP activity profile characterized by active PI3K, Wnt and Notch pathways, comparable to the STP activity profile measured on primary intestinal crypt stem cells. Quantitative STP activity measurement is expected to improve experimental reproducibility and standardization of pluripotent and multipotent stem cell culture/differentiation, and enable controlled manipulation of pluripotency/differentiation state using pathway targeting compounds.

Unique Transcriptomic Changes Underlie Hormonal Interactions During Mammary Histomorphogenesis in Female Pigs

Successful lactation and the risk for developing breast cancer depend on growth and differentiation of the mammary gland (MG) epithelium that is regulated by ovarian steroids (17β-estradiol [E] and progesterone [P]) and pituitary-derived prolactin (PRL). Given that the MG of pigs share histomorphogenic features present in the normal human breast, we sought to define the transcriptional responses within the MG of pigs following exposure to all combinations of these hormones. Hormone-ablated female pigs were administered combinations of E, medroxyprogesterone 17-acetate (source of P), and either haloperidol (to induce PRL) or 2-bromo-α-ergocryptine. We subsequently monitored phenotypic changes in the MG including mitosis, receptors for E and P (ESR1 and PGR), level of phosphorylated STAT5 (pSTAT5), and the frequency of terminal ductal lobular unit (TDLU) subtypes; these changes were then associated with all transcriptomic changes. Estrogen altered the expression of approximately 20% of all genes that were mostly associated with mitosis, whereas PRL stimulated elements of fatty acid metabolism and an inflammatory response. Several outcomes, including increased pSTAT5, highlighted the ability of E to enhance PRL action. Regression of transcriptomic changes against several MG phenotypes revealed 1669 genes correlated with proliferation, among which 29 were E inducible. Additional gene expression signatures were associated with TDLU formation and the frequency of ESR1 or PGR. These data provide a link between the hormone-regulated genome and phenome of the MG in a species having a complex histoarchitecture like that in the human breast, and highlight an underexplored synergy between the actions of E and PRL during MG development.

Characterization of Immunoactive and Immunotolerant CD4+ T Cells in Breast Cancer by Measuring Activity of Signaling Pathways That Determine Immune Cell Function

Simple Summary

Immunotherapy enhances the immune response against cancer and is potentially curative. Unfortunately, few patients with breast cancer benefit from this therapy. It is not possible to predict which patients will benefit. A blood cell, called CD4+ T-cell, plays a role in the immune response and in resistance to immunotherapy. Its function is determined by activity of biochemical processes, called signal transduction pathways (STPs). We developed a new technology to measure activity of these STPs, which was used to investigate whether CD4+ T cells function abnormally in breast cancer patients. We show that in CD4+ T-cells from most of the investigated breast cancer patients a number of these STPs are overactive. The abnormal activity of a few notable STPs (Notch and TGFβ) suggests that CD4+ T-cells have changed into regulatory T-cells, which inhibit the immune response against cancer and have been associated with resistance to immunotherapy. We also provide evidence that this change in the CD4+ T- cells is caused by a factor produced by breast cancer cells. We conclude that this new technology can be used to measure STP activity in blood of patients with cancer and has the potential to better identify patients who will benefit from immunotherapy.

Abstract

Cancer immunotolerance may be reversed by checkpoint inhibitor immunotherapy; however, only a subset of patients responds to immunotherapy. The prediction of clinical response in the individual patient remains a challenge. CD4+ T cells play a role in activating adaptive immune responses against cancer, while the conversion to immunosuppression is mainly caused by CD4+ regulatory T cell (Treg) cells. Signal transduction pathways (STPs) control the main functions of immune cells. A novel previously described assay technology enables the quantitative measurement of activity of multiple STPs in individual cell and tissue samples. The activities of the TGFβ, NFκB, PI3K-FOXO, JAK-STAT1/2, JAK-STAT3, and Notch STPs were measured in CD4+ T cell subsets and used to investigate cellular mechanisms underlying breast cancer-induced immunotolerance. Methods: STP activity scores were measured on Affymetrix expression microarray data of the following: (1) resting and immune-activated CD4+ T cells; (2) CD4+ T-helper 1 (Th1) and T-helper 2 (Th2) cells; (3) CD4+ Treg cells; (4) immune-activated CD4+ T cells incubated with breast cancer tissue supernatants; and (5) CD4+ T cells from blood, lymph nodes, and cancer tissue of 10 primary breast cancer patients. Results: CD4+ T cell activation induced PI3K, NFκB, JAK-STAT1/2, and JAK-STAT3 STP activities. Th1, Th2, and Treg cells each showed a typical pathway activity profile. The incubation of activated CD4+ T cells with cancer supernatants reduced the PI3K, NFκB, and JAK-STAT3 pathway activities and increased the TGFβ pathway activity, characteristic of an immunotolerant state. Immunosuppressive Treg cells were characterized by high NFκB, JAK-STAT3, TGFβ, and Notch pathway activity scores. An immunotolerant pathway activity profile was identified in CD4+ T cells from tumor infiltrate and blood of a subset of primary breast cancer patients, which was most similar to the pathway activity profile in immunosuppressive Treg cells. Conclusion: Signaling pathway assays can be used to quantitatively measure the functional immune response state of lymphocyte subsets in vitro and in vivo. Clinical results suggest that, in primary breast cancer, the adaptive immune response of CD4+ T cells may be frequently replaced by immunosuppressive Treg cells, potentially causing resistance to checkpoint inhibition. In vitro study results suggest that this is mediated by soluble factors from cancer tissue. Signaling pathway activity analysis on TIL and/or blood samples may improve response prediction and monitoring response to checkpoint inhibitors and may provide new therapeutic targets (e.g., the Notch pathway) to reduce resistance to immunotherapy.

Involvement of miRNAs in cellular responses to radiation

PURPOSE

Exposure of living cells to ionizing radiation has different consequences, depending on the dose and cell type. Changes of gene expression at the level of transcription and translation, including those regulated by microRNAs (miRNAs), play a role in intrinsic radiosensitivity of different cells and define their fate, survival or death. The aim of our work was to examine how ionizing radiation may influence the expression of genes regulated by different miRNAs and miRNA biogenesis.

MATERIALS AND METHODS

The work was performed on cultured human melanoma Me45 cells, transiently transfected with plasmids containing Renilla luciferase reporter gene targeted by miRNAs Let-7, miR-21 or miR-24. The levels of reporter mRNAs and mRNAs coding for proteins participating in miRNA biogenesis were assayed at different time points in irradiated and non-irradiated cells using RT-qPCR, and reporter protein by luciferase activity assays. MiRNA-targeted motifs in mRNAs coding for proteins engaged in miRNA biogenesis were extracted from the miRTarBase database.

RESULTS

Messenger RNA and protein levels of transfected luciferase genes fluctuated in time in patterns which depended on the type of miRNA regulation and changed upon irradiation of the cells. The average levels of reporter mRNAs were higher in irradiated cells, whereas the levels of proteins changed in either direction. Radiation also influenced the levels of miRNAs and the expression of genes engaged in their biogenesis suggesting that the changes in gene expression following ionizing radiation result mainly from these changes in expression of genes regulating miRNA biogenesis and the influence of miRNA on mRNA translation.

CONCLUSIONS

Currently, the responses of cells to ionizing radiation are mainly ascribed to changes of their redox conditions and increased intracellular levels of ROS, but the experiments described here suggest that a further important factor is modulation of translation through changes in biogenesis and levels of miRNAs.

The Vulnerability of the Developing Brain: Analysis of Highly Expressed Genes in Infant C57BL/6 Mouse Hippocampus in Relation to Phenotypic Annotation Derived From Mutational Studies

The hippocampus has been shown to have a major role in learning and memory, but also to participate in the regulation of emotions. However, its specific role(s) in memory is still unclear. Hippocampal damage or dysfunction mainly results in memory issues, especially in the declarative memory but, in animal studies, has also shown to lead to hyperactivity and difficulty in inhibiting responses previously taught. The brain structure is affected in neuropathological disorders, such as Alzheimer's, epilepsy, and schizophrenia, and also by depression and stress. The hippocampus structure is far from mature at birth and undergoes substantial development throughout infant and juvenile life. The aim of this study was to survey genes highly expressed throughout the postnatal period in mouse hippocampus and which have also been linked to an abnormal phenotype through mutational studies to achieve a greater understanding about hippocampal functions during postnatal development. Publicly available gene expression data from C57BL/6 mouse hippocampus was analyzed; from a total of 5 time points (at postnatal day 1, 10, 15, 21, and 30), 547 genes highly expressed in all of these time points were selected for analysis. Highly expressed genes are considered to be of potential biological importance and appear to be multifunctional, and hence any dysfunction in such a gene will most likely have a large impact on the development of abilities during the postnatal and juvenile period. Phenotypic annotation data downloaded from Mouse Genomic Informatics database were analyzed for these genes, and the results showed that many of them are important for proper embryo development and infant survival, proper growth, and increase in body size, as well as for voluntary movement functions, motor coordination, and balance. The results also indicated an association with seizures that have primarily been characterized by uncontrolled motor activity and the development of proper grooming abilities. The complete list of genes and their phenotypic annotation data have been compiled in a file for easy access.

Combined Identification of Novel Markers for Diagnosis and Prognostic of Classic Hodgkin Lymphoma

BACKGROUND

An effective diagnostic and prognostic marker based on the gene expression profile of classic Hodgkin lymphoma (cHL) has not yet been developed. The aim of the present study was to investigate potential markers for the diagnosis and prediction of cHL prognosis.

METHODS

The gene expression profiles with all available clinical features were downloaded from the Gene Expression Omnibus (GEO) database. Then, multiple machine learning algorithms were applied to develop and validate a diagnostic signature by comparing cHL with normal control. In addition, we identified prognostic genes and built a prognostic model with them to predict the prognosis for 130 patients with cHL which were treated with first-line treatment (ABVD chemotherapy or an ABVD-like regimen).

RESULTS

A diagnostic prediction signature was constructed and showed high specificity and sensitivity (training cohort: AUC=0.981,95% CI 0.933-0.998, P<0.001, validation cohort: AUC=0.955,95% CI 0.895-0.986, P<0.001). Additionally, nine prognostic genes (LAMP1, STAT1, MMP9, C1QB, ICAM1, CD274, CCL19, HCK and LILRB2) were screened and a prognostic prediction model was constructed with them, which had been confirmed effectively predicting prognosis (P<0.001). Furthermore, the results of the immune infiltration assessment indicated that the high scale of the fraction of CD8 + T cells, M1 macrophages, resting mast cells associated with an adverse outcome in cHL, and naive B cells related to prolonged survival. In addition, a nomogram that combined the prognostic prediction model and clinical characteristics is also suggested to have a good predictive value for the prognosis of patients.

CONCLUSION

The new markers found in this study may be helpful for the diagnosis and prediction of the prognosis of cHL.

BDdb: a comprehensive platform for exploration and utilization of birth defect multi-omics data

Background

Birth defects pose a major challenge to infant health. Thus far, however, the causes of most birth defects remain cryptic. Over the past few decades, considerable effort has been expended on disclosing the underlying mechanisms related to birth defects, yielding myriad treatises and data. To meet the increasing requirements for data resources, we developed a freely accessible birth defect multi-omics database (BDdb, http://t21omics.cngb.org) consisting of multi-omics data and potential disease biomarkers.

Results

In total, omics datasets from 136 Gene Expression Omnibus (GEO) Series records, including 5245 samples, as well as 869 biomarkers of 22 birth defects in six different species, were integrated into the BDdb. The database provides a user-friendly interface for searching, browsing, and downloading data of interest. The BDdb also enables users to explore the correlations among different sequencing methods, such as chromatin immunoprecipitation sequencing (ChIP-Seq) and RNA sequencing (RNA-Seq) from different studies, to obtain the information on gene expression patterns from diverse aspects.

Conclusion

To the best of our knowledge, the BDdb is the first comprehensive database associated with birth defects, which should benefit the diagnosis and prevention of birth defects.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-021-01110-x.

Prognostic Nomogram Based on Circular RNA-Associated Competing Endogenous RNA Network for Patients with Lung Adenocarcinoma

Evidence is increasingly indicating that circular RNAs (circRNAs) are closely involved in tumorigenesis and cancer progression. However, the function and application of circRNAs in lung adenocarcinoma (LUAD) are still unknown. In this study, we constructed a circRNA-associated competitive endogenous RNA (ceRNA) network to investigate the regulatory mechanism of LUAD procession and further constructed a prognostic signature to predict overall survival for LUAD patients. Differentially expressed circRNAs (DEcircRNAs), differentially expressed miRNAs (DEmiRNAs), and differentially expressed mRNAs (DEmRNAs) were selected to construct the ceRNA network. Based on the TargetScan prediction tool and Pearson correlation coefficient, we constructed a circRNA-associated ceRNA network including 11 DEcircRNAs, 8 DEmiRNAs, and 49 DEmRNAs. GO and KEGG enrichment indicated that the ceRNA network might be involved in the regulation of GTPase activity and endothelial cell differentiation. After removing the discrete points, a PPI network containing 12 DEmRNAs was constructed. Univariate Cox regression analysis showed that three DEmRNAs were significantly associated with overall survival. Therefore, we constructed a three-gene prognostic signature for LUAD patients using the LASSO method in the TCGA-LUAD training cohort. By applying the signature, patients could be categorized into the high-risk or low-risk subgroups with significant survival differences (HR: 1.62, 95% CI: 1.12-2.35, log-rank p = 0.009). The prognostic performance was confirmed in an independent GEO cohort (GSE42127, HR: 2.59, 95% CI: 1.32-5.10, log-rank p = 0.004). Multivariate Cox regression analysis proved that the three-gene signature was an independent prognostic factor. Combining the three-gene signature with clinical characters, a nomogram was constructed. The primary and external verification C-indexes were 0.717 and 0.716, respectively. The calibration curves for the probability of 3- and 5-year OS showed significant agreement between nomogram predictions and actual observations. Our findings provided a deeper understanding of the circRNA-associated ceRNA regulatory mechanism in LUAD pathogenesis and further constructed a useful prognostic signature to guide personalized treatment of LUAD patients.

Screening and identification of NOTCH1, CDKN2A, and NOS3 as differentially expressed autophagy-related genes in erectile dysfunction

Background

Loss of function of key autophagy genes are associated with a variety of diseases. However specific role of autophagy-related genes in erectile dysfunction ED remains unclear. This study explores the autophagy-related differentially expressed genes (ARGs) profiles and related molecular mechanisms in Corpus Cavernosum endothelial dysfunction, which is a leading cause of ED.

Methods

The Gene Expression Omnibus (GEO) database was used to identify the key genes and pathways. Differentially expressed genes (DEGs) were mined using the limma package in R language. Next, ARGs were obtained by matching DEGs and autophagy-related genes from GeneCard using Venn diagrams. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of ARGs were described using clusterProfiler and org.Hs.eg.db in R. Moreover, hub ARGs were screened out through protein-protein interaction (PPI), gene-microRNAs, and gene-transcription factors (TFs) networks then visualized using Cytoscape. Of note, the rat model of diabetic ED was established to validate some hub ARGs with qRT-PCR and Western blots.

Results

Twenty ARGs were identified from four ED samples and eight non-ED samples. GO analysis revealed that molecular functions (MF) of upregulated ARGs were mainly enriched in nuclear receptor activity. Also, MF of downregulated ARGs were mainly enriched in oxidoreductase activity, acting on NAD(P)H and heme proteins as acceptors. Moreover, six hub ARGs were identified by setting high degrees in the network. Additionally, hsa-mir-24-3p and hsa-mir-335-5p might play a central role in several ARGs regulation, and the transcription factors-hub genes network was centered with 13 ARGs. The experimental results further showed that the expression of Notch1, NOS3, and CDKN2A in the diabetic ED group was downregulated compared to the control.

Conclusions

Our study deepens the autophagy-related mechanistic understanding of endothelial dysfunction of ED. NOTCH1, CDKN2A, and NOS3 are involved in the regulation of endothelial dysfunction and may be potential therapeutic targets for ED by modulating autophagy.

Practical Considerations for Using RNA Sequencing in Management of B-Cell Acute Lymphoblastic Leukemia: Malaysia-Singapore Acute Lymphoblastic Leukemia-Sequencing 2020 Implementation Strategy

Despite the immense genetic heterogeneity of B-cell acute lymphoblastic leukemia (ALL), RNA sequencing (RNA-Seq) could comprehensively interrogate its genetic drivers, assigning a specific molecular subtype in >90% of patients. However, study groups have only started to use RNA-Seq. For broader clinical use, technical, quality control, and appropriate performance validation are needed. We describe the development and validation of an RNA-Seq workflow for subtype classification, TPMT/NUDT15/TP53 variant discovery, and IGH disease clone identification for Malaysia-Singapore ALL sequencing (ALL-Seq) 2020. We validated this workflow in 377 patients in our preceding Malaysia-Singapore ALL-Seq 2003/Malaysia-Singapore ALL-Seq 2010 studies and proposed the quality control measures for RNA quality, library size, sequencing, and data analysis using the International Organization for Standardization 15189 quality and competence standard for medical laboratories. Compared with conventional methods, we achieved >95% accuracy in oncogene fusion identification, digital karyotyping, and TPMT and NUDT15 variant discovery. We found seven pathogenic TP53 mutations, confirmed with Sanger sequencing, which conferred a poorer outcome. Applying this workflow prospectively to the first 21 patients in Malaysia-Singapore ALL-Seq 2020, we identified the genetic drivers and IGH disease clones in >90% of patients with concordant TPMT, NUDT15, and TP53 variants using PCR-based methods. The median turnaround time was 12 days, which was clinically actionable. In conclusion, RNA-Seq workflow could be used clinically in management of B-cell ALL patients.

Comparative Transcriptomics Reveals Distinct Patterns of Gene Expression Conservation through Vertebrate Embryogenesis

Despite life's diversity, studies of variation often remind us of our shared evolutionary past. Abundant genome sequencing and analyses of gene regulatory networks illustrate that genes and entire pathways are conserved, reused, and elaborated in the evolution of diversity. Predating these discoveries, 19th-century embryologists observed that though morphology at birth varies tremendously, certain stages of vertebrate embryogenesis appear remarkably similar across vertebrates. In the mid to late 20th century, anatomical variability of early and late-stage embryos and conservation of mid-stages embryos (the "phylotypic" stage) was named the hourglass model of diversification. This model has found mixed support in recent analyses comparing gene expression across species possibly owing to differences in species, embryonic stages, and gene sets compared. We compare 186 microarray and RNA-seq data sets covering embryogenesis in six vertebrate species. We use an unbiased clustering approach to group stages of embryogenesis by transcriptomic similarity and ask whether gene expression similarity of clustered embryonic stages deviates from a null expectation. We characterize expression conservation patterns of each gene at each evolutionary node after correcting for phylogenetic nonindependence. We find significant enrichment of genes exhibiting early conservation, hourglass, late conservation patterns in both microarray and RNA-seq data sets. Enrichment of genes showing patterned conservation through embryogenesis indicates diversification of embryogenesis may be temporally constrained. However, the circumstances under which each pattern emerges remain unknown and require both broad evolutionary sampling and systematic examination of embryogenesis across species.

Transcriptomic Signature of Human Embryonic Thyroid Reveals Transition From Differentiation to Functional Maturation

The human thyroid gland acquires a differentiation program as early as weeks 3-4 of embryonic development. The onset of functional differentiation, which manifests by the appearance of colloid in thyroid follicles, takes place during gestation weeks 10-11. By 12-13 weeks functional differentiation is accomplished and the thyroid is capable of producing thyroid hormones although at a low level. During maturation, thyroid hormones yield increases and physiological mechanisms of thyroid hormone synthesis regulation are established. In the present work we traced the process of thyroid functional differentiation and maturation in the course of human development by performing transcriptomic analysis of human thyroids covering the period of gestation weeks 7-11 and comparing it to adult human thyroid. We obtained specific transcriptomic signatures of embryonic and adult human thyroids by comparing them to non-thyroid tissues from human embryos and adults. We defined a non-TSH (thyroid stimulating hormone) dependent transition from differentiation to maturation of thyroid. The study also sought to shed light on possible factors that could replace TSH, which is absent in this window of gestational age, to trigger transition to the emergence of thyroid function. We propose a list of possible genes that may also be involved in abnormalities in thyroid differentiation and/or maturation, hence leading to congenital hypothyroidism. To our knowledge, this study represent the first transcriptomic analysis of human embryonic thyroid and its comparison to adult thyroid.

Screening and prognostic value of potential biomarkers for ovarian cancer

Background

Ovarian cancer is a common gynecological malignant tumor that greatly threatens women's health, so we screened potential biomarkers of ovarian cancer and analyzed their prognostic value.

Methods

The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets were used to analyze the ovarian cancer-related genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to analyze the function of ovarian cancer-related genes. The survival-related genes were screened out through the least absolute shrinkage and selection operator (LASSO) method. Multivariate Cox regression model and stepwise regression analysis were performed to construct the risk model. The receiver operating characteristic (ROC) and the area under the ROC curve (AUC) were used to evaluate the prediction accuracy of risk score model. Finally, gene set enrichment analysis (GSEA) and immune cell infiltration analysis were performed to investigate the biological function and immune cell infiltration.

Results

A total of 111 genes were found to have common effects on survival. These genes were mainly involved in metabolism, protein phosphorylation and immune-related signaling pathways. Seven risk genes (AP3D1, DCAF10, FBXO16, LRFN4, PTPN2, SAYSD1, ZNF426) were screened out. Among these genes, AP3D1 and LRFN4 are risk genes and DCAF10, FBXO16, PTPN2, SAYSD1, and ZNF426 are protective genes. These findings suggest that risk status may be an independent prognostic factor. The risk score had a high predictive value for the prognosis of ovarian cancer. In addition, GSEA revealed that the biological function of genes expressed in patients at a high risk was mostly related to immune-related function. The contents of CD4⁺ T cells, macrophages, myeloid dendritic cells (mDC) and neutrophils were high in samples at a high risk for ovarian cancer.

Conclusions

The abnormal expression of AP3D1, DCAF10, FBXO16, LRFN4, PTPN2, SAYSD1 and ZNF426 is highly related to the progression of ovarian cancer. These seven genes can be used as independent prognostic markers of ovarian cancer. This study not only adds evidence to the pathogenesis of ovarian cancer but also provides scientific basis for judging the prognosis of ovarian cancer.

Prognostic and Predictive Value of Immune-Related Gene Pair Signature in Primary Lower-Grade Glioma Patients

Immune-related gene pairs (IRGPs) have been associated with prognosis in various cancer types, but few studies have examined their prognostic capabilities in glioma patients. Here, we gathered the gene expression and clinical profile data of primary lower-grade glioma (LGG) patients from The Cancer Genome Atlas (TCGA), the Chinese Glioma Genome Atlas (CGGA, containing CGGAseq1 and CGGAseq2), the Gene Expression Omnibus (GEO: GSE16011), and Rembrandt datasets. In the TCGA dataset, univariate Cox regression was performed to detect overall survival (OS)-related IRGs, Lasso regression, and multivariate Cox regression were used to screen robust prognosis-related IRGs, and 19 IRGs were selected for the construction of an IRGP prognostic signature. All patients were allotted to high- and low-risk subgroups based on the TCGA dataset median value risk score. Validation analysis indicated that the IRGP signature returned a stable prognostic value among all datasets. Univariate and multivariate Cox regression analyses indicated that the IRG -signature could efficiently predict the prognosis of primary LGG patients. The IRGP-signature-based nomogram model was built, revealing the reliable ability of the IRGP signature to predict clinical prognosis. The single-sample gene set enrichment analysis (ssGSEA) suggested that high-risk samples contained higher numbers of immune cells but featured lower tumor purity than low-risk samples. Finally, we verified the prognostic ability of the IRGP signature using experiments performed in LGG cells. These results indicated that the IRGP signature could be regarded as a stable prognostic assessment predictor for identifying high-risk primary LGG patients.

An Integrated Analysis of Network Pharmacology, Molecular Docking, and Experiment Validation to Explore the New Candidate Active Component and Mechanism of Cuscutae Semen-Mori Fructus Coupled-Herbs in Treating Oligoasthenozoospermia

PURPOSE

One of the most common types of male infertility is recognized as oligoasthenozoospermia (OA), characterized by low sperm count and quality in males. As a traditional Chinese medicine (TCM), Cuscutae Semen-Mori Fructus coupled-herbs (CSMFCH) has been known to act a curative effect on OA for thousands of years. Nevertheless, the substantial basis and molecular mechanism of CSMFCH in treating OA remain elusive.

METHODS

Herein, an integrated approach, including network pharmacology, molecular docking, and experiment validation, was utilized to reveal the new candidate active component and mechanism of CSMFCH in treating OA.

RESULTS

The results show that kaempferol is the most significant bioactive component of CSMFCH on OA. The mechanism and targets of CSMFCH against OA are relevant to hormone regulation, oxidant stress, and reproductive promotion. In order to validate network pharmacology results, molecular docking and experiment validation were conducted. In detail, molecular docking was employed to verify the strong binding interactions between kaempferol and the core targets. UHPLC-Q-Orbitrap-MS was used to identify kaempferol in the CSMFCH extract. In vitro and in vivo experiments further proved CSMFCH and kaempferol could enhance the mouse Leydig (TM3) and mouse Sertoli (TM4) cell viability, improve the male reproductive organ weights, sperm quality, and decrease testis tissue damage in the OA mouse model induced by CP.

CONCLUSION

Our results not only identify the new candidate active component of CSMFCH in treating OA but also provide new insights into the mechanisms of CSMFCH against OA.

Horizontal meta-analysis identifies common deregulated genes across AML subgroups providing a robust prognostic signature

Advances in transcriptomics have improved our understanding of leukemic development and helped to enhance the stratification of patients. The tendency of transcriptomic studies to combine AML samples, regardless of cytogenetic abnormalities, could lead to bias in differential gene expression analysis because of the differential representation of AML subgroups. Hence, we performed a horizontal meta-analysis that integrated transcriptomic data on AML from multiple studies, to enrich the less frequent cytogenetic subgroups and to uncover common genes involved in the development of AML and response to therapy. A total of 28 Affymetrix microarray data sets containing 3940 AML samples were downloaded from the Gene Expression Omnibus database. After stringent quality control, transcriptomic data on 1534 samples from 11 data sets, covering 10 AML cytogenetically defined subgroups, were retained and merged with the data on 198 healthy bone marrow samples. Differentially expressed genes between each cytogenetic subgroup and normal samples were extracted, enabling the unbiased identification of 330 commonly deregulated genes (CODEGs), which showed enriched profiles of myeloid differentiation, leukemic stem cell status, and relapse. Most of these genes were downregulated, in accordance with DNA hypermethylation. CODEGs were then used to create a prognostic score based on the weighted sum of expression of 22 core genes (CODEG22). The score was validated with microarray data of 5 independent cohorts and by quantitative real time-polymerase chain reaction in a cohort of 142 samples. CODEG22-based stratification of patients, globally and into subpopulations of cytologically healthy and elderly individuals, may complement the European LeukemiaNet classification, for a more accurate prediction of AML outcomes.

Pneumolysin Is Responsible for Differential Gene Expression and Modifications in the Epigenetic Landscape of Primary Monocyte Derived Macrophages

Epigenetic modifications regulate gene expression in the host response to a diverse range of pathogens. The extent and consequences of epigenetic modification during macrophage responses to Streptococcus pneumoniae, and the role of pneumolysin, a key Streptococcus pneumoniae virulence factor, in influencing these responses, are currently unknown. To investigate this, we infected human monocyte derived macrophages (MDMs) with Streptococcus pneumoniae and addressed whether pneumolysin altered the epigenetic landscape and the associated acute macrophage transcriptional response using a combined transcriptomic and proteomic approach. Transcriptomic analysis identified 503 genes that were differentially expressed in a pneumolysin-dependent manner in these samples. Pathway analysis highlighted the involvement of transcriptional responses to core innate responses to pneumococci including modules associated with metabolic pathways activated in response to infection, oxidative stress responses and NFκB, NOD-like receptor and TNF signalling pathways. Quantitative proteomic analysis confirmed pneumolysin-regulated protein expression, early after bacterial challenge, in representative transcriptional modules associated with innate immune responses. In parallel, quantitative mass spectrometry identified global changes in the relative abundance of histone post translational modifications (PTMs) upon pneumococcal challenge. We identified an increase in the relative abundance of H3K4me1, H4K16ac and a decrease in H3K9me2 and H3K79me2 in a PLY-dependent fashion. We confirmed that pneumolysin blunted early transcriptional responses involving TNF-α and IL-6 expression. Vorinostat, a histone deacetylase inhibitor, similarly downregulated TNF-α production, reprising the pattern observed with pneumolysin. In conclusion, widespread changes in the macrophage transcriptional response are regulated by pneumolysin and are associated with global changes in histone PTMs. Modulating histone PTMs can reverse pneumolysin-associated transcriptional changes influencing innate immune responses, suggesting that epigenetic modification by pneumolysin plays a role in dampening the innate responses to pneumococci.

Ten-eleven translocation protein 1 modulates medulloblastoma progression

BACKGROUND

Medulloblastoma (MB) is the most common malignant pediatric brain tumor that originates in the cerebellum and brainstem. Frequent somatic mutations and deregulated expression of epigenetic regulators in MB highlight the substantial role of epigenetic alterations. 5-hydroxymethylcytosine (5hmC) is a highly abundant cytosine modification in the developing cerebellum and is regulated by ten-eleven translocation (TET) enzymes.

RESULTS

We investigate the alterations of 5hmC and TET enzymes in MB and their significance to cerebellar cancer formation. We show total abundance of 5hmC is reduced in MB, but identify significant enrichment of MB-specific 5hmC marks at regulatory regions of genes implicated in stem-like properties and Nanog-binding motifs. While TET1 and TET2 levels are high in MBs, only knockout of Tet1 in the smoothened (SmoA1) mouse model attenuates uncontrolled proliferation, leading to a favorable prognosis. The pharmacological Tet1 inhibition reduces cell viability and platelet-derived growth factor signaling pathway-associated genes.

CONCLUSIONS

These results together suggest a potential key role of 5hmC and indicate an oncogenic nature for TET1 in MB tumorigenesis, suggesting it as a potential therapeutic target for MBs.

Development of a four-gene prognostic model for clear cell renal cell carcinoma based on transcriptome analysis

This study aimed to develop a prognostic model for clear cell renal cell carcinoma (ccRCC) based on transcriptome analysis. We screened Gene Expression Omnibus (GEO) database and the Cancer Genome Atlas (TCGA) database for gene expression data and clinical characteristics of ccRCC. After differentially expression analysis, we identified 533 key genes of the development of ccRCC. Next, a weighted gene co-expression network analysis (WGCNA) was executed to investigate the association between differentially expressed genes and clinical characteristics. Then, based on protein-protein interaction (PPI) network, least absolute shrinkage and selection operator (LASSO) regression and Cox regression, a four-gene (COL4A5, ABCB1, NR3C2 and PLG) prognostic model has been constructed in TCGA training cohort. Finally, we examined the predictive power of this model with survival analysis and receiver operating characteristic (ROC) curve both in training cohort and in validation cohorts. And we found this model was significantly correlated with infiltrating immune cells. The four-gene prognosis model could be a potential prediction tool with high accuracy and reliability for ccRCC patients.

An autophagy-related prognostic signature associated with immune microenvironment features of uveal melanoma

Autophagy is involved in cancer initiation and progression but its role in uveal melanoma (UM) was rarely investigated. Herein, we built an autophagy-related gene (ARG) risk model of UM patients by univariate Cox regression and least absolute shrinkage and selection operator (Lasso) regression model and filtrated out nine prognostic ARGs in The Cancer Genome Atlas (TCGA) cohort. Survival and Receiver Operating Characteristic (ROC) Curve analysis in the TCGA and other four independent UM cohorts (GSE22138, GSE27831, GSE44295 and GSE84976) proved that the ARG-signature possessed robust and steady prognosis predictive ability. We calculated risk scores for patients included in our study and patients with higher risk scores showed worse clinical outcomes. We found the expressions of the nine ARGs were significantly associated with clinical and molecular features (including risk score) and overall survival (OS) of UM patients. Furthermore, we utilized univariate and multivariate Cox regression analyses to determine the independent prognostic ability of the ARG-signature. Functional enrichment analysis showed the ARG-signature was correlated with several immune-related processes and pathways like T-cell activation and T-cell receptor signaling pathway. Gene set enrichment analysis (GSEA) found tumor hallmarks including angiogenesis, IL6-JAK-STAT3-signaling, reactive oxygen species pathway and oxidative phosphorylation were enriched in high-risk UM patients. Finally, infiltrations of several immune cells and immune-related scores were found significantly associated with the ARG-signature. In conclusion, the ARG-signature might be a strong predictor for evaluating the prognosis and immune infiltration of UM patients.