beadarray: R classes and methods for Illumina bead-based data

Association of Lifestyle-Induced Weight Loss With Gene Expression in Subcutaneous Adipose Tissue in Metabolic Syndrome

AIMS

Lifestyle-induced weight loss (LIWL) is considered an effective therapy for the treatment of metabolic syndrome (MetS). The role of differentially expressed genes (DEGs) in adipose tissue function and in the success of LIWL in MetS is still unclear. We investigated the effect of 6 months of LIWL on transcriptional regulation in subcutaneous adipose tissue (SAT). Aiming to identify a LIWL-associated "gene signature" in SAT, DEGs were fitted into a linear regression model.

MATERIALS AND METHODS

The study is embedded in a prospective, two-arm, controlled, monocentric, randomized, 6-month interventional trial in individuals with MetS following LIWL. The trial included 43 nonsmoking, nondiabetic men aged 45-55 years with MetS.

RESULTS

In total, we identified 642 DEGs in SAT after 6 months of LIWL. The identified DEGs were validated in two cross-sectional cohorts analyzing SAT from individuals with and without obesity. Gene enrichment analysis of the DEGs revealed the strongest association with cholesterol metabolic processes. Accordingly, DEGs were correlated with the lipid parameters HDL cholesterol, LDL cholesterol, and triglycerides in corresponding serum samples. We identified 3 genes with an AUC of 0.963 (95% CI: 0.906-1.0) associated with a loss of more than 10% of initial body weight that was maintained for at least 12 months after LIWL, namely SUMO3 (Small ubiquitin-related modifier 3), PRKG2 (Protein Kinase CGMP-Dependent 2), and ADAP2 (ArfGAP with Dual PH Domains 2).

CONCLUSION

In summary, we have identified DEGs in SAT after LIWL, which may play an important role in metabolic functions. In particular, altered gene expression in SAT may predict sustained weight loss.

Transcriptional markers classifying Escherichia coli and Staphylococcus aureus induced sepsis in adults: A data-driven approach

Sepsis is a life-threatening condition mainly caused by gram-negative and gram-positive bacteria. Understanding the type of causative agent in the early stages is essential for precise antibiotic therapy. This study sought to identify a host gene set capable of distinguishing between sepsis induced by gram-negative bacteria; Escherichia coli and gram-positive bacteria; Staphylococcus aureus in community-onset adult patients. In the present study, microarray expression information was used to apply the Least Absolute Shrinkage and Selection Operator (Lasso) technique to select the predictive gene set for classifying sepsis induced by E. coli or S. aureus pathogens. We identified 25 predictive genes, including LILRA5 and TNFAIP6, which had previously been associated with sepsis in other research. Using these genes, we trained a logistic regression classifier to distinguish whether a sample contains an E. coli or S. aureus infection or belongs to a healthy control group, and subsequently assessed its performance. The classifier achieved an Area Under the Curve (AUC) of 0.96 for E. coli and 0.98 for S. aureus-induced sepsis, and perfect discrimination (AUC of 1) for healthy controls from the other conditions in a 10-fold cross-validation. The genes demonstrated an AUC of 0.75 in distinguishing between sepsis patients with E. coli and S. aureus pathogens. These findings were further confirmed in two distinct independent validation datasets which gave high prediction AUC ranging from 0.72-0.87 and 0.62 in distinguishing three groups of participants and two groups of patients respectively. These genes were significantly enriched in the immune system, cytokine signaling in immune system, innate immune system, and interferon signaling. Transcriptional patterns in blood can differentiate patients with E. coli-induced sepsis from those with S. aureus-induced sepsis. These diagnostic markers, upon validation in larger trials, may serve as a foundation for a reliable differential diagnostics assay.

Identification of Y‒linked biomarkers and exploration of immune infiltration of normal-appearing gray matter in multiple sclerosis by bioinformatic analysis

Background

The knowledge of normal‒appearing cortical gray matter (NAGM) in multiple sclerosis (MS) remains unclear. In this study, we aimed to identify diagnostic biomarkers and explore the immune infiltration characteristics of NAGM in MS through bioinformatic analysis and validation in vivo.

Methods

Differentially expressed genes (DEGs) were analyzed. Subsequently, the functional pathways of the DEGs were determined. After screening the overlapping DEGs of MS with two machine learning methods, the biomarkers' efficacy and the expression levels of overlapping DEGs were calculated. Quantitative reverse transcription polymerase chain reaction (qRT‒PCR) identified the robust diagnostic biomarkers. Additionally, infiltrating immune cell populations were estimated and correlated with the biomarkers. Finally, the characteristics of immune infiltration of NAGM from MS were evaluated.

Results

A total of 98 DEGs were identified. They participated in sensory transduction of the olfactory system, synaptic signaling, and immune responses. Nine overlapping genes were screened by machine learning methods. After verified by ROC curve, four genes, namely HLA‒DRB1, RPS4Y1, EIF1AY and USP9Y, were screened as candidate biomarkers. The mRNA expression of RPS4Y1 and USP9Y was significantly lower in MS patients than that in the controls. They were selected as the robust diagnostic biomarkers for male MS patients. RPS4Y1 and USP9Y were both positively correlated with memory B cells. Moreover, naive CD4+ T cells and monocytes were increased in the NAGM of MS patients compared with those in controls.

Conclusions

Low expressed Y‒linked genes, RPS4Y1 and USP9Y, were identified as diagnostic biomarkers for MS in male patients. The inhomogeneity of immune cells in NAGM might exacerbate intricate interplay between the CNS and the immune system in the MS.

IgG glycosylation associates with risk of progression from latent to active tuberculosis

OBJECTIVES

Glycosylation motifs shape antibody structure, stability and antigen affinity and play an important role in antibody localization and function. Serum IgG glycosylation profiles are significantly altered in infectious diseases, including tuberculosis (TB), but have not been studied in the context of progression from latent to active TB.

METHODS

We performed a longitudinal study of paired bulk IgG glycosylation and transcriptomic profiling in blood from individuals with active TB (ATB) or latent TB infection (LTBI) before and after treatment.

RESULTS

We identified that a combination of two IgG1 glycosylation traits were sufficient to distinguish ATB from LTBI with high specificity and sensitivity, prior to, and after treatment. Importantly, these two features positively correlated with previously defined cellular and RNA signatures of ATB risk in LTBI, namely monocyte to lymphocyte ratio and the expression of interferon (IFN)-associated gene signature of progression (IFN-risk signature) in blood prior to treatment. Additional glycosylation features at higher prevalence in LTBI individuals with high expression of the IFN-risk signature prior to treatment included fucosylation on IgG1, IgG2 and IgG3.

CONCLUSIONS

Together, our results demonstrate that bulk IgG glycosylation features could be useful in stratifying the risk of LTBI reactivation and progression to ATB.

Identifying squalene epoxidase as a metabolic vulnerability in high-risk osteosarcoma using an artificial intelligence-derived prognostic index

BACKGROUND

Osteosarcoma (OSA) presents a clinical challenge and has a low 5-year survival rate. Currently, the lack of advanced stratification models makes personalized therapy difficult. This study aims to identify novel biomarkers to stratify high-risk OSA patients and guide treatment.

METHODS

We combined 10 machine-learning algorithms into 101 combinations, from which the optimal model was established for predicting overall survival based on transcriptomic profiles for 254 samples. Alterations in transcriptomic, genomic and epigenomic landscapes were assessed to elucidate mechanisms driving poor prognosis. Single-cell RNA sequencing (scRNA-seq) unveiled genes overexpressed in OSA cells as potential therapeutic targets, one of which was validated via tissue staining, knockdown and pharmacological inhibition. We characterized changes in multiple phenotypes, including proliferation, colony formation, migration, invasion, apoptosis, chemosensitivity and in vivo tumourigenicity. RNA-seq and Western blotting elucidated the impact of squalene epoxidase (SQLE) suppression on signalling pathways.

RESULTS

The artificial intelligence-derived prognostic index (AIDPI), generated by our model, was an independent prognostic biomarker, outperforming clinicopathological factors and previously published signatures. Incorporating the AIDPI with clinical factors into a nomogram improved predictive accuracy. For user convenience, both the model and nomogram are accessible online. Patients in the high-AIDPI group exhibited chemoresistance, coupled with overexpression of MYC and SQLE, increased mTORC1 signalling, disrupted PI3K-Akt signalling, and diminished immune infiltration. ScRNA-seq revealed high expression of MYC and SQLE in OSA cells. Elevated SQLE expression correlated with chemoresistance and worse outcomes in OSA patients. Therapeutically, silencing SQLE suppressed OSA malignancy and enhanced chemosensitivity, mediated by cholesterol depletion and suppression of the FAK/PI3K/Akt/mTOR pathway. Furthermore, the SQLE-specific inhibitor FR194738 demonstrated anti-OSA effects in vivo and exhibited synergistic effects with chemotherapeutic agents.

CONCLUSIONS

AIDPI is a robust biomarker for identifying the high-risk subset of OSA patients. The SQLE protein emerges as a metabolic vulnerability in these patients, providing a target with translational potential.

Clonal and Scalable Endothelial Progenitor Cell Lines from Human Pluripotent Stem Cells

Human pluripotent stem cells (hPSCs) can be used as a renewable source of endothelial cells for treating cardiovascular disease and other ischemic conditions. Here, we present the derivation and characterization of a panel of distinct clonal embryonic endothelial progenitor cells (eEPCs) lines that were differentiated from human embryonic stem cells (hESCs). The hESC line, ESI-017, was first partially differentiated to produce candidate cultures from which eEPCs were cloned. Endothelial cell identity was assessed by transcriptomic analysis, cell surface marker expression, immunocytochemical marker analysis, and functional analysis of cells and exosomes using vascular network forming assays. The transcriptome of the eEPC lines was compared to various adult endothelial lines as well as various non-endothelial cells including both adult and embryonic origins. This resulted in a variety of distinct cell lines with functional properties of endothelial cells and strong transcriptomic similarity to adult endothelial primary cell lines. The eEPC lines, however, were distinguished from adult endothelium by their novel pattern of embryonic gene expression. We demonstrated eEPC line scalability of up to 80 population doublings (pd) and stable long-term expansion of over 50 pd with stable angiogenic properties at late passage. Taken together, these data support the finding that hESC-derived clonal eEPC lines are a potential source of scalable therapeutic cells and cell products for treating cardiovascular disease. These eEPC lines offer a highly promising resource for the development of further preclinical studies aimed at therapeutic interventions.

DNA Methylation Signatures of Multiple Sclerosis Occur Independently of Known Genetic Risk and Are Primarily Attributed to B Cells and Monocytes

Epigenetic mechanisms can regulate how DNA is expressed independently of sequence and are known to be associated with various diseases. Among those epigenetic mechanisms, DNA methylation (DNAm) is influenced by genotype and the environment, making it an important molecular interface for studying disease etiology and progression. In this study, we examined the whole blood DNA methylation profiles of a large group of people with (pw) multiple sclerosis (MS) compared to those of controls. We reveal that methylation differences in pwMS occur independently of known genetic risk loci and show that they more strongly differentiate disease (AUC = 0.85, 95% CI 0.82-0.89, p = 1.22 × 10-29) than known genetic risk loci (AUC = 0.72, 95% CI: 0.66-0.76, p = 9.07 × 10-17). We also show that methylation differences in MS occur predominantly in B cells and monocytes and indicate the involvement of cell-specific biological pathways. Overall, this study comprehensively characterizes the immune cell-specific epigenetic architecture of MS.

Development of a next-generation endogenous OCT4 inducer and its anti-aging effect in vivo

The identification of small molecules capable of replacing transcription factors has been a longstanding challenge in the generation of human chemically induced pluripotent stem cells (iPSCs). Recent studies have shown that ectopic expression of OCT4, one of the master pluripotency regulators, compromised the developmental potential of resulting iPSCs, This highlights the importance of finding endogenous OCT4 inducers for the generation of clinical-grade human iPSCs. Through a cell-based high throughput screen, we have discovered several new OCT4-inducing compounds (O4Is). In this work, we prepared metabolically stable analogues, including O4I4, which activate endogenous OCT4 and associated signaling pathways in various cell lines. By combining these with a transcription factor cocktail consisting of SOX2, KLF4, MYC, and LIN28 (referred to as "CSKML") we achieved to reprogram human fibroblasts into a stable and authentic pluripotent state without the need for exogenous OCT4. In Caenorhabditis elegans and Drosophila, O4I4 extends lifespan, suggesting the potential application of OCT4-inducing compounds in regenerative medicine and rejuvenation therapy.

Landscape of Well-Coordinated Fracture Healing in a Mouse Model Using Molecular and Cellular Analysis

The success of fracture healing relies on overlapping but coordinated cellular and molecular events. Characterizing an outline of differential gene regulation throughout successful healing is essential for identifying crucial phase-specific markers and may serve as the basis for engineering these in challenging healing situations. This study analyzed the healing progression of a standard closed femoral fracture model in C57BL/6N (age = 8 weeks) wild-type male mice. The fracture callus was assessed across various days post fracture (D = days 0, 3, 7, 10, 14, 21, and 28) by microarray, with D0 serving as a control. Histological analyses were carried out on samples from D7 until D28 to support the molecular findings. Microarray analysis revealed a differential regulation of immune response, angiogenesis, ossification, extracellular matrix regulation, mitochondrial and ribosomal genes during healing. In-depth analysis showed differential regulation of mitochondrial and ribosomal genes during the initial phase of healing. Furthermore, the differential gene expression showed an essential role of Serpin Family F Member 1 over the well-known Vascular Endothelial Growth Factor in angiogenesis, especially during the inflammatory phase. The significant upregulation of matrix metalloproteinase 13 and bone sialoprotein from D3 until D21 asserts their importance in bone mineralization. The study also shows type I collagen around osteocytes located in the ossified region at the periosteal surface during the first week of healing. Histological analysis of matrix extracellular phosphoglycoprotein and extracellular signal-regulated kinase stressed their roles in bone homeostasis and the physiological bone-healing process. This study reveals previously unknown and novel candidates, that could serve as a target for specific time points in healing and to remedy cases of impaired healing.

Systems level analysis of sex-dependent gene expression changes in Parkinson's disease

Parkinson's disease (PD) is a heterogeneous disorder, and among the factors which influence the symptom profile, biological sex has been reported to play a significant role. While males have a higher age-adjusted disease incidence and are more frequently affected by muscle rigidity, females present more often with disabling tremors. The molecular mechanisms involved in these differences are still largely unknown, and an improved understanding of the relevant factors may open new avenues for pharmacological disease modification. To help address this challenge, we conducted a meta-analysis of disease-associated molecular sex differences in brain transcriptomics data from case/control studies. Both sex-specific (alteration in only one sex) and sex-dimorphic changes (changes in both sexes, but with opposite direction) were identified. Using further systems level pathway and network analyses, coordinated sex-related alterations were studied. These analyses revealed significant disease-associated sex differences in mitochondrial pathways and highlight specific regulatory factors whose activity changes can explain downstream network alterations, propagated through gene regulatory cascades. Single-cell expression data analyses confirmed the main pathway-level changes observed in bulk transcriptomics data. Overall, our analyses revealed significant sex disparities in PD-associated transcriptomic changes, resulting in coordinated modulations of molecular processes. Among the regulatory factors involved, NR4A2 has already been reported to harbor rare mutations in familial PD and its pharmacological activation confers neuroprotective effects in toxin-induced models of Parkinsonism. Our observations suggest that NR4A2 may warrant further research as a potential adjuvant therapeutic target to address a subset of pathological molecular features of PD that display sex-associated profiles.

A review of bioinformatics tools and web servers in different microarray platforms used in cancer research

Over the past decade, conventional lab work strategies have gradually shifted from being limited to a laboratory setting towards a bioinformatics era to help manage and process the vast amounts of data generated by omics technologies. The present work outlines the latest contributions of bioinformatics in analyzing microarray data and their application to cancer. We dissect different microarray platforms and their use in gene expression in cancer models. We highlight how computational advances empowered the microarray technology in gene expression analysis. The study on protein-protein interaction databases classified into primary, derived, meta-database, and prediction databases describes the strategies to curate and predict novel interaction networks in silico. In addition, we summarize the areas of bioinformatics where neural graph networks are currently being used, such as protein functions, protein interaction prediction, and in silico drug discovery and development. We also discuss the role of deep learning as a potential tool in the prognosis, diagnosis, and treatment of cancer. Integrating these resources efficiently, practically, and ethically is likely to be the most challenging task for the healthcare industry over the next decade; however, we believe that it is achievable in the long term.

Single-cell transcriptomics identifies potential cells of origin of MYC rhabdoid tumors

Rhabdoid tumors (RT) are rare and highly aggressive pediatric neoplasms. Their epigenetically-driven intertumoral heterogeneity is well described; however, the cellular origin of RT remains an enigma. Here, we establish and characterize different genetically engineered mouse models driven under the control of distinct promoters and being active in early progenitor cell types with diverse embryonic onsets. From all models only Sox2-positive progenitor cells give rise to murine RT. Using single-cell analyses, we identify distinct cells of origin for the SHH and MYC subgroups of RT, rooting in early stages of embryogenesis. Intra- and extracranial MYC tumors harbor common genetic programs and potentially originate from fetal primordial germ cells (PGCs). Using PGC specific Smarcb1 knockout mouse models we validate that MYC RT originate from these progenitor cells. We uncover an epigenetic imbalance in MYC tumors compared to PGCs being sustained by epigenetically-driven subpopulations. Importantly, treatments with the DNA demethylating agent decitabine successfully impair tumor growth in vitro and in vivo. In summary, our work sheds light on the origin of RT and supports the clinical relevance of DNA methyltransferase inhibitors against this disease.

Rhabdoid tumors (RT) are aggressive paediatric cancers with yet unknown cells of origin. Here, the authors establish genetically engineered mouse models of RT and, using single-cell RNA-seq and epigenomics, identify potential cells of origin for the SHH and MYC subtypes.

Age-related DNA methylation on Y chromosome and their associations with total mortality among Chinese males

In view of the sex differences in aging‐related diseases, sex chromosomes may play a critical role during aging process. This study aimed to identify age‐related DNA methylation changes on Y chromosome (ChrY). A two‐stage study design was conducted in this study. The discovery stage contained 419 Chinese males, including 205 from the Wuhan‐Zhuhai cohort panel, 107 from the coke oven workers panel, and 107 from the Shiyan panel. The validation stage contained 587 Chinese males from the Dongfeng‐Tongji sub‐cohort. We used the Illumina HumanMethylation BeadChip to determine genome‐wide DNA methylation in peripheral blood of the study participants. The associations between age and methylation levels of ChrY CpGs were investigated by using linear regression models with adjustment for potential confounders. Further, associations of age‐related ChrY CpGs with all‐cause mortality were tested in the validation stage. We identified the significant associations of 41 ChrY CpGs with age at false discovery rate (FDR) <0.05 in the discovery stage, and 18 of them were validated in the validation stage (p < 0.05). Meta‐analysis of both stages confirmed the robust positive associations of 14 CpGs and negative associations of 4 CpGs with age (FDR<0.05). Among them, cg03441493 and cg17816615 were significantly associated with all‐cause mortality risk [HR(95% CI) = 1.37 (1.04, 1.79) and 0.70 (0.54, 0.93), respectively]. Our results highlighted the importance of ChrY CpGs on male aging.

Single cell transcriptomic landscape of diabetic foot ulcers

Diabetic foot ulceration (DFU) is a devastating complication of diabetes whose pathogenesis remains incompletely understood. Here, we profile 174,962 single cells from the foot, forearm, and peripheral blood mononuclear cells using single-cell RNA sequencing. Our analysis shows enrichment of a unique population of fibroblasts overexpressing MMP1, MMP3, MMP11, HIF1A, CHI3L1, and TNFAIP6 and increased M1 macrophage polarization in the DFU patients with healing wounds. Further, analysis of spatially separated samples from the same patient and spatial transcriptomics reveal preferential localization of these healing associated fibroblasts toward the wound bed as compared to the wound edge or unwounded skin. Spatial transcriptomics also validates our findings of higher abundance of M1 macrophages in healers and M2 macrophages in non-healers. Our analysis provides deep insights into the wound healing microenvironment, identifying cell types that could be critical in promoting DFU healing, and may inform novel therapeutic approaches for DFU treatment.

RNA Exosome Component EXOSC4 Amplified in Multiple Cancer Types Is Required for the Cancer Cell Survival

The RNA exosome is a multi-subunit ribonuclease complex that is evolutionally conserved and the major cellular machinery for the surveillance, processing, degradation, and turnover of diverse RNAs essential for cell viability. Here we performed integrated genomic and clinicopathological analyses of 27 RNA exosome components across 32 tumor types using The Cancer Genome Atlas PanCancer Atlas Studies' datasets. We discovered that the EXOSC4 gene, which encodes a barrel component of the RNA exosome, was amplified across multiple cancer types. We further found that EXOSC4 alteration is associated with a poor prognosis of pancreatic cancer patients. Moreover, we demonstrated that EXOSC4 is required for the survival of pancreatic cancer cells. EXOSC4 also repressed BIK expression and destabilized SESN2 mRNA by promoting its degradation. Furthermore, knockdown of BIK and SESN2 could partially rescue pancreatic cells from the reduction in cell viability caused by EXOSC4 knockdown. Our study provides evidence for EXOSC4-mediated regulation of BIK and SESN2 mRNA in the survival of pancreatic tumor cells.

Recommendations for pharmacotranscriptomic profiling of drug response in CNS disorders

Pharmacotranscriptomics is a still very new field of research that has just begun to flourish and promises to enable target discovery, inform biomarker and evaluate drug efficacy beyond pharmacogenomics. The aim of this review is to provide a critical overview of the biological foundations of transcriptomics, methodological approaches to transcriptomic studies, and their advantages and limitations. We present the different RNA species (rRNAs, tRNAs, mtRNAs, snRNAs, scRNAs, mRNAs, ncRNAs, LINE and SINE transcripts, circular RNAs, piRNAs, miRNAs, snoRNAs) and their potential for pharmacotranscriptomic studies as markers to predict treatment response in neurological and psychiatric disorders. We also review the accessible sources of RNA in patients peripheral blood cells (including platelets), plasma, microvesicles, exosomes, apoptotic bodies, and how those affect the integrity and relative abundances of RNAs and reflect the situation in the Central Nervous System (CNS). Finally, we discuss the suitability and indications of different techniques, such as microarrays and RNA-sequencing (RNA-Seq) techniques to understand gene expression differences or to reveal variation in expression levels of coding and non-coding genes. We conclude with some recommendations for future directions, e.g., gaps of knowledge and particular RNAs/tissues that have been overlooked.

Epigenetic Regulation of Interleukin-17-Related Genes and Their Potential Roles in Neutrophil Vascular Infiltration in Preeclampsia

DNA methylation is an epigenetic mechanism controlling gene expression, and reduced methylation is associated with increased gene expression. We hypothesized that IL-17 cytokines are regulated by DNA methylation, are elevated in the circulation of preeclamptic women, and stimulate vascular neutrophil chemokine expression, which could account for vascular infiltration of neutrophils in preeclampsia. We found significantly reduced DNA methylation of IL17A, IL17E, and IL17F genes in omental arteries of preeclamptic women, significantly reduced methylation of IL2, which regulates IL-17-producing T-lymphocytes, and significantly reduced methylation of genes encoding neutrophil chemokines and TNFα receptors related to lymphocyte function. Maternal plasma levels of IL-17A were significantly elevated in the second trimester of preeclamptic pregnancy as compared to normal pregnancy. To test if methylation regulates IL-17 cytokines, a lymphocyte cell line (Jurkat) was cultured with a hypomethylating agent. Hypomethylation increased expression of IL17E (aka IL25), IL17F, and IL2. IL17A was not expressed by Jurkat cells. To test the potential role of IL-17 cytokines in vascular neutrophil infiltration associated with preeclampsia, human vascular smooth muscle cells were cultured with IL-17 cytokines. IL-17A, but not IL-17E or IL-17F, increased gene expression of neutrophil chemokines (IL-8, CXCL5, and CXCL6) that are increased in vascular smooth muscle of preeclamptic women. The monocyte chemokine, CCL-2, was not increased. TNFα also increased neutrophil chemokines. IL-17 cytokines are regulated by DNA methylation; IL-17A is elevated in preeclampsia and stimulates expression of neutrophil chemokines in vascular smooth muscle. IL-17A could be responsible for vascular infiltration of neutrophils in preeclampsia.

Reconstruction of tissue-specific genome-scale metabolic models for human cancer stem cells

Cancer Stem Cells (CSCs) contribute to cancer aggressiveness, metastasis, chemo/radio-therapy resistance, and tumor recurrence. Recent studies emphasized the importance of metabolic reprogramming of CSCs for the maintenance and progression of the cancer phenotype through both the fulfillment of the energetic requirements and the supply of substrates fundamental for fast-cell growth, as well as through metabolite-induced epigenetic regulation. Therefore, it is of paramount importance to develop therapeutic strategies tailored to target the metabolism of CSCs. In this work, we built computational Genome-Scale Metabolic Models (GSMMs) for CSCs of different tissues. Flux simulations were then used to predict metabolic phenotypes, identify potential therapeutic targets, and spot already-known Transcription Factors (TFs), miRNAs and antimetabolites that could be used as part of drug repurposing strategies against cancer. Results were in accordance with experimental evidence, provided insights of new metabolic mechanisms for already known agents, and allowed for the identification of potential new targets and compounds that could be interesting for further in vitro and in vivo validation.

Antiproliferative, Antiangiogenic, and Antimetastatic Therapy Response by Mangiferin in a Syngeneic Immunocompetent Colorectal Cancer Mouse Model Involves Changes in Mitochondrial Energy Metabolism

In spite of the current advances and achievements in cancer treatments, colorectal cancer (CRC) persists as one of the most prevalent and deadly tumor types in both men and women worldwide. Drug resistance, adverse side effects and high rate of angiogenesis, metastasis and tumor relapse remain one of the greatest challenges in long-term management of CRC and urges need for new leads of anticancer drugs. We demonstrate that CRC treatment with the phytopharmaceutical mangiferin (MGF), a glucosylxanthone present in Mango tree stem bark and leaves (Mangifera Indica L.), induces dose-dependent tumor regression and decreases lung metastasis in a syngeneic immunocompetent allograft mouse model of murine CT26 colon carcinoma, which increases overall survival of mice. Antimetastatic and antiangiogenic MGF effects could be further validated in a wound healing in vitro model in human HT29 cells and in a matrigel plug implant mouse model. Interestingly, transcriptome pathway enrichment analysis demonstrates that MGF inhibits tumor growth, metastasis and angiogenesis by multi-targeting of mitochondrial oxidoreductase and fatty acid β-oxidation metabolism, PPAR, SIRT, NFκB, Stat3, HIF, Wnt and GP6 signaling pathways. MGF effects on fatty acid β-oxidation metabolism and carnitine palmitoyltransferase 1 (CPT1) protein expression could be further confirmed in vitro in human HT29 colon cells. In conclusion, antitumor, antiangiogenic and antimetastatic effects of MGF treatment hold promise to reduce adverse toxicity and to mitigate therapeutic outcome of colorectal cancer treatment by targeting mitochondrial energy metabolism in the tumor microenvironment.

Gene Expression Analysis Platform (GEAP): A highly customizable, fast, versatile and ready-to-use microarray analysis platform

There are still numerous challenges to be overcome in microarray data analysis because advanced, state-of-the-art analyses are restricted to programming users. Here we present the Gene Expression Analysis Platform, a versatile, customizable, optimized, and portable software developed for microarray analysis. GEAP was developed in C# for the graphical user interface, data querying, storage, results filtering and dynamic plotting, and R for data processing, quality analysis, and differential expression. Through a new automated system that identifies microarray file formats, retrieves contents, detects file corruption, and solves dependencies, GEAP deals with datasets independently of platform. GEAP covers 32 statistical options, supports quality assessment, differential expression from single and dual-channel experiments, and gene ontology. Users can explore results by different plots and filtering options. Finally, the entire data can be saved and organized through storage features, optimized for memory and data retrieval, with faster performance than R. These features, along with other new options, are not yet present in any microarray analysis software. GEAP accomplishes data analysis in a faster, straightforward, and friendlier way than other similar software, while keeping the flexibility for sophisticated procedures. By developing optimizations, unique customizations and new features, GEAP is destined for both advanced and non-programming users.

Patterns of Maternal Neutrophil Gene Expression at 30 Weeks of Gestation, but Not DNA Methylation, Distinguish Mild from Severe Preeclampsia

Neutrophils are activated and extensively infiltrate blood vessels in preeclamptic women. To identify genes that contribute to neutrophil activation and infiltration, we analyzed the transcriptomes of circulating neutrophils from normal pregnant and preeclamptic women. Neutrophils were collected at 30 weeks’ gestation and RNA and DNA were isolated for RNA sequencing and 5-hydroxy-methylcytosine (5-hmC) sequencing as an index of dynamic changes in neutrophil DNA methylation. Women with normal pregnancy who went on to develop mild preeclampsia at term had the most uniquely expressed genes (697) with 325 gene ontology pathways upregulated, many related to neutrophil activation and function. Women with severe preeclampsia who delivered prematurely had few pathways up- or downregulated. Cluster analysis revealed that gene expression in women with severe preeclampsia was an inverse mirror image of gene expression in normal pregnancy, while gene expression in women who developed mild preeclampsia was remarkably different from both. DNA methylation marks, key regulators of gene expression, are removed by the action of ten-eleven translocation (TET) enzymes, which oxidize 5-methylcytosines (5mCs), resulting in locus-specific reversal of DNA methylation. DNA sequencing for 5-hmC revealed no differences among the three groups. Genome-wide DNA methylation revealed extremely low levels in circulating neutrophils suggesting they are de-methylated. Collectively, these data demonstrate that neutrophil gene expression profiles can distinguish different preeclampsia phenotypes, and in the case of mild preeclampsia, alterations in gene expression occur well before clinical symptoms emerge. These findings serve as a foundation for further evaluation of neutrophil transcriptomes as biomarkers of preeclampsia phenotypes. Changes in DNA methylation in circulating neutrophils do not appear to mediate differential patterns of gene expression in either mild or severe preeclampsia.

Functional screen of inflammatory bowel disease genes reveals key epithelial functions

BACKGROUND

Genetic studies have been tremendously successful in identifying genomic regions associated with a wide variety of phenotypes, although the success of these studies in identifying causal genes, their variants, and their functional impacts has been more limited.

METHODS

We identified 145 genes from IBD-associated genomic loci having endogenous expression within the intestinal epithelial cell compartment. We evaluated the impact of lentiviral transfer of the open reading frame (ORF) of these IBD genes into the HT-29 intestinal epithelial cell line via transcriptomic analyses. By comparing the genes in which expression was modulated by each ORF, as well as the functions enriched within these gene lists, we identified ORFs with shared impacts and their putative disease-relevant biological functions.

RESULTS

Analysis of the transcriptomic data for cell lines expressing the ORFs for known causal genes such as HNF4a, IFIH1, and SMAD3 identified functions consistent with what is already known for these genes. These analyses also identified two major clusters of genes: Cluster 1 contained the known IBD causal genes IFIH1, SBNO2, NFKB1, and NOD2, as well as genes from other IBD loci (ZFP36L1, IRF1, GIGYF1, OTUD3, AIRE and PITX1), whereas Cluster 2 contained the known causal gene KSR1 and implicated DUSP16 from another IBD locus. Our analyses highlight how multiple IBD gene candidates can impact on epithelial structure and function, including the protection of the mucosa from intestinal microbiota, and demonstrate that DUSP16 acts a regulator of MAPK activity and contributes to mucosal defense, in part via its regulation of the polymeric immunoglobulin receptor, involved in the protection of the intestinal mucosa from enteric microbiota.

CONCLUSIONS

This functional screen, based on expressing IBD genes within an appropriate cellular context, in this instance intestinal epithelial cells, resulted in changes to the cell's transcriptome that are relevant to their endogenous biological function(s). This not only helped in identifying likely causal genes within genetic loci but also provided insight into their biological functions. Furthermore, this work has highlighted the central role of intestinal epithelial cells in IBD pathophysiology, providing a scientific rationale for a drug development strategy that targets epithelial functions in addition to the current therapies targeting immune functions.

Fibromine is a multi-omics database and mining tool for target discovery in pulmonary fibrosis

Idiopathic pulmonary fibrosis is a lethal lung fibroproliferative disease with limited therapeutic options. Differential expression profiling of affected sites has been instrumental for involved pathogenetic mechanisms dissection and therapeutic targets discovery. However, there have been limited efforts to comparatively analyse/mine the numerous related publicly available datasets, to fully exploit their potential on the validation/creation of novel research hypotheses. In this context and towards that goal, we present Fibromine, an integrated database and exploration environment comprising of consistently re-analysed, manually curated transcriptomic and proteomic pulmonary fibrosis datasets covering a wide range of experimental designs in both patients and animal models. Fibromine can be accessed via an R Shiny application (http://www.fibromine.com/Fibromine) which offers dynamic data exploration and real-time integration functionalities. Moreover, we introduce a novel benchmarking system based on transcriptomic datasets underlying characteristics, resulting to dataset accreditation aiming to aid the user on dataset selection. Cell specificity of gene expression can be visualised and/or explored in several scRNA-seq datasets, in an effort to link legacy data with this cutting-edge methodology and paving the way to their integration. Several use case examples are presented, that, importantly, can be reproduced on-the-fly by a non-specialist user, the primary target and potential user of this endeavour.

Computational Interspecies Translation Between Alzheimer's Disease Mouse Models and Human Subjects Identifies Innate Immune Complement, TYROBP, and TAM Receptor Agonist Signatures, Distinct From Influences of Aging

Mouse models are vital for preclinical research on Alzheimer’s disease (AD) pathobiology. Many traditional models are driven by autosomal dominant mutations identified from early onset AD genetics whereas late onset and sporadic forms of the disease are predominant among human patients. Alongside ongoing experimental efforts to improve fidelity of mouse model representation of late onset AD, a computational framework termed Translatable Components Regression (TransComp-R) offers a complementary approach to leverage human and mouse datasets concurrently to enhance translation capabilities. We employ TransComp-R to integratively analyze transcriptomic data from human postmortem and traditional amyloid mouse model hippocampi to identify pathway-level signatures present in human patient samples yet predictive of mouse model disease status. This method allows concomitant evaluation of datasets across different species beyond observational seeking of direct commonalities between the species. Additional linear modeling focuses on decoupling disease signatures from effects of aging. Our results elucidated mouse-to-human translatable signatures associated with disease: excitatory synapses, inflammatory cytokine signaling, and complement cascade- and TYROBP-based innate immune activity; these signatures all find validation in previous literature. Additionally, we identified agonists of the Tyro3 / Axl / MerTK (TAM) receptor family as significant contributors to the cross-species innate immune signature; the mechanistic roles of the TAM receptor family in AD merit further dedicated study. We have demonstrated that TransComp-R can enhance translational understanding of relationships between AD mouse model data and human data, thus aiding generation of biological hypotheses concerning AD progression and holding promise for improved preclinical evaluation of therapies.

Treatment resistance analysis reveals GLUT-1-mediated glucose uptake as a major target of synthetic rocaglates in cancer cells

Rocaglates are natural compounds that have been extensively studied for their ability to inhibit translation initiation. Rocaglates represent promising drug candidates for tumor treatment due to their growth‐inhibitory effects on neoplastic cells. In contrast to natural rocaglates, synthetic analogues of rocaglates have been less comprehensively characterized, but were also shown to have similar effects on the process of protein translation. Here, we demonstrate an enhanced growth‐inhibitory effect of synthetic rocaglates when combined with glucose anti‐metabolite 2‐deoxy‐D‐glucose (2DG) in different cancer cell lines. Moreover, we unravel a new aspect in the mechanism of action of synthetic rocaglates involving reduction of glucose uptake mediated by downregulation or abrogation of glucose transporter GLUT‐1 expression. Importantly, cells with genetically induced resistance to synthetic rocaglates showed substantially less pronounced treatment effect on glucose metabolism and did not demonstrate GLUT‐1 downregulation, pointing at the crucial role of this mechanism for the anti‐tumor activity of the synthetic rocaglates. Transcriptome profiling revealed glycolysis as one of the major pathways differentially regulated in sensitive and resistant cells. Analysis of synthetic rocaglate efficacy in a 3D tissue context with a co‐culture of tumor and normal cells demonstrated a selective effect on tumor cells and substantiated the mechanistic observations obtained in cancer cell lines. Increased glucose uptake and metabolism is a universal feature across different tumor types. Therefore, targeting this feature by synthetic rocaglates could represent a promising direction for exploitation of rocaglates in novel anti‐tumor therapies.

Hyperglycemia Induces Trained Immunity in Macrophages and Their Precursors and Promotes Atherosclerosis

BACKGROUND

Cardiovascular risk in diabetes remains elevated despite glucose-lowering therapies. We hypothesized that hyperglycemia induces trained immunity in macrophages, promoting persistent proatherogenic characteristics.

METHODS

Bone marrow-derived macrophages from control mice and mice with diabetes were grown in physiological glucose (5 mmol/L) and subjected to RNA sequencing (n=6), assay for transposase accessible chromatin sequencing (n=6), and chromatin immunoprecipitation sequencing (n=6) for determination of hyperglycemia-induced trained immunity. Bone marrow transplantation from mice with (n=9) or without (n=6) diabetes into (normoglycemic) Ldlr-/- mice was used to assess its functional significance in vivo. Evidence of hyperglycemia-induced trained immunity was sought in human peripheral blood mononuclear cells from patients with diabetes (n=8) compared with control subjects (n=16) and in human atherosclerotic plaque macrophages excised by laser capture microdissection.

RESULTS

In macrophages, high extracellular glucose promoted proinflammatory gene expression and proatherogenic functional characteristics through glycolysis-dependent mechanisms. Bone marrow-derived macrophages from diabetic mice retained these characteristics, even when cultured in physiological glucose, indicating hyperglycemia-induced trained immunity. Bone marrow transplantation from diabetic mice into (normoglycemic) Ldlr-/- mice increased aortic root atherosclerosis, confirming a disease-relevant and persistent form of trained innate immunity. Integrated assay for transposase accessible chromatin, chromatin immunoprecipitation, and RNA sequencing analyses of hematopoietic stem cells and bone marrow-derived macrophages revealed a proinflammatory priming effect in diabetes. The pattern of open chromatin implicated transcription factor Runt-related transcription factor 1 (Runx1). Similarly, transcriptomes of atherosclerotic plaque macrophages and peripheral leukocytes in patients with type 2 diabetes were enriched for Runx1 targets, consistent with a potential role in human disease. Pharmacological inhibition of Runx1 in vitro inhibited the trained phenotype.

CONCLUSIONS

Hyperglycemia-induced trained immunity may explain why targeting elevated glucose is ineffective in reducing macrovascular risk in diabetes and suggests new targets for disease prevention and therapy.

Identifying critical genes associated with aneurysmal subarachnoid hemorrhage by weighted gene co-expression network analysis

Aneurysmal subarachnoid hemorrhage (aSAH) is a life-threatening medical condition with a high mortality and disability rate. aSAH has an unclear pathogenesis, and limited treatment options are available. Here, we aimed to identify critical genes involved in aSAH pathogenesis using peripheral blood gene expression data of 43 patients with aSAH due to ruptured intracranial aneurysms and 18 controls with headache, downloaded from Gene Expression Omnibus. These data were used to construct a co-expression network using weighted gene co-expression network analysis (WGCNA). The biological functions of the hub genes were explored, and critical genes were selected by combining with differentially expressed genes analysis. Fourteen modules were identified by WGCNA. Among those modules, red, blue, brown and cyan modules were closely associated with aSAH. Moreover, 364 hub genes in the significant modules were found to play important roles in aSAH. Biological function analysis suggested that protein biosynthesis-related processes and inflammatory responses-related processes were involved in the pathology of aSAH pathology. Combined with differentially expressed genes analysis and validation in 35 clinical samples, seven gene (CD27, ANXA3, ACSL1, PGLYRP1, ALPL, ARG1, and TPST1) were identified as potential biomarkers for aSAH, and three genes (ANXA3, ALPL, and ARG1) were changed with disease development, that may provide new insights into potential molecular mechanisms for aSAH.

Distinct blood transcriptomic signature of treatment in latent tuberculosis infected individuals at risk of developing active disease

Although only a small fraction will ever develop the active form of tuberculosis (ATB) disease, chemoprophylaxis treatment in latent TB infected (LTBI) individuals is an effective strategy to control pathogen transmission. Characterizing immune responses in LTBI upon chemoprophylactic treatment is important to facilitate treatment monitoring, and thus improve TB control strategies. Here, we studied changes in the blood transcriptome in a cohort of 42 LTBI and 8 ATB participants who received anti-TB therapy. Based on the expression of previously published gene signatures of progression to ATB, we stratified the LTBI cohort in two groups and examined if individuals deemed to be at elevated risk of developing ATB before treatment (LTBI-Risk) differed from others (LTBI-Other). We found that LTBI-Risk and LTBI-Other groups were associated with two distinct transcriptomic treatment signatures, with the LTBI-Risk signature resembling that of treated ATB patients. Notably, overlapping genes between LTBI-Risk and ATB treatment signatures were associated with risk of progression to ATB and interferon (IFN) signaling, and were selectively downregulated upon treatment in the LTBI-Risk but not the LTBI-Other group. Our results suggest that transcriptomic reprogramming following treatment of LTBI is heterogeneous and can be used to distinguish LTBI-Risk individuals from the LTBI cohort at large.

MicroRNAs hsa-miR-618 and hsa-miR-297 Might Modulate the Pleiotropic Effects Exerted by Statins in Endothelial Cells Through the Inhibition of ROCK2 Kinase: in-silico Approach

Several studies show that statin therapy improves endothelial function by cholesterol-independent mechanisms called “pleiotropic effects.” These are due to the inhibition of the RhoA/ROCK kinase pathway, its inhibition being an attractive atheroprotective treatment. In addition, recent work has shown that microRNAs, posttranscriptional regulators of gene expression, can affect the response of statins and their efficacy. For this reason, the objective of this study was to identify by bioinformatic analysis possible new microRNAs that could modulate the pleiotropic effects exerted by statins through the inhibition of ROCK kinases. A bioinformatic study was performed in which the differential expression of miRNAs in endothelial cells was compared under two conditions: Control and treated with simvastatin at 10 μM for 24 h, using a microarray. Seven miRNAs were differentially expressed, three up and four down. Within the up group, the miRNAs hsa-miR-618 and hsa-miR-297 present as a predicted target to ROCK2 kinase. Also, functional and enriched pathway analysis showed an association with mechanisms associated with atheroprotective effects. This work shows an in-silico approach of how posttranscriptional regulation mediated by miRNAs could modulate the pleiotropic effects exerted by statins on endothelial cells, through the inhibition of ROCK2 kinase and its effects.

Meta-analysis of transcriptomic data reveals clusters of consistently deregulated gene and disease ontologies in Down syndrome

Trisomy of human chromosome 21 (HSA21) causes Down syndrome (DS). The trisomy does not simply result in the upregulation of HSA21--encoded genes but also leads to a genome-wide transcriptomic deregulation, which affect differently each tissue and cell type as a result of epigenetic mechanisms and protein-protein interactions. We performed a meta-analysis integrating the differential expression (DE) analyses of all publicly available transcriptomic datasets, both in human and mouse, comparing trisomic and euploid transcriptomes from different sources. We integrated all these data in a "DS network". We found that genome wide deregulation as a consequence of trisomy 21 is not arbitrary, but involves deregulation of specific molecular cascades in which both HSA21 genes and HSA21 interactors are more consistently deregulated compared to other genes. In fact, gene deregulation happens in "clusters", so that groups from 2 to 13 genes are found consistently deregulated. Most of these events of "co-deregulation" involve genes belonging to the same GO category, and genes associated with the same disease class. The most consistent changes are enriched in interferon related categories and neutrophil activation, reinforcing the concept that DS is an inflammatory disease. Our results also suggest that the impact of the trisomy might diverge in each tissue due to the different gene set deregulation, even though the triplicated genes are the same. Our original method to integrate transcriptomic data confirmed not only the importance of known genes, such as SOD1, but also detected new ones that could be extremely useful for generating or confirming hypotheses and supporting new putative therapeutic candidates. We created "metaDEA" an R package that uses our method to integrate every kind of transcriptomic data and therefore could be used with other complex disorders, such as cancer. We also created a user-friendly web application to query Ensembl gene IDs and retrieve all the information of their differential expression across the datasets.

An improvement in skeletal muscle mitochondrial capacity with short-term aerobic training is associated with changes in Tribbles 1 expression

Exercise training and physical activity are known to be associated with high mitochondrial content and oxidative capacity in skeletal muscle. Metabolic diseases including obesity and insulin resistance are associated with low mitochondrial capacity in skeletal muscle. Certain transcriptional factors such as PGC-1α are known to mediate the exercise response; however, the precise molecular mechanisms involved in the adaptation to exercise are not completely understood. We performed multiple measurements of mitochondrial capacity both in vivo and ex vivo in lean or overweight individuals before and after an 18-day aerobic exercise training regimen. These results were compared to lean, active individuals. Aerobic training in these individuals resulted in a marked increase in mitochondrial oxidative respiratory capacity without an appreciable increase in mitochondrial content. These adaptations were associated with robust transcriptome changes. This work also identifies the Tribbles pseudokinase 1, TRIB1, as a potential mediator of the exercise response in human skeletal muscle.

Echinacea purpurea (L.) Moench treatment of monocytes promotes tonic interferon signaling, increased innate immunity gene expression and DNA repeat hypermethylated silencing of endogenous retroviral sequences

Background

Herbal remedies of Echinacea purpurea tinctures are widely used today to reduce common cold respiratory tract infections.

Methods

Transcriptome, epigenome and kinome profiling allowed a systems biology level characterisation of genomewide immunomodulatory effects of a standardized Echinacea purpurea (L.) Moench extract in THP1 monocytes.

Results

Gene expression and DNA methylation analysis revealed that Echinaforce® treatment triggers antiviral innate immunity pathways, involving tonic IFN signaling, activation of pattern recognition receptors, chemotaxis and immunometabolism. Furthermore, phosphopeptide based kinome activity profiling and pharmacological inhibitor experiments with filgotinib confirm a key role for Janus Kinase (JAK)-1 dependent gene expression changes in innate immune signaling. Finally, Echinaforce® treatment induces DNA hypermethylation at intergenic CpG, long/short interspersed nuclear DNA repeat elements (LINE, SINE) or long termininal DNA repeats (LTR). This changes transcription of flanking endogenous retroviral sequences (HERVs), involved in an evolutionary conserved (epi) genomic protective response against viral infections.

Conclusions

Altogether, our results suggest that Echinaforce® phytochemicals strengthen antiviral innate immunity through tonic IFN regulation of pattern recognition and chemokine gene expression and DNA repeat hypermethylated silencing of HERVs in monocytes. These results suggest that immunomodulation by Echinaforce® treatment holds promise to reduce symptoms and duration of infection episodes of common cold corona viruses (CoV), Severe Acute Respiratory Syndrome (SARS)-CoV, and new occurring strains such as SARS-CoV-2, with strongly impaired interferon (IFN) response and weak innate antiviral defense.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12906-021-03310-5.

Therapeutic B-cell depletion reverses progression of Alzheimer's disease

The function of B cells in Alzheimer's disease (AD) is not fully understood. While immunoglobulins that target amyloid beta (Aβ) may interfere with plaque formation and hence progression of the disease, B cells may contribute beyond merely producing immunoglobulins. Here we show that AD is associated with accumulation of activated B cells in circulation, and with infiltration of B cells into the brain parenchyma, resulting in immunoglobulin deposits around Aβ plaques. Using three different murine transgenic models, we provide counterintuitive evidence that the AD progression requires B cells. Despite expression of the AD-fostering transgenes, the loss of B cells alone is sufficient to reduce Aβ plaque burden and disease-associated microglia. It reverses behavioral and memory deficits and restores TGFβ+ microglia, respectively. Moreover, therapeutic depletion of B cells at the onset of the disease retards AD progression in mice, suggesting that targeting B cells may also benefit AD patients.

Elevated glucose represses lysosomal and mTOR-related genes in renal epithelial cells composed of progenitor CD133+ cells

Hyperglycemia is one of the major health concern in many parts of the world. One of the serious complications of high glucose levels is diabetic nephropathy. The preliminary microarray study performed on primary human renal tubular epithelial (hRTE) cells exposed to high glucose levels showed a significant downregulation of mTOR as well as its associated genes as well as lysosomal genes. Based on this preliminary data, the expression of various lysosomal genes as well as mTOR and its associated genes were analyzed in hRTE cells exposed to 5.5, 7.5, 11 and 16 mM glucose. The results validated the microarray analysis, which showed a significant decrease in the mRNA as well as protein expression of the selected genes as the concentration of glucose increased. Co-localization of lysosomal marker, LAMP1 with mTOR showed lower expression of mTOR as the glucose concentration increased, suggesting decrease in mTOR activity. Although the mechanism by which glucose affects the regulation of lysosomal genes is not well known, our results suggest that high levels of glucose may lead to decrease in mTOR expression causing the cells to enter an anabolic state with subsequent downregulation of lysosomal genes.

Cancer Cell Intrinsic and Immunologic Phenotypes Determine Clinical Outcomes in Basal-like Breast Cancer

PURPOSE

Basal-like breast cancer (BLBC) is a particularly aggressive intrinsic molecular subtype of breast cancer that lacks targeted therapies. There is also no clinically useful test to risk stratify patients with BLBC. We hypothesized that a transcriptome-based phenotypic characterization of BLBC tumors and their microenvironments may overcome these challenges.

EXPERIMENTAL DESIGN

We conducted a retrospective correlative genomic sequencing study using a matched pairs design with validation in five independent cohorts. The study was conducted on a large population-based prospective cohort of the major molecular subtypes of breast cancer conducted in the greater Seattle-Puget Sound metropolitan area. Cases consisted of women 20-69 years of age first diagnosed with invasive breast cancer identified through the population-based Surveillance Epidemiology and End Results program. Patients for this analysis (n = 949) were identified from the 1,408 patients with stage I-III triple-negative breast cancer [estrogen receptor-negative (ER^-), progesterone receptor-negative (PR^-), HER2^-]. Of the 949 women, 248 developed a recurrence after their initial diagnosis. A matched set of 67 recurrent and nonrecurrent BLBC tumors was subjected to transcriptome sequencing. Through RNA sequencing of the matched sets of recurrent and nonrecurrent BLBC tumors, we aimed to identify prognostic phenotypes.To identify nonredundant and uncorrelated prognostic genes, we used an ensemble of variable selection algorithms, which resulted in a ranking of genes on the basis of their expected utility in classification. Using leave-one-out cross-validation, we trained a random forest classifier on the basis of the top 21 genes (BRAVO-DX). Validations were performed in five independent triple-negative or BLBC cohorts, and biomarker robustness and transferability were demonstrated by employing real-time PCR.

RESULTS

We found that cancer cell intrinsic and immunologic phenotypes are independent predictors of recurrence. By simultaneously interrogating the tumor and its microenvironment, we developed a compound risk model that stratified patients into low-, medium-, and high-risk groups, with a 14%/56%/74% chance of recurrence, respectively. Biologically, the primary tumors of patients who developed a recurrence had increased growth factor signaling and stem-like features, while nonrecurrent tumors showed high lymphocyte infiltration with clonal expansion of T and B cells, as well as antitumor polarization of macrophages. We validated our model in five independent cohorts, including three large cohorts, where BRAVO-DX was highly informative in identifying patients with disease recurrence [HR, 6.79 (95% confidence interval (CI), 1.89-24.37); HR, 3.45 (95% CI, 2.41-4.93); and HR, 1.69 (95% CI, 1.17-2.46)]. A smaller gene set focused on the tumor immunophenotype, BRAVO-IMMUNE, was highly prognostic in all five cohorts.

CONCLUSIONS

Together, these results indicate that phenotypic characteristics of BLBCs and their microenvironment are associated with recurrence-free survival and demonstrate the utility of intrinsic and extrinsic phenotypes as independent prognostic biomarkers in BLBC. Pending further evaluation and validation, our prognostic model has the potential to inform clinical decision-making for patients with BLBC as it identifies those at high risk of rapidly progressing on standard chemotherapy, as well as those who may benefit from alternative first-line therapies.

Network Analysis Reveals Proteins Associated with Aortic Dilatation in Mucopolysaccharidoses

Mucopolysaccharidoses are caused by a deficiency of enzymes involved in the degradation of glycosaminoglycans. Heart diseases are a significant cause of morbidity and mortality in MPS patients, even in conditions in which enzyme replacement therapy is available. In this sense, cardiovascular manifestations, such as heart hypertrophy, cardiac function reduction, increased left ventricular chamber, and aortic dilatation, are among the most frequent. However, the downstream events which influence the heart dilatation process are unclear. Here, we employed systems biology tools together with transcriptomic data to investigate new elements that may be involved in aortic dilatation in Mucopolysaccharidoses syndrome. We identified candidate genes involved in biological processes related to inflammatory responses, deposition of collagen, and lipid accumulation in the cardiovascular system that may be involved in aortic dilatation in the Mucopolysaccharidoses I and VII. Furthermore, we investigated the molecular mechanisms of losartan treatment in Mucopolysaccharidoses I mice to underscore how this drug acts to prevent aortic dilation. Our data indicate that the association between the TGF-b signaling pathway, Fos, and Col1a1 proteins can play an essential role in aortic dilation's pathophysiology and its subsequent improvement by losartan treatment.

Identification of Crucial Genes and Pathways Associated with Atherosclerotic Plaque in Diabetic Patients

Background

Patients with diabetes have more calcification in atherosclerotic plaque and a higher occurrence of secondary cardiovascular events than patients without diabetes. The objective of this study was to identify crucial genes involved in the development of diabetic atherosclerotic plaque using a bioinformatics approach.

Methods

Microarray dataset GSE118481 was downloaded from the Gene Expression Omnibus (GEO) database; the dataset included 6 patients with diabetic atherosclerotic plaque (DBT) and 6 nondiabetic patients with atherosclerotic plaque (Ctrl). Differentially expressed genes (DEG) between the DBT and Ctrl groups were identified and then subjected to functional enrichment analysis. Based on the enriched pathways of DEGs, diabetic atherosclerotic plaque-related pathways were screened using the comparative toxicogenomics database (CTD). We then constructed a protein–protein interaction (PPI) network and transcription factor (TF)–miRNA–mRNA network.

Results

A total of 243 DEGs were obtained in the DBT group compared with the Ctrl group, including 85 up-regulated and 158 down-regulated DEGs. Functional enrichment analysis showed that up-regulated DEGs were mainly enriched in isoprenoid metabolic process, DNA-binding TF activity, and response to virus. Additionally, DEGs participating in the toll-like receptor signaling pathway were closely related to diabetes, carotid stenosis, and insulin resistance. The TF–miRNA–mRNA network showed that toll-like receptor 4 (TLR4), BCL2-like 11 (BCL2L11), and glutamate-cysteine ligase catalytic subunit (GCLC) were hub genes. Furthermore, TLR4 was regulated by TF signal transducer and activator of transcription 6 (STAT6); BCL2L11 was targeted by hsa-miR-24-3p; and GCLC was regulated by nuclear factor, erythroid 2 like 2 (NFE2L2).

Conclusion

Identification of hub genes and pathways increased our understanding of the molecular mechanisms underlying the atherosclerotic plaque in patients with or without diabetes. These crucial genes (TLR4, BC2L11, and GCLC) might function as molecular biomarkers for diabetic atherosclerotic plaque.

Network analysis of Down syndrome and SARS-CoV-2 identifies risk and protective factors for COVID-19

SARS-CoV-2 infection has spread uncontrollably worldwide while it remains unknown how vulnerable populations, such as Down syndrome (DS) individuals are affected by the COVID-19 pandemic. Individuals with DS have more risk of infections with respiratory complications and present signs of auto-inflammation. They also present with multiple comorbidities that are associated with poorer COVID-19 prognosis in the general population. All this might place DS individuals at higher risk of SARS-CoV-2 infection or poorer clinical outcomes. In order to get insight into the interplay between DS genes and SARS-cov2 infection and pathogenesis we identified the genes associated with the molecular pathways involved in COVID-19 and the host proteins interacting with viral proteins from SARS-CoV-2. We then analyzed the overlaps of these genes with HSA21 genes, HSA21 interactors and other genes consistently differentially expressed in DS (using public transcriptomic datasets) and created a DS-SARS-CoV-2 network. We detected COVID-19 protective and risk factors among HSA21 genes and interactors and/or DS deregulated genes that might affect the susceptibility of individuals with DS both at the infection stage and in the progression to acute respiratory distress syndrome. Our analysis suggests that at the infection stage DS individuals might be more susceptible to infection due to triplication of TMPRSS2, that primes the viral S protein for entry in the host cells. However, as the anti-viral interferon I signaling is also upregulated in DS, this might increase the initial anti-viral response, inhibiting viral genome release, viral replication and viral assembly. In the second pro-inflammatory immunopathogenic phase of the infection, the prognosis for DS patients might worsen due to upregulation of inflammatory genes that might favor the typical cytokine storm of COVID-19. We also detected strong downregulation of the NLRP3 gene, critical for maintenance of homeostasis against pathogenic infections, possibly leading to bacterial infection complications.

Nuclear IL-33 restrains the early conversion of fibroblasts to an extracellular matrix-secreting phenotype

Interleukin (IL)-33 is a cytokine that appears to mediate fibrosis by signaling via its receptor ST2 (IL-33R/IL1RL1). It is also, however, a protein that after synthesis is sorted to the cell nucleus, where it appears to affect chromatin folding. Here we describe a novel role for nuclear IL-33 in regulating the fibroblast phenotype in murine kidney fibrosis driven by unilateral ureteral obstruction. Transcriptional profiling of IL-33-deficient kidneys 24 h after ligation revealed enhanced expression of fibrogenic genes and enrichment of gene sets involved in extracellular matrix formation and remodeling. These changes relied on intracellular effects of IL-33, because they were not reproduced by treatment with a neutralizing antibody to IL-33 that prevents IL-33R/ST2L receptor signaling nor were they observed in IL-33R/ST2-deficient kidneys. To further explore the intracellular function of IL-33, we established transcription profiles of human fibroblasts, observing that knockdown of IL-33 skewed the transcription profile from an inflammatory towards a myofibroblast phenotype, reflected in higher levels of COL3A1, COL5A1 and transgelin protein, as well as lower expression levels of IL6, CXCL8, CLL7 and CCL8. In conclusion, our findings suggest that nuclear IL-33 in fibroblasts dampens the initial profibrotic response until persistent stimuli, as enforced by UUO, can override this protective mechanism.

Identification of Key Pathways and Genes in Obesity Using Bioinformatics Analysis and Molecular Docking Studies

Obesity is an excess accumulation of body fat. Its progression rate has remained high in recent years. Therefore, the aim of this study was to diagnose important differentially expressed genes (DEGs) associated in its development, which may be used as novel biomarkers or potential therapeutic targets for obesity. The gene expression profile of E-MTAB-6728 was downloaded from the database. After screening DEGs in each ArrayExpress dataset, we further used the robust rank aggregation method to diagnose 876 significant DEGs including 438 up regulated and 438 down regulated genes. Functional enrichment analysis was performed. These DEGs were shown to be significantly enriched in different obesity related pathways and GO functions. Then protein-protein interaction network, target genes - miRNA regulatory network and target genes - TF regulatory network were constructed and analyzed. The module analysis was performed based on the whole PPI network. We finally filtered out STAT3, CORO1C, SERPINH1, MVP, ITGB5, PCM1, SIRT1, EEF1G, PTEN and RPS2 hub genes. Hub genes were validated by ICH analysis, receiver operating curve (ROC) analysis and RT-PCR. Finally a molecular docking study was performed to find small drug molecules. The robust DEGs linked with the development of obesity were screened through the expression profile, and integrated bioinformatics analysis was conducted. Our study provides reliable molecular biomarkers for screening and diagnosis, prognosis as well as novel therapeutic targets for obesity.

Piwil1 Regulates Glioma Stem Cell Maintenance and Glioblastoma Progression

Piwi proteins are a subfamily of Argonaute proteins that maintain germ cells in eukaryotes. However, the role of their human homologs in cancer stem cells, and more broadly in cancer, is poorly understood. Here, we report that Piwi-like family members are overexpressed in glioblastoma (GBM), with Piwil1 (Hiwi) most frequently overexpressed (88%). Piwil1 is enriched in glioma stem-like cells (GSCs) to maintain self-renewal. Silencing Piwil1 in GSCs leads to global changes in gene expression resulting in cell-cycle arrest, senescence, or apoptosis. Piwil1 knockdown increases expression of the transcriptional co-regulator BTG2 and the E3-ubiquitin ligase FBXW7, leading to reduced c-Myc expression, as well as loss of expression of stem cell factors Olig2 and Nestin. Piwil1 regulates mRNA stability of BTG2, FBXW7, and CDKN1B. In animal models of GBM, Piwil1 knockdown suppresses tumor growth and promotes mouse survival. These findings support a role of Piwil1 in GSC maintenance and glioblastoma progression.

Huang et al. find that Piwil1 protein is overexpressed in glioblastoma and glioma stem cells (GSCs). Piwil1 maintains GSC self-renewal and survival by regulating gene expression. Targeting Piwil1 extends survival in mouse models of glioblastoma. Piwil1 represents a therapeutic vulnerability.

Multi-Approach Bioinformatics Analysis of Curated Omics Data Provides a Gene Expression Panorama for Multiple Cancer Types

Studies describing the expression patterns and biomarkers for the tumoral process increase in number every year. The availability of new datasets, although essential, also creates a confusing landscape where common or critical mechanisms are obscured amidst the divergent and heterogeneous nature of such results. In this work, we manually curated the Gene Expression Omnibus using rigorous filtering criteria to select the most homogeneous and highest quality microarray and RNA-seq datasets from multiple types of cancer. By applying systems biology approaches, combined with machine learning analysis, we investigated possible frequently deregulated molecular mechanisms underlying the tumoral process. Our multi-approach analysis of 99 curated datasets, composed of 5,406 samples, revealed 47 differentially expressed genes in all analyzed cancer types, which were all in agreement with the validation using TCGA data. Results suggest that the tumoral process is more related to the overexpression of core deregulated machinery than the underexpression of a given gene set. Additionally, we identified gene expression similarities between different cancer types not described before and performed an overall survival analysis using 20 cancer types. Finally, we were able to suggest a core regulatory mechanism that could be frequently deregulated.

Activating transcription factor-2 (ATF2) is a key determinant of resistance to endocrine treatment in an in vitro model of breast cancer

BACKGROUND

Activating transcription factor-2 (ATF2), a member of the leucine zipper family of DNA binding proteins, has been implicated as a tumour suppressor in breast cancer. However, its exact role in breast cancer endocrine resistance is still unclear. We have previously shown that silencing of ATF2 leads to a loss in the growth-inhibitory effects of tamoxifen in the oestrogen receptor (ER)-positive, tamoxifen-sensitive MCF7 cell line and highlighted that this multi-faceted transcription factor is key to the effects of tamoxifen in an endocrine sensitive model. In this work, we explored further the in vitro role of ATF2 in defining the resistance to endocrine treatment.

MATERIALS AND METHODS

We knocked down ATF2 in TAMR, LCC2 and LCC9 tamoxifen-resistant breast cancer cell lines as well as the parental tamoxifen sensitive MCF7 cell line and investigated the effects on growth, colony formation and cell migration. We also performed a microarray gene expression profiling (Illumina Human HT12_v4) to explore alterations in gene expression between MCF7 and TAMRs after ATF2 silencing and confirmed gene expression changes by quantitative RT-PCR.

RESULTS

By silencing ATF2, we observed a significant growth reduction of TAMR, LCC2 and LCC9 with no such effect observed with the parental MCF7 cells. ATF2 silencing was also associated with a significant inhibition of TAMR, LCC2 and LCC9 cell migration and colony formation. Interestingly, knockdown of ATF2 enhanced the levels of ER and ER-regulated genes, TFF1, GREB1, NCOA3 and PGR, in TAMR cells both at RNA and protein levels. Microarray gene expression identified a number of genes known to mediate tamoxifen resistance, to be differentially regulated by ATF2 in TAMR in relation to the parental MCF7 cells. Moreover, differential pathway analysis confirmed enhanced ER activity after ATF2 knockdown in TAMR cells.

CONCLUSION

These data demonstrate that ATF2 silencing may overcome endocrine resistance and highlights further the dual role of this transcription factor that can mediate endocrine sensitivity and resistance by modulating ER expression and activity.

Gene Expression in Spontaneous Experimental Autoimmune Encephalomyelitis Is Linked to Human Multiple Sclerosis Risk Genes

Recent genome-wide association studies have identified over 230 genetic risk loci for multiple sclerosis. Current experimental autoimmune encephalomyelitis (EAE) models requiring active induction of disease may not be optimally suited for the characterization of the function of these genes. We have thus used gene expression profiling to study whether spontaneous opticospinal EAE (OSE) or MOG-induced EAE mirrors the genetic contribution to the pathogenesis of multiple sclerosis more faithfully. To this end, we compared gene expression in OSE and MOG EAE models and analyzed the relationship of both models to human multiple sclerosis risk genes and T helper cell biology. We observed stronger gene expression changes and an involvement of more pathways of the adaptive immune system in OSE than MOG EAE. Furthermore, we demonstrated a more extensive enrichment of human MS risk genes among transcripts differentially expressed in OSE than was the case for MOG EAE. Transcripts differentially expressed only in diseased OSE mice but not in MOG EAE were significantly enriched for T helper cell-specific transcripts. These transcripts are part of immune-regulatory pathways. The activation of the adaptive immune system and the enrichment of both human multiple sclerosis risk genes and T helper cell-specific transcripts were also observed in OSE mice showing only mild disease signs. These expression changes may, therefore, be indicative of processes at disease onset. In summary, more human multiple sclerosis risk genes were differentially expressed in OSE than was observed for MOG EAE, especially in T_H1 cells. When studying the functional role of multiple sclerosis risk genes and pathways during disease onset and their interactions with the environment, spontaneous OSE may thus show advantages over MOG-induced EAE.

Glioma-derived IL-33 orchestrates an inflammatory brain tumor microenvironment that accelerates glioma progression

Despite a deeper molecular understanding, human glioblastoma remains one of the most treatment refractory and fatal cancers. It is known that the presence of macrophages and microglia impact glioblastoma tumorigenesis and prevent durable response. Herein we identify the dual function cytokine IL-33 as an orchestrator of the glioblastoma microenvironment that contributes to tumorigenesis. We find that IL-33 expression in a large subset of human glioma specimens and murine models correlates with increased tumor-associated macrophages/monocytes/microglia. In addition, nuclear and secreted functions of IL-33 regulate chemokines that collectively recruit and activate circulating and resident innate immune cells creating a pro-tumorigenic environment. Conversely, loss of nuclear IL-33 cripples recruitment, dramatically suppresses glioma growth, and increases survival. Our data supports the paradigm that recruitment and activation of immune cells, when instructed appropriately, offer a therapeutic strategy that switches the focus from the cancer cell alone to one that includes the normal host environment.

Cell Lineage-Based Stratification for Glioblastoma

Glioblastoma, the predominant adult malignant brain tumor, has been computationally classified into molecular subtypes whose functional relevance remains to be comprehensively established. Tumors from genetically engineered glioblastoma mouse models initiated by identical driver mutations in distinct cells of origin portray unique transcriptional profiles reflective of their respective lineage. Here, we identify corresponding transcriptional profiles in human glioblastoma and describe patient-derived xenografts with species-conserved subtype-discriminating functional properties. The oligodendrocyte lineage-associated glioblastoma subtype requires functional ERBB3 and harbors unique therapeutic sensitivities. These results highlight the importance of cell lineage in glioblastoma independent of driver mutations and provide a methodology for functional glioblastoma classification for future clinical investigations.

Co-expression analysis reveals interpretable gene modules controlled by trans-acting genetic variants

Understanding the causal processes that contribute to disease onset and progression is essential for developing novel therapies. Although trans-acting expression quantitative trait loci (trans-eQTLs) can directly reveal cellular processes modulated by disease variants, detecting trans-eQTLs remains challenging due to their small effect sizes. Here, we analysed gene expression and genotype data from six blood cell types from 226 to 710 individuals. We used co-expression modules inferred from gene expression data with five methods as traits in trans-eQTL analysis to limit multiple testing and improve interpretability. In addition to replicating three established associations, we discovered a novel trans-eQTL near SLC39A8 regulating a module of metallothionein genes in LPS-stimulated monocytes. Interestingly, this effect was mediated by a transient cis-eQTL present only in early LPS response and lost before the trans effect appeared. Our analyses highlight how co-expression combined with functional enrichment analysis improves the identification and prioritisation of trans-eQTLs when applied to emerging cell-type-specific datasets.

A relational database to identify differentially expressed genes in the endometrium and endometriosis lesions

Endometriosis is a common inflammatory estrogen-dependent gynecological disorder, associated with pelvic pain and reduced fertility in women. Several aspects of this disorder and its cellular and molecular etiology remain unresolved. We have analyzed the global gene expression patterns in the endometrium, peritoneum and in endometriosis lesions of endometriosis patients and in the endometrium and peritoneum of healthy women. In this report, we present the EndometDB, an interactive web-based user interface for browsing the gene expression database of collected samples without the need for computational skills. The EndometDB incorporates the expression data from 115 patients and 53 controls, with over 24000 genes and clinical features, such as their age, disease stages, hormonal medication, menstrual cycle phase, and the different endometriosis lesion types. Using the web-tool, the end-user can easily generate various plot outputs and projections, including boxplots, and heatmaps and the generated outputs can be downloaded in pdf-format.

Availability and implementationThe web-based user interface is implemented using HTML5, JavaScript, CSS, Plotly and R. It is freely available from https://endometdb.utu.fi/.

Measurement(s)	RNA • differential expression analysis data • endometriosis
Technology Type(s)	Microarray Analysis • digital curation
Factor Type(s)	age • disease stage • menstrual cycle phase • hormonal medication • endometriosis lesion type • endometrium
Sample Characteristic - Organism	Homo sapiens

Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12800642

Immune system and angiogenesis-related potential surrogate biomarkers of response to everolimus-based treatment in hormone receptor-positive breast cancer: an exploratory study

Purpose

mTOR inhibitor everolimus is used for hormone receptor-positive (HR+)/HER2-negative metastatic breast cancer (mBC). No reliable predictive biomarker of response is available. Following evidences from other solid tumors, we aimed to assess the association between treatment-associated immune system features and everolimus activity.

Methods

We retrospectively explored a correlation with the therapeutic activity of everolimus and tumor-associated immune pathways with ingenuity pathway analysis (IPA), neutrophil-to-lymphocyte ratio (NLR), circulating lymphocytes, and endothelial cells (CECs) in 3 different HR+ mBC studies, including the BALLET phase IIIb study.

Results

The circulating levels of CD3⁺/CD8⁺, CD3⁺/CD4⁺, and overall T lymphocytes were higher in responders versus non-responders at baseline (p = 0.017, p < 0.001, p = 0.034) and after treatment (p = 0.01, p = 0.003, p = 0.023). Reduced CECs, a tumor neoangiogenesis marker, were observed in responders after treatment (p < 0.001). Patients with low NLR (≤ 4.4) showed a better progression-free survival compared to patients with high NLR (> 4.4) (p = 0.01). IPA showed that the majority of immunity-related genes were found upregulated in responders compared to non-responders before treatment, but not after.

Conclusions

Lymphocytes subpopulations, CECs and NLR could be interesting biomarkers predictive of response to everolimus-based regimens, potentially useful in daily clinical practice to select/monitor everolimus-based treatment in mBC. Further studies to confirm such hypotheses are warranted.