iCluF: an unsupervised iterative cluster-fusion method for patient stratification using multiomics data.

Motivation: Patient stratification is crucial for the effective treatment or management of heterogeneous diseases, including cancers. Multiomic technologies facilitate molecular characterization of human diseases; however, the complexity of data warrants the need for the development of robust data integration tools for patient stratification using machine-learning approaches. Results: iCluF iteratively integrates three types of multiomic data (mRNA, miRNA, and DNA methylation) using pairwise patient similarity matrices built from each omic data. The intermediate omic-specific neighborhood matrices implement iterative matrix fusion and message passing among the similarity matrices to derive a final integrated matrix representing all the omics profiles of a patient, which is used to further cluster patients into subtypes. iCluF outperforms other methods with significant differences in the survival profiles of 8581 patients belonging to 30 different cancers in TCGA. iCluF also predicted the four intrinsic subtypes of Breast Invasive Carcinomas with adjusted rand index and Fowlkes-Mallows scores of 0.72 and 0.83, respectively. The Gini importance score showed that methylation features were the primary decisive players, followed by mRNA and miRNA to identify disease subtypes. iCluF can be applied to stratify patients with any disease containing multiomic datasets. Availability and implementation: Source code and datasets are available at https://github.com/GudaLab/iCluF_core.

Oocyte quality is enhanced by hypoglycosylated FSH through increased cell-to-cell interaction during mouse follicle development.

Macroheterogeneity in follicle-stimulating hormone (FSH) ß-subunit N-glycosylation results in distinct FSH glycoforms. Hypoglycosylated FSH21 is the abundant and more bioactive form in pituitaries of females under 35 years of age, whereas fully glycosylated FSH24 is less bioactive and increases with age. To investigate whether the shift in FSH glycoform abundance contributes to the age-dependent decline in oocyte quality, the direct effects of FSH glycoforms on folliculogenesis and oocyte quality were determined using an encapsulated in vitro mouse follicle growth system. Long-term culture (10-12 days) with FSH21 (10 ng/ml) enhanced follicle growth, estradiol secretion and oocyte quality compared with FSH24 (10 ng/ml) treatment. FSH21 enhanced establishment of transzonal projections, gap junctions and cell-to-cell communication within 24 h in culture. Transient inhibition of FSH21-mediated bidirectional communication abrogated the positive effects of FSH21 on follicle growth, estradiol secretion and oocyte quality. Our data indicate that FSH21 promotes folliculogenesis and oocyte quality in vitro by increasing cell-to-cell communication early in folliculogenesis, and that the shift in in vivo abundance from FSH21 to FSH24 with reproductive aging may contribute to the age-dependent decline in oocyte quality.

Novel RNA-Seq Signatures Post-Methamphetamine and Oxycodone Use in a Model of HIV-Associated Neurocognitive Disorders.

In the 21st century, the effects of HIV-associated neurocognitive disorders (HAND) have been significantly reduced in individuals due to the development of antiretroviral therapies (ARTs). However, the growing epidemic of polysubstance use (PSU) has led to concern for the effects of PSU on HIV-seropositive individuals. To effectively treat individuals affected by HAND, it is critical to understand the biological mechanisms affected by PSU, including the identification of novel markers. To fill this important knowledge gap, we used an in vivo HIV-1 Transgenic (HIV-1 Tg) animal model to investigate the effects of the combined use of chronic methamphetamine (METH) and oxycodone (oxy). A RNA-Seq analysis on the striatum-a brain region that is primarily targeted by both HIV and drugs of abuse-identified key differentially expressed markers post-METH and oxy exposure. Furthermore, ClueGO analysis and Ingenuity Pathway Analysis (IPA) revealed crucial molecular and biological functions associated with ATP-activated adenosine receptors, neuropeptide hormone activity, and the oxytocin signaling pathway to be altered between the different treatment groups. The current study further reveals the harmful effects of chronic PSU and HIV infection that can subsequently impact neurological outcomes in polysubstance users with HAND.

Critical contributions of protein cargos to the functions of macrophage-derived extracellular vesicles.

BACKGROUND: Macrophages are highly plastic innate immune cells that play key roles in host defense, tissue repair, and homeostasis maintenance. In response to divergent stimuli, macrophages rapidly alter their functions and manifest a wide polarization spectrum with two extremes: M1 or classical activation and M2 or alternative activation. Extracellular vesicles (EVs) secreted from differentially activated macrophages have been shown to have diverse functions, which are primarily attributed to their microRNA cargos. The role of protein cargos in these EVs remains largely unexplored. Therefore, in this study, we focused on the protein cargos in macrophage-derived EVs. RESULTS: Naïve murine bone marrow-derived macrophages were treated with lipopolysaccharide or interlukin-4 to induce M1 or M2 macrophages, respectively. The proteins of EVs and their parental macrophages were subjected to quantitative proteomics analyses, followed by bioinformatic analyses. The enriched proteins of M1-EVs were involved in proinflammatory pathways and those of M2-EVs were associated with immunomodulation and tissue remodeling. The signature proteins of EVs shared a limited subset of the proteins of their respective progenitor macrophages, but they covered many of the typical pathways and functions of their parental cells, suggesting their respective M1-like and M2-like phenotypes and functions. Experimental examination validated that protein cargos in M1- or M2-EVs induced M1 or M2 polarization, respectively. More importantly, proteins in M1-EVs promoted viability, proliferation, and activation of T lymphocytes, whereas proteins in M2-EVs potently protected the tight junction structure and barrier integrity of epithelial cells from disruption. Intravenous administration of M2-EVs in colitis mice led to their accumulation in the colon, alleviation of colonic inflammation, promotion of M2 macrophage polarization, and improvement of gut barrier functions. Protein cargos in M2-EVs played a key role in their protective function in colitis. CONCLUSION: This study has yielded a comprehensive unbiased dataset of protein cargos in macrophage-derived EVs, provided a systemic view of their potential functions, and highlighted the important engagement of protein cargos in the pathophysiological functions of these EVs.

Evaluation of Five Mammalian Models for Human Disease Research Using Genomic and Bioinformatic Approaches.

The suitability of an animal model for use in studying human diseases relies heavily on the similarities between the two species at the genetic, epigenetic, and metabolic levels. However, there is a lack of consistent data from different animal models at each level to evaluate this suitability. With the availability of genome sequences for many mammalian species, it is now possible to compare animal models based on genomic similarities. Herein, we compare the coding sequences (CDSs) of five mammalian models, including rhesus macaque, marmoset, pig, mouse, and rat models, with human coding sequences. We identified 10,316 conserved CDSs across the five organisms and the human genome based on sequence similarity. Mapping the human-disease-associated single-nucleotide polymorphisms (SNPs) from these conserved CDSs in each species has identified species-specific associations with various human diseases. While associations with a disease such as colon cancer were prevalent in multiple model species, the rhesus macaque showed the most model-specific human disease associations. Based on the percentage of disease-associated SNP-containing genes, marmoset models are well suited to study many human ailments, including behavioral and cardiovascular diseases. This study demonstrates a genomic similarity evaluation of five animal models against human CDSs that could help investigators select a suitable animal model for studying their target disease.

Microbiome diversity in African American, European American, and Egyptian colorectal cancer patients.

Purpose: Although there is an established role for microbiome dysbiosis in the pathobiology of colorectal cancer (CRC), CRC patients of various race/ethnicities demonstrate distinct clinical behaviors. Thus, we investigated microbiome dysbiosis in Egyptian, African American (AA), and European American (EA) CRC patients. Patients and methods: CRCs and their corresponding normal tissues from Egyptian (n = 17) patients of the Alexandria University Hospital, Egypt, and tissues from AA (n = 18) and EA (n = 19) patients at the University of Alabama at Birmingham were collected. DNA was isolated from frozen tissues, and the microbiome composition was analyzed by 16S rRNA sequencing. Differential microbial abundance, diversity, and metabolic pathways were identified using linear discriminant analysis (LDA) effect size analyses. Additionally, we compared these profiles with our previously published microbiome data derived from Kenyan CRC patients. Results: Differential microbiome analysis of CRCs across all racial/ethnic groups showed dysbiosis. There were high abundances of Herbaspirillum and Staphylococcus in CRCs of Egyptians, Leptotrichia in CRCs of AAs, Flexspiria and Streptococcus in CRCs of EAs, and Akkermansia muciniphila and Prevotella nigrescens in CRCs of Kenyans (LDA score >4, adj. p-value <0.05). Functional analyses showed distinct microbial metabolic pathways in CRCs compared to normal tissues within the racial/ethnic groups. Egyptian CRCs, compared to normal tissues, showed lower l-methionine biosynthesis and higher galactose degradation pathways. Conclusions: Our findings showed altered mucosa-associated microbiome profiles of CRCs and their metabolic pathways across racial/ethnic groups. These findings provide a basis for future studies to link racial/ethnic microbiome differences with distinct clinical behaviors in CRC.

The mutational landscape of a US Midwestern breast cancer cohort reveals subtype-specific cancer drivers and prognostic markers.

BACKGROUND: Female breast cancer remains the second leading cause of cancer-related death in the USA. The heterogeneity in the tumor morphology across the cohort and within patients can lead to unpredictable therapy resistance, metastasis, and clinical outcome. Hence, supplementing classic pathological markers with intrinsic tumor molecular markers can help identify novel molecular subtypes and the discovery of actionable biomarkers. METHODS: We conducted a large multi-institutional genomic analysis of paired normal and tumor samples from breast cancer patients to profile the complex genomic architecture of breast tumors. Long-term patient follow-up, therapeutic regimens, and treatment response for this cohort are documented using the Breast Cancer Collaborative Registry. The majority of the patients in this study were at tumor stage 1 (51.4%) and stage 2 (36.3%) at the time of diagnosis. Whole-exome sequencing data from 554 patients were used for mutational profiling and identifying cancer drivers. RESULTS: We identified 54 tumors having at least 1000 mutations and 185 tumors with less than 100 mutations. Tumor mutational burden varied across the classified subtypes, and the top ten mutated genes include MUC4, MUC16, PIK3CA, TTN, TP53, NBPF10, NBPF1, CDC27, AHNAK2, and MUC2. Patients were classified based on seven biological and tumor-specific parameters, including grade, stage, hormone receptor status, histological subtype, Ki67 expression, lymph node status, race, and mutational profiles compared across different subtypes. Mutual exclusion of mutations in PIK3CA and TP53 was pronounced across different tumor grades. Cancer drivers specific to each subtype include TP53, PIK3CA, CDC27, CDH1, STK39, CBFB, MAP3K1, and GATA3, and mutations associated with patient survival were identified in our cohort. CONCLUSIONS: This extensive study has revealed tumor burden, driver genes, co-occurrence, mutual exclusivity, and survival effects of mutations on a US Midwestern breast cancer cohort, paving the way for developing personalized therapeutic strategies.

RNA-seq analysis identifies age-dependent changes in expression of mRNAs - encoding N-glycosylation pathway enzymes in mouse gonadotropes.

Follicle-stimulating hormone (FSH) is a glycoprotein that is assembled as a heterodimer of α/ß subunits in gonadotropes. Each subunit contains two N-glycan chains. Our previous in vivo genetic studies identified that at least one N-glycan chain must be present on the FSHß subunit for efficient FSH dimer assembly and secretion. Moreover, macroheterogeneity observed uniquely on human FSHß results in ratiometric changes in age-specific FSH glycoforms, particularly during menopausal transition. Despite the recognition of many prominent roles of sugars on FSH including dimer assembly and secretion, serum half-life, receptor binding and signal transduction, the N-glycosylation machinery in gonadotropes has never been defined. Here, we used a mouse model in which gonadotropes are GFP-labeled in vivo and achieved rapid purification of GFP+ gonadotropes from pituitaries of female mice at reproductively young, middle, and old ages. We identified by RNA-seq analysis 52 mRNAs encoding N-glycosylation pathway enzymes expressed in 3- and 8-10-month-old mouse gonadotropes. We hierarchically mapped and localized the enzymes to distinct subcellular organelles within the N-glycosylation biosynthetic pathway. Of the 52 mRNAs, we found 27 mRNAs are differentially expressed between the 3- and 8-10-month old mice. We subsequently selected 8 mRNAs which showed varying changes in expression for confirmation of abundance in vivo via qPCR analysis, using more expanded aging time points with distinct 8-month and 14-month age groups. Real time qPCR analysis indicated dynamic changes in expression of N-glycosylation pathway enzyme-encoding mRNAs across the life span. Notably, computational analysis predicted the promoters of genes encoding these 8 mRNAs contain multiple high probability binding sites for estrogen receptor-1 and progesterone receptor. Collectively, our studies define the N-glycome and identify age-specific dynamic changes in mRNAs encoding N-glycosylation pathway enzymes in mouse gonadotropes. Our studies suggest the age-related decline in ovarian steroids may regulate expression of N-glycosylation enzymes in mouse gonadotropes and explain the age-related N-glycosylation shift previously observed on human FSHß subunit in pituitaries of women.

Transcriptome profile changes in the jejunum of nonhuman primates exposed to supralethal dose of total- or partial-body radiation.

The risk of exposure of the general public or military personnel to high levels of ionizing radiation from nuclear weapons or radiological accidents is a dire national security matter. The development of advanced molecular biodosimetry methods, those that measure biological response, such as transcriptomics, to screen large populations of radiation-exposed victims is key to improving survival outcomes during radiological mass casualty scenarios. In this study, nonhuman primates were exposed to either 12.0 Gy cobalt-60 gamma (total-body irradiation, TBI) or X-ray (partial-body irradiation, PBI) 24 h after administration of a potential radiation medical countermeasure, gamma-tocotrienol (GT3). Changes in the jejunal transcriptomic profiles in GT3-treated and irradiated animals were compared to healthy controls to assess the extent of radiation damage. No major effect of GT3 on radiation-induced transcriptome at this radiation dose was identified. About 80% of the pathways with a known activation or repression state were commonly observed between both exposures. Several common pathways activated due to irradiation include FAK signaling, CREB signaling in the neurons, phagosome formation, and G-protein coupled signaling pathway. Sex-specific differences associated with excessive mortality among irradiated females were identified in this study, including Estrogen receptor signaling. Differential pathway activation was also identified across PBI and TBI, pointing towards altered molecular response for different degrees of bone marrow sparing and radiation doses. This study provides insight into radiation-induced changes in jejunal transcriptional profiles, supporting the investigation for the identification of biomarkers for radiation injury and countermeasure efficacy.

Molecular Subtyping and Survival Analysis of Osteosarcoma Reveals Prognostic Biomarkers and Key Canonical Pathways.

Osteosarcoma (OS) is a common bone malignancy in children and adolescents. Although histological subtyping followed by improved OS treatment regimens have helped achieve favorable outcomes, a lack of understanding of the molecular subtypes remains a challenge to characterize its genetic heterogeneity and subsequently to identify diagnostic and prognostic biomarkers for developing effective treatments. In the present study, global analysis of DNA methylation, and mRNA and miRNA gene expression in OS patient samples were correlated with their clinical characteristics. The mucin family of genes, MUC6, MUC12, and MUC4, were found to be highly mutated in the OS patients. Results revealed the enrichment of molecular pathways including Wnt signaling, Calcium signaling, and PI3K-Akt signaling in the OS tumors. Survival analyses showed that the expression levels of several genes such as RAMP1, CRIP1, CORT, CHST13, and DDX60L, miRNAs and lncRNAs were associated with survival of OS patients. Molecular subtyping using Cluster-Of-Clusters Analysis (COCA) for mRNA, lncRNA, and miRNA expression; DNA methylation; and mutation data from the TARGET dataset revealed two distinct molecular subtypes, each with a distinctive gene expression profile. Between the two subtypes, three upregulated genes, POP4, HEY1, CERKL, and seven downregulated genes, CEACAM1, ABLIM1, LTBP2, ISLR, LRRC32, PTPRF, and GPX3, associated with OS metastasis were found to be differentially regulated. Thus, the molecular subtyping results provide a strong basis for classification of OS patients that could be used to develop better prognostic treatment strategies.

Cell-free DNA in maternal blood and artificial intelligence: accurate prenatal detection of fetal congenital heart defects.

BACKGROUND: DNA cytosine nucleotide methylation (epigenomics and epigenetics) is an important mechanism for controlling gene expression in cardiac development. Combined artificial intelligence and whole-genome epigenomic analysis of circulating cell-free DNA in maternal blood has the potential for the detection of fetal congenital heart defects. OBJECTIVE: This study aimed to use genome-wide DNA cytosine methylation and artificial intelligence analyses of circulating cell-free DNA for the minimally invasive detection of fetal congenital heart defects. STUDY DESIGN: In this prospective study, whole-genome cytosine nucleotide methylation analysis was performed on circulating cell-free DNA using the Illumina Infinium MethylationEPIC BeadChip array. Multiple artificial intelligence approaches were evaluated for the detection of congenital hearts. The Ingenuity Pathway Analysis program was used to identify gene pathways that were epigenetically altered and important in congenital heart defect pathogenesis to further elucidate the pathogenesis of isolated congenital heart defects. RESULTS: There were 12 cases of isolated nonsyndromic congenital heart defects and 26 matched controls. A total of 5918 cytosine nucleotides involving 4976 genes had significantly altered methylation, that is, a P value of <.05 along with ≥5% whole-genome cytosine nucleotide methylation difference, in congenital heart defect cases vs controls. Artificial intelligence analysis of the methylation data achieved excellent congenital heart defect predictive accuracy (areas under the receiver operating characteristic curve, ≥0.92). For example, an artificial intelligence model using a combination of 5 whole-genome cytosine nucleotide markers achieved an area under the receiver operating characteristic curve of 0.97 (95% confidence interval, 0.87-1.0) with 98% sensitivity and 94% specificity. We found epigenetic changes in genes and gene pathways involved in the following important cardiac developmental processes: "cardiovascular system development and function," "cardiac hypertrophy," "congenital heart anomaly," and "cardiovascular disease." This lends biologic plausibility to our findings. CONCLUSION: This study reported the feasibility of minimally invasive detection of fetal congenital heart defect using artificial intelligence and DNA methylation analysis of circulating cell-free DNA for the prediction of fetal congenital heart defect. Furthermore, the findings supported an important role of epigenetic changes in congenital heart defect development.

A Review of Radiation-Induced Alterations of Multi-Omic Profiles, Radiation Injury Biomarkers, and Countermeasures.

Increasing utilization of nuclear power enhances the risks associated with industrial accidents, occupational hazards, and the threat of nuclear terrorism. Exposure to ionizing radiation interferes with genomic stability and gene expression resulting in the disruption of normal metabolic processes in cells and organs by inducing complex biological responses. Exposure to high-dose radiation causes acute radiation syndrome, which leads to hematopoietic, gastrointestinal, cerebrovascular, and many other organ-specific injuries. Altered genomic variations, gene expression, metabolite concentrations, and microbiota profiles in blood plasma or tissue samples reflect the whole-body radiation injuries. Hence, multi-omic profiles obtained from high-resolution omics platforms offer a holistic approach for identifying reliable biomarkers to predict the radiation injury of organs and tissues resulting from radiation exposures. In this review, we performed a literature search to systematically catalog the radiation-induced alterations from multi-omic studies and radiation countermeasures. We covered radiation-induced changes in the genomic, transcriptomic, proteomic, metabolomic, lipidomic, and microbiome profiles. Furthermore, we have covered promising multi-omic biomarkers, FDA-approved countermeasure drugs, and other radiation countermeasures that include radioprotectors and radiomitigators. This review presents an overview of radiation-induced alterations of multi-omics profiles and biomarkers, and associated radiation countermeasures.

Fusion gene recurrence in non-small cell lung cancers and its association with cigarette smoke exposure.

Background: Lung cancer remains the leading cause of cancer-related deaths in the US despite novel treatment protocols, with about 235,000 new cases and 131,000 deaths expected from this cancer in 2021 alone. Lung adenocarcinoma and squamous cell carcinoma, which are both subtypes of non-small cell lung cancer, account for most lung cancer cases, and comparing the molecular signatures in these two cancers can identify novel mechanisms that contribute to non-small cell lung cancer oncogenesis. Methods: We, in this study, performed a comprehensive gene fusion profiling of these cancers, which is understudied in lung cancers. Using an alignment-free fusion detection tool, 'ChimeRScope', we screened for gene fusions in lung adenocarcinoma and squamous cell carcinoma datasets from The Cancer Gene Atlas database. Fusion profiles in these two cancer subtypes were essentially different with minimal overlap. Results: Our analysis revealed a positive association of smoking to fusion frequency in lung adenocarcinoma but not in squamous cell carcinoma and identified several fusion genes that could be explored as markers associated with cigarette smoke exposure. We also identified differentially regulated pathways linked to E2F, G2M checkpoint, and MTORC1 signaling upregulated and P53 pathway downregulated in samples containing high fusions in lung adenocarcinoma. Our results indicate that downregulation of the P53 pathway leads to higher gene fusion formation in lung adenocarcinoma. Conclusions: This manuscript provides a strong rationale for investigating the molecular mechanisms of cigarette smoke-induced gene fusion formation associated with lung cancer. Novel recurrent fusions associated with cigarette smoke were identified in our study, which could further be investigated for patient stratification, personalized therapy, and therapeutic monitoring.

A signature of Prevotella copri and Faecalibacterium prausnitzii depletion, and a link with bacterial glutamate degradation in the Kenyan colorectal cancer patients.

Background: Colorectal cancer (CRC) is the fifth most diagnosed cancer in Sub-Saharan Africa. In Kenya, CRC incidence rates tripled from 1997 to 2017. In the Moi Teaching and Referral Hospital, Moi University, there has been an increase in CRC cases, notably for younger patients. A suggested pathobiology for this increase is gut microbiome dysbiosis. Since, for the Kenyan CRC patient population, microbiome studies are rare, there is a need for a better understanding of how microbiome dysbiosis influences CRC epidemiology in Kenya. In this single-center study, the focus was on profiling the gut microbiome of Kenyan CRC patients and healthy volunteers and evaluating associations between microbiome profiles and the age of CRC patients. Methods: The gut mucosa-associated microbiome of 18 CRC patients and 18 healthy controls were determined by 16S rRNA sequencing and analyzed for alpha and beta diversity, differential abundance, and microbial metabolic profiling. Results: Alpha diversity metrics showed no significant differences, but beta diversity metrics showed dissimilarities in the microbial communities between CRC patients and healthy controls. The most underrepresented species in the CRC group were Prevotella copri (P. copri) and Faecalibacterium prausnitzii (F. prausnitzii), although Bacteroides fragilis (B. fragilis) and Prevotella nigrescens were overrepresented (linear discriminant analysis, LDA score >2, P<0.05). Also, for CRC patients, significant metagenomic functional alterations were evident in microbial glutamate metabolic pathways (L-glutamate degradation VIII was enriched, and L-glutamate and L-glutamine biosynthesis were diminished) (P<0.05, log2 Fold Change >1). Moreover, the microbiome composition was different for patients under 40 years of age compared to older patients (LDA score >2, P<0.05). Conclusions: Microbiome and microbial metabolic profiles of CRC patients are different from those of healthy individuals. CRC microbiome dysbiosis, particularly P. copri and F. prausnitzii depletion and glutamate metabolic alterations, are evident in Kenyan CRC patients.

Lung transcriptome of nonhuman primates exposed to total- and partial-body irradiation.

The focus of radiation biodosimetry has changed recently, and a paradigm shift for using molecular technologies of omic platforms in addition to cytogenetic techniques has been observed. In our study, we have used a nonhuman primate model to investigate the impact of a supralethal dose of 12 Gy radiation on alterations in the lung transcriptome. We used 6 healthy and 32 irradiated animal samples to delineate radiation-induced changes. We also used a medical countermeasure, γ-tocotrienol (GT3), to observe any changes. We demonstrate significant radiation-induced changes in the lung transcriptome for total-body irradiation (TBI) and partial-body irradiation (PBI). However, no major influence of GT3 on radiation was noted in either comparison. Several common signaling pathways, including PI3K/AKT, GADD45, and p53, were upregulated in both exposures. TBI activated DNA-damage-related pathways in the lungs, whereas PTEN signaling was activated after PBI. Our study highlights the various transcriptional profiles associated with γ- and X-ray exposures, and the associated pathways include LXR/RXR activation in TBI, whereas pulmonary wound-healing and pulmonary fibrosis signaling was repressed in PBI. Our study provides important insights into the molecular pathways associated with irradiation that can be further investigated for biomarker discovery.

Ecdysoneless Overexpression Drives Mammary Tumorigenesis through Upregulation of C-MYC and Glucose Metabolism.

Ecdysoneless (ECD) protein is essential for embryogenesis, cell-cycle progression, and cellular stress mitigation with an emerging role in mRNA biogenesis. We have previously shown that ECD protein as well as its mRNA are overexpressed in breast cancer and ECD overexpression predicts shorter survival in patients with breast cancer. However, the genetic evidence for an oncogenic role of ECD has not been established. Here, we generated transgenic mice with mammary epithelium-targeted overexpression of an inducible human ECD transgene (ECDTg). Significantly, ECDTg mice develop mammary hyperplasia, preneoplastic lesions, and heterogeneous tumors with occasional lung metastasis. ECDTg tumors exhibit epithelial to mesenchymal transition and cancer stem cell characteristics. Organoid cultures of ECDTg tumors showed ECD dependency for in vitro oncogenic phenotype and in vivo growth when implanted in mice. RNA sequencing (RNA-seq) analysis of ECDTg tumors showed a c-MYC signature, and alterations in ECD levels regulated c-MYC mRNA and protein levels as well as glucose metabolism. ECD knockdown-induced decrease in glucose uptake was rescued by overexpression of mouse ECD as well as c-MYC. Publicly available expression data analyses showed a significant correlation of ECD and c-MYC overexpression in breast cancer, and ECD and c-MYC coexpression exhibits worse survival in patients with breast cancer. Taken together, we establish a novel role of overexpressed ECD as an oncogenesis driver in the mouse mammary gland through upregulation of c-MYC-mediated glucose metabolism. IMPLICATIONS: We demonstrate ECD overexpression in the mammary gland of mice led to the development of a tumor progression model through upregulation of c-MYC signaling and glucose metabolism.

Meta-Analysis of Altered Gut Microbiota Reveals Microbial and Metabolic Biomarkers for Colorectal Cancer.

Colorectal cancer (CRC) is the second leading cause of cancer mortality worldwide. The dysbiotic gut microbiota and its metabolite secretions play a significant role in CRC development and progression. In this study, we identified microbial and metabolic biomarkers applicable to CRC using a meta-analysis of metagenomic datasets from diverse geographical regions. We used LEfSe, random forest (RF), and co-occurrence network methods to identify microbial biomarkers. Geographic dataset-specific markers were identified and evaluated using area under the ROC curve (AUC) scores and random effect size. Co-occurrence networks analysis showed a reduction in the overall microbial associations and the presence of oral pathogenic microbial clusters in CRC networks. Analysis of predicted metabolites from CRC datasets showed the enrichment of amino acids, cadaverine, and creatine in CRC, which were positively correlated with CRC-associated microbes (Peptostreptococcus stomatis, Gemella morbillorum, Bacteroides fragilis, Parvimonas spp., Fusobacterium nucleatum, Solobacterium moorei, and Clostridium symbiosum), and negatively correlated with control-associated microbes. Conversely, butyrate, nicotinamide, choline, tryptophan, and 2-hydroxybutanoic acid showed positive correlations with control-associated microbes (P < 0.05). Overall, our study identified a set of global CRC biomarkers that are reproducible across geographic regions. We also reported significant differential metabolites and microbe-metabolite interactions associated with CRC. This study provided significant insights for further investigations leading to the development of noninvasive CRC diagnostic tools and therapeutic interventions. IMPORTANCE Several studies showed associations between gut dysbiosis and CRC. Yet, the results are not conclusive due to cohort-specific associations that are influenced by genomic, dietary, and environmental stimuli and associated reproducibility issues with various analysis approaches. Emerging evidence suggests the role of microbial metabolites in modulating host inflammation and DNA damage in CRC. However, the experimental validations have been hindered by cost, resources, and cumbersome technical expertise required for metabolomic investigations. In this study, we performed a meta-analysis of CRC microbiota data from diverse geographical regions using multiple methods to achieve reproducible results. We used a computational approach to predict the metabolomic profiles using existing CRC metagenomic datasets. We identified a reliable set of CRC-specific biomarkers from this analysis, including microbial and metabolite markers. In addition, we revealed significant microbe-metabolite associations through correlation analysis and microbial gene families associated with dysregulated metabolic pathways in CRC, which are essential in understanding the vastly sporadic nature of CRC development and progression.

Hypo-glycosylated hFSH drives ovarian follicular development more efficiently than fully-glycosylated hFSH: enhanced transcription and PI3K and MAPK signaling.

STUDY QUESTION: Does hypo-glycosylated human recombinant FSH (hFSH18/21) have greater in vivo bioactivity that drives follicle development in vivo compared to fully-glycosylated human recombinant FSH (hFSH24)? SUMMARY ANSWER: Compared with fully-glycosylated hFSH, hypo-glycosylated hFSH has greater bioactivity, enabling greater follicular health and growth in vivo, with enhanced transcriptional activity, greater activation of receptor tyrosine kinases (RTKs) and elevated phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) and Mitogen-activated protein kinase (MAPK)/extracellular signal-regulated kinase (ERK) signaling. WHAT IS KNOWN ALREADY: Glycosylation of FSH is necessary for FSH to effectively activate the FSH receptor (FSHR) and promote preantral follicular growth and formation of antral follicles. In vitro studies demonstrate that compared to fully-glycosylated recombinant human FSH, hypo-glycosylated FSH has greater activity in receptor binding studies, and more effectively stimulates the PKA pathway and steroidogenesis in human granulosa cells. STUDY DESIGN, SIZE, DURATION: This is a cross-sectional study evaluating the actions of purified recombinant human FSH glycoforms on parameters of follicular development, gene expression and cell signaling in immature postnatal day (PND) 17 female CD-1 mice. To stimulate follicle development in vivo, PND 17 female CD-1 mice (n = 8-10/group) were treated with PBS (150 µl), hFSH18/21 (1 µg/150 µl PBS) or hFSH24 (1 µg/150 µl PBS) by intraperitoneal injection (i.p.) twice daily (8:00 a.m. and 6:00 p.m.) for 2 days. Follicle numbers, serum anti-Müllerian hormone (AMH) and estradiol levels, and follicle health were quantified. PND 17 female CD-1 mice were also treated acutely (2 h) in vivo with PBS, hFSH18/21 (1 µg) or hFSH24 (1 µg) (n = 3-4/group). One ovary from each mouse was processed for RNA sequencing analysis and the other ovary processed for signal transduction analysis. An in vitro ovary culture system was used to confirm the relative signaling pathways. PARTICIPANTS/MATERIALS, SETTING, METHODS: The purity of different recombinant hFSH glycoforms was analyzed using an automated western blot system. Follicle numbers were determined by counting serial sections of the mouse ovary. Real-time quantitative RT-PCR, western blot and immunofluorescence staining were used to determine growth and apoptosis markers related with follicle health. RNA sequencing and bioinformatics were used to identify pathways and processes associated with gene expression profiles induced by acute FSH glycoform treatment. Analysis of RTKs was used to determine potential FSH downstream signaling pathways in vivo. Western blot and in vitro ovarian culture system were used to validate the relative signaling pathways. MAIN RESULTS AND THE ROLE OF CHANCE: Our present study shows that both hypo- and fully-glycosylated recombinant human FSH can drive follicular growth in vivo. However, hFSH18/21 promoted development of significantly more large antral follicles compared to hFSH24 (P < 0.01). In addition, compared with hFSH24, hFSH18/21 also promoted greater indices of follicular health, as defined by lower BAX/BCL2 ratios and reduced cleaved Caspase 3. Following acute in vivo treatment with FSH glycoforms RNA-sequencing data revealed that both FSH glycoforms rapidly induced ovarian transcription in vivo, but hypo-glycosylated FSH more robustly stimulated Gαs and cAMP-mediated signaling and members of the AP-1 transcription factor complex. Moreover, hFSH18/21 treatment induced significantly greater activation of RTKs, PI3K/AKT and MAPK/ERK signaling compared to hFSH24. FSH-induced indices of follicle growth in vitro were blocked by inhibition of PI3K and MAPK. LARGE SCALE DATA: RNA sequencing of mouse ovaries. Data will be shared upon reasonable request to the corresponding author. LIMITATIONS, REASONS FOR CAUTION: The observations that hFSH glycoforms have different bioactivities in the present study employing a mouse model of follicle development should be verified in nonhuman primates. The gene expression studies reflect transcriptomes of whole ovaries. WIDER IMPLICATIONS OF THE FINDINGS: Commercially prepared recombinant human FSH used for ovarian stimulation in human ART is fully-glycosylated FSH. Our findings that hypo-glycosylated hFSH has greater bioactivity enabling greater follicular health and growth without exaggerated estradiol production in vivo, demonstrate the potential for its development for application in human ART. STUDY FUNDING/COMPETING INTEREST(S): This work was supported by NIH 1P01 AG029531, NIH 1R01 HD 092263, VA I01 BX004272, and the Olson Center for Women's Health. JSD is the recipient of a VA Senior Research Career Scientist Award (1IK6 BX005797). This work was also partially supported by National Natural Science Foundation of China (No. 31872352). The authors declared there are no conflicts of interest.

The Mammalian Ecdysoneless Protein Interacts with RNA Helicase DDX39A To Regulate Nuclear mRNA Export.

The mammalian orthologue of ecdysoneless (ECD) protein is required for embryogenesis, cell cycle progression, and mitigation of endoplasmic reticulum stress. Here, we identified key components of the mRNA export complexes as binding partners of ECD and characterized the functional interaction of ECD with key mRNA export-related DEAD BOX protein helicase DDX39A. We find that ECD is involved in RNA export through its interaction with DDX39A. ECD knockdown (KD) blocks mRNA export from the nucleus to the cytoplasm, which is rescued by expression of full-length ECD but not an ECD mutant that is defective in interaction with DDX39A. We have previously shown that ECD protein is overexpressed in ErbB2+ breast cancers (BC). In this study, we extended the analyses to two publicly available BC mRNA The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) data sets. In both data sets, ECD mRNA overexpression correlated with short patient survival, specifically ErbB2+ BC. In the METABRIC data set, ECD overexpression also correlated with poor patient survival in triple-negative breast cancer (TNBC). Furthermore, ECD KD in ErbB2+ BC cells led to a decrease in ErbB2 mRNA level due to a block in its nuclear export and was associated with impairment of oncogenic traits. These findings provide novel mechanistic insight into the physiological and pathological functions of ECD.