Identification of novel epigenetically inactivated gene PAMR1 in breast carcinoma

NEDD4 facilitates the progression of endometrial carcinoma by enhancing PAMR1 protein degradation through ubiquitination

Endometrial carcinoma (EC) is an epithelial malignant neoplasm that frequently appears in postmenopausal and perimenopausal women. PAMR1 is related to the prognosis of EC. Here, we probed into the significance of PAMR1 in EC progression and its acting mechanism. In silico analysis was conducted to identify the differentially expressed gene PAMR1 and its upstream gene NEDD4 in EC, followed by the determination of their expression in EC tissues and cells. The gene expression, cell proliferation, angiogenesis, migration, invasion, and apoptosis were examined after ectopic expression or knockdown experiments. The interaction between NEDD4 and PAMR1 and the level of PAMR1 ubiquitination were examined. The injection of Ishikawa cell suspensions into nude mice was carried out to establish a tumor xenograft model, validating the roles of PAMR1 and NEDD4 in EC. EC cells exhibited high NEDD4 expression and low PAMR1 expression. NEDD4 knockdown or PAMR1 overexpression suppressed the invasive, migrating, angiogenic, and proliferative properties of EC cells while promoting apoptosis. NEDD4 facilitated PAMR1 protein degradation through ubiquitination. Deletion of PAMR1 abolished the inhibitory effects of NEDD4 knockdown on the malignant behaviors of EC cells. Furthermore, NEDD4 knockdown restrained EC growth in nude mice by increasing PAMR1 protein expression. NEDD4 facilitated EC progression by enhancing PAMR1 protein degradation through ubiquitination.

Benchmarking feature selection and feature extraction methods to improve the performances of machine-learning algorithms for patient classification using metabolomics biomedical data

Objective

Classification tasks are an open challenge in the field of biomedicine. While several machine-learning techniques exist to accomplish this objective, several peculiarities associated with biomedical data, especially when it comes to omics measurements, prevent their use or good performance achievements. Omics approaches aim to understand a complex biological system through systematic analysis of its content at the molecular level. On the other hand, omics data are heterogeneous, sparse and affected by the classical "curse of dimensionality" problem, i.e. having much fewer observation, samples (n) than omics features (p). Furthermore, a major problem with multi-omics data is the imbalance either at the class or feature level. The objective of this work is to study whether feature extraction and/or feature selection techniques can improve the performances of classification machine-learning algorithms on omics measurements.

Methods

Among all omics, metabolomics has emerged as a powerful tool in cancer research, facilitating a deeper understanding of the complex metabolic landscape associated with tumorigenesis and tumor progression. Thus, we selected three publicly available metabolomics datasets, and we applied several feature extraction techniques both linear and non-linear, coupled or not with feature selection methods, and evaluated the performances regarding patient classification in the different configurations for the three datasets.

Results

We provide general workflow and guidelines on when to use those techniques depending on the characteristics of the data available. To further test the extension of our approach to other omics data, we have included a transcriptomics and a proteomics data. Overall, for all datasets, we showed that applying supervised feature selection improves the performances of feature extraction methods for classification purposes. Scripts used to perform all analyses are available at: https://github.com/Plant-Net/Metabolomic_project/.

Predicting gene signature in breast cancer patients with multiple machine learning models

AIMS

The aim of this study was to predict gene signatures in breast cancer patients using multiple machine learning models.

METHODS

In this study, we first collated and merged the datasets GSE54002 and GSE22820, obtaining a gene expression matrix comprising 16,820 genes (including 593 breast cancer (BC) samples and 26 normal control (NC) samples). Subsequently, we performed enrichment analyses using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Disease Ontology (DO).

RESULTS

We identified 177 differentially expressed genes (DEGs), including 40 up-regulated and 137 down-regulated genes, through differential expression analysis. The GO enrichment results indicated that these genes are primarily involved in extracellular matrix organization, positive regulation of nervous system development, collagen-containing extracellular matrix, heparin binding, glycosaminoglycan binding, and Wnt protein binding, among others. KEGG enrichment analysis revealed that the DEGs were primarily associated with pathways such as focal adhesion, the PI3K-Akt signaling pathway, and human papillomavirus infection. DO enrichment analysis showed that the DEGs play a significant role in regulating diseases such as intestinal disorders, nephritis, and dermatitis. Further, through LASSO regression analysis and SVM-RFE algorithm analysis, we identified 9 key feature DEGs (CF-DEGs): ANGPTL7, TSHZ2, SDPR, CLCA4, PAMR1, MME, CXCL2, ADAMTS5, and KIT. Additionally, ROC curve analysis demonstrated that these CF-DEGs serve as a reliable diagnostic index. Finally, using the CIBERSORT algorithm, we analyzed the infiltration of immune cells and the associations between CF-DEGs and immune cell infiltration across all samples.

CONCLUSIONS

Our findings provide new insights into the molecular functions and metabolic pathways involved in breast cancer, potentially aiding in the discovery of new diagnostic and immunotherapeutic biomarkers.

Identification of modules and key genes associated with breast cancer subtypes through network analysis

Breast cancer is the most common malignancy in women around the world. Intratumor and intertumoral heterogeneity persist in mammary tumors. Therefore, the identification of biomarkers is essential for the treatment of this malignancy. This study analyzed 28,143 genes expressed in 49 breast cancer cell lines using a Weighted Gene Co-expression Network Analysis to determine specific target proteins for Basal A, Basal B, Luminal A, Luminal B, and HER2 ampl breast cancer subtypes. Sixty-five modules were identified, of which five were characterized as having a high correlation with breast cancer subtypes. Genes overexpressed in the tumor were found to participate in the following mechanisms: regulation of the apoptotic process, transcriptional regulation, angiogenesis, signaling, and cellular survival. In particular, we identified the following genes, considered as hubs: IFIT3, an inhibitor of viral and cellular processes; ETS1, a transcription factor involved in cell death and tumorigenesis; ENSG00000259723 lncRNA, expressed in cancers; AL033519.3, a hypothetical gene; and TMEM86A, important for regulating keratinocyte membrane properties, considered as a key in Basal A, Basal B, Luminal A, Luminal B, and HER2 ampl breast cancer subtypes, respectively. The modules and genes identified in this work can be used to identify possible biomarkers or therapeutic targets in different breast cancer subtypes.

POFUT1-mediated O-fucosylation of glycoproteins expressed in the baculovirus Sf9 insect cell expression system

The baculovirus-insect cell expression system allows addition of O-fucose to EGF-like domains of glycoproteins, following the action of the protein O-fucosyltransferase 1 named POFUT1. In this study, recombinant Spodoptera frugiperda POFUT1 from baculovirus-infected Sf9 cells was compared to recombinant Mus musculus POFUT1 produced by CHO cells. Contrary to recombinant murine POFUT1 carrying two hybrid and/or complex type N-glycans, Spodoptera frugiperda POFUT1 exhibited paucimannose N-glycans, at least on its highly evolutionary conserved across Metazoa NRT site. The abilities of both recombinant enzymes to add in vitro O -fucose to EGF-like domains of three different recombinant mammalian glycoproteins were then explored. In vitro POFUT1-mediated O-fucosylation experiments, followed by click chemistry and blot analyses, showed that Spodoptera frugiperda POFUT1 was able to add O-fucose to mouse NOTCH1 EGF-like 26 and WIF1 EGF-like 3 domains, similarly to the murine counterpart. As proved by mass spectrometry, full-length human WNT Inhibitor Factor 1 expressed by Sf9 cells was also modified with O-fucose. However, Spodoptera frugiperda POFUT1 was unable to modify the single EGF-like domain of mouse PAMR1 with O-fucose, contrary to murine POFUT1. Absence of orthologous proteins such as PAMR1 in insects may explain the enzyme's difficulty in adding O-fucose to a domain that it never encounters naturally.

Adaptive Sparse Multi-Block PLS Discriminant Analysis: An Integrative Method for Identifying Key Biomarkers from Multi-Omics Data

With the growing use of high-throughput technologies, multi-omics data containing various types of high-dimensional omics data is increasingly being generated to explore the association between the molecular mechanism of the host and diseases. In this study, we present an adaptive sparse multi-block partial least square discriminant analysis (asmbPLS-DA), an extension of our previous work, asmbPLS. This integrative approach identifies the most relevant features across different types of omics data while discriminating multiple disease outcome groups. We used simulation data with various scenarios and a real dataset from the TCGA project to demonstrate that asmbPLS-DA can identify key biomarkers from each type of omics data with better biological relevance than existing competitive methods. Moreover, asmbPLS-DA showed comparable performance in the classification of subjects in terms of disease status or phenotypes using integrated multi-omics molecular profiles, especially when combined with other classification algorithms, such as linear discriminant analysis and random forest. We have made the R package called asmbPLS that implements this method publicly available on GitHub. Overall, asmbPLS-DA achieved competitive performance in terms of feature selection and classification. We believe that asmbPLS-DA can be a valuable tool for multi-omics research.

Expanding the spectrum of GLI1-altered mesenchymal tumors-A high-grade uterine sarcoma harboring a novel PAMR1::GLI1 fusion and literature review of GLI1-altered mesenchymal neoplasms of the gynecologic tract

GLI1-altered mesenchymal tumors comprise a group of seemingly unrelated entities, including pericytoma with t(7;12) translocation, plexiform fibromyxoma, gastroblastoma, malignant epithelioid neoplasm with GLI1 rearrangements, and GLI1-amplified mesenchymal neoplasms. Herein, we report a high-grade uterine sarcoma harboring a novel PAMR1::GLI1 fusion and present a literature review of GLI1-altered mesenchymal neoplasms of the gynecologic tract. A 57-year-old female presented with an abdomino-pelvic mass, felt since a decade prior. Magnetic resonance imaging showed a heterogenous myometrial mass extending beyond the serosa. The patient underwent oncologic surgical resection. Gross examination revealed a perforated multi-nodular uterine tumor (21 cm) with a firm white and soft fleshy cut surface, featuring hemorrhage and necrosis. The tumor was morphologically heterogenous, disclosing frankly sarcomatous areas composed of pleomorphic spindle and focally epithelioid cells, intermingled with a component of low-grade spindle cells arranged in fascicles. There was a rich vascular network and zones of necrosis with peripheral amianthoid-like collagen plaques. Lymphovascular invasion and metastasis to lymph nodes and omentum were present. The tumor was immunopositive for CD10 and cyclinD1, and negative for cytokeratins, myogenic, melanotic, and hormonal markers. ArcherTM Fusion Sarcoma Assay detected PAMR1(exon1)::GLI1(exon4) fusion, confirmed on RT-PCR and Sanger sequencing. The patient received chemo-radiotherapy, however, developed metastatic recurrence and demised 18 months post-surgery. Altogether, this is a rare and diagnostically challenging case of a uterine sarcoma harboring a novel GLI1 fusion. Emerging GLI/Hedgehog inhibitors provide clinical relevance to recognizing these tumors in modern pathology.

MrgprF acts as a tumor suppressor in cutaneous melanoma by restraining PI3K/Akt signaling

The incidence of cutaneous melanoma (CM) has been increasing annually worldwide. In this study, we identify that MrgprF, a MAS related GPR family member, is decreased in cutaneous melanoma tissues and cell lines due to hypermethylation of its promoter region, and show that patients with CM expressing high levels of MrgprF exhibit an improved clinical outcome. We demonstrate that MrgprF forced expression inhibits tumor cell proliferation, migration, xenograft tumor growth, and metastasis. On the contrary, MrgprF knockdown promotes tumor cell proliferation and transformation of immortalized human keratinocyte-HaCaT cells, supporting the inhibitory role of MrgprF during tumor progression. Mechanistic studies reveal that MrgprF reduces the phosphoinositol‑3‑kinase (PI3K) complex formation between p101 and p110γ subunits, the critical step for phosphatidylinositol-(3, 4)-P2 (PIP2) conversion to phosphatidylinositol-(3, 4, 5)-P3 (PIP3), and then reduces the activation of PI3K/Akt signaling. This effect can be reversed by Akt specific agonist SC79. In addition, AMG 706, a previously documented inhibitor for endothelial cell proliferation, is identified as a potential agonist for MrgprF, and can impede tumor growth both in vitro and in vivo. Taken together, our findings suggest that MrgprF, a novel tumor suppressor in cutaneous melanoma, may be useful as a therapeutic target in the future.

Serine pseudoproteases in physiology and disease

Serine proteases (SPs) constitute a very important family of enzymes, both physiologically and pathologically. The effects produced by these proteins have been explained by their proteolytic activity. However, the discovery of pharmacologically active SP molecules that show no enzymatic activity, as the so-called pseudo SPs or SP homologs (SPHs), has exposed a profoundly neglected possibility of nonenzymatic functions of these SP molecules. In this review, the most thoroughly described SPHs are presented. The main physiological domains in which SPHs operate appear to be in reproduction, embryonic development, immune response, host defense, and hemostasis. Hitherto unexplained actions of SPs should therefore be considered also as the result of the ligand-like attributes of SPs. The gain of a novel function by an SPH is a consequence of specific amino acid replacements that have resulted in a novel interaction interface or a 'catalytic trap'. Unraveling the SP/SPH interactome will provide a description of previously unknown physiological functions of SPs/SPHs, aiding the creation of innovative medical approaches.

LASSO and Bioinformatics Analysis in the Identification of Key Genes for Prognostic Genes of Gynecologic Cancer

The aim of this study is to identify potential biomarkers for early diagnosis of gynecologic cancer in order to improve survival. Cervical cancer (CC) and endometrial cancer (EC) are the most common malignant tumors of gynecologic cancer among women in the world. As the underlying molecular mechanisms in both cervical and endometrial cancer remain unclear, a comprehensive and systematic bioinformatics analysis is required. In our study, gene expression profiles of GSE9750, GES7803, GES63514, GES17025, GES115810, and GES36389 downloaded from Gene Expression Omnibus (GEO) were utilized to analyze differential gene expression between cancer and normal tissues. A total of 78 differentially expressed genes (DEGs) common to CC and EC were identified to perform the functional enrichment analyses, including gene ontology and pathway analysis. KEGG pathway analysis of 78 DEGs indicated that three main types of pathway participate in the mechanism of gynecologic cancer such as drug metabolism, signal transduction, and tumorigenesis and development. Furthermore, 20 diagnostic signatures were confirmed using the least absolute shrink and selection operator (LASSO) regression with 10-fold cross validation. Finally, we used the GEPIA2 online tool to verify the expression of 20 genes selected by the LASSO regression model. Among them, the expression of PAMR1 and SLC24A3 in tumor tissues was downregulated significantly compared to the normal tissue, and found to be statistically significant in survival rates between the CC and EC of patients (p < 0.05). The two genes have their function: (1.) PAMR1 is a tumor suppressor gene, and many studies have proven that overexpression of the gene markedly suppresses cell growth, especially in breast cancer and polycystic ovary syndrome; (2.) SLC24A3 is a sodium–calcium regulator of cells, and high SLC24A3 levels are associated with poor prognosis. In our study, the gene signatures can be used to predict CC and EC prognosis, which could provide novel clinical evidence to serve as a potential biomarker for future diagnosis and treatment.

High Expression of PAMR1 Predicts Favorable Prognosis and Inhibits Proliferation, Invasion, and Migration in Cervical Cancer

Peptidase domain containing associated with muscle regeneration 1 (PAMR1) is frequently lost in breast cancer samples and is considered as a tumor suppressor. The roles and mechanisms of PAMR1 in other types of cancers are still unclear. In our present study, we identified PAMR1 as an invasion-related regulator in cervical cancer. Public database and immunohistochemical (IHC) analysis showed that the expression level of PAMR1 in cervical cancer tissues was lower than that in normal cervix tissues and was negatively related to clinicopathologic features. The high expression of PAMR1 also predicted a better prognosis of cervical cancer patients. CCK8, Transwell, and wound-healing assays demonstrated that knockdown of PAMR1 facilitated the proliferation, migration, and invasion of cervical cancer cells. Additionally, gene set enrichment analysis (GSEA) showed a variety of cancer-related pathways potentially activated or suppressed by PAMR1. Moreover, we verified that PAMR1 inhibited MYC target and mTORC1 signaling pathways. In conclusion, our study revealed the suppressor role of PAMR1 in cervical cancer, providing a new insight into the molecular mechanism of cervical cancer progression.

The single EGF-like domain of mouse PAMR1 is modified by O-Glucose, O-Fucose and O-GlcNAc

Epidermal growth factor-like domains (EGF-LDs) of membrane and secreted proteins can be modified by N-glycans and/or potentially elongated O-linked monosaccharides such as O-glucose (O-Glc) found at two positions (O-Glc 1 and O-Glc2), O-fucose (O-Fuc) and O-N-acetylglucosamine (O-GlcNAc). The presence of three O-linked sugars within the same EGF-LD, such as in EGF-LD 20 of NOTCH1, has rarely been evidenced. We searched in KEGG GENES database to list mouse and human proteins with an EGF-LD sequence including one, two, three or four potential O-glycosylation consensus sites. Among the 129 murine retrieved proteins, most had predicted O-fucosylation and/or O-GlcNAcylation sites. Around 68% of EGF-LDs were subjected to only one O-linked sugar modification and near 5% to three modifications. Among these latter, we focused on the peptidase domain-containing protein associated with muscle regeneration 1 (PAMR1), having only one EGF-LD. To test the ability of this domain to be glycosylated, a correctly folded EGF-LD was produced in Escherichia coli periplasm, purified and subjected to in vitro incubations with the recombinant O-glycosyltransferases POGLUT1, POFUT1 and EOGT, adding O-Glc1, O-Fuc and O-GlcNAc, respectively. Using click chemistry and mass spectrometry, isolated PAMR1 EGF-LD was demonstrated to be modified by the three O-linked sugars. Their presence was individually confirmed on EGF-LD of full-length mouse recombinant PAMR1, with at least some molecules modified by both O-Glc1 and O-Fuc. Overall, these results are consistent with the presence of a triple O-glycosylated EGF-LD in mouse PAMR1.

Dysregulated lncRNA-miRNA-mRNA Network Reveals Patient Survival-Associated Modules and RNA Binding Proteins in Invasive Breast Carcinoma

Breast cancer is the most common cancer in women, but few biomarkers are effective in clinic. Previous studies have shown the important roles of non-coding RNAs in diagnosis, prognosis, and therapy selection for breast cancer and have suggested the significance of integrating molecules at different levels to interpret the mechanism of breast cancer. Here, we collected transcriptome data including long non-coding RNA (lncRNA), microRNA (miRNA), and mRNA for ~1,200 samples, including 1079 invasive breast carcinoma samples and 104 normal samples, from The Cancer Genome Atlas (TCGA) project. We identified differentially expressed lncRNAs, miRNAs, and mRNAs that distinguished invasive carcinoma samples from normal samples. We further constructed an integrated dysregulated network consisting of differentially expressed lncRNAs, miRNAs, and mRNAs and found housekeeping and cancer-related functions. Moreover, 58 RNA binding proteins (RBPs) involved in biological processes that are essential to maintain cell survival were found in the dysregulated network, and 10 were correlated with overall survival. In addition, we identified two modules that stratify patients into high- and low-risk subgroups. The expression patterns of these two modules were significantly different in invasive carcinoma versus normal samples, and some molecules were high-confidence biomarkers of breast cancer. Together, these data demonstrated an important clinical application for improving outcome prediction for invasive breast cancers.

Identification of differentially expressed genes and preliminary validations in cardiac pathological remodeling induced by transverse aortic constriction

Cardiac remodeling predisposes to heart failure if the burden is unresolved, and heart failure is an important cause of mortality in humans. The aim of the present study was to identify the key genes involved in cardiac pathological remodeling induced by pressure overload. Gene expression profiles of the GSE5500, GSE18224, GSE36074 and GSE56348 datasets were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs), defined as |log2FC|>1 (FC, fold change) and an adjusted P‑value of <0.05, were screened using the R software with the limma package. Gene ontology enrichment analysis was performed and a protein‑protein interaction (PPI) network of the DEGs was constructed. A cardiac remodeling model induced by transverse aortic constriction (TAC) was established. Furthermore, consistent DEGs were further validated using reverse transcription‑quantitative polymerase chain reaction (RT‑PCR) analysis, western blotting and immunohistochemistry in the ventricular tissue samples after TAC or sham operation. A total of 24 common DEGs were identified (23 significantly upregulated and 1 downregulated), of which 9 genes had been previously confirmed to be directly involved in cardiac remodeling. Hence, the level of expression of the other 15 genes was detected in subsequent studies via RT‑PCR. Based on the results of the PPI network analysis and RT‑PCR, we further detected the protein levels of Itgbl1 and Asporin, which were consistent with the results of bioinformatics analysis and RT‑PCR. The expression of Itgbl1, Aspn, Fstl1, Mfap5, Col8a1, Ltbp2, Mfap4, Pamr1, Cnksr1, Aqp8, Meox1, Gdf15 and Srpx was found to be upregulated in a mouse model of cardiac remodeling, while that of Retnla was downregulated. Therefore, the present study identified the key genes implicated in cardiac remodeling, aiming to provide new insight into the underlying mechanism.

Identification of Crucial Candidate Genes and Pathways in Glioblastoma Multiform by Bioinformatics Analysis

The present study aimed to investigate the molecular mechanisms underlying glioblastoma multiform (GBM) and its biomarkers. The differentially expressed genes (DEGs) were diagnosed using the limma software package. The ToppGene (ToppFun) was used to perform pathway and Gene Ontology (GO) enrichment analysis of the DEGs. Protein-protein interaction (PPI) networks, extracted modules, miRNA-target genes regulatory network and TF-target genes regulatory network were used to obtain insight into the actions of DEGs. Survival analysis for DEGs was carried out. A total of 590 DEGs, including 243 up regulated and 347 down regulated genes, were diagnosed between scrambled shRNA expression and Lin7A knock down. The up-regulated genes were enriched in ribosome, mitochondrial translation termination, translation, and peptide biosynthetic process. The down-regulated genes were enriched in focal adhesion, VEGFR3 signaling in lymphatic endothelium, extracellular matrix organization, and extracellular matrix. The current study screened the genes in the PPI network, extracted modules, miRNA-target genes regulatory network, and TF-target genes regulatory network with higher degrees as hub genes, which included NPM1, CUL4A, YIPF1, SHC1, AKT1, VLDLR, RPL14, P3H2, DTNA, FAM126B, RPL34, and MYL5. Survival analysis indicated that the high expression of RPL36A and MRPL35 were predicting longer survival of GBM, while high expression of AP1S1 and AKAP12 were predicting shorter survival of GBM. High expression of RPL36A and AP1S1 were associated with pathogenesis of GBM, while low expression of ALPL was associated with pathogenesis of GBM. In conclusion, the current study diagnosed DEGs between scrambled shRNA expression and Lin7A knock down samples, which could improve our understanding of the molecular mechanisms in the progression of GBM, and these crucial as well as new diagnostic markers might be used as therapeutic targets for GBM.

TMT Based Proteomic Analysis of Human Follicular Fluid From Overweight/Obese and Normal-Weight Patients With Polycystic Ovary Syndrome

Background: Polycystic ovary syndrome (PCOS) is a major endocrine and metabolic disorder with heterogeneous manifestations and complex etiology. As a leading cause of anovulatory infertility, the molecular diversity of the follicular microenvironment has not been fully elucidated. The aim of the present study was to investigate the follicular fluid proteomic profiles of overweight/obese and normal-weight women with PCOS, to identify novel molecular mechanisms underlying PCOS and to determine the effect of obesity on the follicular fluid protein profiles. Methods: Follicular fluid samples were collected from 3 different groups: overweight/obese PCOS patients (n = 29), normal-weight PCOS patients (n = 29), and normo-ovulatory controls (n = 29). We used a quantitative approach with tandem mass tag labeling and liquid chromatography tandem mass spectrometry to identify the differentially expressed proteins. Differential abundance of four selected proteins was confirmed by ELISA. Gene Set Enrichment Analysis was also conducted to further explore our findings. Furthermore, we compared the clinical, hormonal, and biochemical characteristics of overweight/obese and normal-weight patients with PCOS to determine the effects of obesity. Results: A total of 1,153 proteins were identified, of which 41 and 19 proteins were differentially expressed in the overweight/obese PCOS group vs. the control group, and in the normal-weight PCOS group vs. the control group, respectively. Bioinformatics analyses showed that the inflammatory, immunological, and metabolic-related biological processes were co-enriched in both subgroups of PCOS. Apolipoprotein A-II, complement C5, fetuin-B, and stromal cell-derived factor 1 were found to be involved in various processes and were validated using the ELISA analysis. From clinical features and proteomic data, obesity was found to worsen follicular development disturbances in PCOS. Conclusion: In this proteomic study, a panel of proteins were found differentially expressed in the follicular fluid of PCOS. Inflammatory, immunological, and metabolic abnormalities were identified inside the intra-follicular environment, which could be aggravated by obesity. The identified proteins were correlated with follicular growth and may be considered as candidate biomarkers as well as therapeutic targets of PCOS.

Specific Eph receptor-cytoplasmic effector signaling mediated by SAM-SAM domain interactions

The Eph receptor tyrosine kinase (RTK) family is the largest subfamily of RTKs playing critical roles in many developmental processes such as tissue patterning, neurogenesis and neuronal circuit formation, angiogenesis, etc. How the 14 Eph proteins, via their highly similar cytoplasmic domains, can transmit diverse and sometimes opposite cellular signals upon engaging ephrins is a major unresolved question. Here, we systematically investigated the bindings of each SAM domain of Eph receptors to the SAM domains from SHIP2 and Odin, and uncover a highly specific SAM-SAM interaction-mediated cytoplasmic Eph-effector binding pattern. Comparative X-ray crystallographic studies of several SAM-SAM heterodimer complexes, together with biochemical and cell biology experiments, not only revealed the exquisite specificity code governing Eph/effector interactions but also allowed us to identify SAMD5 as a new Eph binding partner. Finally, these Eph/effector SAM heterodimer structures can explain many Eph SAM mutations identified in patients suffering from cancers and other diseases.

In utero exposure to diesel exhaust particulates is associated with an altered cardiac transcriptional response to transverse aortic constriction and altered DNA methylation

In utero exposure to diesel exhaust air pollution has been associated with increased adult susceptibility to heart failure in mice, but the mechanisms by which this exposure promotes susceptibility to heart failure are poorly understood. To identify the potential transcriptional effects that mediate this susceptibility, we have performed RNA sequencing analysis on adult hearts from mice that were exposed to diesel exhaust in utero and that have subsequently undergone transverse aortic constriction. We identified 3 target genes, Mir133a-2, Ptprf, and Pamr1, which demonstrate dysregulation after exposure and aortic constriction. Examination of expression patterns in human heart tissues indicates a correlation between expression and heart failure. We subsequently assessed DNA methylation modifications at these candidate loci in neonatal cultured cardiac myocytes after in utero exposure to diesel exhaust and found that the promoter for Mir133a-2 is differentially methylated. These target genes in the heart are the first genes to be identified that likely play an important role in mediating adult sensitivity to heart failure. We have also shown a change in DNA methylation within cardiomyocytes as a result of in utero exposure to diesel exhaust.-Goodson, J. M., Weldy, C. S., MacDonald, J. W., Liu, Y., Bammler, T. K., Chien, W.-M., Chin, M. T. In utero exposure to diesel exhaust particulates is associated with an altered cardiac transcriptional response to transverse aortic constriction and altered DNA methylation.

Gene expression profiling of breast cancer in Lebanese women

Breast cancer is commonest cancer in women worldwide. Elucidation of underlying biology and molecular pathways is necessary for improving therapeutic options and clinical outcomes. Molecular alterations in breast cancer are complex and involve cross-talk between multiple signaling pathways. The aim of this study is to extract a unique mRNA fingerprint of breast cancer in Lebanese women using microarray technologies. Gene-expression profiles of 94 fresh breast tissue samples (84 cancerous/10 non-tumor adjacent samples) were analyzed using GeneChip Human Genome U133 Plus 2.0 arrays. Quantitative real-time PCR was employed to validate candidate genes. Differentially expressed genes between breast cancer and non-tumor tissues were screened. Significant differences in gene expression were established for COL11A1/COL10A1/MMP1/COL6A6/DLK1/S100P/CXCL11/SOX11/LEP/ADIPOQ/OXTR/FOSL1/ACSBG1 and C21orf37. Pathways/diseases representing these genes were retrieved and linked using PANTHER^®/Pathway Studio^®. Many of the deregulated genes are associated with extracellular matrix, inflammation, angiogenesis, metastasis, differentiation, cell proliferation and tumorigenesis. Characteristics of breast cancers in Lebanese were compared to those of women from Western populations to explain why breast cancer is more aggressive and presents a decade earlier in Lebanese victims. Delineating molecular mechanisms of breast cancer in Lebanese women led to key genes which could serve as potential biomarkers and/or novel drug targets for breast cancer.

The mechanism of adenosine-mediated activation of lncRNA MEG3 and its antitumor effects in human hepatoma cells

Long non-coding RNA MEG3 is suggested to function as a tumor suppressor. However, the activation mechanism of MEG3 is still not well understood and data are not available on its role under adenosine-induced apoptosis. In this study, HepG2 cells were treated with adenosine or 5-Aza‑cdR. Methylation status of MEG3 promoter was detected by methylation specific PCR (MSP) and MEG3 expression was determined by qRT-PCR. PcDNA3.1-MEG3 recombinant plasmid was constructed and transfected to hepatoma HepG2 and Huh7 cells. Cell growth, morphological changes, cell-cycle distribution and apoptosis were analyzed by MTT assay, fluorescence microscopy and flow cytometry. The mRNA and protein expression levels were detected by qRT-PCR and western blot analysis. MEG3 binding proteins were screened by the improved MS2 biotin tagged RNA affinity purification method. The co-expression network of MEG3 was generated by GO analysis and ILF3 was identified as MEG3 binding protein by RNA pulldown and western blot analysis. Both adenosine and 5-Aza-CdR increased MEG3 mRNA expression and the CpG island of MEG3 gene in HepG2 cells was typical hypermethylation. Ectopic expression of MEG3 inhibited hepatoma cell growth in a time-dependent manner, resulted in cell cycle arrest and induced apoptosis. Ectopic expression of MEG3 increased p53, caspase-3 mRNA and protein levels, decreased MDM2 and cyclin D1 mRNA and protein levels, as well as ILF3 protein expression in HepG2 cells. These findings are the first to identify that adenosine increases MEG3 expression by inhibition of DNA methylation and its antitumor effects is involved in MEG3 activation. ILF3 may participate in the anticancer regulation of MEG3 by interacting with MEG3.

The impact of oil spill to lung health--Insights from an RNA-seq study of human airway epithelial cells

The Deepwater Horizon oil spill (BP oil spill) in the Gulf of Mexico was a unique disaster event, where a huge amount of oil spilled from the sea bed and a large volume of dispersants were applied to clean the spill. The operation lasted for almost 3 months and involved >50,000 workers. The potential health hazards to these workers may be significant as previous research suggested an association of persistent respiratory symptoms with exposure to oil and oil dispersants. To reveal the potential effects of oil and oil dispersants on the respiratory system at the molecular level, we evaluated the transcriptomic profile of human airway epithelial cells grown under treatment of crude oil, the dispersants Corexit 9500 and Corexit 9527, and oil-dispersant mixtures. We identified a very strong effect of Corexit 9500 treatment, with 84 genes (response genes) differentially expressed in treatment vs. control samples. We discovered an interactive effect of oil-dispersant mixtures; while no response gene was found for Corexit 9527 treatment alone, cells treated with Corexit 9527+oil mixture showed an increased number of response genes (46 response genes), suggesting a synergic effect of 9527 with oil on airway epithelial cells. Through GO (gene ontology) functional term and pathway-based analysis, we identified upregulation of gene sets involved in angiogenesis and immune responses and downregulation of gene sets involved in cell junctions and steroid synthesis as the prevailing transcriptomic signatures in the cells treated with Corexit 9500, oil, or Corexit 9500+oil mixture. Interestingly, these key molecular signatures coincide with important pathological features observed in common lung diseases, such as asthma, cystic fibrosis and chronic obstructive pulmonary disease. Our study provides mechanistic insights into the detrimental effects of oil and oil dispersants to the respiratory system and suggests significant health impacts of the recent BP oil spill to those people involved in the cleaning operation.