Inhibitor of DNA Binding Protein 3 (ID3) and Nuclear Respiratory Factor 1 (NRF1) Mediated Transcriptional Gene Signatures are Associated with the Severity of Cerebral Amyloid Angiopathy.

Cerebral amyloid angiopathy (CAA) is a degenerative vasculopathy. We have previously shown that transcription regulating proteins- inhibitor of DNA binding protein 3 (ID3) and the nuclear respiratory factor 1 (NRF1) contribute to vascular dysregulation. In this study, we have identified sex specific ID3 and NRF1-mediated gene networks in CAA patients diagnosed with Alzheimer's Disease (AD). High expression of ID3 mRNA coupled with low NRF1 mRNA levels was observed in the temporal cortex of men and women CAA patients. Low NRF1 mRNA expression in the temporal cortex was found in men with severe CAA. High ID3 expression was found in women with the genetic risk factor APOE4. Low NRF1 expression was also associated with APOE4 in women with CAA. Genome wide transcriptional activity of both ID3 and NRF1 paralleled their mRNA expression levels. Sex specific differences in transcriptional gene signatures of both ID3 and NRF1 were observed. These findings were further corroborated by Bayesian machine learning and the GeNIe simulation models. Dynamic machine learning using a Monte Carlo Markov Chain (MCMC) gene ordering approach revealed that ID3 was associated with disease severity in women. NRF1 was associated with CAA and severity of this disease in men. These findings suggest that aberrant ID3 and NRF1 activity presumably plays a major role in the pathogenesis and severity of CAA. Further analyses of ID3- and NRF1-regulated molecular drivers of CAA may provide new targets for personalized medicine and/or prevention strategies against CAA.

Endocrine Disrupting Chemicals Influence Hub Genes Associated with Aggressive Prostate Cancer.

Prostate cancer (PCa) is one of the most frequently diagnosed cancers among men in the world. Its prevention has been limited because of an incomplete understanding of how environmental exposures to chemicals contribute to the molecular pathogenesis of aggressive PCa. Environmental exposures to endocrine-disrupting chemicals (EDCs) may mimic hormones involved in PCa development. This research aims to identify EDCs associated with PCa hub genes and/or transcription factors (TF) of these hub genes in addition to their protein-protein interaction (PPI) network. We are expanding upon the scope of our previous work, using six PCa microarray datasets, namely, GSE46602, GSE38241, GSE69223, GSE32571, GSE55945, and GSE26126, from the NCBI/GEO, to select differentially expressed genes based on |log2FC| (fold change) ≥ 1 and an adjusted p-value < 0.05. An integrated bioinformatics analysis was used for enrichment analysis (using DAVID.6.8, GO, KEGG, STRING, MCODE, CytoHubba, and GeneMANIA). Next, we validated the association of these PCa hub genes in RNA-seq PCa cases and controls from TCGA. The influence of environmental chemical exposures, including EDCs, was extrapolated using the chemical toxicogenomic database (CTD). A total of 369 overlapping DEGs were identified associated with biological processes, such as cancer pathways, cell division, response to estradiol, peptide hormone processing, and the p53 signaling pathway. Enrichment analysis revealed five up-regulated (NCAPG, MKI67, TPX2, CCNA2, CCNB1) and seven down-regulated (CDK1, CCNB2, AURKA, UBE2C, BUB1B, CENPF, RRM2) hub gene expressions. Expression levels of these hub genes were significant in PCa tissues with high Gleason scores ≥ 7. These identified hub genes influenced disease-free survival and overall survival of patients 60-80 years of age. The CTD studies showed 17 recognized EDCs that affect TFs (NFY, CETS1P54, OLF1, SRF, COMP1) that are known to bind to our PCa hub genes, namely, NCAPG, MKI67, CCNA2, CDK1, UBE2C, and CENPF. These validated differentially expressed hub genes can be potentially developed as molecular biomarkers with a systems perspective for risk assessment of a wide-ranging list of EDCs that may play overlapping and important role(s) in the prognosis of aggressive PCa.

Brain infiltration of breast cancer stem cells is facilitated by paracrine signaling by inhibitor of differentiation 3 to nuclear respiratory factor 1.

Treatment options for brain metastatic breast cancer are limited because the molecular mechanism for how breast cancer cells infiltrate the brain is not fully understood. For breast tumors to metastasize to the brain first, cells need to detach from the primary tumor, enter in the blood circulation, survive within the microvascular niche, and then cross the blood-brain barrier (BBB) to colonize into the brain. It is critical to understand how breast cancer cells transmigrate through the BBB to prevent brain metastasis. Nuclear respiratory factor 1 (NRF1) transcription factor has been reported to be highly active in several human cancers and its aberrant expression facilitates in the acquisition of breast cancer stem cells (BCSCs). Inhibitor of differentiation protein 3 (ID3), a transcription regulating protein, induces pluripotent endothelial stem cells (ESCs). Herein, we investigated if NRF1-induced BCSCs could cross a BBB model and guiding of BCSCs by ID3-induced ESCs across the BBB. BCSCs and ESCs were subjected to functional gain/loss experiments to determine if NRF1/ID3 contributed to lineage-specific BCSCs organ entry. First, we tested whether NRF1 promoted migration of breast cancer using a BBB model consisting of BCSCs or MDA-MB231 cells, brain endothelial cell layer, and astrocytes. NRF1 overexpression increased the propensity for BCSCs and NRF1-induced MDA-MB231 cells to adhere to brain endothelial cells and migrate across a human BBB model. Increased adhesion of NRF1-induced BCSCs to ESCsID3 was detected. NRF1-induced BCSCs crossed through the BBB model and this was promoted by ESCsID3. We also showed that environmental relevant exposure to PCBs (PCB153 and PCB77) produced differential effects. Treatment with PCB153 showed increased growth of NRF1-induced BCSCs tumor spheroids and increased in vivo migration of ESCsID3. Exosomal ID3 released from endothelial cells also supported the growth of NRF1-induced BCSCs and provide the basis for paracrine effects by ESCsID3 associated with breast tumors. Xenograft experiments showed that ID3 overexpressing brain ESCs not only supported the growth of BCSC tumor spheroids but guided them to the neural crest in zebrafish. These findings show for the first time a novel role for ID3 and NRF1 by which ESCsID3 help guide BCSCsNRF1 to distant metastatic sites where they most likely facilitate the colonization, survival, and proliferation of BCSCs. This knowledge is important for pre-clinical testing of NRF1/ID3 modifying agents to prevent the spread of breast cancer to the brain.

Nuclear respiratory factor 1 transcriptomic signatures as prognostic indicators of recurring aggressive mesenchymal glioblastoma and resistance to therapy in White American females.

PURPOSE: The mechanisms contributing to recurrence of glioblastoma (GBM), an aggressive neuroepithelial brain tumor, remain unknown. We have recently shown that nuclear respiratory factor 1 (NRF1) is an oncogenic transcription factor and its transcriptional activity is associated with the progression and prognosis of GBM. Herein, we extend our efforts to (1) identify influential NRF1-driven gene and microRNA (miRNA) expression for the aggressiveness of mesenchymal GBM; and (2) understand the molecular basis for its poor response to therapy. METHODS: Clinical data and RNA-Seq from four independent GBM cohorts were analyzed by Bayesian Network Inference with Java Objects (BANJO) and Markov chain Monte Carlo (MCMC)-based gene order to identify molecular drivers of mesenchymal GBM as well as prognostic indicators of poor response to radiation and chemotherapy. RESULTS: We are the first to report sex-specific NRF1 motif enriched gene signatures showing increased susceptibility to GBM. Risk estimates for GBM were increased by greater than 100-fold with the joint effect of NRF1-driven gene signatures-CDK4, DUSP6, MSH2, NRF1, and PARK7 in female GBM patients and CDK4, CASP2, H6PD, and NRF1 in male GBM patients. NRF1-driven causal Bayesian network genes were predictive of poor survival and resistance to chemoradiation in IDH1 wild-type mesenchymal GBM patients. NRF1-regulatable miRNAs were also associated with poor response to chemoradiation therapy in female IDH1 wild-type mesenchymal GBM. Stable overexpression of NRF1 reprogramed human astrocytes into neural stem cell-like cells expressing SOX2 and nestin. These cells differentiated into neurons and form tumorospheroids. CONCLUSIONS: In summary, our novel discovery shows that NRF1-driven causal genes and miRNAs involved in cancer cell stemness and mesenchymal features contribute to cancer aggressiveness and recurrence of aggressive therapy-resistant glioblastoma.

Environmental Phenol and Paraben Exposure Risks and Their Potential Influence on the Gene Expression Involved in the Prognosis of Prostate Cancer.

Prostate cancer (PCa) is one of the leading malignant tumors in US men. The lack of understanding of the molecular pathology on the risk of food supply chain exposures of environmental phenol (EP) and paraben (PB) chemicals limits the prevention, diagnosis, and treatment options. This research aims to utilize a risk assessment approach to demonstrate the association of EP and PB exposures detected in the urine samples along with PCa in US men (NHANES data 2005−2015). Further, we employ integrated bioinformatics to examine how EP and PB exposure influences the molecular pathways associated with the progression of PCa. The odds ratio, multiple regression model, and Pearson coefficients were used to evaluate goodness-of-fit analyses. The results demonstrated associations of EPs, PBs, and their metabolites, qualitative and quantitative variables, with PCa. The genes responsive to EP and PB exposures were identified using the Comparative Toxicogenomic Database (CTD). DAVID.6.8, GO, and KEGG enrichment analyses were used to delineate their roles in prostate carcinogenesis. The plug-in CytoHubba and MCODE completed identification of the hub genes in Cytoscape software for their roles in the PCa prognosis. It was then validated by using the UALCAN database by evaluating the expression levels and predictive values of the identified hub genes in prostate cancer prognosis using TCGA data. We demonstrate a significant association of higher levels of EPs and PBs in the urine samples, categorical and numerical confounders, with self-reported PCa cases. The higher expression levels of the hub genes (BUB1B, TOP2A, UBE2C, RRM2, and CENPF) in the aggressive stages (Gleason score > 8) of PCa tissues indicate their potential role(s) in the carcinogenic pathways. Our results present an innovative approach to extrapolate and validate hub genes responsive to the EPs and PBs, which may contribute to the severity of the disease prognosis, especially in the older population of US men.

Is Mycobacterium tuberculosis carcinogenic to humans?

We highlight the ability of the tuberculosis (TB) causing bacterial pathogen, Mycobacterium tuberculosis (Mtb), to induce key characteristics that are associated with established IARC classified Group 1 and Group 2A carcinogenic agents. There is sufficient evidence from epidemiological case-control, cohort and meta-analysis studies of increased lung cancer (LC) risk in pre-existing/active/old TB cases. Similar to carcinogens and other pathogenic infectious agents, exposure to aerosol-containing Mtb sprays in mice produce malignant transformation of cells that result in squamous cell carcinoma. Convincing, mechanistic data show several characteristics shared between TB and LC which include chronic inflammation, genomic instability and replicative immortality, just to name a few cancer hallmarks. These hallmarks of cancer may serve as precursors to malignant transformation. Together, these findings form the basis of our postulate that Mtb is a complete human pulmonary carcinogen. We also discuss how Mtb may act as both an initiating agent and promoter of tumor growth. Forthcoming experimental studies will not only serve as proof-of-concept but will also pivot our understanding of how to manage/treat TB cases as well as offer solutions to clinical conundrums of TB lesions masquerading as tumors. Clinical validation of our concept may also help pave the way for next generation personalized medicine for the management of pulmonary TB/cancer particularly for cases that are not responding well to conventional chemotherapy or TB drugs.

Computational modeling and bioinformatic analyses of functional mutations in drug target genes in Mycobacterium tuberculosis.

Tuberculosis (TB) continues to be the leading cause of deaths due to its persistent drug resistance and the consequent ineffectiveness of anti-TB treatment. Recent years witnessed huge amount of sequencing data, revealing mutations responsible for drug resistance. However, the lack of an up-to-date repository remains a barrier towards utilization of these data and identifying major mutations-associated with resistance. Amongst all mutations, non-synonymous mutations alter the amino acid sequence of a protein and have a much greater effect on pathogenicity. Hence, this type of gene mutation is of prime interest of the present study. The purpose of this study is to develop an updated database comprising almost all reported substitutions within the Mycobacterium tuberculosis (M.tb) drug target genes rpoB, inhA, katG, pncA, gyrA and gyrB. Various bioinformatics prediction tools were used to assess the structural and biophysical impacts of the resistance causing non-synonymous single nucleotide polymorphisms (nsSNPs) at the molecular level. This was followed by evaluating the impact of these mutations on binding affinity of the drugs to target proteins. We have developed a comprehensive online resource named MycoTRAP-DB (Mycobacterium tuberculosis Resistance Associated Polymorphisms Database) that connects mutations in genes with their structural, functional and pathogenic implications on protein. This database is accessible at http://139.59.12.92. This integrated platform would enable comprehensive analysis and prioritization of SNPs for the development of improved diagnostics and antimycobacterial medications. Moreover, our study puts forward secondary mutations that can be important for prognostic assessments of drug-resistance mechanism and actionable anti-TB drugs.

The M. tuberculosis Rv1523 Methyltransferase Promotes Drug Resistance Through Methylation-Mediated Cell Wall Remodeling and Modulates Macrophages Immune Responses.

The acquisition of antibiotics resistance is a major clinical challenge limiting the effective prevention and treatment of the deadliest human infectious disease tuberculosis. The molecular mechanisms by which initially Mycobacterium tuberculosis (M.tb) develop drug resistance remain poorly understood. In this study, we report the novel role of M.tb Rv1523 MTase in the methylation of mycobacterial cell envelope lipids and possible mechanism of its contribution in the virulence and drug resistance. Initial interactome analyses predicted association of Rv1523 with proteins related to fatty acid biosynthetic pathways. This promoted us to investigate methylation activity of Rv1523 using cell wall fatty acids or lipids as a substrate. Rv1523 catalyzed the transfer of methyl group from SAM to the cell wall components of mycobacterium. To investigate further the in vivo methylating role of Rv1523, we generated a recombinant Mycobacterium smegmatis strain that expressed the Rv1523 gene. The M. smegmatis strain expressing Rv1523 exhibited altered cell wall lipid composition, leading to an increased survival under surface stress, acidic condition and resistance to antibiotics. Macrophages infected with recombinant M. smegmatis induced necrotic cell death and modulated the host immune responses. In summary, these findings reveal a hitherto unknown role of Rv1523 encoded MTase in cell wall remodeling and modulation of immune responses. Functional gain of mycolic acid Rv1523 methyltransferase induced virulence and resistance to antibiotics in M. smegmatis. Thus, mycolic acid methyltransferase may serve as an excellent target for the discovery and development of novel anti-TB agents.

Causal Bayesian gene networks associated with bone, brain and lung metastasis of breast cancer.

Using a machine learning method, this study aimed to identify unique causal networks of genes associated with bone, brain, and lung metastasis of breast cancer. Bayesian network analysis identified differentially expressed genes in primary breast cancer tissues, in bone, brain, and lung breast cancer metastatic tissues, and the clinicopathological features of patients obtained from the Gene Expression Omnibus microarray datasets. We evaluated the causal Bayesian networks of breast metastasis to distant sites (bone, brain, or lung) by (i) measuring how well the structures of each specific type of breast cancer metastasis fit the data, (ii) comparing the structures with known experimental evidence, and (iii) reporting predictive capabilities of the structures. We report for the first time that the molecular gene signatures are specific to the different types of breast cancer metastasis. Several genes, including CHPF, ARC, ANGPTL4, NR2E1, SH2D1A, CTSW, POLR2J4, SPTLC1, ILK, ALDH3B1, PDE6A, SCTR, ADM, HEY1, KCNF1, and UVRAG, were found to be predictors of the risk for site-specific metastasis of breast cancer. Expression of POLR2JA, SPTLC1, ILK, ALDH3B1, and the estrogen receptor was significantly associated with breast cancer bone metastasis. Expression of PDE6A and NR2E1 was causally linked to breast cancer brain metastasis. Expression of HEY1, KCNF1, UVRAG, and the estrogen and progesterone receptors was strongly associated with breast cancer lung metastasis. The causal Bayesian network structures of these genes identify potential interactions among the genes in distant metastases of breast cancer, including to the bone, brain, and lung, and may serve as target candidates for treatment of breast cancer metastasis.

Sensitivity to differential NRF1 gene signatures contributes to breast cancer disparities.

PURPOSE: Nuclear respiratory factor 1 (NRF1) drives estrogen-dependent breast tumorigenesis. Herein we examined the impact of NRF1 activity on the aggressiveness and disparate molecular signature of breast cancer in Black, White, Asian, and Hispanic women. METHODS: NRF1 activity by transcription factor target enrichment analysis and causal NRF1-target gene signatures by Bayesian Network Inference with Java Objects (BANJO) and Markov Chain Monte Carlo (MCMC)-based gene order were examined in The Cancer Genome Atlas (TCGA) breast cancer cohorts. RESULTS: We are the first to report increased NRF1 activity based on its differential effects on genome-wide transcription associated with luminal A and B, HER2+ and triple-negative (TN) molecular subtypes of breast cancer in women of different race/ethnicity. We observed disparate NRF1 motif-containing causal gene signatures unique to Black, White, Asian, and Hispanic women for luminal A breast cancer. Further gene order searches showed molecular heterogeneity of each subtype of breast cancer. Six different gene order sequences involving CDK1, HMMR, CCNB2, CCNB1, E2F1, CREB3L4, GTSE1, and LMNB1 with almost equal weight predicted the probability of luminal A breast cancer in whites. Three different gene order sequences consisting of CCNB1 and GTSE1, and CCNB1, LMNB1, CDK1 or CASP3 predicted almost 100% probability of luminal B breast cancer in whites; CCNB1 and LMNB1 or GTSE predicted 100% HER2+ breast cancer in whites. GTSE1 and TUBA1C combined together predicted 100% probability of developing TNBC in whites; NRF1, TUBA1B and BAX with EFNA4, and NRF1 and BTRC predicated 100% TNBC in blacks. High expressor NRF1 TN breast tumors showed unfavorable prognosis with a high risk of breast cancer death in white women. CONCLUSION: Our findings showed how sensitivity to high NRF1 transcriptional activity coupled with its target gene signatures contribute to racial differences in luminal A and TN breast cancer subtypes. This knowledge may be useful in personalized intervention to prevent and treat this clinically challenging problem.

Environmental DNA and RNA as Records of Human Exposome, Including Biotic/Abiotic Exposures and Its Implications in the Assessment of the Role of Environment in Chronic Diseases.

Most of environment-related diseases often result from multiple exposures of abiotic and/or biotic stressors across various life stages. The application of environmental DNA/RNA (eDNA/eRNA) to advance ecological understanding has been very successfully used. However, the eminent extension of eDNA/eRNA-based approaches to estimate human exposure to biotic and/or abiotic environmental stressors to understand the environmental causes of chronic diseases has yet to start. Here, we introduce the potential of eDNA/eRNA for bio-monitoring of human exposome and health effects in the real environmental or occupational settings. This review is the first of its kind to discuss how eDNA/eRNA-based approaches can be applied for assessing the human exposome. eDNA-based exposome assessment is expected to rely on our ability to capture the genome- and epigenome-wide signatures left behind by individuals in the indoor and outdoor physical spaces through shedding, excreting, etc. Records of eDNA/eRNA exposome may reflect the early appearance, persistence, and presence of biotic and/or abiotic-exposure-mediated modifications in these nucleic acid molecules. Functional genome- and epigenome-wide mapping of eDNA offer great promise to help elucidate the human exposome. Assessment of longitudinal exposure to physical, biological, and chemical agents present in the environment through eDNA/eRNA may enable the building of an integrative causal dynamic stochastic model to estimate environmental causes of human health deficits. This model is expected to incorporate key biological pathways and gene networks linking individuals, their geographic locations, and random multi-hits of environmental factors. Development and validation of monitoring of eDNA/eRNA exposome should seriously be considered to introduce into safety and risk assessment and as surrogates of chronic exposure to environmental stressors. Here we highlight that eDNA/eRNA reflecting longitudinal exposure of both biotic and abiotic environmental stressors may serve as records of human exposome and discuss its application as molecular tools for understanding the toxicogenomics basis of environment-related health deficits.

Nuclear Respiratory Factor 1 (NRF1) Transcriptional Activity-Driven Gene Signature Association with Severity of Astrocytoma and Poor Prognosis of Glioblastoma.

Despite tremendous progress in understanding the pathobiology of astrocytoma, major gaps remain in our knowledge of the molecular basis underlying the aggressiveness of high-grade astrocytoma (glioblastoma - GBM). Recently, we and others have shown nuclear respiratory factor 1 (NRF1) transcription factor being highly active in human cancers, but its role in astrocytoma remains unknown. Therefore, the purpose of this study was to uncover the role of NRF1 in the progression of GBM. NRF1 has higher mRNA expression and transcription factor activity in astrocytoma compared to non-tumor brain tissue. NRF1 activity also correlated with the aggressiveness of cancer. Increased NRF1 TF activity coupled with overexpression of RHOG was associated with poor survival of GBM patients. NRF1 activity was associated with transcriptomic signatures of neurogenesis, cell stemness, epithelial-mesenchymal transition and cell cycle progression. Overexpression of CDK4, AKT1, APAF1, HDAC1, NBN, TGFB1, & TNFRSF1A and downregulation of CASP3, IL7, STXBP1 and OPA1 predicted GBM malignancy in high expressors of NRF1 activity. Increased expression of the NRF1 motif containing genes, H6PD, NAT10, NBEAL2, and RNF19B predicted poor survival of IDH1 wild-type GBM patients. Poor survival outcomes and resistance to Temozolomide therapy were associated with higher NRF1 expression including its targets - LDHA, ZMAT3, NSUN2, ARMC5, NDEL1, CLPTM1L, ALKBH5, YIPF5, PPP2CA, and TFG. These findings suggest that aberrant NRF1 activity may contribute to the pathogenesis of GBM and severity of astrocytoma. Further analyses of NRF1 gene signatures will pave the way for next generation targeted therapies and drug combination strategies for GBM patients.

Integrated Chip-Seq and RNA-Seq Data Analysis Coupled with Bioinformatics Approaches to Investigate Regulatory Landscape of Transcription Modulators in Breast Cancer Cells.

The objective of this chapter is to describe step-by-step bioinformatics and functional genomics solutions for analyzing ChIP-Seq and RNA-Seq data for understanding the regulatory mechanisms of chromatin modifiers and transcription factors that can drive pathogenesis of chronic complex human diseases, such as cancer. Here we have used two transcription regulatory proteins: nuclear respiratory factor 1 (NRF1) and inhibitor of differentiation protein 3 (ID3) for ChIP-Seq and RNA-Seq data as examples for discussing the importance of selecting the appropriate computational analysis methods, software, and parameters for the processing of raw data as well as their integrative regulatory landscape analysis to obtain accurate and reliable results. Both ChIP-Seq and RNA-Seq analytic methodologies are used as instructional examples to identify NRF1 or ID3 binding to the promoters and enhancers in the genome and their effects on the activity as well as to discover target genes that can drive breast cancer.

Nuclear Respiratory Factor 1 Acting as an Oncoprotein Drives Estrogen-Induced Breast Carcinogenesis.

We have previously shown nuclear respiratory factor 1 (NRF1)-mediated transcriptional programming of mitobiogenesis contributes to estrogen-induced breast cancer through modulating cell cycle progression. In this study, we report a new role of NRF1 that goes beyond that of programming mitobiogenesis. Specifically, we report a novel oncogenic function of NRF1 supporting its causative role in breast cancer development and progression. The gain of NRF1 and/or treatment with 17ß-estradiol (E2) produced heterogeneous breast cancer stem cell (BCSC)-like subsets composed of more than 10 distinct cell sub-populations. Flow sorting combined with confocal imaging of markers for pluripotency, epithelial mesenchymal transition (EMT), and BCSCs phenotypically confirmed that the BCSC-like subset arise from cell re-programming. Thus, we determined the molecular actions of NRF1 on its target gene CXCR4 because of its known role in the acquisition of the BCSC-like subset through EMT. CXCR4 was activated by NRF1 in a redox-dependent manner during malignant transformation. An NRF1-induced BCSC-like subset was able to form xenograft tumors in vivo, while inhibiting transcription of CXCR4 prevented xenograft tumor growth. Consistent with our observation of NRF1-driven breast tumorigenesis in the experimental model, higher protein levels of NRF1 were also found in human breast cancer tissue specimens. This highly novel role of NRF1 in the stochastic acquisition of BCSC-like subsets and their progression to a malignant phenotype may open an entirely new research direction targeting NRF1 signaling in invasive breast cancer. Our discovery of targeting transcriptional activation of CXCR4 to inhibit NRF1-induced oncogenic transformation provides a mechanistic explanation for estrogen-dependent breast carcinogenesis and opens new avenues in strategic therapeutics to fight breast cancer.

NRF1 motif sequence-enriched genes involved in ER/PR -ve HER2 +ve breast cancer signaling pathways.

Nuclear respiratory factor 1 (NRF1) transcription factor has recently been shown to control breast cancer progression. However, mechanistic aspects by which NRF1 may contribute to susceptibility to different breast tumor subtypes are still not fully understood. Since transcriptional control of NRF1 seems to be dependent on epidermal growth factor receptor signaling, herein, we investigated the role of NRF1 in estrogen receptor/progesterone receptor negative, but human epidermal growth factor receptor 2-positive (ER/PR -ve HER2 +ve) breast cancer. We found that both mRNA and protein levels of NRF1 and its transcriptional activity were significantly higher in ER/PR -ve HER2 +ve breast cancer samples compared to normal breast tissues. This was consistent with our observation of higher NRF1 protein expression in the experimental model of HER2+ breast cancer brain metastasis. To identify network-based pathways involved in the susceptibility to the ER/PR -ve HER2 +ve breast cancer subtype, the NRF1 transcriptional regulatory genome-wide landscape was analyzed using the approach consisting of a systematic integration of ChIP DNA-seq, RNA-Microarray, NRF1 protein-DNA motif binding, signal pathway analysis, and Bayesian machine learning. Our findings show that a high percentage of known HER2+ breast cancer susceptibility genes, including EGFR, IGFR, and E2F1, are under transcriptional control of NRF1. Promoters of several genes from the KEGG HER2+ breast cancer pathway and 11 signaling pathways linked to 6 hallmarks of cancer contain the NRF1 motif. By pathway analysis, key breast cancer hallmark genes of epithelial-mesenchymal transition, stemness, cell apoptosis, cell cycle regulation, chromosomal integrity, and DNA damage/repair were highly enriched with NRF1 motifs. In addition, we found using Bayesian network-based machine learning that 30 NRF1 motif-enriched genes including growth factor receptors-FGFR1, IGF1R; E2Fs transcription factor family-E2F1, E2F3; MAPK pathway-SHC2, GRB2, MAPK1; PI3K-AKT-mTOR signaling pathway-PIK3CD, PIK3R1, PIK3R3, RPS6KB2; WNT signaling pathway-WNT7B, DLV1, DLV2, GSK3B, NRF1, and DDB2, known for its role in DNA repair and involvement in early events associated with metastatic progression of breast cancer cells, were associated with HER2-amplified breast cancer. Machine learning search further revealed that the likelihood of HER2-positive breast cancer is almost 100% in a patient with the high NRF1 expression combined with expression patterns of high E2F3, GSK3B, and MAPK1, low or no change in E2F1 and FGFR1, and high or no change in PIK3R3. In summary, our findings suggest novel roles of NRF1 and its regulatory networks in susceptibility to the ER/PR -ve HER2 +ve aggressive breast cancer subtype. Clinical confirmation of our machine learned Bayesian networks will have significant impact on our understanding of the role of NRF1 as a valuable biomarker for breast cancer diagnosis and prognosis as well as provide strong rationale for future studies to develop NRF1 signaling-based therapeutics to target HER2+ breast cancer.

Interplay between NRF1, E2F4 and MYC transcription factors regulating common target genes contributes to cancer development and progression.

BACKGROUND: Nuclear respiratory factor 1 (NRF1), historically perceived as a protein regulating genes controlling mitochondrial biogenesis, is now widely recognized as a multifunctional protein and as a key player in the transcriptional modulation of genes implicated in various cellular functions. Here, we present emerging data supporting novel roles of NRF1 in cancer development and progression through its interplay with the transcription factors E2F4 and MYC. To identify common human NRF1, E2F4 and MYC target genes, we analyzed the Encyclopedia of DNA Elements (ENCODE) NRF1 ChIP-Seq data. By doing so, we identified 9253 common target genes with NRF1, E2F4 and MYC binding motifs. NRF1 binding motifs were found to be present in genes operating in signaling pathways governing all hallmarks of malignant transformation and progression, including proliferation, invasion, self-renewal and apoptosis. CONCLUSIONS: In addition to controlling mitochondrial biogenesis NRF1, in conjunction with E2F4 and MYC, may play a critical role in the acquisition of human cancer characteristics. Additionally, NRF1 may orchestrate both MYC and E2F4 to regulate common target genes linked to multiple networks in the development and progression of cancer. A comprehensive understanding of this dynamic interplay will set the stage, not only for the design of novel treatment strategies, but also for the discovery of pan-cellular transcription factor regulatory strategies to predict cancer risk, therapy response and patient prognosis.

Environmental estrogen-like endocrine disrupting chemicals and breast cancer.

BACKGROUND: Estrogen-mimicking endocrine disruptors (EEDs) such as polychlorinated biphenyls (PCBs), bisphenol A (BPA), and phthalates have been found ubiquitously throughout our environment. Although exposure to EEDs has the ability to interfere with endocrine control of reproductive function and development in both humans and wildlife, inconsistent reports have made it difficult to draw conclusions concerning the hypothesized increased risk of breast cancer associated with EEDs. OBJECTIVES: The purpose of this study was to examine the cross-sectional relationship between exposure to PCBs, BPA or phthalates; and risk of breast cancer in U.S. women using the Centers for Disease Control and Prevention's National Health and Nutrition Examination Survey (NHANES) data between 1999 and 2004. METHODS: We analyzed data from female participants (20 years of age and older) collected by NHANES between 1999 and 2004 for exposure assessment based on lipid adjusted serum levels of 6 individual PCB congeners (PCB 074, 099, 118, 138, 153, and 180), the sum of dioxin-like PCBs (074 and 118), and the sum of non-dioxin-like PCBs (099 + 138 + 153 + 187). Levels of urinary BPA and seven phthalate metabolites mono-n-butyl phthalate (MnBP), mono-isobutyl phthalate (MiBP), mono-ethyl phthalate (MEP), mono-(3-caroxypropyl) phthalate (MCPP), mono-benzyl phthalate (MZP), and three metabolites of di (2-ehtylhexyl) phthalate (DEHP): [mono-2-ethylhexyl phthalate (MEHP), mono-(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), and mono-(2-ethyl-5-oxohexyl) phthalate (MEOHP)] were obtained from the 2003-2010 yearly survey cycles in participants aged 6 years and older. Assessments of EEDs or their metabolites were analyzed in conjunction with medical and reproductive health questionnaire data. Age, race/ethnicity, age at menarche, body mass index (BMI; kg/m2), and lactation were considered as potential confounders in our final models. Geometric means (GM) were calculated to compare PCB, BPA or phthalate concentrations in women who self-reported a breast cancer diagnosis versus women who self-reported never being diagnosed with breast cancer. Logistic regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (CI) for the association between PCB, BPA or phthalate measurements and breast cancer. RESULTS: In age, race/ethnicity, and BMI adjusted models, PCB138 was the only congener found to be significantly associated with breast cancer [OR of 3.16; 95% CI: 1.14-8.76]. We also found the sum of non-dioxin-like PCBs to be significantly associated with breast cancer [OR of 1.14; 95% CI: 1.00-1.29]. Risk of breast cancer, however, was not found to be significantly associated with phthalate, phthalate metabolites, and BPA in unadjusted or adjusted logistic regression models. CONCLUSIONS: Our results suggest a link between environmental exposures to PCB 138 and breast cancer. There were no significant associations between phthalates or BPA and breast cancers. These findings should be interpreted with caution because of the use of cross-sectional self-reported data and a small sample size of breast cancer subjects. Nonetheless, our finding emphasizes a need of comprehensive environmental molecular epidemiologic study to determine the potential role of environmental exposures to PCBs, phthalates, and BPA in the development of breast cancer.

Estrogenic Endocrine Disrupting Chemicals Influencing NRF1 Regulated Gene Networks in the Development of Complex Human Brain Diseases.

During the development of an individual from a single cell to prenatal stages to adolescence to adulthood and through the complete life span, humans are exposed to countless environmental and stochastic factors, including estrogenic endocrine disrupting chemicals. Brain cells and neural circuits are likely to be influenced by estrogenic endocrine disruptors (EEDs) because they strongly dependent on estrogens. In this review, we discuss both environmental, epidemiological, and experimental evidence on brain health with exposure to oral contraceptives, hormonal therapy, and EEDs such as bisphenol-A (BPA), polychlorinated biphenyls (PCBs), phthalates, and metalloestrogens, such as, arsenic, cadmium, and manganese. Also we discuss the brain health effects associated from exposure to EEDs including the promotion of neurodegeneration, protection against neurodegeneration, and involvement in various neurological deficits; changes in rearing behavior, locomotion, anxiety, learning difficulties, memory issues, and neuronal abnormalities. The effects of EEDs on the brain are varied during the entire life span and far-reaching with many different mechanisms. To understand endocrine disrupting chemicals mechanisms, we use bioinformatics, molecular, and epidemiologic approaches. Through those approaches, we learn how the effects of EEDs on the brain go beyond known mechanism to disrupt the circulatory and neural estrogen function and estrogen-mediated signaling. Effects on EEDs-modified estrogen and nuclear respiratory factor 1 (NRF1) signaling genes with exposure to natural estrogen, pharmacological estrogen-ethinyl estradiol, PCBs, phthalates, BPA, and metalloestrogens are presented here. Bioinformatics analysis of gene-EEDs interactions and brain disease associations identified hundreds of genes that were altered by exposure to estrogen, phthalate, PCBs, BPA or metalloestrogens. Many genes modified by EEDs are common targets of both 17 ß-estradiol (E2) and NRF1. Some of these genes are involved with brain diseases, such as Alzheimer's Disease (AD), Parkinson's Disease, Huntington's Disease, Amyotrophic Lateral Sclerosis, Autism Spectrum Disorder, and Brain Neoplasms. For example, the search of enriched pathways showed that top ten E2 interacting genes in AD-APOE, APP, ATP5A1, CALM1, CASP3, GSK3B, IL1B, MAPT, PSEN2 and TNF-underlie the enrichment of the Kyoto Encyclopedia of Genes and Genomes (KEGG) AD pathway. With AD, the six E2-responsive genes are NRF1 target genes: APBB2, DPYSL2, EIF2S1, ENO1, MAPT, and PAXIP1. These genes are also responsive to the following EEDs: ethinyl estradiol (APBB2, DPYSL2, EIF2S1, ENO1, MAPT, and PAXIP1), BPA (APBB2, EIF2S1, ENO1, MAPT, and PAXIP1), dibutyl phthalate (DPYSL2, EIF2S1, and ENO1), diethylhexyl phthalate (DPYSL2 and MAPT). To validate findings from Comparative Toxicogenomics Database (CTD) curated data, we used Bayesian network (BN) analysis on microarray data of AD patients. We observed that both gender and NRF1 were associated with AD. The female NRF1 gene network is completely different from male human AD patients. AD-associated NRF1 target genes-APLP1, APP, GRIN1, GRIN2B, MAPT, PSEN2, PEN2, and IDE-are also regulated by E2. NRF1 regulates targets genes with diverse functions, including cell growth, apoptosis/autophagy, mitochondrial biogenesis, genomic instability, neurogenesis, neuroplasticity, synaptogenesis, and senescence. By activating or repressing the genes involved in cell proliferation, growth suppression, DNA damage/repair, apoptosis/autophagy, angiogenesis, estrogen signaling, neurogenesis, synaptogenesis, and senescence, and inducing a wide range of DNA damage, genomic instability and DNA methylation and transcriptional repression, NRF1 may act as a major regulator of EEDs-induced brain health deficits. In summary, estrogenic endocrine disrupting chemicals-modified genes in brain health deficits are part of both estrogen and NRF1 signaling pathways. Our findings suggest that in addition to estrogen signaling, EEDs influencing NRF1 regulated communities of genes across genomic and epigenomic multiple networks may contribute in the development of complex chronic human brain health disorders.

Integrated Bioinformatics, Environmental Epidemiologic and Genomic Approaches to Identify Environmental and Molecular Links between Endometriosis and Breast Cancer.

We present a combined environmental epidemiologic, genomic, and bioinformatics approach to identify: exposure of environmental chemicals with estrogenic activity; epidemiologic association between endocrine disrupting chemical (EDC) and health effects, such as, breast cancer or endometriosis; and gene-EDC interactions and disease associations. Human exposure measurement and modeling confirmed estrogenic activity of three selected class of environmental chemicals, polychlorinated biphenyls (PCBs), bisphenols (BPs), and phthalates. Meta-analysis showed that PCBs exposure, not Bisphenol A (BPA) and phthalates, increased the summary odds ratio for breast cancer and endometriosis. Bioinformatics analysis of gene-EDC interactions and disease associations identified several hundred genes that were altered by exposure to PCBs, phthalate or BPA. EDCs-modified genes in breast neoplasms and endometriosis are part of steroid hormone signaling and inflammation pathways. All three EDCs-PCB 153, phthalates, and BPA influenced five common genes-CYP19A1, EGFR, ESR2, FOS, and IGF1-in breast cancer as well as in endometriosis. These genes are environmentally and estrogen responsive, altered in human breast and uterine tumors and endometriosis lesions, and part of Mitogen Activated Protein Kinase (MAPK) signaling pathways in cancer. Our findings suggest that breast cancer and endometriosis share some common environmental and molecular risk factors.

Proteomic and Mitochondrial Genomic Analyses of Pediatric Brain Tumors.

The molecular mechanism unraveling why a particular type of pediatric brain tumor (pBT) behaves so differently from child to child or genetic/epigenetic changes in the mitochondrial genome vary from tumor to tumor is not clearly understood. Despite the identification of mitochondrial DNA (mtDNA) mutations in different types of pBT, the contribution of mitochondrial dysfunction-related genes or proteins that are selectively up- or down-regulated in pBT of different types has not been comprehensively examined. In the present study, we combined a 2D DIGE approach with protein identification using MALDI-TOF MS and LC-MS/MS, coupled with mtDNA genomics to screen brain samples for discovering changes in protein expression, and mtDNA sequence variation and mtDNA copy number in the disease states. Two-dimensional gel electrophoresis-based differential proteomic analysis of the brain tumors showed that 116 proteins were found to be up- or down-regulated in brain tumors. Some of the proteins up-regulated in tumors compared to controls were dihydropyrimidinase-like 2; glial fibrillary acidic protein isoform 2; phosphoserine aminotransferase isoform 1; Sirt2 histone deacetylase; and C10orf2 protein, mitochondrial DNA helicase. Proteins down-regulated in brain tumors compared to controls were heat shock protein 90 kDa beta, BiP; guanine nucleotide binding protein (G protein), beta polypeptide 2-like 1, isoform CRA_d; histone H2B.1; neurofilament, light polypeptide 68 kDa; Annexin I; and RAN. These differentially expressed proteins may provide useful information for developing molecular markers of diagnostic or prognostic value. To investigate further the role of mitochondrial dysfunction, we examined the effects of mtDNA copy number, oxidative damage, and mtDNA variants as independent or combined risk factors for the development of pBTs. Bayesian network and mechanistic hierarchical structure Markov Chain Monte Carlo (MCMC) modeling were used to analyze the relationship between these variables. The combined effects of G3196, 9952A, 10006G, 100398G, oxidative mtDNA damages, and mtDNA copy number increased the probability of developing brain tumors in female children by 51 times more when compared to normal incidence of pediatric brain tumors. Comparison of mechanistic structure models also supported the finding that female children who have the wild type allele G3196, variant allele 9952A, variant allele 10006G, variant allele10398A, and high mtDNA copy number had increased probability of developing pediatric brain tumors. Estimation of nuclear genes controlling mitochondrial biogenesis and development of brain, cortical dysplasia, and the effect of the environment using MCMC method showed that these latent variables had a very significant contribution in the development of pediatric brain tumors. Together, these results suggest that mitochondrial genome and tumor proteome are important contributors to brain tumor risk in children, and findings from this study may guide the prospects for targeting mitochondria for therapeutic treatment of childhood brain tumor.