Differential Gene Expression Profiles between N-Terminal Domain and Ligand-Binding Domain Inhibitors of Androgen Receptor Reveal Ralaniten Induction of Metallothionein by a Mechanism Dependent on MTF1

Hormonal therapies for prostate cancer target the androgen receptor (AR) ligand-binding domain (LBD). Clinical development for inhibitors that bind to the N-terminal domain (NTD) of AR has yielded ralaniten and its analogues. Ralaniten acetate is well tolerated in patients at 3600 mgs/day. Clinical trials are ongoing with a second-generation analogue of ralaniten. Binding sites on different AR domains could result in differential effects on AR-regulated gene expression. Here, we provide the first comparison between AR-NTD inhibitors and AR-LBD inhibitors on androgen-regulated gene expression in prostate cancer cells using cDNA arrays, GSEA, and RT-PCR. LBD inhibitors and NTD inhibitors largely overlapped in the profile of androgen-induced genes that they each inhibited. However, androgen also represses gene expression by various mechanisms, many of which involve protein–protein interactions. De-repression of the transcriptome of androgen-repressed genes showed profound variance between these two classes of inhibitors. In addition, these studies revealed a unique and strong induction of expression of the metallothionein family of genes by ralaniten by a mechanism independent of AR and dependent on MTF1, thereby suggesting this may be an off-target. Due to the relatively high doses that may be encountered clinically with AR-NTD inhibitors, identification of off-targets may provide insight into potential adverse events, contraindications, or poor efficacy.

Gene by Environment Interactions reveal new regulatory aspects of signaling network plasticity

Phenotypes can change during exposure to different environments through the regulation of signaling pathways that operate in integrated networks. How signaling networks produce different phenotypes in different settings is not fully understood. Here, Gene by Environment Interactions (GEIs) were used to explore the regulatory network that controls filamentous/invasive growth in the yeast Saccharomyces cerevisiae. GEI analysis revealed that the regulation of invasive growth is decentralized and varies extensively across environments. Different regulatory pathways were critical or dispensable depending on the environment, microenvironment, or time point tested, and the pathway that made the strongest contribution changed depending on the environment. Some regulators even showed conditional role reversals. Ranking pathways’ roles across environments revealed an under-appreciated pathway (OPI1) as the single strongest regulator among the major pathways tested (RAS, RIM101, and MAPK). One mechanism that may explain the high degree of regulatory plasticity observed was conditional pathway interactions, such as conditional redundancy and conditional cross-pathway regulation. Another mechanism was that different pathways conditionally and differentially regulated gene expression, such as target genes that control separate cell adhesion mechanisms (FLO11 and SFG1). An exception to decentralized regulation of invasive growth was that morphogenetic changes (cell elongation and budding pattern) were primarily regulated by one pathway (MAPK). GEI analysis also uncovered a round-cell invasion phenotype. Our work suggests that GEI analysis is a simple and powerful approach to define the regulatory basis of complex phenotypes and may be applicable to many systems.

Functional Significance of Selective Expression of ERα and ERβ in Mammary Gland Organ Culture

Thoracic pair of mammary glands from steroid hormone-pretreated mice respond to hormones structurally and functionally in organ culture. A short exposure of glands for 24 h to 7,12 Dimethylbenz(a)anthracene (DMBA) during a 24-day culture period induced alveolar or ductal lesions. Methods: To differentiate the functional significance of ERα and ERβ, we employed estrogen receptor (ER) knockout mice. We compared the effects of DMBA on the development of preneoplastic lesions in the glands in the absence of ERα (αERKO) and ERβ (βERKO) using an MMOC protocol. Glands were also subjected to microarray analyses. We showed that estradiol can be replaced by EGF for pretreatment of mice. The carcinogen-induced lesions developed under both steroids and EGF pretreatment protocols. The glands from αERKO did not develop any lesions, whereas in βERKO mice in which ERα is intact, mammary alveolar lesions developed. Comparison of microarrays of control, αERKO and βERKO mice showed that ERα was largely responsible for proliferation and the MAP kinase pathways, whereas ERβ regulated steroid metabolism-related genes. The results indicate that ERα is essential for the development of precancerous lesions. Both subtypes, ERα and Erβ, differentially regulated gene expression in mammary glands in organ cultures.

SNPs in miRNAs and Target Sequences: Role in Cancer and Diabetes

miRNAs are fascinating molecular players for gene regulation as individual miRNA can control multiple targets and a single target can be regulated by multiple miRNAs. Loss of miRNA regulated gene expression is often reported to be implicated in various human diseases like diabetes and cancer. Recently, geneticists across the world started reporting single nucleotide polymorphism (SNPs) in seed sequences of miRNAs. Similarly, SNPs are also reported in various target sequences of these miRNAs. Both the scenarios lead to dysregulated gene expression which may result in the progression of diseases. In the present paper, we explore SNPs in various miRNAs and their target sequences reported in various human cancers as well as diabetes. Similarly, we also present evidence of these mutations in various other human diseases.

Transcriptome-wide association study identified candidate genes associated with gut microbiota

Background Gut microbiota is closely associated with host health and disease occurrence. Host genetic factor plays an important role in shaping gut microbial communities. The specific mechanism of host-regulated gene expression affecting gut microbiota has not been elucidated yet. Here we conducted a transcriptome-wide association study (TWAS) for gut microbiota by leveraging expression imputation from large-scale GWAS data sets. Results TWAS detected multiple tissue-specific candidate genes for gut microbiota, such as FUT2 for genus Bifidobacterium in transverse colon (PPERM.ANL = 1.68 × 10–3) and SFTPD for an unclassified genus of Proteobacteria in transverse colon (PPERM.ANL = 5.69 × 10–3). Fine mapping replicated 3 candidate genes in TWAS, such as HELLS for Streptococcus (PIP = 0.685) in sigmoid colon, ANO7 for Erysipelotrichaceae (PIP = 0.449) in sigmoid colon. Functional analyses detected 94 significant GO terms and 11 pathways for various taxa in total, such as GO_NUCLEOSIDE_DIPHOSPHATASE_ACTIVITY for Butyrivibrio (FDR P = 1.30 × 10–4), KEGG_RENIN_ANGIOTENSIN_SYSTEM for Anaerostipes (FDR P = 3.16 × 10–2). Literature search results showed 12 genes prioritized by TWAS were associated with 12 diseases. For instance, SFTPD for an unclassified genus of Proteobacteria was related to atherosclerosis, and FUT2 for Bifidobacterium was associated with Crohn’s disease. Conclusions Our study results provided novel insights for understanding the genetic mechanism of gut microbiota, and attempted to provide clues for revealing the influence of genetic factors on gut microbiota for the occurrence and development of diseases.

Cilium Expression Score Predicts Glioma Survival

The accurate classification, prognostication, and treatment of gliomas has been hindered by an existing cellular, genomic, and transcriptomic heterogeneity within individual tumors and their microenvironments. Traditional clustering is limited in its ability to distinguish heterogeneity in gliomas because the clusters are required to be exclusive and exhaustive. In contrast, biclustering can identify groups of co-regulated genes with respect to a subset of samples and vice versa. In this study, we analyzed 1,798 normal and tumor brain samples using an unsupervised biclustering approach. We identified co-regulated gene expression profiles that were linked to proximally located brain regions and detected upregulated genes in subsets of gliomas, associated with their histologic grade and clinical outcome. In particular, we present a cilium-associated signature that when upregulated in tumors is predictive of poor survival. We also introduce a risk score based on expression of 12 cilium-associated genes which is reproducibly informative of survival independent of other prognostic biomarkers. These results highlight the role of cilia in development and progression of gliomas and suggest potential therapeutic vulnerabilities for these highly aggressive tumors.

Neurobiological Insights into Twice Exceptionality: Circuits, Cells, and Molecules

Twice-exceptional learners face a unique set of challenges arising from the intersection of extraordinary talent and disability. Neurobiology research has the capacity to complement pedagogical research and provide support for twice-exceptional learners. Very few studies have attempted to specifically address the neurobiological underpinnings of twice-exceptionality. However, neurobiologists have built a broad base of knowledge in nervous system function spanning from the level of neural circuits to the molecular basis of behavior. It is known that distinct neural circuits mediate different neural functions, which suggests that 2e learning may result from enhancement in one circuit and disruption in another. Neural circuits are known to adapt and change in response to experience, a cellular process known as neuroplasticity. Plasticity is controlled by a bidirectional connection between the synapse, where neural signals are received, and the nucleus, where regulated gene expression can return to alter synaptic function. Complex molecular mechanisms compose this connection in distinct neural circuits, and genetic alterations in these mechanisms are associated with both memory enhancements and psychiatric disorder. Understanding the consequences of these changes at the molecular, cellular, and circuit levels will provide critical insights into the neurobiological bases of twice-exceptional learning.

Thyrointegrin αVβ3 Antagonist: Implications in Acute Myeloid Leukemia

Leukemic cells are able to receive and send several signals within bone marrow niche that play an important role in their survival. One of the important crosstalk is the interaction between the bone marrow microenvironment proteins (vitronectin, fibronectin, fibrinogen, and ostepontin) and thyrointegrin αVβ3 on leukemic cells, generating ligand-specific outside-in signals that are relevant to a variety of cell functions, including gene transcription, cell division, cell attachment, and motility Our previous experiment using in vivo AML animal models with primary AML cells and cell lines have shown significant reduction of leukemic cell burden 74% and >95% (P<0.0001), respectively, after daily subcutaneous treatment with thyrointegrin αvβ3 antagonist fb-PMT (Ki 0.23 nM) at 3 and 10 mg/kg, for 3-4 weeks. In this study we focused on evaluations of the molecular effects of fb-PMT in leukemic cells. Acute myeloid leukemia cell lines (K562-Luc and KG1a cells) were cultured in 50 cm² cell culture flasks with 10 mL phenol red free RPMI media containing 10% fetal bovine albumin. The leukemic cells were treated (at 50% confluence) with 30 µM fb-PMT for 48 hours. Total RNA was immediately isolated from harvested cells using Triazole and used for microarray analysis. Overall, there were 370 significantly down-regulated gene expression records and 273 significantly up-regulated gene expression records, expression of which were changed at least 1.5-fold in fb-PMT-treated human leukemic cells. Significant examples of the fb-PMT-induced gene expression signatures (GES) of pathway's interference include SNAI, MYC, HIF1A, TWIST1, and TFAP2C (P<0.05). Notably, inference of potential contribution to the fb-PMT anticancer activity of the interference with these pathways seems highly congruent with their known biological functions such as cell cycle control (MYC), survival and maintenance of stem cells (HIF1A, TFAP2C), and essential features of the malignant phenotype (TWIST1, SNAI) (Figure 1). Consistently, examples of the fb-PMT-induced GES of transcriptional pathway's activation include RB1, IRF9, MAML1, RAP1A, and GATA4 pathways (P<0.05), known biological functions of which appear highly consistent with the hypothesis that activation of these pathways might contribute to fb-PMT anticancer activity. Finally, we found that fb-PMT interfered with estrogen signaling in human AML cells. The fb-PMT was associated with decreased phosphorylation and nuclear enrichment of Erα (Figure 1). Collectively, our in vivo study and genomic data have shown the key role thyrointegrin αvβ3 in leukemogenesis. The thyrointegrin αvβ3 antagonist fb-PMT demonstrated potent anticancer actions on human AML through the molecular interference mechanism with multiple signaling pathways supporting growth and survival of leukemic cells Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.