Daogang Guan

Unraveling Regulatory Programs for NF-kappaB, p53 and MicroRNAs in Head and Neck Squamous Cell Carcinoma

In head and neck squamous cell carcinoma (HNSCC), mutations of p53 usually coexist with aberrant activation of NF-kappaB (NF-κB), other transcription factors and microRNAs, which promote tumor pathogenesis. However, how these factors and microRNAs interact to globally modulate gene expression and mediate oncogenesis is not fully understood. We devised a novel bioinformatics method to uncover interactive relationships between transcription factors or microRNAs and genes. This approach is based on matrix decomposition modeling under the joint constraints of sparseness and regulator-target connectivity, and able to integrate gene expression profiling and binding data of regulators. We employed this method to infer the gene regulatory networks in HNSCC. We found that the majority of the predicted p53 targets overlapped with those for NF-κB, suggesting that the two transcription factors exert a concerted modulation on regulatory programs in tumor cells. We further investigated the interrelationships of p53 and NF-κB with five additional transcription factors, AP1, CEBPB, EGR1, SP1 and STAT3, and microRNAs mir21 and mir34ac. The resulting gene networks indicate that interactions among NF-κB, p53, and the two miRNAs likely regulate progression of HNSCC. We experimentally validated our findings by determining expression of the predicted NF-κB and p53 target genes by siRNA knock down, and by examining p53 binding activity on promoters of predicted target genes in the tumor cell lines. Our results elucidating the cross-regulations among NF-κB, p53, and microRNAs provide insights into the complex regulatory mechanisms underlying HNSCC, and shows an efficient approach to inferring gene regulatory programs in biological complex systems.

PTHGRN: unraveling post-translational hierarchical gene regulatory networks using PPI, ChIP-seq and gene expression data

Interactions among transcriptional factors (TFs), cofactors and other proteins or enzymes can affect transcriptional regulatory capabilities of eukaryotic organisms. Post-translational modifications (PTMs) cooperate with TFs and epigenetic alterations to constitute a hierarchical complexity in transcriptional gene regulation. While clearly implicated in biological processes, our understanding of these complex regulatory mechanisms is still limited and incomplete. Various online software have been proposed for uncovering transcriptional and epigenetic regulatory networks, however, there is a lack of effective web-based software capable of constructing underlying interactive organizations between post-translational and transcriptional regulatory components. Here, we present an open web server, post-translational hierarchical gene regulatory network (PTHGRN) to unravel relationships among PTMs, TFs, epigenetic modifications and gene expression. PTHGRN utilizes a graphical Gaussian model with partial least squares regression-based methodology, and is able to integrate protein–protein interactions, ChIP-seq and gene expression data and to capture essential regulation features behind high-throughput data. The server provides an integrative platform for users to analyze ready-to-use public high-throughput Omics resources or upload their own data for systems biology study. Users can choose various parameters in the method, build network topologies of interests and dissect their associations with biological functions. Application of the software to stem cell and breast cancer demonstrates that it is an effective tool for understanding regulatory mechanisms in biological complex systems. PTHGRN web server is publically available at web site http://www.byanbioinfo.org/pthgrn.

Systems‐level quantification of division timing reveals a common genetic architecture controlling asynchrony and fate asymmetry

Coordination of cell division timing is crucial for proper cell fate specification and tissue growth. However, the differential regulation of cell division timing across or within cell types during metazoan development remains poorly understood. To elucidate the systems‐level genetic architecture coordinating division timing, we performed a high‐content screening for genes whose depletion produced a significant reduction in the asynchrony of division between sister cells (ADS) compared to that of wild‐type during Caenorhabditis elegans embryogenesis. We quantified division timing using 3D time‐lapse imaging followed by computer‐aided lineage analysis. A total of 822 genes were selected for perturbation based on their conservation and known roles in development. Surprisingly, we find that cell fate determinants are not only essential for establishing fate asymmetry, but also are imperative for setting the ADS regardless of cellular context, indicating a common genetic architecture used by both cellular processes. The fate determinants demonstrate either coupled or separate regulation between the two processes. The temporal coordination appears to facilitate cell migration during fate specification or tissue growth. Our quantitative dataset with cellular resolution provides a resource for future analyses of the genetic control of spatial and temporal coordination during metazoan development.

PlaMoM: a comprehensive database compiles plant mobile macromolecules.

In plants, various phloem-mobile macromolecules including noncoding RNAs, mRNAs and proteins are suggested to act as important long-distance signals in regulating crucial physiological and morphological transition processes such as flowering, plant growth and stress responses. Given recent advances in high-throughput sequencing technologies, numerous mobile macromolecules have been identified in diverse plant species from different plant families. However, most of the identified mobile macromolecules are not annotated in current versions of species-specific databases and are only available as non-searchable datasheets. To facilitate study of the mobile signaling macromolecules, we compiled the PlaMoM (Plant Mobile Macromolecules) database, a resource that provides convenient and interactive search tools allowing users to retrieve, to analyze and also to predict mobile RNAs/proteins. Each entry in the PlaMoM contains detailed information such as nucleotide/amino acid sequences, ortholog partners, related experiments, gene functions and literature. For the model plant Arabidopsis thaliana, protein–protein interactions of mobile transcripts are presented as interactive molecular networks. Furthermore, PlaMoM provides a built-in tool to identify potential RNA mobility signals such as tRNA-like structures. The current version of PlaMoM compiles a total of 17 991 mobile macromolecules from 14 plant species/ecotypes from published data and literature. PlaMoM is available at http://www.systembioinfo.org/plamom/.

A water-soluble nucleolin aptamer-paclitaxel conjugate for tumor-specific targeting in ovarian cancer

Paclitaxel (PTX) is among the most commonly used first-line drugs for cancer chemotherapy. However, its poor water solubility and indiscriminate distribution in normal tissues remain clinical challenges. Here we design and synthesize a highly water-soluble nucleolin aptamer-paclitaxel conjugate (NucA-PTX) that selectively delivers PTX to the tumor site. By connecting a tumor-targeting nucleolin aptamer (NucA) to the active hydroxyl group at 2′ position of PTX via a cathepsin B sensitive dipeptide bond, NucA-PTX remains stable and inactive in the circulation. NucA facilitates the uptake of the conjugated PTX specifically in tumor cells. Once inside cells, the dipeptide bond linker of NucA-PTX is cleaved by cathepsin B and then the conjugated PTX is released for action. The NucA modification assists the selective accumulation of the conjugated PTX in ovarian tumor tissue rather than normal tissues, and subsequently resulting in notably improved antitumor activity and reduced toxicity.Paclitaxel, a first line chemotherapeutic drug, suffers from poor water solubility and low tissue selectivity. Here, the authors report a water-soluble nucleolin aptamer-paclitaxel conjugate that selectively accumulates in ovarian tumor issues displaying reduced toxicity and improved activity profiles.

Metabolomics and Its Application in the Development of Discovering Biomarkers for Osteoporosis Research

Osteoporosis is a progressive skeletal disorder characterized by low bone mass and increased risk of fracture in later life. The incidence and costs associated with treating osteoporosis cause heavy socio-economic burden. Currently, the diagnosis of osteoporosis mainly depends on bone mineral density and bone turnover markers. However, these indexes are not sensitive and accurate enough to reflect the osteoporosis progression. Metabolomics offers the potential for a holistic approach for clinical diagnoses and treatment, as well as understanding of the pathological mechanism of osteoporosis. In this review, we firstly describe the study subjects of osteoporosis and bio-sample preparation procedures for different analytic purposes, followed by illustrating the biomarkers with potentially predictive, diagnosis and pharmaceutical values when applied in osteoporosis research. Then, we summarize the published metabolic pathways related to osteoporosis. Furthermore, we discuss the importance of chronological data and combination of multi-omics in fully understanding osteoporosis. The application of metabolomics in osteoporosis could provide researchers the opportunity to gain new insight into the metabolic profiling and pathophysiological mechanisms. However, there is still much to be done to validate the potential biomarkers responsible for the progression of osteoporosis and there are still many details needed to be further elucidated.

Molecular Mechanisms and Translational Therapies for Human Epidermal Receptor 2 Positive Breast Cancer

Breast cancer is the second leading cause of cancer death among women. Human epidermal receptor 2 (HER2) positive breast cancer (HER2+ BC) is the most aggressive subtype of breast cancer, with poor prognosis and a high rate of recurrence. About one third of breast cancer is HER2+ BC with significantly high expression level of HER2 protein compared to other subtypes. Therefore, HER2 is an important biomarker and an ideal target for developing therapeutic strategies for the treatment HER2+ BC. In this review, HER2 structure and physiological and pathological roles in HER2+ BC are discussed. Two diagnostic tests, immunohistochemistry (IHC) and fluorescent in situ hybridization (FISH), for evaluating HER2 expression levels are briefly introduced. The current mainstay targeted therapies for HER2+ BC include monoclonal antibodies, small molecule tyrosine kinase inhibitors, antibody–drug conjugates (ADC) and other emerging anti-HER2 agents. In clinical practice, combination therapies are commonly adopted in order to achieve synergistic drug response. This review will help to better understand the molecular mechanism of HER2+ BC and further facilitate the development of more effective therapeutic strategies against HER2+ BC.

PARP1 in Carcinomas and PARP1 Inhibitors as Antineoplastic Drugs

Poly (ADP-ribose) polymerase 1 (PARP1), the best-studied isoform of the nuclear enzyme PARP family, plays a pivotal role in cellular biological processes, such as DNA repair, gene transcription, and so on. PARP1 has been found to be overexpressed in various carcinomas. These all indicate the clinical potential of PARP1 as a therapeutic target of human malignancies. Additionally, multiple preclinical research studies and clinical trials demonstrate that inhibition of PARP1 can repress tumor growth and metastasis. Up until now, PARP1 inhibitors are clinically used not only for monotherapy to suppress various tumors, but also for adjuvant therapy, to maintain or enhance therapeutic effects of mature antineoplastic drugs, as well as protect patients from chemotherapy and surgery-induced injury. To supply a framework for understanding recent research progress of PARP1 in carcinomas, we review the structure, expression, functions, and mechanisms of PARP1, and summarize the clinically mature PARP1-related anticancer agents, to provide some ideas for the development of other promising PARP1 inhibitors in antineoplastic therapy.

A newly identified lncRNA MAR1 acts as a miR-487b sponge to promote skeletal muscle differentiation and regeneration: MAR1 sponges miR-487b to promote muscle differentiation

Skeletal muscle atrophy induced by either aging (sarcopenia) or mechanical unloading is associated with serious health consequences. Long non‐coding RNAs (lncRNAs) are implicated as important regulators in numerous physiological and pathological processes.

An integrative method to decode regulatory logics in gene transcription

Modeling of transcriptional regulatory networks (TRNs) has been increasingly used to dissect the nature of gene regulation. Inference of regulatory relationships among transcription factors (TFs) and genes, especially among multiple TFs, is still challenging. In this study, we introduced an integrative method, LogicTRN, to decode TF–TF interactions that form TF logics in regulating target genes. By combining cis-regulatory logics and transcriptional kinetics into one single model framework, LogicTRN can naturally integrate dynamic gene expression data and TF-DNA-binding signals in order to identify the TF logics and to reconstruct the underlying TRNs. We evaluated the newly developed methodology using simulation, comparison and application studies, and the results not only show their consistence with existing knowledge, but also demonstrate its ability to accurately reconstruct TRNs in biological complex systems.Existing transcriptional regulatory networks models fall short of deciphering the cooperation between multiple transcription factors on dynamic gene expression. Here the authors develop an integrative method that combines gene expression and transcription factor-DNA binding data to decode transcription regulatory logics.