ncStem: a comprehensive resource of curated and predicted ncRNAs in cancer stemness.

Cancer stemness plays an important role in cancer initiation and progression, and is the major cause of tumor invasion, metastasis, recurrence, and poor prognosis. Non-coding RNAs (ncRNAs) are a class of RNA transcripts that generally cannot encode proteins and have been demonstrated to play a critical role in regulating cancer stemness. Here, we developed the ncStem database to record manually curated and predicted ncRNAs associated with cancer stemness.

Integrated analysis of patients with bladder cancer from prospective transcription factor activity: Implications for personalized treatment approaches.

Transcription factors are a specialized group of proteins that play important roles in regulating gene expression in human. These proteins control the transcription and translation of genes by binding to specific sites on DNA, thereby regulating key biological processes such as cell differentiation, proliferation, immune response, and neural development. Moreover, transcription factors are also involved in apoptosis and the pathogenesis of various diseases.

Differential whole-genome doubling based signatures for improvement on clinical outcomes and drug response in patients with breast cancer.

Whole genome doublings (WGD), a hallmark of human cancer, is pervasive in breast cancer patients. However, the molecular mechanism of the complete impact of WGD on survival and treatment response in breast cancer remains unclear. To address this, we performed a comprehensive and systematic analysis of WGD, aiming to identify distinct genetic alterations linked to WGD and highlight its improvement on clinical outcomes and treatment response for breast cancer.

Lysine-specific histone demethylase 1A (KDM1A/LSD1) inhibition attenuates DNA double-strand break repair and augments the efficacy of temozolomide in glioblastoma.

Background: Efficient DNA repair in response to standard chemo and radiation therapies often contributes to glioblastoma (GBM) therapy resistance. Understanding the mechanisms of therapy resistance and identifying the drugs that enhance the therapeutic efficacy of standard therapies may extend the survival of GBM patients. In this study, we investigated the role of KDM1A/LSD1 in DNA double-strand break (DSB) repair and a combination of KDM1A inhibitor and temozolomide (TMZ) in vitro and in vivo using patient-derived glioma stem cells (GSCs).

Deep learning-based transcription factor activity for stratification of breast cancer patients.

Transcription factors directly bind to DNA and regulate the expression of the gene, causing epigenetic modification of the DNA. They often mediate epigenetic parameters of transcriptional and posttranscriptional mechanisms, and their expression activities can be used to characterize genomic aberrations in cancer cell. In this study, the activity profile of transcription factors inferred by VIPER algorithm.

Integrated multi-cohorts for characterizing the immunogenomic landscape and predicting drug response in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is the breast cancer subtype with the highest fatality rate, and it seriously threatens women's health. Recent studies found that the level of immune cell infiltration in TNBC was associated with tumor progression and prognosis. However, due to practical constraints, most of these TNBC immune infiltration studies only used a small number of patient samples and a few immune cell types.

Prognostic and predictive value of a metabolic risk score model in breast cancer: an immunogenomic landscape analysis.

Breast cancer is a kind of malignant tumor that occurs in breast tissue, which is the most common cancer in women. Cellular metabolism is a critical determinant of the viability and function of cancer cells in tumor microenvironment. In this study, based on the gene expression profile of metabolism-related genes, the prognostic value of 20 metabolic pathways in patients with breast cancer was identified.

Beneficial Effects of Green Tea EGCG on Skin Wound Healing: A Comprehensive Review.

Epigallocatechin gallate (EGCG) is associated with various health benefits. In this review, we searched current work about the effects of EGCG and its wound dressings on skin for wound healing. Hydrogels, nanoparticles, micro/nanofiber networks and microneedles are the major types of EGCG-containing wound dressings.

Integrated analysis of telomerase enzymatic activity unravels an association with cancer stemness and proliferation.

Active telomerase is essential for stem cells and most cancers to maintain telomeres. The enzymatic activity of telomerase is related but not equivalent to the expression of TERT, the catalytic subunit of the complex. Here we show that telomerase enzymatic activity can be robustly estimated from the expression of a 13-gene signature.

Systematic analysis of lncRNA and microRNA dynamic features reveals diagnostic and prognostic biomarkers of myocardial infarction.

Analyses of long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) implicated in myocardial infarction (MI) have increased our understanding of gene regulatory mechanisms in MI. However, it is not known how their expression fluctuates over the different stages of MI progression. In this study, we used time-series gene expression data to examine global lncRNA and miRNA expression patterns during the acute phase of MI and at three different time points thereafter.

Identifying FL11 subtype by characterizing tumor immune microenvironment in prostate adenocarcinoma via Chou's 5-steps rule.

Prostate cancer is one of the leading causes of death in men worldwide, revealing a substantial heterogeneity in terms of molecular and clinical behaviors. Tumor infiltrating immune cell is associated with prognosis and response to immunotherapy in several cancer types. However, until now, the immune infiltrate profile of distinct subtypes for prostate cancer remains poorly characterized.

Characterize the difference between TMPRSS2-ERG and non-TMPRSS2-ERG fusion patients by clinical and biological characteristics in prostate cancer.

The TMPRSS2-ERG gene fusion were frequently found in prostate cancer, and thought to play some fundamental mechanisms for the development of prostate cancer. However, until now, the clinical and prognostic significance of TMPRSS2-ERG gene fusion was not fully understood. In this study, based on the 281 prostate cancers that constructed from a historical watchful waiting cohort, the statistically significant associations between TMPRSS2-ERG gene fusion and clinicopathologic characteristics were identified.

Prediction of Non-coding RNAs as Drug Targets.

MiRNA is a class of small non-coding RNA molecule that regulates gene expression at post-transcriptional level. Increasing evidences show aberrant expression of miRNAs in a variety of diseases. Targeting the dysregulated miRNAs with small molecule drugs has become a novel therapeutics for many human diseases, especially cancers.

Clinical significance of the immune microenvironment in ovarian cancer patients.

Ovarian cancer is one of the leading causes of death from gynecologic malignancy in women. High-grade serous carcinomas, low-grade serous carcinomas, endometrioid carcinomas, clear cell carcinomas, and mucinous carcinomas with distinct pathological and clinical characteristics are the main histological subtypes of ovarian cancer. The majority of ovarian cancer patients are diagnosed at an advanced stage due to a lack of suitable screening tests for early detection and specific early symptoms.

Characterization of dysregulated lncRNA-mRNA network based on ceRNA hypothesis to reveal the occurrence and recurrence of myocardial infarction.

Accumulating evidence has demonstrated that long non-coding RNAs (lncRNAs) acting as competing endogenous RNAs (ceRNAs) play important roles in initiation and development of human diseases. However, the mechanism of ceRNA regulated by lncRNA in myocardial infarction (MI) remained unclear. In this study, we performed a multi-step computational method to construct dysregulated lncRNA-mRNA networks for MI occurrence (DLMN_MI_OC) and recurrence (DLMN_MI_Re) based on "ceRNA hypothesis".

Prediction of presynaptic and postsynaptic neurotoxins by combining various Chou's pseudo components.

Presynaptic and postsynaptic neurotoxins are two groups of neurotoxins. Identification of presynaptic and postsynaptic neurotoxins is an important work for numerous newly found toxins. It is both costly and time consuming to determine these two neurotoxins by experimental methods.

Molecular classification of prostate adenocarcinoma by the integrated somatic mutation profiles and molecular network.

Prostate cancer is one of the most common cancers in men and a leading cause of cancer death worldwide, displaying a broad range of heterogeneity in terms of clinical and molecular behavior. Increasing evidence suggests that classifying prostate cancers into distinct molecular subtypes is critical to exploring the potential molecular variation underlying this heterogeneity and to better treat this cancer. In this study, the somatic mutation profiles of prostate cancer were downloaded from the TCGA database and used as the source nodes of the random walk with restart algorithm (RWRA) for generating smoothed mutation profiles in the STRING network.

Large-scale identification of adverse drug reaction-related proteins through a random walk model.

Adverse drug reactions (ADRs) are responsible for drug failure in clinical trials and affect life quality of patients. The identification of ADRs during the early phases of drug development is an important task. Therefore, predicting potential protein targets eliciting ADRs is essential for understanding the pathogenesis of ADRs.

Characterize the relationship between essential and TATA-containing genes for S. cerevisiae by network topologies in the perturbation sensitivity network.

Essential genes are those that are indispensable for the survival and propagation of an organism. TATA-containing genes are associated with responses to various stresses and are highly regulated. Although both essential genes and TATA genes are very important in the function of biological systems, their relationship remains unclear because they have typically been researched independently.

Characterization of BioPlex network by topological properties.

Protein-protein interaction (PPI) networks are emerging as valuable prototypes to study important problems in molecular cellular biology and systems biomedicine. An analysis of the topological properties of a PPI network is very helpful for understanding the function and structure of networks. In this study, we analyzed the topological patterns in the BioPlex network containing interactions among 10,961 proteins; most interactions were previously undocumented.

Comparative analysis of housekeeping and tissue-selective genes in human based on network topologies and biological properties.

Housekeeping genes are genes that are turned on most of the time in almost every tissue to maintain cellular functions. Tissue-selective genes are predominantly expressed in one or a few biologically relevant tissue types. Benefitting from the massive gene expression microarray data obtained over the past decades, the properties of housekeeping and tissue-selective genes can now be investigated on a large-scale manner.

Identifying novel associations between small molecules and miRNAs based on integrated molecular networks.

Motivation: miRNAs play crucial roles in human diseases and newly discovered could be targeted by small molecule (SM) drug compounds. Thus, the identification of small molecule drug compounds (SM) that target dysregulated miRNAs in cancers will provide new insight into cancer biology and accelerate drug discovery for cancer therapy.

Results: In this study, we aimed to develop a novel computational method to comprehensively identify associations between SMs and miRNAs.

Characterization of proteins in S. cerevisiae with subcellular localizations.

Acquiring comprehensive knowledge of protein in various subcellular localizations is one of the fundamental goals in cell biology and proteomics. Although recent large-scale experimental and proteomics studies of S. cerevisiae protein subcellular localizations are archived in various databases, only a few studies use a systems biology approach to characterize S.