Alternative splicing (AS) contributes to the biological heterogeneity between species, sexes, tissues, and cell types. Many diseases are either caused by alterations in AS or by alterations to AS. Therefore, measuring AS accurately and efficiently is critical for assessing molecular phenotypes, including those associated with disease.
View Article and Find Full Text PDFDrug repurposing is promising because approving a drug for a new indication requires fewer resources than approving a new drug. Signature reversion detects drug perturbations most inversely related to the disease-associated gene signature to identify drugs that may reverse that signature. We assessed the performance and biological relevance of three approaches for constructing disease-associated gene signatures (i.
View Article and Find Full Text PDFAlternative splicing (AS) contributes to the biological heterogeneity between species, sexes, tissues, and cell types. Many diseases are either caused by alterations in AS or by alterations to AS. Therefore, measuring AS accurately and efficiently is critical for assessing molecular phenotypes, including those associated with disease.
View Article and Find Full Text PDFGiven the high attrition rate of de novo drug discovery and limited efficacy of single-agent therapies in cancer treatment, combination therapy prediction through in silico drug repurposing has risen as a time- and cost-effective alternative for identifying novel and potentially efficacious therapies for cancer. The purpose of this review is to provide an introduction to computational methods for cancer combination therapy prediction and to summarize recent studies that implement each of these methods. A systematic search of the PubMed database was performed, focusing on studies published within the past 10 years.
View Article and Find Full Text PDFSex differences are essential factors in disease etiology and manifestation in many diseases such as cardiovascular disease, cancer, and neurodegeneration [33]. The biological influence of sex differences (including genomic, epigenetic, hormonal, immunological, and metabolic differences between males and females) and the lack of biomedical studies considering sex differences in their study design has led to several policies. For example, the National Institute of Health's (NIH) sex as a biological variable (SABV) and Sex and Gender Equity in Research (SAGER) policies to motivate researchers to consider sex differences [204].
View Article and Find Full Text PDFObjective: Despite an aggressive multimodal therapeutic regimen, glioblastoma (GBM) continues to portend a grave prognosis, which is driven in part by tumor heterogeneity at both the molecular and cellular levels. Accordingly, herein the authors sought to identify metabolic differences between GBM tumor core cells and edge cells and, in so doing, elucidate novel actionable therapeutic targets centered on tumor metabolism.
Methods: Comprehensive metabolic analyses were performed on 20 high-grade glioma (HGG) tissues and 30 glioma-initiating cell (GIC) sphere culture models.
In many cancers, high proliferation rates correlate with elevation of rRNA and tRNA levels, and nucleolar hypertrophy. However, the underlying mechanisms linking increased nucleolar transcription and tumorigenesis are only minimally understood. Here we show that IMP dehydrogenase-2 (IMPDH2), the rate-limiting enzyme for de novo guanine nucleotide biosynthesis, is overexpressed in the highly lethal brain cancer glioblastoma.
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