A full-proteome, interaction-specific characterization of mutational hotspots across human cancers

Rapid accumulation of cancer genomic data has led to the identification of an increasing number of mutational hotspots with uncharacterized significance. Here we present a biologically informed computational framework that characterizes the functional relevance of all 1107 published mutational hotspots identified in approximately 25,000 tumor samples across 41 cancer types in the context of a human 3D interactome network, in which the interface of each interaction is mapped at residue resolution. Hotspots reside in network hub proteins and are enriched on protein interaction interfaces, suggesting that alteration of specific protein–protein interactions is critical for the oncogenicity of many hotspot mutations. Our framework enables, for the first time, systematic identification of specific protein interactions affected by hotspot mutations at the full proteome scale. Furthermore, by constructing a hotspot-affected network that connects all hotspot-affected interactions throughout the whole-human interactome, we uncover genome-wide relationships among hotspots and implicate novel cancer proteins that do not harbor hotspot mutations themselves. Moreover, applying our network-based framework to specific cancer types identifies clinically significant hotspots that can be used for prognosis and therapy targets. Overall, we show that our framework bridges the gap between the statistical significance of mutational hotspots and their biological and clinical significance in human cancers.

Accumulation of Temozolomide-Induced Apoptosis, Senescence and DNA Damage by Metronomic Dose Schedule: A Proof-of-Principle Study with Glioblastoma Cells

Temozolomide (TMZ), a first-line drug in glioma therapy, targets the tumor DNA at various sites. One of the DNA alkylation products is O6-methylguanine (O6MeG), which is, in the low dose range of TMZ, responsible for nearly all genotoxic and cytotoxic effects relevant for cancer therapy. There is, however, a dispute regarding whether the TMZ concentration in the tumor tissue in patients is sufficient to elicit a significant cytotoxic or cytostatic response. Although treatment with TMZ occurs repeatedly with daily doses (metronomic dose schedule) and in view of the short half-life of the drug it is unclear whether doses are accumulating. Here, we addressed the question whether repeated low doses elicit similar effects in glioblastoma cells than a high cumulative dose. We show that repeated treatments with a low dose of TMZ (5 × 5 µM) caused an accumulation of cytotoxicity through apoptosis, cytostasis through cellular senescence, and DNA double-strand breaks, which was similar to the responses induced by a single cumulative dose of 25 µM TMZ. This finding, together with the previously reported linear dose–response curves, support the notion that TMZ is able to trigger a significant cytotoxic and cytostatic effect in vivo if the low-dose metronomic schedule is applied.

Identified Three Interferon Induced Proteins as Novel Biomarkers of Human Ischemic Cardiomyopathy

Ischemic cardiomyopathy is the most frequent type of heart disease, and it is a major cause of myocardial infarction (MI) and heart failure (HF), both of which require expensive medical treatment. Precise biomarkers and therapy targets must be developed to enhance improve diagnosis and treatment. In this study, the transcriptional profiles of 313 patients’ left ventricle biopsies were obtained from the PubMed database, and functional genes that were significantly related to ischemic cardiomyopathy were screened using the Weighted Gene Co-Expression Network Analysis and protein–protein interaction (PPI) networks enrichment analysis. The rat myocardial infarction model was developed to validate these findings. Finally, the putative signature genes were blasted through the common Cardiovascular Disease Knowledge Portal to explore if they were associated with cardiovascular disorder. Three interferon stimulated genes (IFIT2, IFIT3 and IFI44L), as well as key pathways, have been identified as potential biomarkers and therapeutic targets for ischemic cardiomyopathy, and their alternations or mutations have been proven to be strongly linked to cardiac disorders. These novel signature genes could be utilized as bio-markers or potential therapeutic objectives in precise clinical diagnosis and treatment of ischemic cardiomyopathy.

Integration of transcriptome and proteome profiles in placenta accreta reveals trophoblast over-migration as the underlying pathogenesis

Background Placenta accreta (PA) is a major cause of maternal morbidity and mortality in modern obstetrics, few studies have explored the underlying molecular mechanisms. Methods In our study, transcriptome and proteome profiling were performed in placental tissues from ten participants including five cases each in the PA and control groups to clarify the pathogenesis of PA. Results We identified differential expression of 37,743 transcripts and 160 proteins between the PA and control groups with an overlap rate of 0.09%. The 33 most-significant transcripts and proteins were found and further screened and analyzed. Adhesion-related signature, chemotaxis related signatures and immune related signature were found in the PA group and played a certain role. Sum up two points, three significant indicators, methyl-CpG-binding domain protein 2 (MeCP2), podocin (PODN), and apolipoprotein D (ApoD), which participate in “negative regulation of cell migration”, were downregulated at the mRNA and protein levels in PA group. Furthermore, transwell migration and invasion assay of HTR-8/SVneo cell indicated the all of them impaired the migration and invasion of trophoblast. Conclusion A poor correlation was observed between the transcriptome and proteome data and MeCP2, PODN, and ApoD decreased in transcriptome and proteome profiling, resulting in increased migration of trophoblasts in the PA group, which clarify the mechanism of PA and might be the biomarkers or therapy targets in the future.

Pan-Cancer Analyses of Pyroptosis With Functional Implications in Prognosis and Immunotherapy in Cancer

Background Programmed cell death is an active and orderly form of cell death regulated by intracellular genes, which plays an important role in the normal occurrence and development of the immune system, and pyroptosis has been found to be involved in the tumorigenesis and development. However, compressive analysis and biological regulation about pyroptosis genes are lack in cancers. Methods Using the data from the The Cancer Genome Atlas, we established a score level model to quantify the pyroptosis level of cancer. Multi-omics bioinformatical analyses was performed to detect pyroptosis-related molecular features and effect of pyroptosis on immunotherapy in cancer. Results In the present study, we performed a comprehensive analysis of pyroptosis and its regulator genes in cancers. Most pyroptosis genes were aberrantly expressed among different cancer types, which is contributed by the CAN frequency and differences of DNA methylation level in cancer. We established the modeling of the pyroptosis level and found that pyroptosis showed dual roles across cancers, while the pyroptosis levels were different in multiple and be significantly associated with clinical prognosis. The dual role of pyroptosis also affect the effects of immunotherapy in several cancers. Multiple pyroptosis genes showed close connections with drug sensitivity across cancers, and may be considered as therapy targets in cancer. Conclusions Our comprehensive analyses provide new insight into the functions of pyroptosis in the initiation, development, and progression and treatment across cancers, suggesting corresponding prognostic and therapeutic utility.

Revealing Key LncRNAs in Cytogenetically Normal Acute Myeloid Leukemia by Reconstruction of the LncRNA–miRNA–mRNA Network Based on the Competitive Endogenous RNA Theory

Background Cytogenetically normal acute myeloid leukemia(CN-AML) is a heterogeneous disease with different prognosis.Researches on prognostic indicators and therapy targets of CN-AML are still ongoing.Instead of protein-coding genes,more and more researches were focused on the non-coding RNAs especially long non-coding RNAs(lncRNAs) which may play an important role in the development and prognosis of AML.Although a large number of lncRNAs had been found, our knowledge of their function and pathological significance is still in its infancy.The purpose of this research is to identify the key lncRNAs and explore their function in CN-AML by reconstructing the lncRNA–miRNA–mRNA network based on the competitive endogenous RNA(ceRNA) theory. Results We reconstructed a global triple network based on the ceRNA theory using the data from National Center for Biotechnology Information Gene Expression Omnibus and published literature. According to the topological algorithm,we identified the key lncRNAs which had both the higher node degrees and the higher number of lncRNA–miRNA and miRNA–mRNA pairs in the ceRNA network. Meanwhile, Gene Ontology (GO) and pathway analysis were performed using databases such as DAVID,KOBAS and Cytoscape plug-in ClueGO respectively.The lncRNA–miRNA–mRNA network was composed of 90 lncRNAs,33mRNAs,26 miRNAs and 259 edges in the lncRNA upregulated group,and 18 lncRNAs,11 mRNAs,6 miRNAs and 45 edges in the lncRNA downregulated group.The functional assay showed that 53 pathways and 108 GO terms were enriched. Three lncRNAs(XIST,GABPB1-AS1,TUG1)could possibly be selected as key lncRNAs wihch may play an important role in the development of CN-AML.Particularly,GABPB1-AS1 was highly expressed in CN-AML by both bioinformatics analysis and experimental verification in AML cell line(THP-1) by quantitative real-time polymerase chain reaction.In addition, GABPB1-AS1 was also negatively correlated with overall survival of AML patients. Conclusion The lncRNA–miRNA–mRNA network revealed key lncRNAs and their functions in CN-AML.Particularly,lncRNA GABPB1-AS1 was firstly proposed in AML.We believe that GABPB1-AS1 is expected to become a candidate diagnostic biomarker or potential therapeutic target.

Diverse Roles and Therapeutic Potentials of Circular RNAs in Urological Cancers

Circular RNAs (circRNAs) are a novel class of noncoding RNAs, which are mainly formed as a loop structure at the exons caused by noncanonical splicing; they are much more stable than linear transcripts; recent reports have suggested that the dysregulation of circRNAs is associated with the occurrence and development of diseases, especially various human malignancies. Emerging evidence demonstrated that a large number of circRNAs play a vital role in a series of biological processes such as tumor cell proliferation, migration, drug resistance, and immune escape. Additionally, circRNAs were also reported to be potential prognostic and diagnostic biomarkers in cancers. In this work, we systematically summarize the biogenesis and characteristics of circRNAs, paying special attention to potential mechanisms and clinical applications of circRNAs in urological cancers, which may help develop potential therapy targets for urological cancers in the future.

Glioblastoma gene network reconstruction and ontology analysis by online bioinformatics tools

Glioblastoma is the most aggressive type of brain tumors resistant to a number of antitumor drugs. The problem of therapy and drug treatment course is complicated by extremely high heterogeneity in the benign cell populations, the random arrangement of tumor cells, and polymorphism of their nuclei. The pathogenesis of gliomas needs to be studied using modern cellular technologies, genome- and transcriptome-wide technologies of high-throughput sequencing, analysis of gene expression on microarrays, and methods of modern bioinformatics to find new therapy targets. Functional annotation of genes related to the disease could be retrieved based on genetic databases and cross-validated by integrating complementary experimental data. Gene network reconstruction for a set of genes (proteins) proved to be effective approach to study mechanisms underlying disease progression. We used online bioinformatics tools for annotation of gene list for glioma, reconstruction of gene network and comparative analysis of gene ontology categories. The available tools and the databases for glioblastoma gene analysis are discussed together with the recent progress in this field.

MicroRNAs as Critical Biomarkers of Major Depressive Disorder: A Comprehensive Perspective

Major Depressive Disorder (MDD) represents a major global health concern, a body-mind malady of rising prevalence worldwide nowadays. The complex network of mechanisms involved in MDD pathophysiology is subjected to epigenetic changes modulated by microRNAs (miRNAs). Serum free or vesicles loaded miRNAs have starred numerous publications, denoting a key role in cell-cell communication, systematically and in brain structure and neuronal morphogenesis, activity and plasticity. Upregulated or downregulated expression of these signaling molecules may imply the impairment of genes implicated in pathways of MDD etiopathogenesis (neuroinflammation, brain-derived neurotrophic factor (BDNF), neurotransmitters, hypothalamic-pituitary-adrenal (HPA) axis, oxidative stress, circadian rhythms...). In addition, these miRNAs could serve as potential biomarkers with diagnostic, prognostic and predictive value, allowing to classify severity of the disease or to make decisions in clinical management. They have been considered as promising therapy targets as well and may interfere with available antidepressant treatments. As epigenetic malleable regulators, we also conclude emphasizing lifestyle interventions with physical activity, mindfulness and diet, opening the door to new clinical management considerations.

Biochemical Targets and Molecular Mechanism of Ginsenoside Compound K for Treating Osteoporosis Based on Network Pharmacology

Ginsenosides have been proven to be potential beneficial in treatment of osteoporosis. To investigate the potential of ginsenosides in osteoporosis, ginsenoside compound K (GCK) was selected to explore the potential therapy targets and mechanism based on network pharmacology (NP). 206 and 6590 targets were obtained for GCK and osteoporosis, respectively, in which 138 targets were identified as co-targets of GCK and osteoporosis based on intersection analysis. Five central gene clusters and hub genes (STAT3, PIK3R1, VEGFA, JAK2 and MAP2K1) were identified through protein-protein interaction network analysis. Gene Ontology (GO) enrichment implied that phosphatidylinositol-related biological process, molecular modification and function may play an important role for GCK in treatment and prevention of osteoporosis. Functions and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis suggested that 16 targets were enriched in the osteoclast differentiation. Also, except for being identified as hub targets, MAPK and phosphatidylinositol-related proteins were enriched in the downstream signaling of c-Fms in the osteoclast differentiation pathway. Molecular docking further confirmed that GCK could interact with active cavity on the surface of c-Fms (osteoclast differentiation-related membrane receptor), and their complex could be stabilized by three H-bonds with residues including Glu 664 (3.19 Å), Glu 664 (2.62 Å) and Cys 666 (2.78 Å). Summarily, GCK could interfere the occurrence and progress of osteoporosis through c-Fms-mediated MAPK and phosphatidylinositol-related signaling regulating osteoclast differentiation.