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This Special Issue celebrates the 25th anniversary of the discovery of the first microRNA. The size of the microRNome and complexity of animal body plans and organ systems suggests a role for microRNAs in cell fate determination and differentiation. More than 2000 sequences have been proposed to represent unique microRNA genes in humans, with an increasing number of mechanistic roles identified in developmental, physiological, and pathological processes. Thus, dysregulation of a few key microRNAs can have a profound global effect on the gene expression and molecular programs of a cell. This great potential for clinical intervention has captured the interest and imagination of researchers in many fields. However, very few fields have been as prolific as the field of cancer research. This Special Issue provides but a glimpse of the large body of literature of microRNA biology in cancer research, containing 4 original research studies and 4 review articles that focus on specific hematologic or solid tumors in disease. Collectively, these articles highlight state-of-the-art approaches and methodologies for microRNA detection in tissue, blood, and other body fluids in a range of biomarkers applications, from early cancer detection to prognosis and treatment response. The articles also address some of the challenges regarding clinical implementation.

leukemia --- n/a --- cell lines --- hepatitis B virus --- long non coding RNA --- normalization of miRNA expression in RT-qPCR --- children --- colorectal --- review --- bevacizumab --- tumor budding cells --- oral cancer --- liquid biopsy --- hepatocellular carcinoma --- small t-antigen --- colorectal cancer --- protein-miRNA complex --- biomarkers --- biomarker --- interleukin-1? --- tissue analysis --- miRNAs --- T-cell acute lymphoblastic leukemia (T-ALL) --- leukoplakia --- inflammation --- exosomes --- circulating free DNA --- hepatitis C virus --- miRNA --- miR-21 --- extracellular microRNA --- endogenous controls --- lymphoma --- confocal slide scanning microscopy --- early diagnosis --- reference genes --- large T-antigen --- microRNA --- miRNA (microRNA) --- cancer --- TNF-? --- plasma --- MicroRNAs.

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Cancer is a leading cause of death worldwide, claiming millions of lives each year. Cancer biology is an essential research field to understand how cancer develops, evolves, and responds to therapy. By taking advantage of a series of “omics” technologies (e.g., genomics, transcriptomics, and epigenomics), computational methods in bioinformatics and machine learning can help scientists and researchers to decipher the complexity of cancer heterogeneity, tumorigenesis, and anticancer drug discovery. Particularly, bioinformatics enables the systematic interrogation and analysis of cancer from various perspectives, including genetics, epigenetics, signaling networks, cellular behavior, clinical manifestation, and epidemiology. Moreover, thanks to the influx of next-generation sequencing (NGS) data in the postgenomic era and multiple landmark cancer-focused projects, such as The Cancer Genome Atlas (TCGA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC), machine learning has a uniquely advantageous role in boosting data-driven cancer research and unraveling novel methods for the prognosis, prediction, and treatment of cancer.

tumor mutational burden --- DNA damage repair genes --- immunotherapy --- biomarker --- biomedical informatics --- breast cancer --- estrogen receptor alpha --- persistent organic pollutants --- drug-drug interaction networks --- molecular docking --- NGS --- ctDNA --- VAF --- liquid biopsy --- filtering --- variant calling --- DEGs --- diagnosis --- ovarian cancer --- PUS7 --- RMGs --- CPA4 --- bladder urothelial carcinoma --- immune cells --- T cell exhaustion --- checkpoint --- architectural distortion --- image processing --- depth-wise convolutional neural network --- mammography --- bladder cancer --- Annexin family --- survival analysis --- prognostic signature --- therapeutic target --- R Shiny application --- RNA-seq --- proteomics --- multi-omics analysis --- T-cell acute lymphoblastic leukemia --- CCLE --- sitagliptin --- thyroid cancer (THCA) --- papillary thyroid cancer (PTCa) --- thyroidectomy --- metastasis --- drug resistance --- n/a --- biomarker identification --- transcriptomics --- machine learning --- prediction --- variable selection --- major histocompatibility complex --- bidirectional long short-term memory neural network --- deep learning --- cancer --- incidence --- mortality --- modeling --- forecasting --- Google Trends --- Romania --- ARIMA --- TBATS --- NNAR

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The mechanistic target of rapamycin (mTOR) is a major signaling intermediary that coordinates favorable environmental conditions with cell growth. Indeed, as part of two functionally distinct protein complexes, named mTORC1 and mTORC2, mTOR regulates a variety of cellular processes, including protein, lipid, and nucleotide synthesis, as well as autophagy. Over the last two decades, major molecular advances have been made in mTOR signaling and have revealed the complexity of the events implicated in mTOR function and regulation. In parallel, the role of mTOR in diverse pathological conditions has also been identified, including in cancer, hamartoma, neurological, and metabolic diseases. Through a series of articles, this book focuses on the role played by mTOR in cellular processes, metabolism in particular, and highlights a panel of human diseases for which mTOR inhibition provides or might provide benefits. It also addresses future studies needed to further characterize the role of mTOR in selected disorders, which will help design novel therapeutic approaches. It is therefore intended for everyone who has an interest in mTOR biology and its application in human pathologies.

n/a --- primary cilia --- neurodegeneration --- nutrient sensor --- PI3K --- transcriptomics --- phosphorylation --- metabolic reprogramming --- autophagy --- Alzheimer’s disease --- rapalogs --- liver --- angiogenesis --- mTOR complex --- MBSCs --- advanced biliary tract cancers --- Medulloblastoma --- epithelial to mesenchymal transition --- AMPK --- p70S6K --- lipid metabolism --- thyroid cancer --- sodium iodide symporter (NIS)/SLC5A5 --- male fertility --- anesthesia --- illumina --- mTOR inhibitor --- miRNA --- Hutchinson-Gilford progeria syndrome (HGPS) --- eIFs --- Emery-Dreifuss muscular dystrophy (EDMD) --- glucose --- AKT --- oral cavity squamous cell carcinoma (OSCC) --- glucose and lipid metabolism --- cellular signaling --- aging --- tumor microenvironment --- rapamycin --- leukemia --- chloral hydrate --- rapalogues --- schizophrenia --- T-cell acute lymphoblastic leukemia --- senescence --- lamin A/C --- neurotoxicity --- neurodevelopment --- inhibitor --- methamphetamine --- pulmonary fibrosis --- mTOR --- mTOR inhibitors --- combination therapy --- proteolysis --- fluid shear stress --- tumour cachexia --- biomarkers --- synapse --- gluconeogenesis --- mTOR signal pathway --- Sertoli cells --- immunosenescence --- miRNome --- protein aggregation --- senolytics --- metabolism --- NGS --- mTORC2 --- mTORC1 --- metabolic diseases --- IonTorrent --- apoptosis --- dopamine receptor --- nocodazole --- microenvironment --- everolimus --- acute myeloid leukemia --- immunotherapy --- spermatogenesis --- bone remodeling --- signalling --- targeted therapy --- ageing --- therapy --- NVP-BEZ235 --- fructose --- physical activity --- laminopathies --- MC3T3-E1 cells --- cell signaling --- microRNA --- cancer --- lipolysis --- melatonin --- Parkinson’s disease --- Alzheimer's disease --- Parkinson's disease