About this Research Topic
Pituitary adenomas are a category of neoplasms with a high degree of heterogeneity that occur in the central regulatory organ pituitary, which plays important roles in the hypothalamus–pituitary-targeted organ axis systems that impact on important physiological functions of human body. Rapidly developed multi-omics and systems biology are impacting on treatment of pituitary adenomas and changing the paradigms from the traditional single-factor strategy to a multi-parameter systematic strategy. A series of molecular alterations at different levels of genes (genome), RNAs (transcriptome), proteins (proteome), peptides (peptidome), metabolites (metabolome), and imaging characteristics (radiome) that resulted from exogenous and endogenous carcinogens are involved in pituitary tumorigenesis and mutually associate and function in a molecular network system, thus determines the difficulty in the use of a single molecule as biomarker to clarify its molecular mechanisms, and to predict, prevent, diagnose, and treat a pituitary adenoma. Of them, molecular network study plays central roles. A key molecule-panel biomarker that is derived from molecular network is necessary for accurately clinical practice of a pituitary adenoma. The modern multi-omics, computation biology, and systems biology technologies lead to the possibility in recognizing really reliable molecular-panel biomarker for research and clinical practice in pituitary adenomas.
We welcome authors to submit original research reports, review articles, and opinion articles to address the molecular networks, and molecular network-based molecular-panel biomarkers for pituitary tumors at the single or integrative levels of the DNAs (genome), RNAs (transcriptome), proteins (proteome), metabolites (metabolome), imaging characteristics (radiome), and interactome in this series. Potential topics include, but are not limited to,:
(1) different types of pituitary adenomas, including functional and nonfunctional pituitary adenomas, invasive and noninvasive pituitary adenomas, in the levels of cell, animal, and human models;
(2) different levels of omics study, including DNA, RNA, proteins, metabolite, protein post-translational modifications, and between-molecule crosstalks;
(3) pathway network analysis based on different levels of omics data;
(4) new computation model for molecular network analysis;
(5) molecular mechanisms of pituitary adenomas; (6) molecular-panel biomarkers of pituitary tumors.
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