Zhubatchelor6874

" In this review, we will discuss some examples of therapeutically actionable molecules and pathways related to the regulation of cellular fitness and stress resistance in MM.Even with a rare occurrence of only 1.35% of cancer cases in the United States of America, brain tumors are considered as one of the most lethal malignancies. Ivacaftor The most aggressive and invasive type of brain tumor, glioblastoma, accounts for 60-70% of all gliomas and presents with life expectancy of only 12-18 months. Despite trimodal treatment and advances in diagnostic and therapeutic methods, there are no significant changes in patient outcome. Our understanding of glioblastoma was significantly improved with the introduction of next generation sequencing technologies. This led to the identification of different genetic and molecular subtypes, which greatly improve glioblastoma diagnosis. Still, because of the poor life expectancy, novel diagnostic, and treatment methods are broadly explored. Epigenetic modifications like methylation and changes in histone acetylation are such examples. Recently, in addition to genetic and molecular characteristics, epigenetic profiling of glioblastomas is also used for sample classification. Further advancement of next generation sequencing technologies is expected to identify in detail the epigenetic signature of glioblastoma that can open up new therapeutic opportunities for glioblastoma patients. This should be complemented with the use of computational power i.e., machine and deep learning algorithms for objective diagnostics and design of individualized therapies. Using a combination of phenotypic, genotypic, and epigenetic parameters in glioblastoma diagnostics will bring us closer to precision medicine where therapies will be tailored to suit the genetic profile and epigenetic signature of the tumor, which will grant longer life expectancy and better quality of life. Still, a number of obstacles including potential bias, availability of data for minorities in heterogeneous populations, data protection, and validation and independent testing of the learning algorithms have to be overcome on the way.Glioma groups, including lower-grade glioma (LGG) and glioblastoma multiforme (GBM), are the most common primary brain tumor. Malignant gliomas, especially glioblastomas, are associated with a dismal prognosis. Hypoxia is a driver of the malignant phenotype in glioma groups; it triggers a cascade of immunosuppressive processes and malignant cellular responses (tumor progression, anti-apoptosis, and resistance to chemoradiotherapy), which result in disease progression and poor prognosis. However, approaches to determine the extent of hypoxia in the tumor microenvironment are still unclear. Here, we downloaded 575 LGG patients and 354 GBM patients from Chinese Glioma Genome Atlas (GGGA), and 530 LGG patients and 167 GBM patients from The Cancer Genome Atlas (TCGA) with RNA sequence and clinicopathological data. We developed a hypoxia risk model to reflect the immune microenvironment in glioma and predict prognosis. High hypoxia risk score was associated with poor prognosis and indicated an immunosuppressive microenvironment. Hypoxia signature significantly correlated with clinical and molecular features and could serve as an independent prognostic factor for glioma patients. Moreover, Gene Set Enrichment Analysis showed that gene sets associated with the high-risk group were involved in carcinogenesis and immunosuppression signaling. In conclusion, we developed and validated a hypoxia risk model, which served as an independent prognostic indicator and reflected overall immune response intensity in the glioma microenvironment.Cancer cells show a formidable capacity to survive under stringent conditions, to elude mechanisms of control, such as apoptosis, and to resist therapy. Cancer cells reprogram their metabolism to support uncontrolled proliferation and metastatic progression. Phenotypic and functional heterogeneity are hallmarks of cancer cells, which endow them with aggressiveness, metastatic capacity, and resistance to therapy. This heterogeneity is regulated by a variety of intrinsic and extrinsic stimuli including those from the tumor microenvironment. Increasing evidence points to a key role for the metabolism of non-essential amino acids in this complex scenario. Here we discuss the impact of proline metabolism in cancer development and progression, with particular emphasis on the enzymes involved in proline synthesis and catabolism, which are linked to pathways of energy, redox, and anaplerosis. In particular, we emphasize how proline availability influences collagen synthesis and maturation and the acquisition of cancer cell plasticity and heterogeneity. Specifically, we propose a model whereby proline availability generates a cycle based on collagen synthesis and degradation, which, in turn, influences the epigenetic landscape and tumor heterogeneity. Therapeutic strategies targeting this metabolic-epigenetic axis hold great promise for the treatment of metastatic cancers.Circular RNAs (circRNAs), which act as initiators and promoters of various diseases, were thought to be mostly noncoding RNAs (ncRNAs) in eukaryotes, until recent studies confirmed that some circRNAs have the function of encoding proteins. Accumulating research findings have proved that dysregulation of circRNAs is associated with the developmental process of multiple cancers. circHIPK3, an example of circRNA, is frequently expressed in many diseases, such as diabetes, age-related cataract, idiopathic pulmonary fibrosis, preeclampsia, osteoblasts, and retinal vascular dysfunction, leading to disease development and progression. In addition, circHIPK3 may also serve as a potential biomarker, to help us know more about the rules of occurrence and development of cancers. In recent studies, many circHIPK3-related cancers have been identified, including nasopharyngeal carcinoma, gallbladder cancer, lung cancer, hepatocellular carcinoma, osteosarcoma, glioma, colorectal cancer, ovarian cancer, bladder cancer, prostate cancer, gastric cancer, oral squamous cell carcinoma, and chronic myeloid leukemia. This review summarizes recent studies on the biological mechanisms of circHIPK3 and expounds the molecular mechanisms of circHIPK3 in these malignant tumors.