• Rouse Pehrson posted an update 6 months ago

    with HCC and might be a potential biomarker for prognosis of HCC.

    Overexpression of NOP58 is negatively correlated with overall survival in patients with HCC and might be a potential biomarker for prognosis of HCC.

    STRIVE was a 4-year, multicenter, observational, open-label, single-arm study of natalizumab treatment in anti-JC virus antibody-negative (JCV-negative) relapsing-remitting multiple sclerosis (RRMS) patients with disease duration ≤ 3years. The objective of STRIVE was to examine no evidence of disease activity (NEDA) status and predictors of NEDA in natalizumab-treated patients with early RRMS.

    Proportions of patients with NEDA were evaluated along with baseline predictors of NEDA, annualized relapse rate, 24-week confirmed disability worsening (CDW), magnetic resonance imaging assessments (T2 and gadolinium-enhancing lesions), and serious adverse events.

    In years 1 and 2, 56.1% (95% confidence interval 48.7-63.4%) and 73.6% (95% CI 66.2-80.2%) of patients (intent-to-treat population ), respectively, achieved NEDA. In years 3 and 4, 84.6% (95% CI 78.0-89.9%) and 91.9% (95% CI 86.4-95.8%) of patients, respectively, achieved Clinical NEDA (no relapses or 24-week CDW). Baseline predictors of NEDA in year 4 were Expanded Disability Status Scale score ≤ 2.0 (odds ratio  = 3.85 ; p = 0.004) and T2 lesion volume > 4cc (OR = 0.39 ; p = 0.046), with the latter also predicting Clinical NEDA in year 4 (OR = 0.21 ; p = 0.038). The cumulative probability of CDW at year 4 was 19.3%. Serious adverse events were reported in 11.3% of patients.

    These results support the long-term safety and effectiveness of natalizumab. Baseline predictors of NEDA help to inform benefit-risk assessments of natalizumab treatment in JCV-negative patients with early RRMS.

    ClinicalTrials.gov identifier NCT01485003.

    ClinicalTrials.gov identifier NCT01485003.According to data from the World Health Organization, cardiovascular diseases and cancer are the two leading causes of mortality in the world . Despite the immense effort to study these diseases and the constant innovation in treatment modalities, the number of deaths associated with cardiovascular diseases and cancer is predicted to increase in the coming decades . From 2008 to 2030, due to population growth and population aging in many parts of the world, the number of deaths caused by cancer globally is projected to increase by 45%, corresponding to an annual increase of around four million people . For cardiovascular diseases, this number is six million people . In the United States, treatments for these two diseases are among the most costly and result in a disproportionate impact on low- and middleincome people. learn more As the fight against these fatal diseases continues, it is crucial that we continue our investigation and broaden our understanding of cancer and cardiovascular diseases to innovate me have been medically prescribed to patients to treat certain diseases, such as angina pectoris . Other metabolic pathways, such as tryptophan catabolism and pyruvate metabolism, were also dysregulated in both diseases, making them promising treatment targets. Understanding the overlapping traits exhibited by both cancer metabolism and cardiovascular disease metabolism can give us a more holistic view of how important metabolic dysregulation is in the progression of diseases. Using established links between these illnesses, researchers can take advantage of the discoveries from one field and potentially apply them to the other. In this chapter, we highlight some promising therapeutic discoveries that can support our fight against cancer, based on common metabolic traits displayed in both cancer and cardiovascular diseases.Despite the many recent breakthroughs in cancer research, oncology has traditionally been seen as a distinct field from other diseases. Recently, more attention has been paid to repurposing established therapeutic strategies and targets of other diseases towards cancer treatment, with some of these attempts generating promising outcomes . Recent studies using advanced metabolomics technologies have shown evidence of close metabolic similarities between cancer and neurological diseases. These studies have unveiled several metabolic characteristics shared by these two categories of diseases, including metabolism of glutamine, gamma-aminobutyric acid (GABA), and N-acetyl-aspartyl-glutamate (NAAG) . The striking metabolic overlap between cancer and neurological diseases sheds light on novel therapeutic strategies for cancer treatment. For example, 2-(phosphonomethyl) pentanedioic acid (2-PMPA), one of the glutamate carboxypeptidase II (GCP II) inhibitors that prevent the conversion of NAAG to glutamate, has been shown to suppress cancer growth . These promising results have led to an increased interest in integrating this metabolic overlap between cancer and neurological diseases into the study of cancer metabolism. The advantages of studying this metabolic overlap include not only drug repurposing but also translating existing knowledge from neurological diseases to the field of cancer research. This chapter discusses the specific overlapping metabolic features between cancer and neurological diseases, focusing on glutamine, GABA, and NAAG metabolisms. Understanding the interconnections between cancer and neurological diseases will guide researchers and clinicians to find more effective cancer treatments.Diabetes mellitus, commonly known as diabetes, and cancer are two of the most common diseases plaguing the world today. According to the Centers for Disease Control and Prevention (CDC), there are currently more than 20 million people with diabetes in the United States . According to the International Agency for Research on Cancer (IARC), there were around 18 million people diagnosed with cancer, with approximately ten million deaths globally in 2018 . Given the prevalence and deadliness of diabetes and cancer, these two diseases have long been the focus of many researchers with the goal of improving treatment outcomes. While diabetes and cancer may seem to be two very different diseases at first glance, they share several similarities, especially regarding their metabolic characteristics. This chapter discusses the similarities and relationships between the metabolism of diabetes, especially type 2 diabetes (T2D), and cancer, including their abnormal glucose and amino acid metabolism, the contribution of hyperglycemia to oncogenic mutation, and the contribution of hyperinsulinemia to cancer progression.

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