Gene/Protein Disease Symptom Drug Enzyme Compound
Pivot Concepts:   Target Concepts:
Query: UMLS:C0042963 (vomiting)
 31,883 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

To date, dacarbazine (DTIC) has been the most effective drug in the treatment of advanced metastatic melanoma, achieving response rates of up to 28% (mean, 21%). Multidrug responses were generally no better than those obtained using monotherapy. A quite promising clinical trial was conducted using the new nitrosourea fotemustine. A total of 19 patients presenting with advanced malignant melanoma (clinical stage IV according to the 1987 UICC classification system) underwent treatment involving a more rapid infusion of the drug and a reduction in the rest period from 5 to 3 weeks. This monotherapy with fotemustine yielded two complete responses and seven partial responses; in addition, four patients showed no change and six cases progressed after the induction cycle (median duration of response to date, 7.6 months, including four cases that have not relapsed). Fotemustine was well tolerated by the patients, with the only mild side effects being thrombocytopenia, leukocytopenia and easily controlled nausea/vomiting. Preclinical studies performed previously indicated that fotemustine inhibits enzymes involved in the ribonucleotide reduction pathway (i.e. DNA synthesis), whereby responding patients (n = 3) appeared to favor the thioredoxin reductase/thioredoxin electron transfer to ribonucleotide reductase, whereas non-responders (n = 4) expressed the alternate glutathione reductase/glutaredoxin mechanism. The 47% response rate obtained in these studies vs the 24% reported previously for fotemustine may reflect variations in enzymes in the ribonucleotide reduction pathway in different patients. However, the efficacy of fotemustine against advanced melanoma warrants more extensive trials of this drug, especially since the quality of life of the patients during and after chemotherapy was not severely affected.
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PMID:Positive phase II study in the treatment of advanced malignant melanoma with fotemustine. 174 55

More than 50 million adults in America suffer from chronic pain. Opioids are commonly prescribed for their effectiveness in relieving many types of pain. However, excessive prescribing of opioids can lead to abuse, addiction, and death. Non-steroidal anti-inflammatory drugs (NSAIDs), another major class of analgesic, also have many problematic side effects including headache, dizziness, vomiting, diarrhea, nausea, constipation, reduced appetite, and drowsiness. There is an urgent need for the understanding of molecular mechanisms that underlie drug abuse and addiction to aid in the design of new preventive or therapeutic agents for pain management. To facilitate pain related small-molecule signaling pathway studies and the prediction of potential therapeutic target(s) for the treatment of pain, we have constructed a comprehensive platform of a pain domain-specific chemogenomics knowledgebase (Pain-CKB) with integrated data mining computing tools. Our new computing platform describes the chemical molecules, genes, proteins, and signaling pathways involved in pain regulation. Pain-CKB is implemented with a friendly user interface for the prediction of the relevant protein targets and analysis and visualization of the outputs, including HTDocking, TargetHunter, BBB predictor, and Spider Plot. Combining these with other novel tools, we performed three case studies to systematically demonstrate how further studies can be conducted based on the data generated from Pain-CKB and its algorithms and tools. First, systems pharmacology target mapping was carried out for four FDA approved analgesics in order to identify the known target and predict off-target interactions. Subsequently, the target mapping outcomes were applied to build physiologically based pharmacokinetic (PBPK) models for acetaminophen and fentanyl to explore the drug-drug interaction (DDI) between this pair of drugs. Finally, pharmaco-analytics was conducted to explore the detailed interaction pattern of acetaminophen reactive metabolite and its hepatotoxicity target, thioredoxin reductase.
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PMID:Pain Chemogenomics Knowledgebase (Pain-CKB) for Systems Pharmacology Target Mapping and Physiologically Based Pharmacokinetic Modeling Investigation of Opioid Drug-Drug Interactions. 3296 35