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Adverse Effects of Cancer Chemotherapy: Anything New to Improve Tolerance and Reduce Sequelae?

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889454822 Year: Pages: 245 DOI: 10.3389/978-2-88945-482-2 Language: English
Publisher: Frontiers Media SA
Subject: Science (General) --- Therapeutics --- Medicine (General) --- Oncology
Added to DOAB on : 2019-01-23 14:53:42
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Abstract

Advances in anti-cancer chemotherapy over recent years have led to improved efficacy in curing or controlling many cancers. Some chemotherapy-related side-effects are well recognized and include: nausea, vomiting, bone marrow suppression, peripheral neuropathy, cardiac and skeletal muscle dysfunction and renal impairment. However, it is becoming clearer that some chemotherapy-related adverse effects may persist even in long term cancer survivors. Problems such as cognitive, cardiovascular and gastrointestinal dysfunction, and neuropathy may lead to substantial long term morbidity. Despite improvements in treatments to counteract acute chemotherapy-induced adverse effects, they are often incompletely effective. Furthermore, counter-measures for some acute side-effects and many potential longer term sequelae of anti-cancer chemotherapy have not been developed. Thus, new insights into prevalence and mechanisms of cancer chemotherapy-related side effects are needed and new approaches to improving tolerance and reduce sequelae of cancer chemotherapy are urgently needed.The present Research Topic focuses on adverse effects and sequelae of chemotherapy and strategies to counteract them.

Curcumin in Health and Disease

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ISBN: 9783039214495 / 9783039214501 Year: Pages: 274 DOI: 10.3390/books978-3-03921-450-1 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Chemistry (General)
Added to DOAB on : 2019-12-09 11:49:15
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The plant-derived polyphenol curcumin has been used in promoting health and combating disease for thousands of years. Its therapeutic effects have been successfully utilized in Ayurvedic and Traditional Chinese Medicine in order to treat inflammatory diseases. Current results from modern biomolecular research reveal the modulatory effects of curcumin on a variety of signal transduction pathways associated with inflammation and cancer. In this context, curcumin’s antioxidant, anti-inflammatory, anti-tumorigenic, and even anti-metastatic activities are discussed. On the cellular level, the reduced activity of several transcription factors (such as NFkB or AP-1) and the suppression of inflammatory cytokines, matrix degrading enzymes, metastasis related genes and even microRNAs are reported. On functional levels, these molecular effects translate into reduced proliferative, invasive, and metastatic capacity, as well as induced tumor cell apoptosis. All these effects have been observed not only in vitro but also in animal models. In combination with anti-neoplastic drugs like Taxol, kinase inhibitors, and radiation therapy, curcumin potentiates the drugs’ therapeutic power and can protect against undesired side effects. Natural plant-derived compounds like curcumin have one significant advantage: They do not usually cause side effects. This feature qualifies curcumin for primary prevention in healthy persons with a predisposition to cancer, arteriosclerosis, or chronic inflammatory diseases. Nonetheless, curcumin is considered safe, although potential toxic effects stemming from high dosages, long-term intake, and pharmacological interactions with other compounds have yet to be assessed. This Special Issue examines in detail and updates current research on the molecular targets, protective effects, and modes of action of natural plant-derived compounds and their roles in the prevention and treatment of human diseases.

Keywords

brain ischemia --- curcumin --- Alzheimer’s disease --- neurodegeneration --- amyloid --- tau protein --- autophagy --- mitophagy --- apoptosis --- genes --- glioblastoma multiforme --- autophagy --- mitophagy --- curcumin --- chaperone-mediated autophagy --- Akt/mTOR signaling --- transmission electron microscopy --- Curcuma longa --- turmeric tuber --- Zingiberaceae --- TLC bioautography --- antimicrobial agents --- ImageJ --- TLC-MS --- hydrostatic counter-current chromatography --- centrifugal partition chromatography --- curcumin --- death receptor --- apoptosis --- curcumin --- anticancer --- structure activity relationship --- cellular pathway --- mechanism of action --- delivery system --- wound --- wound healing --- diet --- nutrition --- micronutrients --- macronutrients --- curcumin --- amino-acids --- vitamins --- minerals --- curcumin --- oxidative metabolites --- inflamm-aging --- cancer --- metabolic reprogramming --- direct protein binding --- IL-17 --- STAT3 --- SHMT2 --- ageing --- anti-cancer --- autophagy --- microbiota --- senescence --- senolytics --- curcumin --- transthyretin --- amyloidosis --- protein aggregation --- protein misfolding --- drug discovery --- curcumin --- renal cell cancer --- tumor growth --- tumor proliferation --- cell cycling --- curcumin --- reflux esophagitis --- gastroprotection --- gastric ulcer --- Helicobacter pylori --- gastric cancer --- curcumin --- complementary medicine --- cancer treatment --- supportive care --- antioxidants --- anti-inflamation --- ulcerative colitis --- Crohn’s disease --- necrotizing enterocolitis --- curcumin --- inflammatory bowel disease --- curcumin --- silica --- chitosan --- nanoparticles --- anti-tumor --- antioxidant activity --- n/a

Application of Bioinformatics in Cancers

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ISBN: 9783039217885 / 9783039217892 Year: Pages: 418 DOI: 10.3390/books978-3-03921-789-2 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- Biotechnology
Added to DOAB on : 2019-12-09 11:49:16
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This collection of 25 research papers comprised of 22 original articles and 3 reviews is brought together from international leaders in bioinformatics and biostatistics. The collection highlights recent computational advances that improve the ability to analyze highly complex data sets to identify factors critical to cancer biology. Novel deep learning algorithms represent an emerging and highly valuable approach for collecting, characterizing and predicting clinical outcomes data. The collection highlights several of these approaches that are likely to become the foundation of research and clinical practice in the future. In fact, many of these technologies reveal new insights about basic cancer mechanisms by integrating data sets and structures that were previously immiscible.

Keywords

comorbidity score --- mortality --- locoregionally advanced --- HNSCC --- curative surgery --- traditional Chinese medicine --- health strengthening herb --- cancer treatment --- network pharmacology --- network target --- high-throughput analysis --- brain metastases --- colorectal cancer --- KRAS mutation --- PD-L1 --- tumor infiltrating lymphocytes --- drug resistance --- gefitinib --- erlotinib --- biostatistics --- bioinformatics --- Bufadienolide-like chemicals --- molecular mechanism --- anti-cancer --- bioinformatics --- cancer --- brain --- pathophysiology --- imaging --- machine learning --- extreme learning --- deep learning --- neurological disorders --- pancreatic cancer --- TCGA --- curation --- DNA --- RNA --- protein --- single-biomarkers --- multiple-biomarkers --- cancer-related pathways --- colorectal cancer --- DNA sequence profile --- Monte Carlo --- mixture of normal distributions --- somatic mutation --- tumor --- mutable motif --- activation induced deaminase --- AID/APOBEC --- transcriptional signatures --- copy number variation --- copy number aberration --- TCGA mining --- cancer CRISPR --- firehose --- gene signature extraction --- gene loss biomarkers --- gene inactivation biomarkers --- biomarker discovery --- chemotherapy --- microarray --- ovarian cancer --- predictive model --- machine learning --- overall survival --- observed survival interval --- skin cutaneous melanoma --- The Cancer Genome Atlas --- omics --- breast cancer prognosis --- artificial intelligence --- machine learning --- decision support systems --- cancer prognosis --- independent prognostic power --- omics profiles --- histopathological imaging features --- cancer --- intratumor heterogeneity --- genomic instability --- epigenetics --- mitochondrial metabolism --- miRNAs --- cancer biomarkers --- breast cancer detection --- machine learning --- feature selection --- classification --- denoising autoencoders --- breast cancer --- feature extraction and interpretation --- concatenated deep feature --- cancer modeling --- interaction --- histopathological imaging --- clinical/environmental factors --- oral cancer --- miRNA --- bioinformatics --- datasets --- biomarkers --- TCGA --- GEO DataSets --- hormone sensitive cancers --- breast cancer --- StAR --- estrogen --- steroidogenic enzymes --- hTERT --- telomerase --- telomeres --- alternative splicing --- network analysis --- hierarchical clustering analysis --- differential gene expression analysis --- cancer biomarker --- diseases genes --- variable selection --- false discovery rate --- knockoffs --- bioinformatics --- copy number variation --- cell-free DNA --- methylation --- mutation --- next generation sequencing --- self-organizing map --- head and neck cancer --- treatment de-escalation --- HP --- molecular subtypes --- tumor microenvironment --- Bioinformatics tool --- R package --- machine learning --- meta-analysis --- biomarker signature --- gene expression analysis --- survival analysis --- functional analysis --- bioinformatics --- machine learning --- artificial intelligence --- Network Analysis --- single-cell sequencing --- circulating tumor DNA (ctDNA) --- Neoantigen Prediction --- precision medicine --- Computational Immunology

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