Search results: Found 2

Listing 1 - 2 of 2
Sort by
Cancer Biomarkers and Targets in Digestive Organs

Authors: ---
ISBN: 9783039214631 / 9783039214648 Year: Pages: 146 DOI: 10.3390/books978-3-03921-464-8 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Medicine (General)
Added to DOAB on : 2019-12-09 11:49:15
License:

Loading...
Export citation

Choose an application

Abstract

Identification and development of cancer biomarkers and targets have greatly accelerated progress towards precision medicine in oncology. Studies of tumor biology have not only provided insights into the mechanisms underlying carcinogenesis, but also led to discovery of molecules that have been developed into cancer biomarkers and targets. Multi-platforms for molecular characterization of tumors using next-generation genomic sequencing, immunohistochemistry, in situ hybridization, and blood-based biopsies have greatly expanded the portfolio of potential biomarkers and targets. These cancer biomarkers have been developed for diagnosis, early detection, prognosis, and prediction of treatment response. The molecular targets have been exploited for anti-cancer therapy and delivery of therapeutic agents. This Special Issue of Biomedicines focuses on recent advances in the discovery, characterization, translation, and clinical application of cancer biomarkers and targets in malignant diseases of the digestive system. The goal is to stimulate basic and translational research and clinical collaboration in this exciting field with the hope of developing strategies for prevention and early detection/diagnosis of cancer in digestive organs, and improving therapeutic and psychosocial outcomes in patients with these malignant diseases.

Keywords

colorectal cancer --- intestinal disorder --- intestinal tumors --- zebrafish --- stereotactic body radiation therapy --- immunotherapy --- biomarkers --- Asian Cancer Research Group (ACRG) --- gastric carcinoma --- molecular profiling --- precision therapy --- pembrolizumab --- predictive biomarkers --- ramucirumab --- The Cancer Genome Atlas (TCGA) --- therapeutic targets --- trastuzumab --- biliary tract carcinoma --- chemotherapy --- clinical trial --- colorectal carcinoma --- gastric carcinoma --- gastrointestinal oncology --- hepatocellular carcinoma --- immunotherapy --- pancreatic carcinoma --- targeted therapy --- Liver transplantation --- liver graft injury --- intragraft gene expression profiles --- cell adhesion molecules --- CD274 --- HFE --- hepatocellular carcinoma --- immunohistochemistry --- molecular profiling --- next-generation sequencing --- precision medicine --- predictive biomarkers --- gastrointestinal oncology --- pancreatic carcinoma --- hepatocellular carcinoma --- biliary tract carcinoma --- gastric carcinoma --- colorectal carcinoma --- stereotactic body radiation therapy --- liver transplant --- targeted therapy --- psychosocial support --- G protein–coupled receptors --- cholecystokinin --- gastrin --- gastrin-releasing peptide --- bombesin --- neurokinin --- neurotensin --- somatostatin --- circulating tumor cells --- colorectal carcinoma --- CAM invasion assay --- phenotypic mosaics --- tumor progenitor --- biomarker --- gastrointestinal malignancies --- immunotherapy --- n/a

Application of Bioinformatics in Cancers

Author:
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
License:

Loading...
Export citation

Choose an application

Abstract

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

Listing 1 - 2 of 2
Sort by
Narrow your search

Publisher

MDPI - Multidisciplinary Digital Publishing Institute (2)


License

CC by-nc-nd (2)


Language

eng (2)


Year
From To Submit

2019 (2)