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Cross Talk between Lymph Node Lymphatic Endothelial Cells and T Cells in Inflammation and Cancer

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889453511 Year: Pages: 100 DOI: 10.3389/978-2-88945-351-1 Language: English
Publisher: Frontiers Media SA
Subject: Medicine (General) --- Allergy and Immunology
Added to DOAB on : 2018-02-27 16:16:45
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Abstract

Lymphocytes constantly survey the lymph nodes in search for potential infection by a pathogen. They enter the afferent lymphatic vessel that serves as a conduit to transport the motile lymphocytes to the draining lymph node. Lymphatic vessels (LVs) are present in most vascularized tissues. They are traditionally regarded as passive conduits for soluble antigens and leukocytes. Afferent LVs begin as blind ended capillaries, which give rise to collecting vessels that merge and connect with draining lymph nodes (dLNs). Initial lymphatic capillaries are composed of Lymphatic Endothelial Cells (LECs) connected by discontinuous cell junctions, which join to form larger collecting lymphatic vessels, and ultimately feed into the LN subcapsular sinus. Within the LN, LECs are localized to the subcapsular, cortical, and medullary sinuses, where they interact with incoming and exiting leukocytes. LECs, and in general LN stromal cells, have emerged in the recent years as active players in the immune response. In support to this,studies have shown that the immune response generated during inflammation and under pathologic conditions is accompanied by modeling of the LVs and generation of new lymphatics, a process known as lymphangiogenesis. These facts strongly suggest that LECs and stromal LN cells in general, are not inert players but rather are part of the immune response by organizing immune cells movement, exchanging information and supplying survival factors. The purpose of this research topic is to review the role of the LECs during immune homeostasis and cancer. Considering the critical role of lymphangiogenesis in many pathologies like chronic and acute inflammation, autoimmunity, wound healing, graft rejection, and tumor metastasis, it is important to understand the molecular mechanisms that govern the cross talks between the LECs and immune cells during homeostasis and inflammation.

Pleiotropic Action of Selenium in the Prevention and Treatment of Cancer, and Related Diseases

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ISBN: 9783038976929 Year: Pages: 166 DOI: 10.3390/books978-3-03897-693-6 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Biology --- Science (General)
Added to DOAB on : 2019-04-05 11:07:22
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This book will cover topics related to the preparation and use of heterogeneous catalytic systems for the transformation of renewable sources, as well as of materials deriving from agro-industrial wastes and by-products. At the same time, the ever-increasing importance of bioproducts, due to the acceptance and request of consumers, makes the upgrade of biomass into chemicals and materials not only an environmental issue, but also an economical advantage.

Towards New Promising Discoveries for Lung Cancer Patients: A Selection of Papers from the First Joint Meeting on Lung Cancer of the FHU OncoAge (Nice, France) and the MD Anderson Cancer Center (Houston, TX, USA)

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ISBN: 9783039214518 / 9783039214525 Year: Pages: 230 DOI: 10.3390/books978-3-03921-452-5 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Medicine (General) --- Oncology
Added to DOAB on : 2019-12-09 11:49:15
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This Special Issue of Cancers (Basel) is mainly dedicated to selecting papers from the talks given during the first Joint Meeting on Lung Cancer (JMLC) between the MD Anderson Cancer Center (Houston, Texas USA) and the Hospital University Federation (HUF) OncoAge (University Côte d’Azur, Nice, France) (Nice, September 2018). The central theme of JMLC is to discuss new advances and exchange ideas regarding lung cancer. Notably, the talks covered different topics on new therapeutic strategies (targeted therapy and immuno-oncology), molecular and cellular biology, biomarkers, and the epidemiology of lung cancer. Special attention was also given to lung cancer in elderly patients. The articles published in this Special Issue covered subjects such as the assessment of new biomarkers and new approaches for the early detection of lung cancer, epidemiological data, and emphasized a place for the newly characterized cellular pathways in lung cancer, which opens room for therapeutic perspectives for lung cancer patients.

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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