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      Lung Cancers: Molecular Characterization, Clonal Heterogeneity and Evolution, and Cancer Stem Cells

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          Abstract

          Lung cancer causes the largest number of cancer-related deaths in the world. Most (85%) of lung cancers are classified as non-small-cell lung cancer (NSCLC) and small-cell lung cancer (15%) (SCLC). The 5-year survival rate for NSCLC patients remains very low (about 16% at 5 years). The two predominant NSCLC histological phenotypes are adenocarcinoma (ADC) and squamous cell carcinoma (LSQCC). ADCs display several recurrent genetic alterations, including: KRAS, BRAF and EGFR mutations; recurrent mutations and amplifications of several oncogenes, including ERBB2, MET, FGFR1 and FGFR2; fusion oncogenes involving ALK, ROS1, Neuregulin1 (NRG1) and RET. In LSQCC recurrent mutations of TP53, FGFR1, FGFR2, FGFR3, DDR2 and genes of the PI3K pathway have been detected, quantitative gene abnormalities of PTEN and CDKN2A. Developments in the characterization of lung cancer molecular abnormalities provided a strong rationale for new therapeutic options and for understanding the mechanisms of drug resistance. However, the complexity of lung cancer genomes is particularly high, as shown by deep-sequencing studies supporting the heterogeneity of lung tumors at cellular level, with sub-clones exhibiting different combinations of mutations. Molecular studies performed on lung tumors during treatment have shown the phenomenon of clonal evolution, thus supporting the occurrence of a temporal tumor heterogeneity.

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          Most cited references242

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          Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin.

          Recent genomic analyses of pathologically defined tumor types identify "within-a-tissue" disease subtypes. However, the extent to which genomic signatures are shared across tissues is still unclear. We performed an integrative analysis using five genome-wide platforms and one proteomic platform on 3,527 specimens from 12 cancer types, revealing a unified classification into 11 major subtypes. Five subtypes were nearly identical to their tissue-of-origin counterparts, but several distinct cancer types were found to converge into common subtypes. Lung squamous, head and neck, and a subset of bladder cancers coalesced into one subtype typified by TP53 alterations, TP63 amplifications, and high expression of immune and proliferation pathway genes. Of note, bladder cancers split into three pan-cancer subtypes. The multiplatform classification, while correlated with tissue-of-origin, provides independent information for predicting clinical outcomes. All data sets are available for data-mining from a unified resource to support further biological discoveries and insights into novel therapeutic strategies. Copyright © 2014 Elsevier Inc. All rights reserved.
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            Innate Immune Landscape in Early Lung Adenocarcinoma by Paired Single-Cell Analyses

            To guide the design of immunotherapy strategies for patients with early stage lung tumors, we developed a multiscale immune profiling strategy to map the immune landscape of early lung adenocarcinoma lesions to search for tumor-driven immune changes. Utilizing a barcoding method that allows a simultaneous single cell analysis of the tumor, non-involved lung and blood cells together with multiplex tissue imaging to assess spatial cell distribution, we provide a detailed immune cell atlas of early lung tumors. We show that stage I lung adenocarcinoma lesions already harbor significantly altered T cell and NK cell compartments. Moreover, we identified changes in tumor infiltrating myeloid cell (TIM) subsets that likely compromise anti-tumor T cell immunity. Paired single cell analyses thus offer valuable knowledge of tumor-driven immune changes, providing a powerful tool for the rational design of immune therapies. Comparing single tumor cells with adjacent normal tissue and blood from patients with lung adenocarcinoma charts early changes in tumor immunity and provides insights to guide immunotherapy design.
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              Basal cells as stem cells of the mouse trachea and human airway epithelium.

              The pseudostratified epithelium of the mouse trachea and human airways contains a population of basal cells expressing Trp-63 (p63) and cytokeratins 5 (Krt5) and Krt14. Using a KRT5-CreER(T2) transgenic mouse line for lineage tracing, we show that basal cells generate differentiated cells during postnatal growth and in the adult during both steady state and epithelial repair. We have fractionated mouse basal cells by FACS and identified 627 genes preferentially expressed in a basal subpopulation vs. non-BCs. Analysis reveals potential mechanisms regulating basal cells and allows comparison with other epithelial stem cells. To study basal cell behaviors, we describe a simple in vitro clonal sphere-forming assay in which mouse basal cells self-renew and generate luminal cells, including differentiated ciliated cells, in the absence of stroma. The transcriptional profile identified 2 cell-surface markers, ITGA6 and NGFR, which can be used in combination to purify human lung basal cells by FACS. Like those from the mouse trachea, human airway basal cells both self-renew and generate luminal daughters in the sphere-forming assay.
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                Author and article information

                Journal
                Cancers (Basel)
                Cancers (Basel)
                cancers
                Cancers
                MDPI
                2072-6694
                27 July 2018
                August 2018
                : 10
                : 8
                : 248
                Affiliations
                Department of Hematology, Oncology and Molecular Medicine, Istituto Superiore di Sanità, 00161 Rome, Italy; germana.castelli@ 123456iss.it (G.C.); elvira.pelosi@ 123456iss.it (E.P.)
                Author notes
                [* ]Correspondence: ugo.testa@ 123456iss.it
                Author information
                https://orcid.org/0000-0001-7900-8942
                Article
                cancers-10-00248
                10.3390/cancers10080248
                6116004
                30060526
                eb882e42-2681-4cd3-bdad-0438a6085b49
                © 2018 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 05 June 2018
                : 20 July 2018
                Categories
                Review

                non-small cell lung cancer,small cell lung cancer,cancer stem cells,genomic profiling,membrane cell markers,tumor xenotransplantation assay

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