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      A proteogenomic profile of early lung adenocarcinomas by protein co-expression network and genomic alteration analysis

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          Abstract

          The tumourigenesis of early lung adenocarcinomas, including adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and lepidic predominant invasive adenocarcinoma (LPA), remains unclear. This study aimed to capture disease-related molecular networks characterising each subtype and tumorigenesis by assessing 14 lung adenocarcinomas (AIS, five; MIA, five; LPA, four). Protein–protein interaction networks significant to the three subtypes were elucidated by weighted gene co-expression network analysis and pairwise G-statistics based analysis. Pathway enrichment analysis for AIS involved extracellular matrix proteoglycans and neutrophil degranulation pathway relating to tumour growth and angiogenesis. Whereas no direct networks were found for MIA, proteins significant to MIA were involved in oncogenic transformation, epithelial-mesenchymal transition, and detoxification in the lung. LPA was associated with pathways of HSF1-mediated heat shock response regulation, DNA damage repair, cell cycle regulation, and mitosis. Genomic alteration analysis suggested that LPA had both somatic mutations with loss of function and copy number gains more frequent than MIA. Oncogenic drivers were detected in both MIA and LPA, and also LPA had a higher degree of copy number loss than MIA. Our findings may help identifying potential therapeutic targets and developing therapeutic strategies to improve patient outcomes.

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          OPLS discriminant analysis: combining the strengths of PLS-DA and SIMCA classification

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            Genomic and immune profiling of pre-invasive lung adenocarcinoma

            Adenocarcinoma in situ and minimally invasive adenocarcinoma are the pre-invasive forms of lung adenocarcinoma. The genomic and immune profiles of these lesions are poorly understood. Here we report exome and transcriptome sequencing of 98 lung adenocarcinoma precursor lesions and 99 invasive adenocarcinomas. We have identified EGFR, RBM10, BRAF, ERBB2, TP53, KRAS, MAP2K1 and MET as significantly mutated genes in the pre/minimally invasive group. Classes of genome alterations that increase in frequency during the progression to malignancy are revealed. These include mutations in TP53, arm-level copy number alterations, and HLA loss of heterozygosity. Immune infiltration is correlated with copy number alterations of chromosome arm 6p, suggesting a link between arm-level events and the tumor immune environment.
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              Correlation of relative abundance ratios derived from peptide ion chromatograms and spectrum counting for quantitative proteomic analysis using stable isotope labeling.

              In this study, S. cerevisiae crude membrane fractions were prepared using the acid-labile detergent RapiGest from cells grown under rich and minimal media conditions using 14N and 15N ammonium sulfate as the sole nitrogen source. Four independent MudPIT analyses of 1:1 mixtures of sample were prepared and analyzed via quantitative multidimensional protein identification technology on a two-dimensional ion trap mass spectrometer. Using the method described in this study, low-abundance integral membrane proteins with up to 14 transmembrane domains were identified and their protein expression determined when sufficient spectrum counting and ion chromatogram information was generated. We demonstrate that spectrum counting and mass spectrometry derived ion chromatograms strongly correlate for determining quantitative changes in protein expression. Spectrum counting proved more reproducible and has a wider dynamic range contributing to the deviation of the two quantitative approaches from a perfect positive correlation.
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                Author and article information

                Contributors
                t-nisimura@marianna-u.ac.jp
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                12 August 2020
                12 August 2020
                2020
                : 10
                : 13604
                Affiliations
                [1 ]GRID grid.412764.2, ISNI 0000 0004 0372 3116, Department of Translational Medicine Informatics, , St. Marianna University School of Medicine, ; Kawasaki, Kanagawa 216-8511 Japan
                [2 ]GRID grid.412764.2, ISNI 0000 0004 0372 3116, Department of Chest Surgery, , St. Marianna University School of Medicine, ; Kawasaki, Kanagawa 216-8511 Japan
                [3 ]ACT Genomics Co., LTD., Taipei, 114 Taiwan
                [4 ]GRID grid.412764.2, ISNI 0000 0004 0372 3116, Department of Pathology, , St. Marianna University Hospital, ; Kawasaki, Kanagawa 216-8511 Japan
                [5 ]GRID grid.412764.2, ISNI 0000 0004 0372 3116, Division of Respiratory Medicine, Department of Internal Medicine, , St. Marianna University School of Medicine, ; Kawasaki, Kanagawa 216-8511 Japan
                [6 ]GRID grid.414990.1, ISNI 0000 0004 1764 8305, Department of Thoracic Surgery, , Kanto Central Hospital, ; Tokyo, 158-8531 Japan
                [7 ]GRID grid.410793.8, ISNI 0000 0001 0663 3325, Tokyo Medical University, ; Tokyo, 160-0023 Japan
                [8 ]GRID grid.411731.1, ISNI 0000 0004 0531 3030, International University of Health and Welfare, ; Tokyo, 107-8402 Japan
                Article
                70578
                10.1038/s41598-020-70578-x
                7423934
                32788598
                a3e3202f-9c4b-4c43-8502-f211271ccccb
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 22 February 2020
                : 24 July 2020
                Funding
                Funded by: Chugai Pharmaceutical Co., Ltd.
                Categories
                Article
                Custom metadata
                © The Author(s) 2020

                Uncategorized
                biological techniques,biophysics,cancer,cell biology,computational biology and bioinformatics,molecular biology,stem cells,biomarkers,diseases,molecular medicine,oncology,risk factors

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