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      RNA Sequencing in Comparison to Immunohistochemistry for Measuring Cancer Biomarkers in Breast Cancer and Lung Cancer Specimens

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          Abstract

          RNA sequencing is considered the gold standard for high-throughput profiling of gene expression at the transcriptional level. Its increasing importance in cancer research and molecular diagnostics is reflected in the growing number of its mentions in scientific literature and clinical trial reports. However, the use of different reagents and protocols for RNA sequencing often produces incompatible results. Recently, we published the Oncobox Atlas of RNA sequencing profiles for normal human tissues obtained from healthy donors killed in road accidents. This is a database of molecular profiles obtained using uniform protocol and reagents settings that can be broadly used in biomedicine for data normalization in pathology, including cancer. Here, we publish new original 39 breast cancer (BC) and 19 lung cancer (LC) RNA sequencing profiles obtained for formalin-fixed paraffin-embedded (FFPE) tissue samples, fully compatible with the Oncobox Atlas. We performed the first correlation study of RNA sequencing and immunohistochemistry-measured expression profiles for the clinically actionable biomarker genes in FFPE cancer tissue samples. We demonstrated high (Spearman’s rho 0.65–0.798) and statistically significant ( p < 0.00004) correlations between the RNA sequencing (Oncobox protocol) and immunohistochemical measurements for HER2/ERBB2, ER/ESR1 and PGR genes in BC, and for PDL1 gene in LC; AUC: 0.963 for HER2, 0.921 for ESR1, 0.912 for PGR, and 0.922 for PDL1. To our knowledge, this is the first validation that total RNA sequencing of archived FFPE materials provides a reliable estimation of marker protein levels. These results show that in the future, RNA sequencing can complement immunohistochemistry for reliable measurements of the expression biomarkers in FFPE cancer samples.

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          The CPTAC Data Portal: A Resource for Cancer Proteomics Research.

          The Clinical Proteomic Tumor Analysis Consortium (CPTAC), under the auspices of the National Cancer Institute's Office of Cancer Clinical Proteomics Research, is a comprehensive and coordinated effort to accelerate the understanding of the molecular basis of cancer through the application of proteomic technologies and workflows to clinical tumor samples with characterized genomic and transcript profiles. The consortium analyzes cancer biospecimens using mass spectrometry, identifying and quantifying the constituent proteins and characterizing each tumor sample's proteome. Mass spectrometry enables highly specific identification of proteins and their isoforms, accurate relative quantitation of protein abundance in contrasting biospecimens, and localization of post-translational protein modifications, such as phosphorylation, on a protein's sequence. The combination of proteomics, transcriptomics, and genomics data from the same clinical tumor samples provides an unprecedented opportunity for tumor proteogenomics. The CPTAC Data Portal is the centralized data repository for the dissemination of proteomic data collected by Proteome Characterization Centers (PCCs) in the consortium. The portal currently hosts 6.3 TB of data and includes proteomic investigations of breast, colorectal, and ovarian tumor tissues from The Cancer Genome Atlas (TCGA). The data collected by the consortium is made freely available to the public through the data portal.
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            Ribosome profiling reveals pervasive and regulated stop codon readthrough in Drosophila melanogaster

            Ribosomes can read through stop codons in a regulated manner, elongating rather than terminating the nascent peptide. Stop codon readthrough is essential to diverse viruses, and phylogenetically predicted to occur in a few hundred genes in Drosophila melanogaster, but the importance of regulated readthrough in eukaryotes remains largely unexplored. Here, we present a ribosome profiling assay (deep sequencing of ribosome-protected mRNA fragments) for Drosophila melanogaster, and provide the first genome-wide experimental analysis of readthrough. Readthrough is far more pervasive than expected: the vast majority of readthrough events evolved within D. melanogaster and were not predicted phylogenetically. The resulting C-terminal protein extensions show evidence of selection, contain functional subcellular localization signals, and their readthrough is regulated, arguing for their importance. We further demonstrate that readthrough occurs in yeast and humans. Readthrough thus provides general mechanisms both to regulate gene expression and function, and to add plasticity to the proteome during evolution. DOI: http://dx.doi.org/10.7554/eLife.01179.001
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              Multicenter French harmonization study for PD-L1 IHC testing in non-small cell lung cancer.

              Various PD-L1 immunohistochemistry (IHC) assays have been developed and used in clinical trials in association with different drugs. In order to harmonize and make PD-L1 testing in non-small cell lung cancer (NSCLC) widely available, we conducted a multicenter study comparing PD-L1 standardized assays and laboratory-developed tests (LDT).
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                Author and article information

                Journal
                Biomedicines
                Biomedicines
                biomedicines
                Biomedicines
                MDPI
                2227-9059
                09 May 2020
                May 2020
                : 8
                : 5
                : 114
                Affiliations
                [1 ]Institute of Personalized Medicine, I.M. Sechenov First Moscow State Medical University, 119048 Moscow, Russia; sorokin@ 123456oncobox.com (M.S.); podd-elena@ 123456ya.ru (E.P.); allina_dasha@ 123456mail.ru (D.A.); suntsova86@ 123456mail.ru (M.S.)
                [2 ]Omicsway Corp., Walnut, CA 91789, USA; garazha@ 123456oncobox.com
                [3 ]Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, 117997 Moscow, Russia; uliana.bagina@ 123456gmail.com
                [4 ]Karelia Republic Oncological Hospital, 185000 Petrozavodsk, Russia; kirillignatev@ 123456bk.ru
                [5 ]Vitamed Oncological Clinical Center, 121309 Moscow, Russia
                [6 ]Faculty of Fundamental Medicine, Lomonosov Moscow State University, 119991 Moscow, Russia; gaifulin@ 123456rambler.ru
                [7 ]Kaluga Regional Oncological Hospital, 248007 Kaluga, Russia; lantsov@ 123456mail.ru
                [8 ]Oncological Dispensary of the Republic of Karelia, 185002 Petrozavodsk, Russia; evika9@ 123456rambler.ru
                [9 ]Moscow Institute of Physics and Technology, 141701 Moscow, Russia
                Author notes
                [* ]Correspondence: buzdin@ 123456oncobox.com ; Tel.: +1-626-765-7785
                Article
                biomedicines-08-00114
                10.3390/biomedicines8050114
                7277916
                32397474
                d9897548-f2fc-44a6-9292-b3b6637e0e82
                © 2020 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
                : 29 March 2020
                : 07 May 2020
                Categories
                Article

                transcriptomics,rna sequencing,immunohistochemistry,molecular diagnostics,biomarkers detection,clinical oncology,targeted therapies,personalized medicine,lung cancer,breast cancer,trastuzumab,nct03521245,bioinformatics

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