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      Spatial intratumor heterogeneity of genetic, epigenetic alterations and temporal clonal evolution in esophageal squamous cell carcinoma

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          Abstract

          Esophageal squamous cell carcinoma (ESCC) is among the most common malignancies, but little is known about its spatial intratumor heterogeneity (ITH) and temporal clonal evolutionary processes. To address this, we performed multiregion whole-exome sequencing on 51 tumor regions from 13 ESCCs, and multiregion global methylation profiling on three of these 13 cases. We found an average of 35.8% heterogeneous somatic mutations with strong evidence of ITH. Half of driver mutations located on the branches targeted oncogenes, including PIK3CA, NFE2L2, MTOR, etc. By contrast, the majority of truncal and clonal driver mutations occurred in tumor suppressor genes, including TP53, KMT2D, ZNF750, etc. Interestingly, the phyloepigenetic trees robustly recapitulated the topologic structures of the phylogenetic ones, indicating the possible relationship between genetic and epigenetic alterations. Our integrated investigations of the spatial ITH and clonal evolution provide an important molecular foundation for enhanced understanding of the tumorigenesis and progression of ESCC.

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          Comparison of phylogenetic trees

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            Is Open Access

            SAMBLASTER: fast duplicate marking and structural variant read extraction

            Motivation: Illumina DNA sequencing is now the predominant source of raw genomic data, and data volumes are growing rapidly. Bioinformatic analysis pipelines are having trouble keeping pace. A common bottleneck in such pipelines is the requirement to read, write, sort and compress large BAM files multiple times. Results: We present SAMBLASTER, a tool that reduces the number of times such costly operations are performed. SAMBLASTER is designed to mark duplicates in read-sorted SAM files as a piped post-pass on DNA aligner output before it is compressed to BAM. In addition, it can simultaneously output into separate files the discordant read-pairs and/or split-read mappings used for structural variant calling. As an alignment post-pass, its own runtime overhead is negligible, while dramatically reducing overall pipeline complexity and runtime. As a stand-alone duplicate marking tool, it performs significantly better than PICARD or SAMBAMBA in terms of both speed and memory usage, while achieving nearly identical results. Availability and implementation: SAMBLASTER is open-source C++ code and freely available for download from https://github.com/GregoryFaust/samblaster. Contact: imh4y@virginia.edu
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              Genetic landscape of esophageal squamous cell carcinoma.

              Esophageal squamous cell carcinoma (ESCC) is one of the deadliest cancers. We performed exome sequencing on 113 tumor-normal pairs, yielding a mean of 82 non-silent mutations per tumor, and 8 cell lines. The mutational profile of ESCC closely resembles those of squamous cell carcinomas of other tissues but differs from that of esophageal adenocarcinoma. Genes involved in cell cycle and apoptosis regulation were mutated in 99% of cases by somatic alterations of TP53 (93%), CCND1 (33%), CDKN2A (20%), NFE2L2 (10%) and RB1 (9%). Histone modifier genes were frequently mutated, including KMT2D (also called MLL2; 19%), KMT2C (MLL3; 6%), KDM6A (7%), EP300 (10%) and CREBBP (6%). EP300 mutations were associated with poor survival. The Hippo and Notch pathways were dysregulated by mutations in FAT1, FAT2, FAT3 or FAT4 (27%) or AJUBA (JUB; 7%) and NOTCH1, NOTCH2 or NOTCH3 (22%) or FBXW7 (5%), respectively. These results define the mutational landscape of ESCC and highlight mutations in epigenetic modulators with prognostic and potentially therapeutic implications.
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                Author and article information

                Journal
                9216904
                2419
                Nat Genet
                Nat. Genet.
                Nature genetics
                1061-4036
                1546-1718
                8 September 2016
                17 October 2016
                December 2016
                17 April 2017
                : 48
                : 12
                : 1500-1507
                Affiliations
                [1 ]State Key Laboratory of Molecular Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
                [2 ]Cedars-Sinai Medical Center, Division of Hematology/Oncology, UCLA School of Medicine, Los Angeles, USA
                [3 ]Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Medical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
                [4 ]Center for Bioinformatics and Functional Genomics, Biomedical Sciences, Cedars-Sinai Medical Center, UCLA School of Medicine, Los Angeles, USA
                [5 ]Cancer Science Institute of Singapore, National University of Singapore, Singapore
                [6 ]Faculty of Medicine, Kunming University of Science and Technology, Kunming, Yunnan, China
                [7 ]Department of Pathology, Linzhou Cancer Hospital, Henan, China
                [8 ]Department of Cancer Epidemiology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
                [9 ]National University Cancer Institute, National University Hospital Singapore, Singapore
                Author notes
                [10]

                These authors contributed equally to this work.

                [11 ]Correspondence should be addressed to M-R.W. ( wangmr2015@ 123456126.com ), B.P.B ( Benjamin.Berman@ 123456csmc.edu ), D-C.L. ( dchlin11@ 123456gmail.com ) or W-Q W. ( weiwq2006@ 123456126.com )
                Article
                NIHMS814330
                10.1038/ng.3683
                5127772
                27749841
                1a49c682-4e02-4601-8ec8-6efd0b092a4f

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                Genetics
                Genetics

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