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      Whole-genome sequencing of 508 patients identifies key molecular features associated with poor prognosis in esophageal squamous cell carcinoma

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          Abstract

          Esophageal squamous cell carcinoma (ESCC) is a poor-prognosis cancer type with limited understanding of its molecular etiology. Using 508 ESCC genomes, we identified five novel significantly mutated genes and uncovered mutational signature clusters associated with metastasis and patients’ outcomes. Several functional assays implicated that NFE2L2 may act as a tumor suppressor in ESCC and that mutations in NFE2L2 probably impaired its tumor-suppressive function, or even conferred oncogenic activities. Additionally, we found that the NFE2L2 mutations were significantly associated with worse prognosis of ESCC. We also identified potential noncoding driver mutations including hotspot mutations in the promoter region of SLC35E2 that were correlated with worse survival. Approximately 5.9% and 15.2% of patients had high tumor mutation burden or actionable mutations, respectively, and may benefit from immunotherapy or targeted therapies. We found clinically relevant coding and noncoding genomic alterations and revealed three major subtypes that robustly predicted patients’ outcomes. Collectively, we report the largest dataset of genomic profiling of ESCC useful for developing ESCC-specific biomarkers for diagnosis and treatment.

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          Global Cancer Statistics 2018: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries

          This article provides a status report on the global burden of cancer worldwide using the GLOBOCAN 2018 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer, with a focus on geographic variability across 20 world regions. There will be an estimated 18.1 million new cancer cases (17.0 million excluding nonmelanoma skin cancer) and 9.6 million cancer deaths (9.5 million excluding nonmelanoma skin cancer) in 2018. In both sexes combined, lung cancer is the most commonly diagnosed cancer (11.6% of the total cases) and the leading cause of cancer death (18.4% of the total cancer deaths), closely followed by female breast cancer (11.6%), prostate cancer (7.1%), and colorectal cancer (6.1%) for incidence and colorectal cancer (9.2%), stomach cancer (8.2%), and liver cancer (8.2%) for mortality. Lung cancer is the most frequent cancer and the leading cause of cancer death among males, followed by prostate and colorectal cancer (for incidence) and liver and stomach cancer (for mortality). Among females, breast cancer is the most commonly diagnosed cancer and the leading cause of cancer death, followed by colorectal and lung cancer (for incidence), and vice versa (for mortality); cervical cancer ranks fourth for both incidence and mortality. The most frequently diagnosed cancer and the leading cause of cancer death, however, substantially vary across countries and within each country depending on the degree of economic development and associated social and life style factors. It is noteworthy that high-quality cancer registry data, the basis for planning and implementing evidence-based cancer control programs, are not available in most low- and middle-income countries. The Global Initiative for Cancer Registry Development is an international partnership that supports better estimation, as well as the collection and use of local data, to prioritize and evaluate national cancer control efforts. CA: A Cancer Journal for Clinicians 2018;0:1-31. © 2018 American Cancer Society.
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            Is Open Access

            Fast and accurate short read alignment with Burrows–Wheeler transform

            Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ∼10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: http://maq.sourceforge.net Contact: rd@sanger.ac.uk
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              Cancer statistics in China, 2015.

              With increasing incidence and mortality, cancer is the leading cause of death in China and is a major public health problem. Because of China's massive population (1.37 billion), previous national incidence and mortality estimates have been limited to small samples of the population using data from the 1990s or based on a specific year. With high-quality data from an additional number of population-based registries now available through the National Central Cancer Registry of China, the authors analyzed data from 72 local, population-based cancer registries (2009-2011), representing 6.5% of the population, to estimate the number of new cases and cancer deaths for 2015. Data from 22 registries were used for trend analyses (2000-2011). The results indicated that an estimated 4292,000 new cancer cases and 2814,000 cancer deaths would occur in China in 2015, with lung cancer being the most common incident cancer and the leading cause of cancer death. Stomach, esophageal, and liver cancers were also commonly diagnosed and were identified as leading causes of cancer death. Residents of rural areas had significantly higher age-standardized (Segi population) incidence and mortality rates for all cancers combined than urban residents (213.6 per 100,000 vs 191.5 per 100,000 for incidence; 149.0 per 100,000 vs 109.5 per 100,000 for mortality, respectively). For all cancers combined, the incidence rates were stable during 2000 through 2011 for males (+0.2% per year; P = .1), whereas they increased significantly (+2.2% per year; P < .05) among females. In contrast, the mortality rates since 2006 have decreased significantly for both males (-1.4% per year; P < .05) and females (-1.1% per year; P < .05). Many of the estimated cancer cases and deaths can be prevented through reducing the prevalence of risk factors, while increasing the effectiveness of clinical care delivery, particularly for those living in rural areas and in disadvantaged populations.
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                Author and article information

                Contributors
                zhanqimin@bjmu.edu.cn
                robin@baidu.com
                liuzh@cicams.ac.cn
                Journal
                Cell Res
                Cell Res
                Cell Research
                Springer Singapore (Singapore )
                1001-0602
                1748-7838
                12 May 2020
                October 2020
                : 30
                : 10
                : 902-913
                Affiliations
                [1 ]GRID grid.263452.4, ISNI 0000 0004 1798 4018, Department of Pathology & Shanxi Key Laboratory of Carcinogenesis and Translational Research on Esophageal Cancer, , Shanxi Medical University, ; Taiyuan, Shanxi 030001 China
                [2 ]GRID grid.506261.6, ISNI 0000 0001 0706 7839, State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, , Chinese Academy of Medical Sciences and Peking Union Medical College, ; Beijing, 100021 China
                [3 ]GRID grid.11135.37, ISNI 0000 0001 2256 9319, School of Mathematical Sciences, Center for Statistical Science and Department of Biostatistics, , Peking University, ; Beijing, 100871 China
                [4 ]GRID grid.412474.0, ISNI 0000 0001 0027 0586, Key laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Laboratory of Molecular Oncology, , Peking University Cancer Hospital & Institute, ; Beijing, 100142 China
                [5 ]GRID grid.440601.7, ISNI 0000 0004 1798 0578, Cancer Institute, Peking University Shenzhen Hospital, , Shenzhen Peking University-The Hong Kong University of Science and Technology (PKU-HKUST) Medical Center, ; Shenzhen, Guangdong 518035 China
                [6 ]GRID grid.440201.3, ISNI 0000 0004 1758 2596, Department of Pathology, , Shanxi Cancer Hospital, ; Taiyuan, Shanxi 030001 China
                [7 ]GRID grid.13394.3c, ISNI 0000 0004 1799 3993, Tumor Hospital affiliated to Xinjiang Medical University, ; Urumqi, Xinjiang 830011 China
                [8 ]WuXi NextCODE, Shanghai, 200131 China
                [9 ]GRID grid.440201.3, ISNI 0000 0004 1758 2596, Department of Tumor Surgery, , Shanxi Cancer Hospital, ; Taiyuan, Shanxi 030001 China
                [10 ]GRID grid.440201.3, ISNI 0000 0004 1758 2596, Tumor Biobank, , Shanxi Cancer Hospital, ; Taiyuan, Shanxi 030001 China
                [11 ]GRID grid.263452.4, ISNI 0000 0004 1798 4018, Department of Pathology, the First Hospital, , Shanxi Medical University, ; Taiyuan, Shanxi 030001 China
                [12 ]GRID grid.459383.0, ISNI 0000 0004 4909 268X, Baidu, ; Beijing, 100085 China
                Author information
                http://orcid.org/0000-0001-7545-7361
                http://orcid.org/0000-0002-1731-938X
                http://orcid.org/0000-0003-4242-033X
                Article
                333
                10.1038/s41422-020-0333-6
                7608103
                32398863
                d49c5f52-9a50-4885-90fe-f20ae743efe9
                © Center for Excellence in Molecular Cell Science, CAS 2020

                This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.

                History
                : 21 October 2019
                : 17 April 2020
                Funding
                Funded by: National Key R&D Program of China (2016YFC1302100); CAMS Innovation Fund for Medical Sciences (2016-I2M-1-001, 2019-I2M-1-003); National Natural Science Foundation of China 81330063; Fund of ``San-ming Project" of Medicine in Shenzhen (No. SZSM201812088).
                Funded by: National Natural Science Foundation of China 81490753; the Guangdong Basic and Applied Basic Research Foundation 2019B030302012
                Funded by: the Guangdong Basic and Applied Basic Research Foundation (2019B030302012)
                Categories
                Article
                Custom metadata
                © Center for Excellence in Molecular Cell Science, CAS 2020

                Cell biology
                cancer genomics,oesophageal cancer
                Cell biology
                cancer genomics, oesophageal cancer

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