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      FOXP2 confers oncogenic effects in prostate cancer

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          Abstract

          Identification oncogenes is fundamental to revealing the molecular basis of cancer. Here, we found that FOXP2 is overexpressed in human prostate cancer cells and prostate tumors, but its expression is absent in normal prostate epithelial cells and low in benign prostatic hyperplasia. FOXP2 is a FOX transcription factor family member and tightly associated with vocal development. To date, little is known regarding the link of FOXP2 to prostate cancer. We observed that high FOXP2 expression and frequent amplification are significantly associated with high Gleason score. Ectopic expression of FOXP2 induces malignant transformation of mouse NIH3T3 fibroblasts and human prostate epithelial cell RWPE-1. Conversely, FOXP2 knockdown suppresses the proliferation of prostate cancer cells. Transgenic overexpression of FOXP2 in the mouse prostate causes prostatic intraepithelial neoplasia. Overexpression of FOXP2 aberrantly activates oncogenic MET signaling and inhibition of MET signaling effectively reverts the FOXP2-induced oncogenic phenotype. CUT&Tag assay identified FOXP2-binding sites located in MET and its associated gene HGF. Additionally, the novel recurrent FOXP2-CPED1 fusion identified in prostate tumors results in high expression of truncated FOXP2, which exhibit a similar capacity for malignant transformation. Together, our data indicate that FOXP2 is involved in tumorigenicity of prostate.

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          Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

          Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.
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            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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              The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data.

              Next-generation DNA sequencing (NGS) projects, such as the 1000 Genomes Project, are already revolutionizing our understanding of genetic variation among individuals. However, the massive data sets generated by NGS--the 1000 Genome pilot alone includes nearly five terabases--make writing feature-rich, efficient, and robust analysis tools difficult for even computationally sophisticated individuals. Indeed, many professionals are limited in the scope and the ease with which they can answer scientific questions by the complexity of accessing and manipulating the data produced by these machines. Here, we discuss our Genome Analysis Toolkit (GATK), a structured programming framework designed to ease the development of efficient and robust analysis tools for next-generation DNA sequencers using the functional programming philosophy of MapReduce. The GATK provides a small but rich set of data access patterns that encompass the majority of analysis tool needs. Separating specific analysis calculations from common data management infrastructure enables us to optimize the GATK framework for correctness, stability, and CPU and memory efficiency and to enable distributed and shared memory parallelization. We highlight the capabilities of the GATK by describing the implementation and application of robust, scale-tolerant tools like coverage calculators and single nucleotide polymorphism (SNP) calling. We conclude that the GATK programming framework enables developers and analysts to quickly and easily write efficient and robust NGS tools, many of which have already been incorporated into large-scale sequencing projects like the 1000 Genomes Project and The Cancer Genome Atlas.
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                Author and article information

                Contributors
                Role: Reviewing Editor
                Role: Senior Editor
                Journal
                eLife
                Elife
                eLife
                eLife
                eLife Sciences Publications, Ltd
                2050-084X
                05 September 2023
                2023
                : 12
                : e81258
                Affiliations
                [1 ] The Key Laboratory of Geriatrics, Beijing Hospital, National Center of Gerontology, National Health Commission, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences ( https://ror.org/02jwb5s28) Beijing China
                [2 ] Department of Thoracic Surgery, Peking University Shenzhen Hospital, Shenzhen Peking University ( https://ror.org/03kkjyb15) Shenzhen China
                [3 ] The Hong Kong University of Science and Technology Medical Center ( https://ror.org/00q4vv597) Hong Kong China
                [4 ] Department of Urology, Beijing Hospital, National Health Commission, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences ( https://ror.org/02jwb5s28) Beijing China
                [5 ] Tianjin Institute of Urology, Second Hospital of Tianjin Medical University ( https://ror.org/03rc99w60) Tianjing China
                [6 ] Department of Urology, Second Hospital of Tianjing Medical University ( https://ror.org/03rc99w60) Tianjing China
                [7 ] Genetic Testing Center, Qingdao Women and Children's Hospital ( https://ror.org/05pwzcb81) Qingdao China
                [8 ] Department of Computer Science, City University of Hong Kong ( https://ror.org/03q8dnn23) Hong Kong China
                [9 ] Department of Urology, Beijing Jishuitan Hospital ( https://ror.org/035t17984) Beijing China
                [10 ] Department of Urology, Beijing Tian Tan Hospital, Capital Medical University ( https://ror.org/003regz62) Beijing China
                [11 ] School of Nursing, Harbin Medical University ( https://ror.org/05jscf583) Harbin China
                [12 ] Department of Pathology, Beijing Hospital, National Health Commission, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences ( https://ror.org/02jwb5s28) Beijing China
                [13 ] Department of Urology, Peking University First Hospital, Institute of Urology ( https://ror.org/02z1vqm45) Beijing China
                [14 ] Clinical Institute of China-Japan Friendship Hospital ( https://ror.org/037cjxp13) Beijing China
                [15 ] Department of Surgery, Beijing Hospital, National Health Commission, Institute of Geriatric Medicine, Chinese Academy of Medical Science ( https://ror.org/02jwb5s28) Beijing China
                [16 ] The Department of Ultrasonography, Beijing Hospital, National Health Commission, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences ( https://ror.org/02jwb5s28) Beijing China
                Netherlands Cancer Institute ( https://ror.org/03xqtf034) Netherlands
                University of Helsinki ( https://ror.org/040af2s02) Finland
                Netherlands Cancer Institute ( https://ror.org/03xqtf034) Netherlands
                Netherlands Cancer Institute ( https://ror.org/03xqtf034) Netherlands
                Author information
                https://orcid.org/0000-0002-9099-5835
                https://orcid.org/0000-0001-5139-5311
                Article
                81258
                10.7554/eLife.81258
                10513481
                37668356
                2911c27d-e561-439b-8b4a-a518d337bda4
                © 2023, Zhu et al

                This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

                History
                : 21 June 2022
                : 05 September 2023
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 81872096
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 81541152
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 81472408
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 81570789
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100019018, Chinese Academy of Medical Sciences Initiative for Innovative Medicine;
                Award ID: 2021-I2M-1-050
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100019018, Chinese Academy of Medical Sciences Initiative for Innovative Medicine;
                Award ID: 2018-I2M-1-002
                Award Recipient :
                Funded by: Ministry of Scientific Technology;
                Award ID: 12th 5-year National Program - 2012BAI10B01
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100012166, National Basic Research Program of China;
                Award ID: 973 Program Grants - 2014CB910503
                Award Recipient :
                The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
                Categories
                Research Article
                Biochemistry and Chemical Biology
                Cancer Biology
                Custom metadata
                FOXP2, encoding a forkhead-box transcription factor regarded as vital to proper development of human speech, was revealed to have an oncogenic potential and activate MET signaling in prostate cancer.

                Life sciences
                foxp2,prostate cancer,oncogene,transformation,met signaling,human,mouse
                Life sciences
                foxp2, prostate cancer, oncogene, transformation, met signaling, human, mouse

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