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      Case Report: Temozolomide Treatment of Refractory Prolactinoma Resistant to Dopamine Agonists

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          Abstract

          Therapeutic agents for refractory prolactinomas that are resistant to dopamine agonists (DAs) are troublesome, and surgery often only removes a large part of the tumor without complete remission. Among the various second-line treatment regimens, the treatment effect of the alkylating agent temozolomide (TMZ) is only effective for approximately half of patients; however, complete remission is rare. Here we report a patient with prolactinoma who was resistant to high-dose cabergoline (CAB) treatment, demonstrating a continuous increase in both the tumor volume and the prolactin (PRL) level. Given that this case is a refractory prolactinoma, the patient underwent two transsphenoidal approach (TSA) surgeries. The pathological analysis indicated that the Ki-67 index increased significantly from 3% to 30%, and the expression levels of DRD2 and MGMT were low. Finally, TMZ treatment was recommended. A total of six cycles of TMZ standard chemotherapy shrank the tumor volume and the tumor disappeared completely. During the 6-month follow-up period, the tumor did not relapse again, and the PRL level was also normal. RNA sequencing and DNA whole genome sequencing were performed on this prolactinoma specimen, revealing 16 possible gene mutations, including a missense mutation of the PABPC1 gene. Additionally, the copy number variation analysis results showed that several chromosomes had copy number gains compared to the matched peripheral blood sample. In this case, low expression of DRD2 and high proliferation led to resistance to CAB, whereas low MGMT expression contributed to sensitivity to TMZ treatment. The results of genome sequencing still need further investigation at the molecular level to explain the tumor aggressiveness and high sensitivity to TMZ.

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          Most cited references26

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            STAR: ultrafast universal RNA-seq aligner.

            Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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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
                Journal
                Front Endocrinol (Lausanne)
                Front Endocrinol (Lausanne)
                Front. Endocrinol.
                Frontiers in Endocrinology
                Frontiers Media S.A.
                1664-2392
                12 March 2021
                2021
                : 12
                : 616339
                Affiliations
                [1] 1 Department of Neurosurgery, Center of Pituitary Tumor, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University , Shanghai, China
                [2] 2 State Key Laboratory of Medical Genomics, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University , Shanghai, China
                [3] 3 Department of Pathology, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University , Shanghai, China
                Author notes

                Edited by: Renzhi Wang, Peking Union Medical College Hospital (CAMS), China

                Reviewed by: Luiz Augusto Casulari, University of Brasilia, Brazil; Odelia Cooper, Cedars Sinai Medical Center, United States

                *Correspondence: Zhe Bao Wu, zhebaowu@ 123456aliyun.com

                This article was submitted to Pituitary Endocrinology, a section of the journal Frontiers in Endocrinology

                Article
                10.3389/fendo.2021.616339
                7996095
                5c50664c-f2bd-4a07-b8d9-5d9ef2c5d461
                Copyright © 2021 Tang, Cheng, Huang, Li, Zhang and Wu

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 12 October 2020
                : 12 February 2021
                Page count
                Figures: 3, Tables: 1, Equations: 0, References: 26, Pages: 7, Words: 2714
                Funding
                Funded by: Science and Technology Commission of Shanghai Municipality 10.13039/501100003399
                Funded by: Program of Shanghai Academic Research Leader 10.13039/501100012247
                Categories
                Endocrinology
                Case Report

                Endocrinology & Diabetes
                resistance,dopamine agonist,pabpc1,temozolomide,prolactinoma
                Endocrinology & Diabetes
                resistance, dopamine agonist, pabpc1, temozolomide, prolactinoma

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