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Next-generation sequencing (NGS) has been widely used in clinics, but DNA-based NGS used to detect fusion genes has delivered false-negative results. However, fusion genes can be successfully detected at the transcription level and with higher sensitivity using RNA-based reverse transcription polymerase chain reaction (RT-PCR). This study compared the performance of RT-PCR and NGS in the detection of echinoderm microtubule-associated protein-like 4 (EML4)-ALK fusion in Chinese patients with NSCLC. Formalin-fixed paraffin-embedded tissues from 153 patients who were pathologically diagnosed as having NSCLC were collected from November 2017 to October 2019. Both DNA\u002FRNA-based NGS and RNA-based RT-PCR were used to detect EML4-ALK fusion. For samples with discordant ALK status results, fluorescence in situ hybridization (FISH) or Sanger sequencing was used to further confirm the ALK status. In total, 124 samples were successfully analyzed using both NGS and RT-PCR. For 118 samples, results were consistent between NGS and RT-PCR, with 25 reported as ALK fusion positive and 93 as ALK fusion negative, achieving a concordance rate of 95.16%. Among the six samples with disconcordant results, five were positive using RT-PCR but negative using NGS, and one was positive using NGS but negative using RT-PCR. Four of six cases with disconcordant results (three RT-PCR positive and one NGS positive) were successfully validated using either FISH or Sanger sequencing. Compared with NGS, RT-PCR appears to be a reliable method of detecting EML4-ALK fusion in patients with NSCLC.",{"EN":185},"Detecting ALK Rearrangement with RT-PCR: A Reliable Approach Compared with Next-Generation Sequencing in Patients with NSCLC",{"VOID":187},"[\"14906474683196054324\"]",{"VOID":189},"Solomon BJ, Mok T, Kim DW, Wu YL, Nakagawa K, Mekhail T, et al. First-line crizotinib versus chemotherapy in ALK-positive lung cancer. N Engl J Med. 2014;371(23):2167–77.\nTao H, Shi L, Zhou A, Li H, Gai F, Huang Z, et al. Distribution of EML4-ALK fusion variants and clinical outcomes in patients with resected non-small cell lung cancer. Lung Cancer. 2020;149:154–61.\nShaw AT, Engelman JA. Ceritinib in ALK-rearranged non-small-cell lung cancer. N Engl J Med. 2014;370(26):2537–9.\nSoda M, Choi YL, Enomoto M, et al. Identification of the transforming EML4-ALK fusion gene in non-small-cell lung cancer. Nature. 2007;448(7153):561–6.\nRogers TM, Russell PA, Wright G, et al. Comparison of methods in the detection of ALK and ROS1 rearrangements in lung cancer. J Thorac Oncol. 2015;10(4):611–8.\nTeixidó C, Karachaliou N, Peg V, Gimenez-Capitan A, Rosell R. Concordance of IHC, FISH and RT-PCR for EML4-ALK rearrangements. Transl Lung Cancer Res. 2014;3(2):70–4.\nWu YC, Chang IC, Wang CL, et al. Comparison of IHC, FISH and RT-PCR methods for detection of ALK rearrangements in 312 non-small cell lung cancer patients in Taiwan. PLoS ONE. 2013;8:e70839.\nLu S, Lu C, Xiao Y, et al. Comparison of EML4-ALK fusion gene positive rate in different detection methods and samples of non-small cell lung cancer. J Cancer. 2020;11(6):1525–31.\nWang Y, Zhang J, Gao G, et al. EML4-ALK fusion detected by RT-PCR confers similar response to crizotinib as detected by FISH in patients with advanced non-small-cell lung cancer. J Thorac Oncol. 2015;10:1546–52.\nKamps R, Brandão RD, Bosch BJ, et al. Next-generation sequencing in oncology: genetic diagnosis, risk prediction and cancer classification. Int J Mol Sci. 2017;18:308.\nLetovanec I, Finn S, Zygoura P, et al. Evaluation of NGS and RT-PCR methods for ALK rearrangement in European NSCLC patients: results from the European Thoracic Oncology Platform Lungscape Project. J Thorac Oncol. 2018;13(3):413–25.\nLih CJ, Harrington RD, Sims DJ, Harper KN, Bouk CH, Datta V, Yau J, Singh RR, Routbort MJ, Luthra R, et al. Analytical validation of the next-generation sequencing assay for a nationwide signal-finding clinical trial: molecular analysis for Therapy Choice Clinical Trial. J Mol Diagn. 2017;19:313–27.\nLiu J, Mu Z, Liu L, Li K, Jiang R, Chen P, Zhou Q, Jin M, Ma Y, Xie Y, et al. Frequency, clinical features and differential response to therapy of concurrent ALK\u002FEGFR alterations in Chinese lung cancer patients. Drug Des Devel Ther. 2019;13:1809–17.\nSchmittgen TD, Livak KJ. Analyzing real-time PCR data by the comparative C(T) method. Nat Protoc. 2008;3:1101–8.\nLee WI, Huang JL, Lin SJ, et al. Lower T regulatory and Th17 cell populations predicted by RT-PCR-amplified FOXP3 and RORγt genes are not rare in patients with primary immunodeficiency diseases. Front Immunol. 2020;11:1111.\nWen S, Dai L, Wang L, et al. Genomic signature of driver genes identified by target next-generation sequencing in Chinese non-small cell lung cancer. Oncologist. 2019;24(11):e1070–81.\nLi W, Liu Y, Li W, Chen L, Ying J. Intergenic breakpoints identified by DNA sequencing confound targetable kinase fusion detection in NSCLC. J Thorac Oncol. 2020;15(7):1223–31.\nDavies KD, Lomboy A, Lawrence CA, et al. DNA-based versus RNA-based detection of MET Exon 14 skipping events in lung cancer. J Thorac Oncol. 2019;14(4):737–41.\nBenayed R, Offin M, Mullaney K, et al. High yield of RNA sequencing for targetable kinase fusions in lung adenocarcinomas with no mitogenic driver alteration detected by DNA sequencing and low tumor mutation burden. Clin Cancer Res. 2019;25(15):4712–22.\nThunnissen E, Kerr KM, Herth FJ, et al. The challenge of NSCLC diagnosis and predictive analysis on small samples. Practical approach of a working group. Lung Cancer. 2012;76(1):1–18.\nSmits AJ, Kummer JA, de Bruin PC, et al. The estimation of tumor cell percentage for molecular testing by pathologists is not accurate. Mod Pathol. 2014;27(2):168–74.\nZheng MM, Li YS, Tu HY, et al. Genotyping of cerebrospinal fluid associated with osimertinib response and resistance for leptomeningeal metastases in EGFR-mutated NSCLC. J Thorac Oncol. 2021;16(2):250–8.\nHeriyanto DS, Trisnawati I, Kumara EG, et al. The prevalence of the EML4-ALK fusion gene in cytology specimens from patients with lung adenocarcinoma. Pulm Med. 2020;2020:3578748.\nWang Y, Liu Y, Zhao C, et al. Feasibility of cytological specimens for ALK fusion detection in patients with advanced NSCLC using the method of RT-PCR. 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               Objective: Rituximab is used to deplete B cells and control disease activity, mainly in patients with rheumatoid arthritis (RA) who have not responded to anti-tumor necrosis factor (TNF) therapy. Response rates and time to relapse vary significantly among treated individuals. The objective of this study was to monitor the response of seropositive and seronegative RA patients to rituximab and correlate relapse with B-cell markers in the two groups. \n                Methods: Seventeen RA patients (eight seropositive for rheumatoid factor [RF+] and nine seronegative [RF-]) were treated with two cycles of rituximab. After treatment, all patients were re-evaluated at the outpatient clinic, and rituximab was readministered when disease relapse was confirmed by clinical-laboratory measures (Disease Activity Score [DAS]-28). CD20+ cells and CD20 receptor expression levels were estimated at initiation, relapse, and re-evaluation timepoints, and were compared between the two groups. \n                Results: Seropositive patients responded favorably to treatment compared with the seronegative group. The mean time to relapse was 337.5±127.0 days for the RF+ patients versus 233.3 ± 59.6 days for the RF-patients (p = 0.043), despite more aggressive concomitant treatment in the seronegative group. The DAS28 decrease 3 months after treatment was 1.695 ± 1.076 in seropositive patients versus 0.94±1.62 in seronegative patients. At relapse, CD20 receptor expression (molecules\u002Fcell) was higher in RF+ patients than in their RF-counterparts, despite a significantly lower percentage of CD20+ cells. \n                Conclusion: Rituximab treatment is efficient in both seropositive and seronegative RA. However, seropositive RA patients tend to respond favorably compared with seronegative patients. 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Rheumatology (Oxford) 2001; 40: 205–11",{"doi":717},{"id":713,"text":764,"url":715,"identifiers":765},"Cambridge G, Leandro MJ, Edwards JC, et al. Serologic changes following B lymphocyte depletion therapy for rheumatoid arthritis. Arthritis Rheum 2003; 48: 2146–54",{"doi":717},{"id":713,"text":767,"url":715,"identifiers":768},"Williams ME, Densmore JJ, Pawluczkowycz AW, et al. Thrice-weekly low-dose rituximab decreases CD20 loss via shaving and promotes enhanced targeting in chronic lymphocytic leukaemia. J Immunol 2006; 177: 7435–43",{"doi":717},{"id":713,"text":770,"url":715,"identifiers":771},"Silverman GJ, Boyle DL. Understanding the mechanistic basis in rheumatoid arthritis for clinical response to anti CD20 therapy: the B-cell roadblock hypothesis. Immunol Rev 2008; 223: 175–85",{"doi":717},{"id":773,"createTime":774,"updateTime":775,"relativeEntities":776,"slug":777,"properties":778,"entityType":192,"verifyStatus":193,"verifyTime":789,"verifyNote":195,"languages":20,"translateLanguages":20,"viewCount":21,"primaryUrl":790,"fullTextUrl":20,"authors":791,"publicationType":450,"publisherRelationship":839,"citationCount":21,"citationInfo":899,"publishDate":902,"publishYear":900,"citationAnalyzeStatus":19,"lastCitationAnalyze":775,"indexDatabases":903,"openAccess":20,"references":20,"isForceReanalyzing":518},"456e0a56-0315-4e7e-8085-ccb403a0a78d","2023-12-28T18:34:06.306+00:00","2026-05-10T22:45:54.714+00:00",[],"Rare-Opportunities-CRISPR-Cas-Based-Therapy-Development-for-Rare-Genetic-Diseases",{"abstract":779,"title":781,"gsPaper":783,"references":785,"doi":787},{"EN":780},"Rare diseases pose a global challenge, in that their collective impact on health systems is considerable, whereas their individually rare occurrence impedes research and development of efficient therapies. In consequence, patients and their families are often unable to find an expert for their affliction, let alone a cure. The tide is turning as pharmaceutical companies embrace gene therapy development and as serviceable tools for the repair of primary mutations separate the ability to create cures from underlying disease expertise. Whereas gene therapy by gene addition took decades to reach the clinic by incremental disease-specific refinements of vectors and methods, gene therapy by genome editing in its basic form merely requires certainty about the causative mutation. Suddenly we move from concept to trial in 3 years instead of 30: therapy development in the fast lane, with all the positive and negative implications of the phrase. Since their first application to eukaryotic cells in 2013, the proliferation and refinement in particular of tools based on clustered regularly interspaced short palindromic repeats (CRISPR)\u002FCRISPR-associated protein (Cas) prokaryotic RNA-guided nucleases has prompted a landslide of therapy-development studies for rare diseases. An estimated thousands of orphan diseases are up for adoption, and legislative, entrepreneurial, and research initiatives may finally conspire to find many of them a good home. Here we summarize the most significant recent achievements and remaining hurdles in the application of CRISPR\u002FCas technology to rare diseases and take a glimpse at the exciting road ahead.",{"EN":782},"Rare Opportunities: CRISPR\u002FCas-Based Therapy Development for Rare Genetic Diseases",{"VOID":784},"[\"5704799701399007670\"]",{"VOID":786},"Szajner P, Yusufzai T. Introducing rare diseases. 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Hum Gene Ther. 2015;26:114–26.\nSkvarova Kramarzova K, Osborn MJ, Webber BR, DeFeo AP, McElroy AN, Kim CJ, et al. CRISPR\u002FCas9-mediated correction of the FANCD1 gene in primary patient cells. Int J Mol Sci. 2017;18:1269. https:\u002F\u002Fdoi.org\u002F10.3390\u002Fijms18061269.\nvan Agtmaal EL, André LM, Willemse M, Cumming SA, van Kessel IDG, van den Broek WJAA, et al. CRISPR\u002FCas9-induced (CTG·CAG)n repeat instability in the myotonic dystrophy type 1 locus: implications for therapeutic genome editing. Mol Ther. 2017;25:24–43.\nHuang X, Wang Y, Yan W, Smith C, Ye Z, Wang J, et al. Production of gene-corrected adult beta globin protein in human erythrocytes differentiated from patient iPSCs after genome editing of the sickle point mutation. Stem Cells. 2015;33:1470–9. https:\u002F\u002Fdoi.org\u002F10.1002\u002Fstem.1969.\nDeWitt MA, Magis W, Bray NL, Wang T, Berman JR, Urbinati F, et al. 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A CRISPR\u002FCas9 vector system for tissue-specific gene disruption in zebrafish. Dev Cell. 2015;32:756–64.\nGuan Y, Ma Y, Li Q, Sun Z, Ma L, Wu L, et al. CRISPR\u002FCas9-mediated somatic correction of a novel coagulator factor IX gene mutation ameliorates hemophilia in mouse. EMBO Mol Med. 2016;8:477–88.\nYin H, Xue W, Chen S, Bogorad RL, Benedetti E, Grompe M, et al. Genome editing with Cas9 in adult mice corrects a disease mutation and phenotype. Nat Biotechnol. 2014;32:551–3.\nYin H, Song C-Q, Dorkin JR, Zhu LJ, Li Y, Wu Q, et al. Therapeutic genome editing by combined viral and non-viral delivery of CRISPR system components in vivo. Nat Biotechnol. 2016;34:328–33.\nPankowicz FP, Barzi M, Legras X, Hubert L, Mi T, Tomolonis JA, et al. Reprogramming metabolic pathways in vivo with CRISPR\u002FCas9 genome editing to treat hereditary tyrosinaemia. Nat Commun. 2016;7:1–6. https:\u002F\u002Fdoi.org\u002F10.1038\u002Fncomms12642.\nYang Y, Wang L, Bell P, McMenamin D, He Z, White J, et al. A dual AAV system enables the Cas9-mediated correction of a metabolic liver disease in newborn mice. Nat Biotechnol. 2016;34:334–8.\nJarrett KE, Lee CM, Yeh YH, Hsu RH, Gupta R, Zhang M, et al. Somatic genome editing with CRISPR\u002FCas9 generates and corrects a metabolic disease. Sci Rep. 2017;7:44624. https:\u002F\u002Fdoi.org\u002F10.1038\u002Fsrep44624.\nLong C, McAnally JR, Shelton JM, Mireault AA, Bassel-Duby R, Olson EN. Prevention of muscular dystrophy in mice by CRISPR\u002FCas9-mediated editing of germline DNA. Science. 2014;345:1184–8.\nTabebordbar M, Zhu K, Cheng JKW, Chew WL, Widrick JJ, Yan WX, et al. In vivo gene editing in dystrophic mouse muscle and muscle stem cells. Science. 2016;351:407–11.\nLong C, Amoasii L, Mireault AA, Mcanally JR, Li H, Sanchez-ortiz E, et al. 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Accessed 12 Feb 2019.",{"VOID":788},"10.1007\u002Fs40291-019-00392-3","2024-05-05T15:24:26.932+00:00","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs40291-019-00392-3",[792,809,824],{"id":793,"sortIndex":21,"researcher":20,"roles":794,"affiliations":795,"properties":804,"displayName":806,"givenName":20,"familyName":20},"d31f689a-2d30-466a-b5e0-975d61eb0a32",[201],[796],{"id":797,"sortIndex":21,"affiliation":798,"properties":20},"3a8c5490-c28d-4880-a352-e82f3f718c06",{"id":797,"createTime":20,"updateTime":20,"relativeEntities":799,"slug":20,"properties":800,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":803,"statistic":20},[],{"title":801},{"VI":802},"Department of Molecular Genetics Thalassaemia, Cyprus School of Molecular Medicine and The Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus",[],{"title":805,"gsAuthor":807},{"VI":806},"Panayiota Papasavva",{"VOID":808},"[\"a5by-k4AAAAJ\"]",{"id":810,"sortIndex":213,"researcher":20,"roles":811,"affiliations":812,"properties":819,"displayName":821,"givenName":20,"familyName":20},"12fa6863-79be-4511-bc86-b4bfa7145078",[201],[813],{"id":797,"sortIndex":21,"affiliation":814,"properties":20},{"id":797,"createTime":20,"updateTime":20,"relativeEntities":815,"slug":20,"properties":816,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":818,"statistic":20},[],{"title":817},{"VI":802},[],{"title":820,"gsAuthor":822},{"VI":821},"Marina Kleanthous",{"VOID":823},"[\"z2K4q8MAAAAJ\"]",{"id":825,"sortIndex":149,"researcher":20,"roles":826,"affiliations":827,"properties":834,"displayName":836,"givenName":20,"familyName":20},"fe230deb-c14f-4012-ae73-fdf1a8fa1a99",[201],[828],{"id":797,"sortIndex":21,"affiliation":829,"properties":20},{"id":797,"createTime":20,"updateTime":20,"relativeEntities":830,"slug":20,"properties":831,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":833,"statistic":20},[],{"title":832},{"VI":802},[],{"title":835,"gsAuthor":837},{"VI":836},"Carsten W. 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We propose a simple procedure for classifying or predicting the cancer types of test samples when multiple cancer types and many genes are present. \n                Method: The procedure sequentially combines a gene-sort algorithm and a predictive likelihood-based classifier. Genes that have homogeneous patterns of expression measurements across cancer types are of limited interest. Therefore, this algorithm orders genes on the basis of strong heterogeneous patterns. The proposed classifier then selects the first few genes, which are sufficient to classify most training samples correctly via cross validation. Test samples were classified using only the selected genes. \n                Results and conclusion: This predictive likelihood-based classifier performs well and is simple to understand. Empirical examination revealed good classification accuracy using relatively few genes.",{"EN":914},"The Simple Classification of Multiple Cancer Types Using a Small Number of Significant Genes",{"VOID":916},"[\"18253989267180971490\"]",{"VOID":918},"10.1007\u002FBF03256248","2024-04-30T15:27:15.235+00:00","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002FBF03256248",[922],{"id":923,"sortIndex":21,"researcher":20,"roles":924,"affiliations":925,"properties":934,"displayName":936,"givenName":20,"familyName":20},"704040aa-0161-4903-9e72-64efe1a304d7",[201],[926],{"id":927,"sortIndex":21,"affiliation":928,"properties":20},"ee27075f-fc58-491f-8e51-6f859c1adfbc",{"id":927,"createTime":20,"updateTime":20,"relativeEntities":929,"slug":20,"properties":930,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":933,"statistic":20},[],{"title":931},{"VI":932},"Department of Mathematics, Myongji University, Yongin, Republic of Korea",[],{"title":935},{"VI":936},"Toe Young Yang",{"url":920,"publisher":938,"properties":992},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":939,"slug":10,"properties":940,"entityType":18,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":21,"subjectFields":944,"manageAffiliations":961,"indexDatabases":972,"url":20,"thumbnailPath":20,"statistic":987,"gsStatistic":20,"type":20,"analyzePriority":20},[],{"issn":941,"title":942,"eissn":943},{"VOID":13},{"EN":15},{"VOID":17},[945,949,953,957],{"id":24,"createTime":20,"updateTime":20,"relativeEntities":946,"label":947,"description":948,"parentId":20,"standard":20,"scholarHubFieldId":20},[],{"EN":27},{},{"id":30,"createTime":20,"updateTime":20,"relativeEntities":950,"label":951,"description":952,"parentId":20,"standard":20,"scholarHubFieldId":20},[],{"EN":33},{},{"id":36,"createTime":20,"updateTime":20,"relativeEntities":954,"label":955,"description":956,"parentId":20,"standard":20,"scholarHubFieldId":20},[],{"EN":39},{},{"id":42,"createTime":20,"updateTime":20,"relativeEntities":958,"label":959,"description":960,"parentId":20,"standard":20,"scholarHubFieldId":20},[],{"EN":45},{},[962,967],{"id":49,"createTime":20,"updateTime":20,"relativeEntities":963,"slug":20,"properties":964,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":966,"statistic":20},[],{"title":965},{"EN":53},[],{"id":56,"createTime":20,"updateTime":20,"relativeEntities":968,"slug":20,"properties":969,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":971,"statistic":20},[],{"title":970},{"EN":60},[],[973,980],{"id":64,"indexDatabase":974,"url":75,"indexYears":76,"academicFieldIds":979,"indexDatabaseRanking":82},{"id":66,"createTime":20,"updateTime":20,"relativeEntities":975,"label":976,"description":977,"key":72,"publicationTags":978,"standard":20},[],{"EN":69,"VI":69},{"EN":69,"VI":71},[74],[78,79,80,81],{"id":84,"indexDatabase":981,"url":97,"indexYears":20,"academicFieldIds":986,"indexDatabaseRanking":20},{"id":86,"createTime":20,"updateTime":20,"relativeEntities":982,"label":983,"description":984,"key":93,"publicationTags":985,"standard":20},[],{"EN":89,"VI":89},{"EN":91,"VI":92},[95,96],[99,100],{"impactFactor":21,"impactFactorByYear":988,"i10Index":114,"i10IndexLast5Year":115,"totalPublication":116,"totalPublicationByYear":989,"totalCitation":130,"totalCitationByYear":990,"totalCitationPerPublication":150,"totalCitationPerPublicationByYear":991,"hindexLast5Year":170,"hindex":170},{"2012":103,"2013":104,"2014":105,"2015":106,"2016":107,"2017":108,"2018":109,"2019":110,"2020":107,"2021":111,"2022":112,"2023":113},{"2006":118,"2007":119,"2008":118,"2009":119,"2010":120,"2011":118,"2012":121,"2013":122,"2014":123,"2015":122,"2016":124,"2017":124,"2018":125,"2019":126,"2020":127,"2021":128,"2022":129,"2023":127,"2024":119},{"2006":132,"2007":133,"2008":134,"2009":135,"2010":136,"2011":137,"2012":138,"2013":139,"2014":140,"2015":141,"2016":142,"2017":143,"2018":144,"2019":145,"2020":146,"2021":146,"2022":147,"2023":148,"2024":149},{"2006":152,"2007":153,"2008":154,"2009":155,"2010":156,"2011":157,"2012":158,"2013":159,"2014":160,"2015":161,"2016":162,"2017":163,"2018":164,"2019":165,"2020":166,"2021":167,"2022":168,"2023":169,"2024":109},{"pages":993,"volume":995},{"VOID":994},"265-275",{"VOID":996},"11",{"total":305,"publishYear":697,"statisticByYear":20},"2026-05-05T22:44:06.797+00:00",[95,82],[1001,1004,1007,1010,1013,1016,1019,1022,1025,1028,1031,1034,1037,1040,1043,1046,1052,1055,1058,1061,1064,1067,1070,1073,1076,1079,1082,1085],{"id":713,"text":1002,"url":715,"identifiers":1003},"Armstrong SA, Staunton JE, Silverman LB, et al. MLL translocations specify a distinct gene expression profile that distinguishes a unique leukemia. Nat Genet 2002 Jan; 30(1): 41–7",{"doi":717},{"id":713,"text":1005,"url":715,"identifiers":1006},"Hedenfalk I, Duggan D, Chen Y, et al. Gene expression profiles in hereditary breast cancer. N Engl J Med 2001 Feb 22; 344(8): 539–48",{"doi":717},{"id":713,"text":1008,"url":715,"identifiers":1009},"Golub TR, Slonim D, Tamayo P, et al. Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science 1999 Oct 15; 286(5439): 531–7",{"doi":717},{"id":713,"text":1011,"url":715,"identifiers":1012},"Yeoh EJ, Ross ME, Shurtleff SA, et al. Classification, subtype discovery, and prediction of outcome in pediatric acute lymphoblastic leukemia by gene expression profiling. Cancer Cell 2002 Mar; 1(2): 133–43",{"doi":717},{"id":713,"text":1014,"url":715,"identifiers":1015},"Eisen M, Spellman P, Brown P, et al. Cluster analysis and display of genome-wide expression patterns. Proc Natl Acad Sci U S A 1998 Dec 8; 95(25): 14863–8",{"doi":717},{"id":713,"text":1017,"url":715,"identifiers":1018},"Tavazoie S, Hughes JD, Campbell MJ, et al. Systematic determination of genetic network architecture. Nat Genet 1999 Jul; 22(3): 281–5",{"doi":717},{"id":713,"text":1020,"url":715,"identifiers":1021},"Hastie T, Tibshirani R, Friedman J. The elements of statistical learning: data mining, inference, and prediction. New York: Springer Verlag, 2001",{"doi":717},{"id":713,"text":1023,"url":715,"identifiers":1024},"Yang TY. A tree-based model for homogeneous groupings of multinominals. Stat Med 2005 Nov 30; 24(22): 3513–22",{"doi":717},{"id":713,"text":1026,"url":715,"identifiers":1027},"Wang Y, Makedon FS, Ford J, et al. HykGene: a hybrid approach for selecting marker genes for phenotype classification using microarray gene expression data. 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Int J Mol Sci. 2019;20(16):3951. https:\u002F\u002Fdoi.org\u002F10.3390\u002Fijms20163951.","https:\u002F\u002Fwww.mdpi.com\u002F1422-0067\u002F20\u002F16\u002F3951",{"doi":1815},"10.3390\u002Fijms20163951",{"id":1817,"text":1818,"url":1819,"identifiers":1820},"d862cbb5-7ccc-40db-a6c0-77d087dd93e0","Bubendorf L, Lantuejoul S, de Langen AJ, Thunnissen E. Nonsmall cell lung carcinoma: diagnostic difficulties in small biopsies and cytological specimens. Eur Respir Rev. 2017;26(144):170007. https:\u002F\u002Fdoi.org\u002F10.1183\u002F16000617.0007-2017.","http:\u002F\u002Fpublications.ersnet.org\u002Flookup\u002Fdoi\u002F10.1183\u002F16000617.0007-2017",{"doi":1821},"10.1183\u002F16000617.0007-2017",{"id":1823,"text":1824,"url":1825,"identifiers":1826},"0e2cb0ba-ec67-4239-8427-2465df1ac17c","McLean AEB, Barnes DJ, Troy LK. Diagnosing lung cancer: the complexities of obtaining a tissue diagnosis in the era of minimally invasive and personalised medicine. J Clin Med. 2018;7(7):163. https:\u002F\u002Fdoi.org\u002F10.3390\u002Fjcm7070163.","https:\u002F\u002Fwww.mdpi.com\u002F2077-0383\u002F7\u002F7\u002F163",{"doi":1827},"10.3390\u002Fjcm7070163",{"id":1829,"text":1830,"url":1831,"identifiers":1832},"82960a93-ed76-4eb8-8b52-1c7da3134c65","Wu Y-L, Sequist LV, Hu C-P, Feng J, Lu S, Huang Y, et al. EGFR mutation detection in circulating cell-free DNA of lung adenocarcinoma patients: analysis of LUX-Lung 3 and 6. Br J Cancer. 2017;116(2):175–85. https:\u002F\u002Fdoi.org\u002F10.1038\u002Fbjc.2016.420.","https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fbjc2016420",{"doi":1833},"10.1038\u002Fbjc.2016.420",{"id":20,"text":1835,"url":1836,"identifiers":1837},"Mlika M, Dziri C, Zorgati MM, Ben Khelil M, Mezni F. Liquid biopsy as surrogate to tissue in lung cancer for molecular profiling: a meta-analysis. Curr Respir Med Rev. 2018;14(1):48–60. https:\u002F\u002Fdoi.org\u002F10.2174\u002F1573398X14666180430144452.","https:\u002F\u002Fdoi.org\u002F10.2174\u002F1573398x14666180430144452",{"mag":1838,"pmc":1839,"openalex":1840,"pm":1841,"doi":1842},"2800191155","6128071","W2800191155","30271314","10.2174\u002F1573398x14666180430144452",{"id":1844,"text":1845,"url":1846,"identifiers":1847},"f2938953-8024-434b-bb57-d653ea2c95d5","Garcia J, Forestier J, Dusserre E, Wozny AS, Geiguer F, Merle P, et al. Cross-platform comparison for the detection of RAS mutations in cfDNA (ddPCR Biorad detection assay, BEAMing assay, and NGS strategy). Oncotarget. 2018;9(30):21122–31. https:\u002F\u002Fdoi.org\u002F10.18632\u002Foncotarget.24950.","https:\u002F\u002Fwww.oncotarget.com\u002Flookup\u002Fdoi\u002F10.18632\u002Foncotarget.24950",{"doi":1848},"10.18632\u002Foncotarget.24950",{"id":20,"text":1850,"url":1851,"identifiers":1852},"Liang W, Zhang Y, Kang S, Pan H, Shao W, Deng Q, et al. Impact of EGFR mutation status on tumor response and progression free survival after first-line chemotherapy in patients with advanced non-small-cell lung cancer: a meta-analysis. J Thorac Dis. 2014;6(9):1239–50. https:\u002F\u002Fdoi.org\u002F10.3978\u002Fj.issn.2072-1439.2014.07.33.","https:\u002F\u002Fpubmed.ncbi.nlm.nih.gov\u002F25276366",{"mag":1853,"pmc":1854,"openalex":1855,"pm":1856,"doi":1857},"2137749537","4178107","W2137749537","25276366","10.3978\u002Fj.issn.2072-1439.2014.07.33",{"id":1859,"text":1860,"url":1861,"identifiers":1862},"f6020b95-97f7-466a-85e8-122504bb97bd","Yu HA, Arcila ME, Rekhtman N, Sima CS, Zakowski MF, Pao W, et al. Analysis of tumor specimens at the time of acquired resistance to EGFR-TKI therapy in 155 patients with EGFR-mutant lung cancers. Clin Cancer Res. 2013;19(8):2240–7. https:\u002F\u002Fdoi.org\u002F10.1158\u002F1078-0432.ccr-12-2246.","https:\u002F\u002Faacrjournals.org\u002Fclincancerres\u002Farticle\u002F19\u002F8\u002F2240\u002F207432\u002FAnalysis-of-Tumor-Specimens-at-the-Time-of",{"doi":1863},"10.1158\u002F1078-0432.ccr-12-2246",{"id":1865,"text":1866,"url":1867,"identifiers":1868},"efb7f95f-84e8-4c9b-9967-cf32caec0e08","Chen Y-L, Lin C-C, Yang S-C, Chen W-L, Chen J-R, Hou Y-H, et al. Five technologies for detecting the EGFR T790M mutation in the circulating cell-free DNA of patients with non-small cell lung cancer: a comparison. Front Oncol. 2019;9:631. https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffonc.2019.00631.","https:\u002F\u002Fwww.frontiersin.org\u002Farticle\u002F10.3389\u002Ffonc.2019.00631\u002Ffull",{"doi":1869},"10.3389\u002Ffonc.2019.00631",{"id":1871,"text":1872,"url":1873,"identifiers":1874},"db6c2889-30b1-4d52-97a8-9e85c6cf0fc4","Diaz LA Jr, Bardelli A. Liquid biopsies: genotyping circulating tumor DNA. J Clin Oncol. 2014;32(6):579–86. https:\u002F\u002Fdoi.org\u002F10.1200\u002Fjco.2012.45.2011.","https:\u002F\u002Fascopubs.org\u002Fdoi\u002F10.1200\u002FJCO.2012.45.2011",{"doi":1875},"10.1200\u002Fjco.2012.45.2011",{"id":1877,"text":1878,"url":1879,"identifiers":1880},"3a861fb7-6908-4681-a048-4534b7e0d846","Kempf E, Rousseau B, Besse B, Paz-Ares L. KRAS oncogene in lung cancer: focus on molecularly driven clinical trials. Eur Respir Rev. 2016;25(139):71–6. https:\u002F\u002Fdoi.org\u002F10.1183\u002F16000617.0071-2015.","http:\u002F\u002Fpublications.ersnet.org\u002Flookup\u002Fdoi\u002F10.1183\u002F16000617.0071-2015",{"doi":1881},"10.1183\u002F16000617.0071-2015",{"id":1883,"createTime":1884,"updateTime":1885,"relativeEntities":1886,"slug":1887,"properties":1888,"entityType":192,"verifyStatus":193,"verifyTime":1897,"verifyNote":195,"languages":20,"translateLanguages":20,"viewCount":21,"primaryUrl":1898,"fullTextUrl":20,"authors":1899,"publicationType":450,"publisherRelationship":2004,"citationCount":21,"citationInfo":2063,"publishDate":699,"publishYear":697,"citationAnalyzeStatus":19,"lastCitationAnalyze":2065,"indexDatabases":2066,"openAccess":20,"references":2067,"isForceReanalyzing":518},"bd4a236a-4b59-45d8-8081-8e1bffce8e77","2024-01-29T14:55:51.995+00:00","2026-03-17T17:15:33.721+00:00",[],"Assessment-of-Human-Serotonin-1A-Receptor-Polymorphisms-and-SSRI-Responsiveness",{"abstract":1889,"title":1891,"gsPaper":1893,"doi":1895},{"EN":1890},"\n                Background: Depression is thought to involve, in part, dysregulation of serotonergic neurotransmission. In depressed individuals, the number of serotonin receptors, including the 5-hydroxytryptamine (serotonin)-1A (5-HT1A) autoreceptors, are increased. Clinical improvement with selective serotonin reuptake inhibitors (SSRIs) is not usually observed until several weeks after treatment initiation. This delay may be due to the time it takes for the autoreceptors to downregulate. Roughly one-third of patients with depression do not respond to an initial trial of antidepressant medication treatment, possibly as a result of structural variations in the 5-HT1A receptor. \n                Aims: This study was designed to determine the allelic frequency of seven 5-HT1A receptor polymorphisms in a depressed versus a nondepressed population, and in SSRI responders versus nonresponders. All the polymorphisms studied are single nucleotide polymorphisms (SNPs) in the HTR1A gene, which encodes 5-HT1A. Seven prevalent SNPs were included in the analysis. \n                Results: The study showed no relationship between any of the HTR1A polymorphisms and SSRI responders versus nonresponders. \n                Conclusion: While the study has several limitations, the results are consistent with a growing body of literature that suggests that the pharmacogenetics of depression (an inherently complex disorder) may turn out to be multifactorial, and may include the HTR1A gene in concert with other serotonin-related genes.",{"EN":1892},"Assessment of Human Serotonin 1A Receptor Polymorphisms and SSRI Responsiveness",{"VOID":1894},"[\"885461935583372052\"]",{"VOID":1896},"10.1007\u002FBF03256237","2024-05-04T08:11:48.260+00:00","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002FBF03256237",[1900,1924,1937,1950,1965,1978,1991],{"id":1901,"sortIndex":21,"researcher":20,"roles":1902,"affiliations":1903,"properties":1921,"displayName":1923,"givenName":20,"familyName":20},"ceda13f5-ccec-4d40-bcac-4b6fbe1b02e7",[201],[1904,1912],{"id":1905,"sortIndex":21,"affiliation":1906,"properties":20},"61c71e6c-1f10-47eb-ab98-1206dfc1c3fc",{"id":1905,"createTime":20,"updateTime":20,"relativeEntities":1907,"slug":20,"properties":1908,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1911,"statistic":20},[],{"title":1909},{"EN":1910},"College of Pharmacy University of Florida, Gainesville, USA",[],{"id":1913,"sortIndex":213,"affiliation":1914,"properties":1920},"d58ed863-cffe-48b1-b79f-d42a36d1e1a4",{"id":1913,"createTime":20,"updateTime":20,"relativeEntities":1915,"slug":20,"properties":1916,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1919,"statistic":20},[],{"title":1917},{"VI":1918},"School of Pharmacy, Nova Southeastern University, Davie, USA",[],{},{"title":1922},{"VI":1923},"Gary M. Levin",{"id":1925,"sortIndex":213,"researcher":20,"roles":1926,"affiliations":1927,"properties":1934,"displayName":1936,"givenName":20,"familyName":20},"181bd839-713d-4f5e-852a-8d14effaa1c2",[201],[1928],{"id":1905,"sortIndex":21,"affiliation":1929,"properties":20},{"id":1905,"createTime":20,"updateTime":20,"relativeEntities":1930,"slug":20,"properties":1931,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1933,"statistic":20},[],{"title":1932},{"EN":1910},[],{"title":1935},{"VI":1936},"Toya M. 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Ehret",{"id":1951,"sortIndex":266,"researcher":20,"roles":1952,"affiliations":1953,"properties":1960,"displayName":1962,"givenName":20,"familyName":20},"f224d07d-4351-4bec-92e1-0d3bb3c0b27d",[201],[1954],{"id":1905,"sortIndex":21,"affiliation":1955,"properties":20},{"id":1905,"createTime":20,"updateTime":20,"relativeEntities":1956,"slug":20,"properties":1957,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1959,"statistic":20},[],{"title":1958},{"EN":1910},[],{"title":1961,"gsAuthor":1963},{"VI":1962},"Taimour Langaee",{"VOID":1964},"[\"w_litBEAAAAJ\"]",{"id":1966,"sortIndex":284,"researcher":20,"roles":1967,"affiliations":1968,"properties":1975,"displayName":1977,"givenName":20,"familyName":20},"58df78a0-9d3b-4399-b746-ab0da9e02943",[201],[1969],{"id":1905,"sortIndex":21,"affiliation":1970,"properties":20},{"id":1905,"createTime":20,"updateTime":20,"relativeEntities":1971,"slug":20,"properties":1972,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1974,"statistic":20},[],{"title":1973},{"EN":1910},[],{"title":1976},{"VI":1977},"Jennifer Y. 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Neuroscientist 2004; 10: 575–93",{"doi":717},{"id":713,"text":2072,"url":715,"identifiers":2073},"Stahl SM. Essential psychopharmacology of depression and bipolar disorder. New York: Cambridge University Press, 2000",{"doi":717},{"id":713,"text":2075,"url":715,"identifiers":2076},"Rotondo A, Nielsen DA, Nakhai B, et al. Agonist-promoted down-regulation and functional desensitization in two naturally occurring variants of the human serotonin 1A receptor. Neuropsychopharmacology 1997; 17: 18–26",{"doi":717},{"id":2078,"text":2079,"url":2080,"identifiers":2081},"c11b6074-34c6-4f15-974d-715c95faa08e","Albert PR, Lembo P, Starring JM, et al. The 5-HT1A receptor: signaling, desensitization, and gene transcription. Neuropsychopharmacology 1996; 14: 19–25","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS0893133X96800558",{"doi":2082},"10.1016\u002Fs0893-133x(96)80055-8",{"id":713,"text":2084,"url":715,"identifiers":2085},"Kobilka BK, Frielle T, Collins S, et al. An intronless gene encoding a potential member of the family of receptors coupled to guanine nucleotide regulatory proteins. Nature 1987; 329: 75–9",{"doi":717},{"id":713,"text":2087,"url":715,"identifiers":2088},"Erdmann J, Shimron-Abarbanell D, Cichon S, et al. Systematic screening for mutations in the promoter and the coding region of the 5-HT1A gene. Am J Med Genet 1995; 60: 393–9",{"doi":717},{"id":713,"text":2090,"url":715,"identifiers":2091},"Nakhai B, Nielsen DA, Linnoila M, et al. Two naturally occurring amino acid substitutions in the human 5-HT1A receptor: glycine 22 to serine 22 and isoleucine 28 to valine 28. Biochem Biophys Res Commun 1995; 210: 530–6",{"doi":717},{"id":713,"text":2093,"url":715,"identifiers":2094},"Wu S, Comings DE. A common C-1018G polymorphism in the human 5-HT1A receptor gene. Psychiatr Genetics 1999; 9: 105–6",{"doi":717},{"id":713,"text":2096,"url":715,"identifiers":2097},"Arias B, Arranz MJ, Gasto C, et al. Analysis of structural polymorphisms and C-1018G promoter variant of the 5-HT(1A) receptor gene as putative risk factors in major depression. Mol Psychiatry 2002; 7: 930–2",{"doi":717},{"id":713,"text":2099,"url":715,"identifiers":2100},"Parks CL, Shenk T. The serotonin 1a receptor gene contains a TATA-less promoter that responds to MAZ and Spl. J Biol Chem 1996; 271: 4417–30",{"doi":717},{"id":713,"text":2102,"url":715,"identifiers":2103},"Huang YY, Battistuzzi C, Oquendo MA, et al. Human 5-HT1A receptor C(-1019)G polymorphism and psychopathology. Int J Neuropsychopharmacol 2004; 7: 441–51",{"doi":717},{"id":713,"text":2105,"url":715,"identifiers":2106},"Lemonde S, Turecki G, Bakish D, et al. Impaired repression at a 5-hydroxytryptamine 1A receptor gene polymorphism associated with major depression and suicide. J Neurosci 2003; 23: 8788–99",{"doi":717},{"id":713,"text":2108,"url":715,"identifiers":2109},"Arias B, Catalan R, Gasto C, et al. Evidence for a combined genetic effect of the 5-HT(1A) receptor and serotonin transporter genes in the clinical outcome of major depressive patients treated with citalopram. J Psychopharmacol 2005; 19: 166–72",{"doi":717},{"id":713,"text":2111,"url":715,"identifiers":2112},"Hong CJ, Chen TJ, Yu YW, et al. Response to fluoxetine and serotonin 1A receptor (C-1019G) polymorphism in Taiwan Chinese major depressive disorder. Pharmacogenomics J 2006; 6: 27–33",{"doi":717},{"id":713,"text":2114,"url":715,"identifiers":2115},"Serretti A, Artioli P, Lorenzi C, et al. The C(-1019)G polymorphism of the 5-HT1A gene promoter and antidepressant response in mood disorders: preliminary findings. Int J Neuropsychopharmacol 2004; 7: 453–60",{"doi":717},{"id":713,"text":2117,"url":715,"identifiers":2118},"Yu YW, Tsai SJ, Liou YJ, et al. Association study of two serotonin 1A receptor gene polymorphism and fluoxetine treatment response in Chinese major depressive disorders. Eur Neuropsychopharmacol 2006; 16: 498–503",{"doi":717},{"id":2120,"text":2121,"url":2122,"identifiers":2123},"7a65fc3d-b1b6-496e-a38a-b99aacc377c8","Feldman RS, Meyer JS, Quenzer LF. Principles of neuropsychopharmacology. Sunderland (MA): Sinauer Associates, 1997","https:\u002F\u002Fwww.goodreads.com\u002Fbook\u002Fshow\u002F1720824.Principles_of_Neuropsychopharmacology",{"isbn":2124,"isbn13":2125},"0878931759","9780878931750",{"id":713,"text":2127,"url":715,"identifiers":2128},"Andrisin TE, Humma LM, Johnson JA. Collection of genomic DNA by the noninvasive mouthwash method for use in pharmacogenetic studies. Pharmacotherapy 2002; 22: 954–60",{"doi":717},{"id":713,"text":2130,"url":715,"identifiers":2131},"Langaee T, Ronaghi M. Genetic variation analyses by pyrosequencing. Mutat Res 2005; 573: 96–102",{"doi":717},{"id":713,"text":2133,"url":715,"identifiers":2134},"Bergen A, Wang CY, Nakhai B, et al. Mass allele detection (MAD) of rare 5-HT1A structural variants with allele-specific amplification and electrochemiluminescent detection. Hum Mutat 1996; 7: 135–43",{"doi":717},{"id":2136,"text":2137,"url":2138,"identifiers":2139},"dc876735-a1f1-4352-8729-41709e2fc3d5","Del Tredici AL, Schiffer HH, Burstein ES, et al. Pharmacology of polymorphic variants of the human 5 HT1A receptor. Biochem Pharmacol 2004; 67: 479–90","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS0006295203007664",{"doi":2140},"10.1016\u002Fj.bcp.2003.09.030",{"id":713,"text":2142,"url":715,"identifiers":2143},"Kawanishi Y, Harada S, Tachikawa H, et al. Novel mutations in the promoter and coding region of the human 5-HT1A receptor gene and association analysis in schizophrenia. Am J Med Genet 1998; 81: 434–9",{"doi":717},{"id":713,"text":2145,"url":715,"identifiers":2146},"Lemonde S, Du L, Bakish D, et al. Association of the C(-1019)G 5-HT1A functional promoter polymorphism with antidepressant response. Int J Neuropsychopharmacology 2004; 7: 501–6",{"doi":717},{"id":713,"text":2148,"url":715,"identifiers":2149},"Arias B, Arranz MJ, Gasto C, et al. Analysis of structural polymorphisms and C-1018G promoter variant of the 5-HT(1A) receptor gene as putative risk factors in major depression. Mol Psychiatry 2003; 8: 246",{"doi":717},{"id":713,"text":2151,"url":715,"identifiers":2152},"Parsey RV, Oquendo MA, Ogden T, et al. Altered serotonin 1A binding in major depression: a [carbonyl-C-11l]WAY1000635 positron emission tomography study. Biol Psychiatry 2006; 59: 106–13",{"doi":717},{"id":713,"text":2154,"url":715,"identifiers":2155},"Parsey RV, Olvert DM, Oquendo MA, et al. Higher 5-HT(1A) receptor binding potential during a major depressive episode predicts poor treatment response: preliminary data from a naturalistic study. Neuropsychopharmacology 2006 Aug; 31(8): 1745–9",{"doi":717},{"id":713,"text":2157,"url":715,"identifiers":2158},"Kraft JB, Slager SL, McGrath PJ, et al. Sequence analysis of the serotonin transporter and associations with antidepressant response. Biol Psychiatry 2005; 58: 374–81",{"doi":717},{"id":713,"text":2160,"url":715,"identifiers":2161},"Masoliver E, Menoyo A, Perez V, et al. Serotonin transporter linked promoter (polymorphism) in the serotonin transporter gene may be associated with antidepressant-induced mania in bipolar disorder. Psychiatr Genet 2006; 16: 25–9",{"doi":717},{"id":713,"text":2163,"url":715,"identifiers":2164},"Pollock BG, Ferrell RE, Mulsant BH, et al. Allelic variation in the serotonin transporter promoter affects onset of paroxetine treatment response in late-life depression. Neuropsychopharmacology 2000; 23: 587–90",{"doi":717},{"id":713,"text":2166,"url":715,"identifiers":2167},"Serretti A, Cusin C, Rossini D, et al. Further evidence of a combined effect of SERTPR and TPH on SSRIs response in mood disorders. Am J Med Genet B Neuropsychiatr Genet 2004; 129: 36–40",{"doi":717},{"id":713,"text":2169,"url":715,"identifiers":2170},"Parsey RV, Hastings RS, Oquendo MA, et al. Lower serotonin transporter binding potential in the human brain during major depressive episodes. Am J Psychiatry 2006; 163: 52–8",{"doi":717},{"id":2172,"createTime":2173,"updateTime":2174,"relativeEntities":2175,"slug":2176,"properties":2177,"entityType":192,"verifyStatus":193,"verifyTime":2188,"verifyNote":195,"languages":20,"translateLanguages":20,"viewCount":21,"primaryUrl":2189,"fullTextUrl":20,"authors":2190,"publicationType":450,"publisherRelationship":2374,"citationCount":20,"citationInfo":20,"publishDate":2434,"publishYear":2435,"citationAnalyzeStatus":2436,"lastCitationAnalyze":2437,"indexDatabases":2438,"openAccess":20,"references":20,"isForceReanalyzing":518},"732ee0d0-2218-40f3-80d9-68365c630240","2024-02-15T03:31:29.404+00:00","2026-02-28T02:21:27.488+00:00",[],"Targeted-Therapy-Management-in-NSCLC-Patients-Using-Cytology-Experience-from-a-Tertiary-Care-Cancer-Center",{"abstract":2178,"title":2180,"gsPaper":2182,"references":2184,"doi":2186},{"EN":2179},"Although biopsy is the gold standard for diagnosis, cytological material has often been used to assist in making a pathologic diagnosis as well as for molecular testing in certain cancers such as in the lung, cervix, and head\u002Fneck. Our objective is to share experience from our institution in the use of cytological material in screening for epidermal growth factor receptor (EGFR) mutations in a subset of patients with non-small cell lung cancer (NSCLC). Fine needle aspirates, pleural effusion, cell blocks of 223 NSCLC patients, where cytology suggested malignancy were screened for EGFR mutation in exons 18–21 using Scorpion® ARMS real-time polymerase chain reaction (PCR) technology. Overall, EGFR mutation was seen in 43.5 % of study samples. Deletions were highest in exon 19 (27.2 %), followed by exon 21 (15.5 %), exon 18 (5.3 %), and exon 20 (1.9 %). Chi-squared analysis revealed a significant correlation for mutation status in women compared with men (χ\n                           2 = 5.88, p = 0.02), with exon 19 mutation predominating (χ\n                           2 = 5.66, p = 0.02). Our results demonstrate the successful use of cytology material for molecular testing in a subset of NSCLC patients to direct their treatment.",{"EN":2181},"Targeted Therapy Management in NSCLC Patients Using Cytology: Experience from a Tertiary Care Cancer Center",{"VOID":2183},"[]",{"VOID":2185},"Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J, Jemal A. Global cancer statistics, 2012. CA Cancer J Clin. 2015;65(2):87–108.\nDiamantis A, Beloukas AI, Kalogeraki AM, Magiorkinis E. A brief chronicle of cytology: from Janssen to Papanicolaou and beyond. Diagn Cytopathol. 2013;41(6):555–64.\nZarbo RJ, Fenoglio-Preiser CM. Interinstitutional database for comparison of performance in lung fine-needle aspiration cytology. A College of American Pathologists Q-Probe Study of 5264 cases with histologic correlation. Arch Pathol Lab Med. 1992;116(5):463–70.\nAbedi-Ardekani B, Vielh P. Is liquid-based cytology the magic bullet for performing molecular techniques? Acta Cytol. 2014;58(6):574–81.\nAllegrini S, Antona J, Mezzapelle R, et al. Epidermal growth factor receptor gene analysis with a highly sensitive molecular assay in routine cytologic specimens of lung adenocarcinoma. Am J Clin Pathol. 2012;138(3):377–81.\nDejmek A, Zendehrokh N, Tomaszewska M, Edsjo A. Preparation of DNA from cytological material: effects of fixation, staining, and mounting medium on DNA yield and quality. Cancer Cytopathol. 2013;121:344–53.\nThelwell N, Millington S, Solinas A, Booth J, Brown T. Mode of action and application of Scorpion primers to mutation detection. Nucleic Acids Res. 2000;28:3752–61.\nVeldore VH, Rao RM, Kakara S, et al. Epidermal growth factor receptor mutation in non-small-cell lung carcinomas: a retrospective analysis of 1036 lung cancer specimens from a network of tertiary cancer care centers in India. Indian J Cancer. 2013;50(2):87–93.\nParikh P, Puri T. Personalized medicine: lung cancer leads the way. Indian J Cancer. 2013;50:77–9.\nTokumo M, Toyooka S, Kiura K, et al. The relationship between epidermal growth factor receptor mutations and clinicopathologic features in non-small cell lung cancers. Clin Cancer Res. 2005;11:1167–73.\nYoshida K, Yatabe Y, Park JY, et al. Prospective validation for prediction of gefitinib sensitivity by epidermal growth factor receptor gene mutation in patients with non-small cell lung cancer. J Thorac Oncol. 2007;2:22–8.\nKim HJ, Oh SY, Kim WS, et al. Clinical investigation of EGFR mutation detection by pyrosequencing in lung cancer patients. Oncol Lett. 2013;5:271–6.\nSun PL, Seol H, Lee HJ, et al. High incidence of EGFR mutations in Korean men smokers with no intratumoral heterogeneity of lung adenocarcinomas: correlation with histologic subtypes, EGFR\u002FTTF-1 expressions, and clinical features. J Thorac Oncol. 2012;7:323–30.\nRahman S, Kondo N, Yoneda K, et al. Frequency of epidermal growth factor receptor mutations in Bangladeshi patients with adenocarcinoma of the lung. Int J Clin Oncol. 2014;19(1):45–9.\nLi M, Zhang Q, Liu L, et al. The different clinical significance of EGFR mutations in exon 19 and 21 in non-small cell lung cancer patients of China. Neoplasma. 2011;58:74–81.\nBai H, Wang Z, Chen K, et al. Influence of chemotherapy on EGFR mutation status among patients with non-small-cell lung cancer. J Clin Oncol. 2012;30:3077–83.\nLiam CK, Wahid MI, Rajadurai P, Cheah YK, Ng TS. Epidermal growth factor receptor mutations in lung adenocarcinoma in Malaysian patients. J Thorac Oncol. 2013;8:766–72.\nWang F, Fang P, Hou DY, Leng ZJ, Cao LJ. Comparison of epidermal growth factor receptor mutations between primary tumors and lymph nodes in non-small cell lung cancer: a review and meta-analysis of published data. Asian Pac J Cancer Prev. 2014;15:4493–7.\nYatabe Y, Matsuo K, Mitsudomi T. Heterogeneous distribution of EGFR mutations is extremely rare in lung adenocarcinoma. J Clin Oncol. 2011;29:2972–7.\nda Cunha Santos G, Saieg MA. Preanalytic parameters in epidermal growth factor receptor mutation testing for non-small cell lung carcinoma: a review of cytologic series. Cancer Cytopathol. 2015 (Epub ahead of print).",{"VOID":2187},"10.1007\u002Fs40291-015-0180-1","2024-05-12T22:27:13.698+00:00","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs40291-015-0180-1",[2191,2206,2221,2234,2247,2260,2273,2286,2299,2312,2325,2347],{"id":2192,"sortIndex":21,"researcher":20,"roles":2193,"affiliations":2194,"properties":2203,"displayName":2205,"givenName":20,"familyName":20},"a40777b9-ae28-4079-8b4b-7a144750920a",[201],[2195],{"id":2196,"sortIndex":21,"affiliation":2197,"properties":20},"b5e7b8d9-1e36-4a6c-a525-91c0b6ca8a3b",{"id":2196,"createTime":20,"updateTime":20,"relativeEntities":2198,"slug":20,"properties":2199,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":2202,"statistic":20},[],{"title":2200},{"VI":2201},"Triesta Reference Laboratory, Triesta Sciences, A Unit of Health Care Global Enterprises Ltd., Bangalore, India",[],{"title":2204},{"VI":2205},"Vidya H. 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While, historically, patients with this condition rarely lived into their thirties, they are now living substantially longer as a result of new treatments based on multi-disciplinary care. Despite these advances, the prognosis for DMD patients is limited, and a progressive reduction in quality of life and early death in adulthood cannot be prevented using currently available treatment regimens. The best hopes for a cure lies with cellular and gene therapy approaches that target the underlying genetic defect. In the past several years, viral and nonviral gene therapy methodologies based on adeno-associated viruses, naked plasmid delivery, antisense oligonucleotides, and oligonucleotide-mediated gene editing have advanced to a high degree of sophistication, to the extent that research has moved from the laboratory setting to the clinic. Notwithstanding these accomplishments, shortcomings with each therapy remain, so more work is required to devise an appropriate therapeutic strategy for the management and eventual cure of this debilitating disease.",{"EN":2449},"Molecular-Targeted Therapy for Duchenne Muscular Dystrophy",{"VOID":2451},"[\"12921757396122402844\"]",{"EN":2453},"",{"VOID":2455},"Emery AE. Muscular dystrophy into the new millennium. Neuromuscul Disord 2002 May; 12(4): 343–9\nRando TA. Non-viral gene therapy for Duchenne muscular dystrophy: progress and challenges. Biochim Biophys Acta 2007 Feb; 1772(2): 263–71\nPeault B, Rudnicki M, Torrente Y, et al. Stem and progenitor cells in skeletal muscle development, maintenance, and therapy. Mol Ther 2007 May; 15(5): 867–77\nBlankinship MJ, Gregorevic P, Chamberlain JS. Gene therapy strategies for Duchenne muscular dystrophy utilizing recombinant adeno-associated virus vectors. Mol Ther 2006 Feb; 13(2): 241–9\nArahata K, Engel AG. Monoclonal antibody analysis of mononuclear cells in myopathies: I. Quantitation of subsets according to diagnosis and sites of accumulation and demonstration and counts of muscle fibers invaded by T cells. Ann Neurol 1984 Aug; 16(2): 193–208\nGriggs RC, Moxley RT, Mendell JR, et al. Prednisone in Duchenne dystrophy: a randomized, controlled trial defining the time course and dose response. Clinical Investigation of Duchenne Dystrophy Group. Arch Neurol 1991 Apr; 48(4): 383–8\nMendell JR, Moxley RT, Griggs RC, et al. Randomized, double-blind six-month trial of prednisone in Duchenne’s muscular dystrophy. N Engl J Med 1989 Jun 15; 320(24): 1592–7\nMoxley RT, Ashwal S, Pandya S, et al. Practice parameter: corticosteroid treatment of Duchenne dystrophy: report of the Quality Standards Subcommittee of the American Academy of Neurology and the Practice Committee of the Child Neurology Society. Neurology 2005 Jan 11; 64(1): 13–20\nBalaban B, Matthews DJ, Clayton GH, et al. Corticosteroid treatment and functional improvement in Duchenne muscular dystrophy: long-term effect. Am J Phys Med Rehabil 2005 Nov; 84(11): 843–50\nKinali M, Mercuri E, Main M, et al. An effective, low-dosage, intermittent schedule of prednisolone in the long-term treatment of early cases of Duchenne dystrophy. Neuromuscul Disord 2002 Oct; 12Suppl. 1: S169–74\nWagner KR, Lechtzin N, Judge DP. Current treatment of adult Duchenne muscular dystrophy. Biochim Biophys Acta 2007 Feb; 1772(2): 229–37\nMcDonald DG, Kinali M, Gallagher AC, et al. Fracture prevalence in Duchenne muscular dystrophy. Dev Med Child Neurol 2002 Oct; 44(10): 695–8\nSimonds AK. Respiratory complications of the muscular dystrophies. Semin Respir Crit Care Med 2002 Jun; 23(3): 231–8\nMohr CH, Hill NS. Long-term follow-up of nocturnal ventilatory assistance in patients with respiratory failure due to Duchenne-type muscular dystrophy. Chest 1990 Jan; 97(1): 91–6\nSimonds AK, Muntoni F, Heather S, et al. 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Viral serotype and the transgene sequence influence overlapping adeno-associated viral (AAV) vector-mediated gene transfer in skeletal muscle. J Gene Med 2006 Mar; 8(3): 298–305\nGhosh A, Yue Y, Long C, et al. Efficient whole-body transduction with trans-splicing adeno-associated viral vectors. Mol Ther 2007 Apr; 15(4): 750–5\nLai Y, Yue Y, Liu M, et al. Efficient in vivo gene expression by trans-splicing adeno-associated viral vectors. Nat Biotechnol 2005 Nov; 23(11): 1435–9\nMcCarty DM, Young Jr SM, Samulski RJ. Integration of adeno-associated virus (AAV) and recombinant AAV vectors. Annu Rev Genet 2004; 38: 819–45\nLouboutin JP, Wang L, Wilson JM. Gene transfer into skeletal muscle using novel AAV serotypes. J Gene Med 2005 Apr; 7(4): 442–51\nSchmidt M, Katano H, Bossis I, et al. Cloning and characterization of a bovine adeno-associated virus. J Virol 2004 Jun; 78(12): 6509–16\nBlouin V, Brument N, Toublanc E, et al. 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Cell Transplant 1996 May–Jun; 5(3): 411–9\nWells DJ, Maule J, McMahon J, et al. Evaluation of plasmid DNA for in vivo gene therapy: factors affecting the number of transfected fibers. J Pharm Sci 1998 Jun; 87(6): 763–8\nAcsadi G, Dickson G, Love DR, et al. Human dystrophin expression in mdx mice after intramuscular injection of DNA constructs. Nature 1991 Aug 29; 352(6338): 815–8\nRomero NB, Braun S, Benveniste O, et al. Phase I study of dystrophin plasmid-based gene therapy in Duchenne\u002FBecker muscular dystrophy. Hum Gene Ther 2004 Nov; 15(11): 1065–76\nTaniyama Y, Tachibana K, Hiraoka K, et al. Development of safe and efficient novel nonviral gene transfer using ultrasound: enhancement of transfection efficiency of naked plasmid DNA in skeletal muscle. Gene Ther 2002 Mar; 9(6): 372–80\nDanialou G, Comtois AS, Dudley RW, et al. Ultrasound increases plasmid-mediated gene transfer to dystrophic muscles without collateral damage. Mol Ther 2002 Nov; 6(5): 687–93\nLu QL, Liang HD, Partridge T, et al. Microbubble ultrasound improves the efficiency of gene transduction in skeletal muscle in vivo with reduced tissue damage. Gene Ther 2003 Mar; 10(5): 396–405\nBekeredjian R, Chen S, Frenkel PA, et al. Ultrasound-targeted microbubble destruction can repeatedly direct highly specific plasmid expression to the heart. Circulation 2003 Aug 26; 108(8): 1022–6\nMir LM, Bureau MF, Gehl J, et al. High-efficiency gene transfer into skeletal muscle mediated by electric pulses. Proc Natl Acad Sci U S A 1999 Apr 13; 96(8): 4262–7\nAihara H, Miyazaki J. Gene transfer into muscle by electroporation in vivo. Nat Biotechnol 1998 Sep; 16(9): 867–70\nAndre F, Mir LM. DNA electrotransfer: its principles and an updated review of its therapeutic applications. Gene Ther 2004 Oct; 11Suppl. 1: S33–42\nWong SH, Lowes KN, Quigley AF, et al. DNA electroporation in vivo targets mature fibres in dystrophic mdx muscle. Neuromuscul Disord 2005 Oct; 15(9-10): 630–41\nMurakami T, Nishi T, Kimura E, et al. Full-length dystrophin cDNA transfer into skeletal muscle of adult mdx mice by electroporation. Muscle Nerve 2003 Feb; 27(2): 237–41\nFerrer A, Foster H, Wells KE, et al. Long-term expression of full-length human dystrophin in transgenic mdx mice expressing internally deleted human dystrophins. Gene Ther 2004 Jun; 11(11): 884–93\nLefesvre P, Attema J, van Bekkum D. A comparison of efficacy and toxicity between electroporation and adenoviral gene transfer. BMC Mol Biol 2002 Aug 13; 3: 19\nSchertzer JD, Plant DR, Lynch GS. Optimizing plasmid-based gene transfer for investigating skeletal muscle structure and function. Mol Ther 2006 Apr; 13(4): 795–803\nMolnar MJ, Gilbert R, Lu Y, et al. Factors influencing the efficacy, longevity, and safety of electroporation-assisted plasmid-based gene transfer into mouse muscles. Mol Ther 2004 Sep; 10(3): 447–55\nMennuni C, Calvaruso F, Zampaglione I, et al. 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J Clin Invest 1999 Aug; 104(4): 375–81\nWagner KR, Hamed S, Hadley DW, et al. Gentamicin treatment of Duchenne and Becker muscular dystrophy due to nonsense mutations. Ann Neurol 2001 Jun; 49(6): 706–11\nWelch EM, Barton ER, Zhuo J, et al. PTC124 targets genetic disorders caused by nonsense mutations. Nature 2007 May 3; 447(7140): 87–91\nHirawat S, Welch EM, Elfring GL, et al. Safety, tolerability, and pharmacokinetics of PTC124, a nonaminoglycoside nonsense mutation suppressor, following single- and multiple-dose administration to healthy male and female adult volunteers. J Clin Pharmacol 2007 Apr; 47(4): 430–44\nSafety and efficacy study of PTC124 in Duchenne muscular dystrophy. Trial identifier: NCT00264888 [online]. Available from URL: http:\u002F\u002Fclinicaltrials.gov\u002Fct2\u002Fshow\u002FNCT00264888 [Accessed 2008 Feb 28]",{"VOID":2457},"10.1007\u002FBF03256275","2024-05-12T05:11:54.913+00:00","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002FBF03256275",[2461,2476],{"id":2462,"sortIndex":21,"researcher":20,"roles":2463,"affiliations":2464,"properties":2473,"displayName":2475,"givenName":20,"familyName":20},"f79e7cbe-ebdc-46a2-ad6e-0abdb4f77eef",[201],[2465],{"id":2466,"sortIndex":21,"affiliation":2467,"properties":20},"ade66dab-2156-47af-9e12-366f88d66a81",{"id":2466,"createTime":20,"updateTime":20,"relativeEntities":2468,"slug":20,"properties":2469,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":2472,"statistic":20},[],{"title":2470},{"VI":2471},"Regenerative Medicine Program, Ottawa Health Research Institute, Ottawa, Canada",[],{"title":2474},{"VI":2475},"Anthony Scimè",{"id":2477,"sortIndex":213,"researcher":20,"roles":2478,"affiliations":2479,"properties":2494,"displayName":2496,"givenName":20,"familyName":20},"6491d2bf-c8f8-489f-b3a7-77e59c59ee49",[201],[2480,2486],{"id":2466,"sortIndex":21,"affiliation":2481,"properties":20},{"id":2466,"createTime":20,"updateTime":20,"relativeEntities":2482,"slug":20,"properties":2483,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":2485,"statistic":20},[],{"title":2484},{"VI":2471},[],{"id":2487,"sortIndex":21,"affiliation":2488,"properties":20},"dc870182-fc98-45d4-b4e2-9b97bf209a6b",{"id":2487,"createTime":20,"updateTime":20,"relativeEntities":2489,"slug":20,"properties":2490,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":2493,"statistic":20},[],{"title":2491},{"VI":2492},"Department of Cellular and Molecular Biology, Faculty of Medicine, University of Ottawa, Ottawa, Canada",[],{"title":2495,"gsAuthor":2497},{"VI":2496},"Michael A. 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A vast number of disease-related targets have been used to identify agonistic, antagonistic, or inhibitory aptamers, or aptamer-based targeting ligands. However, only a few aptamers have reached late-stage clinical trials so far and the commercial infrastructure is still far behind that of other therapeutic agents such as monoclonal antibodies. The desirable properties of aptamers such as selectivity, chemical flexibility, or cost-efficiency are faced by challenges, including a short half-life in vivo, immunogenicity, and entrapment in cellular organelles. Aptamer research is still in an early stage, and a deeper understanding of their structure, target interactions, and pharmacokinetics is necessary to catch up to the clinical market. In this review, we will discuss the benefits and limitations in the development of therapeutic aptamers, as well as the advances and future directions of aptamer research. The progress towards effective therapies seems to be slow, but it has not stopped and the best is yet to come.",{"EN":2566},"Aptamers as Therapeutic Agents: Has the Initial Euphoria Subsided?",{"VOID":2568},"[\"8889174680691138990\"]",{"VOID":2570},"10.1007\u002Fs40291-019-00400-6","2024-05-03T12:30:45.056+00:00","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs40291-019-00400-6",[2574,2589],{"id":2575,"sortIndex":21,"researcher":20,"roles":2576,"affiliations":2577,"properties":2586,"displayName":2588,"givenName":20,"familyName":20},"90582830-7f53-47a9-9e72-402145f0cddf",[201],[2578],{"id":2579,"sortIndex":21,"affiliation":2580,"properties":20},"b3932f1a-495d-4e89-a77f-85f928b77463",{"id":2579,"createTime":20,"updateTime":20,"relativeEntities":2581,"slug":20,"properties":2582,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":2585,"statistic":20},[],{"title":2583},{"VI":2584},"Chemical Biology and Chemical Genetics, Life and Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany",[],{"title":2587},{"VI":2588},"S. 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Clin Cancer Res. 2013;19(5):1054–62. https:\u002F\u002Fdoi.org\u002F10.1158\u002F1078-0432.CCR-12-2067.","https:\u002F\u002Fdoi.org\u002F10.1158\u002F1078-0432.ccr-12-2067",{"mag":2695,"openalex":2696,"pm":2697,"doi":2698},"2115596815","W2115596815","23460536","10.1158\u002F1078-0432.ccr-12-2067",{"id":2700,"text":2701,"url":2702,"identifiers":2703},"9d6777c6-4c35-4b2e-9279-24289f8aa1ae","Zhou J, Rossi JJ. Cell-type-specific, aptamer-functionalized agents for targeted disease therapy. Mol Ther Nucleic Acids. 2014;3:e169. https:\u002F\u002Fdoi.org\u002F10.1038\u002Fmtna.2014.21.","https:\u002F\u002Flinkinghub.elsevier.com\u002Fretrieve\u002Fpii\u002FS2162253116303092",{"doi":2704},"10.1038\u002Fmtna.2014.21",{"id":2706,"text":2707,"url":2708,"identifiers":2709},"c4779705-a8d6-425e-82c7-964b0b601a3a","Keefe AD, Pai S, Ellington A. Aptamers as therapeutics. Nat Rev Drug Discov. 2010;9(7):537–50. https:\u002F\u002Fdoi.org\u002F10.1038\u002Fnrd3141.","https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fnrd3141",{"doi":2710},"10.1038\u002Fnrd3141",{"id":2712,"text":2713,"url":2714,"identifiers":2715},"1c684146-d995-491e-bb9a-e0c055c64733","Bock LC, Griffin LC, Latham JA, Vermaas EH, Toole JJ. Selection of single-stranded DNA molecules that bind and inhibit human thrombin. Nature. 1992;355(6360):564–6. https:\u002F\u002Fdoi.org\u002F10.1038\u002F355564a0.","https:\u002F\u002Fwww.nature.com\u002Farticles\u002F355564a0",{"doi":2716},"10.1038\u002F355564a0",{"id":713,"text":2718,"url":715,"identifiers":2719},"Kubik MF, Stephens AW, Schneider D, Marlar RA, Tasset D. High-affinity RNA ligands to human alpha-thrombin. Nucleic Acids Res. 1994;22(13):2619–26.",{"doi":717},{"id":2721,"text":2722,"url":2723,"identifiers":2724},"526d7201-dc5a-4e09-bf7b-6d7bbf10dd4b","Bompiani KM, Monroe DM, Church FC, Sullenger BA. A high affinity, antidote-controllable prothrombin and thrombin-binding RNA aptamer inhibits thrombin generation and thrombin activity. J Thromb Haemost. 2012;10(5):870–80. https:\u002F\u002Fdoi.org\u002F10.1111\u002Fj.1538-7836.2012.04679.x.","https:\u002F\u002Flinkinghub.elsevier.com\u002Fretrieve\u002Fpii\u002FS153878362206264X",{"doi":2725},"10.1111\u002Fj.1538-7836.2012.04679.x",{"id":2727,"text":2728,"url":2729,"identifiers":2730},"8f32b24e-0ca6-48bc-89ee-0984d45689be","Tasset DM, Kubik MF, Steiner W. Oligonucleotide inhibitors of human thrombin that bind distinct epitopes. J Mol Biol. 1997;272(5):688–98. https:\u002F\u002Fdoi.org\u002F10.1006\u002Fjmbi.1997.1275.","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS0022283697912754",{"doi":2731},"10.1006\u002Fjmbi.1997.1275",{"id":2733,"text":2734,"url":2735,"identifiers":2736},"963d64a0-0711-40af-bc4f-5282f81ab5b4","White R, Rusconi C, Scardino E, Wolberg A, Lawson J, Hoffman M, et al. Generation of species cross-reactive aptamers using “toggle” SELEX. Mol Ther. 2001;4(6):567–73. https:\u002F\u002Fdoi.org\u002F10.1006\u002Fmthe.2001.0495.","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS1525001601904952",{"doi":2737},"10.1006\u002Fmthe.2001.0495",{"id":2739,"text":2740,"url":2741,"identifiers":2742},"4bd6d1b6-c5a8-4035-8de1-681c838241f1","Pagratis NC, Bell C, Chang YF, Jennings S, Fitzwater T, Jellinek D, et al. Potent 2’-amino-, and 2’-fluoro-2’-deoxyribonucleotide RNA inhibitors of keratinocyte growth factor. Nat Biotechnol. 1997;15(1):68–73. https:\u002F\u002Fdoi.org\u002F10.1038\u002Fnbt0197-68.","https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fnbt0197-68",{"doi":2743},"10.1038\u002Fnbt0197-68",{"id":713,"text":2745,"url":715,"identifiers":2746},"Binkley J, Allen P, Brown DM, Green L, Tuerk C, Gold L. RNA ligands to human nerve growth factor. 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