靶向测序技术在临床中的运用
The Application of Targeted Sequencing Technology in Clinical Practice
DOI: 10.12677/acm.2024.1451482, PDF,   
作者: 刘金峰:赣南医科大学第一临床医学院,江西 赣州;钟一鸣:赣南医科大学第一附属医院心血管内科,江西 赣州
关键词: 靶向测序下一代测序精准医疗基因变异Targeted Sequencing Next-Generation Sequencing Precision Medicine Gene Mutation
摘要: 靶向测序技术在过去二十年得到迅猛发展,其在精准医疗领域已得到广泛的临床应用。本文详细讨论了靶向测序方法的技术方面,包括PCR富集、杂交捕获和选择性环化等,并深入分析了其在临床肿瘤学、产前筛查、遗传病、传染病和药物反应分析等方面的应用。此外,本文还着重指出了该领域面临的挑战和新兴趋势,如数据分析、成本效益和新靶向技术的发展。这篇文章提供了靶向测序技术在现代医学中的影响和潜力的详细概览。
Abstract: Targeted sequencing technology has experienced rapid development over the past two decades and has been widely applied in the field of precision medicine. This article discusses in detail the technical aspects of targeted sequencing methods, including PCR enrichment, hybrid capture, and selective circularization, and deeply analyzes their applications in clinical oncology, prenatal screening, genetic diseases, infectious diseases, and drug response analysis. Additionally, this paper highlights the challenges and emerging trends in this field, such as data analysis, cost-effectiveness, and the development of new targeted technologies, providing a comprehensive overview of the impact and potential of targeted sequencing in modern medicine.
文章引用:刘金峰, 钟一鸣. 靶向测序技术在临床中的运用[J]. 临床医学进展, 2024, 14(5): 713-719. https://doi.org/10.12677/acm.2024.1451482

参考文献

[1] Ashley, E.A. (2016) Towards Precision Medicine. Nature Reviews Genetics, 17, 507-522. [Google Scholar] [CrossRef] [PubMed]
[2] Berger, B. and Yu, Y.W. (2023) Navigating Bottlenecks and Trade-Offs in Genomic Data Analysis. Nature Reviews Genetics, 24, 235-250. [Google Scholar] [CrossRef] [PubMed]
[3] 常凯, 刘晨霞, 许宏宣, 等. 基因测序在精准医疗中的发展与应用概述[J]. 西南军医, 2021, 23(2): 146-148.
[4] Tong, H., Phan, N.V.T., Nguyen, T.T., et al. (2021) Review on Databases and Bioinformatic Approaches on Pharmacogenomics of Adverse Drug Reactions. Pharmacogenomics and Personalized Medicine, 14, 61-75. [Google Scholar] [CrossRef
[5] Zhao, M., Ma, J., Li, M., et al. (2021) Cytochrome P450 Enzymes and Drug Metabolism in Humans. International Journal of Molecular Sciences, 22, Article No. 12808. [Google Scholar] [CrossRef] [PubMed]
[6] Rehm, H.L. (2013) Disease-Targeted Sequencing: A Cornerstone in the Clinic. Nature Reviews Genetics, 14, 295-300. [Google Scholar] [CrossRef] [PubMed]
[7] Pei, X.M., Yeung, M.H.Y., Wong, A.N.N., et al. (2023) Targeted Sequencing Approach and Its Clinical Applications for the Molecular Diagnosis of Human Diseases. Cells, 12, Article No. 493. [Google Scholar] [CrossRef] [PubMed]
[8] Beadling, C., Neff, T.L., Heinrich, M.C., et al. (2013) Combining Highly Multiplexed PCR with Semiconductor-Based Sequencing for Rapid Cancer Genotyping. The Journal of Molecular Diagnostics, 15, 171-176. [Google Scholar] [CrossRef] [PubMed]
[9] Tewhey, R., Warner, J.B., Nakano, M., et al. (2009) Microdroplet-Based PCR Enrichment for Large-Scale Targeted Sequencing. Nature Biotechnology, 27, 1025-1031. [Google Scholar] [CrossRef] [PubMed]
[10] Hedges, D.J., Guettouche, T., Yang, S., et al. (2011) Comparison of Three Targeted Enrichment Strategies on the SOLiD Sequencing Platform. PLOS ONE, 6, E18595. [Google Scholar] [CrossRef] [PubMed]
[11] Albert, T.J., Molla, M.N., Muzny, D.M., et al. (2007) Direct Selection of Human Genomic Loci by Microarray Hybridization. Nature Methods, 4, 903-905. [Google Scholar] [CrossRef] [PubMed]
[12] Hodges, E., Xuan, Z., Balija, V., et al. (2007) Genome-Wide in Situ Exon Capture for Selective Resequencing. Nature Genetics, 39, 1522-1527. [Google Scholar] [CrossRef] [PubMed]
[13] Pruitt, K.D., Brown, G.R., Hiatt, S.M., et al. (2014) RefSeq: An Update on Mammalian Reference Sequences. Nucleic Acids Research, 42, D756-D763.
[14] Dahl, F., Stenberg, J., Fredriksson, S., et al. (2007) Multigene Amplification and Massively Parallel Sequencing for Cancer Mutation Discovery. Proceedings of the National Academy of Sciences of the United States of America, 104, 9387-9392. [Google Scholar] [CrossRef] [PubMed]
[15] Shen, P., Wang, W., Chi, A.K., et al. (2013) Multiplex Target Capture with Double-Stranded DNA Probes. Genome Medicine, 5, Article No. 50. [Google Scholar] [CrossRef] [PubMed]
[16] Hardenbol, P., Yu, F., Belmont, J., et al. (2005) Highly Multiplexed Molecular Inversion Probe Genotyping: Over 10,000 Targeted SNPs Genotyped in a Single Tube Assay. Genome Research, 15, 269-275. [Google Scholar] [CrossRef] [PubMed]
[17] Turner, E.H., Lee, C., Ng, S.B., et al. (2009) Massively Parallel Exon Capture and Library-Free Resequencing across 16 Genomes. Nature Methods, 6, 315-316. [Google Scholar] [CrossRef] [PubMed]
[18] Mamanova, L., Coffey, A.J., Scott, C.E., et al. (2010) Target-Enrichment Strategies for Next-Generation Sequencing. Nature Methods, 7, 111-118. [Google Scholar] [CrossRef] [PubMed]
[19] Frampton, G.M., Fichtenholtz, A., Otto, G.A., et al. (2013) Development and Validation of a Clinical Cancer Genomic Profiling Test Based on Massively Parallel DNA Sequencing. Nature Biotechnology, 31, 1023-1031. [Google Scholar] [CrossRef] [PubMed]
[20] Cheng, D.T., Mitchell, T.N., Zehir, A., et al. (2015) Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets (MSK-IMPACT): A Hybridization Capture-Based Next-Generation Sequencing Clinical Assay for Solid Tumor Molecular Oncology. The Journal of Molecular Diagnostics, 17, 251-264. [Google Scholar] [CrossRef] [PubMed]
[21] Shi, Z., Lopez, J., Kalliney, W., et al. (2022) Development and Evaluation of ActSeq: A Targeted Next-Generation Sequencing Panel for Clinical Oncology Use. PLOS ONE, 17, E0266914. [Google Scholar] [CrossRef] [PubMed]
[22] Xie, C., Zhong, L., Luo, J., et al. (2023) Identification of Mutation Gene Prognostic Biomarker in Multiple Myeloma Through Gene Panel Exome Sequencing and Transcriptome Analysis in Chinese Population. Computers in Biology and Medicine, 163, Article ID: 107224. [Google Scholar] [CrossRef] [PubMed]
[23] Yatabe, Y., Sunami, K., Goto, K., et al. (2020) Multiplex Gene-Panel Testing for Lung Cancer Patients. Pathology International, 70, 921-931. [Google Scholar] [CrossRef] [PubMed]
[24] 程亚楠, 于津浦. 肿瘤大基因包高通量测序在临床中的应用进展[J]. 中国肿瘤临床, 2019, 46(2): 94-98.
[25] Liu, L., Li, K., Fu, X., et al. (2016) A Forward Look at Noninvasive Prenatal Testing. Trends in Molecular Medicine, 22, 958-968. [Google Scholar] [CrossRef] [PubMed]
[26] Rafati, M., Mohamadhashem, F., Jalilian, K., et al. (2022) Identification of a Novel De Novo Variant in OTX2 in a Patient with Congenital Microphthalmia Using Targeted Next-Generation Sequencing Followed by Prenatal Diagnosis. Ophthalmic Genetics, 43, 262-267. [Google Scholar] [CrossRef] [PubMed]
[27] Zhang, J., Li, J., Saucier, J.B., et al. (2019) Non-Invasive Prenatal Sequencing for Multiple Mendelian Monogenic Disorders Using Circulating Cell-Free Fetal DNA. Nature Medicine, 25, 439-447.
[28] Mohan, P., Lemoine, J., Trotter, C., et al. (2022) Clinical Experience with Non-Invasive Prenatal Screening for Single-Gene Disorders. Ultrasound in Obstetrics & Gynecology, 59, 33-39. [Google Scholar] [CrossRef] [PubMed]
[29] Rather, R.A. and Saha, S.C. (2023) Reappraisal of Evolving Methods in Non-Invasive Prenatal Screening: Discovery, Biology and Clinical Utility. Heliyon, 9, e13923. [Google Scholar] [CrossRef] [PubMed]
[30] Yohe, S. and Thyagarajan, B. (2017) Review of Clinical Next-Generation Sequencing. Archives of Pathology & Laboratory Medicine, 141, 1544-1557. [Google Scholar] [CrossRef
[31] Kermode, W., De Santis, D., Truong, L., et al. (2022) A Novel Targeted Amplicon Next-Generation Sequencing Gene Panel for the Diagnosis of Common Variable Immunodeficiency Has a High Diagnostic Yield: Results from the Perth CVID Cohort Study. The Journal of Molecular Diagnostics, 24, 586-599. [Google Scholar] [CrossRef] [PubMed]
[32] Huang, X., Wu, D., Zhu, L., et al. (2022) Application of a Next-Generation Sequencing (NGS) Panel in Newborn Screening Efficiently Identifies Inborn Disorders of Neonates. Orphanet Journal of Rare Diseases, 17, Article No. 66. [Google Scholar] [CrossRef] [PubMed]
[33] Wang, H., Yang, H., Liu, Z., et al. (2020) Targeted Genetic Analysis in a Chinese Cohort of 208 Patients Related to Familial Hypercholesterolemia. Journal of Atherosclerosis and Thrombosis, 27, 1288-1298. [Google Scholar] [CrossRef] [PubMed]
[34] Leber, A.L., Everhart, K., Daly, J.A., et al. (2018) Multicenter Evaluation of BioFire FilmArray Respiratory Panel 2 for Detection of Viruses and Bacteria in Nasopharyngeal Swab Samples. Journal of Clinical Microbiology, 56, 1110-1128. [Google Scholar] [CrossRef
[35] Hernandez-Neuta, I., Magoulopoulou, A., Pineiro, F., et al. (2023) Highly Multiplexed Targeted Sequencing Strategy for Infectious Disease Surveillance. BMC Biotechnology, 23, Article No. 31. [Google Scholar] [CrossRef] [PubMed]
[36] Park, D.G., Ha, E.S., Kang, B., et al. (2023) Development and Evaluation of A Next-Generation Sequencing Panel for the Multiple Detection and Identification of Pathogens in Fermented Foods. Journal of Microbiology and Biotechnology, 33, 83-95. [Google Scholar] [CrossRef] [PubMed]
[37] Park, D.G., Kwon, J.G., Ha, E.S., et al. (2023) Novel Next Generation Sequencing Panel Method for the Multiple Detection and Identification of Foodborne Pathogens in Agricultural Wastewater. Frontiers in Microbiology, 14, Article ID: 1179934. [Google Scholar] [CrossRef] [PubMed]
[38] Gordon, A.S., Fulton, R.S., Qin, X., et al. (2016) PGRNseq: A Targeted Capture Sequencing Panel for Pharmacogenetic Research and Implementation. Pharmacogenet Genomics, 26, 161-168. [Google Scholar] [CrossRef
[39] Lee, S.B., Shin, J.Y., Kwon, N.J., et al. (2022) ClinPharmSeq: A Targeted Sequencing Panel for Clinical Pharmacogenetics Implementation. PLOS ONE, 17, e0272129. [Google Scholar] [CrossRef] [PubMed]
[40] Fukunaga, K., Momozawa, Y. and Mushiroda, T. (2021) Update on Next Generation Sequencing of Pharmacokinetics-Related Genes: Development of the PKseq Panel, a Platform for Amplicon Sequencing of Drug-Metabolizing Enzyme and Drug Transporter Genes. Drug Metabolism and Pharmacokinetics, 37, Article ID: 100370. [Google Scholar] [CrossRef] [PubMed]
[41] Wu, S.H., Xiao, Y.X., Hsiao, H.C., et al. (2022) Development and Assessment of a Novel Whole-Gene-Based Targeted Next-Generation Sequencing Assay for Detecting the Susceptibility of Mycobacterium Tuberculosis to 14 Drugs. Microbiology Spectrum, 10, e0260522. [Google Scholar] [CrossRef] [PubMed]
[42] Yu, L. (2023) Artificial Intelligence in Molecular Medicine. The New England Journal of Medicine, 389, 1251-1252. [Google Scholar] [CrossRef
[43] You, Y., Lai, X., Pan, Y., et al. (2022) Artificial Intelligence in Cancer Target Identification and Drug Discovery. Signal Transduction and Targeted Therapy, 7, Article No. 156. [Google Scholar] [CrossRef] [PubMed]
[44] Fusaro, M., Rosain, J., Grandin, V., et al. (2021) Improving the Diagnostic Efficiency of Primary Immunodeficiencies with Targeted Next-Generation Sequencing. Journal of Allergy and Clinical Immunology, 147, 734-737. [Google Scholar] [CrossRef] [PubMed]
[45] Lei, Y., Tang, R., Xu, J., et al. (2021) Applications of Single-Cell Sequencing in Cancer Research: Progress and Perspectives. Journal of Hematology & Oncology, 14, Article No. 91. [Google Scholar] [CrossRef] [PubMed]
[46] Langsiri, N., Worasilchai, N., Irinyi, L., et al. (2023) Targeted Sequencing Analysis Pipeline for Species Identification of Human Pathogenic Fungi Using Long-Read Nanopore Sequencing. IMA Fungus, 14, Article No. 18. [Google Scholar] [CrossRef] [PubMed]