Advances in Clinical Medicine
Vol. 11  No. 06 ( 2021 ), Article ID: 43178 , 9 pages
10.12677/ACM.2021.116389

二代测序在妇科肿瘤诊断及治疗中的应用

寻方方1,孟莹1,张萍2*

1山东第一医科大学,山东 济南

2青岛市市立医院,山东 青岛

收稿日期:2021年5月15日;录用日期:2021年6月1日;发布日期:2021年6月17日

摘要

妇科肿瘤的早期诊断和治疗,对女性的健康和生活质量有重要影响。基因检测是近年来肿瘤研究领域中发展最迅速的方向之一,对妇科肿瘤的发生、发展及预后具有重要意义。随着二代测序(也称为下一代测序)的出现,可以快速经济地对大量DNA进行同时测序,进而鉴定妇科肿瘤中的所有类型的突变,使个性化医学的实现变为可能。

关键词

二代测序,妇科肿瘤,肿瘤诊断,肿瘤治疗

Application of Second-Generation Sequencing in the Diagnosis and Treatment of Gynecological Tumors

Fangfang Xun1, Ying Meng1, Ping Zhang2*

1Shandong First Medical University, Jinan Shandong

2Qingdao Municipal Hospital, Qingdao Shandong

Received: May 15th, 2021; accepted: Jun. 1st, 2021; published: Jun. 17th, 2021

ABSTRACT

Early diagnosis and treatment of gynecological tumors have an important impact on women’s health and quality of life. Genetic testing is one of the fastest developing directions in the field of tumor research in recent years, and it is of great significance to the occurrence, development and prognosis of gynecological tumors. With the advent of next-generation sequencing (also called next-generation sequencing), large amounts of DNA can be sequenced quickly and economically at the same time to identify all types of mutations in gynecological tumors, making it possible to realize personalized medicine.

Keywords:Next-Generation Sequencing, Gynecological Tumors, Tumor Diagnosis, Tumor Treatment

Copyright © 2021 by author(s) and Hans Publishers Inc.

This work is licensed under the Creative Commons Attribution International License (CC BY 4.0).

http://creativecommons.org/licenses/by/4.0/

1. 二代测序

1.1. NGS技术进展

肿瘤从本质上是一种基因组疾病,人们需要付出巨大的努力来理解这种异质性疾病集合 [1]。从最开始对肿瘤基因和肿瘤抑制物的早期鉴定,到对最常见癌症的完整注释,最后到所谓的肿瘤基因组格局,测序技术的迅速发展一直在推动我们对肿瘤基因组认识的进步 [2]。而基因突变在肿瘤生物学中起着重要作用,对全部基因组进行测序意味着可在患者肿瘤进程中的多个关键点进行基因检测,从而为肿瘤治疗提供更多机会。

基因检测技术最早是由基于DNA和RNA微阵列以及基于毛细管的DNA测序的基因组表征实验和信息检测方法,即俗称的第一代测序(为了纪念英国生物学家Frederick Sanger而命名的Sanger法)。但一代测序只能用于短小DNA片段的测序,对于检测和诊断癌症基因组的改变存在一定困难。随着测序技术的发展,大规模并行的DNA测序方法,也称为“下一代测序(Next-generation sequencing, NGS)”开始盛行。NGS是将DNA剪切成较小的片段后进行测序,然后通过计算进行重新排序和分析,可以同时分析数百万个DNA片段 [3]。从而以经济高效的方式来鉴定易感基因的遗传变异,其中包括所有体细胞突变,如单核苷酸突变、插入和缺失 [4],拷贝数变异 [5] 和大的基因组序列重排 [6]。NGS的爆炸性进展和能够处理海量数据的计算分析使我们能够在科研和临床水平上全面分析癌症基因组概况,使整个人类基因组测序作为临床工具成为可能 [7]。

1.2. NGS主要测序方法

NGS主要测序方法包括:外显子组测序、RNA测序和全基因组测序。

1) 全外显子组测序(Whole exome sequencing, WES):ES就是利用计算机软件对蛋白质功能的预测,来检测基因组的序列和映射区域,可以几乎同时测试每个蛋白质编码基因 [8]。而遗传或获得性蛋白质编码变体代表了大多数致病性变体,占所有已知致病基因组变异的60%以上 [9] [10]。

2) RNA测序(RNA sequencing, RNA-Seq):又叫转录组测序,可以全面快速地获得特定细胞或组织在某一状态下几乎所有转录本的基因序列信息和表达信息,包括编码蛋白质的mRNA和各种非编码RNA。随着二代测序的发展,RNA-seq方法可用于研究RNA生物学的许多不同方面,包括单细胞基因表达,翻译和RNA结构 [11]。

3) 全基因组测序(Whole genome sequencing, WGS):WGS具有全面检测所有类型基因组变异的潜力。可以检测跨越人类基因组98%的非编码区中的体细胞突变,包括启动子、增强子、内含子和非编码RNA (包括microRNA)以及未注释区的突变 [12]。WGS的广泛使用首次允许在几乎整个基因组中检测不同类型的各种常见和罕见遗传变异,这促进了罕见疾病的研究和临床应用,并从根本上提高了我们对肿瘤潜在生物学模式的理解。并且,WGS最近提供了在临床中发现肿瘤特征和监测肿瘤进展的方法,从而能对相关治疗方式进行指导和评估 [13] [14]。

1.3. NGS临床应用

NGS通过促进针对癌症的基因组依赖性的靶向小分子和基于抗体的疗法的同步发展,推动了基因组测定法向癌症患者的临床应用的转变。除了可以进一步鉴定潜在的可用于治疗癌症的基因之外,根据临床样品中的体细胞突变综合特征,NGS还将对构成疾病的表型、预后、药物反应和化疗耐药性的遗传模式提出新的见解 [6]。此类数据可以通过预测癌症预后的能力,选择已知的对特定癌症基因亚型具有疗效的治疗方案,监测癌症患者对治疗的反应以及在治疗前鉴定出具有耐药性突变的罕见亚克隆来推动个性化的治疗决策 [6]。

2. NGS与妇科肿瘤

2.1. 子宫肌瘤

子宫肌瘤是女性最常见的肿瘤 [15],也称为子宫平滑肌瘤(Uterine leiomyoma, UL),从组织学上讲,肌瘤是良性肿瘤,是子宫平滑肌组织层的单克隆肿瘤。但是,UL是约25%患者中的主要生活质量问题的根源 [15],还是全世界子宫切除术的重要指征,严重影响了社会经济 [16]。约50%至70%的肌瘤中都发生体细胞突变,并且通过全外显子测序,已经确定突变基因介体复合物亚基12 (MED12) [17]。除此之外,外显子组测序研究尚未检测到在平滑肌瘤中反复突变的任何其他基因 [18] [19],这突显了MED12在子宫肌瘤中的独特作用。而Kim等人的研究表明,MED12与β-catenin在物理上和功能上相互作用,β-catenin是经典WNT信号传导的关键效应子,可以激活靶基因的转录 [20]。因此,可利用MED12研究UL治疗的新型治疗靶标,从而为UL进一步的个性化治疗提供有效策略。

2.2. 子宫颈上皮内瘤变

子宫颈上皮内瘤变(Cervical intraepithelial neoplasia, CIN)是与子宫颈浸润癌密切相关的一组子宫颈病变。子宫颈的人乳头瘤病毒(Human papilloma virus, HPV)感染是CIN形成和发展的重要危险因素。但是,只有相对较小比例的感染妇女会发展为高级别CIN或浸润性宫颈癌 [21]。虽然通过HPV检测和高级别CIN的治疗进行子宫颈癌筛查在预防宫颈癌方面最为成功,但是,当前对HPV筛查的准确性仍然很低 [22]。

随着测序技术的飞速发展,探索HPV表观基因组及其宿主相互作用的科学能力逐渐增强。而基于HPV基因组和表观基因组的新型分子检测使人们对疾病过程有更全面的了解,从而提高了子宫颈筛查程序的诊断准确性 [23]。NGS在检测多种HPV感染方面的灵敏度更高 [24],对于高危HPV阳性女性,NGS可能可以实现更好的分类。近期有研究表明,通过对血浆样品进行miRNA测序,以鉴定外泌体中差异表达的miRNA,从而找到可以准确预测不同级别子宫颈上皮内瘤变的miRNA,结果表明所鉴定的外泌体miR-30d-5p和let-7d-3p是用于子宫颈上皮内瘤变的非侵入性筛查的有价值诊断的生物标志物 [22]。

2.3. 卵巢癌

卵巢癌(Ovarian cancer, OC)是妇科肿瘤中致死率排名第二的癌症,在所有癌症中排名第七 [25]。最近的一项META分析显示,自1980年以来,OC的5年总体生存率几乎没有变化,III期或IV期OC患者的5年生存率低至25% [26] [27]。OC患者的预后取决于及时的诊断以及获得规范的手术和全身治疗的机会。但是当前并没有有效的筛查策略可以早期发现卵巢癌,绝大多数病例通常在出现远处转移时才被诊断出来,这极大地影响了OC患者的预后 [28],因此,卵巢癌迫切需要更灵敏的早期诊断和更有效的治疗策略。

液体活检可应用于癌症诊断和治疗的所有阶段,从而可以无创且实时地监测疾病的发展 [29]。外周循环游离DNA (cfDNA)是在血浆或血清液中以无细胞状态检测到的DNA,源自肿瘤的cfDNA,也称为循环肿瘤DNA (ctDNA)。因为所有肿瘤部位都会将ctDNA释放到血液中,所以ctDNA的检测比组织活检更全面,可以充分评估肿瘤的异质性 [30] [31]。而肿瘤特异性突变作为一种新型的癌症生物标志物,可以帮助我们从一组健康个体中识别出癌症患者 [30]。如今,由于NGS技术的迅速发展,ctDNA测序可实现比组织活检更高的敏感性,并可针对不同研究目的进行设计 [32]。

在最近的一项研究中,Pereira等人通过对22名卵巢癌患者进行WES和靶向测序来确定与OC相关的特定突变,并对患者治疗后可检测到的ctDNA结果进行分析,其可显著预测8名卵巢癌患者的存活率,这项研究表明ctDNA的测量在个性化医学中可能发挥作用 [33]。

表观遗传改变在癌症的发生和发展中起着重要的作用,而DNA甲基化异常(主要是启动子甲基化过高)是大多数癌症中的常见事件 [34]。对上皮性卵巢癌患者的cfDNA中SLIT2 [35],OPCML [36] 和RASSF2A [37] 启动子甲基化的研究表明,DNA甲基化的变化有可能作为早期诊断妇科恶性肿瘤的生物标志物 [38]。而NGS可以通过提供单核苷酸分辨率,分析更多的CpG位点 [38]。此外,NGS可以更详细地分析包含人类基因组内所有CpG中约一半的重复区域 [39]。

Flanagan等人通过焦磷酸测序研究了参与III期临床试验(NCT00003998, www.clinicaltrials.gov)的880名上皮性卵巢癌患者的DNA甲基化状态,并报道了SFN甲基化与无进展生存期(PFS)之间的显著相关性(p = 0.016) [40]。同一小组分析了先前临床试验中纳入的247名卵巢癌患者的血液DNA甲基化模式。他们确定了铂类化疗后复发时血液DNA中特定的CpGs改变,并发现其与生存率存在独立的显著关联(p = 2.8 × 10−4) [41]。

靶向疗法是一种新的治疗方法,该疗法通过特定方式靶向癌细胞来攻击癌细胞的致癌机制 [42]。贝伐单抗(BEV)是美国食品和药物管理局批准的首个用于治疗癌症患者的抗血管内皮生长因子(VEGF)药物。在第3次阶段临床试验中,BEV疗法已有效用于治疗和改善晚期转移性卵巢癌患者的PFS [43] [44]。PARP抑制剂Olaparib在一项3期临床试验中已显示出对铂敏感性复发性卵巢癌患者的治疗效果,并提供了显着的PFS改善 [45]。寻找与癌症治疗反应相关的特定生物标志物并对生物标志物的进行优先筛选可以更好地确定靶向化合物的正确组合,并获得最佳的治疗成功率 [42]。随着下一代测序技术和分子生物学技术的发展,我们能够识别出卵巢癌患者中更多的更具针对性的分子改变 [46]。从而得到更多个性化治疗的机会,改善卵巢癌患者的预后。

2.4. 子宫内膜癌

子宫内膜癌(Endometrial cancer, EC)是发达国家中最常见的妇科癌症,约占所有女性癌症的5% [47]。I期子宫内膜癌患者的5年生存率为75%~88%,III期为50%,IV期为15%。因此,对EC的早期诊断可以提高患者生存率 [48]。

在EC的分类方面,如今的组织学分类是根据肿瘤的形态和分级(基于腺体结构和核分级)来确定的 [49]。将分子分类纳入标准组织学分类方案中,有可能更精确地定义子宫内膜癌的各种亚型,并进一步指导分子诊断技术和靶向疗法的开发和使用 [49]。2013年,癌症基因组图谱(TCGA)研究网络报告了373例子宫内膜癌的大规模、全面和综合基因组分析,该研究通过对整个外显子组序列、转录组序列、基因组拷贝数、蛋白质阵列、微卫星稳定性测试和甲基化谱分析 [50],确定了具有不同临床、病理和分子特征的四类子宫内膜癌:POLE (超突变) (7%),微卫星不稳定性(MSI)/超突变(28%),拷贝数低/微卫星稳定(39%)和浆液样/拷贝数高(26%) [51]。这些分子分类不仅为了解各种类型的子宫内膜癌的分子决定因素提供了新的见解,还为在常规病理学实践中结合分子分类和组织病理学特征提供了途径 [50]。

POLE超突变亚组中尽管3级子宫内膜样肿瘤的比例很高,但超突变亚组的癌症,无论肿瘤的级别如何,都显示出良好的预后,没有复发 [51] [52]。MSI超突变源自DNA错配修复(MMR)系统的缺陷。根据拷贝数变化确定的两个不同的分子亚组:拷贝数(CN)低亚组和CN高亚组。CN低群也被称为微卫星稳定群,包含一半以上的低度子宫内膜样肿瘤。而一般来说,CN高亚组的肿瘤在四个分子亚组中的预后最差 [51] [53]。

通过下一代测序进行的DNA突变分析和甲基化状态评估,有望确定有效的预后和预测性生物标志物以改善治疗决策过程 [54]。

正在研究的曲妥珠单抗是一种针对HER2/Neu的人源化单克隆抗体,已被证明与复发性,转移性或进行性子宫浆液性癌的预后改善相关 [55] [56] [57]。Black等人通过WES测试了子宫浆液性癌(USC)细胞系的HER2/neu扩增和PIK3CA突变,并进行曲妥珠单抗的功效实验,结果表明致癌的PIK3CA突变在HER2/neu扩增的USC中很常见,并且可能构成了患者对曲妥珠单抗治疗耐药的主要机制 [58]。最近的一项多机构的前瞻性随机II期临床试验显示,在基于紫杉醇/卡铂的化疗中加入曲妥珠单抗可改善无进展生存期 [59]。

2.5. 宫颈癌

宫颈癌(Cervical cancer, CC)是全球第四大最常见的女性恶性肿瘤,它代表了全球主要的健康挑战 [60]。

在HPV检测方面,由于高危型人乳头瘤病毒(HPV)的持续感染是宫颈癌发生的必要条件。因此,近年来HPV检测已逐渐取代宫颈细胞学成为宫颈癌的主要筛查方法 [61]。但是,特异性差和相应的阳性预测值差限制了单独使用HPV检测作为主要筛查测试,而处于HPV潜伏感染期女性的HPV测试会显示阴性,导致HPV感染的漏检 [62]。

因此,我们迫切需要更准确的HPV检测方法。在宫颈癌中HPV的整合率高达76.3%,并且与宫颈上皮内瘤变(CIN)等级呈正相关 [63],所以HPV的整合可以用作早期诊断CC的一种手段。但是,能够可靠检测和定位HPV整合的检测方法的开发进展缓慢,在鉴定患者病毒–细胞连接方面遇到了技术挑战 [64]。通过与定制的HPV探针杂交并进行深度测序,创新的NGS分析可捕获所有含病毒分子来检测病毒细胞连接 [64],在HPV的早期诊断方面为我们提供了新途径。

NGS被证明是评估肿瘤细胞中拷贝数变化(CNA)的灵活而强大的方法 [65] [66],并且其基因表达水平和拷贝数之间呈正相关 [67]。研究发现宫颈细胞学样本的染色体CNA可以从无肿瘤或CIN组织中强有力地区分出浸润性癌症,因此,使用NGS技术进行细胞学涂片分子分析可能会成为将来宫颈癌筛查的一种非侵入性且有效的方法 [68]。

除了将HPV整合到宿主基因的人类基因组之外,在HPV诱导的癌变过程中宿主基因组的体细胞突变也是研究宫颈癌变的重要方面 [61]。使用NGS分析可以揭示已知和新颖的高频率突变,而这些DNA突变分析在识别癌组织和非癌组织之间的差异、指导诊断和确定治疗方案方面起着重要作用 [61]。癌症基因组图谱(TCGA)突变分析揭示了14种在宫颈癌中经常突变的基因 [69]。如SCC中EGFR拷贝数的增加表明患有这些肿瘤的女性可能会受益于抗EGFR抗体疗法,例如西妥昔单抗 [70]。这些研究表明,基因组测序将进一步检测引发EGFR治疗反应的预测性生物标志物,并加深我们对可在临床上利用的EGFR相关细胞功能障碍的认识 [71]。此外,针对PD-1-PD-L1轴的T细胞免疫检查点抑制剂如pembrolizumab被发现对PD-L1阳性复发或转移性宫颈鳞状细胞癌具有耐受性并很有前途 [72]。

3. 总结与展望

随着测序成本的持续降低和计算机资源的扩展,用于肿瘤基因组研究和临床应用的NGS分析将变得越来越强大。但是,考虑到妇科肿瘤基因组和表型的多样性,还需要分析更多的NGS数据去解释来自妇科肿瘤的突变。

近年来,我们见证了基因组测序和分析技术的历史性进步,这些成就使创建更大、更丰富的数据集,以及追求更具创造性的分析成为可能。当前,NGS研究要实现其在妇科肿瘤中的全部潜能需要克服的关键挑战,是去建立个性化的基因筛查和全面的临床应用,这是NGS迈向个性化医学的重要一步。

文章引用

寻方方,孟 莹,张 萍. 二代测序在妇科肿瘤诊断及治疗中的应用
Application of Second-Generation Sequencing in the Diagnosis and Treatment of Gynecological Tumors[J]. 临床医学进展, 2021, 11(06): 2689-2697. https://doi.org/10.12677/ACM.2021.116389

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  73. NOTES

    *通讯作者。

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