中国医科大学学报  2026, Vol. 55 Issue (3): 193-197

文章信息

卑佳怡, 陈波
BEI Jiayi, CHEN Bo
基于新一代测序技术的乳腺癌精准诊疗策略与耐药机制研究
Precision medicine and drug resistance mechanisms in breast cancer based on next-generation sequencing
中国医科大学学报, 2026, 55(3): 193-197
Journal of China Medical University, 2026, 55(3): 193-197

文章历史

收稿日期:2025-09-09
网络出版时间:2026-03-24 12:00:43
基于新一代测序技术的乳腺癌精准诊疗策略与耐药机制研究
卑佳怡 , 陈波     
中国医科大学附属第一医院乳腺外科, 沈阳 110001
摘要:乳腺癌是全球女性最常见和致死率最高的恶性肿瘤。治疗耐药是乳腺癌临床管理失败的主要原因,其机制涉及药物靶点改变、DNA损伤修复、表观遗传调控、药物外排及细胞死亡抑制等多种途径。新一代测序技术(NGS)通过全面基因组分析(CGP),在揭示耐药机制和指导精准干预方面发挥核心作用。该技术已广泛应用于晚期、复发或耐药患者,并可动态监测克隆演化。尽管NGS显著提升了耐药管理的精确性,仍面临低频突变检测、异质性解析和液体活检标准化等挑战。未来,整合单细胞多组学与人工智能预测模型有望推进个体化治疗。本研究系统总结了基于NGS的乳腺癌耐药机制,旨在构建跨尺度调控网络,为开发逆转耐药策略提供理论依据。
关键词乳腺癌    新一代测序    全面基因组分析    耐药    精准诊疗    
Precision medicine and drug resistance mechanisms in breast cancer based on next-generation sequencing
BEI Jiayi , CHEN Bo     
Department of Breast Surgery, The First Hospital of China Medical University, Shenyang 110001, China
Abstract: Breast cancer remains the most common malignancy and the leading cause of cancer-related mortality among women worldwide. Therapeutic resistance is a major contributor to failure in clinical management of breast cancer, driven by diverse mechanisms including alterations in drug targets, DNA damage repair, epigenetic modulation, drug efflux, and inhibition of cell death. Next-generation sequencing (NGS) plays a central role in elucidating these resistance mechanisms and guiding precision interventions through comprehensive genomic profiling (CGP). This technology has been widely used for molecular analysis in patients with advanced, recurrent, or treatment-resistant cancer, enabling dynamic monitoring of clonal evolution. Although NGS has significantly improved the detection and characterization of treatment resistance, challenges remain, including the detection of low-frequency mutations, interpretation of heterogeneity, and standardization of liquid biopsy. The integration of single-cell multi-omics and artificial intelligence-based predictive models has the potential to substantially improve personalized therapy. This review systematically summarizes recent advances in NGS-based research on drug resistance mechanisms in breast cancer, with the goal of constructing multi-scale regulatory networks and providing a theoretical foundation for developing strategies against resistance.

乳腺癌的发病率和死亡率均居女性恶性肿瘤首位,治疗耐药是乳腺癌临床治疗失败的主要原因。突变的积累是所有肿瘤发生和发展的基础。在乳腺癌中,驱动性基因变异尤为常见,涉及多个关键基因,如ERBB2HER2)、FGFR1PIK3CACCND1,这些变异可通过持续激活信号通路促进肿瘤进展,并具有预测临床结局和指导靶向治疗的潜力[1]。然而,并非所有驱动突变都导致耐药,耐药突变也不限于驱动基因[2]。驱动突变使蛋白获得配体非依赖性激活能力,而耐药突变则通过改变蛋白构象使药物失效。随着肿瘤发生及进展相关遗传机制的阐明,个体化治疗的舞台已然搭建[3]。实施精准诊疗需依据患者肿瘤的遗传特征进行分类,因此在乳腺癌的临床评估中,明确关键基因突变状态至关重要。

乳腺癌的传统DNA测序方法(如BRCA1/2基因检测[4]ESR1评估[5])虽具较高敏感性,但其检测范围通常局限于已知突变热点区域。全面基因组分析(comprehensive genomic profiling,CGP)基于新一代测序(next-generation sequencing,NGS)技术,可一次性检测数百个肿瘤基因中的多种变异类型,已成为实现肿瘤精准诊疗的核心工具,目前广泛应用于晚期、复发或耐药乳腺癌患者的分子诊断[6]。CGP能够识别多种临床可靶向的基因组改变,实现对肿瘤的分子分型并预测治疗敏感性,这些改变常无法通过免疫组织化学(immunohistochemistry,IHC)或热点突变检测发现。本研究基于NGS的乳腺癌精准诊疗策略和耐药机制进行系统阐述,旨在为制定逆转耐药策略提供依据。

1 DNA和RNA测序技术的发展

既往研究[7]集中在基于特定分子特征选择靶向治疗策略。目前,临床常用PCR、Sanger测序、FISH及IHC等技术检测有限数量的肿瘤生物标志物。然而,这些方法在可扩展性和样本量方面存在限制,难以系统地分析乳腺癌原发灶及耐药复发过程中涉及的数百个肿瘤基因变异。

NGS以大规模并行的方式同时对大量DNA片段进行测序,实现了极高的通量与更低的单碱基测序成本。目前NGS技术仍处于快速迭代中,可大致划分为4个发展阶段。第二代测序(如Illumina系列)基于合成测序原理,适用于短读长、高通量应用[8]。第三代测序(如PacBio SMRT)支持长读长,有利于结构变异和复杂基因区域的解析,但错误率相对较高[9]。第四代测序(如纳米孔测序)进一步实现了超长读长和实时测序,在科研和临床应用中显示出潜力[10]

2 NGS技术在临床乳腺癌诊疗中的精准干预 2.1 指导个体化治疗决策

2.1.1 内分泌治疗

在原发性乳腺癌组织中采用IHC检测雌激素受体(estrogen receptor,ER)表达状态,可指导临床中多种内分泌治疗方案的选择。既可用于乳腺癌的预防性干预,也可有效控制ER阳性复发/转移性乳腺癌的疾病进展[11]。现有研究[12]表明,AKT1AKT2BCAR1BCAR3EGFRERBB2等基因的mRNA表达水平变化可作为预测内分泌治疗耐药性的分子标志。

NGS可用于检测循环肿瘤DNA(circulating tumorDNA,ctDNA)中的ESR1突变,随机Ⅲ期EMERALD试验(NCT03778931)中,采用Guardant360 CDx NGS检测方法,能够全面分析55个肿瘤相关基因的变异情况,涵盖ESR1基因310~547密码子之间的可操作突变,能评估超过90.0%的ESR1敏感突变[13]。临床前及临床数据表明,携带此类突变的肿瘤相较于传统内分泌单药治疗,对新型ER抑制剂(特别是选择性ER降解剂SERDs和选择性ER调节剂SERMs)表现出更强的治疗反应性[14]。此外,研究[15]显示,ERBB2基因突变(常伴随CDH1基因突变)在复发型小叶乳腺癌中的出现提示这些遗传变异可能参与调控此类典型ER阳性乳腺癌的内分泌治疗耐药进程。

2.1.2 化疗

运用CGP技术鉴定乳腺癌新辅助治疗、辅助治疗及转移性病变中对细胞毒性治疗反应相关突变的研究近年来刚刚起步。研究[16]表明,约35%的HER2扩增乳腺癌有TOP2A共扩增,HER2/TOP2A共扩增是蒽环类化疗获益的临床潜在预测标志物。尽管CGP结果与铂类药物敏感性及耐药性存在关联,基于深度测序技术选择化疗方案仍未在转移性乳腺癌中广泛应用。

2.1.3 HER2靶向治疗

NGS常用于为复发和转移性乳腺癌患者确定合适的靶向治疗。基于杂交捕获的CGP除了能检测到ERBB2基因扩增,还能识别非扩增激活突变,这类突变在乳腺癌中占2.4%。其典型代表为细胞外结构域S310F突变[17]。携带此类非扩增性ERBB2变异的肿瘤,由于缺乏FISH检测中的拷贝数增加、IHC染色中HER2蛋白过表达和(或)Oncotype Dx等检测中的ERBB2 mRNA过表达,初始会被归类为HER2阴性。伴随ERBB2扩增的ERBB2序列突变已被认为是HER2阳性患者的潜在获得性耐药机制[18]

2.2 监测耐药演变与疾病进展

近年来,基于NGS的研究[19]从时空维度揭示了乳腺癌基因组与转录异质性的动态演变。个体化突变谱可作为预测性生物标志物,指导针对关键靶向突变的精准治疗。包括新辅助治疗(neoadjuvant therapy,NAT)前后瘤内异质性(intratumoral heterogeneity,ITH)的动态变化以及通过连续采集的血液游离DNA(cell-free DNA,cfDNA)样本进行cfDNA-NGS [20]。cfDNA-NGS检测循环基因组特征(circulating genomic signatures,cGSs)为无创肿瘤监测提供了新途径。

除诊断潜力外,液体活检在连续时间点监测中展现出更重要价值。动态cfDNA-NGS可早于影像学预测继发性耐药与复发。有研究[21]报道动态cfDNA-NGS可提前11个月识别转移灶,ctDNA水平升高与不良生存结局显著相关,而特定突变(如HER2扩增、TP53及PI3K/mTOR通路突变等)已成为原发和继发耐药及无进展生存期短的生物标志物。GUAN等[22]开展的临床试验进一步表明,ctDNA拷贝数分析可指导转移性HER2阳性乳腺癌的后续治疗决策。

2.3 开发新型治疗策略

三阴性乳腺癌(triple-negative breast cancer,TNBC)具有高度分子和临床异质性,需通过全面分子分析来指导分层治疗[23]。NGS技术可高通量测序大基因组,促进TNBC新生标志物和治疗靶点的发现[24]。POP等[25]通过Ion Torrent测序发现TP53PIK3CAAKT1等基因的特定突变与患者不良预后相关。BALKO等[26]通过182个基因Panel检测新辅助化疗后TNBC样本,发现复发患者中存在PTEN缺失、JAK2突变、CDK6/CCND1-3扩增等可靶向变异,强调TNBC随访期常规开展分子监测,通过个体化辅助治疗改善预后。HEEKE等[27]对4 647例乳腺癌样本进行592个基因测序,发现约18%的TNBC存在同源重组修复相关基因突变,且该类肿瘤更易呈现高肿瘤突变负荷、PD-L1阳性等免疫治疗敏感特征。EL-BOTTY等[28]结合基因组与代谢组学分析发现,部分转移性ER+乳腺癌呈现氧化磷酸化依赖特征,其抑制剂IACS-010759在耐药模型中显著抑制肿瘤生长,提示OXPHOS可作为克服ER阳性患者内分泌耐药的新靶点。

在免疫治疗方面,HODA等[29]的研究显示PD-L1表达及CBFB突变分布与TNBC亚型及治疗响应相关;TAN等[30]基于ctDNA分析首次提出12基因标志物可预测免疫检查点抑制剂(immune checkpoint inhibitor,ICI)疗效;SIVAPIRAGASAM等[31]则发现TNBC具有最高的免疫治疗响应潜力,并提示STK11/MDM2突变可能与耐药相关。

3 基于NGS技术的乳腺癌耐药机制 3.1 内分泌治疗耐药

乳腺癌内分泌治疗耐药的核心机制在于ESR1基因获得性突变,同时伴随PIK3CA/AKT/mTOR等下游信号通路的异常激活。ESR1配体结合域突变可导致ER配体非依赖性活化,引起对芳香化酶抑制剂的耐药,对他莫昔芬和氟维司群的敏感性降低[32]。在接受氟维司群治疗且已有ESR1激活突变的患者中新发现的F404位点的突变可导致对氟维司群的显著耐药,部分新型SERDs可能有效克服此类耐药[33]。此外,PI3K/AKT/mTOR信号通路的异常激活,提供替代生存信号,亦与内分泌耐药密切相关[34]TP53突变也被发现与他莫昔芬及芳香化酶抑制剂的原发耐药相关[35]

表观遗传调控同样在耐药中发挥关键作用。基于单细胞RNA测序(single-cell RNA sequencing,scRNA-seq)和单细胞ATAC测序(single-cell ATAC sequencing,scATAC-seq)技术的研究[36]发现,他莫昔芬耐药与表观遗传调控导致的细胞类型异质性密切相关,其中关键基因BMP7通过调节MAPK信号通路在耐药中起关键作用。表观遗传机制与基因组演化协同作用,促进肿瘤细胞异质性,增加了耐药克隆的富集概率[37]。例如,PTEN启动子高甲基化及其表达降低与激素受体阳性早期乳腺癌患者接受他莫昔芬辅助治疗后较差的无病生存期和总生存期相关[38]。此外,研究[39]发现,不同内分泌治疗可诱导药物特异性DNA甲基化重编程,基于此类变化构建的表观预测模型可实现治疗响应与预后的动态监测。

3.2 抗HER2治疗耐药

HER2治疗耐药的基因组学机制亦可通过NGS被检测。与此耐药现象相关的主要突变涉及PIK3CAMET基因[39],然而,临床数据对PI3KPTENHER2阳性乳腺癌中的作用尚无定论。研究[40]显示,PIK3CA突变或低PTEN与预后不良和耐药相关。也有研究[41]表明,PIK3CA突变和PTEN状态均与曲妥珠单抗的疾病反应和患者生存无关。

3.3 化疗耐药

乳腺癌化疗耐药的核心在于肿瘤异质性与克隆演化。YATES等[42]研究发现,新辅助化疗可引发动态克隆演化,且相当比例的患者携带可靶向的亚克隆改变。此外,单细胞NGS分析[43]进一步证实了基因组克隆在乳腺癌进程中的动态多样化演变,更深入的分析表明点突变是导致时空克隆演进和ITH的主要原因。相比之下,大的基因组改变如染色体重排和拷贝数变异,似乎在原发肿瘤中已经出现,并在疾病全程中保持稳定[44]。KIM等[45]发现新辅助化疗会导致不同患者克隆灭绝或持续存在,耐药表型被化学治疗适应性选择,在治疗前耐药基因已处于可进行转录重编程的状态,伴随着转录组的重编程,最终演化为完全耐药的表型。克隆消亡组的肿瘤细胞被完全清除,仅残留正常细胞类型;而克隆持续组则存在基因型和表型发生改变的残留肿瘤细胞。此外,这些表型还展现出与耐药相关的特征(如间充质信号转导以及生长因子的增强),从而促进肿瘤细胞的耐药性[46]。这些发现为改善乳腺癌化疗耐药提供了新思路。

4 临床转化与展望

利用CGP研究化疗耐药面临多重挑战,包括肿瘤的时空异质性、化疗机制的复杂性、预测模型的局限性、功能验证的必要性以及较高的成本。未来应着力开发基于CGP的预测模型,以便更精准地识别化疗敏感与耐药患者,从而指导个体化治疗决策;包括对敏感者考虑降阶梯治疗以减少毒性,对耐药者则避免无效化疗并转向靶向或免疫治疗等新策略。同时,可依托基因组标志物优化临床试验设计,提高新药研发效率;推动CGP应用于晚期乳腺癌至早期新辅助治疗疗效预测,进一步增强其临床价值与精准肿瘤学的实践意义。

NGS技术作为肿瘤精准医疗的核心工具之一,能够全面、高效地解析乳腺癌的基因组变异图谱,在揭示新辅助化疗耐药机制、连接基因组学发现与临床决策方面提供了关键支持。尽管其临床应用前景广阔,未来仍需通过深入的功能实验验证所发现基因变异的生物学与临床意义,以最终实现基于基因组学的个体化治疗,提升乳腺癌疗效。

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