2023, Vol. 50
2. 复旦大学附属华山医院血液科 上海 200040
2. Department of Hematology, Huashan Hospital, Fudan University, Shanghai 200040, China
在世界范围内，上皮性卵巢癌(epithelial ovarian cancer，EOC)是女性第八大常见恶性肿瘤[1]，同时也是最为致命的妇科恶性肿瘤。EOC是一组异质性很高的疾病，具有不同类型的组织学、分子和微环境特征；其中卵巢高级别浆液性癌(high-grade serous ovarian cancer，HGSOC)是一种具有侵袭性特征的常见亚型，约占EOC的70%[2]。由于卵巢特殊的解剖学位置，疾病早期症状隐匿，高达70%的患者在诊断时已处于盆腹腔播散状态(Ⅲ/Ⅳ期)。全面分期手术和辅助化疗是HGSOC的标准治疗方式。然而，约70%的患者会在术后2年内复发，最终多因继发性耐药而不治。近年来，得益于遗传性乳腺癌基因1/2(breast cancer 1/2，BRCA1/2)检测的开展及多聚ADP核糖聚合酶(poly-ADP-ribose polymerase，PARP)抑制剂的应用，HGSOC中携带BRCA1/2突变患者的预后已显著改善，SOLO系列研究[3-4]、NOVA研究[5]和ARIEL3研究[6]表明PARP抑制剂可被推荐作为此类患者的一线或长线维持治疗。随着对药物作用机制的深入了解，更多同源重组修复(homologous recombination repair，HRR)相关基因的检测也被纳入到HGSOC的指导治疗中，根据同源重组(homologous recombination，HR)状态区分靶向治疗疗效在上述研究中均有体现。PARP抑制剂的应用作为精准医学在指导HGSOC分型治疗上的一个典型案例，已历经十余年之久；当下，精准医学在HGSOC中的应用则充满着机遇与挑战：以二代测序(next generation sequencing，NGS)为代表的高通量方法已被广泛应用于临床[7]，推动着液体活检等技术的完善与革新[8]；更深层次的单细胞及空间转录组测序技术正在研究机构大规模开展，助力HGSOC瘤内异质性、时空密码和微环境特征等探究[9-10]；HGSOC特征性的糖蛋白及功能蛋白组学也着力探寻着新的治疗靶点[11-12]。然而，HGSOC的复发与耐药却尚未因此而终止，解决棘手的铂耐药与新出现的靶向耐药，如何使患者保持长期缓解和实现个体化治疗仍是精准医学所要面对的难题。本文结合高通量测序等技术的发展，就精准医学在HGSOC中的应用进展做简要综述。
精准医学在HGSOC的病理诊断与分子分型中的应用 在2014年WHO发布的女性生殖器官肿瘤分类指南中，采纳了Kurman提出的二分法模型，将原本含有5个亚型的EOC简化为Ⅰ、Ⅱ两个亚型[13-14]。HGSOC归属于Ⅱ型EOC，较Ⅰ型具有更强的侵袭性，肿瘤进展迅速，发现时常广泛转移，整体预后不良。在基因组方面，Ⅱ型EOC也存在其特殊性：p53突变与基因组存在不稳定性，常伴随DNA修复途径缺陷[15]。
HGSOC的传统病理 在组织病理上，HGSOC在常规HE染色下呈现为实体细胞团，具有典型的狭缝状腺样结构。肿瘤细胞实性生长区域常伴有广泛坏死；在一些特定区域，可见乳头、腺样及筛状结构，类似于输卵管表面上皮。在某些情况下，HGSOC可表现为近似子宫内膜样细胞或移行细胞的实性生长方式，可辅以免疫组化进行鉴别[13-14]。最近，也有研究者提出将这组具有特殊形态结构的HGSOC命名为“SET亚型”(“Solid，pseudo-Endometrioid and/or Transition cell carcinoma-like”)；基于BRCA状态检测的研究提示，与典型的HGSOC相比，SET组肿瘤常与BRCA1突变相关，且瘤内含有更高比例的肿瘤浸润淋巴细胞(tumor-infiltrating lymphocytes，TILs)[16]。在细胞学上，HGSOC存在高度核异型，核大、深染、多形或多核，核分裂相多见；核仁大而明显，呈嗜酸性；常可见沙砾体，是典型的与乳头状肿瘤相关的钙化区[14]。
基于免疫组化的分子病理 免疫组化标记可用于区分HGSOC与其他EOC亚型。与低级别浆液性腺癌不同，约96%的HGSOC存在p53突变。在这些突变中，80%以上的病例表现为由错义突变引起的弥漫强阳性(核)，尚可见由无义突变引起的阴性表达、少见突变相关的胞浆强阳性；对比基因测序，甚至可出现免疫组化下表达正常的p53截短突变[17]。其他HGSOC常见的免疫组化表达模式还包括肾母细胞瘤1蛋白(Wilms tumor 1，WT1)和p16蛋白阳性表达、Ki-67中-高度表达、细胞角蛋白7(cell keratin 7，CK7)阳性表达等[13, 18]。基于“输卵管起源学说”，双链复合蛋白8(paired box 8，PAX8)在HGSOC也常阳性表达[19-20]。此外，约有80%的HGSOC病例可有雌激素受体的阳性表达，孕激素受体的阳性表达则相对少见(30%)。
基于高通量测序的分子病理 在精准医学模式的指导下，高通量测序技术广泛应用于临床，为开展更为精准的HGSOC分子病理诊断铺平了道路[7]。早在2011年，癌症基因组图谱(The Cancer Genome Atlas，TCGA)研究团队通过对489个卵巢癌肿瘤样本进行基因组和转录组测序分析，绘制出了全球最大规模的HGSOC分子特征图谱，为其分子病理学研究奠定了深厚的基础[21]。在这项研究中，p53突变被定义为HGSOC核心分子病理学特征；BRCA1/2的胚系与体细胞突变在该队列中累积占比22%，是HGSOC第二大常见突变。与队列中其他亚型的EOC相比，基因组不稳定性也是HGSOC的典型特征：几乎每个HGSOC肿瘤样本中都存在大量的拷贝数变异，约50%存在HR方面的基因组和/或表观遗传缺陷。其他常见突变涉及视网膜母细胞瘤1(retinoblastoma 1，RB1)、磷脂酰肌醇-3-激酶/鼠肉瘤病毒癌基因同源物(phosphatidylinositol-3-kinase/rat sarcoma viral oncogene homolog，PI3K/RAS)、NOTCH和叉头盒转录因子M1(forkhead box M1，FOXM1)等[21]。
基于转录组测序的分子分型 全转录组测序在HGSOC精准分型也具有重要的应用价值，Tothill等[22]的一项标志性研究报道在转录组学的背景下，HGSOC可进一步被分为4个亚型：C1(间充质型)、C2(免疫反应型)、C3-4(分化型)和C5(增殖型)，在后续的研究中，不同亚组分别被赋予不同的预后意义及微环境特征。基于对2103例HGSOC全转录组谱数据的分析，Wang等[23]在“Tothill分型”基础上又重新定义了5个新的HGSOC亚组，即S1(间充质型)、S2(免疫反应型)、S3(增殖型)、S4(分化型)和S5(抗间充质型)。Sohn等[24]的研究主要参考了HR状态和上皮间质转化(epithelial-mesenchymal transition，EMT)指数，将HGSOC分为HRR活化型和间质型，后者常表现为更差的预后。不难发现在这些新定义的亚型中存在与“Tothill分型”相似成分，提示基于转录组的HGSOC分型具有相对的稳定性[25]。这些亚型所代表的特殊基因表达模式不仅对HGSOC异质的生物学特性提出了新见解，同时也为进一步分型治疗提供了新思路。
然而，要实现上述分型临床转化，可能还面临诸多问题，如在检测中，基质与免疫成分可能会掩盖肿瘤细胞特征性改变。优化的校正算法与新一代组学分析工具(如单细胞转录组学分析)正在被开发用于解决临床转化难题[26]。OVCARE团队采用先进的NanoString技术和改良的算法构建了一个名为“PrOTYPE”的HGSOC分型体系，该体系分型与年龄、分期、残余病灶、TILs状态和预后存在显著相关性，测试准确度高达95%以上[27]。这种全新的分子分型模式为实现精准医学在HGSOC中的应用提供了有力的证据。2022年美国妇科肿瘤学会年会上的一项口头报告指出，间充质分子亚型与CT评分高的患者具有高手术复杂度及肉眼可见的残留病灶倾向，亟需验证该模型在其他队列中的有效性。但同样留下了值得深思的问题：如何在术前开展精准的分子分型检测？明确分子分型是否有助于手术决定(手术与否)，甚至辅助化疗的敏感性及二次减瘤术的疗效预判？
精准医学在HGSOC预后评估中的应用 在分子病理的框架下，结合传统临床参数，对HGSOC患者进行精准的预后评估有助于指导个体化治疗；同时，这些特殊的分子病理标记常与肿瘤的某些生物学特性(如高度侵袭性、EMT、化疗耐药等)相关联，可作为潜在的治疗靶点。表 1列举了近年来可作为HGSOC预后评估典型的生物学标记。
| Author | Sample size (n) | Biological marker | Technique | Clinical significance |
| Chan，et al.[28] | 48 (Optimization) 528 (Training) 764 (Validation) |
CCNE1 | Tissue microarray；Chromogenic in situ hybridization；NanoString and digital PCR | CCNE1 high‐level amplification/overexpression identified patients with a poor prognosis，exclusive to BRCA1/2 mutations，as a negative predictive test to PARP inhibitors |
| Petersen，et al.[29] | 482 (Training) 110 (Validation) |
CCNE1 and BRD4co-amplification | Copy number amplification，reverse phase protein array，IHC tissue microarry | HGSOC with CCNE1 and BRD4 co-amplification were associated with declined OS，high protein expression of CCNE1 was associated with poor OS |
| Jin，et al.[31] | 118 | KIAA0101 | IHC tissue microarry | High expression was associated with declined OS and cisplatin resistant |
| Bu，et al.[32] | 210 | PRC1 | Tissue microarray | High expression was associated with declined survival rate and platinum resistance (first line)；exclusive to BRCA1/2 mutations |
| Communal，et al.[47] | 101 (Training) 1 158(Validation) |
Keratin7 E-cadherin |
Tissue microarray | High expression indicated improved OS and PFS；independent survival factor；chemotherapy response prediction in large cohorts |
| Hanker，et al.[33] | 612 | SPHK1 | IHC | High expression was associated with earlier FIGO stage and R0 cytoreduction，implying prolonged PFS and OS |
| Lu，et al.[34] | 136 (Training) 59 (Validation) |
ALG5 | Transcriptome sequencing | In patients with complete surgical resection，high ALG5 expression suggested increased risks of disease progression (stratified risk indicator for postoperative recurrence) |
| Kim，et al.[35] | 303 | BRCA status | BRCA status detection by NGS | In primary cytoreduction patients，BRCAm group had a higher rate of complete cytoreduction to no residual disease (0 mm) |
| Bischof，et al.[37] | 69 | p53 isotype | qRT-PCR p53sequencing |
Δ133p53 isotype was an independent protective factor for patients’ survival |
| Azzalini，et al.[48] | 103 | AKT3 | RT-droplet digital PCR (ddPCR) | High expression was associated with declined PFS and OS |
| Leonard，et al.[49] | 354 (PFS) 348 (OS) |
APOBEC3G | qRT-PCR | Low expression was associated with declined PFS and OS |
| Zhang，et al.[50] | 73 | ETV5 | qRT-PCR | High expression was associated with declined OS |
| Wang，et al.[51] | 103 | ENPP1 | IHC | High expression suggested an advanced FIGO stage and poor differentiation |
| Lee，et al.[38] | 187 | CD8/FoxP3 CD8/PD-L1 |
Multiplexed immunofluorescence staining | High ratio of CD8/FoxP3 or CD8/PD-L1 implied prolonged OS，high ratio of CD8/PD-L1 implied high sensitivity to chemotherapy |
| Paijens，et al.[39] | 268 | CD8 CD103 marked Tm | Multiplexed immunofluorescence staining | In primary cytoreduction patients，CD8+CD103+ Tm infiltration was associated with survival benefits |
| Henriksen，et al.[52] | 283 | CD8 CD57 PD-L1 |
IHC | High expression of these three markers indicated prolonged OS (CD57：a biomarker for NK cell) |
| de la Fuente， et al.[42] |
130 | PD-1/PD-L1 | IHC tissue microarray | High expression was associated with prolonged OS，macrophage was identified as the cluster expressing PD-1 |
| Darb-Esfahani， et al.[53] |
151 (PFS > 5 y) 77 (PFS < 3 y) |
CD3+CD8+ TILs and MHC2 | IHC | Long-term survivors had better immune infiltrating state and better antigen presenting ability |
| Bansal，et al.[54] | 100 | PD-L1/CD8 | IHC tissue microarray | The prognosis of PD-L1+/CD8+ group was significantly worse than that of PD-L1+/CD8- group |
| Zong，et al.[41] | 93 | VISTA | IHC | High expression was associated with prolonged OS，positively correlated with other immuno-suppressive molecules |
| Li，et al.[2] | 98 | ZEB2 | IHC | High expression was associated with declined PFS and OS |
| Matsumoto，et al.[55] | 99 | ALK | IHC | High expression was associated with declined PFS and OS |
| Baath，et al.[56] | 130 | MET | IHC tissue microarray | Positive MET expression suggested declined OS |
| Jin，et al.[57] | 110 | CXCL11 | IHC | High expression was associated with declined OS |
| 110 | HMGA2 | IHC | High expression was associated with declined OS | |
| Hojnik，et al.[58] | 99 | AKR1B1 | IHC | High expression suggested prolonged disease-free survival，an independent protective factor for survival |
| Trudel，et al.[59] | 112 | ADAM-10 | IHC | High expression suggested low progression risk |
| 112 | Complement factor Ⅰ |
IHC | High expression suggested high progression and death-related risk | |
| Gagné，et al.[60] | 106 | HtrA1 (nucleus) | IHC tissue microarray | Low expression suggested low progression and death-related risk |
化疗耐药相关预后标记 Chan等[28]采用多种检测方法(组织芯片法、显色原位杂交法、NanoString和数字PCR法)对小型队列(N=48)进行优化，并结合两种免疫组化方法在两个大型队列中进行训练与验证。最终，研究提示细胞周期蛋白E1(cyclin E1，CCNE1)高水平扩增合并过表达的患者死亡风险显著提高，且该扩增常与BRCA1/2生殖系突变互斥[28]。Petersen等[29]通过分析拷贝数扩增数据同样证实CCNE1高表达与HGSOC不良预后相关；此外，该研究还关注了溴结合域蛋白4(bromodomain containing 4，BRD4)的扩增状态，提出检测CCNE1与BRD4共扩增模式对患者预后评估可能更为有效。在2015年，发表于Nature的一项研究采用全基因组测序的方法绘制了HGSOC耐药患者的基因图谱[30]，其中CCNE1扩增在原发耐药和复发患者中常被检测到，提示CCNE1可能是一个HGSOC耐药相关基因。其他与化疗反应相关的预后分子也常引起关注，Jin等[31]报道PCNA相关因子(PCNA-associated factor，PCLAF/KIAA0101)在免疫组化中高表达提示患者顺铂耐药几率较高，且总生存期(overall survival，OS)缩短；Bu等[32]研究发现胞质分裂调节蛋白1(protein regulator of cytokinesis 1，PRC1)高表达有着和CCNE1扩增类似的效应，在缩短OS的同时与BRCA突变互斥。这种影响预后的基因互斥现象应在临床和实验室研究中引起高度关注。
手术疗效相关预后标记 基于分子病理的预后评估模式同样被应用于HGSOC手术疗效预测中。在一项纳入612例HGSOC的队列中，Hanker团队发现，鞘氨醇激酶1(sphingosine kinase 1，SPHK1)高表达与更早的FIGO分期和较高R0率相关，并提示无进展生存期(progression free survival，PFS)和OS延长[33]。Lu等[34]通过对公共数据库的挖掘发现天冬酰胺连接糖基化同源物5(asparagine-linked glycosylation homolog 5，ALG5)基因表达增加，提示HGSOC患者初次减瘤术后存在较高复发风险，后经其研究中心数据证实ALG5表达可作为HGSOC术后复发风险的分层指标。当然，在术后复发风险分层上，常规BRCA状态检测本就具有一定指导意义，Kim等[35]的研究证实在初次减瘤患者中，BRCA基因突变者R0率明显较BRCA野生型患者高，并提示存在较低复发风险；Morse等[36]基于BRCA基因检测的细胞学研究也得到一致结果，发现较低的肿瘤细胞核百分比(percentage of neoplastic nuclei，PNN)与较高的R0率及BRCA2突变相关联。而根据Bischof等[37]的报道，p53同种型检测在一定程度上也可对患者预后评估做出指导，在他们的研究中，Δ133p53亚型是术后OS改善的独立预后因素。然而，在这些涉及复发风险评估的研究中，需要考虑手术R0率可能会作为混杂因素影响分子病理对预后的判断。
免疫相关预后标记 免疫相关分子的检测已被视为肿瘤免疫状态评估的重要手段，这在肿瘤分子病理研究中也不例外。最近，多个等团队创新采用多通路复用免疫组化与定量分析的方法探究了HGSOC免疫微环境成分对其预后的影响，发现CD8与程序性死亡配体1(programmed death-ligand 1，PD-L1)比例增加与患者OS改善和化疗的有效性相关[38]；在初次减瘤患者中，CD8+CD103+记忆T细胞浸润增加与生存获益相关[39]。大量的免疫抑制分子如程序性死亡受体1(programmed death 1，PD-1)和含V结构域免疫球蛋白T细胞活化因子(V-domain Ig-containing suppressor of T cell activation，VISTA)等的表达则常与不良预后相关联[40-41]，提示在HGSOC微环境中，免疫细胞的浸润与状态确实可作为预后评估的重要指标。Martin等[42]研究发现，在HGSOC微环境中，TILs表达更高水平的PD-1与预后改善相关，并且提示与铂类敏感性之间存在显著正相关[42]。这种看似反常的现象已被多个研究团队证实[43-45]，其具体机制目前尚不明确。我们推测在HGSOC微环境内免疫抑制分子的表达很可能是一种“抗争”的遗迹，即免疫活化后的静息状态；在一定刺激条件下，这些TILs或可被再次唤醒并执行其抗肿瘤功能[46]；因此，存在高水平PD-1+ TILs的患者有希望从免疫治疗中获益，但仍需要开展完善的临床前研究以证实此观点。
最后，将这些临床定义的预后分子转化为实验室研究，分析其具体作用机制对理解HGSOC病情发展具有重要意义。以本课题组前期研究为例，最初我们发现在HGSOC患者中，免疫组化锌指E结合同源盒转录因子(zinc finger E-box binding homeobox 2，ZEB2)表达增高常提示预后不良，随后对患者腹水来源的肿瘤细胞进行流式分析，发现在一群CD133阳性的卵巢癌干细胞中ZEB2表达上调；表型研究证实ZEB2可能通过EMT途径介导肿瘤细胞的转移，敲减ZEB2可显著抑制小鼠模型中肿瘤的腹腔播散，为靶向卵巢癌干细胞治疗提出了新的理论依据[2]。为此，精准医学模式下的肿瘤研究不仅要求重视临床转化，同时也需要关注临床来源的机制研究；两者在很大程度上相辅相成，推动精准医学螺旋式上升发展。
精准医学在HGSOC治疗指导中的应用 精准医学在HGSOC治疗指导上也具有广泛应用，尤其是在靶向指导和解决耐药问题上，以NGS为代表的高通量测序可为临床提供非常有效的信息。携带BRCA1/2胚系或体细胞突变的HGSOC对PARP抑制剂敏感；因此，检测BRCA1/2状态对确定PARP抑制剂的是否可用至关重要。在临床应用中，NGS已被证明是一种用于评价BRCA1/2状态的可靠方法[61]。随着PARP抑制剂临床适用范围的不断拓展，其他HRR相关基因，如DNA修复蛋白RAD51(DNA repair protein RAD51，RAD51)、毛细血管扩张性共济失调突变(ataxia telangiectasia mutated，ATM)、BRCA2伴侣与定位蛋白(partner and localizer of BRCA2，PALB2)、减数分裂重组11同源物(meiotic recombination 11 homolog，MRE11)等也被纳入到HR状态检测的Panel中来，用以分析基因不稳定状态类型[62-63]。
在HGSOC的耐药研究方面，Patch团队通过全基因组测序的方法绘制了HGSOC耐药人群的特征性基因图谱，发现频繁的基因断裂常使RB1、NF1、RAD51B和PTEN等抑癌基因失活，最终导致获得性耐药的发生；CCNE1的扩增则与肿瘤原发耐药和疾病复发密切相关[30]。对“Tothill分型”的后续研究中发现，某些特殊分子亚型也与HGSOC化疗耐药存在一定联系[22]。基于这些研究，Freimund等[64]对HGSOC耐药机制进行了总结，认为HGSOC原发耐药常见于以下几种情况：DNA修复途径正常，CCNE1(19q12)扩增，C1(基质型)及C5(增殖型)分子亚型；而获得性耐药则可归咎于BRCA突变和/或DNA修复功能的恢复、分子亚型转换、凋亡逃避及药物外排系统的上调表达。在Garziera等[65]发表的一篇案例报道中，HGSOC的p53突变在化疗压力下会出现克隆进化，最终导致耐药克隆的形成。作者联合NGS和Sanger测序技术对1例接受新辅助化疗的HGSOC全病程监测中发现，患者在治疗前p53 c.215C > G(p.P72R)呈现单核苷酸多态性，而在间期减瘤时再次检测该位点单核苷酸多态性发现已完全被C碱基替代；p53 c.375+1G > A突变也在治疗后彻底丢失了G碱基这一野生型的等位点。在后续几轮辅助化疗后，患者很快出现了原方案耐药，提示p53状态改变可能参与了患者获得性耐药的产生。在精准医学的指导下，对于个别出现有限耐药机制的患者，可以实施实时转化研究，通过检相关耐药生物学标志，指导治疗方式变更，使患者获益。
面对新现的靶向耐药，同样需要依靠动态测序识别潜在耐药机制，如PARP1的缺失突变、HR状态的逆转和复制叉保护等[66]。当下，液体活检技术的开展使这种动态检测成为可能。结合实验室研究，破译其耐药的分子机制对于开发新的药物和/或治疗策略，优化HGSOC患者的治疗方案至关重要。Tan等[67]的一项研究发现C/EBPβ可直接靶向并上调多个HR基因(BRCA1，BRIP1，BRIT1，RAD51)，从而诱导HR功能恢复，介导PARP抑制剂获得性耐药的产生。Nesic等[68]通过对HR基因的甲基化测序发现，在PARP抑制剂治疗过程中，获得性RAD51C启动子甲基化缺失可诱导HGSOC的靶向耐药。Sanij等[69]发现的CX-5461则可通过激活DNA损伤反应，与PARP抑制剂存在协同作用，是潜在的耐药逆转媒介。近期，基于单细胞转录组测序技术的HGSOC耐药研究也开始崭露头角。Nath等[70]通过分析两个独立队列的单细胞测序数据，发现HGSOC由3种典型的亚克隆(代谢与增殖、细胞防御反应、DNA修复通路)所驱动，且在进展性HGSOC中，代谢与增殖亚克隆的持续富集常伴随多药耐药表型的产生。上述研究为解决HGSOC中新现的靶向耐药提供了重要线索；可以预见在精准医学模式下，转化研究的有效开展一定能够显著改善HGSOC患者的预后。
结语 HGSOC是一组异质性显著的妇科恶性肿瘤，相较于其他类型的EOC，其侵袭性高、临床预后差，复发与耐药也更为常见。在很长一段时间里，HGSOC的生存状况并未因医学的进步而得到显著改善。近年来，高通量测序技术的飞速发展为HGSOC的精准医学开辟了新道路。BRCA系列基因检测与PARP抑制剂的成功应用使15%~20%的HGSOC患者得到长期缓解。基于全基因组和转录组学分子分型的出现，为了解肿瘤发生过程中复杂的分子机制提供了新见解。在传统病理诊断中，融入多种分子病理诊断技术有助于精准定义患者临床预后，优化临床治疗路径。在治疗指导方面，基于液体活检的动态基因检测使早期识别HGSOC化疗和/或靶向耐药成为可能；同时有利于开展实时转化研究，改善个体治疗方案。然而，精准医学在HGSOC中的应用，在当下尚存在一定局限性。高通量测序技术相对较高的经济成本阻碍了其临床普及；HGSOC分子分型的复杂性使其禁锢于实验室，尚无法承接临床应用；分子病理对预后判断的价值仍需经过大量的临床验证；液体活检技术的应用也多局限于个案研究。因此，相较于其他恶性肿瘤(如肺癌、乳腺癌等)，HGSOC的精准医学之路道阻且长，需要有更多的临床医师与科研工作者齐心协力，在加速科研成果临床转化的同时，不忘探索临床新现问题，逐步完善精准医学在HGSOC中的应用。
作者贡献声明 莫佳航 综述撰写，制表。沈敏 综述撰写。姜桦 综述审校。
利益冲突声明 所有作者均声明不存在利益冲突。
| [1] |
SIEGEL RL, MILLER KD, FUCHS HE, et al. Cancer statistics, 2022[J]. CA Cancer J Clin, 2022, 72(1): 7-33.
[DOI]
|
| [2] |
LI Y, FEI H, LIN Q, et al. ZEB2 facilitates peritoneal metastasis by regulating the invasiveness and tumorigenesis of cancer stem-like cells in high-grade serous ovarian cancers[J]. Oncogene, 2021, 40(32): 5131-5141.
[DOI]
|
| [3] |
PUJADE-LAURAINE E, LEDERMANN JA, SELLE F, et al. Olaparib tablets as maintenance therapy in patients with platinum-sensitive, relapsed ovarian cancer and a BRCA1/2 mutation (SOLO2/ENGOT-Ov21): a double-blind, randomised, placebo-controlled, phase 3 trial[J]. Lancet Oncol, 2017, 18(9): 1274-1284.
[DOI]
|
| [4] |
MOORE K, COLOMBO N, SCAMBIA G, et al. Maintenance olaparib in patients with newly diagnosed advanced ovarian cancer[J]. N Engl J Med, 2018, 379(26): 2495-2505.
[DOI]
|
| [5] |
MIRZA MR, MONK BJ, HERRSTEDT J, et al. Niraparib maintenance therapy in platinum-sensitive, recurrent ovarian cancer[J]. N Engl J Med, 2016, 375(22): 2154-2164.
[DOI]
|
| [6] |
COLEMAN RL, OZA AM, LORUSSO D, et al. Rucaparib maintenance treatment for recurrent ovarian carcinoma after response to platinum therapy (ARIEL3): a randomised, double-blind, placebo-controlled, phase 3 trial[J]. Lancet, 2017, 390(10106): 1949-1961.
[DOI]
|
| [7] |
GOVINDARAJAN M, WOHLMUTH C, WAAS M, et al. High-throughput approaches for precision medicine in high-grade serous ovarian cancer[J]. J Hematol Oncol, 2020, 13(1): 134.
[DOI]
|
| [8] |
SHEN W, SHAN B, LIANG S, et al. Hybrid capture-based genomic profiling of circulating tumor dna from patients with advanced ovarian cancer[J]. Pathol Oncol Res, 2021, 27: 581534.
[DOI]
|
| [9] |
HAO Q, LI J, ZHANG Q, et al. Single-cell transcriptomes reveal heterogeneity of high-grade serous ovarian carcinoma[J]. Clin Transl Med, 2021, 11(8): e500.
|
| [10] |
STUR E, CORVIGNO S, XU M, et al. Spatially resolved transcriptomics of high-grade serous ovarian carcinoma[J]. iScience, 2022, 25(3): 103923.
[DOI]
|
| [11] |
HU Y, PAN J, SHAH P, et al. Integrated proteomic and glycoproteomic characterization of human high-grade serous ovarian carcinoma[J]. Cell Rep, 2020, 33(3): 108276.
[DOI]
|
| [12] |
KURIMCHAK AM, HERRERA-MONTÁVEZ C, BROWN J, et al. Functional proteomics interrogation of the kinome identifies MRCKA as a therapeutic target in high-grade serous ovarian carcinoma[J]. Sci Signal, 2020, 13(619): eaax8238.
[DOI]
|
| [13] |
LISIO MA, FU L, GOYENECHE A, et al. High-grade serous ovarian cancer: basic sciences, clinical and therapeutic standpoints[J]. Int J Mol Sci, 2019, 20(4): 952.
[DOI]
|
| [14] |
KURMAN RJ, CARCANGIU ML, HERRINGTO CS, et al. WHO Classification of Tumours of Female Reproductive Organs[M]. 4th ed. WHO: Geneva, Switzerland, 2014.
|
| [15] |
KURMAN RJ, SHIH IE M. The dualistic model of ovarian carcinogenesis: revisited, revised, and expanded[J]. Am J Pathol, 2016, 186(4): 733-747.
[DOI]
|
| [16] |
SOSLOW RA, HAN G, PARK KJ, et al. Morphologic patterns associated with BRCA1 and BRCA2 genotype in ovarian carcinoma[J]. Mod Pathol, 2012, 25(4): 625-636.
[DOI]
|
| [17] |
NAKAMURA M, OBATA T, DAIKOKU T, et al. The association and significance of p53 in gynecologic cancers: the potential of targeted therapy[J]. Int J Mol Sci, 2019, 20(21): 5482.
[DOI]
|
| [18] |
TAUBE ET, DENKERT C, SEHOULI J, et al. Wilms tumor protein 1 (WT1)-not only a diagnostic but also a prognostic marker in high-grade serous ovarian carcinoma[J]. Gynecol Oncol, 2016, 140(3): 494-502.
[DOI]
|
| [19] |
SHIH IM, WANG Y, WANG TL. The origin of ovarian cancer species and precancerous landscape[J]. Am J Pathol, 2021, 191(1): 26-39.
[DOI]
|
| [20] |
GHANNAM-SHAHBARI D, JACOB E, KAKUN RR, et al. PAX8 activates a p53-p21-dependent pro-proliferative effect in high grade serous ovarian carcinoma[J]. Oncogene, 2018, 37(17): 2213-2224.
[DOI]
|
| [21] |
CANCER GENOME ATLAS RESEARCH N. Integrated genomic analyses of ovarian carcinoma[J]. Nature, 2011, 474(7353): 609-615.
[DOI]
|
| [22] |
TOTHILL RW, TINKER AV, GEORGE J, et al. Novel molecular subtypes of serous and endometrioid ovarian cancer linked to clinical outcome[J]. Clin Cancer Res, 2008, 14(16): 5198-5208.
[DOI]
|
| [23] |
WANG C, ARMASU SM, KALLI KR, et al. Pooled clustering of high-grade serous ovarian cancer gene expression leads to novel consensus subtypes associated with survival and surgical outcomes[J]. Clin Cancer Res, 2017, 23(15): 4077-4085.
[DOI]
|
| [24] |
SOHN MH, KIM SI, SHIN JY, et al. Classification of high-grade serous ovarian carcinoma by epithelial-to-mesenchymal transition signature and homologous recombination repair genes[J]. Genes (Basel), 2021, 12(7): 1103.
[DOI]
|
| [25] |
COOK DP, VANDERHYDEN BC. Ovarian cancer and the evolution of subtype classifications using transcriptional profilingdagger[J]. Biol Reprod, 2019, 101(3): 645-658.
[DOI]
|
| [26] |
CLIFFORD C, VITKIN N, NERSESIAN S, et al. Multi-omics in high-grade serous ovarian cancer: biomarkers from genome to the immunome[J]. Am J Reprod Immunol, 2018, 80(2): e12975.
[DOI]
|
| [27] |
TALHOUK A, GEORGE J, WANG C, et al. Development and validation of the gene expression predictor of high-grade serous ovarian carcinoma molecular SubTYPE (PrOTYPE)[J]. Clin Cancer Res, 2020, 26(20): 5411-5423.
[DOI]
|
| [28] |
CHAN AM, ENWERE E, MCINTYRE JB, et al. Combined CCNE1 high-level amplification and overexpression is associated with unfavourable outcome in tubo-ovarian high-grade serous carcinoma[J]. J Pathol Clin Res, 2020, 6(4): 252-262.
[DOI]
|
| [29] |
PETERSEN S, WILSON AJ, HIRST J, et al. CCNE1 and BRD4 co-amplification in high-grade serous ovarian cancer is associated with poor clinical outcomes[J]. Gynecol Oncol, 2020, 157(2): 405-410.
[DOI]
|
| [30] |
PATCH AM, CHRISTIE EL, ETEMADMOGHADAM D, et al. Whole-genome characterization of chemoresistant ovarian cancer[J]. Nature, 2015, 521(7553): 489-494.
[DOI]
|
| [31] |
JIN C, LIU Z, LI Y, et al. PCNA-associated factor P15(PAF), targeted by FOXM1, predicts poor prognosis in high-grade serous ovarian cancer patients[J]. Int J Cancer, 2018, 143(11): 2973-2984.
[DOI]
|
| [32] |
BU H, LI Y, JIN C, et al. Overexpression of PRC1 indicates a poor prognosis in ovarian cancer[J]. Int J Oncol, 2020, 56(3): 685-696.
|
| [33] |
HANKER LC, EL-BALAT A, DROSOS Z, et al. Sphingosine-kinase-1 expression is associated with improved overall survival in high-grade serous ovarian cancer[J]. J Cancer Res Clin Oncol, 2021, 147(5): 1421-1430.
[DOI]
|
| [34] |
LU H, CUNNEA P, NIXON K, et al. Discovery of a biomarker candidate for surgical stratification in high-grade serous ovarian cancer[J]. Br J Cancer, 2021, 124(7): 1286-1293.
[DOI]
|
| [35] |
KIM SR, MALCOLMSON J, LI X, et al. The correlation between BRCA status and surgical cytoreduction in high-grade serous ovarian carcinoma[J]. Gynecol Oncol, 2021, 162(3): 702-706.
[DOI]
|
| [36] |
MORSE CB, NORQUIST BM, HARRELL MI, et al. Neoplastic cellularity is associated with clinical and molecular features of high-grade serous ovarian carcinoma[J]. Gynecol Oncol, 2016, 143(2): 389-392.
[DOI]
|
| [37] |
BISCHOF K, KNAPPSKOG S, HJELLE SM, et al. Influence of p53 isoform expression on survival in high-grade serous ovarian cancers[J]. Sci Rep, 2019, 9(1): 5244.
[DOI]
|
| [38] |
LEE SW, LEE HY, KANG SW, et al. Application of immunoprofiling using multiplexed immunofluorescence staining identifies the prognosis of patients with high-grade serous ovarian cancer[J]. Int J Mol Sci, 2021, 22(17): 9638.
[DOI]
|
| [39] |
PAIJENS ST, VLEDDER A, LOIERO D, et al. Prognostic image-based quantification of CD8CD103 T cell subsets in high-grade serous ovarian cancer patients[J]. Oncoimmunology, 2021, 10(1): 1935104.
[DOI]
|
| [40] |
WANG L. Prognostic effect of programmed death-ligand 1 (PD-L1) in ovarian cancer: a systematic review, meta-analysis and bioinformatics study[J]. J Ovarian Res, 2019, 12(1): 37.
[DOI]
|
| [41] |
ZONG L, ZHOU Y, ZHANG M, et al. VISTA expression is associated with a favorable prognosis in patients with high-grade serous ovarian cancer[J]. Cancer Immunol Immunother, 2020, 69(1): 33-42.
[DOI]
|
| [42] |
MARTIN DE LA FUENTE L, WESTBOM-FREMER S, ARILDSEN NS, et al. PD-1/PD-L1 expression and tumor-infiltrating lymphocytes are prognostically favorable in advanced high-grade serous ovarian carcinoma[J]. Virchows Arch, 2020, 477(1): 83-91.
[DOI]
|
| [43] |
WEBB JR, MILNE K, KROEGER DR, et al. PD-L1 expression is associated with tumor-infiltrating T cells and favorable prognosis in high-grade serous ovarian cancer[J]. Gynecol Oncol, 2016, 141(2): 293-302.
[DOI]
|
| [44] |
KIM KH, CHOI KU, KIM A, et al. PD-L1 expression on stromal tumor-infiltrating lymphocytes is a favorable prognostic factor in ovarian serous carcinoma[J]. J Ovarian Res, 2019, 12(1): 56.
[DOI]
|
| [45] |
FARRAG MS, ABDELWAHAB K, FARRAG NS, et al. Programmed death ligand-1 and CD8 tumor-infiltrating lymphocytes (TILs) as prognostic predictors in ovarian high-grade serous carcinoma (HGSC)[J]. J Egypt Natl Canc Inst, 2021, 33(1): 16.
[DOI]
|
| [46] |
PULKO V, HARRIS KJ, LIU X, et al. B7-h1 expressed by activated CD8 T cells is essential for their survival[J]. J Immunol, 2011, 187(11): 5606-5614.
[DOI]
|
| [47] |
COMMUNAL L, ROY N, CAHUZAC M, et al. A keratin 7 and E-cadherin signature is highly predictive of tubo-ovarian high-grade serous carcinoma prognosis[J]. Int J Mol Sci, 2021, 22(10): 5325.
[DOI]
|
| [48] |
AZZALINI E, TIERNO D, BARTOLETTI M, et al. AKT isoforms interplay in high-grade serous ovarian cancer prognosis and characterization[J]. Cancers (Basel), 2022, 14(2): 304.
[DOI]
|
| [49] |
LEONARD B, STARRETT GJ, MAURER MJ, et al. APOBEC3G expression correlates with T-cell infiltration and improved clinical outcomes in high-grade serous ovarian carcinoma[J]. Clin Cancer Res, 2016, 22(18): 4746-4755.
[DOI]
|
| [50] |
ZHANG L, FU R, LIU P, et al. Biological and prognostic value of ETV5 in high-grade serous ovarian cancer[J]. J Ovarian Res, 2021, 14(1): 149.
[DOI]
|
| [51] |
WANG H, YE F, ZHOU C, et al. High expression of ENPP1 in high-grade serous ovarian carcinoma predicts poor prognosis and as a molecular therapy target[J]. PLoS One, 2021, 16(2): e0245733.
[DOI]
|
| [52] |
HENRIKSEN JR, DONSKOV F, WALDSTROM M, et al. Favorable prognostic impact of natural killer cells and T cells in high-grade serous ovarian carcinoma[J]. Acta Oncol, 2020, 59(6): 652-659.
[DOI]
|
| [53] |
DARB-ESFAHANI S, KOLASCHINSKI I, TRILLSCH F, et al. Morphology and tumour-infiltrating lymphocytes in high-stage, high-grade serous ovarian carcinoma correlated with long-term survival[J]. Histopathology, 2018, 73(6): 1002-1012.
[DOI]
|
| [54] |
BANSAL A, SRINIVASAN R, ROHILLA M, et al. Immunotyping in tubo-ovarian high-grade serous carcinoma by PD-L1 and CD8+ T-lymphocytes predicts disease-free survival[J]. APMIS, 2021, 129(5): 254-264.
[DOI]
|
| [55] |
MATSUMOTO T, ODA Y, HASEGAWA Y, et al. Anaplastic lymphoma kinase overexpression is associated with aggressive phenotypic characteristics of ovarian high-grade serous carcinoma[J]. Am J Pathol, 2021, 191(10): 1837-1850.
[DOI]
|
| [56] |
BAATH M, JONSSON JM, WESTBOM FREMER S, et al. MET expression and cancer stem cell networks impact outcome in high-grade serous ovarian cancer[J]. Genes (Basel), 2021, 12(5): 742.
[DOI]
|
| [57] |
JIN C, XUE Y, LI Y, et al. A 2-protein signature predicting clinical outcome in high-grade serous ovarian cancer[J]. Int J Gynecol Cancer, 2018, 28(1): 51-58.
[DOI]
|
| [58] |
HOJNIK M, SUSTER NK, SMRKOLJ S, et al. AKR1B1 as a prognostic biomarker of high-grade serous ovarian cancer[J]. Cancers (Basel), 2022, 14(3): 809.
[DOI]
|
| [59] |
TRUDEL D, AVARVAREI LM, ORAIN M, et al. Proteases and their inhibitors as prognostic factors for high-grade serous ovarian cancer[J]. Pathol Res Pract, 2019, 215(6): 152369.
[DOI]
|
| [60] |
GAGNE A, TETU B, ORAIN M, et al. HtrA1 expression and the prognosis of high-grade serous ovarian carcinoma: a cohort study using digital analysis[J]. Diagn Pathol, 2018, 13(1): 57.
[DOI]
|
| [61] |
PEPE F, PISAPIA P, RUSSO G, et al. BRCA1/2 NGS somatic testing in clinical practice: a short report[J]. Genes (Basel), 2021, 12(12): 1917.
[DOI]
|
| [62] |
MARQUARD AM, EKLUND AC, JOSHI T, et al. Pan-cancer analysis of genomic scar signatures associated with homologous recombination deficiency suggests novel indications for existing cancer drugs[J]. Biomark Res, 2015, 3: 9.
[DOI]
|
| [63] |
中华医学会妇科肿瘤学分会. 卵巢癌PARP抑制剂临床应用指南[J]. 中国医学前沿杂志(电子版), 2020, 12(5): 29-37. [CNKI]
|
| [64] |
FREIMUND AE, BEACH JA, CHRISTIE EL, et al. Mechanisms of drug resistance in high-grade serous ovarian cancer[J]. Hematol Oncol Clin North Am, 2018, 32(6): 983-996.
[DOI]
|
| [65] |
GARZIERA M, CECCHIN E, GIORDA G, et al. Clonal evolution of TP53 c. 375+1G > A mutation in pre- and post- neo-adjuvant chemotherapy (NACT) tumor samples in high-grade serous ovarian cancer (HGSOC)[J]. Cells, 2019, 8(10): 1186.
[DOI]
|
| [66] |
CHIAPPA M, GUFFANTI F, BERTONI F, et al. Overcoming PARPi resistance: preclinical and clinical evidence in ovarian cancer[J]. Drug Resist Updat, 2021, 55: 100744.
[DOI]
|
| [67] |
TAN J, ZHENG X, LI M, et al. C/EBPbeta promotes poly(ADP-ribose) polymerase inhibitor resistance by enhancing homologous recombination repair in high-grade serous ovarian cancer[J]. Oncogene, 2021, 40(22): 3845-3858.
[DOI]
|
| [68] |
NESIC K, KONDRASHOVA O, HURLEY RM, et al. Acquired RAD51C promoter methylation loss causes PARP inhibitor resistance in high-grade serous ovarian carcinoma[J]. Cancer Res, 2021, 81(18): 4709-4722.
[DOI]
|
| [69] |
SANIJ E, HANNAN KM, XUAN J, et al. CX-5461 activates the DNA damage response and demonstrates therapeutic efficacy in high-grade serous ovarian cancer[J]. Nat Commun, 2020, 11(1): 2641.
[DOI]
|
| [70] |
NATH A, COSGROVE PA, MIRSAFIAN H, et al. Evolution of core archetypal phenotypes in progressive high grade serous ovarian cancer[J]. Nat Commun, 2021, 12(1): 3039.
[DOI]
|