肿瘤突变负荷用于预测恶性肿瘤患者预后的研究进展
Research Progress of Tumor Mutational Burden in Predicting Prognosis of Patients with Malignant Tumors
DOI: 10.12677/ACM.2022.1281008, PDF, HTML, XML, 下载: 144  浏览: 213 
作者: 饶 舜:浙江大学医学院附属邵逸夫医院,浙江 杭州
关键词: 免疫检查点抑制剂肿瘤突变负荷恶性肿瘤生物标志物预后Immune Checkpoint Inhibitor Tumor Mutational Burden Malignant Tumor Biomarkers Prognosis
摘要: 随着免疫检查点抑制剂(immune checkpoint inhibitor, ICI)在多种恶性肿瘤中的应用,免疫治疗已成为肿瘤治疗的研究焦点。最近,肿瘤突变负荷(tumor mutational burden, TMB)已逐渐成为多种恶性肿瘤免疫治疗选择的可靠生物标志物。本文主要对TMB在恶性肿瘤免疫治疗中相关研究以及与其他生物标志物联合预测肿瘤免疫治疗效果进行综述。
Abstract: With the application of immune checkpoint inhibitor (ICI) in various malignant tumors, immuno-therapy has become the research focus of tumor treatment. Recently, tumor mutational burden (TMB) has gradually become a reliable biomarker for immunotherapy options for a variety of ma-lignant tumors. This review focuses on the related researches of TMB in the immunotherapy of ma-lignant tumors and its combination with other biomarkers to predict the effect of tumor immuno-therapy.
文章引用:饶舜. 肿瘤突变负荷用于预测恶性肿瘤患者预后的研究进展[J]. 临床医学进展, 2022, 12(8): 7000-7004. https://doi.org/10.12677/ACM.2022.1281008

1. 引言

近年来,恶性肿瘤发病率和死亡率迅速增加,2020年全球癌症新发病例约1930万,死亡病例近1000万 [1]。恶性肿瘤的治疗是临床的难点,手术、化疗及放疗只能暂时缓解病情。

以免疫检查点抑制剂(immune checkpoint inhibitor, ICI)为主的免疫疗法是近年来治疗多种实体瘤的最大进展之一 [2]。然而,有相当一部分患者并不能从免疫治疗过程中获益 [3] [4]。此外,ICI费用高,而且常常伴随严重的不良反应 [5] [6]。因此,急需寻找简单、有效的生物标志物筛选免疫治疗的潜在获益人群。研究表明,肿瘤突变负荷(tumor mutational burden, TMB)越高的患者越有可能从免疫治疗中受益,因此,TMB已成为接受ICI治疗患者的预测性标志物。

2. TMB的概念

肿瘤的形成和进展伴随着突变的获得和积累。TMB涉及基因插入或缺失、基因编码错误和碱基替换,是指每兆碱基(Mb)中体细胞突变总数 [7]。对TMB的检测主要采用全外显子组测序(whole-exome sequencing, WES)和靶向下一代测序(targeted next-generation sequencing, NGS)技术。TMB受紫外线、吸烟、化学治疗等驱动 [8]。体细胞外显子区域的大量突变可产生新的蛋白,并被主要组织相容性复合体(major histocompatibility complex, MHC)呈递至肿瘤细胞表面,进一步诱导新抗原的形成,从而激活CD8+细胞毒性T细胞的免疫原性以识别和处理肿瘤细胞,并带来更好的治疗反应 [9] [10] [11] [12]。因此,随着TMB增加,更多的肿瘤新抗原被释放,机体的免疫原性也增强。

3. TMB作为生物标志物在恶性肿瘤免疫治疗中的应用

体细胞错义突变可促进新肿瘤表位的形成,从而产生更多的新抗原 [13]。一般来说,克隆新抗原数量越多的患者越有可能对免疫治疗产生反应。因此,TMB可用于间接代表新生抗原负荷并作为生物标志物在恶性肿瘤免疫治疗中发挥作用。既往多项研究发现,TMB与免疫治疗的疗效和反应率密切相关。GOODMAN等回顾性收集了1638例进行了全面基因组分析和TMB评估的患者的数据 [9]。结果提示,高TMB组和低至中TMB组患者的有效率(response rate, RR)分别为22/38 (58%)和23/113 (20%)。中位无进展生存期(progression-free survival, PFS)分别为12.8个月和3.3个月。对于抗PD-1/PD-L1单药治疗,同样显示高TMB和免疫治疗疗效呈线性相关。在2019年的一项包含1662名接受ICI治疗的晚期癌症患者和5371名非ICI治疗患者的研究中发现,在多种癌症类型中较高的TMB与接受ICI治疗的患者生存率的提高有关 [14]。Cao等为了评估TMB在接受免疫治疗的癌症患者中的预后作用,纳入了45项研究,其中包括103078例癌症患者,研究结果表明,与低TMB组相比,高TMB组具有更好的总生存期(HR = 0.40; 95% confidence interval (CI): 0.30~0.53; P < 0.00001)和更高的无进展生存期(HR = 0.37; 95% CI: 0.26~0.53; P < 0.00001),且与癌症类型和TMB检测方法无关 [15]。此外,2020年,美国食品药品监督管理局(The Food and Drug Administration, FDA)批准使用TMB作为接受pembrolizumab治疗的不可切除或转移性实体瘤患者中反应的生物标志物 [16]。Cuppens等纳入126例接受免疫疗法的晚期非小细胞肺癌患者,结果显示相较于低TMB患者,高TMB患者在免疫治疗开始后6个月具有更高的反应率(49.1% vs 25.4%; P = 0.0084)和生存率(85.5% vs 70.4%; P = 0.0468),证实了TMB对治疗反应和生存结果的预测能力 [17]。

虽然在大部分恶性肿瘤中观察到TMB与接受ICI治疗的患者的生存率相关。有趣的是,在神经胶质瘤患者中,研究人员发现高TMB患者生存率却低于低TMB患者,这可能是由于样本量较小,但具体原因还需进一步探究 [14]。同样,Rizvi等纳入了240例接受ICI治疗的晚期非小细胞肺癌患者,在高TMB组和低TMB组中发现患者PFS无显著差异 [18]。猜测可能是与TMB阈值制定标准不同有关。在另一项涉及16种癌症类型的1678例肿瘤患者的队列研究中,与低TMB组相比,只有11种具有更高的反应率,这说明TMB作为免疫治疗疗效的预测标志物在不同癌症类型之间存在显著差异,但是具体机制还有待进一步探究 [19]。一项对超过10,000例肿瘤患者的分析表明,接受ICI治疗的高TMB的乳腺癌患者的疗效比接受其他抗肿瘤治疗的患者差 [20]。因此,McGrail等人不支持使用TMB作为所有肿瘤类型免疫治疗疗效的预测标志物。

4. TMB联合其他生物标志物预测肿瘤免疫治疗效果

虽然TMB已广泛应用于免疫治疗获益患者的筛选及疗效预测。然而,由于癌症类型之间存在显著差异,单一生物标志物的预测价值是有限的。多项研究表明,TMB和PD-L1两者在包括非小细胞肺癌、黑色素瘤和结直肠癌在内的许多癌症中的表达几乎没有相关性 [21] [22] [23]。Rizvi等提出TMB和PD-L1同时高表达的患者获得更持久的临床获益,且在获得持久有效率的高TMB患者中发现了POLD1、POLE和MSH2基因的突变 [24]。Hellman等发现TMB和PD-L1表达之间没有相关性,但是,同时具有高TMB和PD-L1阳性的非小细胞肺癌患者的客观缓解率(objective response rate, ORR)和PFS显著高于两者都低或其中一项高的患者 [25]。值得注意的是,TP53突变与TMB增加相关。Cuppens等观察到具有双重阳性(高TMB和HLA-1多样性)的非小细胞肺癌患者具有更高的反应率和持久的临床获益 [17]。更重要的是,没有一个三重阴性(低TMB和HLA-1多样性和PD-L1阴性)的患者对免疫治疗表现出反应。简而言之,TMB结合HLA-1和PD-L1可以识别出可能有反应的非小细胞肺癌患者,且更能识别出无法从免疫治疗中获益的患者。

上述研究不仅说明了TMB和PD-L1两者的协同作用可能更有利于预测接受免疫治疗患者的疗效,而且TMB的表达可能与其他基因存在一定程度的相关,但是未来还需要大量前瞻性研究来进一步探索其中的机制。

5. 结论

总体而言,随着免疫治疗研究的不断进展,TMB在恶性肿瘤中的应用受到越来越多重视,迫切需要筛选免疫治疗获益人群。TMB被认为是免疫治疗疗效的预测性生物标志物。本文回顾并总结了TMB的基本概念,TMB在恶性肿瘤免疫治疗中的应用以及TMB联合其他生物标志物预测肿瘤免疫治疗的效果。然而,单纯使用TMB筛选ICI获益患者存在一定局限性,多项研究表明TMB联合其他分子标志物能更好地筛选出接受ICI有效的人群,例如PD-L1、HLA-1等。但是,未来还需要大样本的前瞻性研究来进一步探究联合多种不同的分子标志物来共同预测免疫治疗的疗效,以此来确定最有可能受益的患者来更好地指导ICI在临床实践中的合理应用。

NOTES

*Email: 609627390@qq.com

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