Effect of Lymph Node Metastasis on Prognosis of Small Cell Lung Cancer with M1a Disease: A Study Based on SEER database
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摘要:目的
探讨淋巴结转移对M1a期小细胞肺癌(SCLC)患者生存的影响。
方法回顾性分析SEER数据库中2004—2015年7027例M1a期SCLC患者病例资料,采用Kaplan-Meier法及Log rank检验比较不同N分期亚组患者总体生存率(OS),Cox比例风险模型评估N分期是否为影响预后的独立危险因素。
结果全组中位OS为7月。在所有M1a患者中,无淋巴结转移(N0)患者的OS最好,其次是N1患者,而N2和N3患者的预后最差(P < 0.001)。亚组分析也显示对侧肺结节组、恶性胸腔积液组和恶性心包积液组也存在随N分期升高OS递减的趋势。多因素分析显示淋巴结转移是M1a期SCLC患者的独立预后因素,在M1a不同亚群中也观察到相同的结果。
结论淋巴结转移能够影响M1a期SCLC患者生存,增加额外的预后信息,建议在下一版本的TNM分期系统中进一步完善N描述符。
Abstract:ObjectiveTo investigate the impact of lymph node metastasis on the survival of SCLC patients with M1a disease.
MethodsWe retrospectively analyzed the medical records of 7027 SCLC patients with M1a disease from 2004 to 2015 in SEER database. The Kaplan-Meier method and log-rank test were used to estimate the OS in all N stage subgroups. Cox proportional hazard model was used to assess whether N stage was an independent risk factor for prognosis.
ResultsThe median OS of all patients was 7 months. Among all M1a patients, the patients without lymph node involvement (N0) had the best OS, followed by N1 stage patients; N2 and N3 stage patients had the worst OS (P < 0.001). Similarly, this trend was observed when M1a disease was subdivided into contralateral pulmonary nodules, malignant pleural effusion and malignant pericardial effusion. Multivariate analysis showed that lymph node metastasis was an independent prognostic factor for SCLC patients with M1a disease, and this result was also noticed in all subgroups of M1a disease.
ConclusionLymph node metastasis may affect the survival of SCLC patients with M1a disease, adding prognostic information. And it is recommended to further improve the N descriptor in the next version of TNM staging system.
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Key words:
- Small cell lung cancer /
- N stage /
- M1a stage /
- SEER database /
- Prognosis
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0 引言
长链非编码RNA(long noncoding RNA, LncRNA)是广泛存在于哺乳动物细胞中的一类转录本长度超过200 nt的非编码RNA分子[1]。近年来研究发现LncRNAs参与调控细胞的多个阶段,影响着癌症的发生发展[2],包括肿瘤转移[3]。此外越来越多研究探讨血清LncRNAs作为肿瘤生物标志物的价值[4-5],但其在肺癌骨转移(lung cancer with bone metastasis, LCWBM)诊断中的作用仍未见报道。
本研究通过文献查阅,筛选出与肿瘤转移密切相关的4种LncRNAs。HOTAIR是Homebox C基因位点表达产物,以反式沉默的方式发挥作用。研究显示HOTAIR与人类同源盒基因和癌转移相关,参与多种癌症进展,可作为预后不良的标志物[6]。HOTTIP是HOXA基因远端转录生成的一类LncRNA,已有文献显示HOTTIP可促进常见消化系统恶性肿瘤细胞的增殖、侵袭、转移,抑制癌细胞的凋亡,其高表达与患者的淋巴结转移和总体生存时间密切相关[7]。CRNDE是结直肠癌差异表达的LncRNA,在许多癌组织和癌细胞中表达出现异常,与疾病分期、远处转移、病理类型及生存状态明显相关[8]。AFAP1-AS1是新发现的一种LncRNA,近年研究发现AFAP1-AS1与恶性肿瘤的增殖、转移关系密切[9]。本研究检测HOTAIR、HOTTIP、CRNDE、AFAP1-AS1这4种血清LncRNAs在LCWBM和未发生骨转移肺癌(lung cancer without bone metastasis, LCWOBM)患者中的表达水平,并分析其对LCWBM的诊断价值。
1 资料与方法
1.1 研究对象
选取2016年1月—2018年8月河南省肿瘤医院LCWBM和LCWOBM患者各38例。肺癌患者发生骨转移均经核素骨扫描或PET扫描确诊。LCWOBM肺癌未发生骨转移患者为原发肺癌患者,未发生其他任何转移。所有患者都为未经化疗、放疗或免疫治疗的新发病例。两组研究对象均排除肝功能(包括谷丙转氨酶和谷草转氨酶)异常和肾功能不全(肾小球滤过率≤60 ml/min)的患者,排除妊娠、脑血管疾病等合并症的患者。该研究经郑州大学附属肿瘤医院伦理委员会批准,所有患者均知情同意。
LCWBM组平均年龄为63.92±8.70岁,LCWOBM组平均年龄为57.06±11.44岁,两组患者年龄差异无统计学意义(t=-1.79, P=0.08)。LCWBM患者中男14例、女24例,肺鳞癌15例,肺腺癌23例。LCWOBM患者中男性21例、女性17例,肺鳞癌13例,肺腺癌25例,两组患者性别差异无统计学意义(χ2=2.56, P=0.11)。两组肺癌的病理类型比较,差异亦无统计学意义(χ2=0.23, P=0.63)。
1.2 血液采集与血清制备
采用EDTA抗凝真空采血管采集LCWBM和LCWOBM患者晨起空腹静脉血5 ml,全血离体6 h内进行血清分离。将采血管3 000 r/min离心10 min,收集上清液;之后将上清液12000 r/min再次离心10 min,收集血清,放于-80℃冻存备用。
1.3 试剂和设备
TRIzol试剂盒购自美国Invitrogen公司,反转录试剂盒PrimeScript™ RT reagent Kit with gDNA Eraser(Perfect Real Time)和荧光定量试剂盒TB Green® Premix Ex Taq™(Tli RNaseH Plus)均来自日本Takara公司。PCR仪器使用Illumina公司的PCRmax Eco 48实时荧光定量PCR仪。由尚亚公司合成的GAPDH为内参,LncRNA HOTAIR、HOTTIP、CRNDE和AFAP1-AS1的引物由锐博生物公司设计合成,见表 1。
表 1 qRT-PCR引物序列Table 1 Primers sequences for qRT-PCR1.4 RNA提取、反转录和qRT-PCR实验
采用TRIzol试剂从血清样本中提取总RNA,Thermo Scientific NanoDrop 2000超微量分光光度计检测RNA浓度和纯度。将RNA浓度调整至200~300 ng/μl。采用反转录试剂盒PrimeScript™ RT reagent Kit with gDNA Eraser将RNA反转录为cDNA,采用荧光定量PCR试剂盒TB Green® Premix Ex Taq™检测LncRNA HOTAIR、HOTTIP、CRNDE、AFAP1-AS1的表达水平。在冰上配制25 μl反应体系:cDNA 2 μl,上、下游引物各1.0 μl,SYBR Premix Ex TaqⅡ 12.5 μl,dH2O 8.5 μl。实时定量PCR反应条件:首先95℃ 30 s预变性,其次95℃ 5 s,60℃ 30 s,共40个循环,最后绘制熔化曲线。采用2-∆∆Ct法计算LncRNA在肺癌骨转移患者血清中表达量相对于未发生骨转移肺癌患者血清中表达量的倍数。
1.5 统计学方法
采用SPSS21.0统计软件进行数据分析,计数资料比较采用卡方检验,不符合正态分布的计量资料采用中位数(M)和四分位数间距(P25, P75)表示,非正态分布的计量资料两组间比较采用Mann-Whitney U秩和检验。采用MedCalc医学统计软件15.2绘制受试者工作特征曲线(receiver operating characteristics curve, ROC),计算曲线下面积(area under curve, AUC),得出敏感度、特异性、阳性预测值、阴性预测值。敏感度(试验正确检出阳性患者的率)=真阳性人数/(真阳性人数+假阴性人数)×100%。 特异性(试验正确检出阴性患者的率)=真阴性人数/(真阴性人数+假阳性人数)×100%。 阳性预测值(试验检出真阳性数在试验方法检出总阳性数中的比例)=真阳性例数/(真阳性例数+假阳性例数)×100%;阴性预测值(试验检出真阴性数在试验方法检出总阴性数中的比例)=真阴性例数/(真阴性例数+假阴性例数)×100%。采用二分类Logistic回归分析两个血清LncRNA诊断肺癌骨转移的效果。检验水准为双侧α=0.05。
2 结果
2.1 LCWBM和LCWOBM患者血清中4种LncRNA的表达水平比较
LCWBM患者血清中HOTAIR的表达水平明显低于LCWOBM患者(P < 0.05),LCWBM患者血清中HOTTIP的表达水平明显高于LCWOBM患者(P < 0.05),血清CRNDE、AFAP1-AS1表达水平在LCWBM组和LCWOBM组之间差异无统计学意义(P > 0.05),见表 2。
表 2 LCWBM和LCWOBM患者血清中四种LncRNA的表达水平比较Table 2 Comparison of four serum LncRNA levels between LCWBM group and LCWOBM group2.2 年龄、性别、病理类型和血清4种LncRNA表达量的关系
根据LCWBM患者年龄中位数(58岁)将两组患者分为两个部分。年龄分层后,LCWBM组 < 58岁的低年龄层患者血清HOTTIP表达水平显著高于LCWOBM组,差异有统计学意义(P < 0.05),其余3种血清LncRNAs在两组患者不同年龄层的表达量比较,差异均无统计学意义(P > 0.05),见表 3。
表 3 LCWBM和LCWOBM组年龄与血清中4种lncRNA表达量的关系Table 3 Association between age and four serum lncRNA levels in LCWBM and LCWOBM groups性别和病理类型分层结果显示:性别分层后,LCWBM组女性患者血清HOTAIR表达量明显低于LCWOBM组,差异有统计学意义(P < 0.05);LCWBM组肺腺癌患者血清HOTTIP表达水平明显高于LCWOBM组肺腺癌患者,差异有统计学意义(P < 0.05)。其余3种血清LncRNAs在两组患者不同性别、不同病理类型分层的表达量比较,差异均无统计学意义(P > 0.05),见表 4~5。
表 4 LCWBM和LCWOBM组性别与血清中4种LncRNA表达量的关系Table 4 Association between gender and four serum LncRNA levels in LCWBM and LCWOBM groups表 5 LCWBM和LCWOBM组病理类型与血清中4种LncRNA表达量的关系Table 5 Association between pathological types and four serum LncRNA levels in LCWBM and LCWOBM groups2.3 ROC曲线分析
采用ROC曲线评估四种血清LncRNAs对LCWBM的诊断价值,结果显示:血清HOTAIR诊断LCWBM的ROC曲线下面积(AUC)为0.722(95%CI: 0.562~0.849);敏感度和特异性分别为70.0%和81.3%,阳性预测值和阴性预测值为53.8%和89.7%。血清HOTTIP诊断LCWBM的ROC曲线下面积为0.784(95%CI: 0.538~0.936);敏感度和特异性分别为100.0%和45.5%,阳性预测值和阴性预测值为57.1%和100.0%。血清CRNDE和AFAP1-AS1的ROC曲线下面积分别为0.630和0.558。血清HOTAIR和HOTTIP对LCWBM的诊断效力较好(P=0.027, P=0.008),血清CRNDE和AFAP1-AS1对LCWBM诊断效力较差(P=0.345, P=0.658)。
由于血清HOTAIR和HOTTIP表达水平在两组间差异有统计学意义,将血清HOTAIR和HOTTIP联合,分析其联合诊断LCWBM的效果,结果显示ROC曲线下面积为0.818(95%CI: 0.577~0.955)(P=0.002);敏感度和特异性为87.5%和72.7%,阳性预测值和阴性预测值为70.0%和88.9%,见图 1。
3 讨论
HOTAIR能够调控其靶基因参与多种肿瘤的发生和转移。研究报道非小细胞肺癌患者血清中HOTAIR水平明显高于健康对照者[10];食管鳞癌患者血清中HOTAIR的表达水平亦明显高于健康对照者,采用血清HOTAIR诊断食管鳞癌的ROC曲线下面积为0.793,提示其可能可以作为诊断食管鳞癌的潜在生物标志物[11]。本研究结果显示LCWBM患者血清HOTAIR表达水平明显低于LCWOBM患者,性别分层后发现,女性LCWBM组患者血清HOTAIR表达量明显低于LCWOBM组女性患者,分析其原因,可能是两组研究对象均为肺癌患者,只是发生骨转移的情况不同,而之前报道的研究对象是癌症患者和健康人群;此外LCWBM患者血液中免疫细胞可能因肿瘤细胞的攻击而受到抑制,导致其分泌入血的HOTAIR减少,且在女性患者中更为明显。本研究血清HOTAIR诊断LCWBM的ROC曲线下面积(AUC)为0.722,敏感度和特异性分别为70.0%和81.3%,曲线下面积大于0.7,敏感度和特异性均较高,提示其诊断效力较好。
HOTTIP可以通过广泛的结构域激活组蛋白H3赖氨酸27三甲基化(H3K4me3)转录,提示HOTTIP在协调和激活HOXA簇基因中发挥着重要作用。HOTTIP通过结合WD-repeat-containing protein 5(WDR5),增加β-catenin基因表达水平,增强成骨分化,最终激活下游Wnt/catenin信号通路,因此HOTTIP可以促进骨肉瘤细胞的生长和上皮-间质转化[12]。HOTTIP在大多数癌症中过表达[13],HOTTIP可能通过靶向调控miR-516b-5p/SPIN1参与食管癌凋亡、转移和免疫逃逸[14]。胃癌患者血清外泌体HOTTIP表达明显升高,且与顺铂化疗耐药有关[15]。本研究中,LCWBM组患者血清HOTTIP表达显著上调,特别是在LCWBM组 < 58岁的低年龄层和肺腺癌患者中,血清HOTTIP表达量均明显高于LCWOBM组相应亚型组,说明在 < 58岁且肺癌病理类型为肺腺癌的患者中判断其是否可能发生骨转移,应重点考虑该指标。血清HOTTIP诊断LCWBM的ROC曲线下面积(AUC)为0.784,敏感度和特异性分别为100.0%和45.5%。结果表明血清HOTTIP对肺癌骨转移有较好的诊断潜力,但特异性较低,即血清HOTTIP把实际没有发生骨转移的肺癌患者正确判断为未发生骨转移的能力较低,最终可能导致假阳性增多。然而将血清HOTAIR与HOTTIP两指标联合,其联合诊断肺癌骨转移的ROC曲线下面积为0.818,敏感度和特异性分别为87.5%和72.7%,显示两指标联合诊断效果要明显优于单一指标的诊断效果,即联合血清HOTAIR与HOTTIP有助于提高诊断LCWBM的效力。
血清外泌体CRNDE水平在胰腺导管内黏液腺瘤(IPMN)患者和恶性程度较高的胰腺导管腺癌(PDAC)患者中显著高于健康对照,且其在PDAC患者血清中表达水平高于IPMN患者,提示血清CRNDE表达水平与胰腺癌恶性程度有关[15]。AFAP1-AS1可通过介导miR-423-5p调节Rho/Rac信号通路,促进鼻咽癌细胞的迁移和侵袭;裸鼠转染AFAP1-AS1后鼻咽癌细胞的肺转移率明显高于对照组[16]。本研究中,血清CRNDE和AFAP1-AS1表达水平在两组中差异无统计学意义(P > 0.05),且对LCWBM诊断效力较低(0.5 < AUC < 0.7, P > 0.05),尚不能作为诊断LCWBM的生物标志物。
本研究探讨了血清LncRNA HOTAIR、HOTTIP、CRNDE、AFAP1-AS1对LCWBM的诊断价值。血清检测因其无创、方便、可重复性等特点,更适合作为生物标志物[17]。本研究也存在一些局限:首先,样本数量较少;其次,除了年龄、性别和病理类型,未收集患者的其他基本信息,无法深层次探讨肺癌骨转移患者临床特征与血清LncRNAs表达的关系。今后,将扩大样本量,进一步验证血清LncRNA HOTAIR、HOTTIP在肺癌骨转移诊断中的价值,并探索其生物学效应,揭示其内在的分子机制。
综上所述,血清HOTAIR和HOTTIP对肺癌骨转移有一定的诊断价值,两者联合诊断效果优于单一指标,可能成为诊断肺癌骨转移的新的生物标志物,为肺癌骨转移临床诊断提供新的思路。
Competing interests: The authors declare that they have no competing interests.作者贡献:阳昊:查阅文献、提取数据、统计分析、论文撰写梅同华:把握研究方向、论文指导及修改 -
表 1 7 027例M1a期小细胞肺癌患者临床特征(n(%))
Table 1 Clinical characteristics of 7027 SCLC patients with M1a disease (n(%))
表 2 影响M1a期SCLC患者OS的单因素和多因素分析
Table 2 Univariate and multivariate survival analyses of OS in SCLC patients with M1a Disease
表 3 Cox比例风险回归模型分析对侧肺结节、恶性胸腔积液和恶性心包积液患者的OS
Table 3 Cox proportional hazards regression model analysis of OS in patients with contralateral lung nodules, malignant pleural effusion and malignant pericardial effusion
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