Clinical Significance of WISP-1 and VEGF-A Expression Levels in Elderly Patients with Esophageal Squamous Cell Carcinoma
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摘要:目的
探索WNT1诱导信号通路蛋白-1(WISP-1)及血管内皮生长因子-A(VEGF-A)在老年食管鳞状细胞癌(ESCC)患者中作为新的分子标志物的临床价值。
方法将老年ESCC分为65~70岁组与>70岁组,分别应用免疫组织化学染色法与RT-PCR检测WISP-1、VEGF-A蛋白与mRNA的表达。Log rank检验分析临床病理特征与食管鳞癌预后的关系。
结果ESCC组织中WISP-1阳性表达率明显高于癌旁组织(53.33% vs. 35.42%,P=0.045)、>70岁及有淋巴结转移的患者显著高于65~70岁(P=0.047)及无淋巴结转移的患者(P=0.032)。ESCC组织中VEGF-A蛋白的阳性表达率显著高于癌旁组织(50.00% vs. 20.83%,P=0.001),浸润程度T3~T4期、有淋巴结转移、TNM分期Ⅲ~Ⅳ期显著高于T1~T2、无淋巴结转移、Ⅰ~Ⅱ期患者(P=0.030、0.006、0.010)。WISP-1 mRNA和VEGF-A mRNA表达水平明显高于癌旁组织(P<0.05)。单因素分析结果表明WISP-1及VEGF-A表达水平与老年ESCC的预后相关(P<0.05),多因素分析结果表明淋巴结转移是影响老年ESCC患者预后的独立危险因素。
结论WISP-1及VEGF-A与老年ESCC患者恶性行为相关,且年龄越大,WISP-1表达越高,有作为老年ESCC新的分子标志物的潜能。
Abstract:ObjectiveTo investigate the clinical value of WNT1 inducible signaling pathway protein 1 (WISP-1) and vascular endothelial growth factor-A (VEGF-A) as novel molecular markers of esophageal squamous cell carcinoma (ESCC) in elderly patients.
MethodsElderly patients with ESCC were divided into 65-70 years old group and >70 years old group. Immunohistochemical staining and RT-PCR were used to detect the expression levels of WISP-1 and VEGF-A proteins and mRNAs, respectively. Log rank test was used to analyze correlation between clinicopathological features and prognosis of ESCC in the elderly.
ResultsThe positive expression rate of WISP-1 in ESCC tissues was significantly higher than that in para-cancer tissues (53.33% vs. 35.42%, P=0.045). The positive expression rate of WISP-1 in patients over 70 years old and with lymph node metastasis was significantly higher than that in patients aged 65-70 years and without lymph node metastasis (P=0.047 and 0.032). The positive expression rate of VEGF-A protein in ESCC tissues was significantly higher than that in para-cancer tissues (50.00% vs. 20.83%, P=0.001). The positive expression rate of VEGF-A in patients with depth of infiltration T3-T4 stage, lymph node metastasis, and TNM Ⅲ-Ⅳ stage was significantly higher than that in patients with T1-T2 stage, no lymph node metastasis, and Ⅰ-Ⅱ stage (P=0.030, 0.006, and 0.010, respectively). The mRNA expression levels of these two molecules were significantly higher in ESCC tissues than in para-cancer tissues (P<0.05), and the results of univariate analysis showed that the expression levels of WISP-1 and VEGF-A were correlated with the prognosis of ESCC in the elderly (P<0.05). The results of multivariate analysis showed that lymph node metastasis was the independent risk factor affecting the prognosis of elderly patients with ESCC.
ConclusionWISP-1 and VEGF-A are associated with malignant behavior in elderly patients with ESCC. The expression of WISP-1 increased with age, and it has potential as a novel molecular marker of ESCC in elderly patients.
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Key words:
- Elderly /
- Esophageal squamous cell carcinoma /
- WISP-1 /
- VEGF-A
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0 引言
胃癌(Gastric cancer, GC)作为全球范围内高发的恶性肿瘤之一,其5年生存率不足30%,是癌症相关死亡的重要疾病[1-2]。肿瘤免疫微环境(Tumor microenvironment, TME)以对精确诊断和个体化免疫治疗带来的影响而备受关注[3]。免疫治疗通过激活宿主天然防御系统来识别和清除肿瘤细胞,为胃癌治疗提供了新的希望[4]。然而,胃癌的复杂性和免疫系统的多样性使治疗效果存在差异,因此深入理解免疫细胞在胃癌发展和治疗中的作用机制至关重要。
本研究采用孟德尔随机化(Mendelian randomization, MR)分析方法,旨在阐明免疫细胞表型与胃癌之间的因果关系,为胃癌的预防和治疗提供新的思路和策略。
1 资料与方法
1.1 研究设计
本研究采用双向两样本孟德尔随机化分析,探究731种免疫细胞表型与胃癌之间的因果关系。MR分析旨在通过遗传变异代表风险变量,以阐明单一或多重暴露因素与单一结果之间的因果关系。值得注意的是,作为工具变量(IV),必须满足以下三个基本假设:(1)遗传变异与环境暴露紧密相关;(2)遗传变异与潜在的环境或遗传混杂因素无关;(3)遗传变异、暴露与结果之间的统计强度可估计,且遗传变异仅通过暴露途径影响结果[5-6]。本研究中的暴露与结果样本均来自人类个体,且为已发表数据的二次分析,因此无需伦理审批。
1.2 胃癌特征GWAS数据源
胃癌数据集(ebi-a-GCST90011849)从GWAS数据库(https://gwas.mrcieu.ac.uk/)获取,包含476 116名具有欧洲血统的样本(其中1 029例为胃癌样本,475 087例为对照样本),涉及24 188 662个单核苷酸多态性位点(Single-nucleotide polymorphisms, SNPs)。
1.3 免疫细胞表型GWAS数据源
本研究纳入了包含731种免疫表型的公共目录(GCST0001391至GCST0001121)的GWAS数据[7]。纳入
1757 例欧洲成年人,计算了约22万个单核苷酸多态性位点。GWAS汇总数据包括118种绝对细胞计数(AC)、389种代表表面抗原水平的中位荧光强度(MFI)、32种形态学特征(MP)和192种相对细胞计数(RC),即细胞水平的比值。1.4 工具变量的选择(IVs)
将免疫细胞表型作为暴露,在初始阈值(P<5×10−8)之下,并没有足够的SNPs达到统计学意义,为了获得更全面可靠的结果,我们参考相关文献后调整了阈值P<1×10−5来选择各种免疫细胞表型的显著SNPs[8-9]。基于欧洲千人基因组计划,使用PLINK软件中的clump程序排除了R2<0.001的工具变量。在进行反向孟德尔随机化分析时,将显著性阈值设为5×10−8。
各工具变量中SNP的F统计值计算:(1)通过公式R2=2×(1−MAF)×MAF×β2来计算R2,其中R2代表工具变量解释暴露的程度,MAF代表最小等位基因频率,β代表等位基因效应值。(2)使用公式F=R2×(N−K−1)/[K×(1−R2)]来计算F值,其中N代表总样本量,K代表工具变量数量。(3)为了排除弱工具变量偏倚,将F>10的SNP纳入MR分析[10]。
1.5 孟德尔随机化分析
采用了逆方差加权法(IVW)、加权中位数法(WM)以及MR-Egger回归等方法进行分析。IVW方法是在假设所有SNP均有效且独立的前提下,将回归截距限制为0,以结局方差的倒数作为权重进行拟合。当每个遗传变异都符合工具变量的假设时,IVW将提供最精确的结果,因此IVW的结果通常被认为是因果效应评估的金标准[11]。
本研究以IVW结果作为主要指标来评估因果效应,同时使用其他方法辅助评估MR效应。当不同方法的效应量(β值)方向与IVW一致时,表明结果稳健。运用FDR校正对IVW结果进行多重检验,当PFDR<0.05时认为免疫细胞表型与胃癌风险具有因果关系。
1.6 敏感性分析
为了评估结果的异质性和多效性,我们运用了多种方法。通过Cochran’s Q test进行异质性检验[12]。多效性则通过MR-PRESSO检验与MR-Egger回归截距项(MR-Egger intercept)来评估,当P>0.05时,表明结果不存在异质性或多效性[13]。此外,使用留一法对单个及整体效应的异质性进行分析。本研究主要在R软件(4.2.1版本)中的Two Sample MR软件包中完成。
2 结果
2.1 工具变量结果
共有731个免疫细胞表型的工具变量达到显著阈值,每个表型的工具变量数量从2~688个不等。这些免疫细胞表型工具变量的F值范围为20.88~1159.29,均符合F>10的标准,这表明本研究中使用的工具变量不太可能存在弱工具变量偏倚的问题。
2.2 免疫细胞表型与胃癌的因果关系
采用两样本MR分析,以IVW作为主要分析手段,探究免疫细胞表型与胃癌之间的因果关系。以PFDR<0.05作为判定条件时,四种免疫表型与胃癌具有因果关联。其中IgD on IgD+ B细胞、CD14- CD16- 绝对计数以及IgD+ CD24- B细胞占淋巴细胞百分比的降低与胃癌风险减少有关,而CD4-CD8- T细胞绝对计数的升高则与胃癌风险增加相关,见图1。WM和MR-Egger回归等免疫细胞表型的MR分析方法得出的结论与IVW结果基本一致。
2.3 胃癌对免疫细胞表型的影响
再次采用IVW进行反向MR分析,对731个免疫细胞表型进行探究。经过FDR校正后,以显著性水平0.05为判断标准,未发现胃癌与任何免疫细胞表型之间存在因果关系,见图2。
2.4 敏感性分析结果
在针对异质性与多效性的检验中,Cochran Q检验结果显示,与上述四种免疫细胞表型高度相关的SNP间不存在异质性(P>0.05)。MR-Egger回归的截距项分析表明,这些SNP不存在水平多效性(P>0.05)。MR-PRESSO法分析未发现与上述四种免疫细胞表型高度相关的SNP存在离群值(P>0.05),见表1。此外,留一法分析结果显示,在剔除任何一个SNP后,MR分析结果均保持稳定,无明显改变,见图3。
表 1 Cochran Q检验、MR-Egger回归、MR-PRESSO法分析结果Table 1 Results of Cochran's Q test, MR-Egger regression, and MR-PRESSO analysisExposure Cochran′s Q MR-Egger MR-PRESSO Method Q P Egger intercept P Causal estimate P IgD on IgD+ B cell IVW 15.43 0.16 0.03 0.20 −0.15 0.19 CD4-CD8- T cell Absolute Count IVW 11.10 0.44 −0.01 0.64 0.18 0.51 CD14- CD16- Absolute Count IVW 13.02 0.45 −0.01 0.17 −0.03 0.53 IgD+ CD24- B cell %lymphocyte IVW 13.61 0.56 0.02 0.49 −0.15 0.59 3 讨论
胃癌作为一种具有高度异质性的疾病,可分为弥漫型/混合型和肠型两大类型,这两种类型在临床上呈现出截然不同的结果。在肿瘤发展的动态过程中,免疫细胞扮演着重要的角色。
在胃癌的微环境中,多种免疫细胞与肿瘤细胞相互作用,共同调控肿瘤的生长、扩散和对治疗的响应。Oya等的研究强调了癌相关成纤维细胞以及免疫细胞在胃癌肿瘤微环境中的重要角色,这些细胞与胃癌细胞的交互作用对肿瘤发展具有重要影响[14]。此外,T细胞等免疫细胞在胃癌中的作用日益受到重视。Pernot等根据Lauren分类分析了进展期胃癌中的浸润及周围免疫细胞,并探讨了这些细胞的临床意义[15]。这些研究为我们理解免疫细胞在胃癌中的作用提供了新的视角。
本研究通过双向孟德尔随机化分析,深入探讨了731种免疫细胞表型与胃癌之间的关系。研究结果揭示,四种特定的免疫细胞表型与胃癌存在显著的因果联系。
具体而言,本研究发现IgD+ CD24− B细胞淋巴细胞百分比的增加与胃癌风险降低之间存在密切关联。而CD24在胃癌组织中高表达,促进细胞增殖、侵袭、转移,可能通过激活STAT3、上调钙黏蛋白、纤维连接蛋白、维生素D受体及介导EGF/EGFR信号发挥作用[16]。研究显示,CD24与非萎缩性胃炎到胃癌的病变进程相关[17],并与Hp感染有关[18-20]。
研究结果显示,CD4− CD8− T细胞绝对计数的升高则与胃癌风险增加有关。CD4− CD8−双阴性T细胞是外周T细胞的稀有亚群,其已被证明不仅存在于外周血中,还浸润到实体瘤中,如非小细胞肺癌、肝癌、神经胶质瘤和胰腺瘤[21-22]。此外,黑色素瘤患者淋巴结中CD4− CD8− T细胞数量与疾病进展相关[23]。
值得注意的是,我们还观察到IgD在IgD+ B细胞上的表达水平与胃癌风险之间的负相关[24]。而在某些疾病状态下,例如胃癌,IgD的表达水平相较正常组织会有所变化[25]。本研究发现IgD在IgD+ B细胞的升高可以降低胃癌的发病风险。
本研究存在局限性。首先,利用的是目前最新、样本量最大的GWAS数据,鉴于暴露数据与结局数据需要同一人种,我们找到的免疫细胞GWAS源于欧洲人群,目前暂时只能运用欧洲人群进行分析,可能无法完全适用于其他种族的人群;其次,部分免疫细胞表型的工具变量较少,这可能在一定程度上影响了结果的准确性;最后,受限于当前的样本量,许多免疫细胞表型与胃癌之间的联系尚未达到显著性水平。尽管如此,本研究仍然为理解胃癌的发病机制提供了新的视角,并为开发针对胃癌的新型治疗方法提供了潜在靶点。
Competing interests: The authors declare that they have no competing interests.利益冲突声明:所有作者均声明不存在利益冲突。作者贡献:李晨露:实验实施、数据分析、文献检索及论文撰写黄俊星:研究设计、选题、论文指导及修改 -
表 1 引物序列
Table 1 Primer sequence
Primers Primer sequence (5ʹ-3ʹ) WISP-1 Forword: GAGAGGTGGTCGGATCCTCT Reverse: CCAGTGGAGCTGGGGTAAAG VEGFA Forword: GCTCGGTGCTGGAATTTGAT Reverse: TCACTCACTTTGCCCCTGTC GAPDH Forword: GCACCGTCAAGGCTGAGAAC Reverse: TGGTGAAGACGCCAGTGGA 表 2 WISP-1及VEGF-A在老年ESCC组织中的表达
Table 2 Expression levels of WISP-1 and VEGF-A in elderly patients with ESCC
Group N WISP-1(n(%)) P VEGF-A(n(%)) P Positive Negative Positive Negative Cancerous tissue 90 48(53.33) 42(46.67) 0.04 45(50.00) 45(50.00) 0.001 Para-cancer tissues 48 17(35.42) 31(64.58) 10(20.83) 38(79.17) 表 3 老年ESCC组织中WISP-1及VEGF-A蛋白的表达与临床病理特征的相关性
Table 3 Correlation of WISP-1 and VEGF-A proteins expression levels in cancer tissues with clinicopathological features of elderly ESCC patients
Clinicopathological features N WISP-1(n(%)) P VEGF-A(n(%)) P Positive Negative Positive Negative Gender 0.126 0.634 Male 66 32(48.5) 34(51.5) 32(48.5) 34(51.5) Female 24 16(66.7) 80(33.3) 13(54.2) 11(45.8) Age(years) 0.047 0.267 65-70 59 27(45.8) 32(54.2) 32(54.2) 27(45.8) >70 31 21(67.7) 10(32.3) 13(41.9) 18(58.1) Tumor size(cm) 0.621 0.192 ≤4 56 31(55.4) 25(44.6) 25(44.6) 31(55.4) >4 34 17(50.0) 17(50.0) 20(58.8) 14(41.2) Depth of infiltration 0.706 0.030 T1-T2 34 19(55.9) 15(44.1) 12(35.3) 22(64.7) T3-T4 56 29(51.8) 27(48.2) 33(58.9) 23(41.1) Lymph node metastasis 0.032 0.006 Positive 43 28(65.1) 15(34.8) 28(65.1) 15(34.9) Negative 47 20(42.6) 27(57.4) 17(36.2) 30(63.8) TNM stage 0.458 0.010 Ⅰ-Ⅱ 52 26(50.0) 26(50.0) 20(38.5) 32(61.5) Ⅲ-Ⅳ 38 22(57.9) 16(42.1) 25(65.8) 13(34.2) Vascular invasion 0.073 0.655 Positive 30 12(40.0) 18(60.0) 16(53.3) 14(46.7) Negative 60 36(60.0) 24(40.0) 29(48.3) 31(51.7) Neural invasion 0.114 0.827 Positive 33 14(42.4) 19(57.6) 17(51.5) 16(48.5) Negative 57 34(59.6) 23(40.4) 28(49.1) 29(50.9) Degree of differentiation 0.852 0.813 Poor 39 22(56.4) 17(43.6) 18(46.2) 21(53.8) Moderate 38 19(50.0) 19(50.0) 20(52.6) 18(47.3) Well 13 7(53.8) 6(46.2) 7(53.8) 6(46.2) 表 4 WISP-1与VEGF-A蛋白表达的相关性
Table 4 Correlation between WISP-1 and VEGF-A protein expression levels
WISP-1(+) WISP-1(-) χ2 P VEGF-A(+) 25(27.8%) 20(22.2%) 0.179 0.673 VEGF-A(-) 23(25.6%) 22(24.4%) 表 5 老年ESCC患者总体生存期的影响因素单因素及多因素分析
Table 5 Univariate and multivariate Cox analyses of overall survival in elderly patients with ESCC
Prognostic
indexN mOS
(months)Log rank
univariateMultivariate
Cox analysisχ2 P 95%CI P WISP-1 4.712 0.030 Positive 47 44 Negative 38 VEGF-A 7.299 0.007 Positive 43 43 Negative 42 Gender 0.641 0.423 Male 62 59 Female 23 44 Age
(years)0.002 0.967 65-70 56 51 >70 29 59 Tumor
size (cm)0.102 0.749 ≤4 53 51 >4 32 56 Depth of
infiltration5.384 0.020 T1-T2 33 T3-T4 52 43 Lymph node
metastasis20.591 <0.001 2.067-7.469 <0.001 Positive 42 31 Negative 43 TNM stage 18.055 <0.001 Ⅰ-Ⅱ 48 Ⅲ-Ⅳ 37 31 Vascular
invasion0.297 0.586 Positive 29 56 Negative 56 55 Neural
invasion1.783 0.182 Positive 30 31 Negative 55 59 Degree of
differentiation6.802 0.033 Poor 37 38 Moderate 35 Well 13 61 -
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