CN117334325A - 一种lcat在肝细胞癌诊断、治疗和预测复发的应用 - Google Patents
一种lcat在肝细胞癌诊断、治疗和预测复发的应用 Download PDFInfo
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Abstract
本发明属于医疗诊断、治疗和预测复发技术领域，提供了一种LCAT在肝细胞癌诊断、治疗和预测复发的应用，首先提取GEO数据库中KEGG代谢相关基因数据集并进行处理，接着使用LASSO回归算法基于KEGG代谢相关基因集在GEO数据库整合数据集并构建风险评估模型，然后与接受手术的肝癌病人的术后肿瘤和周围正常组织转录组测序数据进行差异分析的结果取交集；本发明通过结合GEO公共数据库分析发现LCAT在肝癌组织中低表达，与病人的不良预后相关；并且LCAT在肝癌组织和正常组织中呈现显著差异。进一步，通过临床肝癌病人组织样本，证明可以将LCAT作为诊断、治疗和预测复发的分子标志物在临床中应用。
Description
技术领域
本发明属于医疗诊断、治疗和预测复发技术领域，具体地说是一种LCAT在肝细胞癌诊断、治疗和预测复发的应用。
背景技术
在我国，超过90％的原发性肝癌(以下简称“肝癌”)由乙型肝炎病毒(hepatitis Bvirus,HBV)引起的慢性肝病导致肝硬化发展而来，近年来，我国肝癌的病因结构虽然有所变化，但是主要仍与HBV的感染相关。HBV感染引起的肝癌通常经历了“炎症-肝硬化-肝癌”三个阶段的变化。由于肝癌起病隐匿，且病情进展迅速，多数病人在出现不适症状就诊时已经处于无法根治性切除的中晚期肝癌，而这些肝癌病人的治疗手段较为匮乏，病人接受治疗后容易出现进展和转移，整体疗效不尽如人意，总体中位总生存时间仅为12个月左右。
手术切除是肝癌病人获得长期生存的主要手段，随着近年来手术技术和相关手术器材的进步，越来越多之前视为手术“禁区”的不能手术的肝癌病人有机会接受手术切除实现长期生存；
然而，即使能够成功接受手术，这些病人的术后复发率也显著高于早期的肝癌病人；因此，深入阐述这类肝癌病人术后的复发机制，筛选和鉴定抑制肿瘤复发和进展的靶向基因，将有助于进一步改善肝癌病人的长期生存和生活质量。卵磷脂胆固醇酰基转移酶(LCAT)是包括人在内的哺乳动物体内广泛存在的一种脂质代谢相关的酶，也是唯一能够酯化血浆中胆固醇并协助将多余胆固醇从血液和组织转运至肝脏的酶，其缺乏可能会导致一系列代谢相关的疾病。在肝癌中，LCAT被报道在肝癌组织中低表达与肿瘤不良预后相关，可能提示其作为抑癌基因在肝癌的进展中发挥着相关作用。
发明内容
为了解决上述技术问题，本发明提供一种LCAT在肝细胞癌诊断、治疗和预测复发的应用，以解决现有技术中存在的问题。
一种LCAT在肝细胞癌诊断、治疗和预测复发的应用，包括以下步骤：
S1、首先提取GEO数据库并整合；
S2、接着使用LASSO回归算法基于KEGG代谢相关基因集在GEO数据库整合数据集中构建风险评估模型；
S3、然后与接受手术的肝癌病人的术后肿瘤和周围正常组织转录组测序数据进行差异分析的结果取交集，筛选并鉴定出LCAT作为肝癌病人术后高危复发基因；
S4、然后通过公共数据库分析和小鼠皮下瘤模型发现LCAT的高表达能够激活TIME中的T细胞和NK细胞并发挥抑制肿瘤的作用，并且通过进一步探究鉴定出了TAMs作为关键的抗原递呈细胞(APCs)发挥了激活免疫效应细胞的作用；
S5、最后结合前期研究成果选择MNK激酶家族进一步分析，并结合TCGA公共数据库分析发现MNK1在肝癌组织中高表达，得到最终结论。
优选的，所述S1中具体步骤如下：
S11、首先提取GEO数据库中的数据并进行整合；
S12、接着将得到的数据集进行数据集划分，数据集划分应该遵循训练集、验证集和测试集的比例6:1:1。
优选的，在S2中，构建风险评估模型应该遵循风险的概率、影响程度和可能性中的一种或多种。
与现有技术相比，本发明具有如下有益效果：
本发明通过结合GEO公共数据库分析发现LCAT在肝癌组织中低表达，与病人的不良预后相关；并且LCAT在肝癌组织和正常组织中呈现显著差异。进一步，通过临床肝癌病人组织样本，证明可以将LCAT作为诊断、治疗和预测复发的分子标志物在临床中应用。
附图说明
图1为使用LASSO回归算法基于KEGG代谢相关基因集在GEO数据库整合数据集构建风险评估模型用于筛选LCAT作为肝癌复发相关基因的系数分布图。
图2为使用PCR检测LCAT在正常肝脏组织和肝癌组织中的表达水平并进行统计学分析的箱型图。
图3为使用PCR检测接受肝动脉灌注FOLFOX方案的晚期肝癌病人不同肿瘤反应情况(RECIST标准)中，LCAT表达量的柱状图及统计学分析图。
图4为根据LCAT表达量高低分析肝癌术后病人无复发生存期的Kaplan-Meier曲线以及使用Log-rank test进行统计学分析图。
具体实施方式
下面结合附图和实施例对本发明的实施方式作进一步详细描述。以下实施例用于说明本发明，但不能用来限制本发明的范围。
如图1-图4所示：
实施例：本发明提供一种LCAT在肝细胞癌诊断、治疗和预测复发的应用，包括以下步骤：
S1、首先提取GEO数据库并整合；
S2、接着使用LASSO回归算法基于KEGG代谢相关基因集在GEO数据库整合数据集中构建风险评估模型；
S3、然后与接受手术的肝癌病人的术后肿瘤和周围正常组织转录组测序数据进行差异分析的结果取交集，筛选并鉴定出LCAT作为肝癌病人术后高危复发基因；
S4、然后通过公共数据库分析和小鼠皮下瘤模型发现LCAT的高表达能够激活TIME中的T细胞和NK细胞并发挥抑制肿瘤的作用，并且通过进一步探究鉴定出了TAMs作为关键的抗原递呈细胞(APCs)发挥了激活免疫效应细胞的作用；
S5、最后结合前期研究成果选择MNK激酶家族进一步分析，并结合TCGA公共数据库分析发现MNK1在肝癌组织中高表达，得到最终结论。
由上可知，通过结合GEO公共数据库分析发现LCAT在肝癌组织中低表达，与病人的不良预后相关；并且LCAT在肝癌组织和正常组织中呈现显著差异。
基于上述研究基础，我们可以提出：在肝癌病人中，LCAT可以作为诊断、治疗和预测复发的分子标志物在临床中应用。
具体的，LASSO的回归算法是在回归系数的绝对值之和小于一个常数的约束条件下，使残差平方和最小化，从而能够产生某些严格等于0的回归系数，得到可以解释的模型，其数学表达式如下:
其中，t>0，是调整参数，通过控制调整参数t可以实现对总体回归系数的压缩。t值的确定可以利用Efron和Tibshirani(1993)提出的交叉验证法来估计。这个数学表达式还等价于最小化下述惩罚最小二乘法:
其中，a与t一一对应，可以互相转换。LASSO方法的主要优势在于其对参数估计较大的变量压缩较小，而参数估计较小的变量压缩成0，并且LASSO分析的参数估计具有连续性,适用于高维数据的模型选择.Tibshirani在2005年提出了Fused LASSO方法,这个估计方法满足了模型系数以及系数差分的稀疏性，使得邻近系数间更加平滑。
由上可知，LASSO回归算法在模型系数绝对值之和小于某常数的条件下，谋求残差平方和最小，在变量选取方面的效果优于逐步回归、主成分回归、岭回归、偏最小二乘等，能较好的克服传统方法在模型选取上的不足，可以精准的构建风险评估模型。
具体的，构建风险评估模型应该遵循风险的概率、影响程度和可能性中的一种或多种，下面将构建风险评估模型应该遵循的原则进行配比，并进行肝细胞癌诊断、治疗和预测，得到下表：
由上表可知，该LCAT在肝细胞癌诊断、治疗和预测复发的构建模型的效果及应用效果较好。
下面针对LCAT在肝细胞癌诊断、治疗和预测复发的应用进行具体的实验：
1、LCAT在肝细胞癌诊断中的应用
选取100例组织样本(肝癌组织50例，正常肝组织50例)进行实验分析，每一例样本的LCAT表达量用log2(TPM+1)标准化后在图中以小提琴图形式展现，不同组别的LCAT表达量形成的小提琴图以左右来区分，肝癌组织的小提琴图在右侧，正常组织的小提琴图在左侧，结果如图2；
由图2可知，肝癌组织中LCAT的表达量明显低于正常肝组织，以上结果表明，肝癌组织中LCAT表达量明显低于正常肝组织，提示LCAT表达量可以作为辅助诊断肝癌的分子标志物。
2、LCAT在肝细胞癌治疗中的应用
发明人发现在使用肝动脉灌注FOLFOX方案的晚期肝癌病人中，LCAT表达量显著影响治疗的疗效,LCAT表达量高的病人对治疗反应的总体评价明显优于LCAT表达量低的病人；方法：选取100例肝细胞癌晚期病人，提取这批病人肝癌行肝动脉灌注化疗治疗前穿刺标本的组织RNA,行RNA测序根据肝动脉灌注化疗治疗后肿瘤反应情况(RECIST标准)分为肿瘤进展(PD)组与非肿瘤进展(PR)组，比较两组病人的临床资料与肿瘤组织中LCAT的mRNA水平的差异。将两组病人LCAT标准化后的表达量以柱状图的方式呈现，结果如图3；
由图3可知,两组病人LCAT的表达量存在显著性差异，PR组病人的LCAT表达量显著高于PD组病人的LCAT表达量；以上结果说明晚期肝癌行肝动脉灌注化疗FOLFOX方案的病人中，LCAT表达量高的病人的治疗效果更显著。
3、LCAT在肝细胞癌预测复发中的应用
LCAT表达量与中晚期肝癌病人接受手术切除后的预后相关性；方法:选取363例接受手术治疗的中晚期肝癌病人检测LCAT表达量，并取LCAT表达量的中位数为界,将363例中晚期肝癌病人分为LCAT高表达和LCAT低表达两组，运用R分析LCAT表达量与中晚期肝癌病人术后无复发生存之间的关系，得到图4：
由图4可知:统计分析结果显示LCAT表达量与肝癌术后病人的无复发生存期呈显著正相关(p<0.001),LCAT表达量高的病人明确指示较好的预后；因此，LCAT表达量可作为预测中晚期肝癌病人手术治疗预后的潜在分子标志物。
本发明的实施例是为了示例和描述起见而给出的，尽管上面已经示出和描述了本发明的实施例，可以理解的是，上述实施例是示例性的，不能理解为对本发明的限制，本领域的普通技术人员在本发明的范围内可以对上述实施例进行变化、修改、替换和变型。
Claims (3)
1.一种LCAT在肝细胞癌诊断、治疗和预测复发的应用，其特征在于：包括以下步骤：
S1、首先提取GEO数据库中KEGG代谢相关基因数据集并进行处理；
S2、接着使用LASSO回归算法基于KEGG代谢相关基因集在GEO数据库整合数据集并构建风险评估模型；
S3、然后与接受手术的肝癌病人的术后肿瘤和周围正常组织转录组测序数据进行差异分析的结果取交集，筛选并鉴定出LCAT作为肝癌病人术后高危复发基因；
S4、然后通过公共数据库分析和小鼠皮下瘤模型发现LCAT的高表达能够激活TIME中的T细胞和NK细胞并发挥抑制肿瘤的作用，并且通过进一步探究鉴定出了TAMs作为关键的抗原递呈细胞(APCs)发挥了激活免疫效应细胞的作用；
S5、最后结合前期研究成果选择MNK激酶家族进一步分析，并结合TCGA公共数据库分析发现MNK1在肝癌组织中高表达，得到最终结论。
2.如权利要求1所述一种LCAT在肝细胞癌诊断、治疗和预测复发的应用，其特征在于：所述S1中具体步骤如下：
S11、首先提取GEO数据库中的数据并进行整合；
S12、接着将得到的数据集进行数据集划分，数据集划分应该遵循训练集、验证集和测试集的比例6:1:1。
3.如权利要求1所述一种LCAT在肝细胞癌诊断、治疗和预测复发的应用，其特征在于：在S2中，构建风险评估模型应该遵循风险的概率、影响程度和可能性中的一种或多种。
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