Department of Anesthesiology, Women's Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
Department of Pathology, Women's Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
Cancer Med. 2021 Mar;10(6):2063-2074. doi: 10.1002/cam4.3799. Epub 2021 Feb 23.
To investigate novel biomarker for diagnosis of cervical cancer, we analyzed the datasets in Gene Expression Omnibus (GEO) and confirmed the candidate biomarker in patient sample.
We collected major datasets of cervical cancer in GEO, and analyzed the differential expression of normal and cancer samples online with GEO2R and tested the differences, then focus on the GSE63514 to screen the target genes in different histological grades by using the R-Bioconductor package and R-heatmap. Then human specimens from the cervix in different histological grades were used to confirm the top 8 genes expression by immunohistochemical staining using Ki67 as a standard control.
We identified genes differentially expressed in normal and cervical cancer, 274 upregulated genes and 206 downregulated genes. After intersection with GSE63514, we found the obvious tendency in different histological grades. Then we screened the top 24 genes, and confirmed the top 8 genes in human cervix tissues. Immunohistochemical (IHC) results confirmed that keratin 17 (KRT17) was not expressed in normal cervical tissues and was over-expressed in cervical cancer. Cysteine-rich secretory protein-2 (CRISP2) was less expressed in high-grade squamous intraepithelial lesions (HSILs) than in other histological grades.
For the good repeatability and consistency of KRT17 and CRISP2, they may be good candidate biomarkers. Combined analysis of KRT17, CRISP2 expression at both genetic and protein levels can determine different histological grades of cervical squamous cell carcinoma. Such combined analysis is capable of improving diagnostic accuracy of cervical cancer.
为了寻找新的宫颈癌诊断生物标志物，我们分析了基因表达数据库（GEO）中的数据集，并在患者样本中验证了候选生物标志物。
我们收集了 GEO 中主要的宫颈癌数据集，通过 GEO2R 在线分析正常和癌症样本的差异表达，并测试了差异，然后重点关注 GSE63514，使用 R-Bioconductor 包和 R-heatmap 筛选不同组织学分级的靶基因。然后用人宫颈不同组织学分级的标本，通过免疫组化染色（Ki67 作为标准对照）验证前 8 个基因的表达。
我们鉴定了正常和宫颈癌组织中差异表达的基因，有 274 个上调基因和 206 个下调基因。与 GSE63514 交叉后，我们发现了不同组织学分级之间的明显趋势。然后我们筛选了前 24 个基因，并在人宫颈组织中验证了前 8 个基因。免疫组化（IHC）结果证实角蛋白 17（KRT17）在正常宫颈组织中不表达，而在宫颈癌中过度表达。富含半胱氨酸的分泌蛋白 2（CRISP2）在高级别鳞状上皮内病变（HSIL）中的表达低于其他组织学分级。
由于 KRT17 和 CRISP2 的良好可重复性和一致性，它们可能是良好的候选生物标志物。在基因和蛋白质水平上联合分析 KRT17 和 CRISP2 的表达可以确定宫颈鳞状细胞癌的不同组织学分级。这种联合分析能够提高宫颈癌的诊断准确性。
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