THSD7A在宫颈癌细胞侵袭、迁移等恶性生物学行为中的研究

目的 为了探索THSD7A对宫颈癌细胞的侵袭、转移以及凋亡等生物学行为的影响。方法 对宫颈癌C33a细胞和SiHa细胞培养及转染siTHSD7A基因,采用Western blotting和RT-qPCR方法在蛋白和基因水平对其验证。后应用Transwell小室实验、流式细胞术检测THSD7A沉默后对两种宫颈癌细胞的侵袭、转移、细胞周期及凋亡的改变。结果 与空白组和阴性对照组相比,沉默THSD7A的表达后,宫颈癌C33a细胞和SiHa细胞的侵袭、迁移能力明显下降（P＜0.01）;进入S期和G2/M期细胞数目减少,凋亡比例增高（P＜0.05）。结论 提示THSD7A可能作为一种致癌基因,在宫颈癌恶性生物学行为的发展过程中起到推进作用。     

Unidentified genetic variants influence pancreatic cancer risk: an analysis of polygenic susceptibility in the PanScan study

Genome-wide association (GWA) studies have identified several pancreatic cancer (PanCa) susceptibility loci. Methods for assessment of polygenic susceptibility can be employed to detect the collective effect of additional association signals for PanCa. Using data on 492,651 autosomal single nucleotide polymorphisms (SNPs) from the PanScan GWA study (2,857 cases, 2,967 controls), we employed polygenic risk score (PRS) cross-validation (CV) methods to (a) confirm the existence of unidentified association signals, (b) assess the predictive value of PRSs, and (c) assess evidence for polygenic effects in specific genomic locations (genic vs. intergenic). After excluding SNPs in known PanCa susceptibility regions, we constructed PRS models using a training GWA dataset and then tested the model in an independent testing dataset using fourfold CV. We also employed a "power-replication" approach, where power to detect SNP associations was calculated using a training dataset, and power was tested for association with "replication status" in a testing dataset. PRS scores constructed using ≥ 10% of genome-wide SNPs showed significant association with PanCa (P< 0.05) across the majority of CV analyses. Associations were stronger for PRSs restricted to genic SNPs compared to intergenic PRSs. The power-replications approach produced weaker associations that were not significant when restricting to SNPs with low pairwise linkage disequilibrium, whereas PRS results were robust to such restrictions. Although the PRS approach will not dramatically improve PanCa prediction, it provides strong evidence for unidentified association signals for PanCa. Our results suggest that focusing association studies on genic regions and conducting larger GWA studies can reveal additional PanCa susceptibility loci.