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一种用于鉴定透明细胞肾细胞癌(ccRCC)中PBRM1截短突变新功能后果的综合基因组学方法。

An integrative genomics approach for identifying novel functional consequences of PBRM1 truncated mutations in clear cell renal cell carcinoma (ccRCC).

作者信息

Wang Yuanyuan, Guo Xingyi, Bray Michael J, Ding Zhiyong, Zhao Zhongming

机构信息

Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN, 37203, USA.

Division of Epidemiology, Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN, 37232, USA.

出版信息

BMC Genomics. 2016 Aug 22;17 Suppl 7(Suppl 7):515. doi: 10.1186/s12864-016-2906-9.

DOI:10.1186/s12864-016-2906-9
PMID:27556922
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5001239/
Abstract

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer. Recent large-scale next-generation sequencing analyses reveal that PBRM1 is the second most frequently mutated gene harboring many truncated mutations and has a suspected tumor suppressor role in ccRCC. However, the biological consequences of PBRM1 somatic mutations (e.g., truncated mutations) that drive tumor progression in ccRCC remain unclear.

METHODS

In this study, we proposed an integrative genomics approach to explore the functional consequences of PBRM1 truncated mutations in ccRCC by incorporating somatic mutations, mRNA expression, DNA methylation, and microRNA (miRNA) expression profiles from The Cancer Genome Atlas (TCGA). We performed a systematic analysis to detect the differential molecular features in a total of 11 ccRCC samples harboring PBRM1 truncated mutations from the 33 "pan-negative" ccRCC samples. We excluded the samples that had any of the five high-confidence driver genes (VHL, BAP1, SETD2, PTEN and KDM5C) reported in ccRCC to avoid their possible influence in our results.

RESULTS

We identified 613 differentially expressed genes (128 up-regulated and 485 down-regulated genes using cutoff |log2FC| > 1 and p < 0.05) in PBRM1 mutated group versus "pan-negative" group. The gene function enrichment analysis revealed that down-regulated genes were significantly enriched in extracellular matrix organization (adjusted p = 2.05 × 10(-7)), cell adhesion (adjusted p = 2.85 × 10(-7)), and ion transport (adjusted p = 9.97 × 10(-6)). Surprisingly, 26 transcriptional factors (TFs) genes including HOXB9, PAX6 and FOXC1 were found to be significantly differentially expressed (23 over expressed TFs and three lower expressed TFs) in PBRM1 mutated group compared with "pan-negative" group. In addition, we identified 1405 differentially methylated CpG sites (targeting 1308 genes, ||log2FC| > 1, p < 0.01) and 185 significantly altered microRNAs (|log2FC| > 1, p < 0.05) associated with truncated PBRM1 mutations. Our integrative analysis suggested that methylation and miRNA alterations were likely the downstream events associated with PBRM1 truncation mutations.

CONCLUSIONS

In summary, this study provided some important insights into the understanding of tumorigenesis driven by PBRM1 truncated mutations in ccRCC. The approach may be applied to many driver genes in various cancers.

摘要

背景

透明细胞肾细胞癌(ccRCC)是最常见的肾癌类型。近期大规模的下一代测序分析显示,PBRM1是第二常见的发生许多截短突变的基因,并且在ccRCC中具有疑似肿瘤抑制作用。然而,在ccRCC中驱动肿瘤进展的PBRM1体细胞突变(例如截短突变)的生物学后果仍不清楚。

方法

在本研究中,我们提出了一种整合基因组学方法,通过纳入来自癌症基因组图谱(TCGA)的体细胞突变、mRNA表达、DNA甲基化和微小RNA(miRNA)表达谱,来探索ccRCC中PBRM1截短突变的功能后果。我们进行了系统分析,以检测33个“全阴性”ccRCC样本中总共11个携带PBRM1截短突变的ccRCC样本的差异分子特征。我们排除了ccRCC中报道的五个高可信度驱动基因(VHL、BAP1、SETD2、PTEN和KDM5C)中任何一个发生突变的样本,以避免它们对我们的结果产生可能的影响。

结果

我们在PBRM1突变组与“全阴性”组中鉴定出613个差异表达基因(使用|log2FC|>1和p<0.05的截断值,128个上调基因和485个下调基因)。基因功能富集分析显示,下调基因在细胞外基质组织(校正p=2.05×10(-7))、细胞粘附(校正p=2.85×10(-7))和离子转运(校正p=9.97×10(-6))中显著富集。令人惊讶的是,与“全阴性”组相比,在PBRM1突变组中发现26个转录因子(TFs)基因包括HOXB9、PAX6和FOXC1显著差异表达(23个TFs基因表达上调,3个TFs基因表达下调)。此外,我们鉴定出1405个差异甲基化的CpG位点(靶向1308个基因,||log2FC|>1,p<0.01)和185个与截短的PBRM1突变相关的显著改变的微小RNA(|log2FC|>1,p<0.05)。我们的整合分析表明,甲基化和miRNA改变可能是与PBRM1截短突变相关的下游事件。

结论

总之,本研究为理解ccRCC中由PBRM1截短突变驱动的肿瘤发生提供了一些重要见解。该方法可能适用于各种癌症中的许多驱动基因。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/527a/5001239/e1cc1c4f48dc/12864_2016_2906_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/527a/5001239/a4744d62898c/12864_2016_2906_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/527a/5001239/4c7b5f053bd6/12864_2016_2906_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/527a/5001239/528576a0ab78/12864_2016_2906_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/527a/5001239/dc8302e44d73/12864_2016_2906_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/527a/5001239/efe6b1552da4/12864_2016_2906_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/527a/5001239/e1cc1c4f48dc/12864_2016_2906_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/527a/5001239/a4744d62898c/12864_2016_2906_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/527a/5001239/4c7b5f053bd6/12864_2016_2906_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/527a/5001239/528576a0ab78/12864_2016_2906_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/527a/5001239/dc8302e44d73/12864_2016_2906_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/527a/5001239/efe6b1552da4/12864_2016_2906_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/527a/5001239/e1cc1c4f48dc/12864_2016_2906_Fig6_HTML.jpg

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