Proteogenomic analysis prioritises functional single nucleotide variants in cancer samples.
Proteogenomic analysis prioritises functional single nucleotide variants in cancer samples.
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DOI：
10.18632/oncotarget.21339
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发表时间：
2017-11-10
期刊：
影响因子：
--
通讯作者：
Wong JWH
中科院分区：
文献类型：
--
作者：
Ma S;Menon R;Poulos RC;Wong JWH
大规模并行DNA测序能够检测癌症样本中数千种种系和体细胞单核苷酸变体（SNV）。这些突变的功能分析通常通过计算机预测进行，很少进行进一步的下游实验验证。在这里，我们研究了使用基于质谱的蛋白质组学数据进一步注释SNV在癌症样本中的功能的潜力。来自Jurkat细胞的RNA-seq和全基因组测序（WGS）数据用于构建含有肽的单氨基酸变体（SAAV）的定制数据库，并在两个Jurkat蛋白质组学数据集中鉴定了超过1，000种此类肽。该分析使得能够在蛋白质水平上检测剪接调节因子YTHDC 1的截短形式。为了进一步扩展功能注释，分析了Jurkat磷酸蛋白质组学数据集，鉴定了463个含有磷酸肽的SAAV。在这些磷酸肽中，发现24种SAAV通过产生磷酸化位点或激酶识别基序直接影响磷酸化事件。我们确定了一个新的磷酸化位点创建的SAAV剪接因子SF 3B 1，一种蛋白质，经常突变的白血病。据我们所知，这是第一项使用磷酸化蛋白质组学数据直接鉴定SAAV产生磷酸化位点所产生的新磷酸化事件的研究。我们的研究揭示了影响Jurkat细胞中剪接途径的多个功能突变，并证明了整合蛋白基因组学分析对癌症中SNV的高通量功能注释的潜在益处。
Massively parallel DNA sequencing enables the detection of thousands of germline and somatic single nucleotide variants (SNVs) in cancer samples. The functional analysis of these mutations is often carried out through in silico predictions, with further downstream experimental validation rarely performed. Here, we examine the potential of using mass spectrometry-based proteomics data to further annotate the function of SNVs in cancer samples. RNA-seq and whole genome sequencing (WGS) data from Jurkat cells were used to construct a custom database of single amino acid variant (SAAV) containing peptides and identified over 1,000 such peptides in two Jurkat proteomics datasets. The analysis enabled the detection of a truncated form of splicing regulator YTHDC1 at the protein level. To extend the functional annotation further, a Jurkat phosphoproteomics dataset was analysed, identifying 463 SAAV containing phosphopeptides. Of these phosphopeptides, 24 SAAVs were found to directly impact the phosphorylation event through the creation of either a phosphorylation site or a kinase recognition motif. We identified a novel phosphorylation site created by a SAAV in splicing factor SF3B1, a protein that is frequently mutated in leukaemia. To our knowledge, this is the first study to use phosphoproteomics data to directly identify novel phosphorylation events arising from the creation of phosphorylation sites by SAAVs. Our study reveals multiple functional mutations impacting the splicing pathway in Jurkat cells and demonstrates potential benefits of an integrative proteogenomics analysis for high-throughput functional annotation of SNVs in cancer.
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