Identifying common transcriptome signatures of cancer by interpreting deep learning models.
Identifying common transcriptome signatures of cancer by interpreting deep learning models.
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DOI：
10.1186/s13059-022-02681-3
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发表时间：
2022-05-17
期刊：
影响因子：
12.3
通讯作者：
中科院分区：
文献类型：
--
作者：
癌症是一组以不受控制的细胞增殖和周围组织侵袭为特征的疾病。许多与癌症遗传相关或被证明直接促进肿瘤发生的基因在肿瘤类型之间差异很大，但与核心癌症途径相关的常见基因特征也已被识别。然而，尚不清楚是否存在其他组基因或转录组特征，这些基因或转录组特征在癌症生物学中不太为人所知，但在几种癌症类型中通常也不受管制。在这里，我们使用来自 19 种正常组织类型和 18 种实体瘤类型的 13,461 个 RNA-seq 样本，基于蛋白质编码基因表达、lncRNA 表达或剪接连接使用来训练三个前馈神经网络，以不可知的方式识别癌症类型之间常见的转录组特征，以区分正常样本和肿瘤样本。所有三种模型都识别肿瘤中一致的转录组特征。对从我们的模型中提取的归因值的分析表明，在癌症中通常通过表达或剪接变异而改变的基因受到强烈的进化和选择性限制。重要的是，我们发现构成癌症转录组特征的基因并不经常受到突变或基因组改变的影响，并且它们的功能与与癌症遗传相关的基因有很大不同。我们的结果强调，RNA 加工基因的失调和异常剪接是核心癌症途径可能在大量实体瘤类型中汇聚的普遍特征。在线版本包含可在 (10.1186/s13059-022-02681-3) 获取的补充材料。
Cancer is a set of diseases characterized by unchecked cell proliferation and invasion of surrounding tissues. The many genes that have been genetically associated with cancer or shown to directly contribute to oncogenesis vary widely between tumor types, but common gene signatures that relate to core cancer pathways have also been identified. It is not clear, however, whether there exist additional sets of genes or transcriptomic features that are less well known in cancer biology but that are also commonly deregulated across several cancer types. Here, we agnostically identify transcriptomic features that are commonly shared between cancer types using 13,461 RNA-seq samples from 19 normal tissue types and 18 solid tumor types to train three feed-forward neural networks, based either on protein-coding gene expression, lncRNA expression, or splice junction use, to distinguish between normal and tumor samples. All three models recognize transcriptome signatures that are consistent across tumors. Analysis of attribution values extracted from our models reveals that genes that are commonly altered in cancer by expression or splicing variations are under strong evolutionary and selective constraints. Importantly, we find that genes composing our cancer transcriptome signatures are not frequently affected by mutations or genomic alterations and that their functions differ widely from the genes genetically associated with cancer. Our results highlighted that deregulation of RNA-processing genes and aberrant splicing are pervasive features on which core cancer pathways might converge across a large array of solid tumor types. The online version contains supplementary material available at (10.1186/s13059-022-02681-3).
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影响因子：
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影响因子：
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作者：
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DOI：
10.1158/1078-0432.ccr-13-1252
发表时间：
2014-01-15
期刊：
Clinical cancer research : an official journal of the American Association for Cancer Research
影响因子：
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作者：
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通讯作者：
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