Functionally Enigmatic Genes in Cancer: Using TCGA Data to Map the Limitations of Annotations
Functionally Enigmatic Genes in Cancer: Using TCGA Data to Map the Limitations of Annotations
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DOI：
10.1038/s41598-020-60456-x
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发表时间：
2020-03-05
影响因子：
4.6
通讯作者：
Paller, Channing J.
中科院分区：
文献类型：
--
作者：
Maertens, Alexandra;Tran, Vy P.;Paller, Channing J.
癌症是一种研究相对较充分的疾病，尽管几十年来一直受到高度关注，但我们在这里使用癌症基因组图谱的数据证明，与癌症有关的大量基因研究相对较少。这些基因可能会被任何数据分析管道遗漏，例如富集分析，这完全取决于理解生物功能的注释。没有迹象表明研究的数量--由出版物的数量表示--与基因显著性的任何客观指标相关。此外，这些基因并不是随机缺失的，而是反映了我们对基因的信息是以一种有偏见的方式收集的：研究不足的基因更有可能是灵长类特异性的，而不太可能具有孟德尔遗传模式，它们往往在某些生物过程中聚集，而不是其他生物过程。虽然这可能反映了技术的局限性以及众所周知的基因往往会引起研究界更多的兴趣，但如果没有一致的努力以公正的方式研究基因，许多基因（和生物过程）将仍然不透明。
Cancer is a comparatively well-studied disease, yet despite decades of intense focus, we demonstrate here using data from The Cancer Genome Atlas that a substantial number of genes implicated in cancer are relatively poorly studied. Those genes will likely be missed by any data analysis pipeline, such as enrichment analysis, that depends exclusively on annotations for understanding biological function. There is no indication that the amount of research - indicated by number of publications - is correlated with any objective metric of gene significance. Moreover, these genes are not missing at random but reflect that our information about genes is gathered in a biased manner: poorly studied genes are more likely to be primate-specific and less likely to have a Mendelian inheritance pattern, and they tend to cluster in some biological processes and not others. While this likely reflects both technological limitations as well as the fact that well-known genes tend to gather more interest from the research community, in the absence of a concerted effort to study genes in an unbiased way, many genes (and biological processes) will remain opaque.