Multifactorial Deep Learning Reveals Pan-Cancer Genomic Tumor Clusters with Distinct Immunogenomic Landscape and Response to Immunotherapy.
Feng XieJianjun ZhangJiayin WangAlexandre ReubenWei XuXin YiFrederick S VarnYongsheng YeJunwen ChengMiao YuYue WangYufeng LiuPeng DuKe MaXin MaPenghui ZhouShengli YangYaobing ChenGuoping WangXuefeng XiaZhongxing LiaoJohn Victor HeymachIgnacio I WistubaP Andrew FutrealKai YeChao ChengTian XiaPublished in: Clinical cancer research : an official journal of the American Association for Cancer Research (2020)
Our study provides a proof for principle that deep learning modeling may have the potential to discover intrinsic statistical cross-modality correlations of multifactorial input data to dissect the molecular mechanisms underlying primary resistance to immunotherapy, which likely involves multiple factors from both the tumor and host at different molecular levels.