AUTHOR=Meng Fanlin , Zhang Kenan , Yang Changlin , Zhang Ke , Xu Quan , Ren Ruifang , Zhou Yiming , Sun Yimin , Peng Yan , Li Yanze , Guo Hongyan , Ren Yonghong , Zhao Zheng TITLE=Prognostic Pathways Guide Drug Indications in Pan-Cancers JOURNAL=Frontiers in Oncology VOLUME=12 YEAR=2022 URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2022.849552 DOI=10.3389/fonc.2022.849552 ISSN=2234-943X ABSTRACT=

Pathway-level analysis is a powerful approach enabling the interpretation of post-genomic data at a higher level than that of individual molecules. Molecular-targeted therapy focusing on cascade signaling pathways has become a new paradigm in anticancer therapy, instead of a single protein. However, the approaches to narrowing down the long list of biological pathways are limited. Here, we proposed a strategy for in silico Drug Prescription on biological pathways across pan-Cancers (CDP), by connecting drugs to candidate pathways. Applying on a list of 120 traditional Chinese medicines (TCM), we especially identified the “TCM–pathways–cancers” triplet and constructed it into a heterogeneous network across pan-cancers. Applying them into TCMs, the computational prescribing methods deepened the understanding of the efficacy of TCM at the molecular level. Further applying them into Western medicines, CDP could promote drug reposition avoiding time-consuming developments of new drugs.