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Article

Literature-Wide Association Studies (LWAS) for a Rare Disease: Drug Repurposing for Inflammatory Breast Cancer

BRITE Institute and Department of Pharmaceutical Sciences, North Carolina Central University, Durham, NC 27707, USA
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Authors to whom correspondence should be addressed.
Academic Editor: Giosuè Costa
Molecules 2020, 25(17), 3933; https://doi.org/10.3390/molecules25173933
Received: 2 August 2020 / Revised: 24 August 2020 / Accepted: 26 August 2020 / Published: 28 August 2020
(This article belongs to the Special Issue Computational Methods in Drug Design and Food Chemistry)
Drug repurposing is an effective means for rapid drug discovery. The aim of this study was to develop and validate a computational methodology based on Literature-Wide Association Studies (LWAS) of PubMed to repurpose existing drugs for a rare inflammatory breast cancer (IBC). We have developed a methodology that conducted LWAS based on the text mining technology Word2Vec. 3.80 million “cancer”-related PubMed abstracts were processed as the corpus for Word2Vec to derive vector representation of biological concepts. These vectors for drugs and diseases served as the foundation for creating similarity maps of drugs and diseases, respectively, which were then employed to find potential therapy for IBC. Three hundred and thirty-six (336) known drugs and three hundred and seventy (370) diseases were expressed as vectors in this study. Nine hundred and seventy (970) previously known drug-disease association pairs among these drugs and diseases were used as the reference set. Based on the hypothesis that similar drugs can be used against similar diseases, we have identified 18 diseases similar to IBC, with 24 corresponding known drugs proposed to be the repurposing therapy for IBC. The literature search confirmed most known drugs tested for IBC, with four of them being novel candidates. We conclude that LWAS based on the Word2Vec technology is a novel approach to drug repurposing especially useful for rare diseases. View Full-Text
Keywords: text mining; Word2Vec; rare diseases; IBC; inflammatory breast cancer; drug repurposing text mining; Word2Vec; rare diseases; IBC; inflammatory breast cancer; drug repurposing
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MDPI and ACS Style

Ji, X.; Jin, C.; Dong, X.; Dixon, M.S.; Williams, K.P.; Zheng, W. Literature-Wide Association Studies (LWAS) for a Rare Disease: Drug Repurposing for Inflammatory Breast Cancer. Molecules 2020, 25, 3933. https://doi.org/10.3390/molecules25173933

AMA Style

Ji X, Jin C, Dong X, Dixon MS, Williams KP, Zheng W. Literature-Wide Association Studies (LWAS) for a Rare Disease: Drug Repurposing for Inflammatory Breast Cancer. Molecules. 2020; 25(17):3933. https://doi.org/10.3390/molecules25173933

Chicago/Turabian Style

Ji, Xiaojia, Chunming Jin, Xialan Dong, Maria S. Dixon, Kevin P. Williams, and Weifan Zheng. 2020. "Literature-Wide Association Studies (LWAS) for a Rare Disease: Drug Repurposing for Inflammatory Breast Cancer" Molecules 25, no. 17: 3933. https://doi.org/10.3390/molecules25173933

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