Dataset Information

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

ABSTRACT: 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.

SUBMITTER: Ji X

PROVIDER: S-EPMC7504746 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

Ji Xiaojia X Jin Chunming C Dong Xialan X Dixon Maria S MS Williams Kevin P KP Zheng Weifan W

Molecules (Basel, Switzerland) 20200828 17

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 ...[more]

PMID: 32872166

Similar Datasets

Project description:Importance: There is an unprecedented need to rapidly identify safe and effective treatments for the novel coronavirus disease 2019 (COVID-19). Objective: To systematically investigate if any of the available drugs in Electronic Health Record (EHR), including prescription drugs and dietary supplements, can be repurposed as potential treatment for COVID-19. Design, Setting, and Participants: Based on a retrospective cohort analysis of EHR data, drug-wide association studies (DrugWAS) were performed on COVID-19 patients at Vanderbilt University Medical Center (VUMC). For each drug study, multivariable logistic regression with overlap weighting using propensity score was applied to estimate the effect of drug exposure on COVID-19 disease outcomes. Exposures: Patient exposure to a drug during 1-year prior to the pandemic and COVID-19 diagnosis was chosen as exposure of interest. Natural language processing was employed to extract drug information from clinical notes, in addition to the prescription drug data available in structured format. Main Outcomes and Measures: All-cause of death was selected as primary outcome. Hospitalization, admission to the intensive care unit (ICU), and need for mechanical ventilation were identified as secondary outcomes. Results: The study included 7,768 COVID-19 patients, of which 509 (6.55%) were hospitalized, 82 (1.06%) were admitted to ICU, 64 (0.82%) received mechanical ventilation, and 90 (1.16%) died. Overall, 15 drugs were significantly associated with decreased COVID-19 severity. Previous exposure to either Streptococcus pneumoniae vaccines (adjusted odds ratio [OR], 0.38; 95% CI, 0.14-0.98), diphtheria toxoid vaccine (OR, 0.39; 95% CI, 0.15-0.98), and tetanus toxoid vaccine (OR, 0.39; 95% CI, 0.15-0.98) were significantly associated with a decreased risk of death (primary outcome). Secondary analyses identified several other significant associations showing lower risk for COVID-19 outcomes: 2 vaccines (acellular pertussis, Streptococcus pneumoniae), 3 dietary supplements (turmeric extract, flaxseed extract, omega-3 fatty acids), methylprednisolone acetate, pseudoephedrine, ethinyl estradiol, estradiol, ibuprofen, and fluticasone. Conclusions and Relevance: This cohort study leveraged EHR data to identify a list of drugs that could be repurposed to improve COVID-19 outcomes. Further randomized clinical trials are needed to investigate the efficacy of the proposed drugs.

Dataset Information

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

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets