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

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.

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CRISPR screens identify gene targets and drug repositioning opportunities at breast cancer risk loci

10.1101/2021.09.07.459221 ◽

2021 ◽

Author(s):

Natasha K Tuano ◽

Jonathan Beesley ◽

Murray Manning ◽

Wei Shi ◽

Luis Malver-Ortega ◽

...

Keyword(s):

Breast Cancer ◽

Cancer Risk ◽

Drug Repositioning ◽

Association Studies ◽

Drug Repurposing ◽

Genome Wide Association Studies ◽

Risk Variants ◽

Genome Wide ◽

Causal Variants ◽

Cancer Phenotypes

Genome-wide association studies (GWAS) have identified >200 loci associated with breast cancer (BC) risk. The majority of candidate causal variants (CCVs) are in non-coding regions and are likely to modulate cancer risk by regulating gene expression. We recently developed a scoring system, INQUISIT, to predict candidate risk genes at BC-risk loci. Here, we used pooled CRISPR activation and suppression screens to validate INQUISIT predictions, and to define the cancer phenotypes they mediate. We measured proliferation in 2D, 3D, and in immune-deficient mice, as well as the effect on the DNA damage response. We performed 60 CRISPR screens and identified 21 high-confidence INQUISIT predictions that mediate a cancer phenotype. We validated the direct regulation of a subset of genes by BC-risk variants using HiCHIP and CRISPRqtl. Furthermore, we show the utility of expression profiling for drug repurposing against these targets. We provide a platform for identifying gene targets of risk variants, and lay a blueprint of interventions for BC risk reduction and treatment.

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CRISPR screens identify gene targets and drug repositioning opportunities at breast cancer risk loci

10.21203/rs.3.rs-1223972/v1 ◽

2022 ◽

Author(s):

Joseph Rosenbluh ◽

Natasha Tuano ◽

Jonathan Beesley ◽

Murray Manning ◽

Wei Shi ◽

...

Keyword(s):

Breast Cancer ◽

Cancer Risk ◽

Target Genes ◽

Drug Repositioning ◽

Association Studies ◽

Drug Repurposing ◽

Genome Wide Association Studies ◽

Risk Variants ◽

Breast Cells ◽

Cancer Phenotypes

Abstract Genome-wide association studies (GWAS) have identified >200 loci associated with breast cancer (BC) risk. The majority of candidate causal variants (CCVs) are in non-coding regions and likely modulate cancer risk by regulating gene expression. However, pinpointing the exact target of the association and identifying the phenotype it mediates is a major challenge in the interpretation and translation of GWAS. Here, we used pooled CRISPR activation and suppression screens to evaluate predicted GWAS target genes, and to define the cancer phenotypes they mediate. We measured proliferation in 2D, 3D, and in immune-deficient mice, as well as the effect on DNA repair. We performed 60 CRISPR screens and identified 21 genes predicted with high confidence to be GWAS targets that drive a cancer phenotype by driving a proliferation or DNA damage response in breast cells. We validated the regulation of a subset of these genes by BC-risk variants, and show the utility of expression profiling for drug repurposing. We provide a platform for identifying gene targets of risk variants, and present a blueprint of interventions for BC risk reduction and treatment.

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