A Review of Drug Repositioning Based Chemical-induced Cell Line Expression Data

Wang, Fei; Lei, Xiujuan; Wu, Fang‐Xiang

doi:10.2174/0929867325666181101115801

“…In this study, IL-23 receptor gene variants were found to be associated with the development of psoriasis, and therefore the IL-23 receptor became a potential drug target (107). Further, based on biomedical literature, risankizumab was identified as a drug candidate because it targets the IL-23 receptor, and after clinical trials, risankizumab was indeed approved for psoriasis treatment (107,108). Signature matching, another molecular association strategy, has been applied in several cancer applications, as reviewed in Wang et al (108).…”

Section: Overview Of Drug Repurposingmentioning

confidence: 97%

“…Further, based on biomedical literature, risankizumab was identified as a drug candidate because it targets the IL-23 receptor, and after clinical trials, risankizumab was indeed approved for psoriasis treatment (107,108). Signature matching, another molecular association strategy, has been applied in several cancer applications, as reviewed in Wang et al (108). It compares patient molecular profiles to cell line profiles or another model system that were treated with drugs and assessed for a specific phenotype (e.g.., cell viability in cancer cell lines) (108).…”

Section: Overview Of Drug Repurposingmentioning

confidence: 99%

“…Signature matching, another molecular association strategy, has been applied in several cancer applications, as reviewed in Wang et al (108). It compares patient molecular profiles to cell line profiles or another model system that were treated with drugs and assessed for a specific phenotype (e.g.., cell viability in cancer cell lines) (108).…”

Section: Overview Of Drug Repurposingmentioning

confidence: 99%

See 1 more Smart Citation

Considerations and Challenges for Sex-Aware Drug Repurposing

Fisher¹,

Jones²,

Flanary³

et al. 2022

Preprint

0

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Sex differences are essential factors in disease etiology and manifestation in many diseases such as cardiovascular disease, cancer, and neurodegeneration (1). The biological influence of sex differences (including genomic, epigenetic, hormonal, immunological, and metabolic differences between males and females) and the lack of biomedical studies considering sex differences in their study design has led to several policies. For example, the National Institute of Health’s (NIH) sex as a biological variable (SABV) and Sex and Gender Equity in Research (SAGER)) policies to motivate researchers to consider sex differences (2). However, drug repurposing, a promising alternative to traditional drug discovery by identifying novel uses for FDA-approved drugs, lacks sex-aware methods that can improve the identification of drugs that have sex-specific responses (1,3–5). Sex-aware drug repurposing methods either select drug candidates that are more efficacious in one sex or deprioritize drug candidates based on if they are predicted to cause a sex-bias adverse event (SBAE), unintended therapeutic effects that are more likely to occur in one sex. Computational drug repurposing methods are encouraging approaches to develop for sex-aware drug repurposing because they can prioritize sex-specific drug candidates or SBAEs at lower cost and time than traditional drug discovery. Sex-aware methods currently exist for clinical, genomic, and transcriptomic information (3,6,7). They have not expanded to other data types, such as DNA variation, which has been beneficial in other drug repurposing methods that do not consider sex (8). Additionally, some sex-aware methods suffer from poorer performance because a disproportionate number of male and female samples are available to train computational methods (3). However, there is development potential for several different categories (i.e., data mining, ligand binding predictions, molecular associations, and networks). Low-dimensional representations of molecular association and network approaches are also especially promising candidates for future sex-aware drug repurposing methodologies because they reduce the multiple hypothesis testing burden and capture sex-specific variation better than the other methods (9,10). Here we review how sex influences drug response, the current state of drug repurposing including with respect to sex-bias drug response, and how model organism study design choices influence drug repurposing validation.

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“…In this study, IL-23 receptor gene variants were found to be associated with the development of psoriasis, and therefore the IL-23 receptor became a potential drug target (87). Further, based on biomedical literature, risankizumab was identified as a drug candidate because it targets the IL-23 receptor, and after clinical trials, risankizumab was indeed approved for psoriasis treatment (87,88). Signature matching, another molecular association strategy, has been applied in several cancer applications, as reviewed in Wang et al (88).…”

Section: Overview Of Drug Repurposingmentioning

confidence: 97%

“…Further, based on biomedical literature, risankizumab was identified as a drug candidate because it targets the IL-23 receptor, and after clinical trials, risankizumab was indeed approved for psoriasis treatment (87,88). Signature matching, another molecular association strategy, has been applied in several cancer applications, as reviewed in Wang et al (88). It compares patient molecular profiles to cell line profiles or another model system that were treated with drugs and assessed for a specific phenotype (e.g.., cell viability in cancer cell lines) (88).…”

Section: Overview Of Drug Repurposingmentioning

confidence: 99%

Considerations and Challenges for Sex-Aware Drug Repurposing

Fisher¹,

Jones²,

Flanary³

et al. 2021

Preprint

View full text Add to dashboard Cite

Sex differences are essential factors in disease etiology and manifestation in many diseases such as cardiovascular disease, cancer, and neurodegeneration (1). The biological influence of sex differences (including genomic, epigenetic, hormonal, immunological, and metabolic differences between males and females) and the lack of biomedical studies considering sex differences in their study design has led to several policies. For example, the National Institute of Health’s (NIH) sex as a biological variable (SABV) and Sex and Gender Equity in Research (SAGER)) policies to motivate researchers to consider sex differences (2). However, drug repurposing, a promising alternative to traditional drug discovery by identifying novel uses for FDA-approved drugs, lacks sex-aware methods that can improve the identification of drugs that have sex-specific responses (1,3–5). Sex-aware drug repurposing methods either select drug candidates that are more efficacious in one sex or deprioritize drug candidates based on if they are predicted to cause a sex-bias adverse event (SBAE), unintended therapeutic effects that are more likely to occur in one sex. Computational drug repurposing methods are encouraging approaches to develop for sex-aware drug repurposing because they can prioritize sex-specific drug candidates or SBAEs at lower cost and time than traditional drug discovery. Sex-aware methods currently exist for clinical, genomic, and transcriptomic information (3,6,7). They have not expanded to other data types, such as DNA variation, which has been beneficial in other drug repurposing methods that do not consider sex (8). Additionally, some sex-aware methods suffer from poorer performance because a disproportionate number of male and female samples are available to train computational methods (3). However, there is development potential for several different categories (i.e., data mining, ligand binding predictions, molecular associations, and networks). Low-dimensional representations of molecular association and network approaches are also especially promising candidates for future sex-aware drug repurposing methodologies because they reduce the multiple hypothesis testing burden and capture sex-specific variation better than the other methods (9,10). Here we review how sex influences drug response, the current state of drug repurposing including with respect to sex-bias drug response, and how model organism study design choices influence drug repurposing validation.

show abstract