Cargando…

Identifying actionable druggable targets for breast cancer: Mendelian randomization and population-based analyses

BACKGROUND: Drug repurposing provides a cost-effective approach to address the need for breast cancer prevention and therapeutics. We aimed to identify actionable druggable targets using Mendelian randomization (MR) and then validate the candidate drugs using population-based analyses. METHODS: We i...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhang, Naiqi, Li, Yanni, Sundquist, Jan, Sundquist, Kristina, Ji, Jianguang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10628347/
http://dx.doi.org/10.1016/j.ebiom.2023.104859
_version_ 1785131737568772096
author Zhang, Naiqi
Li, Yanni
Sundquist, Jan
Sundquist, Kristina
Ji, Jianguang
author_facet Zhang, Naiqi
Li, Yanni
Sundquist, Jan
Sundquist, Kristina
Ji, Jianguang
author_sort Zhang, Naiqi
collection PubMed
description BACKGROUND: Drug repurposing provides a cost-effective approach to address the need for breast cancer prevention and therapeutics. We aimed to identify actionable druggable targets using Mendelian randomization (MR) and then validate the candidate drugs using population-based analyses. METHODS: We identified genetic instruments for 1406 actionable targets of approved non-oncological drugs based on gene expression, DNA methylation, and protein expression quantitative trait loci (eQTL, mQTL, and pQTL, respectively). Genome-wide association study (GWAS) summary statistics were obtained from the Breast Cancer Association Consortium (122,977 cases, 105,974 controls). We further conducted a nested case–control study using data retrieved from Swedish registers to validate the candidate drugs that were identified from MR analyses. FINDINGS: We identified six significant MR associations with gene expression levels (TUBB, MDM2, CSK, ULK3, MC1R and KCNN4) and two significant associations with gene methylation levels across 21 CpG islands (RPS23 and MAPT). Results from the nested case–control study showed that the use of raloxifene (targeting MAPT) was associated with 35% reduced breast cancer risk (odds ratio, OR, 0.65; 95% confidence interval, CI, 0.51–0.83). However, usage of estradiol, tolterodine, and nitrofurantoin (also targeting MAPT) was associated with increased breast cancer risk, with adjusted ORs and 95% CI of 1.10 (1.07–1.13), 1.16 (1.09–1.24), and 1.09 (1.05–1.13), respectively. The effect of raloxifene and nitrofurantoin lost significance in further validation analyses using active-comparator and new-user design. INTERPRETATION: This large-scale MR analysis, combined with population-based validation, identified eight druggable target genes for breast cancer and suggested that raloxifene is an effective chemoprevention against breast cancer. FUNDING: 10.13039/501100004359Swedish Research Council, 10.13039/501100002794Cancerfonden, 10.13039/501100003173Crafoordska Stiftelsen, Allmänna Sjukhusets i Malmö Stiftelsen för bekämpande av cancer, 10.13039/501100013314111 Project and MAS cancer.
format Online
Article
Text
id pubmed-10628347
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Elsevier
record_format MEDLINE/PubMed
spelling pubmed-106283472023-11-08 Identifying actionable druggable targets for breast cancer: Mendelian randomization and population-based analyses Zhang, Naiqi Li, Yanni Sundquist, Jan Sundquist, Kristina Ji, Jianguang eBioMedicine Articles BACKGROUND: Drug repurposing provides a cost-effective approach to address the need for breast cancer prevention and therapeutics. We aimed to identify actionable druggable targets using Mendelian randomization (MR) and then validate the candidate drugs using population-based analyses. METHODS: We identified genetic instruments for 1406 actionable targets of approved non-oncological drugs based on gene expression, DNA methylation, and protein expression quantitative trait loci (eQTL, mQTL, and pQTL, respectively). Genome-wide association study (GWAS) summary statistics were obtained from the Breast Cancer Association Consortium (122,977 cases, 105,974 controls). We further conducted a nested case–control study using data retrieved from Swedish registers to validate the candidate drugs that were identified from MR analyses. FINDINGS: We identified six significant MR associations with gene expression levels (TUBB, MDM2, CSK, ULK3, MC1R and KCNN4) and two significant associations with gene methylation levels across 21 CpG islands (RPS23 and MAPT). Results from the nested case–control study showed that the use of raloxifene (targeting MAPT) was associated with 35% reduced breast cancer risk (odds ratio, OR, 0.65; 95% confidence interval, CI, 0.51–0.83). However, usage of estradiol, tolterodine, and nitrofurantoin (also targeting MAPT) was associated with increased breast cancer risk, with adjusted ORs and 95% CI of 1.10 (1.07–1.13), 1.16 (1.09–1.24), and 1.09 (1.05–1.13), respectively. The effect of raloxifene and nitrofurantoin lost significance in further validation analyses using active-comparator and new-user design. INTERPRETATION: This large-scale MR analysis, combined with population-based validation, identified eight druggable target genes for breast cancer and suggested that raloxifene is an effective chemoprevention against breast cancer. FUNDING: 10.13039/501100004359Swedish Research Council, 10.13039/501100002794Cancerfonden, 10.13039/501100003173Crafoordska Stiftelsen, Allmänna Sjukhusets i Malmö Stiftelsen för bekämpande av cancer, 10.13039/501100013314111 Project and MAS cancer. Elsevier 2023-10-28 /pmc/articles/PMC10628347/ http://dx.doi.org/10.1016/j.ebiom.2023.104859 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Articles
Zhang, Naiqi
Li, Yanni
Sundquist, Jan
Sundquist, Kristina
Ji, Jianguang
Identifying actionable druggable targets for breast cancer: Mendelian randomization and population-based analyses
title Identifying actionable druggable targets for breast cancer: Mendelian randomization and population-based analyses
title_full Identifying actionable druggable targets for breast cancer: Mendelian randomization and population-based analyses
title_fullStr Identifying actionable druggable targets for breast cancer: Mendelian randomization and population-based analyses
title_full_unstemmed Identifying actionable druggable targets for breast cancer: Mendelian randomization and population-based analyses
title_short Identifying actionable druggable targets for breast cancer: Mendelian randomization and population-based analyses
title_sort identifying actionable druggable targets for breast cancer: mendelian randomization and population-based analyses
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10628347/
http://dx.doi.org/10.1016/j.ebiom.2023.104859
work_keys_str_mv AT zhangnaiqi identifyingactionabledruggabletargetsforbreastcancermendelianrandomizationandpopulationbasedanalyses
AT liyanni identifyingactionabledruggabletargetsforbreastcancermendelianrandomizationandpopulationbasedanalyses
AT sundquistjan identifyingactionabledruggabletargetsforbreastcancermendelianrandomizationandpopulationbasedanalyses
AT sundquistkristina identifyingactionabledruggabletargetsforbreastcancermendelianrandomizationandpopulationbasedanalyses
AT jijianguang identifyingactionabledruggabletargetsforbreastcancermendelianrandomizationandpopulationbasedanalyses