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An integrative multi-omics approach to targeting cellular senescence as a drug repurposing strategy for age-related morbidities


   Faculty of Health and Life Sciences

  Dr S Zhang, Dr Taranjit Singh Rai, Dr David Gibson  Monday, February 06, 2023  Competition Funded PhD Project (Students Worldwide)

About the Project

Age is a major risk factor for various human diseases including cancers, dementia, and cardiovascular diseases. Senescence is a process where cells cease dividing and undergo distinctive phenotypic changes. Senescence has a key role in the aging process and has also been implicated as a major cause of age-related disease. The recent COVID-19 pandemic also clearly showed that age is a prominent risk factor for the severity of the disease.  Indeed SARS-CoV-2 induced senescence is not only a driver but also a therapeutic target in COVID-19. Targeting cellular senescence could potentially alleviate many age-related pathologies.

In this project, we aim to identify therapeutic candidates that could selectively eliminate senescent cells. Such drugs are often referred to as senolytics, which could contribute to the treatment of specific age-related diseases, and potentially could also improve the life and health span of aged individuals.  We propose to deploy an integrative multi-omics connectivity mapping approach to targeting cellular senescence as a drug repurposing strategy for potential applications in age-related diseases.

The overall aim of the project will be achieved through the following steps/objectives:

1) Integration of multiple streams and categories of data in public data repositories from cellular senescence and aging related studies, as well as in-house multi-omics datasets we have generated over the last two years utilizing several past and ongoing grants, including RNA-Seq, WGS, proteomics, and meta transcriptomics for 500 COVID-19 patients.

2) Construction of robust gene signatures for cellular senescence based on the integrative analysis of the multi-omics datasets.

3) Application of our established gene expression connectivity mapping framework to computationally screen a collection of over 1500 approved drugs for the identification of senolytics candidates.

4) In vitro validation of top 3-4 emerging drugs in appropriate lung or other cell line models.


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