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New Software Platform Identifies Prematurely Aging Cells to Aid Disease Research
Prematurely aging cells, known for their detrimental impact on human health, pose significant challenges. These cells, which cease to grow but do not die, can exacerbate conditions such as cardiovascular disease and Alzheimer’s. Identifying them has traditionally proven difficult due to their elusive nature, akin to finding needles in a haystack.
In response to this challenge, a doctoral student at the University of Illinois Chicago has created an advanced software platform called SenePy. In a recent publication in Nature Communications, Mark Sanborn, along with his colleagues from the College of Medicine, introduced this open-source tool designed to detect aging, or senescent, cells within various organs and tissues.
The emergence of SenePy provides researchers with a powerful resource for studying these critical biological cells, enhancing understanding and treatment of multiple diseases. Dr. Jalees Rehman, the lead author and a prominent figure in the university’s Cancer Center, expressed optimism about the tool’s potential impact: “Cellular senescence refers to the early aging of a cell, wherein it ceases normal function and growth. This stagnation prevents the natural replacement of these cells with healthier ones, resulting in persistent inflammation and dysfunction in surrounding cells.”
To create SenePy, Sanborn meticulously analyzed single-cell sequencing data from over 1.6 million cells derived from both humans and mice. He employed computational methodologies to identify genetic markers that differentiate aging cells from more robust counterparts.
However, uncovering a universal set of markers for senescent cells was not straightforward. The research team discovered that the genetic profiling of aging cells varied significantly across different tissues, such as in the heart, lungs, and brain. Ultimately, they identified 72 distinct genetic signatures in mice and 64 in humans.
SenePy simplifies the interpretation of this intricate data, enabling researchers to analyze their own tissue samples in relation to the genetic signatures cataloged by the UIC team. Notably, the platform’s code is freely available as an open-source resource.
“The accessibility of SenePy is crucial; its open nature promotes widespread use and could enhance its therapeutic applications,” Sanborn noted. His position as a doctoral student in the Graduate Education in Biomedical Sciences program reflects his commitment to advancing this tool’s influence in scientific research.
In their article, the research team utilized SenePy to investigate the implications of senescent cells in various medical contexts, including cancer development, heart attacks, COVID-19, and neuroinflammation. Rehman highlighted their findings: “We observed that senescent cells tend to cluster, as the premature aging of one cell can trigger dysfunction and senescence in nearby cells. Additionally, SenePy facilitated our examination of how senescence serves as a natural mechanism to inhibit tumor development, noting the correlation between high levels of a cancer-promoting gene and elevated senescence scores detected by SenePy.”
The researchers also evaluated the efficacy of senolytic drugs, which are designed to eliminate senescent cells, to combat diseases and slow the aging process. “With the identification of specific markers for different types of senescence across various cell types, we can potentially pioneer new senolytic therapies,” added Sanborn.
In addition to Sanborn and Rehman, other contributors from UIC include co-authors Xinge Wang, Shang Gao, and Yang Dai. This research initiative received funding from multiple grants provided by the National Institutes of Health.
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