Artificial Intelligence Could Shed Light on Development, Diagnosis, and Treatment of Prostate Cancer

Artificial Intelligence Could Shed Light on Development, Diagnosis, and Treatment of Prostate Cancer
Using artificial intelligence to identify genetic patterns in prostate cancer tissue could help shed light on how tumors develops and improve clinical diagnosis and treatment, a study reports. The approach uses several samples from a single tumor, creating a kind of spatial map of the tumor's genetic information. The study, “Spatial maps of prostate cancer transcriptomes reveal an unexplored landscape of heterogeneity,” was published in the journal Nature Communications. One of the major issues with cancer treatment is that while one subpopulation of cancer cells will respond to treatment, another subpopulation from the same tumor often won’t. Therefore, after treatment, the resistant cell population can continue to grow. This is attributed to a phenomenon called tumor heterogeneity. Tumor heterogeneity refers to the observation that different cells from the same tumor can vary in gene expression and behavior. It is a pervasive problem across most tumors, including prostate cancer. By using a technique called single-cell RNA sequencing (scRNA-Seq), researchers can determine the differences in gene expression at the individual cell level. And advancements in microfluidics have made it possible to analyze thousands of cells at a time. However, because samples are taken from all around the tumor, there is a lack of spatial information in the scRNA-Seq data, which could make a big difference. In this study, researchers investigated the heterogeneity of prostate cancer using a novel spatial transcriptomics (ST) method, which allows researchers to quantify gene ex
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Iqra holds a MSc in Cellular and Molecular Medicine from the University of Ottawa in Ottawa, Canada. She also holds a BSc in Life Sciences from Queen’s University in Kingston, Canada. Currently, she is completing a PhD in Laboratory Medicine and Pathobiology from the University of Toronto in Toronto, Canada. Her research has ranged from across various disease areas including Alzheimer’s disease, myelodysplastic syndrome, bleeding disorders and rare pediatric brain tumors.

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