Publications by authors named "Bogdan-Alexandru Luca"
The highly heterogeneous clinical course of human prostate cancer has prompted the development of multiple RNA biomarkers and diagnostic tools to predict outcome for individual patients. Biomarker discovery is often unstable with, for example, small changes in discovery dataset configuration resulting in large alterations in biomarker composition. Our hypothesis, which forms the basis of this current study, is that highly significant overlaps occurring between gene signatures obtained using entirely different approaches indicate genes fundamental for controlling cancer progression.
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- Scientists are trying to understand prostate cancer better by using advanced methods to analyze genetic data, instead of just basic methods that overlook important details.
- They used a special model called Latent Process Decomposition (LPD) to look at data from many prostate cancer patients and found a link between a specific gene signature (DESNT) and the risk of cancer worsening.
- By discovering different types of prostate cancer based on this gene signature, they hope to improve treatment and help doctors make better decisions for patients.
Background: A critical problem in the clinical management of prostate cancer is that it is highly heterogeneous. Accurate prediction of individual cancer behaviour is therefore not achievable at the time of diagnosis leading to substantial overtreatment. It remains an enigma that, in contrast to breast cancer, unsupervised analyses of global expression profiles have not currently defined robust categories of prostate cancer with distinct clinical outcomes.
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