A novel prostate cancer subtyping classifier based on luminal and basal phenotypes.
Adam B WeinerYang LiuAlex HakanssonXin ZhaoJames A ProudfootJulian HoJj H ZhangEric V LiR Jeffrey KarnesRobert B DenAmar U KishanRobert E ReiterAnis A HamidAshely E RossPhuoc T TranElai DavicioniDaniel E SprattGerhardt AttardTamara L LotanMelvin Lee Kiang ChuaChristopher J SweeneyEdward M SchaefferPublished in: Cancer (2023)
Prostate cancer can behave in an indolent or aggressive manner and vary in how it responds to certain treatments. To differentiate prostate cancer on the basis of biological features, we developed a novel RNA signature by using data from over 100,000 prostate tumors-the largest data set of its kind. This signature can inform patients and physicians on tumor aggressiveness and susceptibilities to treatments to help personalize cancer management.
Keyphrases
- prostate cancer
- radical prostatectomy
- end stage renal disease
- electronic health record
- primary care
- chronic kidney disease
- ejection fraction
- newly diagnosed
- big data
- papillary thyroid
- prognostic factors
- young adults
- squamous cell carcinoma
- machine learning
- data analysis
- artificial intelligence
- deep learning
- patient reported outcomes
- lymph node metastasis