[HTML][HTML] Unbiased data mining identifies cell cycle transcripts that predict non-indolent Gleason score 7 prostate cancer
WL Johnston, CN Catton, CJ Swallow - BMC urology, 2019 - Springer
Background Patients with newly diagnosed non-metastatic prostate adenocarcinoma are
typically classified as at low, intermediate, or high risk of disease progression using blood …
typically classified as at low, intermediate, or high risk of disease progression using blood …
[HTML][HTML] A hierarchical machine learning model to discover gleason grade-specific biomarkers in prostate cancer
O Hamzeh, A Alkhateeb, JZ Zheng, S Kandalam… - Diagnostics, 2019 - mdpi.com
(1) Background: One of the most common cancers that affect North American men and men
worldwide is prostate cancer. The Gleason score is a pathological grading system to …
worldwide is prostate cancer. The Gleason score is a pathological grading system to …
[HTML][HTML] Crafting a Personalized Prognostic Model for Malignant Prostate Cancer Patients Using Risk Gene Signatures Discovered through TCGA-PRAD Mining …
F Lyu, X Gao, M Ma, M Xie, S Shang, X Ren, M Liu… - Diagnostics, 2023 - mdpi.com
Background: Prostate cancer is a significant clinical issue, particularly for high Gleason
score (GS) malignancy patients. Our study aimed to engineer and validate a risk model …
score (GS) malignancy patients. Our study aimed to engineer and validate a risk model …
Transcriptomics signature from next-generation sequencing data reveals new transcriptomic biomarkers related to prostate cancer
A Alkhateeb, I Rezaeian, S Singireddy… - Cancer …, 2019 - journals.sagepub.com
Prostate cancer is one of the most common types of cancer among Canadian men. Next-
generation sequencing using RNA-Seq provides large amounts of data that may reveal …
generation sequencing using RNA-Seq provides large amounts of data that may reveal …
[HTML][HTML] Expression signatures that correlated with Gleason score and relapse in prostate cancer
M Bibikova, E Chudin, A Arsanjani, L Zhou, EW Garcia… - Genomics, 2007 - Elsevier
Predicting prognosis in prostate carcinoma remains a challenge when using clinical and
pathologic criteria only. We used an array-based DASL® assay to identify molecular …
pathologic criteria only. We used an array-based DASL® assay to identify molecular …
Molecular classification of prostate cancer using curated expression signatures
High Gleason score is currently the best prognostic indicator for poor prognosis in prostate
cancer. However, a significant number of patients with low Gleason scores develop …
cancer. However, a significant number of patients with low Gleason scores develop …
[HTML][HTML] Five-gene signature associating with Gleason score serve as novel biomarkers for identifying early recurring events and contributing to early diagnosis for …
L Zhang, Y Li, X Wang, Y Ping, D Wang, Y Cao… - Journal of …, 2021 - ncbi.nlm.nih.gov
Background: Compared to non-recurrent type, recurrent prostate adenocarcinoma (PCa) is
highly fatal, and significantly shortens the survival time of affected patients. Early and …
highly fatal, and significantly shortens the survival time of affected patients. Early and …
[HTML][HTML] Identification of a transcriptomic prognostic signature by machine learning using a combination of small cohorts of prostate cancer
Determining which treatment to provide to men with prostate cancer (PCa) is a major
challenge for clinicians. Currently, the clinical risk-stratification for PCa is based on clinico …
challenge for clinicians. Currently, the clinical risk-stratification for PCa is based on clinico …
PRADclass: Hybrid Gleason Grade-Informed Computational Strategy Identifies Consensus Biomarker Features Predictive of Aggressive Prostate Adenocarcinoma
AS Balraj, S Muthamilselvan, R Raja… - … in Cancer Research …, 2024 - journals.sagepub.com
Background Prostate adenocarcinoma (PRAD) is a common cancer diagnosis among men
globally, yet large gaps in our knowledge persist with respect to the molecular bases of its …
globally, yet large gaps in our knowledge persist with respect to the molecular bases of its …
Comprehensive evaluation of machine learning models and gene expression signatures for prostate cancer prognosis using large population cohorts
R Li, J Zhu, WD Zhong, Z Jia - Cancer Research, 2022 - AACR
Overtreatment remains a pervasive problem in prostate cancer management due to the
highly variable and often indolent course of disease. Molecular signatures derived from …
highly variable and often indolent course of disease. Molecular signatures derived from …