New paper below [1].
I was intrigued by the title:
"Comprehensive analysis of the progression mechanisms of CRPC and its inhibitor discovery based on machine learning algorithms"
"CCNA2 and CKS2 were identified as promising biomarkers ..."
"These potential biomarkers were further validated and exhibited a strong predictive ability."
"The results of the virtual screening revealed Aprepitant and Dolutegravir as the optimal targeted drugs for CCNA2 and CKS2, respectively."
"The expression of CCNA2 and CKS2 increases with the progression of prostate cancer, which may be one of the driving factors for the progression of prostate cancer and can serve as diagnostic biomarkers and therapeutic targets for CRPC. Additionally, Aprepitant and Dolutegravir show potential as anti-tumor drugs for CRPC."
From Wiki: "Increased expression of cyclin A2 {CCNA2} has been observed in many types of cancer ... While it is not clear whether increased expression of cyclin A2 is a cause or result of tumorigenesis, it is indicative of prognostic values such as predictions of survival or relapse." [2]
Earlier this year, CCNA2 was identified as one of "five hub genes, i.e., CCNA2, CDK2, CTH, DPP4 and SRC" in
"Systematic investigation of the mechanism of herbal medicines for the treatment of prostate cancer" [3]
"Traditional herbal medicine is a whole medical system originated from several thousand years of clinical experience. Nowadays, increasing PCa patients worldwide are starting to use herbal medicines for treatment. However, herbal medicine is a complex system and often possess dozens or even hundreds of various chemical components with diversified structures, making factually the determination of Traditional Chinese Medicine (TCM) content an indispensable while quite challenging work in TCM research. In addition, the multiple targets and multiple biological pathways of herbal medicine also makes it extremely difficult to analyze the molecular mechanism of herbal medicine. Using experimental approaches alone can hardly systematically and scientifically evaluate the function mechanism of TCMs. A computational method to solve this problem is still unavailable up to date. Owing to these facts, the development and application of computational technology is a necessity to overcome these difficulties."
---
"Firstly, using the bibliometric analysis and text statistics mining, 10 most frequently used herbs of PCa and their corresponding constituents were obtained. Secondly, an in silicopharmacokinetic model system was employed to screen out the potential active compounds of anti-PCa herbs and then the targets of these potential active ingredients were fished. Thirdly, the overlapping genes among differentially expressed genes (DEGs) in PCa patients and the target genes of the PCa-related herbal medicines were obtained. Subsequently, five hub genes were applied to perform survival and tumour immunity analysis, revealing their critical roles in PCa."
& so on.
Oddly, there are only 16 other PubMed PCa hits for CCNA2.
The first of these [4] (2010) leads with:
"cRNA microarray and real-time PCR (qPCR) studies from our lab identified five Cell Cycle Pathway (CCP) genes (CCNA2, CCNE2, CDC25A, CDKN1B, and PLK-1) as targets for luteolin in PC-3 prostate cancer cells"
"That luteolin and related type II site ligands are capable of causing G2/M arrest via a c-FOS-p21 regulatory pathway in p53 null malignant cells may have significant clinical implications."
Luteolin happens to be one of my daily PCa supplements.
-Patrick
[1] frontiersin.org/articles/10...
[2] en.wikipedia.org/wiki/Cycli...
