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Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer
Published on: November 2, 2013
Blood-Based Genomic Alteration Signature for Predicting Progression-Free Survival in De Novo Metastatic
Ruiliang Wang1, Jing Xu2,3, Chenyi Zhu2,3
1Department of Urology, Zhongshan Hospital, Fudan University, Shanghai, China.
None:
Metastatic hormone-sensitive prostate cancer (mHSPC) often progresses to castration-resistant prostate cancer despite current therapies, necessitating the use of reliable biomarkers. This study aimed to develop a novel model for predicting progression-free survival (PFS) using ctDNA sequencing. We analyzed 127 patients with mHSPC and compared ctDNA mutations with those in matched primary tumor tissues. A four-gene signature (TRPC: TP53, RB1, PTEN, and CDK12) was identified, forming the basis of the blood-based TRPC (b.TRPC) model. The b.TRPC model demonstrated high specificity and sensitivity in predicting PFS, outperforming ctDNA markers. Internal and external validation confirmed that b.TRPC is an independent prognostic factor with superior predictive performance for 0.5-, 1-, and 2-year PFS. The model also showed significant clinical relevance, with b.TRPC-positive patients exhibiting shorter survival times under androgen deprivation therapy and doublet therapy, although this disparity diminished with triplet therapy. These findings highlight the potential of ctDNA-based gene mutation analysis to guide personalized treatment strategies for mHSPC, offering a noninvasive alternative to tissue-based analyses and improving prognostic accuracy.
Significance:
This study identified a novel noninvasive blood-based biomarker model (b.TRPC) using ctDNA to predict PFS in mHSPC. Analyzing TP53, RB1, PTEN, and CDK12 alterations, it outperformed traditional ctDNA% markers. Findings highlight ctDNA-based biomarkers' potential to guide personalized treatment, bridging real-world and trial data to aid mHSPC management.
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