Plasma genetic and genomic abnormalities predict treatment response and clinical outcome in advanced prostate cancer

Shu Xia, Manish Kohli, Meijun Du, Rachel L. Dittmar, Adam Lee, Debashis Nandy, Tiezheng Yuan, Yongchen Guo, Yuan Wang, Michael R. Tschannen, Elizabeth Worthey, Howard Jacob, William See, Deepak Kilari, Xuexia Wang, Raymond L. Hovey, Chiang Ching Huang, Liang Wang

Research output: Contribution to journalArticlepeer-review

39 Scopus citations


Liquid biopsies, examinations of tumor components in body fluids, have shown promise for predicting clinical outcomes. To evaluate tumor-associated genomic and genetic variations in plasma cell-free DNA (cfDNA) and their associations with treatment response and overall survival, we applied whole genome and targeted sequencing to examine the plasma cfDNAs derived from 20 patients with advanced prostate cancer. Sequencing-based genomic abnormality analysis revealed locusspecific gains or losses that were common in prostate cancer, such as 8q gains, AR amplifications, PTEN losses and TMPRSS2-ERG fusions. To estimate tumor burden in cfDNA, we developed a Plasma Genomic Abnormality (PGA) score by summing the most significant copy number variations. Cox regression analysis showed that PGA scores were significantly associated with overall survival (p < 0.04). After androgen deprivation therapy or chemotherapy, targeted sequencing showed significant mutational profile changes in genes involved in androgen biosynthesis, AR activation, DNA repair, and chemotherapy resistance. These changes may reflect the dynamic evolution of heterozygous tumor populations in response to these treatments. These results strongly support the feasibility of using non-invasive liquid biopsies as potential tools to study biological mechanisms underlying therapy-specific resistance and to predict disease progression in advanced prostate cancer.

Original languageEnglish (US)
Pages (from-to)16411-16421
Number of pages11
Issue number18
StatePublished - 2015


  • Cell free DNA
  • Liquid biopsy
  • Next generation sequencing
  • Plasma
  • Prostate cancer


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