Wang, Liang

Prostate cancer (PCa) accounted for more than 34,000 deaths in US males [...]

Amplification of androgen receptor (AR) is a common genomic event in metastatic castration-resistant prostate cancer (mCRPC). To evaluate the prognostic value of the amplifications of specific loci in the AR gene in cell-free DNA, we developed a multiplex digital PCR (dPCR) assay that targeted AR enhancer (AR-En), AR exon 1 (AR-E1), AR exon 8 (AR-E8) and OPHN1 (downstream of AR). We selected three relatively stable genes, C2orf16, FAM111B, and GRIA3, as reference controls for copy number normalization. One hundred and eight mCRPC patients were recruited to test the association of specific AR loci amplification with clinical outcome. Using a normalized ratio ≥ 1.92 as cutoff, amplification of AR-En, AR-E1, AR-E8 and OPHN1 was observed in 28, 25, 24 and 19 of 108 mCRPC patients, respectively. Among the 41 patients with AR region amplification, 9 (21.9%) showed amplification at all four selected regions and 15 (36.6%) showed amplification at AR-En, AR-E1, and AR-E8. Six (14.6%) patients showed independent AR-En amplification, while the remaining 3 (7.3%) demonstrated AR-E8 amplification only. Kaplan–Meier analysis showed overall survival’s association with the amplification of AR-En (p = 0.02, HR = 1.68 (1.07–2.65)), AR-E8 (p = 0.02, HR = 1.78 (1.08–2.92)) and AR-En-E8 (the combination of AR-En and AR-E8 (p = 0.009, HR = 1.77 (1.15–2.73)). Multivariate models that included AR-En-E8 amplification and clinical factors significantly improved prognostic performance (p = 0.0001). With further validation, the multiplex dPCR assay may assist in prognostication of mCRPC patients.

Genome-wide association studies have identified over 150 risk loci that increase prostate cancer risk. However, few causal variants and their regulatory mechanisms have been characterized. In this study, we utilized our previously developed single-nucleotide polymorphisms sequencing (SNPs-seq) technology to test allele-dependent protein binding at 903 SNP sites covering 28 genomic regions. All selected SNPs have shown significant cis-association with at least one nearby gene. After preparing nuclear extract using LNCaP cell line, we first mixed the extract with dsDNA oligo pool for protein–DNA binding incubation. We then performed sequencing analysis on protein-bound oligos. SNPs-seq analysis showed protein-binding differences (>1.5-fold) between reference and variant alleles in 380 (42%) of 903 SNPs with androgen treatment and 403 (45%) of 903 SNPs without treatment. From these significant SNPs, we performed a database search and further narrowed down to 74 promising SNPs. To validate this initial finding, we performed electrophoretic mobility shift assay in two SNPs (rs12246440 and rs7077275) at CTBP2 locus and one SNP (rs113082846) at NCOA4 locus. This analysis showed that all three SNPs demonstrated allele-dependent protein-binding differences that were consistent with the SNPs-seq. Finally, clinical association analysis of the two candidate genes showed that CTBP2 was upregulated, while NCOA4 was downregulated in prostate cancer (p < 0.02). Lower expression of CTBP2 was associated with poor recurrence-free survival in prostate cancer. Utilizing our experimental data along with bioinformatic tools provides a strategy for identifying candidate functional elements at prostate cancer susceptibility loci to help guide subsequent laboratory studies.

To evaluate the clinical utility of cell‐free DNA (cfDNA), we performed whole‐genome sequencing to systematically examine plasma cfDNA copy number variations (CNVs) in a cohort of patients with colorectal cancer (CRC, n = 80), polyps (n = 20), and healthy controls (n = 35). We initially compared cfDNA yield in 20 paired serum–plasma samples and observed significantly higher cfDNA concentration in serum (median = 81.20 ng, range 7.18–500 ng·mL−1) than in plasma (median = 5.09 ng, range 3.76–62.8 ng·mL−1) (P < 0.0001). However, tumor‐derived cfDNA content was significantly lower in serum than in matched plasma samples tested. With ~10 million reads per sample, the sequencing‐based copy number analysis showed common CNVs in multiple chromosomal regions, including amplifications on 1q, 8q, and 5q and deletions on 1p, 4q, 8p, 17p, 18q, and 22q. Copy number changes were also evident in genes critical to the cell cycle, DNA repair, and WNT signaling pathways. To evaluate whether cumulative copy number changes were associated with tumor stages, we calculated plasma genomic abnormality in colon cancer (PGA‐C) score by summing the most significant CNVs. The PGA‐C score showed predictive performance with an area under the curve from 0.54 to 0.84 for CRC stages I‐IV. Locus‐specific copy number analysis identified nine genomic regions where CNVs were significantly associated with survival in stage III‐IV CRC patients. A multivariate model using six of nine genomic regions demonstrated a significant association of high‐risk score with shorter survival (HR = 5.33, 95% CI = 6.76–94.44, P < 0.0001). Our study demonstrates the importance of using plasma (rather than serum) to test tumor‐related genomic variations. Plasma cfDNA‐based tests can capture tumor‐specific genetic changes and may provide a measurable classifier for assessing clinical outcomes in advanced CRC patients.