Circulating Cell-Free DNA-Based Detection of Tumor Suppressor Gene Copy Number Loss and Its Clinical Implication in Metastatic Prostate Cancer.
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ABSTRACT:
SUBMITTER: Dong X
PROVIDER: S-EPMC8422845 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:In the present study, we aimed to evaluate the association of circulating AR copy number (CN) and outcome in a cohort of patients with advanced castration-resistant prostate cancer (CRPC) treated with enzalutamide after docetaxel. Fifty-nine CRPC patients were evaluated. AR CN was analyzed with real-time and digital PCR in the serum collected at starting of treatment. Progressive disease was defined on the basis of Prostate Cancer Working Group 2 criteria. AR CN gain was found in 21 of 59 (36%) patients. Median baseline PSA, alkaline phosphatase and lactate dehydrogenase levels were higher in the AR CN gained group (p = 0.007, p = 0.003, p = 0.0009, respectively). Median PFS of patients with AR CN gain was 2.4 (95%CI: 1.9-3.2) vs. 4.0 months (95%CI: 3.0-6.5) of those with no gain (p = 0.0004). Median OS of patients with AR CN gain was 6.1 (95%CI: 3.4-8.6) vs. 14.1 months (95%CI: 8.2-20.5) of those with no gain (p = 0.0003). At multivariate analysis, PSA decline ? 50% and AR CN showed a significant association with PFS (p = 0.008 and p = 0.002, respectively) and OS (p = 0.009 and p = 0.001, respectively). These findings indicate that the detection of circulating AR CN gain is a promising non-invasive biomarker for outcome prediction to enzalutamide treatment in CRPC patients.
| S-EPMC5122353 | biostudies-literature
Project description:BackgroundThis study aimed to investigate copy number variations (CNVs) of CYP17A1 and androgen receptor (AR) genes in serum cell-free DNA collected before starting abiraterone in 53 consecutive patients with castration-resistant prostate cancer (CRPC).MethodsSerum DNA was isolated and CNVs were analysed for AR and CYP17A1 genes using Taqman copy number assays. The association between CNVs and progression-free/overall survival (PFS/OS) was evaluated by the Kaplan-Meier method and log-rank test.ResultsMedian PFS of patients with AR gene gain was 2.8 vs 9.5 months of non-gained cases (P < 0.0001). Patients with CYP17A1 gene gain had a median PFS of 2.8 months vs 9.2 months in the non-gained patients (P = 0.0014). A lower OS was reported in both cases (AR: P < 0.0001; CYP17A1: P = 0.0085). Multivariate analysis revealed that PSA decline ? 50%, AR and CYP17A1 CNVs were associated with shorter PFS (P < 0.0001, P = 0.0004 and P = 0.0450, respectively), while performance status, PSA decline ? 50%, AR CNV and DNA concentration were associated with OS (P = 0.0021, P = 0.0014, P = 0.0026 and P = 0.0129, respectively).ConclusionsCNVs of AR and CYP17A1 genes would appear to be associated with outcome of CRPC patients treated with abiraterone.
| S-EPMC4430717 | biostudies-literature
Project description:Current high-sensitivity cancer screening methods, largely utilizing correlative biomarkers, suffer from false positive rates that lead to unnecessary medical procedures and debatable public health benefit overall. Detection of circulating tumor DNA (ctDNA), a causal biomarker, has the potential to revolutionize cancer screening. Thus far, the majority of ctDNA studies have focused on detection of tumor-specific point mutations after cancer diagnosis for the purpose of post-treatment surveillance. However, ctDNA point mutation detection methods developed to date likely lack either the scope or analytical sensitivity necessary to be useful for cancer screening, due to the low (<1%) ctDNA fraction derived from early stage tumors. On the other hand, tumor-derived copy number variant (CNV) detection is hypothetically a superior means of ctDNA-based cancer screening for many tumor types, given that, relative to point mutations, each individual tumor CNV contributes a much larger number of ctDNA fragments to the overall pool of circulating free DNA (cfDNA). A small number of studies have demonstrated the potential of ctDNA CNV-based screening in select cancer types. Here we perform an in silico assessment of the potential for ctDNA CNV-based cancer screening across many common cancers, and suggest ctDNA CNV detection shows promise as a broad cancer screening methodology.
| S-EPMC5501586 | biostudies-literature
Project description:Many studies have shown that primary prostate cancers are multifocal and are composed of multiple genetically distinct cancer cell clones. Whether or not multiclonal primary prostate cancers typically give rise to multiclonal or monoclonal prostate cancer metastases is largely unknown, although studies at single chromosomal loci are consistent with the latter case. Here we show through a high-resolution genome-wide single nucleotide polymorphism and copy number survey that most, if not all, metastatic prostate cancers have monoclonal origins and maintain a unique signature copy number pattern of the parent cancer cell while also accumulating a variable number of separate subclonally sustained changes. We find no relationship between anatomic site of metastasis and genomic copy number change pattern. Taken together with past animal and cytogenetic studies of metastasis and recent single-locus genetic data in prostate and other metastatic cancers, these data indicate that despite common genomic heterogeneity in primary cancers, most metastatic cancers arise from a single precursor cancer cell. This study establishes that genomic archeology of multiple anatomically separate metastatic cancers in individuals can be used to define the salient genomic features of a parent cancer clone of proven lethal metastatic phenotype.
| S-EPMC2839160 | biostudies-literature
Project description:PurposeThe purpose of this study was to measure genomic changes that emerge with enzalutamide treatment using analyses of whole-genome sequencing and RNA sequencing.Experimental designOne hundred and one tumors from men with metastatic castration-resistant prostate cancer (mCRPC) who had not been treated with enzalutamide (n = 64) or who had enzalutamide-resistant mCRPC (n = 37) underwent whole genome sequencing. Ninety-nine of these tumors also underwent RNA sequencing. We analyzed the genomes and transcriptomes of these mCRPC tumors.ResultsCopy number loss was more common than gain in enzalutamide-resistant tumors. Specially, we identified 124 protein-coding genes that were more commonly lost in enzalutamide-resistant samples. These 124 genes included eight putative tumor suppressors located at nine distinct genomic regions. We demonstrated that focal deletion of the 17q22 locus that includes RNF43 and SRSF1 was not present in any patient with enzalutamide-naïve mCRPC but was present in 16% (6/37) of patients with enzalutamide-resistant mCRPC. 17q22 loss was associated with lower RNF43 and SRSF1 expression and poor overall survival from time of biopsy [median overall survival of 19.3 months in 17q22 intact vs. 8.9 months in 17q22 loss, HR, 3.44 95% confidence interval (CI), 1.338-8.867, log-rank P = 0.006]. Finally, 17q22 loss was linked with activation of several targetable factors, including CDK1/2, Akt, and PLK1, demonstrating the potential therapeutic relevance of 17q22 loss in mCRPC.ConclusionsCopy number loss is common in enzalutamide-resistant tumors. Focal deletion of chromosome 17q22 defines a previously unappreciated molecular subset of enzalutamide-resistant mCRPC associated with poor clinical outcome.
| S-EPMC7484240 | biostudies-literature
Project description:BackgroundsAside from Gleason score few factors accurately identify the subset of prostate cancer (PCa) patients at high risk for metastatic progression. We hypothesized that copy number alterations (CNAs), assessed using CpG methylation probes on Illumina Infinium® Human Methylation450 (HM450K) BeadChip arrays, could identify primary prostate tumors with potential to develop metastatic progression.MethodsEpigenome-wide DNA methylation profiling was performed in surgically resected primary tumor tissues from two cohorts of PCa patients with clinically localized disease who underwent radical prostatectomy (RP) as primary therapy and were followed prospectively for at least 5 years: (1) a Fred Hutchinson (FH) Cancer Research Center-based cohort (n = 323 patients); and (2) an Eastern Virginia (EV) Medical School-based cohort (n = 78 patients). CNAs were identified using the R package ChAMP. Metastasis was confirmed by positive bone scan, MRI, CT or biopsy, and death certificates confirmed cause of death.ResultsWe detected 15 recurrent CNAs were associated with metastasis in the FH cohort and replicated in the EV cohort (p < 0.05) without adjusting for Gleason score in the model. Eleven of the recurrent CNAs were associated with metastatic progression in the FH cohort and validated in the EV cohort (p < 0.05) when adjusting for Gleason score.ConclusionsThis study shows that CNAs can be reliably detected from HM450K-based DNA methylation data. There are 11 recurrent CNAs showing association with metastatic-lethal events following RP and improving prediction over Gleason score. Genes affected by these CNAs may functionally relate to tumor aggressiveness and metastatic progression.
| S-EPMC7725282 | biostudies-literature
Project description:Many studies have shown that primary prostate cancers are multifocal1-3, and are composed of multiple genetically distinct cancer cell clones4-6. Whether or not multiclonal primary prostate cancers typically give rise to multiclonal or monoclonal prostate cancer metastases is largely unknown, although studies at single chromosomal loci are consistent with the latter. Here we show through a high-resolution genome-wide SNP and copy number survey that most if not all metastatic prostate cancers have monoclonal origins and maintain a unique signature copy number pattern of the parent cancer cell while also accumulating a variable number of separate subclonally sustained changes. We find no relationship between anatomic site of metastasis and genomic copy number change pattern. Taken together with past animal and cytogenetic studies of metastasis7, and recent single-locus genetic data in prostate and other metastatic cancers8-10, it appears that despite common genomic heterogeneity in primary cancers, most metastatic cancers arise from a single precursor cancer cell. Methodologically, this study establishes that genomic archeology of multiple anatomically separate metastatic cancers in individuals can be used to define the salient genomic features of a parent cancer clone of proven lethal metastatic phenotype.
2009-04-12 | GSE14996 | GEO
Project description:BackgroundSomatic copy number alterations (SCNAs) occurring in tumors can provide information about tumor classification, patient's outcome or treatment targets. Liquid biopsies, incl. plasma samples containing circulating cell-free tumor DNA (ccfDNA) can be used to assess SCNAs for clinical purposes, however specify and reliability of methods have to be tested.MethodsSNP microarrays (Affymetrix) were used to generate whole-genome copy number profiles from plasma ccfDNA (OncoScan) and paired tumor biopsies (CytoScan) from ten patients with metastatic cancers. Numerical, segmental and focal SCNAs were assessed using ASCAT/TuScan and SNP-FASST2.ResultsAberrations in ccfDNA in 4 patients resembled numerical (76%) and segmental (80%) aberrations in tDNA. Three patients represented low correlation due to postponed sampling time, ccfDNA quality and possible treatment interference. Breakpoints of high-amplitude amplification were assessed with high accuracy and relative breakpoints difference of only 7% (0.02-37%). Similarly, biallelic losses were reliably detected. Array was 100% successful in detection of SCNAs on clinically relevant genes compared to SCNAs in tumor biopsies. Tracking of SCNAs changes during the treatment course of one patient also indicated that apoptosis/necrosis of non-cancerous cells presumably induced by treatment can influence ccfDNA composition and introduce false-negative findings into the analysis of liquid biopsies.ConclusionsGenomic alterations detected in ccfDNA from liquid biopsies by comprehensive SNP array are reliable source for information for stratification of patients for targeted treatment.General significanceClinically relevant SCNAs can be detected in ccfDNA with high resolution and can therefore serve as an alternative to tumor biopsy in defining treatment targets.
| S-EPMC5390666 | biostudies-literature
Project description:Neuroendocrine prostate cancer is an aggressive variant of prostate cancer that may arise de novo or develop from pre-existing prostate adenocarcinoma as a mechanism of treatment resistance. The combined loss of tumor suppressors RB1, TP53, and PTEN are frequent in NEPC but also present in a subset of prostate adenocarcinomas. Most clinical and preclinical studies support a trans-differentiation process, whereby NEPC arises clonally from a prostate adenocarcinoma precursor during the course of treatment resistance. Here we highlight a case of NEPC with significant intra-patient heterogeneity observed across metastases. We further demonstrate how single-cell genomic analysis of circulating tumor cells combined with a phenotypic evaluation of cellular diversity can be considered as a window into tumor heterogeneity in patients with advanced prostate cancer.
| S-EPMC8361159 | biostudies-literature
Project description:MotivationThe ability to detect copy-number variation (CNV) and loss of heterozygosity (LOH) from exome sequencing data extends the utility of this powerful approach that has mainly been used for point or small insertion/deletion detection.ResultsWe present ExomeCNV, a statistical method to detect CNV and LOH using depth-of-coverage and B-allele frequencies, from mapped short sequence reads, and we assess both the method's power and the effects of confounding variables. We apply our method to a cancer exome resequencing dataset. As expected, accuracy and resolution are dependent on depth-of-coverage and capture probe design.AvailabilityCRAN package 'ExomeCNV'.Contactfsathira@fas.harvard.edu; snelson@ucla.eduSupplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC3179661 | biostudies-literature