Abstract Background An early report on the molecular subtyping of muscle-invasive bladder cancer (MIBC) by gene expression suggested that response to neoadjuvant chemotherapy (NAC) varies by subtype. ...Objective To investigate the ability of molecular subtypes to predict pathological downstaging and survival after NAC. Design, setting, and participants Whole transcriptome profiling was performed on pre-NAC transurethral resection specimens from 343 patients with MIBC. Samples were classified according to four published molecular subtyping methods. We developed a single-sample genomic subtyping classifier (GSC) to predict consensus subtypes (claudin-low, basal, luminal-infiltrated and luminal) with highest clinical impact in the context of NAC. Overall survival (OS) according to subtype was analyzed and compared with OS in 476 non-NAC cases (published datasets). Intervention Gene expression analysis was used to assign subtypes. Outcome measurements and statistical analysis Receiver-operating characteristics were used to determine the accuracy of GSC. The effect of GSC on survival was estimated by Cox proportional hazard regression models. Results and limitations The models generated subtype calls in expected ratios with high concordance across subtyping methods. GSC was able to predict four consensus molecular subtypes with high accuracy (73%), and clinical significance of the predicted consensus subtypes could be validated in independent NAC and non-NAC datasets. Luminal tumors had the best OS with and without NAC. Claudin-low tumors were associated with poor OS irrespective of treatment regimen. Basal tumors showed the most improvement in OS with NAC compared with surgery alone. The main limitations of our study are its retrospective design and comparison across datasets. Conclusions Molecular subtyping may have an impact on patient benefit to NAC. If validated in additional studies, our results suggest that patients with basal tumors should be prioritized for NAC. We discovered the first single-sample classifier to subtype MIBC, which may be suitable for integration into routine clinical practice. Patient summary Different molecular subtypes can be identified in muscle-invasive bladder cancer. Although cisplatin-based neoadjuvant chemotherapy improves patient outcomes, we identified that the benefit is highest in patients with basal tumors. Our newly discovered classifier can identify these molecular subtypes in a single patient and could be integrated into routine clinical practice after further validation.
Summary Background Clinical prognostic groupings for localised prostate cancers are imprecise, with 30–50% of patients recurring after image-guided radiotherapy or radical prostatectomy. We aimed to ...test combined genomic and microenvironmental indices in prostate cancer to improve risk stratification and complement clinical prognostic factors. Methods We used DNA-based indices alone or in combination with intra-prostatic hypoxia measurements to develop four prognostic indices in 126 low-risk to intermediate-risk patients (Toronto cohort) who will receive image-guided radiotherapy. We validated these indices in two independent cohorts of 154 (Memorial Sloan Kettering Cancer Center cohort MSKCC cohort) and 117 (Cambridge cohort) radical prostatectomy specimens from low-risk to high-risk patients. We applied unsupervised and supervised machine learning techniques to the copy-number profiles of 126 pre-image-guided radiotherapy diagnostic biopsies to develop prognostic signatures. Our primary endpoint was the development of a set of prognostic measures capable of stratifying patients for risk of biochemical relapse 5 years after primary treatment. Findings Biochemical relapse was associated with indices of tumour hypoxia, genomic instability, and genomic subtypes based on multivariate analyses. We identified four genomic subtypes for prostate cancer, which had different 5-year biochemical relapse-free survival. Genomic instability is prognostic for relapse in both image-guided radiotherapy (multivariate analysis hazard ratio HR 4·5 95% CI 2·1–9·8; p=0·00013; area under the receiver operator curve AUC 0·70 95% CI 0·65–0·76) and radical prostatectomy (4·0 1·6–9·7; p=0·0024; AUC 0·57 0·52–0·61) patients with prostate cancer, and its effect is magnified by intratumoral hypoxia (3·8 1·2–12; p=0·019; AUC 0·67 0·61–0·73). A novel 100-loci DNA signature accurately classified treatment outcome in the MSKCC low-risk to intermediate-risk cohort (multivariate analysis HR 6·1 95% CI 2·0–19; p=0·0015; AUC 0·74 95% CI 0·65–0·83). In the independent MSKCC and Cambridge cohorts, this signature identified low-risk to high-risk patients who were most likely to fail treatment within 18 months (combined cohorts multivariate analysis HR 2·9 95% CI 1·4–6·0; p=0·0039; AUC 0·68 95% CI 0·63–0·73), and was better at predicting biochemical relapse than 23 previously published RNA signatures. Interpretation This is the first study of cancer outcome to integrate DNA-based and microenvironment-based failure indices to predict patient outcome. Patients exhibiting these aggressive features after biopsy should be entered into treatment intensification trials. Funding Movember Foundation, Prostate Cancer Canada, Ontario Institute for Cancer Research, Canadian Institute for Health Research, NIHR Cambridge Biomedical Research Centre, The University of Cambridge, Cancer Research UK, Cambridge Cancer Charity, Prostate Cancer UK, Hutchison Whampoa Limited, Terry Fox Research Institute, Princess Margaret Cancer Centre Foundation, PMH-Radiation Medicine Program Academic Enrichment Fund, Motorcycle Ride for Dad (Durham), Canadian Cancer Society.
Epigenetics is emerging as an attractive mechanism to explain the persistent genomic embedding of early-life experiences. Tightly linked to chromatin, which packages DNA into chromosomes, epigenetic ...marks primarily serve to regulate the activity of genes. DNA methylation is the most accessible and characterized component of the many chromatin marks that constitute the epigenome, making it an ideal target for epigenetic studies in human populations. Here, using peripheral blood mononuclear cells collected from a community-based cohort stratified for early-life socioeconomic status, we measured DNA methylation in the promoter regions of more than 14,000 human genes. Using this approach, we broadly assessed and characterized epigenetic variation, identified some of the factors that sculpt the epigenome, and determined its functional relation to gene expression. We found that the leukocyte composition of peripheral blood covaried with patterns of DNA methylation at many sites, as did demographic factors, such as sex, age, and ethnicity. Furthermore, psychosocial factors, such as perceived stress, and cortisol output were associated with DNA methylation, as was early-life socioeconomic status. Interestingly, we determined that DNA methylation was strongly correlated to the ex vivo inflammatory response of peripheral blood mononuclear cells to stimulation with microbial products that engage Toll-like receptors. In contrast, our work found limited effects of DNA methylation marks on the expression of associated genes across individuals, suggesting a more complex relationship than anticipated.
Ethnic differences in human DNA methylation have been shown for a number of CpG sites, but the genome-wide patterns and extent of these differences are largely unknown. In addition, whether the ...genetic control of polymorphic DNA methylation is population-specific has not been investigated.
Here we measure DNA methylation near the transcription start sites of over 14, 000 genes in 180 cell lines derived from one African and one European population. We find population-specific patterns of DNA methylation at over a third of all genes. Furthermore, although the methylation at over a thousand CpG sites is heritable, these heritabilities also differ between populations, suggesting extensive divergence in the genetic control of DNA methylation. In support of this, genetic mapping of DNA methylation reveals that most of the population specificity can be explained by divergence in allele frequencies between populations, and that there is little overlap in genetic associations between populations. These population-specific genetic associations are supported by the patterns of DNA methylation in several hundred brain samples, suggesting that they hold in vivo and across tissues.
These results suggest that DNA methylation is highly divergent between populations, and that this divergence may be due in large part to a combination of differences in allele frequencies and complex epistasis or gene × environment interactions.
Objectives To evaluate the ability of the Decipher genomic classifier in predicting metastasis from analysis of prostate needle biopsy diagnostic tumor tissue specimens. Materials and Methods ...Fifty-seven patients with available biopsy specimens were identified from a cohort of 169 men treated with radical prostatectomy in a previously reported Decipher validation study at Cleveland Clinic. A Cox multivariable proportional hazards model and survival C -index were used to evaluate the performance of Decipher. Results With a median follow up of 8 years, 8 patients metastasized and 3 died of prostate cancer. The Decipher plus National Comprehensive Cancer Network (NCCN) model had an improved C -index of 0.88 (95% confidence interval CI 0.77-0.96) compared to NCCN alone ( C -index 0.75, 95% CI 0.64-0.87). On multivariable analysis, Decipher was the only significant predictor of metastasis when adjusting for age, preoperative prostate-specific antigen and biopsy Gleason score (Decipher hazard ratio per 10% increase 1.72, 95% CI 1.07-2.81, P = .02). Conclusion Biopsy Decipher predicted the risk of metastasis at 10 years post radical prostatectomy. While further validation is required on larger cohorts, preoperative knowledge of Decipher risk derived from biopsy could indicate the need for multimodality therapy and help set patient expectations of therapeutic burden.
Abstract Background Decipher is a validated genomic classifier developed to determine the biological potential for metastasis after radical prostatectomy (RP). Objective To evaluate the ability of ...biopsy Decipher to predict metastasis and Prostate cancer-specific mortality (PCSM) in primarily intermediate- to high-risk patients treated with RP or radiation therapy (RT). Design, setting, and participants Two hundred and thirty-five patients treated with either RP ( n = 105) or RT ± androgen deprivation therapy ( n = 130) with available genomic expression profiles generated from diagnostic biopsy specimens from seven tertiary referral centers. The highest-grade core was sampled and Decipher was calculated based on a locked random forest model. Outcome measurements and statistical analysis Metastasis and PCSM were the primary and secondary outcomes of the study, respectively. Cox analysis and c-index were used to evaluate the performance of Decipher. Results and limitations With a median follow-up of 6 yr among censored patients, 34 patients developed metastases and 11 died of prostate cancer. On multivariable analysis, biopsy Decipher remained a significant predictor of metastasis (hazard ratio: 1.37 per 10% increase in score, 95% confidence interval CI: 1.06–1.78, p = 0.018) after adjusting for clinical variables. For predicting metastasis 5-yr post-biopsy, Cancer of the Prostate Risk Assessment score had a c-index of 0.60 (95% CI: 0.50–0.69), while Cancer of the Prostate Risk Assessment plus biopsy Decipher had a c-index of 0.71 (95% CI: 0.60–0.82). National Comprehensive Cancer Network risk group had a c-index of 0.66 (95% CI: 0.53–0.77), while National Comprehensive Cancer Network plus biopsy Decipher had a c-index of 0.74 (95% CI: 0.66–0.82). Biopsy Decipher was a significant predictor of PCSM (hazard ratio: 1.57 per 10% increase in score, 95% CI: 1.03–2.48, p = 0.037), with a 5-yr PCSM rate of 0%, 0%, and 9.4% for Decipher low, intermediate, and high, respectively. Conclusions Biopsy Decipher predicted metastasis and PCSM from diagnostic biopsy specimens of primarily intermediate- and high-risk men treated with first-line RT or RP. Patient summary Biopsy Decipher predicted metastasis and prostate cancer-specific mortality risk from diagnostic biopsy specimens.
Purpose To perform the first meta-analysis of the performance of the genomic classifier test, Decipher, in men with prostate cancer postprostatectomy. Methods MEDLINE, EMBASE, and the Decipher ...genomic resource information database were searched for published reports between 2011 and 2016 of men treated by prostatectomy that assessed the benefit of the Decipher test. Multivariable Cox proportional hazards models fit to individual patient data were performed; meta-analyses were conducted by pooling the study-specific hazard ratios (HRs) using random-effects modeling. Extent of heterogeneity between studies was determined with the I
test. Results Five studies (975 total patients, and 855 patients with individual patient-level data) were eligible for analysis, with a median follow-up of 8 years. Of the total cohort, 60.9%, 22.6%, and 16.5% of patients were classified by Decipher as low, intermediate, and high risk, respectively. The 10-year cumulative incidence metastases rates were 5.5%, 15.0%, and 26.7% ( P < .001), respectively, for the three risk classifications. Pooling the study-specific Decipher HRs across the five studies resulted in an HR of 1.52 (95% CI, 1.39 to 1.67; I
= 0%) per 0.1 unit. In multivariable analysis of individual patient data, adjusting for clinicopathologic variables, Decipher remained a statistically significant predictor of metastasis (HR, 1.30; 95% CI, 1.14 to 1.47; P < .001) per 0.1 unit. The C-index for 10-year distant metastasis of the clinical model alone was 0.76; this increased to 0.81 with inclusion of Decipher. Conclusion The genomic classifier test, Decipher, can independently improve prognostication of patients postprostatectomy, as well as within nearly all clinicopathologic, demographic, and treatment subgroups. Future study of how to best incorporate genomic testing in clinical decision-making and subsequent treatment recommendations is warranted.
Measurement of genome-wide DNA methylation (DNAm) has become an important avenue for investigating potential physiologically-relevant epigenetic changes. Illumina Infinium (Illumina, San Diego, CA, ...USA) is a commercially available microarray suite used to measure DNAm at many sites throughout the genome. However, it has been suggested that a subset of array probes may give misleading results due to issues related to probe design. To facilitate biologically significant data interpretation, we set out to enhance probe annotation of the newest Infinium array, the HumanMethylation450 BeadChip (450 k), with >485,000 probes covering 99% of Reference Sequence (RefSeq) genes (National Center for Biotechnology Information (NCBI), Bethesda, MD, USA). Annotation that was added or expanded on includes: 1) documented SNPs in the probe target, 2) probe binding specificity, 3) CpG classification of target sites and 4) gene feature classification of target sites.
Probes with documented SNPs at the target CpG (4.3% of probes) were associated with increased within-tissue variation in DNAm. An example of a probe with a SNP at the target CpG demonstrated how sample genotype can confound the measurement of DNAm. Additionally, 8.6% of probes mapped to multiple locations in silico. Measurements from these non-specific probes likely represent a combination of DNAm from multiple genomic sites. The expanded biological annotation demonstrated that based on DNAm, grouping probes by an alternative high-density and intermediate-density CpG island classification provided a distinctive pattern of DNAm. Finally, variable enrichment for differentially methylated probes was noted across CpG classes and gene feature groups, dependant on the tissues that were compared.
DNAm arrays offer a high-throughput approach for which careful consideration of probe content should be utilized to better understand the biological processes affected. Probes containing SNPs and non-specific probes may affect the assessment of DNAm using the 450 k array. Additionally, probe classification by CpG enrichment classes and to a lesser extent gene feature groups resulted in distinct patterns of DNAm. Thus, we recommend that compromised probes be removed from analyses and that the genomic context of DNAm is considered in studies deciphering the biological meaning of Illumina 450 k array data.
Abstract Background Radical prostatectomy (RP) is a primary treatment option for men with intermediate- and high-risk prostate cancer. Although many are effectively cured with local therapy alone, ...these men are by definition at higher risk of adverse pathologic features and clinical disease recurrence. It has been shown that the Decipher test predicts metastatic progression in cohorts that received adjuvant and salvage therapy following RP. Objective To evaluate the Decipher genomic classifier in a natural history cohort of men at risk who received no additional treatment until the time of metastatic progression. Design, setting, and participants Retrospective case-cohort design for 356 men who underwent RP between 1992 and 2010 at intermediate or high risk and received no additional treatment until the time of metastasis. Participants met the following criteria: (1) Cancer of the Prostate Risk Assessment postsurgical (CAPRA-S) score ≥3; (2) pathologic Gleason score ≥7; and (3) post-RP prostate-specific antigen nadir <0.2 ng/ml. Outcome measurements and statistical analysis The primary endpoint was defined as regional or distant metastases. Time-dependent receiver operating characteristic (ROC) curves, extension of decision curve analysis to survival data, and univariable and multivariable Cox proportional-hazards models were used to measure the discrimination, net benefit, and prognostic potential of genomic and pathologic risk factors. Cumulative incidence curves were constructed using Fine-Gray competing-risks analysis with appropriate weighting of the controls to account for the case-cohort study design. Results and limitations Ninety six patients had unavailable tumor blocks or failed microarray quality control. Decipher scores were then obtained for 260 patients, of whom 99 experienced metastasis. Decipher correlated with increased cumulative incidence of biochemical recurrence, metastasis, and prostate cancer–specific mortality ( p < 0.01). The cumulative incidence of metastasis was 12% and 47% for patients with low and high Decipher scores, respectively, at 10 yr after RP. Decipher was independently prognostic of metastasis in multivariable analysis (hazard ratio 1.26 per 10% increase; p < 0.01). Decipher had a c -index of 0.76 and increased the c -index of Eggener and CAPRA-S risk models from 0.76 and 0.77 to 0.86 and 0.87, respectively, at 10 yr after RP. Although the cohort was large, the single-center retrospective design is an important limitation. Conclusions In a patient population that received no adjuvant or salvage therapy after prostatectomy until metastatic progression, higher Decipher scores correlated with clinical events, and inclusion of Decipher scores improved the prognostic performance of validated clinicopathologic risk models. These results confirm the utility already reported for Decipher. Patient summary The Decipher test improves identification of patients most at risk of metastatic progression and death from prostate cancer after radical prostatectomy.
Fifteen-year-old adolescents (N = 109) in a longitudinal study of child development were recruited to examine differences in DNA methylation in relation to parent reports of adversity during the ...adolescents' infancy and preschool periods. Microarray technology applied to 28,000 cytosine—guanine dinucleotide sites within DNA derived from buccal epithelial cells showed differential methylation among adolescents whose parents reported high levels of stress during their children's early lives. Maternal stressors in infancy and paternal stressors in the preschool years were most strongly predictive of differential methylation, and the patterning of such epigenetic marks varied by children's gender. To the authors' knowledge, this is the first report of prospective associations between adversities in early childhood and the epigenetic conformation of adolescents' genomic DNA.
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