To expedite the development and application of potentially transformative multicancer early detection assays, an international summit was hosted by the Mayo Clinic Cancer Center, the American Cancer ...Society, and the Union for International Cancer Control on World Cancer Day 2020 at the historic Mayowood Mansion in Rochester, Minnesota. Insights shared during this unique summit have been formulated into a series of expert‐authored commentaries, which accompany this introductory article.
Patients with inflammatory bowel diseases (IBDs), including ulcerative colitis and Crohn's disease, are at increased risk for colorectal cancer (CRC). Analyses of DNA methylation patterns in stool ...samples have been reported to detect CRC in patients with IBD. We sought to validate these findings in larger cohorts and assess the accuracy of analysis of DNA methylation patterns in stool for detection of CRC and high-grade dysplasia (HGD) normalized to methylation level at ZDHHC1.
We obtained buffered, frozen stool samples from a US case-control study and from 2 European surveillance cohorts (referral or population based) of patients with chronic ulcerative colitis (n = 248), Crohn's disease (n = 82), indeterminate colitis (n = 2), or IBD with primary sclerosing cholangitis (n = 38). Stool samples were collected before bowel preparation for colonoscopy or at least 1 week after colonoscopy. Among the study samples, stools from individuals with IBD but without neoplasia were used as controls (n = 291). DNA was isolated from stool, exposed to bisulfite, and then assayed by multiplex quantitative allele-specific real-time target and signal amplification. We analyzed methylation levels of BMP3, NDRG4, VAV3, and SFMBT2 relative to the methylation level of ZDHHC1, and compared these between patients with CRC or HGD and controls.
Levels of methylation at BMP3 and VAV3, relative to ZDHHC1 methylation, identified patients with CRC and HGD with an area under the curve value of 0.91 (95% CI, 0.77-1.00). Methylation levels at specific promotor regions of these genes identified 11 of the 12 patients with CRC and HGD, with 92% sensitivity (95% CI, 60%-100%) and 90% specificity (95% CI, 86%-93%). The proportion of false-positive results did not differ significantly among the case-control, referral cohort, and population cohort studies (P = .60) when the 90% specificity cut-off from the whole sample set was applied.
In an analysis of stool samples from 3 independent studies of 332 patients with IBD, we associated levels of methylation at 2 genes (BMP3 and VAV3), relative to level of methylation at ZDHHC1, with detection of CRC and HGD. These methylation patterns identified patients with CRC and HGD with more than 90% specificity, and might be used in CRC surveillance.
The role of methylation in pancreatic cancer risk remains unclear. We integrated genome and methylome data to identify CpG sites (CpG) with the genetically predicted methylation to be associated with ...pancreatic cancer risk. We also studied gene expression to understand the identified associations.
Using genetic data and white blood cell methylation data from 1,595 subjects of European descent, we built genetic models to predict DNA methylation levels. After internal and external validation, we applied prediction models with satisfactory performance to the genetic data of 8,280 pancreatic cancer cases and 6,728 controls of European ancestry to investigate the associations of predicted methylation with pancreatic cancer risk. For associated CpGs, we compared their measured levels in pancreatic tumor versus benign tissue.
We identified 45 CpGs at nine loci showing an association with pancreatic cancer risk, including 15 CpGs showing an association independent from identified risk variants. We observed significant correlations between predicted methylation of 16 of the 45 CpGs and predicted expression of eight adjacent genes, of which six genes showed associations with pancreatic cancer risk. Of the 45 CpGs, we were able to compare measured methylation of 16 in pancreatic tumor versus benign pancreatic tissue. Of them, six showed differentiated methylation.
We identified methylation biomarker candidates associated with pancreatic cancer using genetic instruments and added additional insights into the role of methylation in regulating gene expression in pancreatic cancer development.
A comprehensive study using genetic instruments identifies 45 CpG sites at nine genomic loci for pancreatic cancer risk.
Background
Limited data are available on the epidemiology of gastroesophageal junction adenocarcinoma (GEJAC), particularly in comparison to esophageal adenocarcinoma (EAC). With the advent of ...molecular non-endoscopic Barrett’s esophagus (BE) detection tests which sample the esophagus and gastroesophageal junction, early detection of EAC and GEJAC has become a possibility and their epidemiology has gained importance.
Aims
We sought to evaluate time trends in the epidemiology and survival of patients with EAC and GEJAC in a population-based cohort.
Methods
EAC and GEJAC patients from 1976 to 2019 were identified using ICD 9 and 10 diagnostic codes from the Rochester Epidemiology Project (REP). Clinical data and survival status were abstracted. Poisson regression was used to calculate incidence rate ratios (IRR). Survival analysis and Cox proportional models were used to assess predictors of survival.
Results
We included 443 patients (287 EAC,156 GEJAC). The incidence of EAC and GEJAC during 1976–2019 was 1.40 (CI 1.1–1.74) and 0.83 (CI 0.61–1.11) per 100,000 people, respectively. There was an increase in the incidence of EAC (IRR = 2.45,
p
= 0.011) and GEJAC (IRR = 3.17,
p
= 0.08) from 2000 to 2004 compared to 1995–1999, plateauing in later time periods. Most patients had associated BE and presented at advanced stages, leading to high 5-year mortality rates (66% in EAC and 59% in GEJAC). Age and stage at diagnosis were predictors of mortality.
Conclusion
The rising incidence of EAC/GEJAC appears to have plateaued somewhat in the last decade. However, both cancers present at advanced stages with persistently poor survival, underscoring the need for early detection.
Gastric adenocarcinoma is the third most common cause of cancer mortality worldwide. Accurate and affordable noninvasive detection methods have potential value for screening and surveillance. Herein, ...we identify novel methylated DNA markers (MDM) for gastric adenocarcinoma, validate their discrimination for gastric adenocarcinoma in tissues from geographically separate cohorts, explore marker acquisition through the oncogenic cascade, and describe distributions of candidate MDMs in plasma from gastric adenocarcinoma cases and normal controls.
Following discovery by unbiased whole-methylome sequencing, candidate MDMs were validated by blinded methylation-specific PCR in archival case-control tissues from U.S. and South Korean patients. Top MDMs were then assayed by an analytically sensitive method (quantitative real-time allele-specific target and signal amplification) in a blinded pilot study on archival plasma from gastric adenocarcinoma cases and normal controls.
Whole-methylome discovery yielded novel and highly discriminant candidate MDMs. In tissue, a panel of candidate MDMs detected gastric adenocarcinoma in 92% to 100% of U.S. and South Korean cohorts at 100% specificity. Levels of most MDMs increased progressively from normal mucosa through metaplasia, adenoma, and gastric adenocarcinoma with variation in points of greatest marker acquisition. In plasma, a 3-marker panel (
detected 86% (95% CI, 71-95) of gastric adenocarcinomas at 95% specificity.
Novel MDMs appear to accurately discriminate gastric adenocarcinoma from normal controls in both tissue and plasma. The point of aberrant methylation during oncogenesis varies by MDM, which may have relevance to marker selection in clinical applications. Further exploration of these MDMs for gastric adenocarcinoma screening and surveillance is warranted.
.
We have previously identified tissue methylated DNA markers (MDMs) associated with pancreatic ductal adenocarcinoma (PDAC). In this case-control study, we aimed to assess the diagnostic performance ...of plasma MDMs for PDAC.
Thirteen MDMs (
, and
) were identified on the basis of selection criteria applied to results of prior tissue experiments and assays were optimized in plasma. Next, 340 plasma samples (170 PDAC cases and 170 controls) were assayed using target enrichment long-probe quantitative amplified signal method. Initially, 120 advanced-stage PDAC cases and 120 healthy controls were used to train a prediction algorithm at 97.5% specificity using random forest modeling. Subsequently, the locked algorithm derived from the training set was applied to an independent blinded test set of 50 early-stage PDAC cases and 50 controls. Finally, data from all 340 patients were combined, and cross-validated.
The cross-validated area under the receiver operating characteristic curve (AUC) for the training set was 0.93 (0.89-0.96) for the MDM panel alone, 0.91 (95% confidence interval, 0.87-0.96) for carbohydrate antigen 19-9 (CA19-9) alone, and 0.99 (0.98-1) for the combined MDM-CA19-9 panel. In the test set of early-stage PDAC, the AUC for MDMs alone was 0.84 (0.76-0.92), CA19-9 alone was 0.87 (0.79-0.94), and combined MDM-CA19-9 panel was 0.90 (0.84-0.97) significantly better compared with either MDMs alone or CA19-9 alone (
= 0.0382 and 0.0490, respectively). At a preset specificity of 97.5%, the sensitivity for the combined panel in the test set was 80% (28%-99%) for stage I disease and 82% (68%-92%) for stage II disease. Using the combined datasets, the cross-validated AUC was 0.9 (0.86-0.94) for the MDM panel alone and 0.89 for CA19-9 alone (0.84-0.93) versus 0.97 (0.94-0.99) for the combined MDM-CA19-9 panel (
≤ 0.0001). Overall, cross-validated sensitivity of MDM-CA19-9 panel was 92% (83%-98%), with an observed specificity of 92% at the preset specificity of 97.5%.
Plasma MDMs in combination with CA19-9 detect PDAC with significantly higher accuracy compared with either biomarker individually.
Pancreatic cancer (PanC) presents at late stage with high mortality. Effective early detection methods are needed. Aberrantly methylated genes are unexplored as markers for noninvasive detection by ...stool testing. The authors aimed to select discriminant methylated genes and to assess accuracy of these and mutant KRAS in stool to detect PanC.
Nine target genes were assayed by real-time methylation-specific polymerase chain reaction (MSP) in bisulfite-treated DNA from microdissected frozen specimens of 24 PanC cases and 30 normal colon controls. Archived stools from 58 PanC cases and 65 controls matched on sex, age, and smoking were analyzed. Target genes from fecal supernatants were enriched by hybrid capture, bisulfite-treated, and assayed by MSP. KRAS mutations were assayed using the QuARTS technique.
Areas under the receiver operating characteristics curves (AUCs) for tissue BMP3, NDRG4, EYA4, UCHL1, MDFI, Vimentin, CNTNAP2, SFRP2, and TFPI2 were 0.90, 0.79, 0.78, 0.78, 0.77, 0.77, 0.69, 0.67, and 0.66, respectively. The top 4 markers and mutant KRAS were evaluated in stool. BMP3 was the most discriminant methylation marker in stool. At 90% specificity, methylated BMP3 alone detected 51% of PanCs, mutant KRAS detected 50%, and combination detected 67%. AUCs for methylated BMP3, mutant KRAS, and combination in stool were 0.73, 0.75, and 0.85, respectively.
This study demonstrates that stool assay of a methylated gene marker can detect PanC. Among candidate methylated markers discriminant in tissue, BMP3 alone performed well in stool. Combining methylated BMP3 and mutant KRAS increased stool detection over either marker alone.
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