DNA-methylation signature accurately differentiates pancreatic cancer from chronic pancreatitis in tissue and plasma.

OBJECTIVE: Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy. Differentiation from chronic pancreatitis (CP) is currently inaccurate in about one-third of cases. Misdiagnoses in both directions, however, have severe consequences for patients. We set out to identify molecular markers for a clear distinction between PDAC and CP. DESIGN: Genome-wide variations of DNA-methylation, messenger RNA and microRNA level as well as combinations thereof were analysed in 345 tissue samples for marker identification. To improve diagnostic performance, we established a random-forest machine-learning approach. Results were validated on another 48 samples and further corroborated in 16 liquid biopsy samples. RESULTS: Machine-learning succeeded in defining markers to differentiate between patients with PDAC and CP, while low-dimensional embedding and cluster analysis failed to do so. DNA-methylation yielded the best diagnostic accuracy by far, dwarfing the importance of transcript levels. Identified changes were confirmed with data taken from public repositories and validated in independent sample sets. A signature of six DNA-methylation sites in a CpG-island of the protein kinase C beta type gene achieved a validated diagnostic accuracy of 100% in tissue and in circulating free DNA isolated from patient plasma. CONCLUSION: The success of machine-learning to identify an effective marker signature documents the power of this approach. The high diagnostic accuracy of discriminating PDAC from CP could have tremendous consequences for treatment success, once the result from still a limited number of liquid biopsy samples would be confirmed in a larger cohort of patients with suspected pancreatic cancer.

Blood-Based Diagnosis and Risk Stratification of Patients with Pancreatic Intraductal Papillary Mucinous Neoplasm (IPMN).

PURPOSE: Intraductal papillary mucinous neoplasm (IPMN) is a precursor of pancreatic ductal adenocarcinoma. Low-grade dysplasia has a relatively good prognosis, whereas high-grade dysplasia and IPMN invasive carcinoma require surgical intervention. However, diagnostic distinction is difficult. We aimed to identify biomarkers in peripheral blood for accurate discrimination. EXPERIMENTAL DESIGN: Sera were obtained from 302 patients with IPMNs and 88 healthy donors. For protein biomarkers, serum samples were analyzed on microarrays made of 2,977 antibodies. A support vector machine (SVM) algorithm was applied to define classifiers, which were validated on a separate sample set. For microRNA biomarkers, a PCR-based screen was performed for discovery. Biomarker candidates confirmed by quantitative PCR were used to train SVM classifiers, followed by validation in a different sample set. Finally, a combined SVM classifier was established entirely independent of the earlier analyses, again using different samples for training and validation. RESULTS: Panels of 26 proteins or seven microRNAs could distinguish high- and low-risk IPMN with an AUC value of 95% and 94%, respectively. Upon combination, a panel of five proteins and three miRNAs yielded an AUC of 97%. These values were much better than those obtained in the same patient cohort by using the guideline criteria for discrimination. In addition, accurate discrimination was achieved between other patient subgroups. CONCLUSIONS: Protein and microRNA biomarkers in blood allow precise diagnosis and risk stratification of IPMN cases, which should improve patient management and thus the prognosis of IPMN patients. See related commentary by Löhr and Pantel, p. 1387.

Blood biomarkers for differential diagnosis and early detection of pancreatic cancer.

Pancreatic cancer is currently the most lethal tumor entity and case numbers are rising. It will soon be the second most frequent cause of cancer-related death in the Western world. Mortality is close to incidence and patient survival after diagnosis stands at about five months. Blood-based diagnostics could be one crucial factor for improving this dismal situation and is at a stage that could make this possible. Here, we are reviewing the current state of affairs with its problems and promises, looking at various molecule types. Reported results are evaluated in the overall context. Also, we are proposing steps toward clinical utility that should advance the development toward clinical application by improving biomarker quality but also by defining distinct clinical objectives and the respective diagnostic accuracies required to achieve them. Many of the discussed points and conclusions are highly relevant to other solid tumors, too.

Association of DNA repair gene polymorphisms with colorectal cancer risk and treatment outcomes.

Colorectal cancer (CRC) is the third most common carcinoma worldwide. Despite the progress in screening and treatment, CRC remains a leading cause of cancer-related mortality. Alterations to normal nucleic acid processing may drive neoplastic transformation of colorectal epithelium. DNA repair machinery performs an essential function in the protection of genome by reducing the number of genetic polymorphisms/variations that may drive carcinogenicity. Four essential DNA repair systems are known which include nucleotide excision repair (NER), base excision repair (BER), mismatch repair (MMR), and double-strand break repair (DSBR). Polymorphisms of DNA repair genes have been shown to influence the risk of cancer development as well as outcomes of treatment. Several studies demonstrated the association between genetic polymorphism of DNA repair genes and increased risk of CRC in different populations. In this review, we have summarized the impact of DNA repair gene polymorphisms on risk of CRC development and treatment outcomes. Advancements of the current understanding for the impact of DNA repair gene polymorphisms on the risk and treatment of CRC may support diagnostic and predictive roles in patients with CRC.

Association of a New Germline Variant in the MUTYH DNA Glycosylase Gene with Colorectal Adenoma Transformation into Malignancy

Background: MUTYH DNA glycosylase germline mutations are linked to the recessive inheritance of multiple adenoma. Studies have revealed that germline mutations in this gene are ethnicity related. This study aimed to identify the germline mutations in MUTYH gene and determine their prevalence among Jordanian patients with colorectal adenoma. Methods: In this study, 150 colorectal adenoma patients and 150 cancer-free individuals with no previous history of polyps were recruited. Sanger DNA sequencing of the MUTYH gene (accession number NG_008189.1) was carried out using 3130xL Genetic Analyzer. Sequencing results were analyzed by ChromasPro, and mutational effects were predicted by online bioinformatics tools. Results: Two novel variants, g.87C>T and c.1264G>C, were identified. g.87C>T was also found in 60 (40%) patients and 10 (6.7%) controls. However, c.1264G>C was detected in 90 (60%) patients and 7 (4.7%) controls. Thus, a significant association was observed between these two variants and colorectal adenoma (p value for both variants was <0.0001). Moreover, the newly identified germline variant, c.1264G>C, was found to be significantly associated with colorectal adenoma transformation into malignancy (p < 0.0001). Conclusion: The data showed high prevalence of two germline mutations in MUTYH gene among Jordanians with colorectal adenoma, which may make them as potential early biomarkers for diagnosis of colorectal adenoma.