In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. A key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process vs. those that measure flux through the autophagy pathway (i.e., the complete process); thus, a block in macroautophagy that results in autophagosome accumulation needs to be differentiated from stimuli that result in increased autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field
Cell-free circulating DNA carries not only tumor-specific changes in its sequence but also distinctive epigenetic marks, namely DNA methylation, in certain GC-rich fragments. These fragments are usually located within the promoters and first exons of many genes, comprising CpG islands. Analysis of DNA methylation using cell-free circulating DNA can facilitate development of very accurate biomarkers for detection, diagnosis, prediction of response to therapy and prognosis of outcomes. Recent data suggest that benign and inflammatory diseases have very specific methylation patterns within cell-free circulating DNA, which are different from the pattern of a malignant tumor of the same organ. In addition, specific methylation patterns have been detected for cancers of different organs, so a differential diagnosis of site-specific cancer appears feasible. Currently, cancer-related applications dominate the field, although methylation-based biomarkers may also be possible for other diseases, including neurodegenerative and psychiatric disorders.
BACKGROUND: Although patients with chronic pancreatitis (CP) have an increased risk of pancreatic cancer (PanCa), the timely detection of PanCa often is difficult, because the symptoms of CP and PanCa are very similar. Moreover, secondary inflammation may be identified in PanCa, further complicating diagnosis. To improve the survival of patients with PanCa, a reliable test to differentiate CP from PanCa is needed. In this article, the authors describe a methylation profile of cell-free plasma DNA that distinguished CP from PanCa with >90% accuracy. METHODS: Methylation in cell-free, plasma DNA was compared among 30 samples from patients with CP, 30 samples from patients with PanCa, and 30 samples from healthy controls (N) using a microarray-mediated methylation analysis of 56 fragments in each sample (MethDet56). Statistical analysis was done by using the Fisher exact test, a naive Bayes algorithm, and 25 rounds of 5-fold cross-validation. RESULTS: The MethDet56 methylation analysis technique identified 17 gene promoters as informative (8 for distinguishing N from CP and 14 for distinguishing CP from PanCa). It achieved 81.7% sensitivity and 78% specificity (P<.01) in the detection of CP (N vs CP) and 91.2% sensitivity and 90.8% specificity (P<.01) in the differential detection of PanCa (PanCa vs CP). CONCLUSIONS: The current data suggested that, among patients with pancreatic disease, the methylation profiles of inflammatory disease and cancer are different and open a new venue for the development of biomarkers for differential diagnosis. Further investigation of diagnostic biomarkers for pancreatic cancer based on methylation in cell-free, circulating DNA appears to be warranted.
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