Distinguishing Gastric/Esophageal Adenocarcinoma from Pancreatic Adenocarcinoma Using Methylation-Based Droplet Digital PCR.

The goal of this study was to develop a methylation-based droplet digital PCR to separate 2 cancer classes that do not have sensitive and specific immunohistochemical stains: gastric/esophageal and pancreatic adenocarcinomas. The assay used methylation-independent primers and methylation-dependent probes to assess a single differentially methylated CpG site; analyses of array data from The Cancer Genome Atlas network showed that high methylation at the cg06118999 probe supports the presence of cells originating from the stomach or esophagus (eg, as in gastric metastasis), whereas low methylation suggests that these cells are rare to absent (eg, pancreatic metastasis). On validation using formalin-fixed paraffin-embedded primary and metastatic samples from our institution, methylation-based droplet digital PCR targeting the corresponding CpG dinucleotide generated evaluable data for 60 of the 62 samples (97%) and correctly classified 50 of the 60 evaluable cases (83.3%), mostly adenocarcinomas from the stomach or pancreas. This ddPCR was created to be easy-to-interpret, rapid, inexpensive, and compatible with existing platforms at many clinical laboratories. We suggest that similarly accessible PCRs could be developed for other differentials in pathology that do not have sensitive and specific immunohistochemical stains.

Minimalist approaches to cancer tissue-of-origin classification by DNA methylation.

Classification of cancers by tissue-of-origin is fundamental to diagnostic pathology. While the combination of clinical data, tissue histology, and immunohistochemistry is usually sufficient, there remains a small but not insignificant proportion of difficult-to-classify cases. These challenging cases provide justification for ancillary molecular testing, including high-throughput DNA methylation array profiling, which promises cell-of-origin information and compatibility with formalin-fixed specimens. While diagnostically powerful, methylation profiling platforms are costly and technically challenging to implement, particularly for less well-resourced laboratories. To address this, we simulated the performance of "minimalist" methylation-based tests for cancer classification using publicly-available and internal institutional profiling data. These analyses showed that small and focused sets of the most informative CpG biomarkers from the arrays are sufficient for accurate diagnoses. As an illustrative example, one classifier, using information from just 53 out of about 450,000 available CpG probes, achieved an accuracy of 94.5% on 2575 fresh primary validation cases across 28 cancer types from The Cancer Genome Atlas Network. By training minimalist classifiers on formalin-fixed primary and metastatic cases, generally high accuracies were also achieved on additional datasets. These results support the potential of minimalist methylation testing, possibly via quantitative PCR and targeted next-generation sequencing platforms, in cancer classification.

DNA Methylation-Based Classification of Small B-Cell Lymphomas: A Proof-of-Principle Study.

Although most small B-cell lymphomas (SBCLs) can be diagnosed using routine methods, challenges exist. For example, marginal zone lymphomas (MZLs) can be difficult to rule-in, in large part because no widely-used, sensitive, and specific biomarker is available for the marginal zone cell of origin. In this study, it was hypothesized that DNA methylation array profiling can assist with the classification of SBCLs, including MZLs. Extramedullary SBCLs, including challenging cases, were reviewed internally for pathology consensus and profiled. By combining the resulting array data set with data sets from other groups, a set of 26 informative probes was selected and used to train machine learning models to classify 4 common SBCLs: chronic lymphocytic leukemia/small lymphocytic lymphoma, follicular lymphoma, mantle cell lymphoma, and MZL. Prediction probability cutoff was used to separate classifiable from unclassifiable cases, and show that the trained model was able to classify 95% of independent test cases (n = 264/279). The concordance between model predictions and pathology diagnoses was 99.6% (n = 262/263) among classifiable test cases. One validation reference test case was reclassified based on model prediction. The model was also used to predict the diagnoses of two challenging SBCLs. Although the differential examined and data on difficult cases are limited, these results support accurate methylation-based classification of SBCLs. Furthermore, high specificities of predictions suggest that methylation signatures can be used to rule-in MZLs.

Citocinas en la patogenia de la enfermedad inflamatoria intestinal / Cytokines in the pathogenesis of inflammatory bowel diseases

La enfermedad inflamatoria intestinal (EII) se debe a una respuesta exagerada frente a la flora bacteriana en la mucosa intestinal, en la que intervienen factores ambientales y genéticos. Los linfocitos T actúan tanto en el origen como en el mantenimiento de la EII, y su patrón de citocinas es diferente en la enfermedad de Crohn, con predominio de citocinas Th1, y en la CU, donde el perfil es Th2. Una vez iniciado el proceso inflamatorio, el balance entre citocinas proinflamatorias y reguladoras determina el grado de afectación y la forma de presentación de la enfermedad. El conocimiento en los mecanismos inmunológicos que intervienen en la EII, ha abierto nuevas líneas de trabajo con fines terapéuticos como son: la neutralización de citocinas proinflamatorias mediante anticuerpos y la administración de citocinas antiinflamatorias, que se encuentran en diferentes fases de investigación

Inflammatory bowel disease (IBD) is produced by an exaggerated response to bacterial flora within the intestinal mucous, in which both environmental and genetic factors are involved. T lymphocytes are involved during the genesis and maintenance of IBD, and their cytokine profile in Crohn's disease (mostly Th1 cytokines) is different from that in ulcerative colitis (mainly Th2 cytokines). After the inflammatory response has been established, the balance between proinflammatory and regulatory cytokines determines the degree of mucosal damage and the form of presentation. A deeper knowledge of the immunological mechanisms involved in IBD has opened new research lines aimed to the development of new therapies such as the neutralization of proinflammatory cytokines with antibodies and the administration of antiinflammatory cytokines, which are currently at different stages of research