DNA Methylation Profiling Enables Accurate Classification of Nonductal Primary Pancreatic Neoplasms

Background & Aims: Cytologic and histopathologic diagnosis of non-ductal pancreatic neoplasms can be challenging in daily clinical practice, whereas it is crucial for therapy and prognosis. The cancer methylome is successfully used as a diagnostic tool in other cancer entities. Here, we investigate if methylation profiling can improve the diagnostic work-up of pancreatic neoplasms. Methods: DNA methylation data were obtained for 301 primary tumors spanning 6 primary pancreatic neoplasms and 20 normal pancreas controls. Neural Network, Random Forest, and extreme gradient boosting machine learning models were trained to distinguish between tumor types. Methylation data of 29 nonpancreatic neoplasms (n = 3708) were used to develop an algorithm capable of detecting neoplasms of non-pancreatic origin. Results: After benchmarking 3 state-of-the-art machine learning models, the random forest model emerged as the best classifier with 96.9% accuracy. All classifications received a probability score reflecting the confidence of the prediction. Increasing the score threshold improved the random forest classifier performance up to 100% with 87% of samples with scores surpassing the cutoff. Using a logistic regression model, detection of nonpancreatic neoplasms achieved an area under the curve of >0.99. Analysis of biopsy specimens showed concordant classification with their paired resection sample. Conclusions: Pancreatic neoplasms can be classified with high accuracy based on DNA methylation signatures. Additionally, non-pancreatic neoplasms are identified with near perfect precision. In summary, methylation profiling can serve as a valuable adjunct in the diagnosis of pancreatic neoplasms with minimal risk for misdiagnosis, even in the pre-operative setting

Sarcoma classification by DNA methylation profiling

Sarcomas are malignant soft tissue and bone tumours affecting adults, adolescents and children. They represent a morphologically heterogeneous class of tumours and some entities lack defining histopathological features. Therefore, the diagnosis of sarcomas is burdened with a high inter-observer variability and misclassification rate. Here, we demonstrate classification of soft tissue and bone tumours using a machine learning classifier algorithm based on array-generated DNA methylation data. This sarcoma classifier is trained using a dataset of 1077 methylation profiles from comprehensively pre-characterized cases comprising 62 tumour methylation classes constituting a broad range of soft tissue and bone sarcoma subtypes across the entire age spectrum. The performance is validated in a cohort of 428 sarcomatous tumours, of which 322 cases were classified by the sarcoma classifier. Our results demonstrate the potential of the DNA methylation-based sarcoma classification for research and future diagnostic applications

Sclerosing epithelioid mesenchymal neoplasm of the pancreas - a proposed new entity

Contains fulltext : 217590.pdf (Publisher’s version ) (Closed access

Evolving Objects: a general purpose evolutionary computation library

This paper presents the evolving objects library (EOlib), an object-oriented framework for evolutionary computation (EC) that aims to provide a exible set of classes to build EC applications. EOlib design objective is to be able to evolve any object in which tness makes sense

Colorectal Carcinomas Containing Hypermethylated MLH1 Promoter and Wild-Type BRAF/KRAS Are Enriched for Targetable Kinase Fusions

Kinase fusions are rare and poorly characterized in colorectal carcinoma, yet they present unique opportunities for targeted therapy. In this study, we characterized kinase fusions from patients with advanced colorectal carcinoma who had MSK-IMPACT testing of their tumors between January 2014 and June 2018. Patients were analyzed for the presence of fusions, microsatellite instability (MSI), and mutations. Mismatch repair (MMR), IHC, and promoter hypermethylation status of MLH1 (MLH1ph) in microsatellite instability-high (MSI-H) colorectal carcinoma with fusions were investigated. Fusion transcripts were confirmed using a targeted RNA-seq panel assay. Of 2,314 colorectal carcinomas with MSK-IMPACT testing, 21 harbored kinase fusions. Overall 57% (12/21) of colorectal carcinoma fusions were MSI-H/MMR-D. Loss of MLH1 and MLH1ph was confirmed in all 12 and all 10 cases with available material, respectively. Fusions were present in 5% of MSI-H/MMR-D colorectal carcinoma compared with 0.4% of MSS/MMR-P colorectal carcinoma ( < 0.001) and 15% of MSI-H/MMR-D colorectal carcinoma with wild-type . Of 24 total MLH1-deficient colorectal carcinomas with MLH1ph and wild-type , 10 (42%) harbored kinase fusions. Kinase fusions in MSI-H colorectal carcinoma were associated with sporadic MLH1ph rather than with Lynch syndrome, and these patients may be eligible for kinase inhibitors, particularly following resistance or toxicity in response to immunotherapy. These findings identify a molecular subset of colorectal carcinoma with kinase fusions that may be responsive to kinase inhibitors. A high frequency of targetable kinase fusions in wild-type, MSI-H colorectal carcinoma offers a rationale for routine screening to identify patients with colorectal carcinoma with kinase fusions that may be responsive to kinase inhibitors.

Integrated clinical and genomic analysis identifies driver events and molecular evolution of colitis-associated cancers

Inflammation has long been recognized to contribute to cancer development, particularly across the gastrointestinal tract. Patients with inflammatory bowel disease have an increased risk for bowel cancers, and it has been posited that a field of genetic changes may underlie this risk. Here, we define the clinical features, genomic landscape, and germline alterations in 174 patients with colitis-associated cancers and sequenced 29 synchronous or isolated dysplasia. TP53 alterations, an early and highly recurrent event in colitis-associated cancers, occur in half of dysplasia, largely as convergent evolution of independent events. Wnt pathway alterations are infrequent, and our data suggest transcriptional rewiring away from Wnt. Sequencing of multiple dysplasia/cancer lesions from mouse models and patients demonstrates rare shared alterations between lesions. These findings suggest neoplastic bowel lesions developing in a background of inflammation experience lineage plasticity away from Wnt activation early during tumorigenesis and largely occur as genetically independent events

Sclerosing epithelioid mesenchymal neoplasm of the pancreas\ua0-\ua0a proposed new entity

We have encountered pancreatic tumors with unique histologic features, which do not conform to any of the known tumors of the pancreas or other anatomical sites. We aimed to define their clinicopathologic features and whether they are characterized by recurrent molecular signatures. Eight cases were identified; studied histologically and by immunohistochemistry. Selected cases were also subjected to whole-exome sequencing (WES; n\u2009=\u20094), RNA-sequencing (n\u2009=\u20096), Archer FusionPlex assay (n\u2009=\u20095), methylation profiling using the Illumina MethylationEPIC (850k) array platform (n\u2009=\u20096), and TERT promoter sequencing (n\u2009=\u20095). Six neoplasms occurred in females. The mean age was 43 years (range: 26-75). Five occurred in the head/neck of the pancreas. All patients were treated surgically; none received neoadjuvant/adjuvant therapy. All patients are free of disease after 53 months of median follow-up (range: 8-94). The tumors were well-circumscribed, and the median size was 1.8\u2009cm (range: 1.3-5.8). Microscopically, the unencapsulated tumors had a geographic pattern of epithelioid cell nests alternating with spindle cell fascicles. Some areas showed dense fibrosis, in which enmeshed tumor cells imparted a slit-like pattern. The predominant epithelioid cells had scant cytoplasm and round-oval nuclei with open chromatin. The spindle cells displayed irregular, hyperchromatic nuclei. Mitoses were rare. No lymph node metastases were identified. All tumors were positive for vimentin, CD99 and cytokeratin (patchy), while negative for markers of solid pseudopapillary neoplasm, neuroendocrine, acinar, myogenic/rhabdoid, vascular, melanocytic, or lymphoid differentiation, gastrointestinal stromal tumor as well as MUC4. Whole-exome sequencing revealed no recurrent somatic mutations or amplifications/homozygous deletions in any known oncogenes or tumor suppressor genes. RNA-sequencing and the Archer FusionPlex assay did not detect any recurrent likely pathogenic gene fusions. Single sample gene set enrichment analysis revealed that these tumors display a likely mesenchymal transcriptomic program. Unsupervised analysis (t-SNE) of their methylation profiles against a set of different mesenchymal neoplasms demonstrated a distinct methylation pattern. Here, we describe pancreatic neoplasms with unique morphologic/immunophenotypic features and a distinct methylation pattern, along with a lack of abnormalities in any of key genetic drivers, supporting that these neoplasms represent a novel entity with an indolent clinical course. Given their mesenchymal transcriptomic features, we propose the designation of "sclerosing epithelioid mesenchymal neoplasm" of the pancreas