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.

We elucidated genomic and transcriptomic changes that accompany the evolution of melanoma from pre-malignant lesions by sequencing DNA and RNA from primary melanomas and their adjacent precursors, as well as matched primary tumors and regional metastases. In total, we analyzed 230 histopathologically distinct areas of melanocytic neoplasia from 82 patients. Somatic alterations sequentially induced mitogen-activated protein kinase (MAPK) pathway activation, upregulation of telomerase, modulation of the chromatin landscape, G1/S checkpoint override, ramp-up of MAPK signaling, disruption of the p53 pathway, and activation of the PI3K pathway; no mutations were specifically associated with metastatic progression, as these pathways were perturbed during the evolution of primary melanomas. UV radiation-induced point mutations steadily increased until melanoma invasion, at which point copy-number alterations also became prevalent.

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 RAS/BRAF 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 (P < 0.001) and 15% of MSI-H/MMR-D colorectal carcinoma with wild-type RAS/BRAF. Of 24 total MLH1deficient colorectal carcinomas with MLH1ph and wild-type RAS/BRAF, 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.Significance: A high frequency of targetable kinase fusions in BRAF/RAS 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.

Recent proliferation of low-cost DNA sequencing techniques will soon lead to an explosive growth in the number of sequenced genomes and will turn manual annotations into a luxury. Mass spectrometry recently emerged as a valuable technique for proteogenomic annotations that improves on the state-of-the-art in predicting genes and other features. However, previous proteogenomic approaches were limited to a single genome and did not take advantage of analyzing mass spectrometry data from multiple genomes at once. We show that such a comparative proteogenomics approach (like comparative genomics) allows one to address the problems that remained beyond the reach of the traditional "single proteome" approach in mass spectrometry. In particular, we show how comparative proteogenomics addresses the notoriously difficult problem of "one-hit-wonders" in proteomics, improves on the existing gene prediction tools in genomics, and allows identification of rare post-translational modifications. We therefore argue that complementing DNA sequencing projects by comparative proteogenomics projects can be a viable approach to improve both genomic and proteomic annotations.

Circulating cell-free DNA from blood plasma of cancer patients can be used to non-invasively interrogate somatic tumor alterations. Here we develop MSK-ACCESS (Memorial Sloan Kettering - Analysis of Circulating cfDNA to Examine Somatic Status), an NGS assay for detection of very low frequency somatic alterations in 129 genes. Analytical validation demonstrated 92% sensitivity in de-novo mutation calling down to 0.5% allele frequency and 99% for a priori mutation profiling. To evaluate the performance of MSK-ACCESS, we report results from 681 prospective blood samples that underwent clinical analysis to guide patient management. Somatic alterations are detected in 73% of the samples, 56% of which have clinically actionable alterations. The utilization of matched normal sequencing allows retention of somatic alterations while removing over 10,000 germline and clonal hematopoiesis variants. Our experience illustrates the importance of analyzing matched normal samples when interpreting cfDNA results and highlights the importance of cfDNA as a genomic profiling source for cancer patients.

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Background The establishment of whole-slide imaging (WSI) as a medical diagnostic device allows that pathologists may evaluate mitotic activity with this new technology. Furthermore, the image digitalization provides an opportunity to develop algorithms for automatic quantifications, ideally leading to improved reproducibility as compared to the naked eye examination by pathologists. In order to implement them effectively, accuracy of mitotic figure detection using WSI should be investigated. In this study, we aimed to measure pathologist performance in detecting mitotic figures (MFs) using multiple platforms (multiple scanners) and compare the results with those obtained using a brightfield microscope. Methods Four slides of canine oral melanoma were prepared and digitized using 4 WSI scanners. In these slides, 40 regions of interest (ROIs) were demarcated, and five observers identified the MFs using different viewing modes: microscopy and WSI. We evaluated the inter- and intra-observer agreements between modes with Cohen’s Kappa and determined “true” MFs with a consensus panel. We then assessed the accuracy (agreement with truth) using the average of sensitivity and specificity. Results In the 40 ROIs, 155 candidate MFs were detected by five pathologists; 74 of them were determined to be true MFs. Inter- and intra-observer agreement was mostly “substantial” or greater (Kappa = 0.594–0.939). Accuracy was between 0.632 and 0.843 across all readers and modes. After averaging over readers for each modality, we found that mitosis detection accuracy for 3 of the 4 WSI scanners was significantly less than that of the microscope ( p = 0.002, 0.012, and 0.001). Conclusions This study is the first to compare WSIs and microscopy in detecting MFs at the level of individual cells. Our results suggest that WSI can be used for mitotic cell detection and offers similar reproducibility to the microscope, with slightly less accuracy.

A subset of glioblastomas (GBMs) harbors potentially druggable oncogenic FGFR3-TACC3 (F3T3) fusions. However, their associated molecular and clinical features are poorly understood. Here we analyze the frequency of F3T3-fusion positivity, its associated genetic and methylation profiles, and its impact on survival in 906 IDH-wildtype GBM patients. We establish an F3T3 prevalence of 4.1% and delineate its associations with cancer signaling pathway alterations. F3T3-positive GBMs had lower tumor mutational and copy-number alteration burdens than F3T3-wildtype GBMs. Although F3T3 fusions were predominantly mutually exclusive with other oncogenic RTK pathway alterations, they did rarely co-occur with EGFR amplification. They were less likely to harbor TP53 alterations. By methylation profiling, they were more likely to be assigned the mesenchymal or RTK II subclass. Despite being older at diagnosis and having similar frequencies of MGMT promoter hypermethylation, patients with F3T3-positive GBMs lived about 8 months longer than those with F3T3-wildtype tumors. While consistent with IDH-wildtype GBM, F3T3-positive GBMs exhibit distinct biological features, underscoring the importance of pursuing molecular studies prior to clinical trial enrollment and targeted treatment.