VEGAWES: variational segmentation on whole exome sequencing for copy number detection

A variational algorithm to detect the clonal copy number substructure of tumors from scRNA-seq data

Single-cell RNA sequencing is the reference technology to characterize the composition of the tumor microenvironment and to study tumor heterogeneity at high resolution. Here we report Single CEll Variational ANeuploidy analysis (SCEVAN), a fast variational algorithm for the deconvolution of the clonal substructure of tumors from single-cell RNA-seq data. It uses a multichannel segmentation algorithm exploiting the assumption that all the cells in a given copy number clone share the same breakpoints. Thus, the smoothed expression profile of every individual cell constitutes part of the evidence of the copy number profile in each subclone. SCEVAN can automatically and accurately discriminate between malignant and non-malignant cells, resulting in a practical framework to analyze tumors and their microenvironment. We apply SCEVAN to datasets encompassing 106 samples and 93,322 cells from different tumor types and technologies. We demonstrate its application to characterize the intratumor heterogeneity and geographic evolution of malignant brain tumors.

The Use of Genetics for Reaching a Diagnosis in XY DSD

Reaching a firm diagnosis is vital for the long-term management of a patient with a difference or disorder of sex development (DSD). This is especially the case in XY DSD where the diagnostic yield is particularly low. Molecular genetic technology is playing an increasingly important role in the diagnostic process, and it is highly likely that it will be used more often at an earlier stage in the diagnostic process. In many cases of DSD, the clinical utility of molecular genetics is unequivocally clear, but in many other cases there is a need for careful exploration of the benefit of genetic diagnosis through long-term monitoring of these cases. Furthermore, the incorporation of molecular genetics into the diagnostic process requires a careful appreciation of the strengths and weaknesses of the evolving technology, and the interpretation of the results requires a clear understanding of the wide range of conditions that are associated with DSD.

Comprehensive Genomic Profiling of Patient-matched Head and Neck Cancer Cells: A Preclinical Pipeline for Metastatic and Recurrent Disease

Metastases and tumor recurrence have a major prognostic impact in head and neck squamous cell carcinoma (HNSCC); however, cellular models that comprehensively characterize metastatic and recurrent HNSCC are lacking. To this end, we obtained genomic, transcriptomic, and copy number profiles of the UM-SCC cell line panel, encompassing patient-matched metastatic and recurrent cells. UM-SCC cells recapitulate the most prevalent genomic alterations described in HNSCC, featuring common TP53, PI3K, NOTCH, and Hippo pathway mutations. This analysis identified a novel F977Y kinase domain PIK3CA mutation exclusively present in a recurrent cell line (UM-SCC14B), potentially conferring resistance to PI3K inhibitors. Small proline-rich protein 2A (SPRR2A), a protein involved in epithelial homeostasis and invasion, was one of the most consistently downregulated transcripts in metastatic and recurrent UM-SCC cells. Assessment of SPRR2A protein expression in a clinical cohort of patients with HNSCC confirmed common SPRR2A downregulation in primary tumors (61.9% of cases) and lymph node metastases (31.3%), but not in normal tissue. High expression of SPRR2A in lymph node metastases was, along with nonoropharyngeal location of the primary tumor, an independent prognostic factor for regional disease recurrence after surgery and radiotherapy (HR 2.81; 95% CI, 1.16-6.79; P = 0.02). These results suggest that SPRR2A plays a dual role in invasion and therapeutic resistance in HNSCC, respectively through its downregulation and overexpression. IMPLICATIONS: The current study reveals translationally relevant mechanisms underlying metastasis and recurrence in HNSCC and represents an adjuvant tool for preclinical research in this disease setting. Underlining its discovery potential this approach identified a PIK3CA-resistant mutation as well as SPRR2A as possible theragnostic markers.