Clonal selection drives genetic divergence of metastatic medulloblastoma

Medulloblastoma, the most common malignant paediatric brain tumour, arises in the cerebellum and disseminates through the cerebrospinal fluid in the leptomeningeal space to coat the brain and spinal cord. Dissemination, a marker of poor prognosis, is found in up to 40% of children at diagnosis and in most children at the time of recurrence. Affected children therefore are treated with radiation to the entire developing brain and spinal cord, followed by high-dose chemotherapy, with the ensuing deleterious effects on the developing nervous system. The mechanisms of dissemination through the cerebrospinal fluid are poorly studied, and medulloblastoma metastases have been assumed to be biologically similar to the primary tumour. Here we show that in both mouse and human medulloblastoma, the metastases from an individual are extremely similar to each other but are divergent from the matched primary tumour. Clonal genetic events in the metastases can be demonstrated in a restricted subclone of the primary tumour, suggesting that only rare cells within the primary tumour have the ability to metastasize. Failure to account for the bicompartmental nature of metastatic medulloblastoma could be a major barrier to the development of effective targeted therapies.     

Moving beyond Volatility Index (VIX): HARnessing the term structure of implied volatility

This paper considers how information from the implied volatility (IV) term structure can be harnessed to improve stock return volatility forecasting within the state-of-the-art HAR model. Factors are extracted from the IV term structure and included as exogenous variables in the HAR framework. We found that including slope and curvature factors leads to significant forecast improvements over the HAR benchmark at a range of forecast horizons, compared with the standard HAR model and HAR model with VIX as IV information set.     

The landscape of cancer genes and mutational processes in breast cancer

All cancers carry somatic mutations in their genomes. A subset, known as driver mutations, confer clonal selective advantage on cancer cells and are causally implicated in oncogenesis, and the remainder are passenger mutations. The driver mutations and mutational processes operative in breast cancer have not yet been comprehensively explored. Here we examine the genomes of 100 tumours for somatic copy number changes and mutations in the coding exons of protein-coding genes. The number of somatic mutations varied markedly between individual tumours. We found strong correlations between mutation number, age at which cancer was diagnosed and cancer histological grade, and observed multiple mutational signatures, including one present in about ten per cent of tumours characterized by numerous mutations of cytosine at TpC dinucleotides. Driver mutations were identified in several new cancer genes including AKT2, ARID1B, CASP8, CDKN1B, MAP3K1, MAP3K13, NCOR1, SMARCD1 and TBX3. Among the 100 tumours, we found driver mutations in at least 40 cancer genes and 73 different combinations of mutated cancer genes. The results highlight the substantial genetic diversity underlying this common disease.