Major international projects are now underway aimed at creating a comprehensive catalog of all genes responsible for the initiation and progression of cancer. These studies involve sequencing of matched tumor–normal samples followed by mathematical analysis to identify those genes in which mutations occur more frequently than expected by random chance. Here, we describe a fundamental problem with cancer genome studies: as the sample size increases, the list of putatively significant genes produced by current analytical methods burgeons into the hundreds. The list includes many implausible genes (such as those encoding olfactory receptors and the muscle protein titin), suggesting extensive false positive findings that overshadow true driver events. Here, we show that this problem stems largely from mutational heterogeneity and provide a novel analytical methodology, MutSigCV, for resolving the problem. We apply MutSigCV to exome sequences from 3,083 tumor-normal pairs and discover extraordinary variation in (i) mutation frequency and spectrum within cancer types, which shed light on mutational processes and disease etiology, and (ii) mutation frequency across the genome, which is strongly correlated with DNA replication timing and also with transcriptional activity. By incorporating mutational heterogeneity into the analyses, MutSigCV is able to eliminate most of the apparent artefactual findings and allow true cancer genes to rise to attention.

Embryonal tumours of the central nervous system (CNS) represent a heterogeneous group of tumours about which little is known biologically, and whose diagnosis, on the basis of morphologic appearance alone, is controversial. Medulloblastomas, for example, are the most common malignant brain tumour of childhood, but their pathogenesis is unknown, their relationship to other embryonal CNS tumours is debated, and patients' response to therapy is difficult to predict. We approached these problems by developing a classification system based on DNA microarray gene expression data derived from 99 patient samples. Here we demonstrate that medulloblastomas are molecularly distinct from other brain tumours including primitive neuroectodermal tumours (PNETs), atypical teratoid/rhabdoid tumours (AT/RTs) and malignant gliomas. Previously unrecognized evidence supporting the derivation of medulloblastomas from cerebellar granule cells through activation of the Sonic Hedgehog (SHH) pathway was also revealed. We show further that the clinical outcome of children with medulloblastomas is highly predictable on the basis of the gene expression profiles of their tumours at diagnosis.

Clinical and pathological features of 52 infants and children with atypical teratoid/rhabdoid tumor (ATT/RhT) of the central nervous system are defined. This tumor is typically misdiagnosed as a primitive neuroectodermal tumor (PNET) primarily because 70% of ATT/RhTs contain fields indistinguishable from classic PNETs. Separation of these two tumor types is crucial because the prognosis for ATT/RhT is given even when treatment includes surgery with or without radio and/or chemotherapy. These tumors are most common in infants less than 2 years of age. The cases described in this study arose in intracranially in all but one instance, although one-third had already spread throughout the subarachnoid space at presentation. Clinical signs and symptoms and radiological features do not distinguish ATT/RhTs from PNETs. The tumors are composed entirely (13%) or partly (77%) or rhabdoid cells. Seventy percent contains fields of typical PNET alone or in combinations with mesenchymal and/r epithelial elements. The immunohistochemical profile is unique: epithelial membrane antigen, vimentin, and smooth-muscle actin are positive in the majority of tumors and markers for germ-cell tumors are consistently negative. Abnormalities of chromosome 22 distinguish ATT/RhTs from PNETs, which typically display an i(17q) abnormality.