We have sequenced the genomes of 110 small cell lung cancers (SCLC), one of the deadliest human cancers. In nearly all the tumours analysed we found bi-allelic inactivation of TP53 and RB1, sometimes by complex genomic rearrangements. Two tumours with wild-type RB1 had evidence of chromothripsis leading to overexpression of cyclin D1 (encoded by the CCND1 gene), revealing an alternative mechanism of Rb1 deregulation. Thus, loss of the tumour suppressors TP53 and RB1 is obligatory in SCLC. We discovered somatic genomic rearrangements of TP73 that create an oncogenic version of this gene, TP73Δex2/3. In rare cases, SCLC tumours exhibited kinase gene mutations, providing a possible therapeutic opportunity for individual patients. Finally, we observed inactivating mutations in NOTCH family genes in 25% of human SCLC. Accordingly, activation of Notch signalling in a pre-clinical SCLC mouse model strikingly reduced the number of tumours and extended the survival of the mutant mice. Furthermore, neuroendocrine gene expression was abrogated by Notch activity in SCLC cells. This first comprehensive study of somatic genome alterations in SCLC uncovers several key biological processes and identifies candidate therapeutic targets in this highly lethal form of cancer.

Mutational activation of BRAF is the earliest and most common genetic alteration in human melanoma. Hence, to build a model of human melanoma, we generated mice with conditional melanocyte-specific expression of BRafV600E. Upon induction of BRafV600E expression, mice developed benign melanocytic hyperplasias that failed to progress to melanoma over 15-20 months. By contrast, expression of BRafV600E combined with Pten tumor suppressor gene silencing elicited development of melanoma with 100% penetrance, short latency and with metastases observed in lymph nodes and lungs. Melanoma was prevented by inhibitors of mTorc1 (Rapamycin) or MEK1/2 (PD325901) but, upon cessation of drug administration, mice developed melanoma indicating the presence of long-lived melanoma-initiating cells in this system. Importantly, combined treatment with Rapamycin and PD325901 led to shrinkage of established melanomas. These mice, engineered with a common genetic profile to human melanoma, provide an excellent system to study melanoma’s cardinal feature of metastasis and for pre-clinical evaluation of agents designed to prevent or treat metastatic disease.

Myc is a pleiotropic basic helix–loop–helix leucine zipper transcription factor that coordinates expression of the diverse intracellular and extracellular programs that together are necessary for growth and expansion of somatic cells1. In principle, this makes inhibition of Myc an attractive pharmacological approach for treating diverse types of cancer. However, enthusiasm has been muted by lack of direct evidence that Myc inhibition would be therapeutically efficacious, concerns that it would induce serious side effects by inhibiting proliferation of normal tissues, and practical difficulties in designing Myc inhibitory drugs. We have modelled genetically both the therapeutic impact and the side effects of systemic Myc inhibition in a preclinical mouse model of Ras-induced lung adenocarcinoma by reversible, systemic expression of a dominant-interfering Myc mutant. We show that Myc inhibition triggers rapid regression of incipient and established lung tumours, defining an unexpected role for endogenous Myc function in the maintenance of Ras-dependent tumours in vivo. Systemic Myc inhibition also exerts profound effects on normal regenerating tissues. However, these effects are well tolerated over extended periods and rapidly and completely reversible. Our data demonstrate the feasibility of targeting Myc, a common downstream conduit for many oncogenic signals, as an effective, efficient and tumour-specific cancer therapy.

Background:Classification of endometrial carcinomas (ECs) by morphologic features is inconsistent, and yields limited prognostic and predictive information. A new system for classification based on the molecular categories identified in The Cancer Genome Atlas is proposed.Methods:Genomic data from the Cancer Genome Atlas (TCGA) support classification of endometrial carcinomas into four prognostically significant subgroups; we used the TCGA data set to develop surrogate assays that could replicate the TCGA classification, but without the need for the labor-intensive and cost-prohibitive genomic methodology. Combinations of the most relevant assays were carried forward and tested on a new independent cohort of 152 endometrial carcinoma cases, and molecular vs clinical risk group stratification was compared.Results:Replication of TCGA survival curves was achieved with statistical significance using multiple different molecular classification models (16 total tested). Internal validation supported carrying forward a classifier based on the following components: mismatch repair protein immunohistochemistry, POLE mutational analysis and p53 immunohistochemistry as a surrogate for ‘copy-number' status. The proposed molecular classifier was associated with clinical outcomes, as was stage, grade, lymph-vascular space invasion, nodal involvement and adjuvant treatment. In multivariable analysis both molecular classification and clinical risk groups were associated with outcomes, but differed greatly in composition of cases within each category, with half of POLE and mismatch repair loss subgroups residing within the clinically defined ‘high-risk' group. Combining the molecular classifier with clinicopathologic features or risk groups provided the highest C-index for discrimination of outcome survival curves.Conclusions:Molecular classification of ECs can be achieved using clinically applicable methods on formalin-fixed paraffin-embedded samples, and provides independent prognostic information beyond established risk factors. This pragmatic molecular classification tool has potential to be used routinely in guiding treatment for individuals with endometrial carcinoma and in stratifying cases in future clinical trials.

Molecular classification of ECs can be achieved using clinically applicable methods and provides independent prognostic information beyond established clinicopathologic risk factors available at diagnosis. Consistent, biologically relevant categorization enables stratification for clinical trials and/or targeted therapy, identification of women who are at increased risk of having Lynch syndrome, and may guide clinical management. Cancer 2017;123:802-13. © 2016 American Cancer Society.

SUMMARY The molecular basis for p53-mediated tumor suppression remains unclear. Here, to elucidate mechanisms of p53 tumor suppression, we use knock-in mice expressing an allelic series of p53 transcriptional activation mutants. Microarray analysis reveals that one mutant, p5325,26, is severely compromised for transactivation of most p53 target genes and cannot induce G1-arrest or apoptosis in response to acute DNA damage. Surprisingly, p5325,26 retains robust activity in senescence and tumor suppression, indicating that efficient transactivation of the majority of known p53 targets is dispensable for these pathways. In contrast, the transactivation-dead p5325,26,53,54 mutant cannot induce senescence or inhibit tumorigenesis, like p53-nullizygosity. Thus, p53 transactivation is essential for tumor suppression, but, intriguingly, in association with a small set of novel p53 target genes. Together, our studies distinguish the p53 transcriptional programs involved in acute DNA-damage responses and tumor suppression -- a critical goal for designing therapeutics that block p53-dependent side effects of chemotherapy without compromising p53 tumor suppression.

We have developed, confirmed, and now validated a pragmatic molecular classification tool (ProMisE) that provides consistent categorization of tumors and identifies four distinct prognostic molecular subtypes. ProMisE can be applied to diagnostic samples and thus could be used to inform surgical procedure(s) and/or need for adjuvant therapy. Based on the IOM guidelines this classifier is now ready for clinical evaluation through prospective clinical trials.

To identify common alleles associated with different histotypes of epithelial ovarian cancer (EOC), we pooled data from multiple genome-wide genotyping projects totaling 25,509 EOC cases and 40,941 controls. We identified nine new susceptibility loci for different EOC histotypes: six for serous EOC histotypes (3q28, 4q32.3, 8q21.11, 10q24.33, 18q11.2 and 22q12.1), two for mucinous EOC (3q22.3, 9q31.1) and one for endometrioid EOC (5q12.3). We then meta-analysed the results for high-grade serous ovarian cancer with the results from analysis of 31,448 BRCA1 and BRCA2 mutation carriers, including 3,887 mutation carriers with EOC. This identified an additional three loci at 2q13, 8q24.1 and 12q24.31. Integrated analyses of genes and regulatory biofeatures at each locus predicted candidate susceptibility genes, including OBFC1, a novel susceptibility gene for low grade/borderline serous EOC.