[Show abstract][Hide abstract] ABSTRACT: We present a novel hierarchical Bayes statistical model, xseq, to systematically quantify the impact of somatic mutations on expression profiles. We establish the theoretical framework and robust inference characteristics of the method using computational benchmarking. We then use xseq to analyse thousands of tumour data sets available through The Cancer Genome Atlas, to systematically quantify somatic mutations impacting expression profiles. We identify 30 novel cis-effect tumour suppressor gene candidates, enriched in loss-of-function mutations and biallelic inactivation. Analysis of trans-effects of mutations and copy number alterations with xseq identifies mutations in 150 genes impacting expression networks, with 89 novel predictions. We reveal two important novel characteristics of mutation impact on expression: (1) patients harbouring known driver mutations exhibit different downstream gene expression consequences; (2) expression patterns for some mutations are stable across tumour types. These results have critical implications for identification and interpretation of mutations with consequent impact on transcription in cancer.
[Show abstract][Hide abstract] ABSTRACT: Patient-derived xenograft (PDX) models are now being widely used in cancer research and have the potential to greatly inform our understanding of cancer biology. However, many questions remain, especially regarding the ability of PDX models to affect clinical decision making. With these points in mind, we asked three scientists to give their opinions on the generation and uses of PDX models and the future of this field.
Nature Reviews Cancer 04/2015; 15(5):311-6. DOI:10.1038/nrc3944 · 37.40 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: IntroductionThe extracellular signals regulating mammary epithelial cell growth are of relevance to understanding the pathophysiology of mammary epithelia, yet they remain poorly characterized. Here we applied an unbiased approach to understanding the functional role of signaling molecules in several models of normal physiological growth and translated these results to the biological understanding of breast cancer subtypes.Methods
We developed and utilized a cytogenetically normal clonal line of hTERT immortalized human mammary epithelial cells in a fibroblast-enhanced co-culture assay to conduct a genome-wide siRNA screen evaluating the functional effect of silencing each gene. Our selection endpoint was inhibition of growth. Rigorous post-screen validation processes including RT-QPCR to ensure on-target silencing, deconvolution of pooled siRNAs, and independent confirmation of effects with lentiviral shRNA constructs, identified a subset of genes required for mammary epithelial cell growth. Using three-dimensional (3D) Matrigel growth/differentiation assays and primary human mammary epithelial cell colony assays, we confirm that these growth effects are not limited to the 184hTERT cell line. We utilized the METABRIC dataset of 1,998 breast cancer patients to evaluate both the differential expression of these genes across breast cancer subtypes and their prognostic significance.ResultsWe identified 47 genes that are critically important for fibroblast-enhanced mammary epithelial cell growth. This group was enriched for several axonal guidance molecules and GPCRs, as well as the endothelin receptor, PROCR. The majority (43 out of 47) of genes identified in 2D were also required for 3D growth, with HSD17B2, SNN, and PROCR showing greater than 10-fold reductions in acinar formation. Several genes, including PROCR and the neuronal pathfinding molecules EFNA4 and NTN1, were also required for proper differentiation/polarization in 3D cultures. The 47 genes identified show a significant non-random enrichment for differential expression among 10 molecular subtypes of breast cancer, sampled from 1,998 patients. CD79A, SERPINH1, KCNJ5, and TMEM14C exhibit breast cancer subtype-independent overall survival differences.Conclusion
Diverse transmembrane signals are required for mammary epithelial cell growth in 2D and 3D conditions. Strikingly, we define novel roles for axonal pathfinding receptors and ligands and the endothelin receptor in both growth and differentiation.
Breast cancer research: BCR 01/2015; 17(1):4. DOI:10.1186/s13058-014-0510-y · 5.49 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Complex focal chromosomal rearrangements in cancer genomes, also called “firestorms”, can be scored from DNA copy number data. The complex arm-wise aberration index (CAAI) is a score that captures DNA copy number alterations that appear as focal complex events in tumors, and has potential prognostic value in breast cancer. This study aimed to validate this DNA-based prognostic index in breast cancer and test for the first time its potential prognostic value in ovarian cancer. Copy number alteration (CNA) data from 1950 breast carcinomas (METABRIC cohort) and 508 high-grade serous ovarian carcinomas (TCGA dataset) were analyzed. Cases were classified CAAI positive if at least one complex focal event was scored. Complex alterations were frequently localized on chromosome 8p (n = 159), 17q (n = 176) and 11q (n = 251). CAAI events on 11q were most frequent in estrogen receptor positive (ER+) cases and on 17q in estrogen receptor negative (ER−) cases. We found only a modest correlation between CAAI and the overall rate of genomic instability (GII) and number of breakpoints (r = 0.27 and r = 0.42, p < 0.001). Breast cancer specific survival (BCSS), overall survival (OS) and ovarian cancer progression free survival (PFS) were used as clinical end points in Cox proportional hazard model survival analyses. CAAI positive breast cancers (43%) had higher mortality: hazard ratio (HR) of 1.94 (95%CI, 1.62–2.32) for BCSS, and of 1.49 (95%CI, 1.30–1.71) for OS. Representations of the 70-gene and the 21-gene predictors were compared with CAAI in multivariable models and CAAI was independently significant with a Cox adjusted HR of 1.56 (95%CI, 1.23–1.99) for ER+ and 1.55 (95%CI, 1.11–2.18) for ER− disease. None of the expression-based predictors were prognostic in the ER− subset. We found that a model including CAAI and the two expression-based prognostic signatures outperformed a model including the 21-gene and 70-gene signatures but excluding CAAI. Inclusion of CAAI in the clinical prognostication tool PREDICT significantly improved its performance. CAAI positive ovarian cancers (52%) also had worse prognosis: HRs of 1.3 (95%CI, 1.1–1.7) for PFS and 1.3 (95%CI, 1.1–1.6) for OS. This study validates CAAI as an independent predictor of survival in both ER+ and ER− breast cancer and reveals a significant prognostic value for CAAI in high-grade serous ovarian cancer.
[Show abstract][Hide abstract] ABSTRACT: Genomic and phenotypic analyses indicate extensive intra- as well as intertumoral hetero- geneity in primary human malignant cell populations despite their clonal origin. Cellular DNA barcoding offers a powerful and unbiased alternative to track the number and size of multiple subclones within a single human tumour xenograft and their response to continued in vivo passaging. Using this approach we find clone-initiating cell frequencies that vary from B1/10 to B1/10,000 cells transplanted for two human breast cancer cell lines and breast cancer xenografts derived from three different patients. For the cell lines, these frequencies are negatively affected in transplants of more than 20,000 cells. Serial transplants reveal five clonal growth patterns (unchanging, expanding, diminishing, fluctuating or of delayed onset), whose predominance is highly variable both between and within original samples. This study thus demonstrates the high growth potential and diverse growth properties of xenografted human breast cancer cells.
[Show abstract][Hide abstract] ABSTRACT: Human cancers, including breast cancers, comprise clones differing in mutation content. Clones evolve dynamically in space and time following principles of Darwinian evolution, underpinning important emergent features such as drug resistance and metastasis. Human breast cancer xenoengraftment is used as a means of capturing and studying tumour biology, and breast tumour xenografts are generally assumed to be reasonable models of the originating tumours. However, the consequences and reproducibility of engraftment and propagation on the genomic clonal architecture of tumours have not been systematically examined at single-cell resolution. Here we show, using deep-genome and single-cell sequencing methods, the clonal dynamics of initial engraftment and subsequent serial propagation of primary and metastatic human breast cancers in immunodeficient mice. In all 15 cases examined, clonal selection on engraftment was observed in both primary and metastatic breast tumours, varying in degree from extreme selective engraftment of minor (<5% of starting population) clones to moderate, polyclonal engraftment. Furthermore, ongoing clonal dynamics during serial passaging is a feature of tumours experiencing modest initial selection. Through single-cell sequencing, we show that major mutation clusters estimated from tumour population sequencing relate predictably to the most abundant clonal genotypes, even in clonally complex and rapidly evolving cases. Finally, we show that similar clonal expansion patterns can emerge in independent grafts of the same starting tumour population, indicating that genomic aberrations can be reproducible determinants of evolutionary trajectories. Our results show that measurement of genomically defined clonal population dynamics will be highly informative for functional studies using patient-derived breast cancer xenoengraftment.
[Show abstract][Hide abstract] ABSTRACT: BRCA2 mutations are significantly associated with early onset breast cancer, and the tumour suppressing function of BRCA2 has been attributed to its involvement in homologous recombination (HR)-mediated DNA repair. In order to identify additional functions of BRCA2, we generated BRCA2-knockout HCT116 human colorectal carcinoma cells. Using genome-wide microarray analyses, we have discovered a link between the loss of BRCA2 and the up-regulation of a subset of interferon (IFN)-related genes, including APOBEC3F and APOBEC3G. The over-expression of IFN-related genes was confirmed in different human BRCA2−/− and mouse Brca2−/− tumour cell lines, and was independent of senescence and apoptosis. In isogenic wild type BRCA2 cells, we observed over-expression of IFN-related genes after treatment with DNA-damaging agents, and following ionizing radiation. Cells with endogenous DNA damage because of defective BRCA1 or RAD51 also exhibited over-expression of IFN-related genes. Transcriptional activity of the IFN-stimulated response element (ISRE) was increased in BRCA2 knockout cells, and the expression of BRCA2 greatly decreased IFN-α stimulated ISRE reporter activity, suggesting that BRCA2 directly represses the expression of IFN-related genes through the ISRE. Finally, the colony forming capacity of BRCA2 knockout cells was significantly reduced in the presence of either IFN-β or IFN-γ, suggesting that IFNs may have potential as therapeutic agents in cancer cells with BRCA2 mutations.
The Journal of Pathology 11/2014; 234(3). DOI:10.1002/path.4404 · 7.43 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The evolution of cancer genomes within a single tumor creates mixed cell populations with divergent somatic mutational landscapes. Inference of tumor subpopulations has been disproportionately focused on the assessment of somatic point mutations, whereas computational methods targeting evolutionary dynamics of copy number alterations (CNA) and loss of heterozygosity (LOH) in whole genome sequencing data remain under-developed. We present a novel probabilistic model, TITAN, to infer CNA and LOH events while accounting for mixtures of cell populations, thereby estimating the proportion of cells harboring each event. We evaluate TITAN on idealized mixtures, simulating clonal populations from whole genome sequences taken from genomically heterogeneous ovarian tumor sites collected from the same patient. In addition, we show in 23 whole genomes of breast tumors that inference of CNA and LOH using TITAN critically inform population structure and the nature of the evolving cancer genome. Finally, we experimentally validated subclonal predictions using fluorescence in situ hybridization (FISH) and single-cell sequencing from an ovarian cancer patient sample, thereby recapitulating the key modeling assumptions of TITAN.
Genome Research 07/2014; 24(11). DOI:10.1101/gr.180281.114 · 14.63 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The gut endocrine system is emerging as a central player in the control of appetite and glucose homeostasis, and as a rich source of peptides with therapeutic potential in the field of diabetes and obesity. In this study we have explored the physiology of insulin-like peptide 5 (Insl5), which we identified as a product of colonic enteroendocrine L-cells, better known for their secretion of glucagon-like peptide-1 and peptideYY. i.p. Insl5 increased food intake in wild-type mice but not mice lacking the cognate receptor Rxfp4. Plasma Insl5 levels were elevated by fasting or prolonged calorie restriction, and declined with feeding. We conclude that Insl5 is an orexigenic hormone released from colonic L-cells, which promotes appetite during conditions of energy deprivation.
Proceedings of the National Academy of Sciences 07/2014; 111(30). DOI:10.1073/pnas.1411413111 · 9.67 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Hypomethylating agents are widely used in patients with myelodysplastic syndromes and unfit patients with acute myeloid leukemia. However, it is not well understood why only some patients respond to hypomethylating agents. We found previously that the effect of decitabine on hematopoietic stem cell viability differed between Mll5 wildtype and null cells. We therefore investigated the role of MLL5 expression levels on outcome of acute myeloid leukemia patients who were treated with decitabine. MLL5 above the median expression level predicted longer overall survival independent of DNMT3A mutation status in bivariate analysis (median overall survival for high vs. low MLL5 expression, 292 vs. 167 days, P=.026). In patients who received 3 or more courses decitabine, high MLL5 expression and wildtype DNMT3A independently predicted improved overall survival (median overall survival for high vs. low MLL5 expression, 468 vs. 243 days, P=.012). In transformed murine cells, loss of Mll5 was associated with resistance to low-dose decitabine, less global DNA methylation in promoter regions, and reduced DNA demethylation upon decitabine treatment. Together, these data support our clinical observation of improved outcome in decitabine treated patients who express MLL5 at high levels, and suggest a mechanistic role of MLL5 in the regulation of DNA methylation.
[Show abstract][Hide abstract] ABSTRACT: In breast cancer, the TP53 gene is frequently mutated and the mutations have been associated with poor prognosis. The prognostic impact of the different types of TP53 mutations across the different molecular subtypes is still poorly understood. Here, we characterize the spectrum and prognostic significance of TP53 mutations with respect to the PAM50 subtypes and Integrative Clusters (IC). Experimental design: TP53 mutation status was obtained for 1420 tumor samples from the METABRIC cohort by sequencing all coding exons using the Sanger method.
TP53 mutations were found in 28.3% of the tumors, conferring a worse overall and breast cancer specific survival (HR=2.03, 95%CI=1.65-2.48, p<0.001), and were also found to be an independent marker of poor prognosis in estrogen receptor positive cases (HR=1.86, 95%CI=1.39-2.49, p<0.001). The mutation spectrum of TP53 varied between the breast cancer subtypes, and individual alterations showed subtype specific association. TP53 mutations were associated with increased mortality in patients with Luminal B, HER2-enriched and Normal-like tumors, but not in patients with Luminal A and Basal-like tumors. Similar observations were made in ICs, where mutation associated with poorer outcome in IC1, IC4 and IC5. The combined effect of TP53 mutation, TP53 LOH and MDM2 amplification on mortality was additive.
This study reveals that TP53 mutations have different clinical relevance in molecular subtypes of breast cancer, and suggests diverse roles for TP53 in the biology underlying breast cancer development.
Clinical Cancer Research 05/2014; 20(13). DOI:10.1158/1078-0432.CCR-13-2943 · 8.72 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Cancer evolves by mutation, with somatic reactivation of retrotransposons being one such mutational process. Germline retrotransposition can cause processed pseudogenes, but whether this occurs somatically has not been evaluated. Here we screen sequencing data from 660 cancer samples for somatically acquired pseudogenes. We find 42 events in 17 samples, especially non-small cell lung cancer (5/27) and colorectal cancer (2/11). Genomic features mirror those of germline LINE element retrotranspositions, with frequent target-site duplications (67%), consensus TTTTAA sites at insertion points, inverted rearrangements (21%), 5 0 truncation (74%) and polyA tails (88%). Transcriptional consequences include expression of pseudogenes from UTRs or introns of target genes. In addition, a somatic pseudogene that integrated into the promoter and first exon of the tumour suppressor gene, MGA, abrogated expression from that allele. Thus, formation of processed pseudogenes represents a new class of mutation occurring during cancer development, with potentially diverse functional consequences depending on genomic context.
[Show abstract][Hide abstract] ABSTRACT: We introduce PyClone, a statistical model for inference of clonal population structures in cancers. PyClone is a Bayesian clustering method for grouping sets of deeply sequenced somatic mutations into putative clonal clusters while estimating their cellular prevalences and accounting for allelic imbalances introduced by segmental copy-number changes and normal-cell contamination. Single-cell sequencing validation demonstrates PyClone's accuracy.
[Show abstract][Hide abstract] ABSTRACT: Amplification of the EMSY gene in sporadic breast and ovarian cancers is a poor prognostic indicator. Although EMSY has been linked to transcriptional silencing, its mechanism of action is unknown. Here, we report that EMSY acts as an oncogene, causing the transformation of cells in vitro and potentiating tumor formation and metastatic features in vivo. We identify an inverse correlation between EMSY amplification and miR-31 expression, an antimetastatic microRNA, in the METABRIC cohort of human breast samples. Re-expression of miR-31 profoundly reduced cell migration, invasion, and colony-formation abilities of cells overexpressing EMSY or haboring EMSY amplification. We show that EMSY is recruited to the miR-31 promoter by the DNA binding factor ETS-1, and it represses miR-31 transcription by delivering the H3K4me3 demethylase JARID1b/PLU-1/KDM5B. Altogether, these results suggest a pathway underlying the role of EMSY in breast cancer and uncover potential diagnostic and therapeutic targets in sporadic breast cancer.