An ordinary differential equation model for the multistep transformation to cancer

Cancer is viewed as a multistep process whereby a normal cell is transformed into a cancer cell through the acquisition of mutations. We reduce the complexities of cancer progression to a simple set of underlying rules that govern the transformation of normal cells to malignant cells. In doing so, we derive an ordinary differential equation model that explores how the balance of angiogenesis, cell death rates, genetic instability, and replication rates give rise to different kinetics in the development of cancer. The key predictions of the model are that cancer develops fastest through a particular ordering of mutations and that mutations in genes that maintain genomic integrity would be the most deleterious type of mutations to inherit. In addition, we perform a sensitivity analysis on the parameters included in the model to determine the probable contribution of each. This paper presents a novel approach to viewing the genetic basis of cancer from a systems biology perspective and provides the groundwork for other models that can be directly tied to clinical and molecular data.Comment: 12 pages, submitted to Journal of Theoretical Biolog

Cancer gene prioritization by integrative analysis of mRNA expression and DNA copy number data: a comparative review

A variety of genome-wide profiling techniques are available to probe complementary aspects of genome structure and function. Integrative analysis of heterogeneous data sources can reveal higher-level interactions that cannot be detected based on individual observations. A standard integration task in cancer studies is to identify altered genomic regions that induce changes in the expression of the associated genes based on joint analysis of genome-wide gene expression and copy number profiling measurements. In this review, we provide a comparison among various modeling procedures for integrating genome-wide profiling data of gene copy number and transcriptional alterations and highlight common approaches to genomic data integration. A transparent benchmarking procedure is introduced to quantitatively compare the cancer gene prioritization performance of the alternative methods. The benchmarking algorithms and data sets are available at http://intcomp.r-forge.r-project.orgComment: PDF file including supplementary material. 9 pages. Preprin

A preexisting rare PIK3CA e545k subpopulation confers clinical resistance to MEK plus CDK4/6 inhibition in NRAS melanoma and is dependent on S6K1 signaling

Combined MEK and CDK4/6 inhibition (MEKi + CDK4i) has shown promising clinical outcomes in patients with NRAS- mutant melanoma. Here, we interrogated longitudinal biopsies from a patient who initially responded to MEKi + CDK4i therapy but subsequently developed resistance. Whole-exome sequencing and functional validation identified an acquired PIK3CA E545K mutation as conferring drug resistance. We demonstrate that PIK3CA E545K preexisted in a rare subpopulation that was missed by both clinical and research testing, but was revealed upon multiregion sampling due to PIK3CA E545K being nonuniformly distributed. This resistant population rapidly expanded after the initiation of MEKi + CDK4i therapy and persisted in all successive samples even after immune checkpoint therapy and distant metastasis. Functional studies identified activated S6K1 as both a key marker and specific therapeutic vulnerability downstream of PIK3CA E545K -induced resistance. These results demonstrate that difficult-to-detect preexisting resistance mutations may exist more often than previously appreciated and also posit S6K1 as a common downstream therapeutic nexus for the MAPK, CDK4/6, and PI3K pathways. SIGNIFICANCE: We report the first characterization of clinical acquired resistance to MEKi + CDK4i, identifying a rare preexisting PIK3CA E545K subpopulation that expands upon therapy and exhibits drug resistance. We suggest that single-region pretreatment biopsy is insufficient to detect rare, spatially segregated drug-resistant subclones. Inhibition of S6K1 is able to resensitize PIK3CA E545K -expressing NRAS-mutant melanoma cells to MEKi + CDK4i. © 2018 AAC

SVDetect: a tool to identify genomic structural variations from paired-end and mate-pair sequencing data

Summary: We present SVDetect, a program designed to identify genomic structural variations from paired-end and mate-pair next-generation sequencing data produced by the Illumina GA and ABI SOLiD platforms. Applying both sliding-window and clustering strategies, we use anomalously mapped read pairs provided by current short read aligners to localize genomic rearrangements and classify them according to their type, e.g. large insertions–deletions, inversions, duplications and balanced or unbalanced inter-chromosomal translocations. SVDetect outputs predicted structural variants in various file formats for appropriate graphical visualization

TopoGSA: network topological gene set analysis

Summary: TopoGSA (Topology-based Gene Set Analysis) is a web-application dedicated to the computation and visualization of network topological properties for gene and protein sets in molecular interaction networks. Different topological characteristics, such as the centrality of nodes in the network or their tendency to form clusters, can be computed and compared with those of known cellular pathways and processes

Statistical tests for intra-tumour clonal co-occurrence and exclusivity

Tumour progression is an evolutionary process in which different clones evolve over time, leading to intra-tumour heterogeneity. Interactions between clones can affect tumour evolution and hence disease progression and treatment outcome. Intra-tumoural pairs of mutations that are overrepresented in a co-occurring or clonally exclusive fashion over a cohort of patient samples may be suggestive of a synergistic effect between the different clones carrying these mutations. We therefore developed a novel statistical testing framework, called GeneAccord, to identify such gene pairs that are altered in distinct subclones of the same tumour. We analysed our framework for calibration and power. By comparing its performance to baseline methods, we demonstrate that to control type I errors, it is essential to account for the evolutionary dependencies among clones. In applying GeneAccord to the single-cell sequencing of a cohort of 123 acute myeloid leukaemia patients, we find 1 clonally co-occurring and 8 clonally exclusive gene pairs. The clonally exclusive pairs mostly involve genes of the key signalling pathways

Amplification and Overexpression of Hsa-miR-30b, Hsa-miR-30d and KHDRBS3 at 8q24.22-q24.23 in Medulloblastoma

Medulloblastoma is the most common malignant brain tumour of childhood. The identification of critical genes involved in its pathogenesis will be central to advances in our understanding of its molecular basis, and the development of improved therapeutic approaches.We performed a SNP-array based genome-wide copy number analysis in medulloblastoma cell lines, to identify regions of genomic amplification and homozygous deletion, which may harbour critical disease genes. A series of novel and established medulloblastoma defects were detected (MYC amplification (n = 4), 17q21.31 high-level gain (n = 1); 9p21.1-p21.3 (n = 1) and 6q23.1 (n = 1) homozygous deletion). Most notably, a novel recurrent region of genomic amplification at 8q24.22-q24.23 was identified (n = 2), and selected for further investigation. Additional analysis by interphase fluorescence in situ hybridisation (iFISH), PCR-based mapping and SNP-array revealed this novel amplification at 8q24.22-q24.23 is independent of MYC amplification at 8q24.21, and is unique to medulloblastoma in over 800 cancer cell lines assessed from different tumour types, suggesting it contains key genes specifically involved in medulloblastoma development. Detailed mapping identified a 3Mb common minimal region of amplification harbouring 3 coding genes (ZFAT1, LOC286094, KHDRBS3) and two genes encoding micro-RNAs (hsa-miR-30b, hsa-miR-30d). Of these, only expression of hsa-miR-30b, hsa-miR-30d and KHDRBS3 correlated with copy number status, and all three of these transcripts also displayed evidence of elevated expression in sub-sets of primary medulloblastomas, measured relative to the normal cerebellum.These data implicate hsa-miR-30b, hsa-miR-30d and KHDRBS3 as putative oncogenic target(s) of a novel recurrent medulloblastoma amplicon at 8q24.22-q24.23. Our findings suggest critical roles for these genes in medulloblastoma development, and further support the contribution of micro-RNA species to medulloblastoma pathogenesis

The driver landscape of sporadic chordoma.

Chordoma is a malignant, often incurable bone tumour showing notochordal differentiation. Here, we defined the somatic driver landscape of 104 cases of sporadic chordoma. We reveal somatic duplications of the notochordal transcription factor brachyury (T) in up to 27% of cases. These variants recapitulate the rearrangement architecture of the pathogenic germline duplications of T that underlie familial chordoma. In addition, we find potentially clinically actionable PI3K signalling mutations in 16% of cases. Intriguingly, one of the most frequently altered genes, mutated exclusively by inactivating mutation, was LYST (10%), which may represent a novel cancer gene in chordoma.Chordoma is a rare often incurable malignant bone tumour. Here, the authors investigate driver mutations of sporadic chordoma in 104 cases, revealing duplications in notochordal transcription factor brachyury (T), PI3K signalling mutations, and mutations in LYST, a potential novel cancer gene in chordoma