Mutational signatures in tumours induced by high and low energy radiation in Trp53 deficient mice.

Ionising radiation (IR) is a recognised carcinogen responsible for cancer development in patients previously treated using radiotherapy, and in individuals exposed as a result of accidents at nuclear energy plants. However, the mutational signatures induced by distinct types and doses of radiation are unknown. Here, we analyse the genetic architecture of mammary tumours, lymphomas and sarcomas induced by high (56Fe-ions) or low (gamma) energy radiation in mice carrying Trp53 loss of function alleles. In mammary tumours, high-energy radiation is associated with induction of focal structural variants, leading to genomic instability and Met amplification. Gamma-radiation is linked to large-scale structural variants and a point mutation signature associated with oxidative stress. The genomic architecture of carcinomas, sarcomas and lymphomas arising in the same animals are significantly different. Our study illustrates the complex interactions between radiation quality, germline Trp53 deficiency and tissue/cell of origin in shaping the genomic landscape of IR-induced tumours

Understanding the role of genetic and environmental factors in cancer development

Cancer is a complex constellation of diseases, each driven by a variety of different environmental and genetic influences. Understanding how cancer development is shaped by these influences is paramount to developing better treatment and prevention protocols. In pursuit of this understanding I have undertaken an investigation into the forces molding tumor development in mouse models of cancer. To characterize the influence of the environment on tumor development as well as progression, I have utilized two independent models of chemical carcinogenesis. In the first model, we induced mouse lung tumors by either chemical or genetic means. By comparing between the two induction strategies we were able to demonstrate that chemical induction leaves an indelible mark on the tumor and is significantly different from signature of genetic induction. In the second model chemical carcinogens were used to induce primary carcinomas that were allowed to develop into metastases. By comparing the primary and metastatic lesions we found that shared mutations were defined by the chemical specificity of the inducing carcinogen, while mutations private to the metastases were representative of genomic instability. These results show that the influence of environmental factors can wax and wane during tumor development and progression.To gain insight on the genetic factors influencing cancer susceptibility, we investigated the genetics of body-mass index (BMI) and how this factor influences tumor development. We found that in a genetically heterogeneous mouse population elevated BMI strongly influenced cancer susceptibility. By carefully dissecting the genetics influencing BMI in this population we were able to identify a candidate gene (Panx3) linking BMI and tumorigenesis. This represents a significant step forward in our understanding of the genetics underlying these traits. Finally, we profiled the genetic elements contributing to the development of inflammation-driven tumors. Through a combined approach involving sequence, expression, and gene coexpression network analysis we were able to implicate the S100 gene family as a major factor influencing inflammation driven tumorigenesis. We further validated these claims in a human tumor cohort and demonstrated that network expression levels are severely impacted during tumor progression. The combined result of the work detailed in this dissertation is to illuminate the relationship between both environmental and genetic factors and cancer development through the use of mouse models. By extending these observations and methods to human data we hope to develop a better understanding of how human tumors develop, in order to improve both prevention and treatment strategies

Panx3 links body mass index and tumorigenesis in a genetically heterogeneous mouse model of carcinogen-induced cancer.

BackgroundBody mass index (BMI) has been implicated as a primary factor influencing cancer development. However, understanding the relationship between these two complex traits has been confounded by both environmental and genetic heterogeneity.MethodsIn order to gain insight into the genetic factors linking BMI and cancer, we performed chemical carcinogenesis on a genetically heterogeneous cohort of interspecific backcross mice ((Mus Spretus × FVB/N) F1 × FVB/N). Using this cohort, we performed quantitative trait loci (QTL) analysis to identify regions linked to BMI. We then performed an integrated analysis incorporating gene expression, sequence comparison between strains, and gene expression network analysis to identify candidate genes influencing both tumor development and BMI.ResultsAnalysis of QTL linked to tumorigenesis and BMI identified several loci associated with both phenotypes. Exploring these loci in greater detail revealed a novel relationship between the Pannexin 3 gene (Panx3) and both BMI and tumorigenesis. Panx3 is positively associated with BMI and is strongly tied to a lipid metabolism gene expression network. Pre-treatment Panx3 gene expression levels in normal skin are associated with tumor susceptibility and inhibition of Panx function strongly influences inflammation.ConclusionsThese studies have identified several genetic loci that influence both BMI and carcinogenesis and implicate Panx3 as a candidate gene that links these phenotypes through its effects on inflammation and lipid metabolism

Panx3 links body mass index and tumorigenesis in a genetically heterogeneous mouse model of carcinogen-induced cancer.

BackgroundBody mass index (BMI) has been implicated as a primary factor influencing cancer development. However, understanding the relationship between these two complex traits has been confounded by both environmental and genetic heterogeneity.MethodsIn order to gain insight into the genetic factors linking BMI and cancer, we performed chemical carcinogenesis on a genetically heterogeneous cohort of interspecific backcross mice ((Mus Spretus × FVB/N) F1 × FVB/N). Using this cohort, we performed quantitative trait loci (QTL) analysis to identify regions linked to BMI. We then performed an integrated analysis incorporating gene expression, sequence comparison between strains, and gene expression network analysis to identify candidate genes influencing both tumor development and BMI.ResultsAnalysis of QTL linked to tumorigenesis and BMI identified several loci associated with both phenotypes. Exploring these loci in greater detail revealed a novel relationship between the Pannexin 3 gene (Panx3) and both BMI and tumorigenesis. Panx3 is positively associated with BMI and is strongly tied to a lipid metabolism gene expression network. Pre-treatment Panx3 gene expression levels in normal skin are associated with tumor susceptibility and inhibition of Panx function strongly influences inflammation.ConclusionsThese studies have identified several genetic loci that influence both BMI and carcinogenesis and implicate Panx3 as a candidate gene that links these phenotypes through its effects on inflammation and lipid metabolism

Additional file 3: Table S7. of Panx3 links body mass index and tumorigenesis in a genetically heterogeneous mouse model of carcinogen-induced cancer

Gene expression phenotypes and sample IDs. This Excel file (.xlsx) contains phenotype information for the cohort of mice used for expression analysis. The samples are labeled both by mouse ID as well as by.CEL name, corresponding to the.CEL files available from the GEO site under access number GSE52650. (XLSX 90 kb

Additional file 2: Supplementary figures S1-S5 and supplementary tables S2-S6. of Panx3 links body mass index and tumorigenesis in a genetically heterogeneous mouse model of carcinogen-induced cancer

Supplementary figures and supplementary tables S2-S6. A Word (.docx) document containing all supplementary figures and supplementary tables S2-S6. Table S2: Sex interactions by QTL. Difference refers to the difference in means between heterozygous and homozygous mice. Table S3: BMI QTL and papilloma burden. Table S4: Genes significantly associated with BMI. Table S5: Panx3 network gene correlation levels by sex. Table S6: Panx3 polymorphisms between Spret and FVB mice. Figure S1: Twenty-week papilloma burden by BMI for male and female mice. Figure S2: QTL effect for the strongest autosomal QTL for each phenotype by sex for raw and mean-centered phenotype values. Figure S3: Proximal and distal regions of chromosome 10 influence weight in opposing directions. Figure S4: Effect of sex-specific QTL on BMI. Figure S5: Panx3 expression and tumor development. (DOCX 224 kb

Additional file 1: Table S1. of Panx3 links body mass index and tumorigenesis in a genetically heterogeneous mouse model of carcinogen-induced cancer

Genotype marker locations and associated rsIDs. An Excel file (.xlsx) containing information about the genotyping markers used in this analysis. (XLSX 66 kb

Evolution of metastasis revealed by mutational landscapes of chemically induced skin cancers

Human tumors show a high level of genetic heterogeneity, but the processes that influence the timing and route of metastatic dissemination of the subclones are unknown. Here we have used whole-exome sequencing of 103 matched benign, malignant and metastatic skin tumors from genetically heterogeneous mice to demonstrate that most metastases disseminate synchronously from the primary tumor, supporting parallel rather than linear evolution as the predominant model of metastasis. Shared mutations between primary carcinomas and their matched metastases have the distinct A-to-T signature of the initiating carcinogen dimethylbenzanthracene, but non-shared mutations are primarily G-to-T, a signature associated with oxidative stress. The existence of carcinomas that either did or did not metastasize in the same host animal suggests that there are tumor-intrinsic factors that influence metastatic seeding. We also demonstrate the importance of germline polymorphisms in determining allele-specific mutations, and we identify somatic genetic alterations that are specifically related to initiation of carcinogenesis by Hras or Kras mutations. Mouse tumors that mimic the genetic heterogeneity of human cancers can aid our understanding of the clonal evolution of metastasis and provide a realistic model for the testing of novel therapies

Gene Expression Architecture of Mouse Dorsal and Tail Skin Reveals Functional Differences in Inflammation and Cancer

Inherited germline polymorphisms can cause gene expression levels in normal tissues to differ substantially between individuals. We present an analysis of the genetic architecture of normal adult skin from 470 genetically unique mice, demonstrating the effect of germline variants, skin tissue location, and perturbation by exogenous inflammation or tumorigenesis on gene signaling pathways. Gene networks related to specific cell types and signaling pathways, including sonic hedgehog (Shh), Wnt, Lgr family stem cell markers, and keratins, differed at these tissue sites, suggesting mechanisms for the differential susceptibility of dorsal and tail skin to development of skin diseases and tumorigenesis. The Pten tumor suppressor gene network is rewired in premalignant tumors compared to normal tissue, but this response to perturbation is lost during malignant progression. We present a software package for expression quantitative trait loci (eQTL) network analysis and demonstrate how network analysis of whole tissues provides insights into interactions between cell compartments and signaling molecules