IST Austria Technical Report

A comprehensive understanding of the clonal evolution of cancer is critical for understanding neoplasia. Genome-wide sequencing data enables evolutionary studies at unprecedented depth. However, classical phylogenetic methods often struggle with noisy sequencing data of impure DNA samples and fail to detect subclones that have different evolutionary trajectories. We have developed a tool, called Treeomics, that allows us to reconstruct the phylogeny of a cancer with commonly available sequencing technologies. Using Bayesian inference and Integer Linear Programming, robust phylogenies consistent with the biological processes underlying cancer evolution were obtained for pancreatic, ovarian, and prostate cancers. Furthermore, Treeomics correctly identified sequencing artifacts such as those resulting from low statistical power; nearly 7% of variants were misclassified by conventional statistical methods. These artifacts can skew phylogenies by creating illusory tumor heterogeneity among distinct samples. Importantly, we show that the evolutionary trees generated with Treeomics are mathematically optimal

Juvenile hormone regulates body size and perturbs insulin signaling in Drosophila

The role of juvenile hormone (JH) in regulating the timing and nature of insect molts is well-established. Increasing evidence suggests that JH is also involved in regulating final insect size. Here we elucidate the developmental mechanism through which JH regulates body size in developing Drosophila larvae by genetically ablating the JH-producing organ, the corpora allata (CA). We found that larvae that lack CA pupariated at smaller sizes than control larvae due to a reduced larval growth rate. Neither the timing of the metamorphic molt nor the duration of larval growth was affected by the loss of JH. Further, we show that the effects of JH on growth rate are dependent on the forkhead box O transcription factor (FOXO), which is negatively regulated by the insulin-signaling pathway. Larvae that lacked the CA had elevated levels of FOXO activity, whereas a loss-of-function mutation of FOXO rescued the effects of CA ablation on final body size. Finally, the effect of JH on growth appears to be mediated, at least in part, via ecdysone synthesis in the prothoracic gland. These results indicate a role of JH in regulating growth rate via the ecdysone- and insulin-signaling pathways.National Science Foundation Grants: (IOS-0919855, IOS-084584), Howard Hughes Medical Institute, Fundação Calouste Gulbenkian, FCT : [SFRH/Bolsas de Pós-Doutoramento (BPD)/74313/2010]

Prevalence of filarioid nematodes and trypanosomes in American robins and house sparrows, Chicago USA

AbstractHosts are commonly infected with a suite of parasites, and interactions among these parasites can affect the size, structure, and behavior of host–parasite communities. As an important step to understanding the significance of co-circulating parasites, we describe prevalence of co-circulating hemoparasites in two important avian amplification hosts for West Nile virus (WNV), the American robin (Turdus migratorius) and house sparrow (Passer domesticus), during the 2010–2011 in Chicago, Illinois, USA. Rates of nematode microfilariemia were 1.5% of the robins (n=70) and 4.2% of the house sparrows (n=72) collected during the day and 11.1% of the roosting robins (n=63) and 0% of the house sparrows (n=11) collected at night. Phylogenetic analysis of nucleotide sequences of the 18S rRNA and cytochrome oxidase subunit I (COI) genes from these parasites resolved two clades of filarioid nematodes. Microscopy revealed that 18.0% of American robins (n=133) and 16.9% of house sparrows (n=83) hosted trypanosomes in the blood. Phylogenetic analysis of nucleotide sequences from the 18s rRNA gene revealed that the trypanosomes fall within previously described avian trypanosome clades. These results document hemoparasites in the blood of WNV hosts in a center of endemic WNV transmission, suggesting a potential for direct or indirect interactions with the virus

Abstract 2374: Reconstructing the evolutionary history of metastatic cancers

Reconstructing the evolutionary history of metastases is critical for understanding their basic biological principles and has profound clinical implications. Genome-wide sequencing data has enabled modern phylogenomic methods to accurately dissect subclones and their phylogenies from noisy and impure bulk tumor samples at unprecedented depth. However, existing methods are not designed to infer metastatic seeding patterns. We have developed a tool, called Treeomics, that utilizes Bayesian inference and Integer Linear Programming to reconstruct the phylogeny of metastases. Treeomics allowed us to infer comprehensive seeding patterns for pancreatic, ovarian, and prostate cancers. Moreover, Treeomics correctly disambiguated true seeding patterns from sequencing artifacts; 7% of variants were misclassified by conventional statistical methods. These artifacts can skew phylogenies by creating illusory tumor heterogeneity among distinct samples. Last, we performed in silico benchmarking on simulated tumor phylogenies across a wide range of sample purities (30-90%) and sequencing depths (50-800x) to demonstrate the high accuracy of Treeomics compared to existing methods.Mathematic

Limited heterogeneity of known driver gene mutations among the metastases of individual patients with pancreatic cancer

The extent of heterogeneity among driver gene mutations present in naturally occurring metastases - that is, treatment-naive metastatic disease - is largely unknown. To address this issue, we carried out 60× whole-genome sequencing of 26 metastases from four patients with pancreatic cancer. We found that identical mutations in known driver genes were present in every metastatic lesion for each patient studied. Passenger gene mutations, which do not have known or predicted functional consequences, accounted for all intratumoral heterogeneity. Even with respect to these passenger mutations, our analysis suggests that the genetic similarity among the founding cells of metastases was higher than that expected for any two cells randomly taken from a normal tissue. The uniformity of known driver gene mutations among metastases in the same patient has critical and encouraging implications for the success of future targeted therapies in advanced-stage disease

Widespread somatic L1 retrotransposition occurs early during gastrointestinal cancer evolution

Somatic L1 retrotransposition events have been shown to occur in epithelial cancers. Here, we attempted to determine how early somatic L1 insertions occurred during the development of gastrointestinal (GI) cancers. Using L1-targeted resequencing (L1-seq), we studied different stages of four colorectal cancers arising from colonic polyps, seven pancreatic carcinomas, as well as seven gastric cancers. Surprisingly, we found somatic L1 insertions not only in all cancer types and metastases but also in colonic adenomas, well-known cancer precursors. Some insertions were also present in low quantities in normal GI tissues, occasionally caught in the act of being clonally fixed in the adjacent tumors. Insertions in adenomas and cancers numbered in the hundreds, and many were present in multiple tumor sections, implying clonal distribution. Our results demonstrate that extensive somatic insertional mutagenesis occurs very early during the development of GI tumors, probably before dysplastic growth

Neoantigen quality predicts immunoediting in survivors of pancreatic cancer.

Cancer immunoediting1 is a hallmark of cancer2 that predicts that lymphocytes kill more immunogenic cancer cells to cause less immunogenic clones to dominate a population. Although proven in mice1,3, whether immunoediting occurs naturally in human cancers remains unclear. Here, to address this, we investigate how 70 human pancreatic cancers evolved over 10 years. We find that, despite having more time to accumulate mutations, rare long-term survivors of pancreatic cancer who have stronger T cell activity in primary tumours develop genetically less heterogeneous recurrent tumours with fewer immunogenic mutations (neoantigens). To quantify whether immunoediting underlies these observations, we infer that a neoantigen is immunogenic (high-quality) by two features-'non-selfness'  based on neoantigen similarity to known antigens4,5, and 'selfness'  based on the antigenic distance required for a neoantigen to differentially bind to the MHC or activate a T cell compared with its wild-type peptide. Using these features, we estimate cancer clone fitness as the aggregate cost of T cells recognizing high-quality neoantigens offset by gains from oncogenic mutations. With this model, we predict the clonal evolution of tumours to reveal that long-term survivors of pancreatic cancer develop recurrent tumours with fewer high-quality neoantigens. Thus, we submit evidence that that the human immune system naturally edits neoantigens. Furthermore, we present a model to predict how immune pressure induces cancer cell populations to evolve over time. More broadly, our results argue that the immune system fundamentally surveils host genetic changes to suppress cancer

Epigenetic and Transcriptional Variability Shape Phenotypic Plasticity.

Epigenetic and transcriptional variability contribute to the vast diversity of cellular and organismal phenotypes and are key in human health and disease. In this review, we describe different types, sources, and determinants of epigenetic and transcriptional variability, enabling cells and organisms to adapt and evolve to a changing environment. We highlight the latest research and hypotheses on how chromatin structure and the epigenome influence gene expression variability. Further, we provide an overview of challenges in the analysis of biological variability. An improved understanding of the molecular mechanisms underlying epigenetic and transcriptional variability, at both the intra- and inter-individual level, provides great opportunity for disease prevention, better therapeutic approaches, and personalized medicine

An exactly solvable, spatial model of mutation accumulation in cancer

One of the hallmarks of cancer is the accumulation of driver mutations which increase the net reproductive rate of cancer cells and allow them to spread. This process has been studied in mathematical models of well mixed populations, and in computer simulations of three-dimensional spatial models. But the computational complexity of these more realistic, spatial models makes it difficult to simulate realistically large and clinically detectable solid tumours. Here we describe an exactly solvable mathematical model of a tumour featuring replication, mutation and local migration of cancer cells. The model predicts a quasi-exponential growth of large tumours, even if different fragments of the tumour grow sub-exponentially due to nutrient and space limitations. The model reproduces clinically observed tumour growth times using biologically plausible rates for cell birth, death, and migration rates. We also show that the expected number of accumulated driver mutations increases exponentially in time if the average fitness gain per driver is constant, and that it reaches a plateau if the gains decrease over time. We discuss the realism of the underlying assumptions and possible extensions of the model