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

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

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

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

The Genetic Evolution and Natural History of Pancreatic Adenocarcinoma

Pancreatic cancer evolves via the step-wise accumulation of genetic mutations, yet the dynamics of this process are unknown. Multiple cancer tissues from a patient – collected via biopsy, surgery, or autopsy – enable analyses with profound implications for treatment as well as for understanding tumor evolution. My thesis focuses on the mutations acquired during two critical transitions in pancreatic cancer: the advancement of the precursor lesion to the primary tumor, and the evolution of metastatic disease. For the former, we sequenced 21 exomes from tumor precursors and matched cancers. We observed clonality of all concomitant lesions, even when multiple precursors existed within a patient. Yet, most precursors acquired unique mutations – some with numbers comparable to the matched cancer – indicating genetic divergence during carcinogenesis. In addition, known cancer drivers were detected among other somatically acquired alterations. Current efforts aim to determine the order of mutations and the genetic heterogeneity of the lesions – ultimately, a mathematical model will facilitate analysis. For the evolution of metastasis, we analyzed 26 distinct metastatic tumors from four end stage, treatment-naive patients. Using a quantitative measure of genetic relatedness, we found that pancreatic cancers and their metastases demonstrated a level of relatedness that was markedly higher than that expected for any two cells randomly taken from a normal tissue. This minimal amount of genetic divergence among very large, distinct, advanced lesions indicates that genetic heterogeneity, when quantitatively defined, is not a fundamental feature of the natural history of untreated pancreatic cancers. Overall, these analyses reveal the evolutionary history of pancreatic cancer – as recorded by genetic mutations – from initiation to metastasis

Reconstructing metastatic seeding patterns of human 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. Here we develop a tool, called Treeomics, to reconstruct the phylogeny of metastases and map subclones to their anatomic locations. Treeomics infers comprehensive seeding patterns for pancreatic, ovarian, and prostate cancers. Moreover, Treeomics correctly disambiguates 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. In silico benchmarking on simulated tumor phylogenies across a wide range of sample purities (15-95%) and sequencing depths (25-800x) demonstrates the accuracy of Treeomics compared to existing methods.MathematicsOrganismic and Evolutionary Biolog

An analysis of genetic heterogeneity in untreated cancers

Genetic intratumoural heterogeneity is a natural consequence of imperfect DNA replication. Any two randomly selected cells, whether normal or cancerous, are therefore genetically different. Here, we review the different forms of genetic heterogeneity in cancer and re-analyse the extent of genetic heterogeneity within seven types of untreated epithelial cancers, with particular regard to its clinical relevance. We find that the homogeneity of predicted functional mutations in driver genes is the rule rather than the exception. In primary tumours with multiple samples, 97% of driver-gene mutations in 38 patients were homogeneous. Moreover, among metastases from the same primary tumour, 100% of the driver mutations in 17 patients were homogeneous. With a single biopsy of a primary tumour in 14 patients, the likelihood of missing a functional driver-gene mutation that was present in all metastases was 2.6%. Furthermore, all functional driver-gene mutations detected in these 14 primary tumours were present among all their metastases. Finally, we found that individual metastatic lesions responded concordantly to targeted therapies in 91% of 44 patients. These analyses indicate that the cells within the primary tumours that gave rise to metastases are genetically homogeneous with respect to functional driver-gene mutations, and we suggest that future efforts to develop combination therapies have the potential to be curative