Spatial intratumoral heterogeneity and temporal clonal evolution in esophageal squamous cell carcinoma.

Esophageal squamous cell carcinoma (ESCC) is among the most common malignancies, but little is known about its spatial intratumoral heterogeneity (ITH) and temporal clonal evolutionary processes. To address this, we performed multiregion whole-exome sequencing on 51 tumor regions from 13 ESCC cases and multiregion global methylation profiling for 3 of these 13 cases. We found an average of 35.8% heterogeneous somatic mutations with strong evidence of ITH. Half of the driver mutations located on the branches of tumor phylogenetic trees targeted oncogenes, including PIK3CA, NFE2L2 and MTOR, among others. By contrast, the majority of truncal and clonal driver mutations occurred in tumor-suppressor genes, including TP53, KMT2D and ZNF750, among others. Interestingly, phyloepigenetic trees robustly recapitulated the topological structures of the phylogenetic trees, indicating a possible relationship between genetic and epigenetic alterations. Our integrated investigations of spatial ITH and clonal evolution provide an important molecular foundation for enhanced understanding of tumorigenesis and progression in ESCC

Helmsman: fast and efficient mutation signature analysis for massive sequencing datasets

Abstract Background The spectrum of somatic single-nucleotide variants in cancer genomes often reflects the signatures of multiple distinct mutational processes, which can provide clinically actionable insights into cancer etiology. Existing software tools for identifying and evaluating these mutational signatures do not scale to analyze large datasets containing thousands of individuals or millions of variants. Results We introduce Helmsman, a program designed to perform mutation signature analysis on arbitrarily large sequencing datasets. Helmsman is up to 300 times faster than existing software. Helmsman’s memory usage is independent of the number of variants, resulting in a small enough memory footprint to analyze datasets that would otherwise exceed the memory limitations of other programs. Conclusions Helmsman is a computationally efficient tool that enables users to evaluate mutational signatures in massive sequencing datasets that are otherwise intractable with existing software. Helmsman is freely available at https://github.com/carjed/helmsman .https://deepblue.lib.umich.edu/bitstream/2027.42/146537/1/12864_2018_Article_5264.pd

Clonal Heterogeneity and Tumor Evolution: Past, Present, and the Future

Intratumor heterogeneity, which fosters tumor evolution, is a key challenge in cancer medicine. Here, we review data and technologies that have revealed intra-tumor heterogeneity across cancer types and the dynamics, constraints, and contingencies inherent to tumor evolution. We emphasize the importance of macro-evolutionary leaps, often involving large-scale chromosomal alterations, in driving tumor evolution and metastasis and consider the role of the tumor microenvironment in engendering heterogeneity and drug resistance. We suggest that bold approaches to drug development, harnessing the adaptive properties of the immune-microenvironment while limiting those of the tumor, combined with advances in clinical trial-design, will improve patient outcome

Mechanisms of cancer evolution and drivers of tumour heterogeneity

Cancer drug resistance is almost inevitable in the majority of patients with advanced metastatic tumours. Intra-tumour heterogeneity, facilitating rapid tumour evolution, is a main cause of resistance to cancer therapies. In this thesis, I explore how cancer genome sequencing data can shed light intratumour heterogeneity and the processes shaping cancer genome evolution over space and time. Multi-region and single-sample sequencing data was harnessed to temporally and clonally dissect mutations across 10 major cancer-types. The existence of branched tumour evolution and widespread heterogeneity was demonstrated. Although mutations in known cancer genes typically occurred early in cancer evolution, subclonal ‘actionable’ mutations, including BRAF (V600E), IDH1 (R132H), PIK3CA (E545K), and EGFR (L858R), were also identified. Temporal dissection of mutational signatures revealed that APOBEC-mediated mutagenesis is frequently a late event in cancer evolution and plays a key role in the acquisition of subclonal driver mutations. Copy number analysis suggested that genome doubling is prevalent across tumour types and that it frequently occurs early in tumour evolution in colorectal cancer. A cancer cell-line system was used to demonstrate that rare cells that survive genome-doubling display increased tolerance to chromosome aberrations and a genome-doubling event was found to be independently predictive of reduced relapse-free survival in two independent cohorts. Finally, the clinical impact of intra-tumour heterogeneity was explored in the context of cancer neo-antigens and immune-modulation. The number of clonal neoantigens was associated with survival outcome in lung adenocarcinoma patients and T cells reactive to clonal neo-antigens were identified. Sensitivity to anti-PD-1 therapy was dependent on neo-antigen clonal burden and intra-tumour heterogeneity. Thus, immunotherapeutic strategies targeting clonal neo-antigens in combination with checkpoint-blockade may provide a tractable approach to tackling lung adenocarcinomas. This thesis demonstrates how analyses of genomic data can shed light on the biology and clinical relevance of cancer evolution and intra-tumour heterogeneity

Longitudinal transcriptomic and genetic landscape of radiotherapy response in canine melanoma

Canine malignant melanoma (MM) is a highly aggressive tumour with a low survival rate and represents an ideal spontaneous model for the human counterpart. Considerable progress has been recently obtained, but the therapeutic success for canine melanoma is still challenging. Little is known about the mechanisms beyond pathogenesis and melanoma development, and the molecular response to radiotherapy has never been explored before. A faster and deeper understanding of cancer mutational processes and developing mechanisms are now possible through next generation sequencing technologies. In this study, we matched whole exome and transcriptome sequencing in four dogs affected by MM at diagnosis and at disease progression to identify possible genetic mechanisms associated with therapy failure. According to previous studies, a genetic similarity between canine MM and its human counterpart was observed. Several somatic mutations were functionally related to MAPK, PI3K/AKT and p53 signalling pathways, but located in genes other than BRAF, RAS and KIT. At disease progression, several mutations were related to therapy effects. Natural killer cell-mediated cytotoxicity and several immune-system-related pathways resulted activated opening a new scenario on the microenvironment in this tumour. In conclusion, this study suggests a potential role of the immune system associated to radiotherapy in canine melanoma, but a larger sample size associated with functional studies are needed

Mapping the Landscape of Mutation Rate Heterogeneity in the Human Genome: Approaches and Applications

All heritable genetic variation is ultimately the result of mutations that have occurred in the past. Understanding the processes which determine the rate and spectra of new mutations is therefore fundamentally important in efforts to characterize the genetic basis of heritable disease, infer the timing and extent of past demographic events (e.g., population expansion, migration), or identify signals of natural selection. This dissertation aims to describe patterns of mutation rate heterogeneity in detail, identify factors contributing to this heterogeneity, and develop methods and tools to harness such knowledge for more effective and efficient analysis of whole-genome sequencing data. In Chapters 2 and 3, we catalog granular patterns of germline mutation rate heterogeneity throughout the human genome by analyzing extremely rare variants ascertained from large-scale whole-genome sequencing datasets. In Chapter 2, we describe how mutation rates are influenced by local sequence context and various features of the genomic landscape (e.g., histone marks, recombination rate, replication timing), providing detailed insight into the determinants of single-nucleotide mutation rate variation. We show that these estimates reflect genuine patterns of variation among de novo mutations, with broad potential for improving our understanding of the biology of underlying mutation processes and the consequences for human health and evolution. These estimated rates are publicly available at http://mutation.sph.umich.edu/. In Chapter 3, we introduce a novel statistical model to elucidate the variation in rate and spectra of multinucleotide mutations throughout the genome. We catalog two major classes of multinucleotide mutations: those resulting from error-prone translesion synthesis, and those resulting from repair of double-strand breaks. In addition, we identify specific hotspots for these unique mutation classes and describe the genomic features associated with their spatial variation. We show how these multinucleotide mutation processes, along with sample demography and mutation rate heterogeneity, contribute to the overall patterns of clustered variation throughout the genome, promoting a more holistic approach to interpreting the source of these patterns. In chapter 4, we develop Helmsman, a computationally efficient software tool to infer mutational signatures in large samples of cancer genomes. By incorporating parallelization routines and efficient programming techniques, Helmsman performs this task up to 300 times faster and with a memory footprint 100 times smaller than existing mutation signature analysis software. Moreover, Helmsman is the only such program capable of directly analyzing arbitrarily large datasets. The Helmsman software can be accessed at https://github.com/carjed/helmsman. Finally, in Chapter 5, we present a new method for quality control in large-scale whole-genome sequencing datasets, using a combination of dimensionality reduction algorithms and unsupervised anomaly detection techniques. Just as the mutation spectrum can be used to infer the presence of underlying mechanisms, we show that the spectrum of rare variation is a powerful and informative indicator of sample sequencing quality. Analyzing three large-scale datasets, we demonstrate that our method is capable of identifying samples affected by a variety of technical artifacts that would otherwise go undetected by standard ad hoc filtering criteria. We have implemented this method in a software package, Doomsayer, available at https://github.com/carjed/doomsayer.PHDBioinformaticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/147537/1/jedidiah_1.pd

Immune editing and surveillance in cancer evolution

Cancer is an evolutionary disease, reliant on genetic diversity and sculpted by selective forces from the immune microenvironment. Here, I use genomics data to decipher the tumor’s evolutionary trajectory and corresponding shifts in the immune contexture to elucidate the events governing tumor immunogenicity and the immune evasive mechanisms evolved by the tumor. To better understand the mutational processes contributing to intratumor heterogeneity in individual tumors, a method to quantify the activity of mutational processes in a single tumor sample was developed and applied to temporally dissected mutations. The clinical relevance of intratumor heterogeneity was examined in the context of immune recognition and modulation. Increased clonal neoantigen burden and minimal neoantigen intratumor heterogeneity were found to associate with improved patient outcome, both in the treatment-naïve and immunotherapy-treated setting. The identification of T-cells recognizing clonal neoantigens further supported the clinical importance of targeting neoantigens present in every cancer cell. Mechanisms of immune evasion were considered through the development of a method to identify loss-of-heterozygosity at the HLA locus, overcoming the challenges posed by the polymorphic nature of the locus. HLA loss-of-heterozygosity was found to be a frequent subclonal event in NSCLC, under strong selective pressure and associated with increased subclonal neoantigen burden. Finally, the immune microenvironment was examined through multi-region RNAseq, permitting the quantification of immune infiltration and allowing for the identification of heterogeneously immune infiltrated tumors. Supporting the interplay between genetic events and the immune contexture, a relationship between the genomic features of the tumor and immune infiltration was observed, with HLA loss-of-heterozygosity specifically identified as occurring within a highly active immune microenvironment. This thesis shows how an improved understanding of the relationship between the tumor and the immune system can illuminate features dictating immune recognition and evasion and how that knowledge may inform the development and implementation of successful immunotherapy

Translational studies of epithelial cancer

Tumors stemming from specialized epithelial cells cause the most common cancer types and are among the leading causes of death in the western world. Although great strides have been made in early cancer detection, defining prognostic factors, and improving survival with novel treatments, cancers such as colorectal cancer and prostate cancer are incurable in their advanced stages. In the work presented in this thesis, we aim to explore the biological underpinnings of tumor initiation and progression and determine novel pharmaceutical treatment strategies against epithelial cancer. We do so by combining preclinical methodologies of cell culture and animal models of disease with epidemiological studies of population and patient cohorts. EphB tyrosine kinase receptors promote intestinal tumor proliferation via the tyrosine-protein kinase Abl1 (Abl kinase) (Genander et al., 2009; Holmberg et al., 2006). In paper I, we find that the Abl kinase inhibitor imatinib blocks EphB receptor regulated tumor initiation and growth in mouse models of early-stage intestinal tumors, reduces proliferation in ex vivo human adenomas and prolongs survival of tumor bearing mice. We propose imatinib as a possible prevention and early treatment strategy for people prone to develop intestinal adenomas. In paper II, we explore the immune system and antiviral immunity as potential markers of prostate cancer prognosis. In prostate cancer patients, the Human Leukocyte Antigen (HLA) alleles HLA-A*02:01 and HLA-A*11 are associated with poor disease recurrence free survival after prostatectomy. Immunity to the human herpesvirus cytomegalovirus (CMV) in prostate tumors is associated with particularly poor disease recurrence free survival in HLA-A*02:01+ prostate cancer patients. In paper III, we find that CMV commonly chronically infects epithelium in the healthy and malignant prostate, prostate cancer metastases and prostate cancer cell lines. Experimental and therapeutic inhibition of CMV in in vitro and in vivo models of prostate cancer reveal that CMV promotes its viability and growth and propose that CMV targeting drugs can be repurposed against prostate cancer. In paper IV, we describe that CMV seropositivity is associated with high CMV abundance in healthy and malignant prostate. Studying a large prospective population cohort, we find that CMV seropositivity is not associated with prostate cancer incidence but is associated with increased risk of dying from prostate cancer after receiving a prostate cancer diagnosis