Abstract
Malignant cells leave their initial tumor of growth and disperse to other tissues to form metastases. Dispersals also occur in nature when individuals in a population migrate from their area ...of origin to colonize other habitats. In cancer, phylogenetic biogeography is concerned with the source and trajectory of cell movements. We examine the suitability of primary features of organismal biogeography, including genetic diversification, dispersal, extinction, vicariance, and founder effects, to describe and reconstruct clone migration events among tumors. We used computer-simulated data to compare fits of seven biogeographic models and evaluate models’ performance in clone migration reconstruction. Models considering founder effects and dispersals were often better fit for the clone phylogenetic patterns, especially for polyclonal seeding and reseeding of metastases. However, simpler biogeographic models produced more accurate estimates of cell migration histories. Analyses of empirical datasets of basal-like breast cancer had model fits consistent with the patterns seen in the analysis of computer-simulated datasets. Our analyses reveal the powers and pitfalls of biogeographic models for modeling and inferring clone migration histories using tumor genome variation data. We conclude that the principles of molecular evolution and organismal biogeography are useful in these endeavors but that the available models and methods need to be applied judiciously.
Dispersal routes of metastatic cells are not medically detected or even visible. A molecular evolutionary analysis of tumor variation provides a way to retrospectively infer metastatic migration ...histories and answer questions such as whether the majority of metastases are seeded from clones within primary tumors or seeded from clones within pre-existing metastases, as well as whether the evolution of metastases is generally consistent with any proposed models. We seek answers to these fundamental questions through a systematic patient-centric retrospective analysis that maps the dynamic evolutionary history of tumor cell migrations in many cancers. We analyzed tumor genetic heterogeneity in 51 cancer patients and found that most metastatic migration histories were best described by a hybrid of models of metastatic tumor evolution. Synthesizing across metastatic migration histories, we found new tumor seedings arising from clones of pre-existing metastases as often as they arose from clones from primary tumors. There were also many clone exchanges between the source and recipient tumors. Therefore, a molecular phylogenetic analysis of tumor variation provides a retrospective glimpse into general patterns of metastatic migration histories in cancer patients.
Abstract
Integration of ecological and evolutionary features has begun to understand the interplay of tumor heterogeneity, microenvironment, and metastatic potential. Developing a theoretical ...framework is intrinsic to deciphering tumors’ tremendous spatial and longitudinal genetic variation patterns in patients. Here, we propose that tumors can be considered evolutionary island-like ecosystems, that is, isolated systems that undergo evolutionary and spatiotemporal dynamic processes that shape tumor microenvironments and drive the migration of cancer cells. We examine attributes of insular systems and causes of insularity, such as physical distance and connectivity. These properties modulate migration rates of cancer cells through processes causing spatial and temporal isolation of the organs and tissues functioning as a supply of cancer cells for new colonizations. We discuss hypotheses, predictions, and limitations of tumors as islands analogy. We present emerging evidence of tumor insularity in different cancer types and discuss their relevance to the islands model. We suggest that the engagement of tumor insularity into conceptual and mathematical models holds promise to illuminate cancer evolution, tumor heterogeneity, and metastatic potential of cells.
Abstract
Summary
Metastases cause a vast majority of cancer morbidity and mortality. Metastatic clones are formed by dispersal of cancer cells to secondary tissues, and are not medically detected or ...visible until later stages of cancer development. Clone phylogenies within patients provide a means of tracing the otherwise inaccessible dynamic history of migrations of cancer cells.
Here, we present a new Bayesian approach, PathFinder, for reconstructing the routes of cancer cell migrations. PathFinder uses the clone phylogeny, the number of mutational differences among clones, and the information on the presence and absence of observed clones in primary and metastatic tumors. By analyzing simulated datasets, we found that PathFinder performes well in reconstructing clone migrations from the primary tumor to new metastases as well as between metastases. It was more challenging to trace migrations from metastases back to primary tumors. We found that a vast majority of errors can be corrected by sampling more clones per tumor, and by increasing the number of genetic variants assayed per clone. We also identified situations in which phylogenetic approaches alone are not sufficient to reconstruct migration routes.
In conclusion, we anticipate that the use of PathFinder will enable a more reliable inference of migration histories and their posterior probabilities, which is required to assess the relative preponderance of seeding of new metastasis by clones from primary tumors and/or existing metastases.
Availability and implementation
PathFinder is available on the web at https://github.com/SayakaMiura/PathFinder.
Understanding tumor progression and metastatic potential are important in cancer biology. Metastasis is the migration and colonization of clones in secondary tissues. Here, we posit that clone ...migration events between tumors resemble the dispersal of individuals between distinct geographic regions. This similarity makes Bayesian biogeographic analysis suitable for inferring cancer cell migration paths. We evaluated the accuracy of a Bayesian biogeography method (BBM) in inferring metastatic patterns and compared it with the accuracy of a parsimony-based approach (metastatic and clonal history integrative analysis, MACHINA) that has been specifically developed to infer clone migration patterns among tumors. We used computer-simulated datasets in which simple to complex migration patterns were modeled. BBM and MACHINA were effective in reliably reconstructing simple migration patterns from primary tumors to metastases. However, both of them exhibited a limited ability to accurately infer complex migration paths that involve the migration of clones from one metastatic tumor to another and from metastasis to the primary tumor. Therefore, advanced computational methods are still needed for the biologically realistic tracing of migration paths and to assess the relative preponderance of different types of seeding and reseeding events during cancer progression in patients.
Abstract BACKGROUND Pediatric brain and spinal cord tumors are the leading cause of cancer-related mortality in children. An incomplete understanding of brain tumor biology and associated limited ...access to high-quality biological samples for research are the main factors driving the lack of clinical therapeutic development for pediatric brain tumors that recur or progress. Post-mortem tissue donation provides an unprecedented resource for addressing some of these limitations. METHODS The Gift from a Child (GFAC) program by the Swifty Foundation has a unique mission to increase post-mortem pediatric brain tissue donations through advocacy as well as the education of clinicians and families. Through GFAC’s strategic collaboration with the Children’s Brain Tumor Network (CBTN), CBTN has leveraged postmortem tissue to expand the Pediatric Brain Tumor Atlas (PBTA), a cross-histology multi-omics atlas resource. As part of the effort CBTN has sequenced and released data for over 350 post-mortem pediatric brain tumor specimens including multiple brain region sampling cases with specimen and sequencing quality metrics. RESULTS Here we present an assessment of postmortem samples and available multi-omic data on postmortem samples within the PBTA dataset. Data have been harmonized and released with no publication embargo. To access data, researchers can utilize existing open source data resources and platforms including PedCbioPortal and OpenPedCan to: (1) Identify tumor spatial and temporal specific alterations (2) Establish tumor evolution trajectory leading to therapeutic resistance and tumor progression; (3) Understand tumor heterogeneity longitudinally across multiple ‘omics layers; and (4) Identify and request specimens and derived tumor models. CONCLUSIONS Together, we present the largest deeply characterized cohort of postmortem pediatric brain tumor samples as powerful expansion of the PBTA cohort of >3,000 pediatric brain tumors. CBTN’s open-science model supported by the GFAC mission highlights the value and utility of autopsy-based specimen collection on behalf of improving outcomes for children with brain tumors.
Abstract BACKGROUND The contribution of rare pathogenic germline variation to central nervous system (CNS) tumor formation in pediatric patients without a family history of cancer remains unclear. ...METHODS We characterized the prevalence of pathogenic germline variants in 214 cancer predisposition genes (CPGs) in 837 patients profiled in the Pediatric Brain Tumor Atlas by whole genome or exome sequencing (n=820 and n=17, respectively). Rare SNVs and small INDELs were annotated as pathogenic (P) or likely pathogenic (LP) consistent with American College of Medical Genetics criteria using AutoGVP, our open-source automated pathogenicity assessment tool. We classified pathogenicity of germline structural variants (SVs) using ClassifyCNV and AnnotSV. Somatic alterations and mutational signatures from matched tumor sequencing were integrated to identify functional consequences associated with germline pathogenic variation. RESULTS We observed 206 germline P/LP SNVs/small INDELs and 18 SVs (16 deletions, 2 duplications) within 78 unique CPGs in 195 patients (23.3%). We detected syndrome-associated P/LP variants in 45/58 patients with a clinically-reported cancer predisposition syndrome and incidentally in 41 patients. Ninety-five (42%) germline P/LP variants co-occurred with at least one somatic alteration in the same gene in matched tumors: n=6 oncogenic SNVs, n=28 CNVs, n=54 loss of heterozygosity (LOH), n=26 differential gene or protein expression, and n=18 alternative splicing. NF1, TSC1, and TSC2 germline P/LP carriers exhibited significantly higher tumor LOH scores and lower gene expression in tumors relative to non-P/LP carriers. Patients with germline splice region P/LP variants exhibited significantly increased skipping of most the proximal exon in matched tumor relative to patients with non-splice region P/LP variants (W=401, p=1.1E-04). CONCLUSION We have identified rare germline P/LP variants associated with cancer predisposition syndromes and diverse functional consequences in pediatric CNS tumor patients. Efforts are underway to extend this work to include 1,801 additional probands and 1,105 parents to further characterize the prevalence and heritability of germline pathogenic variation in children diagnosed with CNS tumors.
The genus Eumerus Meigen (Diptera: Syrphidae) is considered one of the most species-rich hoverfly genera. Here, we present two new species, E. montanum Grković, Radenković et Vujić sp. nov. ...(Montenegro, Greece) and E. rubrum Grković et Vujić sp. nov. (Greece), and one species, E. uncipes Rondani, 1850, recorded for the first time in southeastern Europe. The species are members of three different taxon groups, respectively E. strigatus sensu Speight et al. (2013), E. tricolor sensu Chroni et al. (2017) and E. clavatus as defined here. Diagnostic characters for each of the three taxon groups and descriptions of the two new species are provided. In addition, we employed morphological and molecular data for available taxa of the E. strigatus taxon group in order to corroborate their taxonomical status and systematic position. Finally, we discuss the diversity of these taxon groups (E. clavatus, E. strigatus and E. tricolor) and give a detailed overview of the differences between closely-related species.
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