Dynamic and adaptive cancer stem cell population admixture in colorectal neoplasia.

Intestinal homeostasis is underpinned by LGR5+ve crypt-base columnar stem cells (CBCs), but following injury, dedifferentiation results in the emergence of LGR5-ve regenerative stem cell populations (RSCs), characterized by fetal transcriptional profiles. Neoplasia hijacks regenerative signaling, so we assessed the distribution of CBCs and RSCs in mouse and human intestinal tumors. Using combined molecular-morphological analysis, we demonstrate variable expression of stem cell markers across a range of lesions. The degree of CBC-RSC admixture was associated with both epithelial mutation and microenvironmental signaling disruption and could be mapped across disease molecular subtypes. The CBC-RSC equilibrium was adaptive, with a dynamic response to acute selective pressure, and adaptability was associated with chemoresistance. We propose a fitness landscape model where individual tumors have equilibrated stem cell population distributions along a CBC-RSC phenotypic axis. Cellular plasticity is represented by position shift along this axis and is influenced by cell-intrinsic, extrinsic, and therapeutic selective pressures.

Homeostasis limits keratinocyte evolution.

Recent studies have revealed that normal human tissues accumulate many somatic mutations. In particular, human skin is riddled with mutations, with multiple subclones of variable sizes. Driver mutations are frequent and tend to have larger subclone sizes, suggesting selection. To begin to understand the histories encoded by these complex somatic mutations, we incorporated genomes into a simple agent-based skin-cell model whose prime directive is homeostasis. In this model, stem-cell survival is random and dependent on proximity to the basement membrane. This simple homeostatic skin model recapitulates the observed log-linear distributions of somatic mutations, where most mutations are found in increasingly smaller subclones that are typically lost with time. Hence, neutral mutations are "passengers" whose fates depend on the random survival of their stem cells, where a rarer larger subclone reflects the survival and spread of mutations acquired earlier in life. The model can also maintain homeostasis and accumulate more frequent and larger driver subclones if these mutations (NOTCH1 and TP53) confer relatively higher persistence in normal skin or during tissue damage (sunlight). Therefore, a relatively simple model of epithelial turnover indicates how observed passenger and driver somatic mutations could accumulate without violating the prime directive of homeostasis in normal human tissues.

Immunosuppressive niche engineering at the onset of human colorectal cancer.

The evolutionary dynamics of tumor initiation remain undetermined, and the interplay between neoplastic cells and the immune system is hypothesized to be critical in transformation. Colorectal cancer (CRC) presents a unique opportunity to study the transition to malignancy as pre-cancers (adenomas) and early-stage cancers are frequently resected. Here, we examine tumor-immune eco-evolutionary dynamics from pre-cancer to carcinoma using a computational model, ecological analysis of digital pathology data, and neoantigen prediction in 62 patient samples. Modeling predicted recruitment of immunosuppressive cells would be the most common driver of transformation. As predicted, ecological analysis reveals that progressed adenomas co-localized with immunosuppressive cells and cytokines, while benign adenomas co-localized with a mixed immune response. Carcinomas converge to a common immune "cold" ecology, relaxing selection against immunogenicity and high neoantigen burdens, with little evidence for PD-L1 overexpression driving tumor initiation. These findings suggest re-engineering the immunosuppressive niche may prove an effective immunotherapy in CRC.

Gattaca: Base-Pair Resolution Mutation Tracking for Somatic Evolution Studies using Agent-based Models.

Research over the past two decades has made substantial inroads into our understanding of somatic mutations. Recently, these studies have focused on understanding their presence in homeostatic tissue. In parallel, agent-based mechanistic models have emerged as an important tool for understanding somatic mutation in tissue; yet no common methodology currently exists to provide base-pair resolution data for these models. Here, we present Gattaca as the first method for introducing and tracking somatic mutations at the base-pair resolution within agent-based models that typically lack nuclei. With nuclei that incorporate human reference genomes, mutational context, and sequence coverage/error information, Gattaca is able to realistically evolve sequence data, facilitating comparisons between in silico cell tissue modeling with experimental human somatic mutation data. This user-friendly method, incorporated into each in silico cell, allows us to fully capture somatic mutation spectra and evolution.

Fluctuating methylation clocks for cell lineage tracing at high temporal resolution in human tissues.

Molecular clocks that record cell ancestry mutate too slowly to measure the short-timescale dynamics of cell renewal in adult tissues. Here, we show that fluctuating DNA methylation marks can be used as clocks in cells where ongoing methylation and demethylation cause repeated 'flip-flops' between methylated and unmethylated states. We identify endogenous fluctuating CpG (fCpG) sites using standard methylation arrays and develop a mathematical model to quantitatively measure human adult stem cell dynamics from these data. Small intestinal crypts were inferred to contain slightly more stem cells than the colon, with slower stem cell replacement in the small intestine. Germline APC mutation increased the number of replacements per crypt. In blood, we measured rapid expansion of acute leukemia and slower growth of chronic disease. Thus, the patterns of human somatic cell birth and death are measurable with fluctuating methylation clocks (FMCs).

Normal tissue architecture determines the evolutionary course of cancer.

Cancer growth can be described as a caricature of the renewal process of the tissue of origin, where the tissue architecture has a strong influence on the evolutionary dynamics within the tumor. Using a classic, well-studied model of tumor evolution (a passenger-driver mutation model) we systematically alter spatial constraints and cell mixing rates to show how tissue structure influences functional (driver) mutations and genetic heterogeneity over time. This approach explores a key mechanism behind both inter-patient and intratumoral tumor heterogeneity: competition for space. Time-varying competition leads to an emergent transition from Darwinian premalignant growth to subsequent invasive neutral tumor growth. Initial spatial constraints determine the emergent mode of evolution (Darwinian to neutral) without a change in cell-specific mutation rate or fitness effects. Driver acquisition during the Darwinian precancerous stage may be modulated en route to neutral evolution by the combination of two factors: spatial constraints and limited cellular mixing. These two factors occur naturally in ductal carcinomas, where the branching topology of the ductal network dictates spatial constraints and mixing rates.

Evolutionary dynamics of neoantigens in growing tumors.

Cancers accumulate mutations that lead to neoantigens, novel peptides that elicit an immune response, and consequently undergo evolutionary selection. Here we establish how negative selection shapes the clonality of neoantigens in a growing cancer by constructing a mathematical model of neoantigen evolution. The model predicts that, without immune escape, tumor neoantigens are either clonal or at low frequency; hypermutated tumors can only establish after the evolution of immune escape. Moreover, the site frequency spectrum of somatic variants under negative selection appears more neutral as the strength of negative selection increases, which is consistent with classical neutral theory. These predictions are corroborated by the analysis of neoantigen frequencies and immune escape in exome and RNA sequencing data from 879 colon, stomach and endometrial cancers.

Hybrid Automata Library: A flexible platform for hybrid modeling with real-time visualization.

The Hybrid Automata Library (HAL) is a Java Library developed for use in mathematical oncology modeling. It is made of simple, efficient, generic components that can be used to model complex spatial systems. HAL's components can broadly be classified into: on- and off-lattice agent containers, finite difference diffusion fields, a GUI building system, and additional tools and utilities for computation and data collection. These components are designed to operate independently and are standardized to make them easy to interface with one another. As a demonstration of how modeling can be simplified using our approach, we have included a complete example of a hybrid model (a spatial model with interacting agent-based and PDE components). HAL is a useful asset for researchers who wish to build performant 1D, 2D and 3D hybrid models in Java, while not starting entirely from scratch. It is available on GitHub at https://github.com/MathOnco/HAL under the MIT License. HAL requires the Java JDK version 1.8 or later to compile and run the source code.

EvoFreq: visualization of the Evolutionary Frequencies of sequence and model data.

BACKGROUND: High throughput sequence data has provided in depth means of molecular characterization of populations. When recorded at numerous time steps, such data can reveal the evolutionary dynamics of the population under study by tracking the changes in genotype frequencies over time. This necessitates a simple and flexible means of visualizing an increasingly complex set of data. RESULTS: Here we offer EvoFreq as a comprehensive tool set to visualize the evolutionary and population frequency dynamics of clones at a single point in time or as population frequencies over time using a variety of informative methods. EvoFreq expands substantially on previous means of visualizing the clonal, temporal dynamics and offers users a range of options for displaying their sequence or model data. CONCLUSIONS: EvoFreq, implemented in R with robust user options and few dependencies, offers a high-throughput means of quickly building, and interrogating the temporal dynamics of hereditary information across many systems. EvoFreq is freely available via https://github.com/MathOnco/EvoFreq.

NeoPredPipe: high-throughput neoantigen prediction and recognition potential pipeline.

BACKGROUND: Next generation sequencing has yielded an unparalleled means of quickly determining the molecular make-up of patient tumors. In conjunction with emerging, effective immunotherapeutics for a number of cancers, this rapid data generation necessitates a paired high-throughput means of predicting and assessing neoantigens from tumor variants that may stimulate immune response. RESULTS: Here we offer NeoPredPipe (Neoantigen Prediction Pipeline) as a contiguous means of predicting putative neoantigens and their corresponding recognition potentials for both single and multi-region tumor samples. NeoPredPipe is able to quickly provide summary information for researchers, and clinicians alike, on predicted neoantigen burdens while providing high-level insights into tumor heterogeneity given somatic mutation calls and, optionally, patient HLA haplotypes. Given an example dataset we show how NeoPredPipe is able to rapidly provide insights into neoantigen heterogeneity, burden, and immune stimulation potential. CONCLUSIONS: Through the integration of widely adopted tools for neoantigen discovery NeoPredPipe offers a contiguous means of processing single and multi-region sequence data. NeoPredPipe is user-friendly and adaptable for high-throughput performance. NeoPredPipe is freely available at https://github.com/MathOnco/NeoPredPipe .

Highly Disordered Proteins in Prostate Cancer.

Prostate cancer is one of the major threats to the man's health. There are several mechanisms of the prostate cancer development characterized by the involvement of various androgen-related and androgen-unrelated factors in prostate cancer pathogenesis and in the metastatic carcinogenesis of prostate. In all these processes, proteins play various important roles, and the KEGG database has information on 88 human proteins experimentally shown to be involved in prostate cancer. It is known that many proteins associated with different human maladies are intrinsically disordered (i.e., they do not have stable secondary and/or tertiary structure in their unbound states). The goal of this review is to consider several highly disordered proteins known to be associated with the prostate cancer pathogenesis in order to better understand the roles of disordered proteins in this disease. We also hope that consideration of the pathology-related proteins from the perspective of intrinsic disorder can potentially lead to future experimental studies of these proteins to find novel pathways associated with prostate cancer.

Unfoldomics of prostate cancer: on the abundance and roles of intrinsically disordered proteins in prostate cancer.

Prostatic diseases such as prostate cancer and benign prostatic hyperplasia are highly prevalent among men. The number of studies focused on the abundance and roles of intrinsically disordered proteins in prostate cancer is rather limited. The goal of this study is to analyze the prevalence and degree of disorder in proteins that were previously associated with the prostate cancer pathogenesis and to compare these proteins to the entire human proteome. The analysis of these datasets provides means for drawing conclusions on the roles of disordered proteins in this common male disease. We also hope that the results of our analysis can potentially lead to future experimental studies of these proteins to find novel pathways associated with this disease.

Novel circular single-stranded DNA viruses identified in marine invertebrates reveal high sequence diversity and consistent predicted intrinsic disorder patterns within putative structural proteins.

Viral metagenomics has recently revealed the ubiquitous and diverse nature of single-stranded DNA (ssDNA) viruses that encode a conserved replication initiator protein (Rep) in the marine environment. Although eukaryotic circular Rep-encoding ssDNA (CRESS-DNA) viruses were originally thought to only infect plants and vertebrates, recent studies have identified these viruses in a number of invertebrates. To further explore CRESS-DNA viruses in the marine environment, this study surveyed CRESS-DNA viruses in various marine invertebrate species. A total of 27 novel CRESS-DNA genomes, with Reps that share less than 60.1% identity with previously reported viruses, were recovered from 21 invertebrate species, mainly crustaceans. Phylogenetic analysis based on the Rep revealed a novel clade of CRESS-DNA viruses that included approximately one third of the marine invertebrate associated viruses identified here and whose members may represent a novel family. Investigation of putative capsid proteins (Cap) encoded within the eukaryotic CRESS-DNA viral genomes from this study and those in GenBank demonstrated conserved patterns of predicted intrinsically disordered regions (IDRs), which can be used to complement similarity-based searches to identify divergent structural proteins within novel genomes. Overall, this study expands our knowledge of CRESS-DNA viruses associated with invertebrates and explores a new tool to evaluate divergent structural proteins encoded by these viruses.

Global morphological analysis of marine viruses shows minimal regional variation and dominance of non-tailed viruses.

Viruses influence oceanic ecosystems by causing mortality of microorganisms, altering nutrient and organic matter flux via lysis and auxiliary metabolic gene expression and changing the trajectory of microbial evolution through horizontal gene transfer. Limited host range and differing genetic potential of individual virus types mean that investigations into the types of viruses that exist in the ocean and their spatial distribution throughout the world's oceans are critical to understanding the global impacts of marine viruses. Here we evaluate viral morphological characteristics (morphotype, capsid diameter and tail length) using a quantitative transmission electron microscopy (qTEM) method across six of the world's oceans and seas sampled through the Tara Oceans Expedition. Extensive experimental validation of the qTEM method shows that neither sample preservation nor preparation significantly alters natural viral morphological characteristics. The global sampling analysis demonstrated that morphological characteristics did not vary consistently with depth (surface versus deep chlorophyll maximum waters) or oceanic region. Instead, temperature, salinity and oxygen concentration, but not chlorophyll a concentration, were more explanatory in evaluating differences in viral assemblage morphological characteristics. Surprisingly, given that the majority of cultivated bacterial viruses are tailed, non-tailed viruses appear to numerically dominate the upper oceans as they comprised 51-92% of the viral particles observed. Together, these results document global marine viral morphological characteristics, show that their minimal variability is more explained by environmental conditions than geography and suggest that non-tailed viruses might represent the most ecologically important targets for future research.