Developmental hematopoietic stem cell variation explains clonal hematopoiesis later in life

Clonal hematopoiesis becomes increasingly common with age, but its cause is enigmatic because driver mutations are often absent. Serial observations infer weak selection indicating variants are acquired much earlier in life with unexplained initial growth spurts. Here we use fluctuating CpG methylation as a lineage marker to track stem cell clonal dynamics of hematopoiesis. We show, via the shared prenatal circulation of monozygotic twins, that weak selection conferred by stem cell variation created before birth can reliably yield clonal hematopoiesis later in life. Theory indicates weak selection will lead to dominance given enough time and large enough population sizes. Human hematopoiesis satisfies both these conditions. Stochastic loss of weakly selected variants is naturally prevented by the expansion of stem cell lineages during development. The dominance of stem cell clones created before birth is supported by blood fluctuating CpG methylation patterns that exhibit low correlation between unrelated individuals but are highly correlated between many elderly monozygotic twins. Therefore, clonal hematopoiesis driven by weak selection in later life appears to reflect variation created before birth.

Testing Adaptive Therapy Protocols Using Gemcitabine and Capecitabine in a Preclinical Model of Endocrine-Resistant Breast Cancer

Adaptive therapy, an ecologically inspired approach to cancer treatment, aims to overcome resistance and reduce toxicity by leveraging competitive interactions between drug-sensitive and drug-resistant subclones, prioritizing patient survival and quality of life instead of killing the maximum number of cancer cells. In preparation for a clinical trial, we used endocrine-resistant MCF7 breast cancer to stimulate second-line therapy and tested adaptive therapy using capecitabine, gemcitabine, or their combination in a mouse xenograft model. Dose modulation adaptive therapy with capecitabine alone increased survival time relative to MTD but not statistically significantly (HR = 0.22, 95% CI = 0.043-1.1, p = 0.065). However, when we alternated the drugs in both dose modulation (HR = 0.11, 95% CI = 0.024-0.55, p = 0.007) and intermittent adaptive therapies, the survival time was significantly increased compared to high-dose combination therapy (HR = 0.07, 95% CI = 0.013-0.42, p = 0.003). Overall, the survival time increased with reduced dose for both single drugs (p < 0.01) and combined drugs (p < 0.001), resulting in tumors with fewer proliferation cells (p = 0.0026) and more apoptotic cells (p = 0.045) compared to high-dose therapy. Adaptive therapy favors slower-growing tumors and shows promise in two-drug alternating regimens instead of being combined.

Growth Dynamics of Ductal Carcinoma in Situ Recapitulate Normal Breast Development

Ductal carcinoma in situ (DCIS) and invasive breast cancer share many morphologic, proteomic, and genomic alterations. Yet in contrast to invasive cancer, many DCIS tumors do not progress and may remain indolent over decades. To better understand the heterogenous nature of this disease, we reconstructed the growth dynamics of 18 DCIS tumors based on the geo-spatial distribution of their somatic mutations. The somatic mutation topographies revealed that DCIS is multiclonal and consists of spatially discontinuous subclonal lesions. Here we show that this pattern of spread is consistent with a new 'Comet' model of DCIS tumorigenesis, whereby multiple subclones arise early and nucleate the buds of the growing tumor. The discontinuous, multiclonal growth of the Comet model is analogous to the branching morphogenesis of normal breast development that governs the rapid expansion of the mammary epithelium during puberty. The branching morphogenesis-like dynamics of the proposed Comet model diverges from the canonical model of clonal evolution, and better explains observed genomic spatial data. Importantly, the Comet model allows for the clinically relevant scenario of extensive DCIS spread, without being subjected to the selective pressures of subclone competition that promote the emergence of increasingly invasive phenotypes. As such, the normal cell movement inferred during DCIS growth provides a new explanation for the limited risk of progression in DCIS and adds biologic rationale for ongoing clinical efforts to reduce DCIS overtreatment.

Testing Adaptive Therapy Protocols using Gemcitabine and Capecitabine on a Mouse Model of Endocrine-Resistant Breast Cancer

Highly effective cancer therapies often face limitations due to acquired resistance and toxicity. Adaptive therapy, an ecologically inspired approach, seeks to control therapeutic resistance and minimize toxicity by leveraging competitive interactions between drug-sensitive and drug-resistant subclones, prioritizing patient survival and quality of life over maximum cell kill. In preparation for a clinical trial in breast cancer, we used large populations of MCF7 cells to rapidly generate endocrine-resistance breast cancer cell line. We then mimicked second line therapy in ER+ breast cancers by treating the endocrine-resistant MCF7 cells in a mouse xenograft model to test adaptive therapy with capecitabine, gemcitabine, or the combination of those two drugs. Dose-modulation adaptive therapy with capecitabine alone increased survival time relative to MTD, but not statistically significant (HR: 0.22, 95% CI 0.043- 1.1 P = 0.065). However, when we alternated the drugs in both dose modulation (HR = 0.11, 95% CI: 0.024 - 0.55, P = 0.007) and intermittent adaptive therapies significantly increased survival time compared to high dose combination therapy (HR = 0.07, 95% CI: 0.013 - 0.42; P = 0.003). Overall, survival time increased with reduced dose for both single drugs (P < 0.01) and combined drugs (P < 0.001). Adaptive therapy protocols resulted in tumors with lower proportions of proliferating cells (P = 0.0026) and more apoptotic cells (P = 0.045). The results show that Adaptive therapy outperforms high-dose therapy in controlling endocrine-resistant breast cancer, favoring slower-growing tumors, and showing promise in two-drug alternating regimens.

The co-evolution of the genome and epigenome in colorectal cancer

Colorectal malignancies are a leading cause of cancer-related death1 and have undergone extensive genomic study2,3. However, DNA mutations alone do not fully explain malignant transformation4-7. Here we investigate the co-evolution of the genome and epigenome of colorectal tumours at single-clone resolution using spatial multi-omic profiling of individual glands. We collected 1,370 samples from 30 primary cancers and 8 concomitant adenomas and generated 1,207 chromatin accessibility profiles, 527 whole genomes and 297 whole transcriptomes. We found positive selection for DNA mutations in chromatin modifier genes and recurrent somatic chromatin accessibility alterations, including in regulatory regions of cancer driver genes that were otherwise devoid of genetic mutations. Genome-wide alterations in accessibility for transcription factor binding involved CTCF, downregulation of interferon and increased accessibility for SOX and HOX transcription factor families, suggesting the involvement of developmental genes during tumourigenesis. Somatic chromatin accessibility alterations were heritable and distinguished adenomas from cancers. Mutational signature analysis showed that the epigenome in turn influences the accumulation of DNA mutations. This study provides a map of genetic and epigenetic tumour heterogeneity, with fundamental implications for understanding colorectal cancer biology.

Phenotypic plasticity and genetic control in colorectal cancer evolution

Genetic and epigenetic variation, together with transcriptional plasticity, contribute to intratumour heterogeneity1. The interplay of these biological processes and their respective contributions to tumour evolution remain unknown. Here we show that intratumour genetic ancestry only infrequently affects gene expression traits and subclonal evolution in colorectal cancer (CRC). Using spatially resolved paired whole-genome and transcriptome sequencing, we find that the majority of intratumour variation in gene expression is not strongly heritable but rather 'plastic'. Somatic expression quantitative trait loci analysis identified a number of putative genetic controls of expression by cis-acting coding and non-coding mutations, the majority of which were clonal within a tumour, alongside frequent structural alterations. Consistently, computational inference on the spatial patterning of tumour phylogenies finds that a considerable proportion of CRCs did not show evidence of subclonal selection, with only a subset of putative genetic drivers associated with subclone expansions. Spatial intermixing of clones is common, with some tumours growing exponentially and others only at the periphery. Together, our data suggest that most genetic intratumour variation in CRC has no major phenotypic consequence and that transcriptional plasticity is, instead, widespread within a tumour.

Lineage tracing in human tissues

The dynamical process of cell division that underpins homeostasis in the human body cannot be directly observed in vivo, but instead is measurable from the pattern of somatic genetic or epigenetic mutations that accrue in tissues over an individual's lifetime. Because somatic mutations are heritable, they serve as natural lineage tracing markers that delineate clonal expansions. Mathematical analysis of the distribution of somatic clone sizes gives a quantitative readout of the rates of cell birth, death, and replacement. In this review we explore the broad range of somatic mutation types that have been used for lineage tracing in human tissues, introduce the mathematical concepts used to infer dynamical information from these clone size data, and discuss the insights of this lineage tracing approach for our understanding of homeostasis and cancer development. We use the human colon as a particularly instructive exemplar tissue. There is a rich history of human somatic cell dynamics surreptitiously written into the cell genomes that is being uncovered by advances in sequencing and careful mathematical analysis lineage of tracing data. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Abstract A019: Mutation agnostic diagnosis of clonal hematopoiesis of indeterminate potential (CHIP) using fluctuating methylation clocks

Clonal hematopoiesis (CH), such as clonal hematopoiesis of indeterminant potential (CHIP), is diagnosed based on somatic genomic alterations in the absence of hematologic malignancy. At present, CHIP is diagnosed using peripheral blood, where putative driver point mutations and small insertions/deletions whose variant allele frequency is greater or equal to two percent. Generally, the prevalence of CH increases as an individual ages and conveys a risk for progression to a malignancy. CH is thought to be driven by the underlying hematopoietic stem cells of an unknown quantity, with estimates in the literature for stem cell numbers differing by orders of magnitude. Previously, we developed a method using fluctuating CpG (fCpG) sites to serve as a fluctuating methylation clock to uncover stem cell dynamics in glandular tissues and orthogonally validated our method using publicly available datasets of human blood from normal cohorts and malignant cohorts. Here we expand on this work by presenting 38 new patients with distinct VAF groups from 1-2% VAF up to greater than 10% VAF for putative drivers with corresponding DNA methylation profiles using the Illumina EPIC array platform. We identify fCpG from our normal and CHIP cohorts to train and validate a machine learning approach that allows us to diagnose CHIP without DNA sequencing. Importantly, our approach allows for the identification of patients who may have CH driven by structural variants such as copy number alterations. We use this method to evaluate two publicly available methylation datasets of reportedly normal patients (n=656 and n=732) showing that evidence of CHIP can be found in 19% and 29% of these datasets, respectively. We then evaluate copy number differences in burden within our CHIP cohort and these newly identified CHIP cohorts. Using a mechanistic model of hematopoietic stem cells containing fCpGs we examine the temporal dynamics of competing founder CHIP drivers and the number of stem cells in the hematopoietic stem cell compartment.

Citation Format: Ryan O. Schenck, Niels Asger Jakobsen, Virginia Turati, Darryl Shibata, Paresh Vyas, Simon Leedham, Alexander R.A. Anderson. Mutation agnostic diagnosis of clonal hematopoiesis of indeterminate potential (CHIP) using fluctuating methylation clocks [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr A019.

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).

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.

A Bayesian hierarchical model to estimate DNA methylation conservation in colorectal tumors

MOTIVATION

Conservation is broadly used to identify biologically important (epi)genomic regions. In the case of tumor growth, preferential conservation of DNA methylation can be used to identify areas of particular functional importance to the tumor. However, reliable assessment of methylation conservation based on multiple tissue samples per patient requires the decomposition of methylation variation at multiple levels.

RESULTS

We developed a Bayesian hierarchical model that allows for variance decomposition of methylation on three levels: between-patient normal tissue variation, between-patient tumor-effect variation and within-patient tumor variation. We then defined a model-based conservation score to identify loci of reduced within-tumor methylation variation relative to between-patient variation. We fit the model to multi-sample methylation array data from 21 colorectal cancer (CRC) patients using a Monte Carlo Markov Chain algorithm (Stan). Sets of genes implicated in CRC tumorigenesis exhibited preferential conservation, demonstrating the model's ability to identify functionally relevant genes based on methylation conservation. A pathway analysis of preferentially conserved genes implicated several CRC relevant pathways and pathways related to neoantigen presentation and immune evasion. Our findings suggest that preferential methylation conservation may be used to identify novel gene targets that are not consistently mutated in CRC. The flexible structure makes the model amenable to the analysis of more complex multi-sample data structures.

AVAILABILITY AND IMPLEMENTATION

The data underlying this article are available in the NCBI GEO Database, under accession code GSE166212. The R analysis code is available at https://github.com/kevin-murgas/DNAmethylation-hierarchicalmodel.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Functional human genes typically exhibit epigenetic conservation

Recent DepMap CRISPR-Cas9 single gene disruptions have identified genes more essential to proliferation in tissue culture. It would be valuable to translate these finding with measurements more practical for human tissues. Here we show that DepMap essential genes and other literature curated functional genes exhibit cell-specific preferential epigenetic conservation when DNA methylation measurements are compared between replicate cell lines and between intestinal crypts from the same individual. Culture experiments indicate that epigenetic drift accumulates through time with smaller differences in more functional genes. In NCI-60 cell lines, greater targeted gene conservation correlated with greater drug sensitivity. These studies indicate that two measurements separated in time allow normal or neoplastic cells to signal through conservation which human genes are more essential to their survival in vitro or in vivo.

Comparison of traditional two-injection dorsal digital block versus transthecal and subcutaneous single-injection digital block: A systematic review and meta-analysis

Digital nerve block is a common procedure with several techniques, including the traditional digital nerve block, transthecal digital nerve block, and single subcutaneous palmar digital nerve block. This review aimed to evaluate the efficacy of these three methods. A systematic search was performed in the PubMed, Scopus, and Cochrane Library databases. The risk of bias of the studies was assessed using the Cochrane Collaboration's tool for assessing the risk of bias and the Risk of Bias Assessment Tool for Non-Randomized Studies. Fourteen prospective randomized controlled studies and one prospective comparative study were included. The three methods of digital block showed similar onset times, durations, injection pain and incidence of incomplete anesthesia. This review confirmed that all three methods of digital block are equally effective. Considering that patients prefer a single injection and the potential risk of complications, the single subcutaneous digital block could be more widely used.

Epigenetic Conservation Is a Beacon of Function: An Analysis Using Methcon5 Software for Studying Gene Methylation

PURPOSE

Different epigenetic configurations allow one genome to develop into multiple cell types. Although the rules governing what epigenetic features confer gene expression are increasingly being understood, much remains uncertain. Here, we used a novel software package, Methcon5, to explore whether the principle of biologic conservation can be used to identify expressed genes. The hypothesis is that epigenetic configurations of important expressed genes will be conserved within a tissue.

MATERIALS AND METHODS

We compared the DNA methylation of approximately 850,000 CpG sites between multiple clonal crypts or glands of human colon, small intestine, and endometrium. We performed this analysis using the new software package, Methcon5, which enables detection of regions of high (or low) conservation.

RESULTS

We showed that DNA methylation is preferentially conserved at gene-associated CpG sites, particularly in gene promoters (eg, near the transcription start site) or the first exon. Furthermore, higher conservation correlated well with gene expression levels and performed better than promoter DNA methylation levels. Most conserved genes are in canonical housekeeping pathways.

CONCLUSION

This study introduces the new software package, Methcon5. In this example application, we showed that epigenetic conservation provides an alternative method for identifying functional genomic regions in human tissues.

Abstract PR02: Inferring the evolutionary dynamics of ductal carcinoma in situ through multi-regional sequencing and mathematical modeling

Introduction. The natural history of preinvasive breast cancer, or ductal carcinoma in situ (DCIS) remains poorly understood. Overcoming this gap would allow risk-appropriate treatment for patients diagnosed with DCIS. We used a multiregional sequencing approach in combination with mathematical modeling to characterize the evolutionary dynamics of DCIS initiation and progression. Methods. We analyzed a cohort of 18 patients diagnosed with DCIS, either with (n=9) or without (n=9) synchronous invasive cancer. Based on whole exome sequencing, tumor-specific mutation panels were constructed, each targeting 29-75 mutations (median: 60). From each tumor, and using selective ultraviolet radiation fractionation (SURF), we microdissected small spots (encompassing 1-3 duct cross-sections) from 3-4 spatially separated microscope sections (mean slide separation: 1.25cm, range: 0.34-6.0cm). Spots were spatially registered and genotyped based on targeted sequencing of the tumor-specific mutation panels. For each tumor, we performed unsupervised clonal deconvolution of the spot genotypes (CloneFinder) and constructed phylogenetic subclone trees. To quantify the spatial patterns of subclonal mutations, we introduced a dispersion index (DI), ranging from low (DI=0%) to high (DI=100%). To provide a spatio-temporal context for the heterogeneity patterns we developed a family of stochastic mathematical models of DCIS initiation and progression. Thereby, we embedded the evolutionary dynamics of tumor cell expansion in the branching topology of mammary ductal trees. Results. A total of 485 microdissected spots (median per tumor: 23, range: 10-50) were spatially registered and sequenced (median depth: 9,000x). All tumors were multiclonal, containing a median of 5 subclones (range: 2-14). Surprisingly, the correlation between spatial and genomic distances of spots was low. Individual subclones were diffusely dispersed across tumors. DCIS with synchronous DCIS and invasive cancer (mixed DCIS) had a higher mutation dispersion (DI=84.7%) than those without (pure DCIS, DI=70.5%; p=0.03, Wilcoxon rank-sum test). Mixed DCIS also had a higher fraction of spots containing more than one subclone than pure DCIS (median: 30.4% vs 0%, p=0.03). Among 7 mixed DCIS with invasive spots, 5 showed evidence of multiclonal invasion, that is more than one invading subclones were found in both in situ and invasive regions of the tumor. Mathematical modeling analyses show that the observed spatial patterns of genetic heterogeneity are consistent with a single expansion of mixing subclones across the ductal tree architecture. Conclusions. Our findings provide novel insights into the early growth and invasion dynamics of DCIS lesions. Further, we identified potential evolutionary markers for the delineation between indolent (pure) and aggressive (mixed) DCIS. This constitutes an important step towards identification of patients with low-risk DCIS who could be appropriately managed with less aggressive treatment.

Citation Format: Marc D. Ryser, Inmaculada C. Sorribes, Matthew Greenwald, Ethan Wu, Allison Hall, Diego Mallo, Lorraine M. King, Timothy Hardman, Lunden Simpson, Carlo C. Maley, Jeffrey R. Marks, Darryl Shibata, E. Shelley Hwang. Inferring the evolutionary dynamics of ductal carcinoma in situ through multi-regional sequencing and mathematical modeling [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr PR02.

Navigating the path to distant metastasis

How ‘difficult’ is it for somatic evolution to produce a cell that is capable of leaving the primary tumor and growing in a distant organ? In this issue, Reiter et al. assess genetic diversity across metastatic lesions and identify a tight selective bottleneck preceding distant metastasis.

Visualizing Human Colorectal Cancer Intratumor Heterogeneity with Phylogeography

Phylogeography combines ancestry with location and can be translated to intratumor heterogeneity (ITH) to visualize how tumors spread. ITH is common in human tumors, with many genetic and phenotypic differences between regions. The roles of ITH in progression are uncertain because many subclones lack discernable driver mutations. ITH can be visualized by mapping mutations onto microscopic sections, where subclones are directly associated with phenotypes, especially the deeper areas with the more invasive cells that confer worst clinical outcomes. Instead of a stepwise hierarchy where subclones segregate by phenotype with later branching subclones in more invasive areas, multiple subclones share superficial and invasive phenotype and are jigsaw arrayed in vertical columns. Phylogeography shows that both early and late subclones extend from the surface to the invasive front, suggesting that founder cells start with phenotypic plasticity and essentially all the drivers necessary to rapidly grow into large invasive tumors.

0044 Association Between Chronotype and Circulating Levels of Interleukin-6 in Colorectal Cancer Patients: Preliminary Results from the ColoCare Study

Introduction

Accumulating evidence suggests that chronotype, i.e., circadian topology of an individual indicating morning or evening type, is associated with inflammation. To date, no study has examined the relationship between chronotype and inflammation in colorectal cancer patients. We investigated the associations between chronotype and inflammatory and angiogenesis biomarkers in colorectal cancer patients.

Methods

We used pre-surgery serum samples from n=67 newly diagnosed colorectal cancer patients (stage I-IV) recruited at the ColoCare Study site in Heidelberg, Germany. The ColoCare Study is an ongoing, international, multisite, prospective cohort study in colorectal cancer patients. Inflammatory and angiogenesis biomarkers [c-reactive protein (CRP), interleukin (IL)-6, IL-8, monocyte chemoattractant protein-1 (MCP-1), soluble intercellular adhesion molecule-1 (sICAM-1), soluble vascular cell adhesion molecule-1 (sVCAM-1)] were measured at the Huntsman Cancer Institute, USA using the Meso Scale Discovery platform and were log transformed. Chronotype was assessed prior to surgery with the reduced Morningness-Eveningness Questionnaire (rMEQ; scale 4–25; a higher score indicates more morning-type). Patients were dichotomized, based on the median values for rMEQ, into 2 groups: rMEQ-low (score≤16.0; n=35; indicating more evening-type) or rMEQ-high (score&gt;16.0; n=32; indicating more morning-type).

Results

Using Mann-Whitney U test, we observed that rMEQ-low group (i.e., more evening-type) compared to rMEQ-high group (i.e., more morning-type) had approx. two times significantly higher levels of log transformed IL-6 (mean=2.24 vs. 1.30; U=382.0; Z=-2.23; p=0.03), but not for other inflammatory or angiogenesis biomarkers. This association between chronotype and IL-6 was maintained even after adjusting for age, sex, tumor stage, tumor site, and sleep duration using a generalized estimating equations model (adjusted mean difference=1.10; 95% confidence interval=0.33, 1.88; p=0.01; effect size, Cohen’s d=0.69).

Conclusion

These preliminary findings suggest that the evening chronotype is associated with increased IL-6 inflammatory biomarker in colorectal cancer patients. Further research is needed to confirm and understand the mechanistic underpinnings of the observed results.

Support

Funding: NCI U01 CA206110, R01 CA189184, and R01 CA207371.

Deep learned tissue "fingerprints" classify breast cancers by ER/PR/Her2 status from H&E images

Because histologic types are subjective and difficult to reproduce between pathologists, tissue morphology often takes a back seat to molecular testing for the selection of breast cancer treatments. This work explores whether a deep-learning algorithm can learn objective histologic H&E features that predict the clinical subtypes of breast cancer, as assessed by immunostaining for estrogen, progesterone, and Her2 receptors (ER/PR/Her2). Translating deep learning to this and related problems in histopathology presents a challenge due to the lack of large, well-annotated data sets, which are typically required for the algorithms to learn statistically significant discriminatory patterns. To overcome this limitation, we introduce the concept of “tissue fingerprints,” which leverages large, unannotated datasets in a label-free manner to learn H&E features that can distinguish one patient from another. The hypothesis is that training the algorithm to learn the morphological differences between patients will implicitly teach it about the biologic variation between them. Following this training internship, we used the features the network learned, which we call “fingerprints,” to predict ER, PR, and Her2 status in two datasets. Despite the discovery dataset being relatively small by the standards of the machine learning community (n = 939), fingerprints enabled the determination of ER, PR, and Her2 status from whole slide H&E images with 0.89 AUC (ER), 0.81 AUC (PR), and 0.79 AUC (Her2) on a large, independent test set (n = 2531). Tissue fingerprints are concise but meaningful histopathologic image representations that capture biological information and may enable machine learning algorithms that go beyond the traditional ER/PR/Her2 clinical groupings by directly predicting theragnosis.

Minimal barriers to invasion during human colorectal tumor growth

Intra-tumoral heterogeneity (ITH) could represent clonal evolution where subclones with greater fitness confer more malignant phenotypes and invasion constitutes an evolutionary bottleneck. Alternatively, ITH could represent branching evolution with invasion of multiple subclones. The two models respectively predict a hierarchy of subclones arranged by phenotype, or multiple subclones with shared phenotypes. We delineate these modes of invasion by merging ancestral, topographic, and phenotypic information from 12 human colorectal tumors (11 carcinomas, 1 adenoma) obtained through saturation microdissection of 325 small tumor regions. The majority of subclones (29/46, 60%) share superficial and invasive phenotypes. Of 11 carcinomas, 9 show evidence of multiclonal invasion, and invasive and metastatic subclones arise early along the ancestral trees. Early multiclonal invasion in the majority of these tumors indicates the expansion of co-evolving subclones with similar malignant potential in absence of late bottlenecks and suggests that barriers to invasion are minimal during colorectal cancer growth.

Tumorigenesis as the Paradigm of Quasi-neutral Molecular Evolution

In the absence of both positive and negative selections, coding sequences evolve at a neutral rate (R = 1). Such a high genomic rate is generally not achievable due to the prevalence of negative selection against codon substitutions. Remarkably, somatic evolution exhibits the seemingly neutral rate R ∼ 1 across normal and cancerous tissues. Nevertheless, R ∼ 1 may also mean that positive and negative selections are both strong, but equal in intensity. We refer to this regime as quasi-neutral. Indeed, individual genes in cancer cells often evolve at a much higher, or lower, rate than R ∼ 1. Here, we show that 1) quasi-neutrality is much more likely when populations are small (N < 50); 2) stem-cell populations in single normal tissue niches, from which tumors likely emerge, have a small N (usually <50) but selection at this stage is measurable and strong; 3) when N dips below 50, selection efficacy decreases precipitously; and 4) notably, N is smaller in the stem-cell niche of the small intestine than in the colon. Hence, the ∼70-fold higher rate of phenotypic evolution (observed as cancer risk) in the latter can be explained by the greater efficacy of selection, which then leads to the fixation of more advantageous and fewer deleterious mutations in colon cancers. In conclusion, quasi-neutral evolution sheds a new light on a general evolutionary principle that helps to explain aspects of cancer evolution.

Mutational signatures in colon cancer

OBJECTIVE

Recently, many tumor sequencing studies have inferred and reported on mutational signatures, short nucleotide patterns at which particular somatic base substitutions appear more often. A number of signatures reflect biological processes in the patient and factors associated with cancer risk. Our goal is to infer mutational signatures appearing in colon cancer, a cancer for which environmental risk factors vary by cancer subtype, and compare the signatures to those in adult stem cells from normal colon. We also compare the mutational signatures to others in the literature.

RESULTS

We apply a probabilistic mutation signature model to somatic mutations previously reported for six adult normal colon stem cells and 431 colon adenocarcinomas. We infer six mutational signatures in colon cancer, four being specific to tumors with hypermutation. Just two signatures explained the majority of mutations in the small number of normal aging colon samples. All six signatures are independently identified in a series of 295 Chinese colorectal cancers.

6070Association of blood pressure measures with brain structure and function: the Southall and Brent REvisited (SABRE) study

Background

In our rapidly ageing society, dementia and neurocognitive decline are significant global public health problems. Blood pressure (BP), an established cardiovascular risk factor, has been extensively studied with respect to brain structure and function; however, findings across the literature differ depending on the BP component in consideration, and the use of brachial rather than central BP.

Purpose

We set out to assess associations between detailed measures of brain structure and function with comprehensive measures of central and peripheral BP. Furthermore, we performed comprehensive mediation analyses on the associations to investigate potential micro and macro vascular mediatory pathways.

Methods

A community-based sample of 1438 individuals (69.7±6.2 years) from a tri-ethnic cohort. underwent vascular, cognitive and MRI based structural brain measures. BP measures included central (cSBP (Pulsecor)) and peripheral systolic BP (pSBP), diastolic BP (DBP), brachial (bPP) and central pulse pressure (cPP), and mean arterial pressure (MAP). Cognitive assessments comprised tests which explored global/overall function (CSID), executive function and memory. For brain structure, hippocampal brain volume was our key measure. Potential macro- and microvascular mediators included: arterial stiffness (cfPWV), carotid intima-media thickness, retinopathy, white matter hyperintensities and infarcts. Multivariable regression analyses were used to assess associations of BP components with cognitive function scores and brain volumes, adjusted for age, sex and ethnicity as well as macro- and microvascular risk factors. Multiple imputation was performed to account for missing data.

Results

After adjusting for age, sex and ethnicity, both cSBP and pSBP were negatively associated with memory (data are β±SE (z-score) −0.014±0.006, p=0.04), while DBP was positively associated with hippocampal volume (0.006±0.003, p=0.03). cPP was negatively associated with memory (−0.020±0.009, p=0.03), executive function (−0.018±0.006, p=0.002) and hippocampal volume (−0.007±0.003, p=0.005), while bPP was negatively associated with CSID (−0.008±0.004, p=0.04), memory (−0.020±0.008, p=0.02), executive function (−0.016±0.005, p=0.002) and hippocampal volume (−0.006±0.002, p=0.007). There was a stronger association between both PP measures and brain structure and function than with the other BP components, especially MAP. There was little difference in association between cPP and bPP measures with brain structure and function. Furthermore, these associations do not appear to be mediated by either macro- or microvascular disease.

Conclusion

These results suggest that there is a direct association between increased PP and a decline in brain structure and function. This implies that older patients with suboptimal PP control may be at increased risk of developing cognitive impairment and that measuring PP offers mechanistic information above and beyond conventional BP measures.

Acknowledgement/Funding

Wellcome Trust, British Heart Foundation

HiLDA: a statistical approach to investigate differences in mutational signatures

We propose a hierarchical latent Dirichlet allocation model (HiLDA) for characterizing somatic mutation data in cancer. The method allows us to infer mutational patterns and their relative frequencies in a set of tumor mutational catalogs and to compare the estimated frequencies between tumor sets. We apply our method to two datasets, one containing somatic mutations in colon cancer by the time of occurrence, before or after tumor initiation, and the second containing somatic mutations in esophageal cancer by sex, age, smoking status, and tumor site. In colon cancer, the relative frequencies of mutational patterns were found significantly associated with the time of occurrence of mutations. In esophageal cancer, the relative frequencies were significantly associated with the tumor site. Our novel method provides higher statistical power for detecting differences in mutational signatures.

Cancer cell evolution through the ages

A transmissible dog cancer that has been evolving for 6000 years rapidly reached its optimal state

Abstract 1648: Deep learning tissue "fingerprints" to identify patients and predict clinical subtypes of breast cancer from digital pathology images

Inspired by facial recognition, we define an analogous problem in digital pathology called tissue matching. The objective is to match histology image patches to the patient. Unlike many classification problems in pathology, tissue matching comes with its own ground truth, and does not require subjective annotation. Using tissue-matching via deep neural networks, we developed strategies to overcome common sources of noise in histology data, including H&E and slide scanner variability. We demonstrate that the typical approach of increasing the training set size, in the current study up to 12,000 tissue cores, yields only moderate gains in test accuracy, while including a loss term promoting style-invariance cooperatively improves the impact of scaling training set size. Our best neural network learned features that matched patients from the test set of H&E image patches with 93% accuracy (n=104 patients, baseline accuracy &lt;1%). Leveraging this network’s identification ability, we applied its internal representation as a feature vector (tissue fingerprint) to apply to other problems in pathology. We found that a fingerprint-based classifier could predict estrogen receptor status from breast cancer whole-slides on two separate cohorts with high accuracy (AUCROC=0.89), a sizeable improvement over previous approaches. This work presents a novel, scalable, and transparent approach to train neural networks to identify distinctive features of pathology images. These features have demonstrated utility in classifying biomarkers from morphology and have the potential to assist in a number of difficult tasks in pathology, including tissue subtype classification and patient tumor similarity assessments based on morphometry.

Citation Format: Rishi Rawat, Fei Sha, Darryl Shibata, Daniel Ruderman, David Agus. Deep learning tissue "fingerprints" to identify patients and predict clinical subtypes of breast cancer from digital pathology images [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1648.

Evolutionary Stem Cell Poker and Cancer Risks: The Paradox of The Large And Small Intestines

Purpose of review

Recent studies demonstrate that normal human tissues accumulate substantial numbers of somatic mutations with aging, to levels comparable to their corresponding cancers. If mutations cause cancer, how do tissues avoid cancer when mutations are unavoidable?

Recent findings

The small intestines (SI) and colon accumulate similar numbers of replication errors, but SI adenocarcinoma is much rarer than colorectal cancer. Both the small and large intestines are subdivided into millions of small neighborhoods (crypts) that are maintained by small numbers of stem cells. To explain the SI cancer paradox, four fundamental evolution parameters (mutation, drift, selection, and population size) are translated to crypts.

Summary

The accumulations of driver mutations in a single stem cell may be analogous to an evolutionary poker game. The rarity of SI cancer may reflect that SI crypts are smaller and have fewer stem cells than the colon, which reduces the numbers of cells at risk for mutation and perhaps selection efficiency. Tissue microarchitecture may physically modulate cancer evolution by controlling the numbers of directly competing neighboring cells. A better understanding of the SI cancer paradox may illuminate how tissues naturally avoid cancers when mutations are unavoidable.

Epigenetic Heterogeneity in Human Colorectal Tumors Reveals Preferential Conservation And Evidence of Immune Surveillance

Genomic intratumoral heterogeneity (ITH) is common in cancers, but the extent of phenotypic ITH is uncertain because most subclonal mutations are passengers. Since tumor phenotypes are largely driven by epigenetics, methylomic analyses can provide insights into phenotypic ITH. Following this principle, we determined the extent of epigenetic ITH in 16 human colorectal tumors by comparing the methylomes from spatially separated regions in each tumor. Methylomes from opposite tumor sides were similar (Pearson correlation >0.95) with little evidence of ITH or stepwise selection during growth, suggesting that the epigenome of a sampled tumor largely reflects that of its founder cell. Epigenetic conservation was functional, with higher conservation at promoters and expressed genes compared to non-coding regions. Despite epigenomic conservation, RNA expression varied between individual tumor glands, indicating continued adaption during growth. Because many promoters and enhancers were unmethylated, continued adaptation may be due to phenotypic plasticity. Gene enrichment analyses identified that interferon signaling and antigen-processing and presenting pathways were strongly conserved during tumor growth, suggesting a mechanism for immune evasion. In summary, our findings suggest that epigenomes are preferentially conserved during tumor growth and that early tumor cells are poised for rapid growth, phenotypic adaptation, and immune evasion.

Somatic cell evolution: how to improve with age

A recent article published in this journal illuminates a rare example of somatic evolution where cells improve rather than deteriorate with age. In mitotic intestinal crypts, stem cells with higher levels of a deleterious heteroplasmic germline mitochondrial mutation are purged through time, leading to crypts without the mutation. Similar somatic mitochondrial mutations are not purged from crypts, indicating that special conditions are needed to improve with age. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Phylogenetic and phylodynamic analyses of hepatitis C virus subtype 1a in Okinawa, Japan

Okinawa Island, located in Southern Japan, has a higher prevalence rate of hepatitis C virus subtype 1a (HCV-1a) infection than that in mainland Japan. Okinawa has a history of US military occupation after World War II. To elucidate the transmission history of HCV-1a in Okinawa, 26 whole-genome sequences were obtained from 29 patients during 2011-2016. Phylogenetic trees were reconstructed to identify the origin and characteristics of HCV-1a in Okinawa with epidemiological information. A phylogenetic tree based on whole-genome sequencing revealed that all of the samples were located below the US branches. Additionally, we identified one cluster comprised of 17 strains (Okinawa, n = 16; United States, n = 1). The majority of the patients in this cluster were people who inject drugs (PWID), indicating the presence of a people who inject drugs (PWID) cluster. Subsequently, Bayesian analyses were employed to reveal viral population dynamics. Intriguingly, a phylodynamic analysis uncovered a substantial increase in effective population size of HCV-1a from 1965 to 1980 and a slight increase in mid-2000, which were associated with an increase in illicit drug use in Okinawa. The estimated divergence time of the PWID cluster was 1967.6 (1964.2-1971.1). These findings suggest that HCV-1a was introduced into Okinawa from the United States in the late 1960s, coincident with the Vietnam War. Subsequently, HCV-1a might have spread among the Japanese population with the spread of injecting drug use. Our study provides an understanding of HCV transmission dynamics in Okinawa, as well as the key role of PWID in HCV transmission.

Classifying the evolutionary and ecological features of neoplasms

Neoplasms change over time through a process of cell-level evolution, driven by genetic and epigenetic alterations. However, the ecology of the microenvironment of a neoplastic cell determines which changes provide adaptive benefits. There is widespread recognition of the importance of these evolutionary and ecological processes in cancer, but to date, no system has been proposed for drawing clinically relevant distinctions between how different tumours are evolving. On the basis of a consensus conference of experts in the fields of cancer evolution and cancer ecology, we propose a framework for classifying tumours that is based on four relevant components. These are the diversity of neoplastic cells (intratumoural heterogeneity) and changes over time in that diversity, which make up an evolutionary index (Evo-index), as well as the hazards to neoplastic cell survival and the resources available to neoplastic cells, which make up an ecological index (Eco-index). We review evidence demonstrating the importance of each of these factors and describe multiple methods that can be used to measure them. Development of this classification system holds promise for enabling clinicians to personalize optimal interventions based on the evolvability of the patient's tumour. The Evo- and Eco-indices provide a common lexicon for communicating about how neoplasms change in response to interventions, with potential implications for clinical trials, personalized medicine and basic cancer research.

Between-region genetic divergence reflects the mode and tempo of tumor evolution

Given the implications of tumor dynamics for precision medicine, there is a need to systematically characterize the mode of evolution across diverse solid tumor types. In particular, methods to infer the role of natural selection within established human tumors are lacking. By simulating spatial tumor growth under different evolutionary modes and examining patterns of between-region subclonal genetic divergence from multiregion sequencing (MRS) data, we demonstrate that it is feasible to distinguish tumors driven by strong positive subclonal selection from those evolving neutrally or under weak selection, as the latter fail to dramatically alter subclonal composition. We developed a classifier based on measures of between-region subclonal genetic divergence and projected patient data into model space, finding different modes of evolution both within and between solid tumor types. Our findings have broad implications for how human tumors progress, how they accumulate intratumoral heterogeneity, and ultimately how they may be more effectively treated.

Early mutation bursts in colorectal tumors

Tumor growth is an evolutionary process involving accumulation of mutations, copy number alterations, and cancer stem cell (CSC) division and differentiation. As direct observation of this process is impossible, inference regarding when mutations occur and how stem cells divide is difficult. However, this ancestral information is encoded within the tumor itself, in the form of intratumoral heterogeneity of the tumor cell genomes. Here we present a framework that allows simulation of these processes and estimation of mutation rates at the various stages of tumor development and CSC division patterns for single-gland sequencing data from colorectal tumors. We parameterize the mutation rate and the CSC division pattern, and successfully retrieve their posterior distributions based on DNA sequence level data. Our approach exploits Approximate Bayesian Computation (ABC), a method that is becoming widely-used for problems of ancestral inference.

Abstract 2382: Novel integration of genomic and morphological information reveals tumor tissue heterogeneity

Cancer treatment decisions today are predominantly based upon decades-old histological methods, which more recently have been combined with simple phenotypic or molecular tests. To advance this paradigm, we have developed a digital molecular morphology platform that integrates histological images with next-generation sequencing (NGS) or PCR data. This allows us to visualize DNA mutations and RNA expression levels across a histological image, and to correlate mutational or expression status to cell morphological features. Thus, providing a novel approach to mapping tumor heterogeneity. The basic approach is to overlay a microstructure on top of H&E-stained FFPE slides to create a large number of tissue-bottomed micro-wells, which can be as small as a single cell or contain clusters of cells. Reagents are added to the micro-wells and biochemical reactions are carried out and analyzed in place (PCR) or partially offline (NGS). In the case of NGS, barcodes are used to reference the resulting sequence back to the tissue image. Software is then used to analyze and visualize the resulting genetic information in the context of the original histological image. Our initial work has focused on FFPE cancer biopsies using targeted cancer genes and gene panels. Here we demonstrate the use of this approach to measure and visualize KRAS G12V mutational status in colorectal cancer tissues, using both PCR and NGS detection modalities. We show that with this method we are able to efficiently extract DNA from the tissue while maintaining a leak-proof physical integrity from one micro-well to another. Further, we are able to PCR-amplify DNA in the micro-wells for direct fluorescence detection, or to create libraries for sequencing. Detection of KRAS G12V correlates well with malignant morphological features in the H&E stained tissue, and appears to present a more sensitive way to detect mutations than PCR or NGS from bulk FFPE tissue alone. We are currently applying this technology to a variety of research and clinical applications, ranging from assessment of tumor heterogeneity and evolution, to prediction of patient outcome, to post-operative NGS-based characterization of surgical margins. This integration of cellular and molecular data promises to more fully enable precision medicine to guide the course of treatment and improve individual patient outcomes.

Citation Format: Chen-Chung Lee, Paul Predki, Christopher Raub, Darryl Shibata, Clive Taylor, Emil Kartalov, Kenna Anderes. Novel integration of genomic and morphological information reveals tumor tissue heterogeneity. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2382.

At least two well-spaced samples are needed to genotype a solid tumor

Background

Human cancers are often sequenced to identify mutations. However, cancers are spatially heterogeneous populations with public mutations in all cells and private mutations in some cells. Without empiric knowledge of how mutations are distributed within a solid tumor it is uncertain whether single or multiple samples adequately sample its heterogeneity.

Methods

Using a cohort of 12 human colorectal tumors with well-validated mutations, the abilities to correctly classify public and private mutations were tested (paired t-test) with one sample or two samples obtained from opposite tumor sides.

Results

Two samples were significantly better than a single sample for correctly identifying public (99 % versus 97 %) and private mutations (85 % versus 46 %). Confounding single sample accuracy was that many private mutations appeared “clonal” in individual samples. Two samples detected the most frequent private mutations in 11 of the 12 tumors.

Conclusions

Two spatially-separated samples efficiently distinguish public from private mutations because private mutations common in one specimen are usually less frequent or absent in another sample. The patch-like private mutation topography in most colorectal tumors inherently limits the information in single tumor samples. The correct identification of public and private mutations may aid efforts to target mutations present in all tumor cells.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-016-2202-8) contains supplementary material, which is available to authorized users.

HistoMosaic Detecting KRAS G12V Mutation Across Colorectal Cancer Tissue Slices through in Situ PCR

We report on HistoMosaic, a novel technique for genetic analysis of formalin-fixed, paraffin-embedded tissue slices. It combines microfluidic compartmentalization, in situ allele-specific PCR, and fluorescence microscopy. The experimental proof of principle was achieved by in situ detection of KRAS G12V mutation in colorectal cancer tissues and is presented herein. HistoMosaic offers the ability to detect mutations over the entire tissue slide simultaneously, rapidly, economically, and without selection bias, while coregistering the genetic information with the preserved morphological information. Thus, HistoMosaic has wide applicability in basic science as a tool to map genetic heterogeneity. It is also a platform to build companion diagnostics for targeted therapies in oncology, to help ensure that the right drug is given to the right patient, thereby saving healthcare resources and improving patient outcomes.

Synchronous rectal adenocarcinoma and splenic marginal zone lymphoma

Synchronous cancers of different primary origin are rare. Here, we describe the case of a patient with concomitant diagnoses of rectal adenocarcinoma and splenic marginal zone lymphoma (smzl). A 57-year-old woman initially presented with abdominal pain. Physical examination and computed tomography demonstrated massive splenomegaly, and a complete blood count revealed microcytic anemia and lymphopenia. During the subsequent evaluation, she presented with hematochezia, melena, and constipation, which prompted gastroenterology referral. Subsequent endoscopic rectal ultrasonography revealed a T3N1 moderately differentiated rectal adenocarcinoma, with computed tomography imaging of chest, abdomen, and pelvis confirming no metastasis. Thus, the cancer was classified as clinical stage T3N1M0, stage iii. Bone marrow biopsy confirmed co-existing marginal zone lymphoma, and with the clinical presentation of massive splenomegaly, a diagnosis of smzl was made. The patient's management was individually tailored for simultaneous optimal treatment of both conditions. Concurrent treatment with neoadjuvant rituximab and 5-fluorouracil chemotherapy, with external-beam radiation therapy to the pelvis, was administered, followed by surgery consisting of en bloc splenectomy and distal pancreatectomy, and low anterior resection. The patient completed a standard course of adjuvant folfox (fluorouracil-leucovorin-oxaliplatin) chemotherapy and has remained disease-free for 7 years. To our knowledge, this report is the first to specifically describe simultaneous diagnoses of locally advanced rectal cancer and smzl. We also describe the successful combined neoadjuvant treatment combination of 5-fluorouracil, rituximab, and pelvic radiation.

Derivation of induced pluripotent stem cells from orangutan skin fibroblasts

Background

Orangutans are an endangered species whose natural habitats are restricted to the Southeast Asian islands of Borneo and Sumatra. Along with the African great apes, orangutans are among the closest living relatives to humans. For potential species conservation and functional genomics studies, we derived induced pluripotent stem cells (iPSCs) from cryopreserved somatic cells obtained from captive orangutans.

Results

Primary skin fibroblasts from two Sumatran orangutans were transduced with retroviral vectors expressing the human OCT4, SOX2, KLF4, and c-MYC factors. Candidate orangutan iPSCs were characterized by global gene expression and DNA copy number analysis. All were consistent with pluripotency and provided no evidence of large genomic insertions or deletions. In addition, orangutan iPSCs were capable of producing cells derived from all three germ layers in vitro through embryoid body differentiation assays and in vivo through teratoma formation in immune-compromised mice.

Conclusions

We demonstrate that orangutan skin fibroblasts are capable of being reprogrammed into iPSCs with hallmark molecular signatures and differentiation potential. We suggest that reprogramming orangutan somatic cells in genome resource banks could provide new opportunities for advancing assisted reproductive technologies relevant for species conservation efforts. Furthermore, orangutan iPSCs could have applications for investigating the phenotypic relevance of genomic changes that occurred in the human, African great ape, and/or orangutan lineages. This provides opportunities for orangutan cell culture models that would otherwise be impossible to develop from living donors due to the invasive nature of the procedures required for obtaining primary cells.

Electronic supplementary material

The online version of this article (doi:10.1186/s13104-015-1567-0) contains supplementary material, which is available to authorized users.

Induced pluripotent stem cell models of Zellweger spectrum disorder show impaired peroxisome assembly and cell type-specific lipid abnormalities

Introduction

Zellweger spectrum disorder (PBD-ZSD) is a disease continuum caused by mutations in a subset of PEX genes required for normal peroxisome assembly and function. They highlight the importance of peroxisomes in the development and functions of the central nervous system, liver, and other organs. To date, the underlying bases for the cell-type specificity of disease are not fully elucidated.

Methods

Primary skin fibroblasts from seven PBD-ZSD patients with biallelic PEX1, PEX10, PEX12, or PEX26 mutations and three healthy donors were transduced with retroviral vectors expressing Yamanaka reprogramming factors. Candidate induced pluripotent stem cells (iPSCs) were subject to global gene expression, DNA methylation, copy number variation, genotyping, in vitro differentiation and teratoma formation assays. Confirmed iPSCs were differentiated into neural progenitor cells (NPCs), neurons, oligodendrocyte precursor cells (OPCs), and hepatocyte-like cell cultures with peroxisome assembly evaluated by microscopy. Saturated very long chain fatty acid (sVLCFA) and plasmalogen levels were determined in primary fibroblasts and their derivatives.

Results

iPSCs were derived from seven PBD-ZSD patient-derived fibroblasts with mild to severe peroxisome assembly defects. Although patient and control skin fibroblasts had similar gene expression profiles, genes related to mitochondrial functions and organelle cross-talk were differentially expressed among corresponding iPSCs. Mitochondrial DNA levels were consistent among patient and control fibroblasts, but varied among all iPSCs. Relative to matching controls, sVLCFA levels were elevated in patient-derived fibroblasts, reduced in patient-derived iPSCs, and not significantly different in patient-derived NPCs. All cell types derived from donors with biallelic null mutations in a PEX gene showed plasmalogen deficiencies. Reporter gene assays compatible with high content screening (HCS) indicated patient-derived OPC and hepatocyte-like cell cultures had impaired peroxisome assembly.

Conclusions

Normal peroxisome activity levels are not required for cellular reprogramming of skin fibroblasts. Patient iPSC gene expression profiles were consistent with hypotheses highlighting the role of altered mitochondrial activities and organelle cross-talk in PBD-ZSD pathogenesis. sVLCFA abnormalities dramatically differed among patient cell types, similar to observations made in iPSC models of X-linked adrenoleukodystrophy. We propose that iPSCs could assist investigations into the cell type-specificity of peroxisomal activities, toxicology studies, and in HCS for targeted therapies for peroxisome-related disorders.

Electronic supplementary material

The online version of this article (doi:10.1186/s13287-015-0149-3) contains supplementary material, which is available to authorized users.

Many private mutations originate from the first few divisions of a human colorectal adenoma

Intratumoural mutational heterogeneity (ITH) or the presence of different private mutations in different parts of the same tumour is commonly observed in human tumours. The mechanisms generating such ITH are uncertain. Here we find that ITH can be remarkably well structured by measuring point mutations, chromosome copy numbers, and DNA passenger methylation from opposite sides and individual glands of a 6 cm human colorectal adenoma. ITH was present between tumour sides and individual glands, but the private mutations were side-specific and subdivided the adenoma into two major subclones. Furthermore, ITH disappeared within individual glands because the glands were clonal populations composed of cells with identical mutant genotypes. Despite mutation clonality, the glands were relatively old, diverse populations when their individual cells were compared for passenger methylation and by FISH. These observations can be organized into an expanding star-like ancestral tree with co-clonal expansion, where many private mutations and multiple related clones arise during the first few divisions. As a consequence, most detectable mutational ITH in the final tumour originates from the first few divisions. Much of the early history of a tumour, especially the first few divisions, may be embedded within the detectable ITH of tumour genomes.

Can oncology recapitulate paleontology? Lessons from species extinctions

Although we can treat cancers with cytotoxic chemotherapies, target them with molecules that inhibit oncogenic drivers, and induce substantial cell death with radiation, local and metastatic tumours recur, resulting in extensive morbidity and mortality. Indeed, driving a tumour to extinction is difficult. Geographically dispersed species of organisms are perhaps equally resistant to extinction, but >99.9% of species that have ever existed on this planet have become extinct. By contrast, we are nowhere near that level of success in cancer therapy. The phenomena are broadly analogous--in both cases, a genetically diverse population mutates and evolves through natural selection. The goal of cancer therapy is to cause cancer cell population extinction, or at least to limit any further increase in population size, to prevent the tumour burden from overwhelming the patient. However, despite available treatments, complete responses are rare, and partial responses are limited in duration. Many patients eventually relapse with tumours that evolve from cells that survive therapy. Similarly, species are remarkably resilient to environmental change. Paleontology can show us the conditions that lead to extinction and the characteristics of species that make them resistant to extinction. These lessons could be translated to improve cancer therapy and prognosis.

A Big Bang model of human colorectal tumor growth

What happens in the early, still undetectable human malignancy is unknown because direct observations are impractical. Here we present and validate a “Big Bang” model, whereby tumors grow predominantly as a single expansion producing numerous intermixed sub-clones that are not subject to stringent selection, and where both public (clonal) and most detectable private (subclonal) alterations arise early during growth. Genomic profiling of 349 individual glands from 15 colorectal tumors revealed the absence of selective sweeps, uniformly high intra-tumor heterogeneity (ITH), and sub-clone mixing in distant regions, as postulated by our model. We also verified the prediction that most detectable ITH originates from early private alterations, and not from later clonal expansions, thus exposing the profile of the primordial tumor. Moreover, some tumors appear born-to-be-bad, with sub-clone mixing indicative of early malignant potential. This new model provides a quantitative framework to interpret tumor growth dynamics and the origins of ITH with significant clinical implications.

Ancestral inference in tumors: how much can we know?

A tumor is thought to start from a single cell and genome. Yet genomes in the final tumor are typically heterogeneous. The mystery of this intratumoral heterogeneity (ITH) has not yet been uncovered, but much of this ITH may be secondary to replication errors. Methylation of cytosine bases often exhibits ITH and therefore may encode the ancestry of the tumor. In this study, we measure the passenger methylation patterns of a specific CpG region in 9 colorectal tumors by bisulfite sequencing and apply a tumor development model. Based on our model, we are able to retrieve information regarding the ancestry of each tumor using approximate Bayesian computation. With a large simulation study we explore the conditions under which we can estimate the model parameters, and the initial state of the first transformed cell. Finally we apply our analysis to clinical data to gain insight into the dynamics of tumor formation.

Direct measurements of human colon crypt stem cell niche genetic fidelity: the role of chance in non-darwinian mutation selection

Perfect human stem cell genetic fidelity would prevent aging and cancer. However, perfection would be difficult to achieve, and aging is universal and cancers common. A hypothesis is that because mutations are inevitable over a human lifetime, downstream mechanisms have evolved to manage the deleterious effects of beneficial and lethal mutations. In the colon, a crypt stem cell architecture reduces the number of mitotic cells at risk for mutation accumulation, and multiple niche stem cells ensure that a lethal mutation within any single stem cell does not lead to crypt death. In addition, the architecture of the colon crypt stem cell niche may harness probability or chance to randomly discard many beneficial mutations that might lead to cancer. An analysis of somatic chromosome copy number alterations (CNAs) reveals a lack of perfect fidelity in individual normal human crypts, with age-related increases and higher frequencies in ulcerative colitis, a proliferative, inflammatory disease. The age-related increase in somatic CNAs appears consistent with relatively normal replication error and cell division rates. Surprisingly, and similar to point mutations in cancer genomes, the types of crypt mutations were more consistent with random fixation rather than selection. In theory, a simple “non-Darwinian” way to nullify selection is to reduce the size of the reproducing population. Fates are more determined by chance rather than selection in very small populations, and therefore selection may be minimized within small crypt niches. The desired effect is that many beneficial mutations that might lead to cancer are randomly lost by drift rather than fixed by selection. The subdivision of the colon into multiple very small stem cell niches may trade Darwinian evolution for non-Darwinian somatic cell evolution, capitulating to aging but reducing cancer risks.

Abstract A14: Transforming growth factor beta signaling regulates the fate of intestinal stem cells

Transforming growth factor beta signaling has important roles in stem cell behavior, differentiation, cell motility, cell cycle and apoptosis. Here, we have utilized a novel mouse model that facilitates the sporadic inactivation of TgfβR2 via frameshift reversion of Cre in single, isolated cells and concomitant lineage tracing with a Cre-reporter. Short-term lineage tracing of TgfβR2-deficient crypts revealed reduced expansion suggesting a growth disadvantage among crypts. In contrast, long-term lineage tracing of TgfβR2-deficient crypts revealed an increased number suggesting a growth advantage within the crypt. To reconcile these apparently contradictory findings, we studied the dynamics of proliferative, Lgr5+ stem cells following TgfβR2 loss. We found that TgfβR2-deficient stem cell lineages required more time to reach monoclonality within the crypt. Using mathematical modeling of stem cell neutral drift, we found that increased “stemness” or a greater probability of a self-renewing asymmetrical outcome for TgfβR2-deficient stem cells was more consistent with our experimental results. Further analysis of TgfβR2-deficient stem cells in vivo revealed a decreased production of Paneth cells, a finding we corroborated in cultured intestinal organoids by treating with either a TgfβR1/2 inhibitor or low levels of the Tgfβ1 ligand. Recent studies by others suggested that quiescent stem cells are intermediaries between proliferative Lgr5+ stem cells and Paneth cells and that Tgfβ signaling is important in the formation of quiescent stem cells in other tissues. Therefore, we are currently asking whether Tgfβ signaling is important in the formation of quiescent stem cells in the intestine.

Citation Format: Jared M. Fischer, Ashleigh Miller, Peter P. Calabrese, Darryl Shibata, R Michael Liskay. Transforming growth factor beta signaling regulates the fate of intestinal stem cells. [abstract]. In: Proceedings of the Third AACR International Conference on Frontiers in Basic Cancer Research; Sep 18-22, 2013; National Harbor, MD. Philadelphia (PA): AACR; Cancer Res 2013;73(19 Suppl):Abstract nr A14.