CINner: modeling and simulation of chromosomal instability in cancer at single-cell resolution.

Cancer development is characterized by chromosomal instability, manifesting in frequent occurrences of different genomic alteration mechanisms ranging in extent and impact. Mathematical modeling can help evaluate the role of each mutational process during tumor progression, however existing frameworks can only capture certain aspects of chromosomal instability (CIN). We present CINner, a mathematical framework for modeling genomic diversity and selection during tumor evolution. The main advantage of CINner is its flexibility to incorporate many genomic events that directly impact cellular fitness, from driver gene mutations to copy number alterations (CNAs), including focal amplifications and deletions, missegregations and whole-genome duplication (WGD). We apply CINner to find chromosome-arm selection parameters that drive tumorigenesis in the absence of WGD in chromosomally stable cancer types. We found that the selection parameters predict WGD prevalence among different chromosomally unstable tumors, hinting that the selective advantage of WGD cells hinges on their tolerance for aneuploidy and escape from nullisomy. Direct application of CINner to model the WGD proportion and fraction of genome altered (FGA) further uncovers the increase in CNA probabilities associated with WGD in each cancer type. CINner can also be utilized to study chromosomally stable cancer types, by applying a selection model based on driver gene mutations and focal amplifications or deletions. Finally, we used CINner to analyze the impact of CNA probabilities, chromosome selection parameters, tumor growth dynamics and population size on cancer fitness and heterogeneity. We expect that CINner will provide a powerful modeling tool for the oncology community to quantify the impact of newly uncovered genomic alteration mechanisms on shaping tumor progression and adaptation.

Another view of sequential sampling in the birth process with immigration.

We explore properties of the family sizes arising in a linear birth process with immigration (BI). In particular, we study the correlation of the number of families observed during consecutive disjoint intervals of time. Letting S(a, b) be the number of families observed in (a, b), we study the expected sample variance and its asymptotics for p consecutive sequential samples [Formula: see text], for [Formula: see text]. By conditioning on the sizes of the samples, we provide a connection between [Formula: see text] and p sequential samples of sizes [Formula: see text], drawn from a single run of a Chinese Restaurant Process. Properties of the latter were studied in da Silva et al. (Bernoulli 29:1166-1194, 2023. https://doi.org/10.3150/22-BEJ1494 ). We show how the continuous-time framework helps to make asymptotic calculations easier than its discrete-time counterpart. As an application, for a specific choice of [Formula: see text], where the lengths of intervals are logarithmically equal, we revisit Fisher's 1943 multi-sampling problem and give another explanation of what Fisher's model could have meant in the world of sequential samples drawn from a BI process.

Correction: Spatial regulation of Drosophila ovarian Follicle Stem Cell division rates and cell cycle transitions.

[This corrects the article DOI: 10.1371/journal.pgen.1010965.].

Spatial regulation of Drosophila ovarian Follicle Stem Cell division rates and cell cycle transitions.

Drosophila ovarian Follicle Stem Cells (FSCs) present a favorable paradigm for understanding how stem cell division and differentiation are balanced in communities where those activities are independent. FSCs also allow exploration of how this balance is integrated with spatial stem cell heterogeneity. Posterior FSCs become proliferative Follicle Cells (FCs), while anterior FSCs become quiescent Escort Cells (ECs) at about one fourth the frequency. A single stem cell can nevertheless produce both FCs and ECs because it can move between anterior and posterior locations. Studies based on EdU incorporation to approximate division rates suggested that posterior FSCs divide faster than anterior FSCs. However, direct measures of cell cycle times are required to ascertain whether FC output requires a net flow of FSCs from anterior to posterior. Here, by using live imaging and FUCCI cell-cycle reporters, we measured absolute division rates. We found that posterior FSCs cycle more than three times faster than anterior FSCs and produced sufficient new cells to match FC production. H2B-RFP dilution studies supported different cycling rates according to A/P location and facilitated live imaging, showing A/P exchange of FSCs in both directions, consistent with the dynamic equilibrium inferred from division rate measurements. Inversely graded Wnt and JAK-STAT pathway signals regulate FSC differentiation to ECs and FCs. JAK-STAT promotes both differentiation to FCs and FSC cycling, affording some coordination of these activities. When JAK-STAT signaling was manipulated to be spatially uniform, the ratio of posterior to anterior division rates was reduced but remained substantial, showing that graded JAK-STAT signaling only partly explains the graded cycling of FSCs. By using FUCCI markers, we found a prominent G2/M cycling restriction of posterior FSCs together with an A/P graded G1/S restriction, that JAK-STAT signaling promotes both G1/S and G2/M transitions, and that PI3 kinase signaling principally stimulates the G2/M transition.

Single-Cell RNA Sequencing Unifies Developmental Programs of Esophageal and Gastric Intestinal Metaplasia.

Intestinal metaplasia in the esophagus (Barrett's esophagus IM, or BE-IM) and stomach (GIM) are considered precursors for esophageal and gastric adenocarcinoma, respectively. We hypothesize that BE-IM and GIM follow parallel developmental trajectories in response to differing inflammatory insults. Here, we construct a single-cell RNA-sequencing atlas, supported by protein expression studies, of the entire gastrointestinal tract spanning physiologically normal and pathologic states including gastric metaplasia in the esophagus (E-GM), BE-IM, atrophic gastritis, and GIM. We demonstrate that BE-IM and GIM share molecular features, and individual cells simultaneously possess transcriptional properties of gastric and intestinal epithelia, suggesting phenotypic mosaicism. Transcriptionally E-GM resembles atrophic gastritis; genetically, it is clonal and has a lower mutational burden than BE-IM. Finally, we show that GIM and BE-IM acquire a protumorigenic, activated fibroblast microenvironment. These findings suggest that BE-IM and GIM can be considered molecularly similar entities in adjacent organs, opening the path for shared detection and treatment strategies. SIGNIFICANCE: Our data capture the gradual molecular and phenotypic transition from a gastric to intestinal phenotype (IM) in the esophagus and stomach. Because BE-IM and GIM can predispose to cancer, this new understanding of a common developmental trajectory could pave the way for a more unified approach to detection and treatment. See related commentary by Stachler, p. 1291. This article is highlighted in the In This Issue feature, p. 1275.

Imaging and Molecular Annotation of Xenographs and Tumours (IMAXT): High throughput data and analysis infrastructure.

With the aim of producing a 3D representation of tumors, imaging and molecular annotation of xenografts and tumors (IMAXT) uses a large variety of modalities in order to acquire tumor samples and produce a map of every cell in the tumor and its host environment. With the large volume and variety of data produced in the project, we developed automatic data workflows and analysis pipelines. We introduce a research methodology where scientists connect to a cloud environment to perform analysis close to where data are located, instead of bringing data to their local computers. Here, we present the data and analysis infrastructure, discuss the unique computational challenges and describe the analysis chains developed and deployed to generate molecularly annotated tumor models. Registration is achieved by use of a novel technique involving spherical fiducial marks that are visible in all imaging modalities used within IMAXT. The automatic pipelines are highly optimized and allow to obtain processed datasets several times quicker than current solutions narrowing the gap between data acquisition and scientific exploitation.

Rearrangement processes and structural variations show evidence of selection in oesophageal adenocarcinomas.

Oesophageal adenocarcinoma (OAC) provides an ideal case study to characterize large-scale rearrangements. Using whole genome short-read sequencing of 383 cases, for which 214 had matched whole transcriptomes, we observed structural variations (SV) with a predominance of deletions, tandem duplications and inter-chromosome junctions that could be identified as LINE-1 mobile element (ME) insertions. Complex clusters of rearrangements resembling breakage-fusion-bridge cycles or extrachromosomal circular DNA accounted for 22% of complex SVs affecting known oncogenes. Counting SV events affecting known driver genes substantially increased the recurrence rates of these drivers. After excluding fragile sites, we identified 51 candidate new drivers in genomic regions disrupted by SVs, including ETV5, KAT6B and CLTC. RUNX1 was the most recurrently altered gene (24%), with many deletions inactivating the RUNT domain but preserved the reading frame, suggesting an altered protein product. These findings underscore the importance of identification of SV events in OAC with implications for targeted therapies.

CamGFR v2: A New Model for Estimating the Glomerular Filtration Rate from Standardized or Non-standardized Creatinine in Patients with Cancer.

PURPOSE: Management of patients with cancer, specifically carboplatin dosing, requires accurate knowledge of glomerular filtration rate (GFR). Direct measurement of GFR is resource limited. Available models for estimated GFR (eGFR) are optimized for patients without cancer and either isotope dilution mass spectrometry (IDMS)- or non-IDMS-standardized creatinine measurements. We present an eGFR model for patients with cancer compatible with both creatinine measurement methods. EXPERIMENTAL DESIGN: GFR measurements, biometrics, and IDMS- or non-IDMS-standardized creatinine values were collected for adult patients from three cancer centers. Using statistical modeling, an IDMS and non-IDMS creatinine-compatible eGFR model (CamGFR v2) was developed. Its performance was compared with that of the existing models Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI), Modification of Diet in Renal Disease (MDRD), Full Age Spectrum (FAS), Lund-Malmö revised, and CamGFR v1, using statistics for bias, precision, accuracy, and clinical robustness. RESULTS: A total of 3,083 IDMS- and 4,612 non-IDMS-standardized creatinine measurements were obtained from 7,240 patients. IDMS-standardized creatinine values were lower than non-IDMS-standardized values in within-center comparisons (13.8% lower in Cambridge; P < 0.0001 and 19.3% lower in Manchester; P < 0.0001), and more consistent between centers. CamGFR v2 was the most accurate [root-mean-squared error for IDMS, 14.97 mL/minute (95% confidence interval, 13.84-16.13) and non-IDMS, 15.74 mL/minute (14.86-16.63)], most clinically robust [proportion with >20% error of calculated carboplatin dose for IDMS, 0.12 (0.09-0.14) and non-IDMS, 0.17 (0.15-0.2)], and least biased [median residual for IDMS, 0.73 mL/minute (-0.68 to 2.2) and non-IDMS, -0.43 mL/minute (-1.48 to 0.91)] eGFR model, particularly when eGFR was larger than 60 ml/minute. CONCLUSIONS: CamGFR v2 can utilize IDMS- and non-IDMS-standardized creatinine measurements and outperforms previous models. CamGFR v2 should be examined prospectively as a practice-changing standard of care for eGFR-based carboplatin dosing.

The mutREAD method detects mutational signatures from low quantities of cancer DNA.

Mutational processes acting on cancer genomes can be traced by investigating mutational signatures. Because high sequencing costs limit current studies to small numbers of good-quality samples, we propose a robust, cost- and time-effective method, called mutREAD, to detect mutational signatures from small quantities of DNA, including degraded samples. We show that mutREAD recapitulates mutational signatures identified by whole genome sequencing, and will ultimately allow the study of mutational signatures in larger cohorts and, by compatibility with formalin-fixed paraffin-embedded samples, in clinical settings.

Identification of Subtypes of Barrett's Esophagus and Esophageal Adenocarcinoma Based on DNA Methylation Profiles and Integration of Transcriptome and Genome Data.

BACKGROUND & AIMS: Esophageal adenocarcinomas (EACs) are heterogeneous and often preceded by Barrett's esophagus (BE). Many genomic changes have been associated with development of BE and EAC, but little is known about epigenetic alterations. We performed epigenetic analyses of BE and EAC tissues and combined these data with transcriptome and genomic data to identify mechanisms that control gene expression and genome integrity. METHODS: In a retrospective cohort study, we collected tissue samples and clinical data from 150 BE and 285 EAC cases from the Oesophageal Cancer Classification and Molecular Stratification consortium in the United Kingdom. We analyzed methylation profiles of all BE and EAC tissues and assigned them to subgroups using non-negative matrix factorization with k-means clustering. Data from whole-genome sequencing and transcriptome studies were then incorporated; we performed integrative methylation and RNA-sequencing analyses to identify genes that were suppressed with increased methylation in promoter regions. Levels of different immune cell types were computed using single-sample gene set enrichment methods. We derived 8 organoids from 8 EAC tissues and tested their sensitivity to different drugs. RESULTS: BE and EAC samples shared genome-wide methylation features, compared with normal tissues (esophageal, gastric, and duodenum; controls) from the same patients and grouped into 4 subtypes. Subtype 1 was characterized by DNA hypermethylation with a high mutation burden and multiple mutations in genes in cell cycle and receptor tyrosine signaling pathways. Subtype 2 was characterized by a gene expression pattern associated with metabolic processes (ATP synthesis and fatty acid oxidation) and lack methylation at specific binding sites for transcription factors; 83% of samples of this subtype were BE and 17% were EAC. The third subtype did not have changes in methylation pattern, compared with control tissue, but had a gene expression pattern that indicated immune cell infiltration; this tumor type was associated with the shortest time of patient survival. The fourth subtype was characterized by DNA hypomethylation associated with structure rearrangements, copy number alterations, with preferential amplification of CCNE1 (cells with this gene amplification have been reported to be sensitive to CDK2 inhibitors). Organoids with reduced levels of MGMT and CHFR expression were sensitive to temozolomide and taxane drugs. CONCLUSIONS: In a comprehensive integrated analysis of methylation, transcriptome, and genome profiles of more than 400 BE and EAC tissues, along with clinical data, we identified 4 subtypes that were associated with patient outcomes and potential responses to therapy.

Multicenter Validation of the CamGFR Model for Estimated Glomerular Filtration Rate.

Important oncological management decisions rely on kidney function assessed by serum creatinine-based estimated glomerular filtration rate (eGFR). However, no large-scale multicenter comparisons of methods to determine eGFR in patients with cancer are available. To compare the performance of formulas for eGFR based on routine clinical parameters and serum creatinine not calibrated with isotope dilution mass spectrometry, we studied 3620 patients with cancer and 166 without cancer who had their glomerular filtration rate (GFR) measured with an exogenous nuclear tracer at one of seven clinical centers. The mean measured GFR was 86 mL/min. Accuracy of all models was center dependent, reflecting intercenter variability of isotope dilution mass spectrometry-creatinine measurements. CamGFR was the most accurate model for eGFR (root-mean-squared error 17.3 mL/min) followed by the Chronic Kidney Disease Epidemiology Collaboration model (root-mean-squared error 18.2 mL/min).

Loss of the interleukin-6 receptor causes immunodeficiency, atopy, and abnormal inflammatory responses.

IL-6 excess is central to the pathogenesis of multiple inflammatory conditions and is targeted in clinical practice by immunotherapy that blocks the IL-6 receptor encoded by IL6R We describe two patients with homozygous mutations in IL6R who presented with recurrent infections, abnormal acute-phase responses, elevated IgE, eczema, and eosinophilia. This study identifies a novel primary immunodeficiency, clarifying the contribution of IL-6 to the phenotype of patients with mutations in IL6ST, STAT3, and ZNF341, genes encoding different components of the IL-6 signaling pathway, and alerts us to the potential toxicity of drugs targeting the IL-6R.

The landscape of selection in 551 esophageal adenocarcinomas defines genomic biomarkers for the clinic.

Esophageal adenocarcinoma (EAC) is a poor-prognosis cancer type with rapidly rising incidence. Understanding of the genetic events driving EAC development is limited, and there are few molecular biomarkers for prognostication or therapeutics. Using a cohort of 551 genomically characterized EACs with matched RNA sequencing data, we discovered 77 EAC driver genes and 21 noncoding driver elements. We identified a mean of 4.4 driver events per tumor, which were derived more commonly from mutations than copy number alterations, and compared the prevelence of these mutations to the exome-wide mutational excess calculated using non-synonymous to synonymous mutation ratios (dN/dS). We observed mutual exclusivity or co-occurrence of events within and between several dysregulated EAC pathways, a result suggestive of strong functional relationships. Indicators of poor prognosis (SMAD4 and GATA4) were verified in independent cohorts with significant predictive value. Over 50% of EACs contained sensitizing events for CDK4 and CDK6 inhibitors, which were highly correlated with clinically relevant sensitivity in a panel of EAC cell lines and organoids.

Fixation and Spread of Somatic Mutations in Adult Human Colonic Epithelium.

We investigated the means and timing by which mutations become fixed in the human colonic epithelium by visualizing somatic clones and mathematical inference. Fixation requires two sequential steps. First, one of approximately seven active stem cells residing within each colonic crypt has to be mutated. Second, the mutated stem cell has to replace neighbors to populate the entire crypt in a process that takes several years. Subsequent clonal expansion due to crypt fission is infrequent for neutral mutations (around 0.7% of all crypts undergo fission in a single year). Pro-oncogenic mutations subvert both stem cell replacement to accelerate fixation and clonal expansion by crypt fission to achieve high mutant allele frequencies with age. The benchmarking of these behaviors allows the advantage associated with different gene-specific mutations to be compared irrespective of the cellular mechanisms by which they are conferred.

Ancestral inference from haplotypes and mutations.

We consider inference about the history of a sample of DNA sequences, conditional upon the haplotype counts and the number of segregating sites observed at the present time. After deriving some theoretical results in the coalescent setting, we implement rejection sampling and importance sampling schemes to perform the inference. The importance sampling scheme addresses an extension of the Ewens Sampling Formula for a configuration of haplotypes and the number of segregating sites in the sample. The implementations include both constant and variable population size models. The methods are illustrated by two human Y chromosome datasets.

Sequencing of prostate cancers identifies new cancer genes, routes of progression and drug targets.

Prostate cancer represents a substantial clinical challenge because it is difficult to predict outcome and advanced disease is often fatal. We sequenced the whole genomes of 112 primary and metastatic prostate cancer samples. From joint analysis of these cancers with those from previous studies (930 cancers in total), we found evidence for 22 previously unidentified putative driver genes harboring coding mutations, as well as evidence for NEAT1 and FOXA1 acting as drivers through noncoding mutations. Through the temporal dissection of aberrations, we identified driver mutations specifically associated with steps in the progression of prostate cancer, establishing, for example, loss of CHD1 and BRCA2 as early events in cancer development of ETS fusion-negative cancers. Computational chemogenomic (canSAR) analysis of prostate cancer mutations identified 11 targets of approved drugs, 7 targets of investigational drugs, and 62 targets of compounds that may be active and should be considered candidates for future clinical trials.

Division-independent differentiation mandates proliferative competition among stem cells.

Cancer-initiating gatekeeper mutations that arise in stem cells would be especially potent if they stabilize and expand an affected stem cell lineage. It is therefore important to understand how different stem cell organization strategies promote or prevent variant stem cell amplification in response to different types of mutation, including those that activate proliferation. Stem cell numbers can be maintained constant while producing differentiated products through individually asymmetrical division outcomes or by population asymmetry strategies in which individual stem cell lineages necessarily compete for niche space. We considered alternative mechanisms underlying population asymmetry and used quantitative modeling to predict starkly different consequences of altering proliferation rate: A variant, faster proliferating mutant stem cell should compete better only when stem cell division and differentiation are independent processes. For most types of stem cells, it has not been possible to ascertain experimentally whether division and differentiation are coupled. However, Drosophila follicle stem cells (FSCs) provided a favorable system with which to investigate population asymmetry mechanisms and also for measuring the impact of altered proliferation on competition. We found from detailed cell lineage studies that division and differentiation of an individual FSC are not coupled. We also found that FSC representation, reflecting maintenance and amplification, was highly responsive to genetic changes that altered only the rate of FSC proliferation. The FSC paradigm therefore provides definitive experimental evidence for the general principle that relative proliferation rate will always be a major determinant of competition among stem cells specifically when stem cell division and differentiation are independent.

Simulating the component counts of combinatorial structures.

This article describes and compares methods for simulating the component counts of random logarithmic combinatorial structures such as permutations and mappings. We exploit the Feller coupling for simulating permutations to provide a very fast method for simulating logarithmic assemblies more generally. For logarithmic multisets and selections, this approach is replaced by an acceptance/rejection method based on a particular conditioning relationship that represents the distribution of the combinatorial structure as that of independent random variables conditioned on a weighted sum. We show how to improve its acceptance rate. We illustrate the method by estimating the probability that a random mapping has no repeated component sizes, and establish the asymptotic distribution of the difference between the number of components and the number of distinct component sizes for a very general class of logarithmic structures.