Spatial and Temporal Heterogeneity in High-Grade Serous Ovarian Cancer: A Phylogenetic Analysis

Background

The major clinical challenge in the treatment of high-grade serous ovarian cancer (HGSOC) is the development of progressive resistance to platinum-based chemotherapy. The objective of this study was to determine whether intra-tumour genetic heterogeneity resulting from clonal evolution and the emergence of subclonal tumour populations in HGSOC was associated with the development of resistant disease.

Methods and Findings

Evolutionary inference and phylogenetic quantification of heterogeneity was performed using the MEDICC algorithm on high-resolution whole genome copy number profiles and selected genome-wide sequencing of 135 spatially and temporally separated samples from 14 patients with HGSOC who received platinum-based chemotherapy. Samples were obtained from the clinical CTCR-OV03/04 studies, and patients were enrolled between 20 July 2007 and 22 October 2009. Median follow-up of the cohort was 31 mo (interquartile range 22–46 mo), censored after 26 October 2013. Outcome measures were overall survival (OS) and progression-free survival (PFS). There were marked differences in the degree of clonal expansion (CE) between patients (median 0.74, interquartile range 0.66–1.15), and dichotimization by median CE showed worse survival in CE-high cases (PFS 12.7 versus 10.1 mo, p = 0.009; OS 42.6 versus 23.5 mo, p = 0.003). Bootstrap analysis with resampling showed that the 95% confidence intervals for the hazard ratios for PFS and OS in the CE-high group were greater than 1.0. These data support a relationship between heterogeneity and survival but do not precisely determine its effect size. Relapsed tissue was available for two patients in the CE-high group, and phylogenetic analysis showed that the prevalent clonal population at clinical recurrence arose from early divergence events. A subclonal population marked by a NF1 deletion showed a progressive increase in tumour allele fraction during chemotherapy.

Conclusions

This study demonstrates that quantitative measures of intra-tumour heterogeneity may have predictive value for survival after chemotherapy treatment in HGSOC. Subclonal tumour populations are present in pre-treatment biopsies in HGSOC and can undergo expansion during chemotherapy, causing clinical relapse.     

The role of memory in non-genetic inheritance and its impact on cancer treatment resistance

Intra-tumour heterogeneity is a leading cause of treatment failure and disease progression in cancer. While genetic mutations have long been accepted as a primary mechanism of generating this heterogeneity, the role of phenotypic plasticity is becoming increasingly apparent as a driver of intra-tumour heterogeneity. Consequently, understanding the role of this plasticity in treatment resistance and failure is a key component of improving cancer therapy. We develop a mathematical model of stochastic phenotype switching that tracks the evolution of drug-sensitive and drug-tolerant subpopulations to clarify the role of phenotype switching on population growth rates and tumour persistence. By including cytotoxic therapy in the model, we show that, depending on the strategy of the drug-tolerant subpopulation, stochastic phenotype switching can lead to either transient or permanent drug resistance. We study the role of phenotypic heterogeneity in a drug-resistant, genetically homogeneous population of non-small cell lung cancer cells to derive a rational treatment schedule that drives population extinction and avoids competitive release of the drug-tolerant sub-population. This model-informed therapeutic schedule results in increased treatment efficacy when compared against periodic therapy, and, most importantly, sustained tumour decay without the development of resistance.     

Intra-Tumour Signalling Entropy Determines Clinical Outcome in Breast and Lung Cancer

The cancer stem cell hypothesis, that a small population of tumour cells are responsible for tumorigenesis and cancer progression, is becoming widely accepted and recent evidence has suggested a prognostic and predictive role for such cells. Intra-tumour heterogeneity, the diversity of the cancer cell population within the tumour of an individual patient, is related to cancer stem cells and is also considered a potential prognostic indicator in oncology. The measurement of cancer stem cell abundance and intra-tumour heterogeneity in a clinically relevant manner however, currently presents a challenge. Here we propose signalling entropy, a measure of signalling pathway promiscuity derived from a sample’s genome-wide gene expression profile, as an estimate of the stemness of a tumour sample. By considering over 500 mixtures of diverse cellular expression profiles, we reveal that signalling entropy also associates with intra-tumour heterogeneity. By analysing 3668 breast cancer and 1692 lung adenocarcinoma samples, we further demonstrate that signalling entropy correlates negatively with survival, outperforming leading clinical gene expression based prognostic tools. Signalling entropy is found to be a general prognostic measure, valid in different breast cancer clinical subgroups, as well as within stage I lung adenocarcinoma. We find that its prognostic power is driven by genes involved in cancer stem cells and treatment resistance. In summary, by approximating both stemness and intra-tumour heterogeneity, signalling entropy provides a powerful prognostic measure across different epithelial cancers.     

Phylogenetic analysis under reticulate evolution

The usual assumption that species have evolved from a common ancestor by a simple branching process--where each branch is genetically isolated--has been challenged by the observation of frequent hybridization between species in natural populations. In fact, most plant species are thought to have hybrid origins. This reticulate pattern of species evolution has posed problems in the definition of speciation and in phylogenetic reconstruction, especially when molecular data are used. As a result, hybridization has been largely treated as an evolutionary accident or statistical error in phylogenetic analysis. In this paper, I explicitly incorporate hybridization as an evolutionary occurrence and then conduct phylogenetic reconstruction. I first examine the reticulate evolution under a pure drift model, and then extend the theory to fit a mutation model. A least-squares method is developed for reconstructing a reticulate phylogeny using gene frequency data. The efficacy of the method under the pure drift model is verified via Monte Carlo simulations.     

On the correlation between composition and site-specific evolutionary rate: implications for phylogenetic inference

Model-based phylogenetic reconstruction methods traditionally assume homogeneity of nucleotide frequencies among sequence sites and lineages. Yet, heterogeneity in base composition is a characteristic shared by most biological sequences. Compositional variation in time, reflected in the compositional biases among contemporary sequences, has already been extensively studied, and its detrimental effects on phylogenetic estimates are known. However, fewer studies have focused on the effects of spatial compositional heterogeneity within genes. We show here that different sites in an alignment do not always share a unique compositional pattern, and we provide examples where nucleotide frequency trends are correlated with the site-specific rate of evolution in RNA genes. Spatial compositional heterogeneity is shown to affect the estimation of evolutionary parameters. With standard phylogenetic methods, estimates of equilibrium frequencies are found to be biased towards the composition observed at fast-evolving sites. Conversely, the ancestral composition estimates of some time-heterogeneous but spatially homogeneous methods are found to be biased towards frequencies observed at invariant and slow-evolving sites. The latter finding challenges the result of a previous study arguing against a hyperthermophilic last universal ancestor from the low apparent G + C content of its rRNA sequences. We propose a new model to account for compositional variation across sites. A Gaussian process prior is used to allow for a smooth change in composition with evolutionary rate. The model has been implemented in the phylogenetic inference software PHASE, and Bayesian methods can be used to obtain the model parameters. The results suggest that this model can accurately capture the observed trends in present-day RNA sequences.     

Estimating phylogenetic inertia in Tithonia (Asteraceae): a comparative approach

Abstract.— Phylogenetic inertia is a difficult issue in evolutionary biology because we have yet to reach a consensus about how to measure it. In this study a comparative approach is used to evaluate phylogenetic inertia in 14 demographic and morphological characters in 10 species and one subspecies of the genus Tithonia (Asteraceae). Three different methods, autocorrelational analysis, phylogenetic correlograms, and ancestor-state reconstruction, were used to evaluate phylogenetic inertia in these traits. Results were highly dependent on the method applied. Autoregression and phylogenetic eigenvector regression (PVR) methods found more inertia in morphological traits. In contrast, phylogenetic correlograms and ancestor-state reconstruction suggest that morphological characters exhibit less phylogenetic inertia than demographic ones. The differences between results are discussed and methods are compared in an effort to understand phylogenetic inertia more thoroughly.     

系统发育研究中“长枝吸引”现象概述

系统发育研究(phylogeny)不仅有助于重建地球所有生物体的进化历史, 而且还可以揭示进化生物学领域中的一些基本问题。清晰了解各生物物种进化历程及不同物种之间的进化关系, 是进一步研究和探索生物学其他学科的基础。但是现今广泛应用的所有系统发育分析方法都存在一定的局限性, 在一定程度上不能有效消除各种误差, 从而不能客观地处理和分析数据, 也就不能成功重建生物进化历程, 真实反映物种进化关系。系统发育研究中, “长枝吸引” (Long-branch Attraction, LBA)假象是最为困扰研究者的问题。文章从“长枝吸引”问题的产生原由、检测方法以及消除策略等多个方面进行详尽概述, 并通过列举典型实例, 阐述了解决“长枝吸引”问题的途径。     

Rapid maximum likelihood ancestral state reconstruction of continuous characters: A rerooting‐free algorithm

Ancestral state reconstruction is a method used to study the evolutionary trajectories of quantitative characters on phylogenies. Although efficient methods for univariate ancestral state reconstruction under a Brownian motion model have been described for at least 25 years, to date no generalization has been described to allow more complex evolutionary models, such as multivariate trait evolution, non‐Brownian models, missing data, and within‐species variation. Furthermore, even for simple univariate Brownian motion models, most phylogenetic comparative R packages compute ancestral states via inefficient tree rerooting and full tree traversals at each tree node, making ancestral state reconstruction extremely time‐consuming for large phylogenies. Here, a computationally efficient method for fast maximum likelihood ancestral state reconstruction of continuous characters is described. The algorithm has linear complexity relative to the number of species and outperforms the fastest existing R implementations by several orders of magnitude. The described algorithm is capable of performing ancestral state reconstruction on a 1,000,000‐species phylogeny in fewer than 2 s using a standard laptop, whereas the next fastest R implementation would take several days to complete. The method is generalizable to more complex evolutionary models, such as phylogenetic regression, within‐species variation, non‐Brownian evolutionary models, and multivariate trait evolution. Because this method enables fast repeated computations on phylogenies of virtually any size, implementation of the described algorithm can drastically alleviate the computational burden of many otherwise prohibitively time‐consuming tasks requiring reconstruction of ancestral states, such as phylogenetic imputation of missing data, bootstrapping procedures, Expectation‐Maximization algorithms, and Bayesian estimation. The described ancestral state reconstruction algorithm is implemented in the Rphylopars functions anc.recon and phylopars.     

On a functional-morphological approach to phylogenetic reconstruction: A critique

A method of phylogenetic reconstruction as proposed by a number of scientists of the Senckenberg Research Institute is discussed. The method is based on functional-morphological studies, the evolutionary adaptation principle of Bock and Von Wahlert (1965) and so-called model reconstruction. It is argued in this paper that direction of the adaptation process cannot be determined because of lack of knowledge about particular selective forces and that theories of model reconstruction are not open to contradiction in the sense of Popperian falsification. Although it has been claimed that the method provides the only valid directional argument for morphoclines in cladistic studies, it remains unclear how to proceed when morphoclines show contradictory polarities. Moreover, it is doubtful whether polarities of morphoclines can be determined independently of phylogenetic hypotheses, and also whether the use of multistate morphoclines is methodologically valid. By relying on a particular evolutionary theory, i.e. the neo-Darwinian theory, and consequently assigning natural selection as the major agent of directional progress, the Senckenburg method of phylogenetic reconstruction restricts itself to microevolutionary change and, therefore, cannot be used when other hypotheses on the evolutionary process appear to explain the speciation process more plausibly, i.e. hypotheses on macroevolution. Furthermore, it is an unproved statement that evolution always proceeds according to the principle of economy.     

The tortoise and the hare II: relative utility of 21 noncoding chloroplast DNA sequences for phylogenetic analysis

Chloroplast DNA sequences are a primary source of data for plant molecular systematic studies. A few key papers have provided the molecular systematics community with universal primer pairs for noncoding regions that have dominated the field, namely trnL-trnF and trnK/matK. These two regions have provided adequate information to resolve species relationships in some taxa, but often provide little resolution at low taxonomic levels. To obtain better phylogenetic resolution, sequence data from these regions are often coupled with other sequence data. Choosing an appropriate cpDNA region for phylogenetic investigation is difficult because of the scarcity of information about the tempo of evolutionary rates among different noncoding cpDNA regions. The focus of this investigation was to determine whether there is any predictable rate heterogeneity among 21 noncoding cpDNA regions identified as phylogenetically useful at low levels. To test for rate heterogeneity among the different cpDNA regions, we used three species from each of 10 groups representing eight major phylogenetic lineages of phanerogams. The results of this study clearly show that a survey using as few as three representative taxa can be predictive of the amount of phylogenetic information offered by a cpDNA region and that rate heterogeneity exists among noncoding cpDNA regions.     

THE RELATIONSHIP BETWEEN EVOLUTIONARY THEORY AND PHYLOGENETIC ANALYSIS

The relationship between phylogenetic reconstruction and evolutionary theory is reassessed. It is argued here that phylogenies, and evolutionary principles, should be analysed initially as independently from each other as possible. Only then can they be used to test one another. If the phylogenies and evolutionary principles are totally consistent with one another, this consilience of independent lines of evidence increases confidence in both. If, however, there is a conflict, then one should assess the relative support for each hypothesis, and tentatively accept the more strongly supported one. We review examples where the phylogenetic hypothesis is preferred over the evolutionary principle, and vice versa, and instances where the conflict cannot be readily resolved. Because the analyses of pattern and process must initially be kept separate, the temporal order in which they are performed is unimportant. Therefore, the widespread methodology of always proceeding from cladogram to evolutionary ‘scenario’ cannot be justified philosophically. Such an approach means that cladograms cannot be properly tested against evolutionary principles, and that evolutionary ‘scenarios’ have no independent standing. Instead, we propose the ‘consilience’ approach where phylogenetic and evolutionary hypotheses are formulated independently from each other and then examined for agreement.     

Phylogenetic Inference with Weighted Codon Evolutionary Distances

We develop a new approach to estimate a matrix of pairwise evolutionary distances from a codon-based alignment based on a codon evolutionary model. The method first computes a standard distance matrix for each of the three codon positions. Then these three distance matrices are weighted according to an estimate of the global evolutionary rate of each codon position and averaged into a unique distance matrix. Using a large set of both real and simulated codon-based alignments of nucleotide sequences, we show that this approach leads to distance matrices that have a significantly better treelikeness compared to those obtained by standard nucleotide evolutionary distances. We also propose an alternative weighting to eliminate the part of the noise often associated with some codon positions, particularly the third position, which is known to induce a fast evolutionary rate. Simulation results show that fast distance-based tree reconstruction algorithms on distance matrices based on this codon position weighting can lead to phylogenetic trees that are at least as accurate as, if not better, than those inferred by maximum likelihood. Finally, a well-known multigene dataset composed of eight yeast species and 106 codon-based alignments is reanalyzed and shows that our codon evolutionary distances allow building a phylogenetic tree which is similar to those obtained by non-distance-based methods (e.g., maximum parsimony and maximum likelihood) and also significantly improved compared to standard nucleotide evolutionary distance estimates.     

Informational gene phylogenies do not support a fourth domain of life for nucleocytoplasmic large DNA viruses

Mimivirus is a nucleocytoplasmic large DNA virus (NCLDV) with a genome size (1.2 Mb) and coding capacity ( 1000 genes) comparable to that of some cellular organisms. Unlike other viruses, Mimivirus and its NCLDV relatives encode homologs of broadly conserved informational genes found in Bacteria, Archaea, and Eukaryotes, raising the possibility that they could be placed on the tree of life. A recent phylogenetic analysis of these genes showed the NCLDVs emerging as a monophyletic group branching between Eukaryotes and Archaea. These trees were interpreted as evidence for an independent "fourth domain" of life that may have contributed DNA processing genes to the ancestral eukaryote. However, the analysis of ancient evolutionary events is challenging, and tree reconstruction is susceptible to bias resulting from non-phylogenetic signals in the data. These include compositional heterogeneity and homoplasy, which can lead to the spurious grouping of compositionally-similar or fast-evolving sequences. Here, we show that these informational gene alignments contain both significant compositional heterogeneity and homoplasy, which were not adequately modelled in the original analysis. When we use more realistic evolutionary models that better fit the data, the resulting trees are unable to reject a simple null hypothesis in which these informational genes, like many other NCLDV genes, were acquired by horizontal transfer from eukaryotic hosts. Our results suggest that a fourth domain is not required to explain the available sequence data.     

PHYLOGENETIC CONSTRAINTS IN KEY FUNCTIONAL TRAITS BEHIND SPECIES’ CLIMATE NICHES: PATTERNS OF DESICCATION AND COLD RESISTANCE ACROSS 95 DROSOPHILA SPECIES

Species distributions are often constrained by climatic tolerances that are ultimately determined by evolutionary history and/or adaptive capacity, but these factors have rarely been partitioned. Here, we experimentally determined two key climatic niche traits (desiccation and cold resistance) for 92–95 Drosophila species and assessed their importance for geographic distributions, while controlling for acclimation, phylogeny, and spatial autocorrelation. Employing an array of phylogenetic analyses, we documented moderate‐to‐strong phylogenetic signal in both desiccation and cold resistance. Desiccation and cold resistance were clearly linked to species distributions because significant associations between traits and climatic variables persisted even after controlling for phylogeny. We used different methods to untangle whether phylogenetic signal reflected phylogenetically related species adapted to similar environments or alternatively phylogenetic inertia. For desiccation resistance, weak phylogenetic inertia was detected; ancestral trait reconstruction, however, revealed a deep divergence that could be traced back to the genus level. Despite drosophilids’ high evolutionary potential related to short generation times and high population sizes, cold resistance was found to have a moderate‐to‐high level of phylogenetic inertia, suggesting that evolutionary responses are likely to be slow. Together these findings suggest species distributions are governed by evolutionarily conservative climate responses, with limited scope for rapid adaptive responses to future climate change.     

New Weighting Methods for Phylogenetic Tree Reconstruction Using Multiple Loci

Efficient determination of evolutionary distances is important for the correct reconstruction of phylogenetic trees. The performance of the pooled distance required for reconstructing a phylogenetic tree can be improved by applying large weights to appropriate distances for reconstructing phylogenetic trees and small weights to inappropriate distances. We developed two weighting methods, the modified Tajima–Takezaki method and the modified least-squares method, for reconstructing phylogenetic trees from multiple loci. By computer simulations, we found that both of the new methods were more efficient in reconstructing correct topologies than the no-weight method. Hence, we reconstructed hominoid phylogenetic trees from mitochondrial DNA using our new methods, and found that the levels of bootstrap support were significantly increased by the modified Tajima–Takezaki and by the modified least-squares method.     

Phylogenetic signal, evolutionary process, and rate

A recent advance in the phylogenetic comparative analysis of continuous traits has been explicit, model-based measurement of "phylogenetic signal" in data sets composed of observations collected from species related by a phylogenetic tree. Phylogenetic signal is a measure of the statistical dependence among species' trait values due to their phylogenetic relationships. Although phylogenetic signal is a measure of pattern (statistical dependence), there has nonetheless been a widespread propensity in the literature to attribute this pattern to aspects of the evolutionary process or rate. This may be due, in part, to the perception that high evolutionary rate necessarily results in low phylogenetic signal; and, conversely, that low evolutionary rate or stabilizing selection results in high phylogenetic signal (due to the resulting high resemblance between related species). In this study, we use individual-based numerical simulations on stochastic phylogenetic trees to clarify the relationship between phylogenetic signal, rate, and evolutionary process. Under the simplest model for quantitative trait evolution, homogeneous rate genetic drift, there is no relation between evolutionary rate and phylogenetic signal. For other circumstances, such as functional constraint, fluctuating selection, niche conservatism, and evolutionary heterogeneity, the relationship between process, rate, and phylogenetic signal is complex. For these reasons, we recommend against interpretations of evolutionary process or rate based on estimates of phylogenetic signal.     

Effects of nucleotide composition bias on the success of the parsimony criterion in phylogenetic inference

Convergence in nucleotide composition (CNC) in unrelated lineages is a factor potentially affecting the performance of most phylogeny reconstruction methods. Such convergence has deleterious effects because unrelated lineages show similarities due to similar nucleotide compositions and not shared histories. While some methods (such as the LogDet/paralinear distance measure) avoid this pitfall, the amount of convergence in nucleotide composition necessary to deceive other phylogenetic methods has never been quantified. We examined analytically the relationship between convergence in nucleotide composition and the consistency of parsimony as a phylogenetic estimator for four taxa. Our results show that rather extreme amounts of convergence are necessary before parsimony begins to prefer the incorrect tree. Ancillary observations are that (for unweighted Fitch parsimony) transition/transversion bias contributes to the impact of CNC and, for a given amount of CNC and fixed branch lengths, data sets exhibiting substantial site-to-site rate heterogeneity present fewer difficulties than data sets in which rates are homogeneous. We conclude by reexamining a data set originally used to illustrate the problems caused by CNC. Using simulations, we show that in this case the convergence in nucleotide composition alone is insufficient to cause any commonly used methods to fail, and accounting for other evolutionary factors (such as site-to-site rate heterogeneity) can give a correct inference without accounting for CNC.     

Directional biases in phylogenetic structure quantification: a Mediterranean case study

Recent years have seen an increasing effort to incorporate phylogenetic hypotheses to the study of community assembly processes. The incorporation of such evolutionary information has been eased by the emergence of specialized software for the automatic estimation of partially resolved supertrees based on published phylogenies. Despite this growing interest in the use of phylogenies in ecological research, very few studies have attempted to quantify the potential biases related to the use of partially resolved phylogenies and to branch length accuracy, and no work has examined how tree shape may affect inference of community phylogenetic metrics. In this study, we tested the influence of phylogenetic resolution and branch length information on the quantification of phylogenetic structure, and also explored the impact of tree shape (stemminess) on the loss of accuracy in phylogenetic structure quantification due to phylogenetic resolution. For this purpose, we used 9 sets of phylogenetic hypotheses of varying resolution and branch lengths to calculate three indices of phylogenetic structure: the mean phylogenetic distance (NRI), the mean nearest taxon distance (NTI) and phylogenetic diversity (stdPD) metrics. The NRI metric was the less sensitive to phylogenetic resolution, stdPD showed an intermediate sensitivity, and NTI was the most sensitive one; NRI was also less sensitive to branch length accuracy than NTI and stdPD, the degree of sensitivity being strongly dependent on the dating method and the sample size. Directional biases were generally towards type II errors. Interestingly, we detected that tree shape influenced the accuracy loss derived from the lack of phylogenetic resolution, particularly for NRI and stdPD. We conclude that well‐resolved molecular phylogenies with accurate branch length information are needed to identify the underlying phylogenetic structure of communities, and also that sensitivity of phylogenetic structure measures to low phylogenetic resolution can strongly vary depending on phylogenetic tree shape.     

Effect of site-specific heterogeneous evolution on phylogenetic reconstruction: a simple evaluation

Recent studies have shown that heterogeneous evolution may mislead phylogenetic analysis, which has been neglected for a long time. We evaluate the effect of heterogeneous evolution on phylogenetic analysis, using 18 fish mitogenomic coding sequences as an example. Using the software DIVERGE, we identify 198 amino acid sites that have experienced heterogeneous evolution. After removing these sites, the rest of sites are shown to be virtually homogeneous in the evolutionary rate. There are some differences between phylogenetic trees built with heterogeneous sites ("before tree") and without heterogeneous sites ("after tree"). Our study demonstrates that for phylogenetic reconstruction, an effective approach is to identify and remove sites with heterogeneous evolution, and suggests that researchers can use the software DIVERGE to remove the influence of heterogeneous evolution before reconstructing phylogenetic trees.