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1.
J Immunother Cancer ; 8(1)2020 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-32217756

RESUMO

BACKGROUND: Tumor mutational burden (TMB), defined as the number of somatic mutations per megabase of interrogated genomic sequence, demonstrates predictive biomarker potential for the identification of patients with cancer most likely to respond to immune checkpoint inhibitors. TMB is optimally calculated by whole exome sequencing (WES), but next-generation sequencing targeted panels provide TMB estimates in a time-effective and cost-effective manner. However, differences in panel size and gene coverage, in addition to the underlying bioinformatics pipelines, are known drivers of variability in TMB estimates across laboratories. By directly comparing panel-based TMB estimates from participating laboratories, this study aims to characterize the theoretical variability of panel-based TMB estimates, and provides guidelines on TMB reporting, analytic validation requirements and reference standard alignment in order to maintain consistency of TMB estimation across platforms. METHODS: Eleven laboratories used WES data from The Cancer Genome Atlas Multi-Center Mutation calling in Multiple Cancers (MC3) samples and calculated TMB from the subset of the exome restricted to the genes covered by their targeted panel using their own bioinformatics pipeline (panel TMB). A reference TMB value was calculated from the entire exome using a uniform bioinformatics pipeline all members agreed on (WES TMB). Linear regression analyses were performed to investigate the relationship between WES and panel TMB for all 32 cancer types combined and separately. Variability in panel TMB values at various WES TMB values was also quantified using 95% prediction limits. RESULTS: Study results demonstrated that variability within and between panel TMB values increases as the WES TMB values increase. For each panel, prediction limits based on linear regression analyses that modeled panel TMB as a function of WES TMB were calculated and found to approximately capture the intended 95% of observed panel TMB values. Certain cancer types, such as uterine, bladder and colon cancers exhibited greater variability in panel TMB values, compared with lung and head and neck cancers. CONCLUSIONS: Increasing uptake of TMB as a predictive biomarker in the clinic creates an urgent need to bring stakeholders together to agree on the harmonization of key aspects of panel-based TMB estimation, such as the standardization of TMB reporting, standardization of analytical validation studies and the alignment of panel-based TMB values with a reference standard. These harmonization efforts should improve consistency and reliability of panel TMB estimates and aid in clinical decision-making.

2.
Transl Lung Cancer Res ; 7(6): 616-630, 2018 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-30505706

RESUMO

Background: Tumor mutational burden (TMB) is an increasingly important biomarker for immune checkpoint inhibitors. Recent publications have described strong association between high TMB and objective response to mono- and combination immunotherapies in several cancer types. Existing methods to estimate TMB require large amount of input DNA, which may not always be available. Methods: In this study, we develop a method to estimate TMB using the Oncomine Tumor Mutation Load (TML) Assay with 20 ng of DNA, and we characterize the performance of this method on various formalin-fixed, paraffin-embedded (FFPE) research samples of several cancer types. We measure the analytical performance of TML workflow through comparison with control samples with known truth, and we compare performance with an orthogonal method which uses matched normal sample to remove germline variants. We perform whole exome sequencing (WES) on a batch of FFPE samples and compare the WES TMB values with TMB estimates by the TML assay. Results: In-silico analyses demonstrated the Oncomine TML panel has sufficient genomic coverage to estimate somatic mutations with a strong correlation (r2=0.986) to WES. Further, in silico prediction using WES data from three separate cohorts and comparing with a subset of the WES overlapping with the TML panel, confirmed the ability to stratify responders and non-responders to immune checkpoint inhibitors with high statistical significance. We found the rate of somatic mutations with the TML assay on cell lines and control samples were similar to the known truth. We verified the performance of germline filtering using only a tumor sample in comparison to a matched tumor-normal experimental design to remove germline variants. We compared TMB estimates by the TML assay with that from WES on a batch of FFPE research samples and found high correlation (r2=0.83). We found biologically interesting tumorigenesis signatures on FFPE research samples of colorectal cancer (CRC), lung, and melanoma origin. Further, we assessed TMB on a cohort of FFPE research samples including lung, colon, and melanoma tumors to discover the biologically relevant range of TMB values. Conclusions: These results show that the TML assay targeting a 1.7-Mb genomic footprint can accurately predict TMB values that are comparable to the WES. The TML assay workflow incorporates a simple workflow using the Ion GeneStudio S5 System. Further, the AmpliSeq chemistry allows the use of low input DNA to estimate mutational burden from FFPE samples. This TMB assay enables scalable, robust research into immuno-oncology biomarkers with scarce samples.

3.
Proc Natl Acad Sci U S A ; 112(41): 12764-9, 2015 Oct 13.
Artigo em Inglês | MEDLINE | ID: mdl-26385966

RESUMO

Reconstructing the phylogenetic relationships that unite all lineages (the tree of life) is a grand challenge. The paucity of homologous character data across disparately related lineages currently renders direct phylogenetic inference untenable. To reconstruct a comprehensive tree of life, we therefore synthesized published phylogenies, together with taxonomic classifications for taxa never incorporated into a phylogeny. We present a draft tree containing 2.3 million tips-the Open Tree of Life. Realization of this tree required the assembly of two additional community resources: (i) a comprehensive global reference taxonomy and (ii) a database of published phylogenetic trees mapped to this taxonomy. Our open source framework facilitates community comment and contribution, enabling the tree to be continuously updated when new phylogenetic and taxonomic data become digitally available. Although data coverage and phylogenetic conflict across the Open Tree of Life illuminate gaps in both the underlying data available for phylogenetic reconstruction and the publication of trees as digital objects, the tree provides a compelling starting point for community contribution. This comprehensive tree will fuel fundamental research on the nature of biological diversity, ultimately providing up-to-date phylogenies for downstream applications in comparative biology, ecology, conservation biology, climate change, agriculture, and genomics.


Assuntos
Classificação/métodos , Filogenia , Animais , Humanos
4.
Bioinformatics ; 31(3): 432-3, 2015 Feb 01.
Artigo em Inglês | MEDLINE | ID: mdl-25273112

RESUMO

SUMMARY: MulRF is a platform-independent software package for phylogenetic analysis using multi-copy gene trees. It seeks the species tree that minimizes the Robinson-Foulds (RF) distance to the input trees using a generalization of the RF distance to multi-labeled trees. The underlying generic tree distance measure and fast running time make MulRF useful for inferring phylogenies from large collections of gene trees, in which multiple evolutionary processes as well as phylogenetic error may contribute to gene tree discord. MulRF implements several features for customizing the species tree search and assessing the results, and it provides a user-friendly graphical user interface (GUI) with tree visualization. The species tree search is implemented in C++ and the GUI in Java Swing. AVAILABILITY: MulRF's executable as well as sample datasets and manual are available at http://genome.cs.iastate.edu/CBL/MulRF/, and the source code is available at https://github.com/ruchiherself/MulRFRepo. CONTACT: ruchic@ufl.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.


Assuntos
Dosagem de Genes/genética , Filogenia , Análise de Sequência de DNA/métodos , Software , Algoritmos , Simulação por Computador , Evolução Molecular , Humanos , Linguagens de Programação
5.
Syst Biol ; 64(2): 325-39, 2015 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-25540456

RESUMO

With the availability of genomic sequence data, there is increasing interest in using genes with a possible history of duplication and loss for species tree inference. Here we assess the performance of both nonprobabilistic and probabilistic species tree inference approaches using gene duplication and loss and coalescence simulations. We evaluated the performance of gene tree parsimony (GTP) based on duplication (Only-dup), duplication and loss (Dup-loss), and deep coalescence (Deep-c) costs, the NJst distance method, the MulRF supertree method, and PHYLDOG, which jointly estimates gene trees and species tree using a hierarchical probabilistic model. We examined the effects of gene tree and species sampling, gene tree error, and duplication and loss rates on the accuracy of phylogenetic estimates. In the 10-taxon duplication and loss simulation experiments, MulRF is more accurate than the other methods when the duplication and loss rates are low, and Dup-loss is generally the most accurate when the duplication and loss rates are high. PHYLDOG performs well in 10-taxon duplication and loss simulations, but its run time is prohibitively long on larger data sets. In the larger duplication and loss simulation experiments, MulRF outperforms all other methods in experiments with at most 100 taxa; however, in the larger simulation, Dup-loss generally performs best. In all duplication and loss simulation experiments with more than 10 taxa, all methods perform better with more gene trees and fewer missing sequences, and they are all affected by gene tree error. Our results also highlight high levels of error in estimates of duplications and losses from GTP methods and demonstrate the usefulness of methods based on generic tree distances for large analyses.


Assuntos
Classificação/métodos , Filogenia , Análise de Sequência de DNA/métodos , Simulação por Computador , Deleção de Genes , Duplicação Gênica , Análise de Sequência de DNA/normas , Software/normas
6.
Algorithms Mol Biol ; 8(1): 28, 2013 Nov 01.
Artigo em Inglês | MEDLINE | ID: mdl-24180377

RESUMO

BACKGROUND: Constructing species trees from multi-copy gene trees remains a challenging problem in phylogenetics. One difficulty is that the underlying genes can be incongruent due to evolutionary processes such as gene duplication and loss, deep coalescence, or lateral gene transfer. Gene tree estimation errors may further exacerbate the difficulties of species tree estimation. RESULTS: We present a new approach for inferring species trees from incongruent multi-copy gene trees that is based on a generalization of the Robinson-Foulds (RF) distance measure to multi-labeled trees (mul-trees). We prove that it is NP-hard to compute the RF distance between two mul-trees; however, it is easy to calculate this distance between a mul-tree and a singly-labeled species tree. Motivated by this, we formulate the RF problem for mul-trees (MulRF) as follows: Given a collection of multi-copy gene trees, find a singly-labeled species tree that minimizes the total RF distance from the input mul-trees. We develop and implement a fast SPR-based heuristic algorithm for the NP-hard MulRF problem.We compare the performance of the MulRF method (available at http://genome.cs.iastate.edu/CBL/MulRF/) with several gene tree parsimony approaches using gene tree simulations that incorporate gene tree error, gene duplications and losses, and/or lateral transfer. The MulRF method produces more accurate species trees than gene tree parsimony approaches. We also demonstrate that the MulRF method infers in minutes a credible plant species tree from a collection of nearly 2,000 gene trees. CONCLUSIONS: Our new phylogenetic inference method, based on a generalized RF distance, makes it possible to quickly estimate species trees from large genomic data sets. Since the MulRF method, unlike gene tree parsimony, is based on a generic tree distance measure, it is appealing for analyses of genomic data sets, in which many processes such as deep coalescence, recombination, gene duplication and losses as well as phylogenetic error may contribute to gene tree discord. In experiments, the MulRF method estimated species trees accurately and quickly, demonstrating MulRF as an efficient alternative approach for phylogenetic inference from large-scale genomic data sets.

7.
BMC Bioinformatics ; 13 Suppl 10: S11, 2012 Jun 25.
Artigo em Inglês | MEDLINE | ID: mdl-22759416

RESUMO

BACKGROUND: Gene tree - species tree reconciliation problems infer the patterns and processes of gene evolution within a species tree. Gene tree parsimony approaches seek the evolutionary scenario that implies the fewest gene duplications, duplications and losses, or deep coalescence (incomplete lineage sorting) events needed to reconcile a gene tree and a species tree. While a gene tree parsimony approach can be informative about genome evolution and phylogenetics, error in gene trees can profoundly bias the results. RESULTS: We introduce efficient algorithms that rapidly search local Subtree Prune and Regraft (SPR) or Tree Bisection and Reconnection (TBR) neighborhoods of a given gene tree to identify a topology that implies the fewest duplications, duplication and losses, or deep coalescence events. These algorithms improve on the current solutions by a factor of n for searching SPR neighborhoods and n2 for searching TBR neighborhoods, where n is the number of taxa in the given gene tree. They provide a fast error correction protocol for ameliorating the effects of gene tree error by allowing small rearrangements in the topology to improve the reconciliation cost. We also demonstrate a simple protocol to use the gene rearrangement algorithm to improve gene tree parsimony phylogenetic analyses. CONCLUSIONS: The new gene tree rearrangement algorithms provide a fast method to address gene tree error. They do not make assumptions about the underlying processes of genome evolution, and they are amenable to analyses of large-scale genomic data sets. These algorithms are also easily incorporated into gene tree parsimony phylogenetic analyses, potentially producing more credible estimates of reconciliation cost.


Assuntos
Algoritmos , Evolução Molecular , Duplicação Gênica , Genômica/métodos , Biologia Computacional/métodos , Genoma , Modelos Teóricos , Filogenia , Leveduras/genética
8.
Artigo em Inglês | MEDLINE | ID: mdl-22431553

RESUMO

A Robinson-Foulds (RF) supertree for a collection of input trees is a tree containing all the species in the input trees that is at minimum total RF distance to the input trees. Thus, an RF supertree is consistent with the maximum number of splits in the input trees. Constructing RF supertrees for rooted and unrooted data is NP-hard. Nevertheless, effective local search heuristics have been developed for the restricted case where the input trees and the supertree are rooted. We describe new heuristics, based on the Edge Contract and Refine (ECR) operation, that remove this restriction, thereby expanding the utility of RF supertrees. Our experimental results on simulated and empirical data sets show that our unrooted local search algorithms yield better supertrees than those obtained from MRP and rooted RF heuristics in terms of total RF distance to the input trees and, for simulated data, in terms of RF distance to the true tree.


Assuntos
Algoritmos , Biologia Computacional/métodos , Filogenia , Análise por Conglomerados , Simulação por Computador , Bases de Dados Factuais
9.
BMC Bioinformatics ; 11: 574, 2010 Nov 23.
Artigo em Inglês | MEDLINE | ID: mdl-21092314

RESUMO

BACKGROUND: The ever-increasing wealth of genomic sequence information provides an unprecedented opportunity for large-scale phylogenetic analysis. However, species phylogeny inference is obfuscated by incongruence among gene trees due to evolutionary events such as gene duplication and loss, incomplete lineage sorting (deep coalescence), and horizontal gene transfer. Gene tree parsimony (GTP) addresses this issue by seeking a species tree that requires the minimum number of evolutionary events to reconcile a given set of incongruent gene trees. Despite its promise, the use of gene tree parsimony has been limited by the fact that existing software is either not fast enough to tackle large data sets or is restricted in the range of evolutionary events it can handle. RESULTS: We introduce iGTP, a platform-independent software program that implements state-of-the-art algorithms that greatly speed up species tree inference under the duplication, duplication-loss, and deep coalescence reconciliation costs. iGTP significantly extends and improves the functionality and performance of existing gene tree parsimony software and offers advanced features such as building effective initial trees using stepwise leaf addition and the ability to have unrooted gene trees in the input. Moreover, iGTP provides a user-friendly graphical interface with integrated tree visualization software to facilitate analysis of the results. CONCLUSIONS: iGTP enables, for the first time, gene tree parsimony analyses of thousands of genes from hundreds of taxa using the duplication, duplication-loss, and deep coalescence reconciliation costs, all from within a convenient graphical user interface.


Assuntos
Genômica/métodos , Filogenia , Software , Algoritmos , Bases de Dados Genéticas , Evolução Molecular , Duplicação Gênica , Genoma
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