Estimating an oncogenetic tree when false negatives and positives are present

Szabó, Anikó; Boucher, Kenneth M.

doi:10.1016/s0025-5564(02)00086-x

Cited by 49 publications

(75 citation statements)

References 13 publications

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“…Recurrent CNAs were defined as gains or deletions of material occurring in the same region in at least two patients and plotted as a heatmap (Fig S1). The recurrent CNAs were then analysed further with a CRAN R package Oncotree 0·31 to determine a tree model for oncogenesis (Desper et al, 1999;Szabo & Boucher, 2002). To explore functional modules that are potentially affected by the CNAs, enrichment analysis on protein-protein interaction complexes was performed using custom written Perl scripts.…”

Section: Data Visualization and Biological Correlationsmentioning

confidence: 99%

Genome‐wide analysis of cytogenetic aberrations in ETV6/RUNX1‐positive childhood acute lymphoblastic leukaemia

et al. 2012

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SummaryThe chromosomal translocation t(12;21) resulting in the ETV6/RUNX1 fusion gene is the most frequent structural cytogenetic abnormality among patients with childhood acute lymphoblastic leukaemia (ALL). We investigated 62 ETV6/RUNX1-positive childhood ALL patients by single nucleotide polymorphism array to explore acquired copy number alterations (CNAs) at diagnosis. The mean number of CNAs was 2·82 (range 0-14). Concordance with available G-band karyotyping and comparative genomic hybridization was 93%. Based on three major protein-protein complexes disrupted by these CNAs, patients could be categorized into four distinct subgroups, defined by different underlying biological mechanisms relevant to the aetiology of childhood ALL. When recurrent CNAs were evaluated by an oncogenetic tree analysis classifying their sequential order, the most common genetic aberrations (deletions of 6q, 9p, 13q and X, and gains of 10 and 21) seemed independent of each other. Finally, we identified the most common regions with recurrent gains and losses, which comprise microRNA clusters with known oncogenic or tumour-suppressive roles. The present study sheds further light on the genetic diversity of ETV6/ RUNX1-positive childhood ALL, which may be important for understanding poor responses among this otherwise highly curable subset of ALL and lead to novel targeted treatment strategies.

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Section: Data Visualization and Biological Correlationsmentioning

confidence: 99%

Genome‐wide analysis of cytogenetic aberrations in ETV6/RUNX1‐positive childhood acute lymphoblastic leukaemia

et al. 2012

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“…Recent work by Szabo and Boucher (2002) has indicated that the tree modeling method can be improved somewhat by allowing for the possibility of false positive and false negative rates (⑀ ϩ and ⑀ Ϫ , respectively). In particular, the branching reconstruction process is quite tolerant of large false negative rates, and, although the method is less tolerant of false positives, reconstruction is still possible with biologically reasonable false positive rates.…”

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confidence: 99%

Construction of tree models for pathogenesis of nasopharyngeal carcinoma

Huang

Desper

Schäffer

et al. 2004

Genes Chromosomes & Cancer

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Pathogenesis of nasopharyngeal carcinoma (NPC) is a multistep and multipathway process that cannot be fully explained by a fixed linear progression model. We used distance-based and branching-tree methods to construct more general tree-like models for NPC carcinogenesis from 170 comparative genomic hybridization (CGH) samples previously published in five smaller studies. Imbalances were classified into "overlap regions," each containing the most commonly gained or lost band on each chromosome arm as well as adjacent bands that were gained or lost almost as often. The chromosome abnormalities associated with NPC were -3p26-13 (48.9%), -11q22-25 (38.1%), -16q12-24 (38.1%), -14q24-32 (32.4%), -13q21-32 (22.3%), -9p23-21(21.6%), +12p12 (46%), +12q13-15 (43.9%), +1q22-32 (33.1%), +3q13.1-26.2 (30.2%), and +8q22.1-24.2 (27.3%). NPC can be classified into two groups, one marked by +12p12 and +8q22.1-24.2 and the other by -3p26-13, -11q22-25, -14q24-32, and +1q22-32. The tree models predicted -3p26-13 and +12p12 as early events and +8q22.1-24.2 as a late event. The predictions for -3p26-13 and +8q22.1-24.2 were consistent with previous studies. The prediction for +12p12 is being reported for the first time. Many known NPC-related genes on chromosomal regions of these tree models are discussed, some of which may merit additional study. The potential applications of tree models are also discussed.

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“…Moreover, two types of tree models can be simultaneously constructed to boost confidence on the results. Szabo et al [22] tested the robustness of the pure oncogenetic tree models by introducing observational errors, the results show that false positive and false negative observations occurring with small probability would not impact on the reconstruction of tree models, although it is more sensitive to false positive observations. However, one major limitation of tree models is that it can not be employed to explain the phenomenon of converging pathways.…”

Section: Comparison Of Mathematical Modeling Methodsmentioning

confidence: 99%

“…Since proposed, tree models have been used by many researchers to explore the molecular mechanism of tumor development, including the CGH data from renal cell carcinoma [20,22] , hereditary breast cancers [23] , bladder cancer [24] , head and neck squamous cell cancer [25] , nasopharyngeal carcinoma [14,26] , thymoma [27] , and rat mammary tumors [28] , and breakpoint data from ovarian cancer [21] . These models have been used to identify early events, as well as marker events of subtypes of tumors, defining the sequence of these events and the involved pathways.…”

Section: Oncogenetic Tree Modelsmentioning

confidence: 99%

Mathematical modeling of carcinogenesis based on chromosome aberration data

2009

Chin. J. Cancer Res.

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Objective:The progression of human cancer is characterized by the accumulation of genetic instability. An increasing number of experimental genetic molecular techniques have been used to detect chromosome aberrations. Previous studies on chromosome abnormalities often focused on identifying the frequent loci of chromosome alterations, but rarely addressed the issue of interrelationship of chromosomal abnormalities. In the last few years, several mathematical models have been employed to construct models of carcinogenesis, in an attempt to identify the time order and cause-and-effect relationship of chromosome aberrations. The principles and applications of these models are reviewed and compared in this paper. Mathematical modeling of carcinogenesis can contribute to our understanding of the molecular genetics of tumor development, and identification of cancer related genes, thus leading to improved clinical practice of cancer.

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Estimating an oncogenetic tree when false negatives and positives are present

Cited by 49 publications

References 13 publications

Genome‐wide analysis of cytogenetic aberrations in ETV6/RUNX1‐positive childhood acute lymphoblastic leukaemia

Genome‐wide analysis of cytogenetic aberrations in ETV6/RUNX1‐positive childhood acute lymphoblastic leukaemia

Construction of tree models for pathogenesis of nasopharyngeal carcinoma

Mathematical modeling of carcinogenesis based on chromosome aberration data

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