Inferring models of multiscale copy number evolution for single-tumor phylogenetics

Bioinformatics

Volumn 31, Issue 12, 2015, Pages i258-i267

  Chowdhury, Salim Akhter ^a,b   Gertz, E Michael ^c   Wangsa, Darawalee ^d   Heselmeyer Haddad, Kerstin ^d   Ried, Thomas ^d   Schäffer, Alejandro A ^c   Schwartz, Russell ^b,e  

^a UNIVERSITY OF PITTSBURGH   (United States)

^b Carnegie Mellon University   (United States)

^c NATIONAL INSTITUTES OF HEALTH   (United States)

^d NATIONAL CANCER INSTITUTE   (United States)

^e CARNEGIE MELLON UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; BIOLOGICAL MODEL; COMPUTER PROGRAM; DISEASE COURSE; FEMALE; GENE DOSAGE; GENETICS; GENOMICS; HUMAN; MOLECULAR EVOLUTION; NEOPLASM; PHYLOGENY; UTERINE CERVIX TUMOR;

ALGORITHMS; DISEASE PROGRESSION; EVOLUTION, MOLECULAR; FEMALE; GENE DOSAGE; GENOMICS; HUMANS; MODELS, GENETIC; NEOPLASMS; PHYLOGENY; SOFTWARE; UTERINE CERVICAL NEOPLASMS;

EID: 84931026698     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btv233     Document Type: Conference Paper

References (38)

1. Bandelt H., et al. (1999). Median-joining networks for inferring intraspecific phylogenies. Mol. Biol. Evol., 16, 37-48
2. Beaumont M.A. (2010). Approximate Bayesian computation in evolution and ecology. Annu. Rev. Ecol. Evol. Syst., 41, 379-406
3. Beerenwinkel N., et al. (2015). Cancer evolution: mathematical models and computational inference. Syst. Biol., 64, e1-e25
4. Chowdhury S.A., et al. (2013). Phylogenetic analysis of multiprobe fluorescence in situ hybridization data from tumor cell populations. Bioinformatics, 29, i189-i198
5. Chowdhury S.A., et al. (2014). Algorithms to model single gene, single chromosome, and whole genome copy number changes jointly in tumor phylogenetics. PLoS Comp. Biol., 10, e1003740
6. Csurös, M. (2010). Count: evolutionary analysis of phylogenetic profiles with parsimony and likelihood. Bioinformatics, 26, 1910-1912
7. Dempster A.P., et al. (1977). Maximum likelihood from incomplete data via the EM algorithm. J. R. Stat. Soc. B, 39, 1-38
8. Desper R., et al. (1999). Inferring tree models of oncogenesis from comparative genomic hybridization data. J. Comput. Biol., 6, 37-51
9. Desper R., et al. (2000). Distance-based reconstruction of tree models for oncogenesis. J. Comput. Biol., 7, 789-803
10. Di Noia J. and Neuberger M. (2007). Molecular mechanisms of antibody somatic hypermutation. Annu. Rev. Biochem., 76, 1-22
11. Felsenstein J. (2004). Inferring Phylogenies. Sinauer Associates, Inc., Sunderland, MA
12. Fisher R., et al. (2013). Cancer heterogeneity: implications for targeted therapeutics. Br. J. Cancer, 108, 479-485
13. Greenman C.D., et al. (2010). Estimation of rearrangement phylogeny for cancer genomes. Genome Res., 22, 346-361
14. Greenblatt M.S., et al. (1994). Mutations in the p53 tumor suppressor gene: clues to cancer etiology and molecular pathogenesis. Cancer Res., 54, 4855-4878
15. Harris R., et al. (2002). RNA editing enzyme APOBEC1 and some of its homologs can act as DNA mutators. Mol. Cell, 10, 1247-1253
16. Heng H.H., et al. (2013). Chromosome instability (CIN): what it is and why it is crucial to cancer evolution. Cancer Metastasis Rev., 32, 325-340
17. Heselmeyer-Haddad K., et al. (2012). Single-cell genetic analysis of ductal carcinoma in situ and invasive breast cancer reveals enormous tumor heterogeneity, yet conserved genomic imbalances and gain of MYC during progression. Am. J. Pathol., 181, 1807-1822
18. Hjelm M., et al. (2006). New probabilistic network models and algorithms for oncogenesis. J. Comput. Biol., 13, 853-865
19. Karp R.M. (1971). A simple derivation of edmonds' algorithm for optimum branchings. Networks, 1, 265-272
20. Liu J., et al. (2009). Inferring progression models for CGH data. Bioinformatics, 25, 2208-2215
21. Loeb L.A. (1991). Mutator phenotype may be required for multistage carcinogenesis. Cancer Res., 51, 3075-3079
22. Martins F.C., et al. (2012). Evolutionary pathways in BRCA1-associated breast tumors. Cancer Discov., 2, 503-511
23. Marusyk A. and Polyak K. (2010). Tumor heterogeneity: causes and consequences. Biochim. Biophys. Acta (BBA) Rev. Cancer, 1805, 105-117
24. Navin N., et al. (2011). Tumour evolution inferred by single-cell sequencing. Nature, 472, 90-94
25. Newton M.A. (2002). Discovering combinations of genomic aberrations associated with cancer. J. Am. Stat. Assoc., 97, 931-942
26. Nowell P.C. (1976). The clonal evolution of tumor cell populations. Science, 194, 23-28
27. Pennington G., et al. (2007). Reconstructing tumor phylogenies from heterogeneous single-cell data. J. Bioinform. Comput. Biol., 5, 407-427
28. Petrova T.V., et al. (2008). Transcription factor PROX1 induces colon cancer progression by promoting the transition from benign to highly dysplastic phenotype. Cancer Cell, 13, 407-419
29. Purdom E., et al. (2013). Methods and challenges in timing chromosomal abnormalities within cancer samples. Bioinformatics, 29, 3113-3120
30. Snuderl M., et al. (2011). Mosaic amplification of multiple receptor tyrosine kinase genes in glioblastoma. Cancer Cell, 20, 810-817
31. Sotiropoulou N., et al. (2010). Tumour expression of lymphangiogenic growth factors but not lymphatic density is implicated in human cervical progression. Pathology, 42, 629-636
32. Sprouffske K., et al. (2011). Accurate reconstruction of the temporal order of mutations in neoplastic progression. Cancer Prev. Res., 4, 1135-1144
33. Szerlip N.J., et al. (2012). Intratumoral heterogeneity of receptor tyrosine kinases EGFR and PDGFRA amplification in glioblastoma defines subpopulations with distinct growth factor response. Proc. Natl Acad. Sci. U.S.A, 109, 3041-3046
34. Tarjan R.E. (1977). Finding optimum branchings. Networks, 7, 25-35
35. Timmermann B., et al. (2010). Somatic mutation profiles of MSI and MSS colorectal cancer identified by whole exome next generation sequencing and bioinformatics analysis. PLoS One, 5, e15661
36. Urbschat S., et al. (2011). Clonal cytogenetic progression within intratumorally heterogeneous meningiomas predicts tumor recurrence. Int. J. Oncol., 39, 1601-1608
37. Wang Y., et al. (2014). Clonal evolution in breast cancer revealed by single nucleus genome sequencing. Nature, 512, 155-160
38. Wangsa D., et al. (2009). Fluorescence in situ hybridization markers for prediction of cervical lymph node metastases. Am. J. Pathol., 175, 2637-2645