Elucidating the altered transcriptional programs in breast cancer using independent component analysis.
The quantity of mRNA transcripts in a cell is determined by a complex interplay of cooperative and counteracting biological processes. Independent Component Analysis (ICA) is one of a few number of unsupervised algorithms that have been applied to microarray gene expression data in an attempt to understand phenotype differences in terms of changes in the activation/inhibition patterns of biological pathways. While the ICA model has been shown to outperform other linear representations of the data such as Principal Components Analysis (PCA), a validation using explicit pathway and regulatory element information has not yet been performed. We apply a range of popular ICA algorithms to six of the largest microarray cancer datasets and use pathway-knowledge and regulatory-element databases for validation. We show that ICA outperforms PCA and clustering-based methods in that ICA components map closer to known cancer-related pathways, regulatory modules, and cancer phenotypes. Furthermore, we identify cancer signalling and oncogenic pathways and regulatory modules that play a prominent role in breast cancer and relate the differential activation patterns of these to breast cancer phenotypes. Importantly, we find novel associations linking immune response and epithelial-mesenchymal transition pathways with estrogen receptor status and histological grade, respectively. In addition, we find associations linking the activity levels of biological pathways and transcription factors (NF1 and NFAT) with clinical outcome in breast cancer. ICA provides a framework for a more biologically relevant interpretation of genomewide transcriptomic data. Adopting ICA as the analysis tool of choice will help understand the phenotype-pathway relationship and thus help elucidate the molecular taxonomy of heterogeneous cancers and of other complex genetic diseases.
Teschendorff
Andrew E
AE
Breast Cancer Functional Genomics Laboratory, Cancer Research UK Cambridge Research Institute, Cambridge, United Kingdom. aet21@cam.ac.uk
Journée
Michel
M
Absil
Pierre A
PA
Sepulchre
Rodolphe
R
Caldas
Carlos
C
D000222:Adaptation, Physiological / Q000502:physiology; D000465:Algorithms; D001943:Breast Neoplasms / Q000235:genetics*; D020869:Gene Expression Profiling / Q000379:methods*; D015972:Gene Expression Regulation, Neoplastic / Q000235:genetics; D006801:Humans; D008957:Models, Genetic; D009363:Neoplasm Proteins / Q000235:genetics*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods; D025341:Principal Component Analysis; D015398:Signal Transduction / Q000235:genetics*; D014158:Transcription, Genetic / Q000235:genetics*
D009363:Neoplasm Proteins
Mol Biol Rep. 1999 Dec;26(4):223-30
10634504
Oncogene. 2007 Mar 1;26(10):1507-16
16936776
Nature. 2000 Aug 17;406(6797):747-52
10963602
Bioinformatics. 2002 Jan;18(1):51-60
11836211
Proc Natl Acad Sci U S A. 2002 Oct 1;99(20):12963-8
12297621
Bioinformatics. 2002 Dec;18(12):1617-24
12490446
N Engl J Med. 2002 Dec 19;347(25):1999-2009
12490681
Proc Natl Acad Sci U S A. 2003 Mar 18;100(6):3351-6
12631705
Mol Biol Cell. 2003 Aug;14(8):3208-15
12925757
Proc Natl Acad Sci U S A. 2003 Sep 2;100(18):10393-8
12917485
Oncogene. 2003 Oct 16;22(46):7155-69
14562044
Genome Biol. 2003;4(11):R76
14611662
Proc Natl Acad Sci U S A. 2003 Nov 11;100(23):13418-23
14593198
Proc Natl Acad Sci U S A. 2003 Dec 23;100(26):15522-7
14673099
Comput Biol Chem. 2004 Feb;28(1):3-10
15022635
Proc Natl Acad Sci U S A. 2004 Jun 22;101(25):9309-14
15184677
Oncogene. 2004 Aug 26;23(39):6677-83
15247901
Nat Genet. 2004 Oct;36(10):1090-8
15448693
Oncogene. 2004 Oct 28;23(50):8238-46
15378019
Adv Immunol. 1997;64:65-104
9100980
Proc Natl Acad Sci U S A. 1998 Dec 8;95(25):14863-8
9843981
Neural Comput. 1999 Jan 1;11(1):157-92
9950728
Oncogene. 2004 Nov 18;23(54):8743-55
15467738
Br J Cancer. 2004 Nov 29;91(11):1924-30
15558074
J Comput Biol. 2004;11(6):1090-109
15662200
Nat Genet. 2000 May;25(1):25-9
10802651
Oncogene. 2007 Sep 27;26(44):6420-30
17452973
Lancet. 2005 Feb 19-25;365(9460):671-9
15721472
Nature. 2005 Mar 17;434(7031):338-45
15735639
Nat Genet. 2005 Jun;37(6):579-83
15920519
Bioinformatics. 2005 Jul 1;21(13):3025-33
15860564
Proc Natl Acad Sci U S A. 2005 Oct 25;102(43):15545-50
16199517
Eur J Hum Genet. 2005 Dec;13(12):1303-11
16205741
Mol Cell. 2005 Nov 23;20(4):539-50
16307918
Int J Oncol. 2006 Jan;28(1):67-76
16327981
Nature. 2006 Jan 19;439(7074):353-7
16273092
J Natl Cancer Inst. 2006 Feb 15;98(4):262-72
16478745
Eur J Cancer. 2006 Mar;42(4):485-91
16380248
Oncogene. 2006 Apr 6;25(15):2273-84
16288205
BMC Bioinformatics. 2006;7:175
16569230
J Biol Chem. 2006 May 5;281(18):12210-7
16505480
N Engl J Med. 2006 Jun 8;354(23):2419-30
16760442
Arch Immunol Ther Exp (Warsz). 2006 May-Jun;54(3):149-63
16652219
Mol Cell Biol. 2006 Aug;26(16):6024-36
16880514
Bioinformatics. 2006 Aug 1;22(15):1855-62
16709589
BMC Bioinformatics. 2006;7:290
16762055
Clin Cancer Res. 2006 Oct 1;12(19):5641-7
17000652
Oncogene. 2006 Oct 30;25(51):6758-80
17072327
Mol Cancer. 2006;5(1):55
17081305
Nat Genet. 2006 Dec;38(12):1386-96
17099711
Nat Genet. 2007 Jan;39(1):41-51
17173048
Genome Biol. 2006;7(10):R93
17044931
Genome Biol. 2006;7(10):R101
17076897
J Med Genet. 2007 Aug;44(8):481-4
17369502