Considering positional bias in regulatory motifs of genes associated with breast cancer

1. Considering positional bias in regulatory motifs of genes associated with breast cancer Nathaniel Gustafson Dr. Garry Larson (City of Hope)

2. Cancer Studies • Can we tie genetic variation (eg. SNPs) to Cancer Risk? • Myriad Genetics found BrCa1 and BrCa2 • Mutations in BrCa1/2 tied to 800% increase in breast cancer risk • Most research is on exonic regions • Changes protein composition http://members.cox.net/amgough/Fanconi-genetics-genetics-primer.htm

3. Our approach • What about regulatory regions? • Motif: • Recurring sequence, usu. 6-20 bp. • Generally functional • Hypothesis: Regulatory motifs upstream of the transcriptional start site (TSS) may play some role in breast cancer ATG stop 5` 3` 5` - upstream

4. Mutation G A C C T T C T A C A BrCa Pt. G A C C T A C T A C A G A G C T A C T A C T ~5 myr G A C T T A A T T C A ~70 myr Sequence phylogeny G A GC T A C - A G A ~300 myr ~475 myr G A GT T A A T GGT Orthologous bases: identical by descent Disease Mutations in Phylogenetically Conserved Motifs Nonorthologous Bases in red

5. Background • Meta-Analysis pools several brca ER+/-* studies • Statistics used to find genes that have consistent differences in expression levels in ER+ vs ER- cell lines *ER = Estrogen Receptor – a common way of classifying breast cancer cells

6. GCCATnTT x 9 GCCATnTT x 50

7. Aims • Investigate regulatory motifs for these genes • Compare occurrences of each motif across gene sets • Hypothesis: genes overexpressed in the same tumor type share motifs

8. Weak Results

9. Are we missing the signal? • Old counting method ER+ < ER- gene set motif occurrences ER+ > ER- gene set motif occurrences -2000 -1500 -1000 -500 TSS -2000 -1500 -1000 -500 TSS 15 10 P-val: .30 NOT significant

10. Are we missing the signal? • New counting method: use position bias ER+ < ER- gene set motif occurrences ER+ > ER- gene set motif occurrences -2000 -1500 -1000 -500 TSS -2000 -1500 -1000 -500 TSS 12 3 P-val: .03 significant

11. Tools • Perl • Handy scripting language • Great for parsing textual data • mySQL • Storage and retrieval of structured data www.yusoft.net/yu-graph/main/logo-mysql.jpg

12. Problems • Lack of data specificity • What do Xie’s pos. biases mean? • Insufficient data • Needed position of motif relative to TSS • Improperly annotated data • Position shown to be inconsistent • Collaboration • Norway is about 10 time zones away

13. Results • Reading 100 bp from positional bias • No window (Previous results)

14. Any SNPs in this motif? • One SNP was found from HapMap in this motif • But it was at a degenerate position (eg. Y = C or G) = still satisfied the motif • Might still affect expression

15. Biological Significance • SCGGAAGY found more in ER+ overexpressed genes • Known as a binding site for ELK-1 • Might provide some insight into ER+/ER- cell differentiation • Verification in vivo remains to be done

16. 3’UTR Motif List -6/7mer miRNA seeds -Phylogenetic conser. motifs HapMap BrCa GWAS Datasets SNP_list BrCa Somatic Mutations (Sjöblom) Hunter, et al (CGEMS) Linkage Studies in BrCa (Smith, et al.) Gold, et al. (MSKCC) LD Mapping Proxy SNPs SNPs Rank & Biological Testing LOH (aCGH) in BrCa Easton, et al.(UK) (unavailable) Stacey (deCode) (unavailable) In-House Independent Association Studies Thermodynamic Profiling (STarMir, PITA) Evolutionary Conser- vation (miRNA seeds) 3’UTR-luc Fusion Assay Allele frequency in HapMap Population(s) Additional Biological Testing Reciprocal Allelic testing-no effect Reciprocal Allelic Testing-Effect

17. GWAS • “Genome Wide Association Study” • Genotypes cases and controls at thousands of loci • Intended to be an unbiased approach • Potentially identifies pertinent mutations http://www2.bioinformatics.tll.org.sg/img/species/karyotype_Homo_sapiens.png

18. BrCa GWAS Datasets

19. BrCa GWAS Datasets YES

20. Bring this... SM70 SG74 LF52 SM17 SH14 L5721 SM56 SF63 L5957 L5349 L5420 L5713 SH5 LF48 SJG4 L6029 SG21 L5352 L6121 SG69 L5952 SM78 SM113 SF23 L5573 SN6 SF1 SM91 L5895 L5518 L5501 L5328 L5772 SG08 SG28 SM52 SM106 SM67 L5463 L5494 SA17 L5796 L6014 SN15 rs2180341 chr6 127642323 + ncbi_b35 MSKCCOffit AffyEAv3 PhaseIGold_et_al TT TT TT CT CT CC TT CT TT TTTTTT CT TT CT TT CT TT TT CT TT TTTT CT CTCTCTCTCT CT TT CT CT TT TT CT CC TT TT CT TT TT CT TT CT CTCTCT TT TTTT CT CTCT TT TT CT TT TTTTTTTTTT CT TT TTTTTT CT TT TT CT TT TTTT CT CT TT CT CT TT CT TT ... rs6569480 chr6 127663441 + ncbi_b35 MSKCCOffit AffyEAv3 PhaseIGold_et_al GG GG GG GG AG AA GG AG GG GGGGGG AG GG GGGG AG GG GG AG GG GGGG AG AGAGAGAGAG AG GG AG AG GG GG AG AA GG GG AG GG GG AG GG AG AGAGAG GG GGGG AG AGAG GG GG AG GG GG NN GG GGGG AG GG GGGGGG AG GG GG AG GG GGGG AG GG GG AG AG GG AG GG ... To this...

21. Future Work • We’ve digested the Gold data set • Employ this in the triage for producing a gene list • Combine with other triage methods to find the most interesting genes • Test these in vivo

22. Special Thanks Funding • Dr. Garry Larson • SoCalBSI program • SoCalBSI mentors • City of Hope • Komen for the Cure • National Science Foundation • National Institute of Health • Employment and Workforce Development

23. References • XieX, Mikkelsen TS, Gnirke A, Lindblad-Toh K, Kellis M, Lander ES. Systematic discovery of regulatory motifs in conserved regions of the human genome, including thousands of CTCF insulator sites. Proc NatlAcadSci U S A. 2007 Apr 24;104(17):7145-50. • D. Smith, P. Sætrom, O. SnøveJr, C. Lundberg, G. Rivas, C. Glackin and G. Larson. Meta-analysis of breast cancer microarray studies in conjunction with conserved cis-elements suggest patterns for coordinate regulation. BMC Bioinformatics 2008, 9:63