SUPPLEMENTARY: Epigenetic Silencing Mediated Through Activated PI3K/AKT Signaling in Breast Cancer Tao Zuo, Ta-Ming Liu, Xun Lan, Yu-I Weng, Rulong Shen, Fei Gu, Yi-Wen Huang, Sandya Liyanarachchi, Daniel E. Deatherage, Pei-Yin Hsu, Cenny Taslim, Bhuvaneswari Ramaswamy, Charles L. Shapiro, Huey-Jen L. Lin, Alfred S. L. Cheng, Victor X. Jin, and Tim H.-M. Huang 1 Table of Content: 1. Fig. S1. Elevated AKT1 kinase activity in myrAKT1- transfected MCF10A cells. ---------------------------------------------------------------------------------------------------- page 4 2. Fig. S2. Genome-wide view of H3K27me3 in mammary epithelial cells. ---------------------------------------------------------------------------------------------------- page 5 3. Fig. S3. Biological functions of PI3K/AKT- downstream genes. ----------------- page 6 4. Fig. S4. Genomic maps of 40 genes. ------------------------------------------------- page 8 5. Fig. S5. Comparing DNA methylation levels of four CpG islands measured by meDIP-qPCR and MassARRAY.------------------------------------------------------- page 11 6. Fig. S6. Validation of DNA methylation by MBDCap-seq.----------------------- page 13 7. Table S1. Summary of H3K27me3 ChIP-seq data ------------------------------ page 14 8. Table S2. Distribution of H3K27me3 in MCF10A genome ---------------------- page 14 9. Table S3. Genes (n=488) enriched with H3K27me3 and downregulated by PI3K/AKT- signaling ---------------------------------------------------------------------- page 15 10. Table S4. Genes (n=1005) enriched with H3K27me3 but without downregulation -------------------------------------------------------------------------------------------------- page 26 11. Table S5. Genes (n=723) downregulated by PI3K/AKT- but without enrichment of H3K27me3 ---------------------------------------------------------------------------------- page 45 2 12. Table S6. Summary of 21 breast cancer cell lines -------------------------------- page 60 13. Table S7. Summary of in silico expression values of 180 genes in 21 breast cancer lines and 4 normal human mammary epithelial samples (HMECs) -------------------------------------------------------------------------------------------------- page 62 14. Table S8. ChIP-qPCR of H3K27me3 in 21 breast cancer cell lines and 4 HMECs -------------------------------------------------------------------------------------------------- page 66 15. Table S9. meDIP-qPCR in 21 breast cancer lines, 4 HMECs and myrAKT1- or Vector transfected MCF10A cells ----------------------------------------------------- page 68 16. Table S10. PCR primers of 40 genes ------------------------------------------------ page 70 17. Table S11. Gene expression after drug treatment -------------------------------- page 71 18. Table S12. RT-PCR primers of 40 genes ------------------------------------------- page 75 19. Table S13. MassARRAY PCR primers of 4 genes -------------------------------- page 76 20. Table S14. Summary of MBDCap-seq data ---------------------------------------- page 76 21. Table S15. Differentially methylated genes (n=143) identified by MBDCap-seq analysis .-------------------------------------------------------------------------------------- page 76 22. Experimental procedures ---------------------------------------------------------------- page 79 23. Reference ----------------------------------------------------------------------------------- page 80 3 SUPPLEMENTAL DATA: Fig. S1. Elevated AKT1 kinase activity in myrAKT1- transfected MCF10A cells. AKT1 kinase activity increased 4-fold in myrAKT1- transfected MCF10A compared with vector control cells. 4 Fig. S2. Genome-wide view of H3K27me3 in mammary epithelial cells. Top 1% enrichment regions of H3K27me3 are indicated as bars in the figure, i.e., AKT1 (Red) and Vector (Green) transfected MCF10A. Disseminated bars were matched to corresponding locations at chromosome bands in each of 23 chromosomes in the human genome. H3K27me3 enrichment was identified by the ChIP-seq peak calling program, bin-base enrichment thresholds (BELT) algorithm (Frietze et al., 2010; Cited in main text), with a False Discovery Rate (FDR) less than 0.05. 5 Fig. S3. Biological functions of PI3K/AKT- downstream genes. Functional analyses were performed using IPA (Ingenuity Pathway Analysis) software. PI3K/AKT- downstream targets were divided into three sets according to their gene expression and H3K27me3 status shown in Figure1D. Then gene lists were uploaded to IPA for statistical analyses. Of 488 genes marked by H3K27me3 and downregulated by AKT1, 172 genes (Table S3) are related to cancer (p = 9.74 x 10−13), while p values are 8.55 x 10−3 (19 of 1005 genes, Table S4) and 2.05 x 10−9 (207 of 723 genes, Table S5) in other two groups respectively. As shown in figure, the y-axis indicates negative exponent of the p-value, the results of three categories are ordered parallel within each 6 function. 12 biological functions shown in figure are most significant ones derived from the analysis of 488 genes. 7 Figure S4 8 Figure S4 9 Figure S4 Fig. S4. Genomic maps of 40 genes. A total of 40 genes, as shown in Figure 3A, were subjected to meDIP- and ChIP-qPCR assays. As shown in the figure, genomic maps illustrate distribution of CpG sites (vertical bars) and locations of PCR primers (head-to-head arrows) around TSS region at each locus. 10 Figure S5 11 Fig. S5. Comparing DNA methylation levels of four CpG islands measured by meDIP-qPCR and MassARRAY . A, genomic maps show CpG islands at promoter regions of four genes, i.e., SFRP1, HOXA5, HOXA9, and SYNE2. Transcription start sites (TSSs) and locations of PCR primers were indicated in maps. B, DNA methylation levels of these 4 genes in 20 breast cancer cell lines and 4 normal breast epithelial cell samples (Fig.3 and 4) were assessed by meDIP-qPCR and MassARRAY, respectively. Pearson's correlation analysis was conducted to compare methylation levels measured by these two methods. The linear regression r-squared (r2) values were shown in figure. Methylation levels measured at the SYNE2 CpG island show the strongest correlation. 12 Figure S6 Fig. S6. Validation of DNA methylation by MBDCap-seq. Box plot represents DNA methylation of 180 loci identified in Fig. 2A. Two of loci were not found in the MBDCap-seq dataset. Methylation levels were assessed by MBDCap- seq in T-47D cells treated with DAC and/or LY294002. Significance of differences among drug treatments was determined by Student’s t-test. *P<0.05, **P<0.01. 13 a Table S1. Summary of H3K27me3 ChIP-seq data AKT1 Vector Subtracted Reads 40,585,026 27,308,019 - Mapped Reads 21,195,941 17,394,048 - Unique Mapped Reads 15,589,956 11,789,771 - Peaks (Top 1%) 12,113 9,743 11,577 Peaks (Top 2%) 27,688 19,229 20,656 Peaks (Top 10%) 130,709 130,075 122,727 Note: a) ChIP-Seq analysis is described in Experimental procedures. a Table S2. Distribution of H3K27me3 in MCF10A genome AKT1 Vector Subtracted Gene desert (>100-kb) 43,104 44,129 42,081 5' distal (-100 to -4-kb) 20,553 19,821 18,030 5' TSS (-4 to 2-kb) 7,485 7,232 6,154 Intragenic 39,454 39,237 39,050 3' end (<10-kb) 4,168 3,936 3,682 3' distal (>10-kb) 15,945 15,720 13,730 Total 130,709 130,075 122,727 Note: a) Genome-wide distribution of top 10% H3K27me3 peaks were shown in table. 14 Table S3. Genes (n=488) enriched with H3K27me3 and downregulated by PI3K/AKT signaling Expressio H3K27me3 Polycomb Gene b Affymetrix c d Cancer a Accession Chr. n folds peak targets in f Symbol (Strand) Prob_ID (AKT1 vs. (distance to e related ES cells Vector) TSS [bp]) A2ML1 NM_144670 12(+) 1564307_a_at -9.83 1950 ABCA12 NM_173076 2(-) 215465_at -25.70 1838 ABCA5 NM_018672 17(-) 213353_at -3.59 1223 Yes Yes ABCA8 NM_007168 17(-) 204719_at -6.52 1265 Yes Yes ABCC2 NM_000392 10(+) 206155_at -4.06 -1454 Yes ABHD4 NM_022060 14(+) 218581_at -1.90 1637 NM_001003 ABLIM1 10(-) 200965_s_at -1.78 1172 408 ACACB NM_001093 12(+) 49452_at -4.09 -715 ACPL2 NM_152282 3(+) 226925_at -4.11 -1331 Yes ADD3 NM_016824 10(+) 201753_s_at -3.66 -1176 Yes ADRB2 NM_000024 5(+) 206170_at -1.76 1660 Yes Yes AFTPH NM_203437 2(+) 222472_at -1.58 -395 AGA NM_000027 4(-) 204333_s_at -1.63 918 AGPAT4 NM_020133 6(-) 228667_at -2.70 1924 AKR1C3 NM_003739 10(+) 209160_at -1.75 1127 Yes NM_001031 ALDH3A2 17(+) 202054_s_at -1.74 507 806 ALOX5AP NM_001629 13(+) 204174_at -2.41 -1493 AMOTL1 NM_130847 11(+) 225450_at -1.71 1221 AMY2B NM_020978 1(+) 228023_x_at -1.71 -590 Yes ► ANKRA2 NM_023039 5(-) 218769_s_at -1.85 -716 ANKRD38 NM_181712 1(-) 229125_at -3.83 -1945 Yes ANXA3 NM_005139 4(+) 209369_at -2.23 -63 AP1M2 NM_005498 19(-) 65517_at -4.80 957 ARHGAP29 NM_004815 1(-) 1558280_s_at -4.70 867 Yes ARHGAP8 NM_181335 22(+) 37117_at -7.57 -362 Yes ARL6IP NM_015161 16(-) 211935_at -2.21 1448 Yes ARRDC3 NM_020801 5(-) 224797_at -2.72 1410 ASAH1 NM_004315 8(-) 213702_x_at -1.55 -1898 Yes ASPM NM_018136 1(-) 219918_s_at -2.57 -247 ASS1 NM_000050 9(+) 207076_s_at -3.78 -905 Yes ATP9A NM_006045 20(-) 212062_at -11.16 -1497 ATXN1 NM_000332 6(-) 203232_s_at -5.25 533 ► AUH NM_001698 9(-) 205052_at -1.76 1882 AYTL1 NM_017839 16(+) 227889_at -1.81 -1716 B3GALTL NM_194318 13(+) 227083_at -1.50 -568 BAMBI NM_012342 10(+) 203304_at -2.86 -1594 Yes Yes BBX NM_020235 3(+) 223135_s_at -1.60 -1856 BDH2 NM_020139 4(-) 218285_s_at -1.74 1924 NM_001007 BRWD1 21(-) 231960_at -1.62 413 246 BSDC1 NM_018045 1(-) 218004_at -1.75 -247 BTG1 NM_001731 12(-) 200920_s_at -1.73 -134 ► BTG2 NM_006763 1(+) 201236_s_at -1.61 1429 Yes Yes 15 BTN3A3 NM_006994 6(+) 204821_at -3.08 1504 C10orf58 NM_032333 10(+)