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1 Supplementary information for Aberrant luminal progenitors as the candidate target population for basal tumor development in BRCA1 mutation carriers Elgene Lim, François Vaillant, Di Wu, Natasha C Forrest, Bhupinder Pal, Adam H Hart, Marie-Liesse Asselin-Labat, David E Gyorki, Teresa Ward, Audrey Partanen, Frank Feleppa, Lily I Huschtscha, Heather J Thorne, kconfab, Stephen B Fox, Max Yan, Juliet D French, Melissa A Brown, Gordon K Smyth, Jane E Visvader, Geoffrey J Lindeman

2 Supplementary Methods and References Microarray data analysis: cell subpopulations Microarray profiling was undertaken for four cell subpopulations (identified as MaSCenriched, Lum Prog, Mat Lum and Stroma) from three patients. Data analysis used the lumi and limma packages of the Bioconductor open-source software project ( Raw intensities were normexp background corrected with offset 16 1, quantile normalized 2 then log 2 -transformed. Probes were filtered if not detected in any sample (detection P-value.1). A linear model was fitted to the expression data including random effects for the three patients 3. Pairwise comparisons were made between the three cell populations other than Stroma using empirical Bayes moderated t-statistics 4. The false discovery rate (FDR) was controlled globally using the Benjamini and Hochberg algorithm. Probes with FDR <.5 and fold-change > 2 were judged to be differentially expressed. Microarray data analysis: breast tissue Microarray profiles were available for breast tissue from 36 individuals (13 with BRCA1 mutations, 12 normal controls, and 11 non-brca1/2 individuals defined as not having BRCA1 or BRCA2 mutations but with a strong family history of breast cancer). Normalization and probe filtering was as for the cell population arrays. Sample quality was assessed in three ways using the expression profile data. First, samples were checked for cytokeratin gene expression levels as a marker for epithelium tissue. Fifteen samples (6 BRCA1, 3 non-brca1/2 and 6 normal) were removed because two or more cytokeratin genes (KRT5, KRT8, KRT14, KRT18, KRT19 or KRT72) lacked detectable expression (BeadStudio detection P-value.1). Second, the normal samples were examined for atypical individuals, and one more normal sample was removed because it showed an expression profile unlike any of the other individuals. This left 2 samples (seven BRCA1, five normal controls, and eight non-brca1/2) which passed our quality filters. Third, empirical array quality weights were estimated using the method of Ritchie et al 5. A linear model, incorporating the array weights, was fitted to the expression data. Differential expression between the BRCA1 and normal groups was assessed using empirical Bayes moderated t-statistics 4. 2

3 Microarray data analysis: breast tumors Expression profiles of human breast tumors were downloaded from GEO series GSE3165 ( In order to standardize on one microarray platform, only the 94 arrays of platform GPL887 (Agilent Human 1A Microarray V2) were included in the analysis. The samples and arrays are described by Herschkowitz et al 6. Associated clinical data was downloaded from the UNC Microarray Database ( The clinical data included the Singe Sample Predictor Subtypes assigned by Hu et al 7 and Claudin-low sample designations assigned by Herschkowitz et al 6 by clustering (Table S3). Data analysis used the raw Agilent Feature Extraction data files and probe annotation from GEO. Control probes were filtered, then expression values were normexp background corrected with offset 2 1, then log-ratios were global loess normalized 8. A linear model was fitted to the expression data, and empirical Bayes moderated t-statistics were computed for all pair-wise comparisons between the six cancer subtypes 4. Subpopulation expression signatures The cell subpopulation microarray data was used to identify a set of signature probes whose expression, or lack of expression, characterizes each of the three cell subpopulations (MaSCenriched, luminal progenitor and mature luminal). For each subpopulation, signature probes were defined as those which were significantly differentially expressed in the same direction versus both of the other two cell subpopulations (Table S4). Each signature gene was then associated with an average log-fold change x g as a measure of its discriminatory strength, defined as the average log 2 -fold change for that probe versus the other two cell populations. For each breast sample (tissue or tumor), an expression signature score was computed to measure concordance of that sample with each cell subpopulation. Higher scores indicate that the expression signature of the cell subpopulation is found in the breast sample. Expression signature scores are defined as weighted averages, s! g =! g x y g x g g 3

4 where the sum is over genes in the signature set, x g is the average log 2 -fold-change for that gene from the cell population data and y g is log 2 -expression for the same gene in the breast tissue sample. In computing the signatures scores, only one representative Illumina probe and one representative Agilent probe was used for each signature gene. Signature probes without a gene symbol were discarded and, for each gene symbol, only the probe with highest average expression level was retained. Mean-rank gene set enrichment tests 9 were used to assess the rankings of the signature probes in the various differential expression analyses described above, i.e., between the tumor subtypes for the cancer samples and between the BRCA1 mutation and normal groups for the breast tissue. One-sided P-values were evaluated (by Wilcoxon s method) for the mean-rank of each up-regulated or down-regulated signature set under random permutation of probes. Limiting dilution analysis Repopulating frequencies were calculated using the limdil webtool ( as described 1. Statistical tests P-values in Fig. 3 are two-sided t-tests (common variance) and P-values in Fig. 4 are two-sided Wilcoxon tests. References 1. Ritchie, M.E., et al. A comparison of background correction methods for two-colour microarrays. Bioinformatics 23, (27). 2. Bolstad, B.M., Irizarry, R.A., Astrand, M. & Speed, T.P. A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics 19, (23). 3. Smyth, G.K., Michaud, J. & Scott, H.S. Use of within-array replicate spots for assessing differential expression in microarray experiments. Bioinformatics 21, (25). 4. Smyth, G.K. Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Stat Appl Genet Mol Biol 3, Article3 (24). 4

5 5. Ritchie, M.E., et al. Empirical array quality weights in the analysis of microarray data. BMC Bioinformatics 7, 261 (26). 6. Herschkowitz, J.I., et al. Identification of conserved gene expression features between murine mammary carcinoma models and human breast tumors. Genome Biol 8, R76 (27). 7. Hu, Z., et al. The molecular portraits of breast tumors are conserved across microarray platforms. BMC Genomics 7, 96 (26). 8. Smyth, G.K. & Speed, T. Normalization of cdna microarray data. Methods 31, (23). 9. Michaud, J., et al. Integrative analysis of RUNX1 downstream pathways and target genes. BMC Genomics 9, 363 (28). 1. Hu, Y. & Smyth, G.K. ELDA: Extreme limiting dilution analysis for comparing depleted and enriched populations in stem cell and other assays. J Immunol Methods Epub 27 June (29). 5

6 Supplementary Table 1. Limiting dilution analysis of Lin subpopulations CD49f EpCAM CD49f EpCAM + CD49f + EpCAM + CD49f hi EpCAM Dose Outgrowth* Dose Outgrowth* Dose Outgrowth* Dose Outgrowth* 28, 48, 67, /4 /3 8, 15,5 16,5 2, 25, 26, 5, 1, /1 /3 13, 15, 16,8 3, 35, 67, 75, 1, /3 /3 2,5 25, 26, 27,5 33, 1, 3/4 3/4 2/2 2/4 1/2 8/8 LD < 1 in 136,5 < 1 in 175, < 1 in 269, 1 in 21,5 (CI: 1 in 38, 1 in 12,) Normal human mammary cells sorted from the Lin gate (Fig. 1b) were injected at the indicated ( ) number (based on machine counts) into cleared mammary fat pads (MFPs), together with 5, htert fibroblasts, as described in the Methods. MFPs were analysed and the mammary repopulating frequency was calculated by limiting dilution analysis as described in Supplementary Methods. Data are pooled from six independent experiments. *Shown as number of outgrowths per number of injected MFPs. Limiting Dilution (CI, 95% Confidence Interval). 6

7 Supplementary Table 2. Classification of pathogenic BRCA1 mutations in prophylactic mastectomy samples Patient ID Age (yrs) BIC Classification* HGVS Classification^ FACs Analysis/Sort Matrigel: B27 independence _3348 del AG (STOP 184) BRCA1c.3228_3229delAG (p.arg176argfs) CD49f,EpCAM Yes _2677 ins A (STOP 92) BRCA1c.2558dupA (p.asp853glufsx5) CD49f,EpCAM Yes C>T (R1443X) BRCA1c.4327C>T (p.arg1443x) CD49f,EpCAM Yes C>T (R1835X) BRCA1c.553C>T (p.arg1835x) CD49f,EpCAM Yes _232 del 14 BRCA1c.2188_221del14 (p.glu73thrfsx5) CD49f,EpCAM Yes T>G (C61G) BRCA1c.181T>G (p.cys61gly) CD49f,EpCAM NA del G (STOP 764) BRCA1c.2269delG (p.val757phefsx8) CD49f,EpCAM NA _918 del TT (STOP 285) BRCA1c.798_799delTT (p.ser267lysfsx19) CD49f,EpCAM NA del GAAA (STOP 7) BRCA1c.1953_1956delGAAA (p.lys653serfsx47) CD49f,EpCAM NA del A (STOP 7) BRCA1c.1961delA (p.lys654serfxx47) CD49f,EpCAM No del C (STOP 233) BRCA1c.52delC (p.gln174lysfsx6) CD49f,EpCAM Yes del exon 3 BRCA1g ?_138+?del (del exon3) CD49f,EpCAM Yes _4187 del TCAA (STOP 1364) BRCA1c delTCAA (p.asn1355lysfsx1) CD49f,EpCAM NA _2777 del CT (STOP 91) BRCA1c.2657_2658delCT (p.ser886cysfsx16) CD49f,CD24,CD133 Yes _1333 del 4 (STOP 397) BRCA1c.1175_1214del4 (p.leu392glnfsx5) CD49f,CD24,CD133 Yes _1333 del 4 (STOP 397) BRCA1c del4 (p.leu392glnfsx5) CD49f,CD24,CD133 Yes _5383 ins C (STOP 1829) BRCA1c.5266dupC (p.gln1756profsx74) Lin - only Yes G>T (E1134X) BRCA1c.34G>T (p.glu1134x) Lin - only Yes _5383 ins C (STOP 1829) BRCA1c.5266dupC (p.gln1756profsx74) Lin - only Yes C>T (R1835X) BRCA1c.553C>T (p.arg1835x) Lin - only Yes * BIC; An Open Access On-Line Breast Cancer Mutation Data Base. ^ HGVS; Human Genome Variation Society. All CD49f,EpCAM sorted samples from patients < 5 yrs were included in Fig. 3b. NA Not applicable; no Matrigel experiment performed. 7

8 Supplementary Table 3. Number of samples for each breast tumor subtype. Cancer subtype Number of samples Basal-like 33 Claudin-low 5 HER2+/ER 14 Luminal A 23 Luminal B 14 Normal breast-like 5 Total 94 The datasets for tumor subgroups are from Herschkowitz et al, Genome Biol 8, R76 (27). 8

9 Supplementary Table 4. Number of probes and unique genes in each subpopulation signature set. Cell subpopulation Down-regulated signature probes (genes) Up-regulated signature probes (genes) MaSC-enriched 1113 (942) 1186 (942) Luminal progenitor 28 (179) 437 (358) Mature luminal 322 (257) 77 (562) Brackets refer to the number of unique genes represented by the probes. 9

10 a CD14b + CD14b EpCAM b CD49f CD49f EpCAM + CD49f + EpCAM CD49f EpCAM 183 CD49f hi EpCAM CD c 23 CD49f EpCAM + CD49f + EpCAM CD49f EpCAM 49 CD49f hi EpCAM CD Supplementary Figure 1. Characterisation of human mammary cell subpopulations defined by CD49f and EpCAM. (a) Depletion of the CD49f EpCAM population by the fibroblast-specific marker CD14b (PDGFR β). A single cell suspension was prepared either in the absence (left panel) or presence (right panel) of anti-cd14b. The proportion of CD49f EpCAM cells was noted to be variable, consistent with the variation in stromal tissue that occurs between individuals. (b and c) CD133 and CD24 are differentially expressed in the four populations defined by CD49f and EpCAM. Cells co-stained with either anti-cd133 (b) or anti-cd24 (c). The expression of the marker is shown for each population with the shaded profiles depicting isotype controls.

a H&E b CK8/18 p63 Vim Supplementary Figure 2.

when transplanted into de-epithelialized mammary fat pads of

(a) H&E section of an outgrowth, eight weeks following

reduction mammoplasty from a 41 year-old woman, admixed with 5,

The image represents a composite of two contiguous fields.

11 a H&E b CK8/18 p63 Vim Supplementary Figure 2. Orthotopic xenotransplantation of Lin cells gives rise to outgrowths when transplanted into de-epithelialized mammary fat pads of NOD-SCID Il2rg / mice. (a) H&E section of an outgrowth, eight weeks following transplantation of 25, CD45 CD235a CD31 (Lin ) cells derived from a reduction mammoplasty from a 41 year-old woman, admixed with 5, htert-immortalized breast stromal fibroblasts. The image represents a composite of two contiguous fields. Scale bar, 1 µm. (b) Sections were stained with antibodies against cytokeratin-8/18, p63 and vimentin. Scale bars, 1 µm. Arrows indicate human fibroblasts stained with a human-specific antibody.

CK8/18 p63 Vim CK14 Supplementary Figure 3.

A single cell suspension was prepared from mammary fat pads eight weeks following

Each was secondarily transplanted into multiple cleared fat pads.

1/6 and 2/6 fat pads; BRCA1 tissue, 2/4 fat pads).

12 CK8/18 p63 Vim CK14 Supplementary Figure 3. CD49f hi EpCAM cells have limited self-renewing activity. A single cell suspension was prepared from mammary fat pads eight weeks following primary transplantation of CD49f hi EpCAM cells. Each was secondarily transplanted into multiple cleared fat pads. Only occasional secondary mammary epithelial structures were observed (normal tissue, 1/6 and 2/6 fat pads; BRCA1 tissue, 2/4 fat pads). The human secondary outgrowth depicted is from a BRCA1 mutation carrier. Sections were stained with antibodies against cytokeratin-8/18, vimentin, p63 and cytokeratin-14. Staining for cytokeratin-8/18 and vimentin (both human-specific) proved donor origin. Scale bars, 5 µm.

Percentage of total colonies stained 1 8 6 4 2 Normal BRCA1-mut p63 CK14 CK5/6 CK8/18 p63 CK14 CK5/6 CK8/18 CD49f hi EpCAM CD49f+EpCAM+ Supplementary Figure 4.

13 Percentage of total colonies stained Normal BRCA1-mut p63 CK14 CK5/6 CK8/18 p63 CK14 CK5/6 CK8/18 CD49f hi EpCAM CD49f+EpCAM+ Supplementary Figure 4. Expression of lineage markers in Matrigel-derived colonies. Cells from CD49f hi EpCAM and CD49f + EpCAM + subpopulations derived from BRCA1 mutationassociated and normal breast tissue were cultured in Matrigel in the presence of B27 supplement (14 d), fixed and then immunostained with antibodies against p63, cytokeratin-14, cytokeratin- 5/6 and cytokeratin-8/18. Data represent mean ± s.e.m. A minimum of three experiments was performed for each antibody.

a Littermate Control MMTV-cre- Brca1 f/f B27 + B27 b Colonies (per 1, cells) 16 14 12 1 8 6 4 2 + B27

Murine luminal progenitor cells from Brca1-deficient mammary glands exhibit B27 factor-independent

(a) Sorted luminal progenitor cells (CD29 lo CD24 + CD61 + ) from control and MMTV-cre-Brca1 f/f

14 a Littermate Control MMTV-cre- Brca1 f/f B27 + B27 b Colonies (per 1, cells) B27 B27 Littermate Control (n = 6) MMTV-cre- Brca1 f/f (n = 6) Supplementary Figure 5. Murine luminal progenitor cells from Brca1-deficient mammary glands exhibit B27 factor-independent growth. (a) Sorted luminal progenitor cells (CD29 lo CD24 + CD61 + ) from control and MMTV-cre-Brca1 f/f mammary glands were embedded in Matrigel and cultured for 14 d in media with or without B27 supplement. Scale bars,.5 mm. (b) Bar chart depicting the colony forming ability of luminal progenitor cells from mouse mammary glands of littermate control (n = 6) or MMTV-cre Brca1 f/f (n = 6) in Matrigel (1, cells in 2 µl) and cultured for 14 d in media with (black bars) or without (white bars) B27 supplement. Data represent mean ± s.e.m.

15 CD49f EpCAM CD49f EpCAM+ CD49f+EpCAM+ CD49fhiEpCAM PgR CK5/6 CD49f EpCAM CD49f EpCAM+ CD49f+EpCAM+ CD49fhiEpCAM PgR CK5/6 1.2 ±.2 % 31.7 ± 14.6 % 5.4 ±.1 % 2.1 ±.1 % 3.1 ±.3 % 39.7 ± 8.6 % 46.9 ± 23.6 % 63. ± 16.7 % Supplementary Figure 6. Immunohistochemical analysis of Lin subpopulations defined by CD49f and EpCAM, isolated from prophylactic mastectomies from BRCA1 mutation carriers. Cells were sorted (at > 9% purity) and cytospun for immunohistochemical staining. A minimum of three independent samples were evaluated by immunostaining using the indicated antibodies. Data represents mean ± s.e.m. Scale bars, 5 µm.

a b 14 12 1 8 6 CD49f + CD49f hi EpCAM + CD49f EpCAM + EpCAM CD49f EpCAM 2 4 c 2. 1.5 Dimension 2 1..5 -.5-1. -2-1 1 2 Dimension 1 Supplementary Figure 7.

16 a b CD49f + CD49f hi EpCAM + CD49f EpCAM + EpCAM CD49f EpCAM 2 4 c Dimension Dimension 1 Supplementary Figure 7. The human mammary cell subpopulations defined by CD49f and EpCAM have distinct gene expression profiles. (a) Hierarchical clustering and heatmap of the 5 genes most variable between the MaSC-enriched (CD49f hi EpCAM ), luminal progenitor (CD49f + EpCAM + ), mature luminal (CD49f EpCAM + ) and stromal (CD49f EpCAM ) mammary cell subpopulations. (b) Color key and histogram of log 2 -expression of the genes in the heatmap. (c) Multidimension scaling plot showing clear separation of the MaSC-enriched (hms), luminal progenitor (hpl), mature luminal (hml) and stromal (hstr) subpopulations.

P value: Basal Normal.25 < 1 6 Basal Claudinlow < 1 6 < 1 4 Basal ERBB2 < 1 6 < 1 6 Basal Lum B < 1 6 < 1 6 Basal Lum A < 1 6 < 1 6 Upregulated Downregulated Supplementary Figure 8.

17 P value: Basal Normal.25 < 1 6 Basal Claudinlow < 1 6 < 1 4 Basal ERBB2 < 1 6 < 1 6 Basal Lum B < 1 6 < 1 6 Basal Lum A < 1 6 < 1 6 Upregulated Downregulated Supplementary Figure 8. Barcode plots demonstrating the ability of luminal progenitor signature genes to distinguish basal-like, normal breast-like, claudin-low, ERBB2, luminal A and luminal B subtypes of breast cancer, with corresponding one-sided mean-rank gene set test P-values. Red bars designate upregulated signature genes while blue bars designate downregulated signature genes.

a CD49f EpCAM CD49f EpCAM+ CD49f+EpCAM+ CD49fhiEpCAM

5 ± 1.6 % 5.6 ± 2.4 % 12.7 ± 6.2 % 73.2 ± 11. % 6.2 ± 2.

Total Duct TDLU BRCA1- associated basal tumor 11 (52.

6) 21 c BRCA1- associated non-basal tumor 2 (33.

4) 7 BRCA1 tumor non-brca1/2 tumor Supplementary Figure

luminal progenitor cells and BRCA1-associated tumors.

Lin subpopulations defined by CD49f and EpCAM.

panel shows preneoplastic tissue from BRCA1 mutation

Data represents mean percentage of c-kitpositive cells

(b) Heterogeneous c-kit staining of luminal cells in a

BRCA1-associated and non-brca1/2 breast tumors.

18 a CD49f EpCAM CD49f EpCAM+ CD49f+EpCAM+ CD49fhiEpCAM BRCA1-mut Wild-type.3 ±.1 % 2.4 ±.4 % 46.2 ± 6.5 % 4.5 ± 1.6 % 5.6 ± 2.4 % 12.7 ± 6.2 % 73.2 ± 11. % 6.2 ± 2.1 % b d Tumor subtype Positive (%) c-kit Negative (%) Total Duct TDLU BRCA1- associated basal tumor 11 (52.4) 1 (47.6) 21 c BRCA1- associated non-basal tumor 2 (33.3) 4 (66.7) 6 non- BRCA1/2 basal tumor 2 (28.6) 5 (71.4) 7 BRCA1 tumor non-brca1/2 tumor Supplementary Figure 9. Increased expression of c-kit in CD49f + EpCAM + luminal progenitor cells and BRCA1-associated tumors. (a) c-kit immunostaining of cytospun cells from sorted Lin subpopulations defined by CD49f and EpCAM. Top panel shows normal breast tissue (n = 3) and bottom panel shows preneoplastic tissue from BRCA1 mutation carriers (n = 3). Data represents mean percentage of c-kitpositive cells (± s.e.m.). Scale bars, 5 µm. (b) Heterogeneous c-kit staining of luminal cells in a normal duct and Terminal Ductal Lobular Unit (TDLU). Scale bars, 5 µm. (c) Representative c-kit immunostaining in BRCA1-associated and non-brca1/2 breast tumors. (d) Frequency of c-kit immunostaining in basal and non-basal breast tumors. Basal tumors were defined as negative for both ERα and HER2, and positive for either cytokeratin-5/6 or EGFR, as defined by Nielsen et al, Clin Cancer Res, 1, (24).

Supplementary Table 1. Classification of pathogenic BRCA1 mutations in prophylactic mastectomy samples

Supplementary Table 1. Classification of pathogenic BRCA1 mutations in prophylactic mastectomy samples Patient ID Age (yrs) BIC classification * HGVS classification # 1 2 BRCA1 del exon BRCA1g.71598-?_71681+?del