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Supplementary Table S1. Partial list of probes preferentially expressed in the Lin-CD29HCD24L cells. Supplementary Table S3. Co-transplantation of increasing numbers of niche cells resulted in increasing numbers of tumors. Supplementary Table S4. a. Pairwise comparisons using fixed number of niche cells displayed a reduced tumor latency with increasing numbers of TICs. b. Pairwise comparisons using 10 TICs demonstrated that tumor formation was more rapid with 10 niche cells as compared to 0. c. Pairwise comparisons using 20 TICs demonstrated that tumor formation was faster with 10 niche cells as compared to 0. Supplementary Table S5. Different types of niche cells were associated with different tumor forming frequencies. Supplementary Table S6. a. No difference observed between shRNA groups for 0 niche cell relative to the control shRNA. b. No difference observed between shRNA groups for 2 niche cells relative to the control shRNA. c. A marginal difference for 10 niche cells relative to the control shRNA. d. A significant difference for 20 niche cells as relative to the control shRNA.

Supplementary Figure S3. Cell cycle analysis of the CD29LCD24H and CD29LCD24L subpopulations.

Supplementary Table S2. A detailed explanation for mice used in Table 1.

Supplementary Data from Identification of Novel Kinase Targets for the Treatment of Estrogen Receptor–Negative Breast Cancer

Table S11. 80 Gene Signature for NMF Cluster 1 (LAR). Table S12. 80 Gene Signature for NMF Cluster 2 (MES). Table S13. 80 Gene Signature for NMF Cluster 3 (BLIS). Table S14. 80 Gene Signature for NMF Cluster 4 (BLIA). Table S15. Assignment of Discovery Set Clusters by Discovery Set Centroids and Comparison to Discovery Set NMF. Table S16. Assignment of Validation Set Clusters by Discovery Set Centroids and Comparison to Validation Set NMF. Table S17. Description of Publically Available Data Sets, with IHC Data for ER/PR/HER2, Downloaded from Gene Omnibus Employed in 'External Set'. Table S18. Assignment of External Set Clusters by Discovery Set Centroids

Purpose: Previous gene expression profiling studies of breast cancer have focused on the entire genome to identify genes differentially expressed between estrogen receptor (ER) α–positive and ER-α–negative cancers.Experimental Design: Here, we used gene expression microarray profiling to identify a distinct kinase gene expression profile that identifies ER-negative breast tumors and subsets ER-negative breast tumors into four distinct subtypes.Results: Based on the types of kinases expressed in these clusters, we identify a cell cycle regulatory subset, a S6 kinase pathway cluster, an immunomodulatory kinase–expressing cluster, and a mitogen-activated protein kinase pathway cluster. Furthermore, we show that this specific kinase profile is validated using independent sets of human tumors and is also seen in a panel of breast cancer cell lines. Kinase expression knockdown studies show that many of these kinases are essential for the growth of ER-negative, but not ER-positive, breast cancer cell lines. Finally, survival analysis of patients with breast cancer shows that the S6 kinase pathway signature subtype of ER-negative cancers confers an extremely poor prognosis, whereas patients whose tumors express high levels of immunomodulatory kinases have a significantly better prognosis.Conclusions: This study identifies a list of kinases that are prognostic and may serve as druggable targets for the treatment of ER-negative breast cancer. (Clin Cancer Res 2009;15(20):6327–40)

CCR Translation for the Article from Identification of Novel Kinase Targets for the Treatment of Estrogen Receptor–Negative Breast Cancer

Supplementary Table S2 from Ductal Carcinoma In situ and the Emergence of Diversity during Breast Cancer Evolution

Supplementary Figures S1-S4.

Figure S1. Full clustering metrics in support of a 4 cluster model in the discovery set with membership as defined by TNBCType. Figure S2. Full clustering metrics in support of a 4 cluster model in the validation set with membership as defined by the TNBCType tool Figure S3. Allred scores for clinical IHC of ER, PR, and Her2 protein expression for samples in the discovery and validation sets. Figure S4. Gene expression for discovery and validation sets by NMF Figure S5. NMF of both datasets (discovery and validation, renormalized together) of study data using feature set of 2188 genes utilized in Lehmann et al. (2010) and comparison of resulting clusters t Figure S6. ESR1 expression for ER-positive breast cancers, LAR TNBCs, and all other TNBCs. Figure S7. Expression of common differentially expressed genes in claudin-low tumors selected for their role in luminal differentiation from Prat et al. (2010). Figure S8. Aberrant fraction and ploidy of ASCAT derived copy number estimates. Figure S9. ASCAT derived copy number events reveals distinctive gains and losses that segregate LAR subtype tumors from remaining subtypes.

Purpose: Genomic profiling studies suggest that triple-negative breast cancer (TNBC) is a heterogeneous disease. In this study, we sought to define TNBC subtypes and identify subtype-specific markers and targets.Experimental Design: RNA and DNA profiling analyses were conducted on 198 TNBC tumors [estrogen receptor (ER) negativity defined as Allred scale value ≤ 2] with >50% cellularity (discovery set: n = 84; validation set: n = 114) collected at Baylor College of Medicine (Houston, TX). An external dataset of seven publically accessible TNBC studies was used to confirm results. DNA copy number, disease-free survival (DFS), and disease-specific survival (DSS) were analyzed independently using these datasets.Results: We identified and confirmed four distinct TNBC subtypes: (i) luminal androgen receptor (AR; LAR), (ii) mesenchymal (MES), (iii) basal-like immunosuppressed (BLIS), and (iv) basal-like immune-activated (BLIA). Of these, prognosis is worst for BLIS tumors and best for BLIA tumors for both DFS (log-rank test: P = 0.042 and 0.041, respectively) and DSS (log-rank test: P = 0.039 and 0.029, respectively). DNA copy number analysis produced two major groups (LAR and MES/BLIS/BLIA) and suggested that gene amplification drives gene expression in some cases [FGFR2 (BLIS)]. Putative subtype-specific targets were identified: (i) LAR: androgen receptor and the cell surface mucin MUC1, (ii) MES: growth factor receptors [platelet-derived growth factor (PDGF) receptor A; c-Kit], (iii) BLIS: an immunosuppressing molecule (VTCN1), and (iv) BLIA: Stat signal transduction molecules and cytokines.Conclusion: There are four stable TNBC subtypes characterized by the expression of distinct molecular profiles that have distinct prognoses. These studies identify novel subtype-specific targets that can be targeted in the future for the effective treatment of TNBCs. Clin Cancer Res; 21(7); 1688–98. ©2014 AACR.See related commentary by Vidula and Rugo, p. 1511

Purpose:Tumor-infiltrating lymphocytes (TIL) are associated with benefit to trastuzumab and chemotherapy in patients with early-stage HER2+ breast cancer. The predictive value of TILs, TIL subsets, and other immune cells in patients receiving chemotherapy-sparing lapatinib plus trastuzumab treatment is unclear.Experimental Design: Hematoxylin and eosin–stained slides (n = 59) were used to score stromal (s-)TILs from pretreatment biopsies of patients enrolled in the neoadjuvant TBCRC006 trial of 12-week lapatinib plus trastuzumab therapy (plus endocrine therapy for ER+ tumors). A 60% threshold was used to define lymphocyte-predominant breast cancer (LPBC). Multiplexed immunofluorescence (m-IF) staining (CD4, CD8, CD20, CD68, and FoxP3) and multispectral imaging were performed to characterize immune infiltrates in single formalin-fixed paraffin-embedded slides (n = 33).Results:The pathologic complete response (pCR) rate was numerically higher in patients with LPBC compared with patients with non-LPBC (50% vs. 19%, P = 0.057). Unsupervised hierarchical clustering of the five immune markers identified two patient clusters with different responses to lapatinib plus trastuzumab treatment (pCR = 7% vs. 50%, for cluster 1 vs. 2 respectively; P = 0.01). In multivariable analysis, cluster 2, characterized by high CD4+, CD8+, CD20+ s-TILs, and high CD20+ intratumoral TILs, was independently associated with a higher pCR rate (P = 0.03). Analysis of single immune subpopulations revealed a significant association of pCR with higher baseline infiltration by s-CD4, intratumoral (i-) CD4, and i-CD20+ TILs.Conclusions:LPBC was marginally associated with higher pCR rate than non-LPBC in patients with lapatinib plus trastuzumab treated HER2+ breast cancer. Quantitative assessment of the immune infiltrate by m-IF is feasible and may help correlate individual immune cell subpopulations and immune cell profiles with treatment response.

Purpose: Human invasive breast cancers (IBC) show enormous histologic and biological diversity. This study comprehensively evaluated diversity in ductal carcinoma in situ (DCIS), the immediate precursors of IBCs.Experimental Design: The extent of diversity for conventional histologic grade and standard prognostic biomarkers assessed by immunohistochemistry was evaluated in a series of pure DCIS (n = 200) compared with a contemporaneous series of IBCs (n = 200). A subset of the DCIS (n = 25) was evaluated by DNA microarrays for the presence of luminal, basal, and erbB2 intrinsic subtypes. The extent of diversity within individual cases of DCIS (n = 120) was determined by assessing multiple regions independently for histologic (nuclear) grade and several biomarkers by immunohistochemistry, which approximate microarrays in determining intrinsic subtypes.Results: DCIS showed a broad distribution of conventional histologic grades and standard biomarkers ranging from well to poorly differentiated, nearly identical to IBCs. Microarrays showed the same intrinsic subtypes in DCIS as in IBCs. However, higher resolution analysis showed that multiple histologic grades, biomarker phenotypes, and intrinsic subtypes often coexist within the same DCIS, and these diverse regions probably compete for dominance. Diversity within cases of DCIS was highly correlated with mutated p53 (P = 0.0007).Conclusions: These results support the hypothesis that poorly differentiated DCIS gradually evolve from well-differentiated DCIS by randomly acquiring genetic defects resulting in increasingly abnormal cellular features. This diversity is amplified by defects resulting in genetic instability (e.g., p53 mutation), and the alterations are propagated to IBC in a manner independent of progression to invasion.

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Supplementary tables

Purpose: Tamoxifen (Tam) is the most prescribed hormonal agent for treatment of estrogen receptor α (ERα)-positive breast cancer patients. Using microarray analysis, we observed that metastatic breast tumors resistant to Tam therapy had elevated levels of Dicer.Experimental Design: We overexpressed Dicer in ERα-positive MCF-7 human breast cancer cells and observed a concomitant increase in expression of the breast cancer resistance protein (BCRP). We thus hypothesized that Tam resistance associated with Dicer overexpression in ERα-positive breast cancer cells may involve BCRP. We analyzed BCRP function in Dicer-overexpressing cells using growth in soft agar and mammosphere formation and evaluated intracellular Tam efflux.Results: In the presence of Tam, Dicer-overexpressing cells formed resistant colonies in soft agar, and treatment with BCRP inhibitors restored Tam sensitivity. Tumor xenograft studies confirmed that Dicer-overexpressing cells were resistant to Tam in vivo. Tumors and distant metastases could be initiated with as few as five mammosphere cells from both vector and Dicer-overexpressing cells, indicating that the mammosphere assay selected for cells with enhanced tumor-initiating and metastatic capacity. Dicer-overexpressing cells with elevated levels of BCRP effluxed Tam more efficiently than control cells, and BCRP inhibitors were able to inhibit efflux.Conclusion: Dicer-overexpressing breast cancer cells enriched for cells with enhanced BCRP function. We hypothesize that it is this population which may be involved in the emergence of Tam-resistant growth. BCRP may be a novel clinical target to restore Tam sensitivity. Clin Cancer Res; 17(20); 6510–21. ©2011 AACR.

Supplementary Figures S1-S2 and Supplementary Table S1 from Ductal Carcinoma In situ and the Emergence of Diversity during Breast Cancer Evolution

Purpose: We previously reported an insulin-like growth factor (IGF) gene expression signature, based on genes induced or repressed by IGF-I, which correlated with poor prognosis in breast cancer. We tested whether the IGF signature was affected by anti–IGF-I receptor (IGF-IR) inhibitors and whether the IGF signature correlated with response to a dual anti–IGF-IR/insulin receptor (InsR) inhibitor, BMS-754807.Experimental Design: An IGF gene expression signature was examined in human breast tumors and cell lines and changes were noted following treatment of cell lines or xenografts with anti–IGF-IR antibodies or tyrosine kinase inhibitors. Sensitivity of cells to BMS-754807 was correlated with levels of the IGF signature. Human primary tumorgrafts were analyzed for the IGF signature and IGF-IR levels and activity, and MC1 tumorgrafts were treated with BMS-754807 and chemotherapy.Results: The IGF gene expression signature was reversed in three different models (cancer cell lines or xenografts) treated with three different anti–IGF-IR therapies. The IGF signature was present in triple-negative breast cancers (TNBC) and TNBC cell lines, which were especially sensitive to BMS-754807, and sensitivity was significantly correlated to the expression of the IGF gene signature. The TNBC primary human tumorgraft MC1 showed high levels of both expression and activity of IGF-IR and IGF gene signature score. Treatment of MC1 with BMS-754807 showed growth inhibition and, in combination with docetaxel, tumor regression occurred until no tumor was palpable. Regression was associated with reduced proliferation, increased apoptosis, and mitotic catastrophe.Conclusions: These studies provide a clear biological rationale to test anti–IGF-IR/InsR therapy in combination with chemotherapy in patients with TNBC. Clin Cancer Res; 17(8); 2314–27. ©2011 AACR.

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Supplementary Fig 1 � PDF file 42K, General design of the xenografting program

Supplementary Figure 2 from Identification of Tumor-Initiating Cells in a p53-Null Mouse Model of Breast Cancer

10 figures and 2 tables provided as supplementary material supporting the major conclusions of the manuscript and experimental details.

Table S2 - XLSX file 77K, Verification of lentiviral shRNA knock-down in SUM159 cells by quantitative RT-PCR

Supplementary Figure 7 from Identification of Tumor-Initiating Cells in a p53-Null Mouse Model of Breast Cancer

Supplementary Figure 1 from Identification of Tumor-Initiating Cells in a p53-Null Mouse Model of Breast Cancer

Supplementary Table 1 from Tamoxifen Resistance in Breast Tumors Is Driven by Growth Factor Receptor Signaling with Repression of Classic Estrogen Receptor Genomic Function

Approximately 20% of early-stage breast cancers display amplification or overexpression of the ErbB2/HER2 oncogene, conferring poor prognosis and resistance to endocrine therapy. Targeting HER2+ tumors with trastuzumab or the receptor tyrosine kinase (RTK) inhibitor lapatinib significantly improves survival, yet tumor resistance and progression of metastatic disease still develop over time. Although the mechanisms of cytosolic HER2 signaling are well studied, nuclear signaling components and gene regulatory networks that bestow therapeutic resistance and limitless proliferative potential are incompletely understood. Here, we use biochemical and bioinformatic approaches to identify effectors and targets of HER2 transcriptional signaling in human breast cancer. Phosphorylation and activity of the Steroid Receptor Coactivator-3 (SRC-3) is reduced upon HER2 inhibition, and recruitment of SRC-3 to regulatory elements of endogenous genes is impaired. Transcripts regulated by HER2 signaling are highly enriched with E2F1 binding sites and define a gene signature associated with proliferative breast tumor subtypes, cell-cycle progression, and DNA replication. We show that HER2 signaling promotes breast cancer cell proliferation through regulation of E2F1-driven DNA metabolism and replication genes together with phosphorylation and activity of the transcriptional coactivator SRC-3. Furthermore, our analyses identified a cyclin-dependent kinase (CDK) signaling node that, when targeted using the CDK4/6 inhibitor palbociclib, defines overlap and divergence of adjuvant pharmacologic targeting. Importantly, lapatinib and palbociclib strictly block de novo synthesis of DNA, mostly through disruption of E2F1 and its target genes. These results have implications for rational discovery of pharmacologic combinations in preclinical models of adjuvant treatment and therapeutic resistance. Cancer Res; 76(6); 1463–75. ©2016 AACR.

Supplementary Fig 2 � PDF file 783K, Histology of unmatched xenograft lines

Supplementary Methods and Materials from Development of Resistance to Targeted Therapies Transforms the Clinically Associated Molecular Profile Subtype of Breast Tumor Xenografts

Figure S3 - PDF file 1318K, Expression LPAR2 in breast cancers, and the importance of LPAR2 in the expression of cytokines in SUM159

Supp Fig 5 - A) PTP4A3 and Myc amplification status in Luminal A/B and Basal-like breast cancers from TCGA data set. B) PTP4A3 and Myc amplification status in ovarian cancer from TCGA data set. C) Map detailing the location of the genes analyzed for gene amplification. D) Comparative analysis of PTP4A3 gene copy number and expression levels

Supplementary Text - PDF file 109K, Supplementary Figure Legends

Supplementary Figure 4 from Identification of Tumor-Initiating Cells in a p53-Null Mouse Model of Breast Cancer

Not all breast cancers respond to tamoxifen, and many develop resistance despite initial benefit. We used an in vivo model of estrogen receptor (ER)–positive breast cancer (MCF-7 xenografts) to investigate mechanisms of this resistance and develop strategies to circumvent it. Epidermal growth factor receptor (EGFR) and HER2, which were barely detected in control estrogen-treated tumors, increased slightly with tamoxifen and were markedly increased when tumors became resistant. Gefitinib, which inhibits EGFR/HER2, improved the antitumor effect of tamoxifen and delayed acquired resistance, but had no effect on estrogen-stimulated growth. Phosphorylated levels of p42/44 and p38 mitogen-activated protein kinases (both downstream of EGFR/HER2) were increased in the tamoxifen-resistant tumors and were suppressed by gefitinib. There was no apparent increase in phosphorylated AKT (also downstream of EGFR/HER2) in resistant tumors, but it was nonetheless suppressed by gefitinib. Phosphorylated insulin-like growth factor-IR (IGF-IR), which can interact with both EGFR and membrane ER, was elevated in the tamoxifen-resistant tumors compared with the sensitive group. However, ER-regulated gene products, including total IGF-IR itself and progesterone receptor, remained suppressed even at the time of acquired resistance. Tamoxifen's antagonism of classic ER genomic function was retained in these resistant tumors and even in tumors that overexpress HER2 (MCF-7 HER2/18) and are de novo tamoxifen-resistant. In conclusion, EGFR/HER2 may mediate tamoxifen resistance in ER-positive breast cancer despite continued suppression of ER genomic function by tamoxifen. IGF-IR expression remains dependent on ER but is activated in the tamoxifen-resistant tumors. This study provides a rationale to combine HER inhibitors with tamoxifen in clinical studies, even in tumors that do not initially overexpress EGFR/HER2. [Cancer Res 2008;68(3):826–33]

Triple-negative breast cancer (TNBC) has the worst prognosis of all breast cancers, and women diagnosed with TNBC currently lack targeted treatment options. To identify novel targets for TNBC, we evaluated phosphatase expression in breast tumors and characterized their contributions to in vitro and in vivo growth of TNBC. Using Affymetrix microarray analysis of 102 breast cancers, we identified 146 phosphatases that were significantly differentially expressed in TNBC compared with estrogen receptor (ER)-positive tumors. Of these, 19 phosphatases were upregulated (0.66-fold; FDR = 0.05) in TNBC compared with ER-positive breast cancers. We knocked down 17 overexpressed phosphatases in four triple-negative and four ER-positive breast cancer lines using specific siRNAs and found that depletion of six of these phosphatases significantly reduced growth and anchorage-independent growth of TNBC cells to a greater extent than ER-positive cell lines. Further analysis of the phosphatase PTP4A3 (also known as PRL-3) demonstrated its requirement for G1–S cell-cycle progression in all breast cancer cells, but PTP4A3 regulated apoptosis selectively in TNBC cells. In addition, PTP4A3 inhibition reduced the growth of TNBC tumors in vivo. Moreover, in silico analysis revealed the PTP4A3 gene to be amplified in 29% of basal-like breast cancers, and high expression of PTP4A3 could serve as an independent prognostic indicator for worse overall survival. Collectively, these studies define the importance of phosphatase overexpression in TNBC and lay the foundation for the development of new targeted therapies directed against phosphatases or their respective signaling pathways for TNBC patients. Cancer Res; 76(7); 1942–53. ©2016 AACR.

Supplementary Table 3 � XLXS file 39K, Patient/xenograft biomarker comparison

Supplementary Fig 4 � PDF file 123K, Treatment response concordance with the tumor of origin

Supplementary Figure 9 from Identification of Tumor-Initiating Cells in a p53-Null Mouse Model of Breast Cancer

Supp Fig 2 - Cleaved caspase 7 is selective increased in basal-like breast cancers with low PTP4A3 expression.

Supplementary Table 2 � XLXS file 18K, STR Results

Supp Fig 4 - A) Curtis data set analyzed for expression levels of PTP4A3 in normal breast tissue compared to invasive ductal carcinoma (IDC). B) Curtis data set analyzed for expression levels of PTP4A3 in non-TNBCs versus TNBCs. C) Kaplan-Meier curves of overall survival of all breast cancer patients (Kao Dataset) stratified by PTP4A3 expression and ER. D) Kaplan-Meier curves of disease-specific survival of all breast cancer patients (Curtis Dataset) stratified by PTP4A3 expression.

Using a syngeneic p53-null mouse mammary gland tumor model that closely mimics human breast cancer, we have identified, by limiting dilution transplantation and in vitro mammosphere assay, a Lin−CD29HCD24H subpopulation of tumor-initiating cells. Upon subsequent transplantation, this subpopulation generated heterogeneous tumors that displayed properties similar to the primary tumor. Analysis of biomarkers suggests the Lin−CD29HCD24H subpopulation may have arisen from a bipotent mammary progenitor. Differentially expressed genes in the Lin−CD29HCD24H mouse mammary gland tumor-initiating cell population include those involved in DNA damage response and repair, as well as genes involved in epigenetic regulation previously shown to be critical for stem cell self-renewal. These studies provide in vitro and in vivo data that support the cancer stem cell (CSC) hypothesis. Furthermore, this p53-null mouse mammary tumor model may allow us to identify new CSC markers and to test the functional importance of these markers. [Cancer Res 2008;68(12):4674–82]

Supplementary Table 1 � XLXS file 41K, Patient characteristics by transplant generation

Supplementary Figure 5 from Identification of Tumor-Initiating Cells in a p53-Null Mouse Model of Breast Cancer

Spreadsheet containing Gene ID and ontology analysis for all transcripts downregulated with HER2 depletion.

Supp Tab 2 - Cox proportional hazard ratio analysis of the Curtis Data set.

Legends to Supplementary Figures - PDF file 65K, Legends to supplementary figures

Supplementary Methods, Tables 1-4, Figure Legends 1-9 from Identification of Tumor-Initiating Cells in a p53-Null Mouse Model of Breast Cancer