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Supplementary Figures 1-2, Materials, Tables 1-4 and Table 7 from Systematic Analysis of MicroRNAs Targeting the Androgen Receptor in Prostate Cancer Cells

Supplementary Table 5 from Systematic Analysis of MicroRNAs Targeting the Androgen Receptor in Prostate Cancer Cells

Supplementary Table 6 from Systematic Analysis of MicroRNAs Targeting the Androgen Receptor in Prostate Cancer Cells

Androgen receptor (AR) is expressed in all stages of prostate cancer progression, including in castration-resistant tumors. Eliminating AR function continues to represent a focus of therapeutic investigation, but AR regulatory mechanisms remain poorly understood. To systematically characterize mechanisms involving microRNAs (miRNAs), we conducted a gain-of function screen of 1129 miRNA molecules in a panel of human prostate cancer cell lines and quantified changes in AR protein content using protein lysate microarrays. In this way, we defined 71 unique miRNAs that influenced the level of AR in human prostate cancer cells. RNA sequencing data revealed that the 3′UTR of AR (and other genes) is much longer than currently used in miRNA target prediction programs. Our own analyses predicted that most of the miRNA regulation of AR would target an extended 6 kb 3′UTR. 3′UTR-binding assays validated 13 miRNAs that are able to regulate this long AR 3′UTR (miR-135b, miR-185, miR-297, miR-299-3p, miR-34a, miR-34c, miR-371–3p, miR-421, miR-449a, miR-449b, miR-634, miR-654–5p, and miR-9). Fifteen AR downregulating miRNAs decreased androgen-induced proliferation of prostate cancer cells. In particular, analysis of clinical prostate cancers confirmed a negative correlation of miR-34a and miR-34c expression with AR levels. Our findings establish that miRNAs interacting with the long 3′UTR of the AR gene are important regulators of AR protein levels, with implications for developing new therapeutic strategies to inhibit AR function and androgen-dependent cell growth. Cancer Res; 71(5); 1956–67. ©2011 AACR.

Pharmacological inhibition of DOT1L blocks estrogen receptor signaling in breast cancer., Breast cancer (BC) resistance to endocrine therapy results from constitutively active or aberrant estrogen receptor α (ERα) signaling, and ways to block ERα pathway in these tumors are sought after. We identified the H3K79 methyltransferase DOT1L as a novel cofactor of ERα in BC cell chromatin, where the two proteins colocalize to regulate estrogen target gene transcription. DOT1L blockade reduces proliferation of hormone-responsive BC cells in vivo and in vitro, consequent to cell cycle arrest and apoptotic cell death, with widespread effects on ER-dependent gene transcription, including ERα and FOXA1 gene silencing. Antiestrogen-resistant BC cells respond to DOT1L inhibition also in mouse xenografts, with reduction in ERα levels, H3K79 methylation, and tumor growth. These results indicate that DOT1L is an exploitable epigenetic target for treatment of endocrine therapy–resistant ERα-positive BCs.

Background The estrogen receptor (ER) inhibitor tamoxifen reduces breast cancer mortality by 31 % and has served as the standard treatment for ER-positive breast cancers for decades. However, 50 % of advanced ER-positive cancers display de novo resistance to tamoxifen, and acquired resistance evolves in 40 % of patients who initially respond. Mechanisms underlying resistance development remain poorly understood and new therapeutic opportunities are urgently needed. Here, we report the generation and characterization of seven tamoxifen-resistant breast cancer cell lines from four parental strains. Methods Using high throughput drug sensitivity and resistance testing (DSRT) with 279 approved and investigational oncology drugs, exome-sequencing and network analysis, we for the first time, systematically determine the drug response profiles specific to tamoxifen resistance. Results We discovered emerging vulnerabilities towards specific drugs, such as ERK1/2-, proteasome- and BCL-family inhibitors as the cells became tamoxifen-resistant. Co-resistance to other drugs such as the survivin inhibitor YM155 and the chemotherapeutic agent paclitaxel also occurred. Conclusion This study indicates that multiple molecular mechanisms dictate endocrine resistance, resulting in unexpected vulnerabilities to initially ineffective drugs, as well as in emerging co-resistances. Thus, combatting drug-resistant tumors will require patient-tailored strategies in order to identify new drug vulnerabilities, and to understand the associated co-resistance patterns. Electronic supplementary material The online version of this article (doi:10.1186/s12885-016-2452-5) contains supplementary material, which is available to authorized users.

Estrogen receptor alpha (ERalpha) is a ligand dependent transcription factor that regulates the expression of target genes through interacting with cis-acting estrogen response elements (EREs). However, only a minority of ERalpha binding sites are located within the proximal promoter regions of responsive genes. Here we report the characterization of an ERE located 9kbp upstream of the TSS of the cathepsin D gene (CTSD) that up-regulates CTSD expression upon estrogen stimulation in MCF-7 cells. Using ChIP, we show recruitment of ERalpha and phosphorylated PolII at the CTSD distal enhancer region. Moreover, we determine the kinetics of transient CpG methylation on the promoter region of CTSD and for the first time, at a distal enhancer element. We show that ERalpha is crucial for long-distance regulation of CTSD expression involving a looping mechanism.

Sara Kangaspeska, Brenda Stride : These authors equally contributed to this work.; International audience; Methylation of CpG dinucleotides is generally associated with epigenetic silencing of transcription and is maintained through cellular division. Multiple CpG sequences are rare in mammalian genomes, but frequently occur at the transcriptional start site of active genes, with most clusters of CpGs being hypomethylated. We reported previously that the proximal region of the trefoil factor 1 (TFF1, also known as pS2) and oestrogen receptor alpha (ERalpha) promoters could be partially methylated by treatment with deacetylase inhibitors, suggesting the possibility of dynamic changes in DNA methylation. Here we show that cyclical methylation and demethylation of CpG dinucleotides, with a periodicity of around 100 min, is characteristic for five selected promoters, including the oestrogen (E2)-responsive pS2 gene, in human cells. When the pS2 gene is actively transcribed, DNA methylation occurs after the cyclical occupancy of ERalpha and RNA polymerase II (polII). Moreover, we report conditions that provoke methylation cycling of the pS2 promoter in cell lines in which pS2 expression is quiescent and the proximal promoter is methylated. This coincides with a low-level re-expression of ERalpha and of pS2 transcripts.

FusionCatcher is a software tool for finding somatic fusion genes in paired-end RNA-sequencing data from human or other vertebrates. FusionCatcher achieves competitive detection rates and real-time PCR validation rates in RNA-sequencing data from tumor cells. FusionCatcher is available at http://code.google.com/p/fusioncatcher

Resistance to aromatase inhibitors (AIs) is a major clinical problem in the treatment of estrogen receptor (ER)-positive breast cancer. In two breast cancer cell line models of AI resistance, we identified widespread DNA hyper- and hypomethylation, with enrichment for promoter hypermethylation of developmental genes. For the homeobox gene HOXC10, methylation occurred in a CpG shore, which overlapped with a functional ER binding site, causing repression of HOXC10 expression. Although short-term blockade of ER signaling caused relief of HOXC10 repression in both cell lines and breast tumors, it also resulted in concurrent recruitment of EZH2 and increased H3K27me3, ultimately transitioning to increased DNA methylation and silencing of HOXC10. Reduced HOXC10 in vitro and in xenografts resulted in decreased apoptosis and caused antiestrogen resistance. Supporting this, we used paired primary and metastatic breast cancer specimens to show that HOXC10 was reduced in tumors that recurred during AI treatment. We propose a model in which estrogen represses apoptotic and growth-inhibitory genes such as HOXC10, contributing to tumor survival, whereas AIs induce these genes to cause apoptosis and therapeutic benefit, but long-term AI treatment results in permanent repression of these genes via methylation and confers resistance. Therapies aimed at inhibiting AI-induced histone and DNA methylation may be beneficial in blocking or delaying AI resistance.

Tamoxifen, as a standard treatment of estrogen receptor (ER)-positive breast cancer, reduces breast cancer mortality by 31%. In 50% of advanced ER-positive cancers, however, de novo resistance exists and in 40% of patients with initial response acquired resistance frequently evolves. In order to explore mechanisms underlying endocrine therapy resistance in breast cancer and to identify new opportunities to treat patients, we created seven tamoxifen-resistant breast cancer cell line models that represent the luminal A subtype (MCF-7, T-47D, ZR-75-1), which expresses ER, and the luminal B subtype (BT-474), which additionally expresses the HER2 oncoprotein. We then performed drug sensitivity and resistance testing (DSRT), exome-sequencing and network analysis on all these cancer cell lines to determine the molecular and drug response profiles specific to tamoxifen resistance. As the cells became tamoxifen-resistant, we observed increasing sensitivity towards drugs like ERK1/2-, proteasome- and BCL-family inhibitors, but each of the isogenic cell line pairs had its distinct genomic and drug response profile. We then studied the molecular profiles of the 7 drug-resistant variants by RNA-sequencing in comparison to their 4 isogenic parental cells. We could not detect any common significantly differentially expressed genes (more than 2 fold change) across all the cell lines. However, the cell lines could be grouped into two different categories: The ones with low amount of differentially expressed genes, < 800 genes in the BT-474 and ZR-75-1 cell line pairs (with a 1,2% overlap), and the ones with high amount of differentially expressed genes, >1800 genes in T-47D and MCF-7 (with 7,3% overlap). Further analysis with the Ingenuity pathway analysis tool revealed an involvement of “Fatty Acid Activation” as well as “Stearate Biosynthesis I” in this group. Additionally, we discovered that genes involved in iron metabolism (TFRC, IREB2 and FTL) or iron-regulated genes like CP and NDRG1 are deregulated. These genes and pathways thereby provide avenues to identify new drug vulnerabilities for the tamoxifen resistant cancer cells, which we are now investigating at gene and protein level e.g. by image-based phenotyping. In summary, by combining drug testing data with the RNA-sequencing results, we hope to provide a number of potential drugs as well as matching biomarkers for planning clinical trials for patients with tamoxifen-resistant breast cancer. Citation Format: Susanne Hultsch, Sara Kangaspeska, Matti Kankainen, Vilja Pietiäinen, Olli Kallioniemi. Systematic drug testing and RNA-sequencing of tamoxifen resistant breast cancer cell lines. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2935.

Background Until recently, chromosomal translocations and fusion genes have been an underappreciated class of mutations in solid tumors. Next-generation sequencing technologies provide an opportunity for systematic characterization of cancer cell transcriptomes, including the discovery of expressed fusion genes resulting from underlying genomic rearrangements. Results We applied paired-end RNA-seq to identify 24 novel and 3 previously known fusion genes in breast cancer cells. Supported by an improved bioinformatic approach, we had a 95% success rate of validating gene fusions initially detected by RNA-seq. Fusion partner genes were found to contribute promoters (5' UTR), coding sequences and 3' UTRs. Most fusion genes were associated with copy number transitions and were particularly common in high-level DNA amplifications. This suggests that fusion events may contribute to the selective advantage provided by DNA amplifications and deletions. Some of the fusion partner genes, such as GSDMB in the TATDN1-GSDMB fusion and IKZF3 in the VAPB-IKZF3 fusion, were only detected as a fusion transcript, indicating activation of a dormant gene by the fusion event. A number of fusion gene partners have either been previously observed in oncogenic gene fusions, mostly in leukemias, or otherwise reported to be oncogenic. RNA interference-mediated knock-down of the VAPB-IKZF3 fusion gene indicated that it may be necessary for cancer cell growth and survival. Conclusions In summary, using RNA-sequencing and improved bioinformatic stratification, we have discovered a number of novel fusion genes in breast cancer, and identified VAPB-IKZF3 as a potential fusion gene with importance for the growth and survival of breast cancer cells.

Androgen receptor (AR) is expressed in all stages of prostate cancer progression, including in castration-resistant tumors. Eliminating AR function continues to represent a focus of therapeutic investigation, but AR regulatory mechanisms remain poorly understood. To systematically characterize mechanisms involving microRNAs (miRNAs), we conducted a gain-of function screen of 1129 miRNA molecules in a panel of human prostate cancer cell lines and quantified changes in AR protein content using protein lysate microarrays. In this way, we defined 71 unique miRNAs that influenced the level of AR in human prostate cancer cells. RNA sequencing data revealed that the 3′UTR of AR (and other genes) is much longer than currently used in miRNA target prediction programs. Our own analyses predicted that most of the miRNA regulation of AR would target an extended 6 kb 3′UTR. 3′UTR-binding assays validated 13 miRNAs that are able to regulate this long AR 3′UTR (miR-135b, miR-185, miR-297, miR-299-3p, miR-34a, miR-34c, miR-371–3p, miR-421, miR-449a, miR-449b, miR-634, miR-654–5p, and miR-9). Fifteen AR downregulating miRNAs decreased androgen-induced proliferation of prostate cancer cells. In particular, analysis of clinical prostate cancers confirmed a negative correlation of miR-34a and miR-34c expression with AR levels. Our findings establish that miRNAs interacting with the long 3′UTR of the AR gene are important regulators of AR protein levels, with implications for developing new therapeutic strategies to inhibit AR function and androgen-dependent cell growth. Cancer Res; 71(5); 1956–67. ©2011 AACR.

In recent years, there has been a growing realization that a static two-dimensional model of gene activation by transcription factors is inadequate. Based on the work from a number of groups (Kang et al. 2002; Liu and Bagchi 2004; Metivier et al. 2003; Park et al. 2005; Reid et al. 2003; Shang et al. 2000; Sharma and Fondell 2002; Vaisanen et al. 2005), it is becoming clear that transcriptional regulation by nuclear receptors is a dynamic and cyclical process (Metivier et al. 2006). There are significant consequences that arise from this shift in understanding, from nuclear receptors as ligand activated factors that bind to a response element to activate expression of a target gene to a process where the receptor repeatedly binds in order to achieve transcription. New insights that arise from viewing the activation process as cyclical and the consequences of this for developing new strategies that modulate the activity of the estrogen receptor are outlined in this chapter.

Wang and colleagues identify a fusion between UBE2L3 and KRAS in a subset of metastatic prostate cancers. Cancer Discovery; 1(1); 12–3. ©2011 AACR. Commentary on Wang et al., p. 35

Most drug-testing approaches published so far focus on identifying a single drug that shows favorable response and is associated with a known cancer biomarker such as the drug Imatinib in BCR-ABL gene fusion positive cells. We developed and applied drug set enrichment analysis (DSEA) to find enriched patterns or statistically significant similarities (overlaps) between the drug responses of a test sample against a cohort of 182 previously screened cancer samples. The samples studied included established (ATCC) cancer cell lines, drug-resistant cancer cell models, ex-vivo patient cancer cells in primary cultures, including conditionally reprogrammed cancer cells from patients. DSEA is adopting Gene Set Enrichment Analysis statistics commonly used for gene expression analysis to high throughput drug testing data. Our drug screening (Pemovska et al., Cancer Discovery, 2013) was done with a panel of 306 established (FDA-approved) and emerging targeted cancer drugs such as tyrosine-kinase inhibitors (e.g. EGFR, PDGFR, BRAF, MET), S/T-type inhibitors, (e.g. MEK, Plk1, Akt, Aurora, Chk1), and inhibitors of other pathways (HDACs, Hh, BCL2, PI3K, PARP) and many others. The readout was based on viability of cells after a 72 hour culture. The DSEA approach is based on taking the top most sensitive drugs (above a defined sensitivity score cut-off) in an individual cancer sample and then identifying overlapping drug response profiles in previously screened reference samples. Our hypothesis is that the most sensitive drug sets in any given sample tend to show similar response profiles in a cohort of similar samples. We convey the correlations and drug set enrichment analysis results as dendrogram trees, plots and tables with enrichment and significance scores. Interestingly, our results show that clustering of drug sensitivity testing data does not place all cancer cell line samples within well-established subgroups based on biological features or histological origin. We find a similar tendency in ex vivo patient samples. Therefore, comprehensive drug response profiles seen may reveal novel biological data that reflect pharmacologically-relevant, phenotypic cancer cell states. DSEA could also provide novel means to subtype previously poorly characterized cancer samples based on their drug response profiles and thereby in the future facilitate the choice of therapies to patients whose cancers repond in an atypical way as compared to the expectations based on anatomical origin or genomic composition. Citation Format: John Patrick Mpindi, Dimitry Bychkov, Yadav Bhagwan, Disha Malani, Hirasawa Akira, Khalid Saeed, Susanne Hultsch, Sara Kangaspeska, Astrid Murumägi, Caroline A Heckman, Kimmo Porkka, Tero Aittokallio, Krister Wennerberg, Päivi Östling, Olli Kallioniemi. Drug set enrichment analysis : A computational approach to identify functional drug sets. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4184. doi:10.1158/1538-7445.AM2014-4184

Androgen receptor (AR) is expressed in all stages of prostate cancer progression and its levels increase in the castration-resistant tumors. However, the mechanisms regulating AR expression remain poorly understood. Here, our aim was to determine the role of miRNAs in regulating AR protein. To this end, we performed a systematic gain-of function screen for 1129 miRNA molecules in prostate cancer cell lines and quantified changes in AR protein content using protein lysate microarrays. We identified 71 unique miRNAs that influenced the level of AR in LNCaP, LAPC-4, 22Rv1, CWR-1R and MDA-PCa-2B cells. Our RNA-sequencing data showed that the 3’UTRs of many genes, including the AR, are much longer than currently used by target prediction programs. Our analyses predicted that the majority of the miRNA regulation of AR would occur through the extended 6 kb 3’UTR. 3’UTR-binding assays validated 13 miRNAs (miR-135b, miR-185, miR-297, miR-299-3p, miR-34a, miR-34c, miR-371-3p, miR-421, miR-449a, miR-449b, miR-634, miR-654-5p, and miR-9) as direct AR regulators. Fifteen AR down-regulating miRNAs decreased androgen-induced proliferation of prostate cancer cells in vitro. Negative correlation of miR-34a and miR-34c expression with AR levels was also found in clinical prostate cancers. To conclude, our results demonstrate that miRNAs interacting with the long 3’UTR of the AR gene are important regulators of AR protein levels. This could be applied for developing novel therapeutic strategies to inhibit AR function and androgen-dependent cell growth. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 3977. doi:10.1158/1538-7445.AM2011-3977

Fusion genes have recently been described in common solid tumors, revealing an important class of mutations that contribute to cancer development and progression. Next-generation sequencing technologies allow systematic characterization of cancer cell transcriptomes, including the fusion genes resulting from underlying chromosomal translocations. Using paired-end RNA-sequencing in conjunction with high-resolution chromosomal copy number analyses we characterized 24 novel and 3 previously known fusion genes in breast cancer cell lines. An improved bioinformatic approach allowed fusion gene validation with a 95% success rate by RT-PCR, Sanger sequencing and FISH. Among the identified fusions, partner genes were found to contribute both promoters (5′UTR; e.g. TATDN1-GSDMB), coding sequences (e.g. ACACA-STAC2) as well as 3′UTRs (e.g. CSE1L-ENSG00000236127). Most fusion genes (82%) were associated with copy number transitions, such as high level amplifications at e.g. 8q21, 17q12, 17q23 and 20q13, implying that fusion gene formation may contribute to the selective advantage provided by copy number amplifications. Although no prevalent single fusion gene was detected, the functional importance of the multiple fusion genes is supported by several lines of evidence. First, some of the fusion partner genes were expressed exclusively as fusion transcripts, e.g. TATDN1-GSDMB, indicating that the fusion event lead to the activation of a latent gene. Second, several fusion gene partners, including ACACA, NOTCH1 and RARA, have been previously found to be involved in oncogenic fusions in leukemias and lymphomas. Third, functional analysis using RNAi-mediated knockdown suggested a potential role for two fusion genes in controlling cancer cell proliferation. In conclusion, using RNA-sequencing together with improved bioinformatics and genomic copy number profiling, we have discovered multiple novel fusion genes in breast cancer, which may provide new insights on breast cancer, and provide therapeutic and diagnostic clues. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4850. doi:10.1158/1538-7445.AM2011-4850

We describe here comprehensive multi-layered genomic, molecular, functional and drug-sensitivity profiles of cancer specimens for clinical diagnostic and therapeutic use. A clinically and histologically atypical metastatic bone tumor was studied with the intent to inform clinicians in real time, should actionable findings emerge. This represents a pilot for future individualized molecular oncology. Methods: We describe integration of the following profiling data: 1) Full genomic sequencing and bioinformatic analysis with 31x coverage of the tumor and 36x of germline DNA 2) aCGH analysis of the tumor and comparison with tumor derived primary cell line 3) Full transcriptome sequencing and microarray analysis 4) Bioinformatic analysis linking gene expression profiles from the patient's tumor with published data on 47 normal and 57 cancer types 5) Phosphoprotein analysis with antibody microarrays and MS covering most therapeutically relevant pathways 6) IHC profiles with multiple antibodies 7) Establishment and molecular representativity of an in vitro cell culture model and mouse xenograft 8) development of personalized plasma-DNA based monitoring of tumor load 9) High-throughput drug sensitivity testing of the patient-derived cell line against a panel of 1500 compounds, including most clinically actionable cancerdrugs and their combinations. Selected key results: The tumor resembled malignant fibrocytic histiocytoma, was pleiomorphic with high mitotic counts. Clinical presentation was atypical with multiple metastatic bone lesions but no primary tumor. Genome sequencing revealed 12 genomic rerrangements and 34 putative missense mutations, including an oncogenic p53 mutation. Array-CGH revealed p16 deletion, and amplification of PDGFRA, KIT and VEGFR2 at 4q, but no clear overexpression. In vitro drug sensitivity testing revealed little impact of targeted drugs and kinase inhibitors like sunitinib, but strong inhibition by eg. bortezomib, daunorubicin, taxanes and zolendronic acid, which helped clinicial treatment decisions. The bone cancer initially responded to the treatment, but later progressed in soft tissues. Conclusions: This deep individualized molecular oncology study highlights the advantages and challenges of translating molecular oncology data on individual patients. Transcriptome and protein expression of the primary tumors and drug sensitivity testing with representative in vitro cell lines may be informative even when diagnostic or therapeutically “actionable” gene mutations are not found. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4836. doi:10.1158/1538-7445.AM2011-4836