Juha Rantala

Systematic knockdown of epigenetic enzymes identifies a novel histone demethylase PHF8 overexpressed in prostate cancer with an impact on cell proliferation, migration and invasion

Our understanding of key epigenetic regulators involved in specific biological processes and cancers is still incomplete, despite great progress in genome-wide studies of the epigenome. Here, we carried out a systematic, genome-wide analysis of the functional significance of 615 epigenetic proteins in prostate cancer (PrCa) cells. We used the high-content cell-spot microarray technology and siRNA silencing of PrCa cell lines for functional screening of cell proliferation, survival, androgen receptor (AR) expression, histone methylation and acetylation. Our study highlights subsets of epigenetic enzymes influencing different cancer cell phenotypes. Plant homeo domain (PHD) finger proteins have a key role in cell survival and histone methylation, whereas histone deacetylases were primarily involved in regulating AR expression. In contrast, JumonjiC-domain (JmjC) containing histone lysine demethylases (KDMs) mainly had an impact on cell proliferation. Our results show that the KDMs JARID1B, PHF8, KDM3A, KDM3B and KDM4A were highly expressed in clinical PrCa samples. The PHD-finger protein 8 (PHF8), a transcriptional coactivator with both PHD- and JmjC-domains, was moderately to strongly expressed in 80% of clinical PrCa samples, whereas 76% of normal and benign samples were negative or only showed weak PHF8 expression. Strong PHF8 expression correlated significantly with high Gleason grade and was borderline significant for poor prognosis. The results of functional PHF8 knockdown implicate a role in cell migration and invasion, as shown by cell motility and 3-D invasion assays. Our study suggests that various cellular phenotypes are regulated by distinct subsets of epigenetic enzymes. Proteins interpreting and modifying histone methylation, such as JmjC-domain and particularly PHD-finger proteins like PHF8, are activated in subsets of PrCas and promote cancer relevant phenotypes.

CDK-mediated activation of the SCFFBXO28 ubiquitin ligase promotes MYC-driven transcription and tumourigenesis and predicts poor survival in breast cancer

SCF (Skp1/Cul1/F‐box) ubiquitin ligases act as master regulators of cellular homeostasis by targeting key proteins for ubiquitylation. Here, we identified a hitherto uncharacterized F‐box protein, FBXO28 that controls MYC‐dependent transcription by non‐proteolytic ubiquitylation. SCFFBXO28 activity and stability are regulated during the cell cycle by CDK1/2‐mediated phosphorylation of FBXO28, which is required for its efficient ubiquitylation of MYC and downsteam enhancement of the MYC pathway. Depletion of FBXO28 or overexpression of an F‐box mutant unable to support MYC ubiquitylation results in an impairment of MYC‐driven transcription, transformation and tumourigenesis. Finally, in human breast cancer, high FBXO28 expression and phosphorylation are strong and independent predictors of poor outcome. In conclusion, our data suggest that SCFFBXO28 plays an important role in transmitting CDK activity to MYC function during the cell cycle, emphasizing the CDK‐FBXO28‐MYC axis as a potential molecular drug target in MYC‐driven cancers, including breast cancer.

The gene expression landscape of breast cancer is shaped by tumor protein p53 status and epithelial-mesenchymal transition

IntroductionGene expression data derived from clinical cancer specimens provide an opportunity to characterize cancer-specific transcriptional programs. Here, we present an analysis delineating a correlation-based gene expression landscape of breast cancer that identifies modules with strong associations to breast cancer-specific and general tumor biology.MethodsModules of highly connected genes were extracted from a gene co-expression network that was constructed based on Pearson correlation, and module activities were then calculated using a pathway activity score. Functional annotations of modules were experimentally validated with an siRNA cell spot microarray system using the KPL-4 breast cancer cell line, and by using gene expression data from functional studies. Modules were derived using gene expression data representing 1,608 breast cancer samples and validated in data sets representing 971 independent breast cancer samples as well as 1,231 samples from other cancer forms.ResultsThe initial co-expression network analysis resulted in the characterization of eight tightly regulated gene modules. Cell cycle genes were divided into two transcriptional programs, and experimental validation using an siRNA screen showed different functional roles for these programs during proliferation. The division of the two programs was found to act as a marker for tumor protein p53 (TP53) gene status in luminal breast cancer, with the two programs being separated only in luminal tumors with functional p53 (encoded by TP53). Moreover, a module containing fibroblast and stroma-related genes was highly expressed in fibroblasts, but was also up-regulated by overexpression of epithelial-mesenchymal transition factors such as transforming growth factor beta 1 (TGF-beta1) and Snail in immortalized human mammary epithelial cells. Strikingly, the stroma transcriptional program related to less malignant tumors for luminal disease and aggressive lymph node positive disease among basal-like tumors.ConclusionsWe have derived a robust gene expression landscape of breast cancer that reflects known subtypes as well as heterogeneity within these subtypes. By applying the modules to TP53-mutated samples we shed light on the biological consequences of non-functional p53 in otherwise low-proliferating luminal breast cancer. Furthermore, as in the case of the stroma module, we show that the biological and clinical interpretation of a set of co-regulated genes is subtype-dependent.

Expanding the Diversity of Imaging-Based RNAi Screen Applications Using Cell Spot Microarrays

Over the past decade, great strides have been made in identifying gene aberrations and deregulated pathways that are associated with specific disease states. These association studies guide experimental studies aimed at identifying the aberrant genes and networks that cause the disease states. This requires functional manipulation of these genes and networks in laboratory models of normal and diseased cells. One approach is to assess molecular and biological responses to high-throughput RNA interference (RNAi)-induced gene knockdown. These responses can be revealed by immunofluorescent staining for a molecular or cellular process of interest and quantified using fluorescence image analysis. These applications are typically performed in multiwell format, but are limited by high reagent costs and long plate processing times. These limitations can be mitigated by analyzing cells grown in cell spot microarray (CSMA) format. CSMAs are produced by growing cells on small (~200 μm diameter) spots with each spot carrying an siRNA with transfection reagent. The spacing between spots is only a few hundred micrometers, thus thousands of cell spots can be arranged on a single cell culture surface. These high-density cell cultures can be immunofluorescently stained with minimal reagent consumption and analyzed quickly using automated fluorescence microscopy platforms. This review covers basic aspects of imaging-based CSMA technology, describes a wide range of immunofluorescence assays that have already been implemented successfully for CSMA screening and suggests future directions for advanced RNAi screening experiments.

MHC class I loaded ligands from breast cancer cell lines: A potential HLA-I-typed antigen collection

To build a catalog of peptides presented by breast cancer cells, we undertook systematic MHC class I immunoprecipitation followed by elution of MHC class I-loaded peptides in breast cancer cells. We determined the sequence of 3196 MHC class I ligands representing 1921 proteins from a panel of 20 breast cancer cell lines. After removing duplicate peptides, i.e., the same peptide eluted from more than one cell line, the total number of unique peptides was 2740. Of the unique peptides eluted, more than 1750 had been previously identified, and of these, sixteen have been shown to be immunogenic. Importantly, half of these immunogenic peptides were shared between different breast cancer cell lines. MHC class I binding probability was used to plot the distribution of the eluted peptides in accordance with the binding score for each breast cancer cell line. We also determined that the tested breast cancer cells presented 89 mutation-containing peptides and peptides derived from aberrantly translated genes, 7 of which were shared between four or two different cell lines. Overall, the high throughput identification of MHC class I-loaded peptides is an effective strategy for systematic characterization of cancer peptides, and could be employed for design of multi-peptide anticancer vaccines. SIGNIFICANCE By employing proteomic analyses of eluted peptides from breast cancer cells, the current study has built an initial HLA-I-typed antigen collection for breast cancer research. It was also determined that immunogenic epitopes can be identified using established cell lines and that shared immunogenic peptides can be found in different cancer types such as breast cancer and leukemia. Importantly, out of 3196 eluted peptides that included duplicate peptides in different cells 89 peptides either contained mutation in their sequence or were derived from aberrant translation suggesting that mutation-containing epitopes are on the order of 2-3% in breast cancer cells. Finally, our results suggest that interfering with MHC class I function is one of the mechanisms of how tumor cells escape immune system attack.

The PI3K/Akt1 pathway enhances steady-state levels of FANCL

The Fanconi anemia pathway supports hematopoietic stem cell survival in response to inflammatory and metabolic stress. We show that polyubiquitination and proteasome degradation of FANCL is inhibited by Akt1 activation, revealing a potentially important mechanism for the maintenance of stem cell function.

Metabolic reprogramming ensures cancer cell survival despite oncogenic signaling blockade

There is limited knowledge about the metabolic reprogramming induced by cancer therapies and how this contributes to therapeutic resistance. Here we show that although inhibition of PI3K-AKT-mTOR signaling markedly decreased glycolysis and restrained tumor growth, these signaling and metabolic restrictions triggered autophagy, which supplied the metabolites required for the maintenance of mitochondrial respiration and redox homeostasis. Specifically, we found that survival of cancer cells was critically dependent on phospholipase A2 (PLA2) to mobilize lysophospholipids and free fatty acids to sustain fatty acid oxidation and oxidative phosphorylation. Consistent with this, we observed significantly increased lipid droplets, with subsequent mobilization to mitochondria. These changes were abrogated in cells deficient for the essential autophagy gene ATG5 Accordingly, inhibition of PLA2 significantly decreased lipid droplets, decreased oxidative phosphorylation, and increased apoptosis. Together, these results describe how treatment-induced autophagy provides nutrients for cancer cell survival and identifies novel cotreatment strategies to override this survival advantage.

Abstract 1831: Interrogating HER2+ plasticity and lapatinib resistance with MicroEnvironment MicroArrays

Proceedings: AACR Annual Meeting 2014; April 5-9, 2014; San Diego, CA Treatment of HER2+ breast cancer with the targeted therapeutic lapatinib has shown promising results, but faces the major obstacles of de novo and acquired resistance in clinical use. Much of this resistance can be attributed to intratumoral heterogeneity, giving rise to drug resistant cell populations. An important factor of intratumoral heterogeneity is spatial heterogeneity of cancer cells, which results in differential contact with extra cellular matrix (ECM) proteins, stromal cells, and growth factors and signaling molecules within the tumor microenvironment. This can variably alter the intracellular signaling network of cancer cells, modulating cellular plasticity and drug response. To assess the effect cellular interactions with the microenvironment has on lapatinib resistance, we are utilizing MicroEnvironment MicroArrays (MEMA), which consist of combinations of functional ECMs, growth factors, and cytokines printed onto a solid surface, allowing for the simultaneous interrogation of thousands of unique microenvironments in a single assay. We have grown HER2+ breast cancer cells on the MEMA spots, treated with lapatinib, and measured functional response to each protein combination by immunofluorescent assay and high throughput image acquisition and analysis. By focusing on markers of proliferation, apoptosis, and cellular subtype differentiation, we have identified protein combinations that confer resistance to lapatinib. One of the combinations that came out of this preliminary screen is the desmosome protein Desmoglein II and the growth factor HGF, which continued to drive proliferation of HER2+ cells in the presence of lapatinib. Validation experiments found that on their own these two proteins could modulate the differentiation status of HER2+ cells, and combined to provide resistance to lapatinib treatment in traditional cell culture assays. In addition, the extent of drug resistance provided by protein interaction was found to be strongly linked to the differentiation status of the HER2+ cells. Both HGF and Desmoglein II are reported to be important in the progression of breast cancer, but their effect in combination is a novel finding from the use of MEMA analysis. We plan to utilize RNAseq analysis to inform a probabilistic computational model of network signaling to determine what pathways are enhanced by the microenvironment factors, and siRNA knockdown or small molecule inhibitors of identified pathway nodes can then determine which interactions can be targeted to restore drug sensitivity. Citation Format: Spencer Watson, James Korkola, Juha Rantala, Joe Gray. Interrogating HER2+ plasticity and lapatinib resistance with MicroEnvironment MicroArrays. [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 1831. doi:10.1158/1538-7445.AM2014-1831

Differentiation-state plasticity is a targetable resistance mechanism in basal-like breast cancer

Intratumoral heterogeneity in cancers arises from genomic instability and epigenomic plasticity and is associated with resistance to cytotoxic and targeted therapies. We show here that cell-state heterogeneity, defined by differentiation-state marker expression, is high in triple-negative and basal-like breast cancer subtypes, and that drug tolerant persister (DTP) cell populations with altered marker expression emerge during treatment with a wide range of pathway-targeted therapeutic compounds. We show that MEK and PI3K/mTOR inhibitor-driven DTP states arise through distinct cell-state transitions rather than by Darwinian selection of preexisting subpopulations, and that these transitions involve dynamic remodeling of open chromatin architecture. Increased activity of many chromatin modifier enzymes, including BRD4, is observed in DTP cells. Co-treatment with the PI3K/mTOR inhibitor BEZ235 and the BET inhibitor JQ1 prevents changes to the open chromatin architecture, inhibits the acquisition of a DTP state, and results in robust cell death in vitro and xenograft regression in vivo.Resistance to therapy can be driven by intratumoral heterogeneity. Here, the authors show that drug tolerant persistent cell populations emerge during treatment, and these emergent populations arise through epigenetically mediated cell state transitions rather than sub population selection.

Abstract B52: Overcoming phenotypic heterogeneity and plasticity in basal-like breast cancer through targeting adaptive pathway use

The use of small-molecule kinase inhibitors is a promising therapeutic strategy for the management of breast cancer. Positive responses to these agents, however, are often transient, and acquired resistance arises in the course of weeks to months. Recent studies have demonstrated that phenotypic plasticity in cancer cell populations can provide adaptive resistance to small-molecule kinase inhibitors, whereby cancer cells transition to drug-tolerant phenotypic states, reliant on compensatory survival and proliferative signaling pathways. Drug combinations and sequences can prevent this adaptive resistance to targeted therapy, however, nominating effective drug pairs is challenging. In this study, we seek to identify such drug combinations through first identifying single agent therapeutics that reduce phenotypic heterogeneity and enrich distinct cell-states with common pathway reliance. To do so, we focus on phenotypic heterogeneity in tumor-cell lineage-state; using immunofluorescent staining against markers of the luminal, basal, and mesenchymal lineages, we combine high-throughput drug screening with high-content imaging and pursue small-molecule inhibitors that reduce phenotypic heterogeneity and promote the accumulation of particular lineage-states in residual cell populations. We observe pronounced lineage-state heterogeneity in Triple-Negative tumors and Basal-Like breast cancer cell lines, and find that the lineage-state distributions are greatly influenced by numerous therapeutics. MEK and PI3K/mTOR inhibitors in particular induce robust time- and dose-dependent alterations is lineage-state distribution in residual cell populations, selecting for a cell population enriched in, or depleted of a basal lineage-state, respectively. Through gene expression profiling and master-regulator analysis of active transcriptional states in the residual cell populations, we are able to identify compensatory-signaling pathways. We demonstrate that combining MEK and PI3K/mTOR inhibitors with agents targeting these compensatory pathways induces synergistic antiproliferative effects. Citation Format: Tyler Risom, Ellen Langer, Juha Rantala, Mariano Alvarez, Katie Johnson-Camacho, Carl Pelz, Nicholas Wang, Paul Spellman, Andrea Califano, Joe Gray, Rosalie Sears. Overcoming phenotypic heterogeneity and plasticity in basal-like breast cancer through targeting adaptive pathway use. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Breast Cancer Research; Oct 17-20, 2015; Bellevue, WA. Philadelphia (PA): AACR; Mol Cancer Res 2016;14(2_Suppl):Abstract nr B52.