Piia Mikkonen

FHOD1, a Formin Upregulated in Epithelial-Mesenchymal Transition, Participates in Cancer Cell Migration and Invasion

Cancer cells can obtain their ability to invade and metastasise by undergoing epithelial-to-mesenchymal transition (EMT). Exploiting this mechanism of cellular plasticity, malignant cells can remodel their actin cytoskeleton and down-regulate proteins needed for cell-cell contacts. The mechanisms of cytoskeletal reorganisation resulting in mesenchymal morphology and increased invasive potential are poorly understood. Actin nucleating formins have been implicated as key players in EMT. Here, we analysed which formins are altered in squamous cell carcinoma related EMT. FHOD1, a poorly studied formin, appeared to be markedly upregulated upon EMT. In human tissues FHOD1 was primarily expressed in mesenchymal cells, with little expression in epithelia. However, specimens from oral squamous cell cancers demonstrated consistent FHOD1 upregulation in mesenchymally transformed cells at the invasive edge. This upregulation was confirmed in an oral squamous carcinoma model, where FHOD1 expression was markedly increased upon EMT in a PI3K signalling dependent manner. In the EMT cells FHOD1 contributed to the spindle-shaped morphology and mesenchymal F-actin organization. Furthermore, functional assays demonstrated that FHOD1 contributes to cell migration and invasion. Finally, FHOD1 depletion reduced the ability of EMT cancer cells to form invadopodia and to degrade extracellular matrix. Our results indicate that FHOD1 participates in cytoskeletal changes in EMT. In addition, we show that FHOD1 upregulation occurs during cancer cell EMT in vivo, which indicates that FHOD1 may contribute to tumour progression.

Abstract 5302: Phenotypic heterogeneity of patient-derived tumor cells visualized by unsupervised analysis in cell-based personalized drug testing

Patient-derived tumor cells are highly variable in their morphology and molecular phenotypes and after exposure to a library of drugs their heterogeneity further increases as the cells respond to the perturbations. The complete phenotypic diversity of the tumor cells and drug response patterns may remain undetectable if only few simple readouts, such as individual biomarkers in pre-defined tumor cells, are considered. Therefore, novel techniques that capture and visualize the entire spectrum of heterogeneous phenotypic changes in ex-vivo patient-derived tumor cells are needed. Here, we applied unsupervised machine learning for comprehensive visualization of cell phenotypes with the aim to improve the analysis of image-based drug screening results. We performed high content screening of patient-derived renal clear cell carcinoma cells, exposed to 36 drugs in nine concentrations applied in 384-well format. The nuclei were stained with Hoechst and cell proliferation using Ki67, and images were acquired with a high-content imaging microscope (PE Operetta, 20x). To quantitatively describe the cell phenotypes, we used CellProfiler for cell segmentation and feature extraction and then applied a large-scale data embedding method (LargeVis) to cluster the cells based on their phenotypes. Using the clustering, we created an image-based phenotype-map to describe the phenotypic landscape. Overlaying the drug treatments on different concentrations on top of the map allowed for visualization of unique phenotypic fingerprints for each drug at the single cell resolution. Visual inspection of the phenotype-map displayed visually similar cells clustering together. Likewise, a comparison with an expert trained supervised classification indicated consistency with the phenotype-map. As expected, Ki67-positive and -negative cells as well as dying cells formed clusters. Interestingly, the phenotype-map identified sub-clusters within the Ki67-positive and -negative cells. Furthermore, the map also allowed us to adjust for classification errors occurring in the supervised classification. In conclusion, we find that phenotypic signatures provide an intuitive way of linking and comparing phenotypes of distinct populations of drug-treated cells at a single-cell level. This will reveal additional systematic information of the drug responses, complementing traditional readout, such as cell viability, by highlighting the phenotypic changes over concentrations. Citation Format: Riku Turkki, Lassi Paavolainen, Piia Mikkonen, Paivi Ostling, Peter Horvath, Vilja Pietiainen, Olli Kallioniemi. Phenotypic heterogeneity of patient-derived tumor cells visualized by unsupervised analysis in cell-based personalized drug testing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5302.

Abstract B47: Novel integrative approach to identify therapy sensitive and insensitive ovarian cancer patients.

We present a novel computational approach, Prognostic Subgroup Finder (PSFinder), to predict outcome of platinum and taxane combination therapy in high-grade serous ovarian cancer (HGS-OvCa) at treatment-naive stage. PSFinder fuses transcriptomics and clinical data to identify subgroups that have significant survival association (if such exist in the data) stratified by co-expressed markers. Thus, the results from PSFinder are readily interpretable, which is in sharp contrast to the existing methods. PSFinder uses an iterative rule-based approach to search for co-expressed genes that divide the samples into groups with significant association to survival data. The iterative process starts from all the samples in the cohort and proceeds to identify subsets of samples until the subsets cannot be further divided. PSFinder was applied to HGS-OvCa samples from patients treated with the platinum-taxane therapy available at The Cancer Genome Atlas (TCGA). We identified 61 transcripts (32 genes) that define three subgroups with outcome differences (Kaplan-Meier, log-rank test p = 0.007). The results were validated in eight independent data sets, including a prospectively collected ovarian cancer cohort. HGS-OvCa patients with dysfunctional DNA repair genes BRCA1 and/or BRCA2 have increased overall survival due to better response to cytotoxic chemotherapy. Multivariate Cox regression analysis using age, grade, stage, residual disease, BRCA1/2 mutation status, and PSFinder identified subgroups shows that the strongest predictors of HGS-OvCa patient outcome are the BRCA1/2 mutation status (p = 0.0003) and the PSFinder identified prognostic types (p = 0.02). Integration of BRCA1/2 mutation data with the PSFinder signature produced markedly improved prediction of HGS-OvCa patients who benefit from platinum and taxane treatment: None of the patients carrying BRCA1/2 mutation and predicted to be good responder by PSFinder signature died during the 5-year follow-up period, whereas 61% of the patients without BRCA1/2 mutation and predicted to be poor responders by PSFinder died within five years after diagnosis. The group of exceptional responders included approximately 8% of the patients in the TCGA cohort (Chen, et al. Cancer Research 2015). As basal-like breast cancer (BL-BrCa) and HGS-OvCa share several molecular commonalities, etiology and similar therapeutic opportunities, we applied the PSFinder HGS-OvCa predictor (32 genes) to BL-BrCa data from TCGA. Interestingly, the PSFinder signature was able to identify BL-BrCa patients that benefit from platinum-treatment (Kaplan-Meier, log-rank p = 0.017; unpublished). Additionally, we applied PSFinder signatures to other cancers, such as endometrium, melanoma, cervix, colorectal cancer and glioblastoma (unpublished). In conclusion, this contribution provides a crucially needed method for precision medicine in ovarian cancer. The use of PSFinder predicted prognostic subsets and BRCA1/2 mutation status allows identification of HGS-OvCa patients who truly benefit from platinum and taxane combination therapy and patients who require alternative treatment strategies. Extending the HGS-OvCa derived signature to other cancers further demonstrates the usefulness of the signature as well as the PSFinder approach. Identifying patients having similar molecular landscape and response to therapy regardless of tumor histology facilitates identification of subjects, such as exceptional or refractory responders, to basket trials. Citation Format: Ping Chen, Kaisa Huhtinen, Katja Kaipio, Piia Mikkonen, Viljami Aittomaki, Rony Lindell, Johanna Hynninen, Annika Auranen, Seija Grenman, Rainer Lehtonen, Olli Carpen, Sampsa Hautaniemi. Novel integrative approach to identify therapy sensitive and insensitive ovarian cancer patients. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research: Exploiting Vulnerabilities; Oct 17-20, 2015; Orlando, FL. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(2 Suppl):Abstract nr B47.

Abstract A31: High-grade serous ovarian cancer subtyping identifies pathways for targeted therapy.

Introduction: We recently identified three prognostic groups for high-grade serous ovarian cancers (HGS-OvCa) patients treated with platinum and taxane using transcriptomics and clinical data (Chen, Huhtinen, et al. Cancer Res. 2015). In this contribution we first use pathway analysis methods to identify transcript markers and pathways that drive resistance to platinum and experimentally inhibit of the key pathways to restore sensitivity to platinum. Two of the prognostic groups (Poor I and Poor II) were associated with poor survival but have distinct expression profiles. Poor II express high stromal response genes and confirms the C1 subtype characterized by Tothill et al. (2008), whereas Poor I is previously unidentified and characterized by genome-wide hypermethylation. Our objectives here are to: 1) identify key pathways for Poor I and Poor II based on transcriptomics data (data unpublished), 2) inhibit the herein identified pathways to suggest combinatorial therapeutics options for platinum resistance HGS-OvCa patients (data unpublished), 3) test the impact of hypermethylation drug Decitabine to platinum resistance in vitro (data partially unpublished). Methods: Expression levels were qRT-PCR validated using well described prospective patient cohort. The role of hypermethylation and specific pathways on cell viability were studied in vitro using commercial (CAOV4, NIHOVCAR3, OVCAR8, TYKnu) and spheroidal primary HGS-OvCa cell lines. Results: Poor I subtype presents with significantly higher methylation of CpG loci (p To evaluate signaling pathways that are associated with platinum-taxane resistance we evaluated common pathways enriched in Poor I and Poor II using the transcriptomics data available at The Cancer Genome Atlas repository. The most prominent pathway is MAPK signaling pathway of which four genes (FAS, MAPK1, AKT and NR4A1) emerged from the analysis. Pathway analysis further suggested ERK5 and AKT as upstream regulators for NR4A1 in platinum-taxane resistance in HGS-OvCa. The impact of ERK5 and AKT pathways on platinum resistance was evaluated in vitro using commercial and primary HGS-OvCa cell lines with wild-type BRCA1/2. The combination of AKT-inhibitor API-2 and Cisplatin resulted in a marked decrease in cell viability over Cisplatin alone whereas AKT-inhibitor alone had only little effect. In contrast, ERK5 inhibition with XMD8-92 combined with Cisplatin did not have an effect on HGS-OvCa cell viability. However, XMD8-92 enhanced the effect of API-2 in subset of the cell lines. Thus, we tested whether combination of the three drugs results in better response. In general, the addition of XMD8-92 did not improve the effect of API-2 and Cisplatin. However, in two highly platinum resistant cell lines, CAOV-4 and M022i primary cell line, the combination of API-2, XMD8-92 and Cisplatin produced the highest reduction in cell viability. In conclusion, we have identified pathways that are likely driving drug resistance in HGS-OvCa and tested the impact of platinum combined with targeted AKT and ERK5 inhibition in vitro. We further show that the Poor I type HGS-OvCa cells are sensitive to Decitabine. Thus, Decitabine may be an effective (combinatorial) treatment option for patients with the Poor I subtype disease. Combination of AKT and ERK5 inhibitors with platinum can also be effective for a subset of platinum resistant ovarian cancer patients. Citation Format: Kaisa Huhtinen, Ping Chen, Katja Kaipio, Piia Mikkonen, Viljami Aittomaki, Rony Lindell, Johanna Hynninen, Annika Auranen, Seija Grenman, Rainer Lehtonen, Sampsa Hautaniemi, Olli Carpen. High-grade serous ovarian cancer subtyping identifies pathways for targeted therapy. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research: Exploiting Vulnerabilities; Oct 17-20, 2015; Orlando, FL. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(2 Suppl):Abstract nr A31.

Abstract PR17: Characterization of ascites and tumor-derived ovarian cancer stem-like cells.

Intratumoral heterogeneity of high grade serous ovarian cancer (HGS-OvCa) provides a major challenge for current treatments. The non-responsiveness of ovarian cancer stem-like cells to current therapies is likely to be a reason for relapse and treatment failure. Here, we studied the ovarian cancer stem cell hypothesis and treatment failure with a population of 13 well characterized primary HGS-OvCa cell lines, 7 commonly available cell lines (Caov-3, Caov-4, TYK-nu, TYK-nu CP-r, NIHOVCAR3, OVCAR8, and SKOV3) and 29 tissue samples originated from patients with stage III and IV HGS-OvCa. Study patients were treated either with primary surgery followed by adjuvant platinum and taxane based chemotherapy (6 chemotherapy cycles, naiive samples) or neoadjuvant chemotherapy (3 cycles of platinum and taxane) followed by interval debulking surgery and 3 to 6 additional chemotherapy cycles (interval samples). Tissue samples, commonly available cell lines and primary cell lines isolated from tumor or ascites were thoroughly characterized with a panel of nine stemness associated markers: ALDH1A1, Cip2A (KIAA1524), c-Myc, Lin28A, Nanog, POU1F5B (Oct-4A), Oct3/4, Sox-2, CD133 and BMI-1. The expression of these markers was studied in two cell culture conditions; spheroidal, which is believed to promote stemness, and adherent. Additionally, we explored the effect of platinum and taxane based chemotherapy on stemness marker expression profile and furthermore the association of stemness markers with survival. The comparison of spheroidal and adherent cell growth conditions indicated that spheroidal culture conditions induce the expression of stem cell markers specifically in cultured primary HGS-OvCa cell lines. Quantitative RT-PCR data analysis showed elevated levels of a number of genes, such as ALDH1A1 (p=0.042), Cip2A (p=0.005), Oct4A (p=0.021), Sox-2 (p=0.019) and BMI-1 (p=0.003). Based on clustering analysis with primary and commonly used HGS-OvCa cell lines and tissue samples, primary cell lines and tissue samples expressed more stemness markers than commonly available cell lines. Spheroidal cells were more resistant to platinum and taxane chemotherapy than adherently grown cells and clustered closer to tissue samples suggesting stemness marker expression profile similarity between primary spheroidal cells and tissues. Platinum and taxane chemotherapy increased the expression of several stemness associated markers, most prominently ALDH1A1, in interval samples as compared to naive samples. Importantly, strong immunohistochemical ALDH1A1 staining was significantly associated with short platinum free survival (p=0.027). We further validated the expression of stemness markers in an independent ovarian cancer cohort containing 144 primary tumor samples from HGS-OvCa patients. The expression of eight stemness marker genes stratified patient samples into two clusters with distinct stem cell marker expression profiles. ALDH1A1, Cip2A, c-Myc, Lin28A, Nanog, Oct3/4, Sox-2, CD133 and BMI-1 were clustered together and were associated with shorter overall survival (log-rank test p=0.047). In conclusion, we have associated spheroidal cell growth conditions with tissue and stem cell -like profiles. Our results indicate that ALDH1A1 is one of the strongest markers of stemness in HGS-OvCa, and stem cell-like phenotype is enriched in interval samples as compared to naiive samples. Our results imply that conventional platinum taxane chemotherapy may enrich the population of stem-like cells and thus contribute to treatment failure. This abstract is also presented as Poster B65. Citation Format: Katja Kaipio, Ping Chen, Kaisa Huhtinen, Piia Mikkonen, Paivi Ostling, John Patrick Mpindi, Laura Lehtinen, Pia Roering, Taina Korpela, Krister Wennerberg, Bhagwan Yadav, Tero Aittokallio, Evgeny Kulesskiy, Johanna Hynninen, Annika Auranen, Seija Grenman, Sampsa Hautaniemi, Olli Carpen. Characterization of ascites and tumor-derived ovarian cancer stem-like cells. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research: Exploiting Vulnerabilities; Oct 17-20, 2015; Orlando, FL. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(2 Suppl):Abstract nr PR17.

Abstract B43: Xenograft mouse models for ovarian cancer

Ovarian cancer is the most lethal gynecologic malignancy in developed countries. The incidence is 1 in 70 women, and 5-year survival rate below 50 %. Although major achievements have been reached in understanding the molecular alterations underlying the disease, the discoveries need yet to be integrated into clinical practice. A major obstacle in this process may be the translation of in vitro findings into diagnostic tests and novel therapeutic approaches. Well-characterized and representative preclinical mouse models that recapitulate the heterogeneity of tumors in patients are crucial in narrowing the gap between experimental and clinical studies. The aim of this work was to test and validate various mouse xenograft models for their applicability in ovarian cancer research. We tested several xenograft mouse models using (1) established commercially available ovarian cancer cell lines, (2) primary cell lines originating from high grade serous ovarian cancers or ascitic fluid, and (3) primary or metastatic tumor tissue directly from operation. Cell growth, tumor take rate and histopathological correlation between mouse and human tumors were applied for selection of commercial cell lines in xenograft experiments into athymic nude mice. Intrabursal orthotopic inoculations were used to model early, and intraperitoneal inoculations to model late stage ovarian cancer. Translational aspects were studied by comparing the histopathology between mouse tumors and human ovarian cancer specimens and by testing the utility of serum biomarkers CA-125 and HE-4 in mouse models. The mouse xenograft models faithfully represented the morphology of human serous ovarian cancer and many of the tissue markers were similarly expressed in human and mouse tumors. Importantly, the serum biomarker analysis developed in this study allowed follow-up of the tumor burden ex vivo. Such biomarker will be useful in studying drug responses and other tumor modifying therapies. The primary cell lines were inoculated subcutaneously to immunodeficient NOD-SCID and NOG mice in order to enrich and characterize ovarian cancer initiating cells (OCICs). Due to the low rate of tumor formation of in vitro cultured OCICs, we have started to use patient derived tumor xenograft (PDTX) transplantations. In this model fresh surgical tissue, sectioned in app. 3 mm3 pieces are implanted into the flanks of immunodeficient NOG mice. The preliminary results show a take rate of 75 % with PDTXs. Histopathological comparisons of original human specimen to mouse tumors reveals that this model also recapitulates the human microenvironment in PDTX modelling. Also, the PDTX model appears to increase the probability for successfully establishing novel primary cell lines. In conclusion, mouse xenograft models offer translational and important validation methods for pre-clinical cancer drug development and diagnostics. Citation Format: Tarja Lamminen, Katja Kaipio, Piia Mikkonen, Pia Roering, Olli Carpen. Xenograft mouse models for ovarian cancer. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research: From Concept to Clinic; Sep 18-21, 2013; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2013;19(19 Suppl):Abstract nr B43.