Project description:Full title: Comprehensive Characterization of Three-Dimensional Models for Prostate Cancer Growth and Invasion in Laminin-rich Extracellular Matrix Prostate Cancer (PrCa) cells undergo acinar morphogenesis and spheroid formation in three-dimensional (3D) culture, supported by laminin-rich extracellular matrix (lrECM, Matrigel). We developed miniaturized 3D model systems that facilitate investigation of morphogenesis and invasion of normal and PrCa cell lines in lrECM. Primary and non-transformed cell lines formed round structures with strong cell-cell contacts and epithelial polarization, lumen and a complete basal lamina (BL). In contrast, most PrCa cell lines formed either defective, “mass” spheroids with incomplete BL, or invasive “stellate” structures. The bioinformatic analyses of genome-wide mRNA expression data revealed massive alteration of key functional and signaling pathways in 3D cultures, with lipid and steroid metabolism, epigenetic reprogramming, and differentiation-related transcription factors induced across all cell lines by lrECM. In invasive cells, AKT, PI3Kinase, mTOR, and hedgehog signaling pathways were most highly activated, validated by small molecule inhibitors compounds specifically targeting key regulatory molecules. Compounds against AKT and PI3kinase pathways were significantly more effective in invasive cells, compared to mass or round/normal phenotype spheroids, and monolayer culture. A severe morphologic conversion was observed in PC-3 and PC-3M cells, transforming initially round, normal-appearing epithelial spheroids into rapidly invading cell masses. Markers for EMT (epithelial-mesenchymal transition) were highly expressed already in early stage, round spheroids prior to invasive conversion, and were not further increased in invasive cells. This indicates that PrCa cells can display extraordinary plasticity. EMT may be involved in providing a metastable genotype that allows morphological transformation, but is not be required for invasive processes themselves. Total RNA was obtained from non-transformed prostate epithelial cells and prostate cancer cells cultured in monolayer and three-dimensional laminin-rich extracellular matrix (growth factor-reduced Matrigel).

Project description:Background: Breast (BCa) and prostate (PCa) cancers are hormone receptor (HR)-driven cancers. Estrogen receptor alpha (ERa) is overexpressed in 70% of diagnosed BCa patients and androgen receptor (AR) is overexpressed in 80-90% of diagnosed PCa patients. Thus, BCa and PCa patients are given therapy that reduces hormone levels or directly blocks HR activity; but most patients eventually develop treatment resistance. 15-30% of BCa patients and ≥ 30% of PCa patients that acquire treatment resistance develop tumors enriched in cancer cells with low or no HR accumulation. Furthermore, 15-20% of BCa patients and 10-20% of PCa patients are intrinsically HR-negative (HR-), and thus, have intrinsic resistance to therapy. We have previously reported that interleukin-1 (IL-1) inflammatory cytokine downregulates ERa and AR mRNA in HR-positive (HR+) BCa and PCa cell lines. Additionally, we had identified pro-survival proteins and processes upregulated by IL-1 in HR+ BCa and PCa cells, that are basally high in HR- BCa and PCa cells. Therefore, we hypothesize that IL-1 confers a conserved gene expression pattern in HR+ BCa and PCa cells that mimics conserved basal gene expression patterns in HR- BCa and PCa cells, to promote HR-independent survival and tumorigenicity. Methods: To identify changes in global gene expression we performed RNA sequencing (RNA-seq) for HR+ BCa and PCa cell lines exposed to IL-1 and for untreated HR- BCa and PCa cell lines. We confirmed expression patterns of select genes by RT-qPCR and used siRNA and/or drug inhibition to silence select genes in BCa and PCa cell lines. We also compared our gene expression data with publicly available data sets from hormone receptor-independent sublines. Finally, we performed Ingenuity Pathway Analysis (IPA) to identify signaling pathways encode by our RNA-seq data set. Results: We identified 350 genes in common between BCa and PCa cells that are induced or repressed by IL-1 in HR+ cells that are, respectively, basally high or low in HR- cells. Among these genes, we identified Sequestome-1 (SQSTM1/p62) and SRY (Sex-Determining Region Y)-Box 9 (SOX9) to be essential for survival of HR- BCa and PCa cell lines. Analysis of publicly available data indicates that p62 and SOX9 expression are elevated in hormone receptor-independent BCa and PCa sublines generated in vitro, suggesting that p62 and SOX9 have a role in acquired treatment resistance. We also assessed HR- cell line viability in response verteporfin, an FDA approved therapy for macular degeneration known to target p62, and we found that verteporfin is cytotoxic for HR- cells lines. Conclusions: Taken together, our 350 gene set can be used to identify novel therapeutic targets and/or biomarkers conserved among acquired (e.g. due to inflammation) or intrinsic hormone receptor-independent BCa and PCa.

Project description:Full title: Comprehensive Characterization of Three-Dimensional Models for Prostate Cancer Growth and Invasion in Laminin-rich Extracellular Matrix Prostate Cancer (PrCa) cells undergo acinar morphogenesis and spheroid formation in three-dimensional (3D) culture, supported by laminin-rich extracellular matrix (lrECM, Matrigel). We developed miniaturized 3D model systems that facilitate investigation of morphogenesis and invasion of normal and PrCa cell lines in lrECM. Primary and non-transformed cell lines formed round structures with strong cell-cell contacts and epithelial polarization, lumen and a complete basal lamina (BL). In contrast, most PrCa cell lines formed either defective, “mass” spheroids with incomplete BL, or invasive “stellate” structures. The bioinformatic analyses of genome-wide mRNA expression data revealed massive alteration of key functional and signaling pathways in 3D cultures, with lipid and steroid metabolism, epigenetic reprogramming, and differentiation-related transcription factors induced across all cell lines by lrECM. In invasive cells, AKT, PI3Kinase, mTOR, and hedgehog signaling pathways were most highly activated, validated by small molecule inhibitors compounds specifically targeting key regulatory molecules. Compounds against AKT and PI3kinase pathways were significantly more effective in invasive cells, compared to mass or round/normal phenotype spheroids, and monolayer culture. A severe morphologic conversion was observed in PC-3 and PC-3M cells, transforming initially round, normal-appearing epithelial spheroids into rapidly invading cell masses. Markers for EMT (epithelial-mesenchymal transition) were highly expressed already in early stage, round spheroids prior to invasive conversion, and were not further increased in invasive cells. This indicates that PrCa cells can display extraordinary plasticity. EMT may be involved in providing a metastable genotype that allows morphological transformation, but is not be required for invasive processes themselves.

Project description:Prostate cancer (PrCa) is one of the most common malignancies in Western countries. However, the pathways that promote invasion, especially in late-stage castration-resistant PrCa (CRPC), are poorly understood. Heat shock factors (HSFs) are transcriptional regulators essential for cell survival upon proteotoxic stress, and HSF1 is also identified as a driver of oncogenesis. Here, our aim was to elucidate the molecular mechanisms that contribute to CRPC and invasion. In silico analyses showed that high HSF1 expression levels correlate with poor survival and high Gleason score in PrCa. In the same data set, HSF2, which has not previously been linked to cancer, displayed decreased expression. Using 3-dimensional (3D) organotypic PrCa cultures that spontaneously undergo an invasive conversion, opposite effects of HSF1 and HSF2 were observed; tumor spheroids lacking HSF1 grew slowly, were polarized and devoid of invasive structures, and depletion of HSF2 potentiated invasiveness. In the in vivo xenograft chorioallantoic membrane model, HSF1 silencing caused tumor regression and fibrosis, and knockdown of HSF2 generated large invasive tumors, verifying the results from the 3D-cultures. Gene expression profiling revealed enrichment of genes connected to translational control when either HSF1 or HSF2 was silenced. HSF1-specific targets were associated with progression of tumorigenesis, whereas HSF2 targets were involved in focal adhesion, critical for invasion. This study provides the first evidence for HSF2 functioning in cancer, i.e. as a tumor suppressor. Moreover, human PrCa tissue microarrays demonstrated increased nuclear HSF1 expression, which significantly correlated with high-grade Gleason score. Cytoplasmic HSF1 was detected in a subset of tumors and intriguingly, correlated with decreased disease-specific survival. This was most pronounced in intermediate Gleason score 7 tumors and in metastases. We propose the use of HSF1 as a biomarker to predict PrCa outcome, thus facilitating clinical decision-making and supporting individualized treatment choices. HSF1 and HSF2 siRNA transfection was performed in triplicates (biological replicates), for 5 and 8 days prior to harvesting total RNA; and compared to PC-3 cells transfected with scrambled control siRNAs for 5 and 8 days, respectively.

Project description:Background: Inter-patient prostate cancer (PrCa) heterogeneity results in highly variable patient outcomes. Multi-purpose biomarkers to dissect this heterogeneity are urgently required to improve treatment and accelerate drug development in PrCa. Circulating biomarkers are most practical for evaluating this disease. We pursued the analytical validation and clinical qualification of blood mRNA expression arrays. Methods: Whole blood samples were collected into PaxGeneTM tubes from PrCa patients: 31 good prognosis patients selected for active surveillance (AS) and 63 advanced castration resistant PrCa (CRPC) patients. RNA was extracted, amplified, biotinylated, and hybridised to Affymetrix U133plus2 microarrays and analysis of genome-wide expression profiles were analysed using Bayesian Latent Process Decomposition (LPD). Findings: LPD analysis of the mRNA expression data divided the evaluable patients (n=94) into 4 separate groups. LPD1 and LPD2 consisted almost entirely of CRPC patients (14/14; 17/18); LPD3 (15/31) and LDP4 (12/21) comprised both AS and CRPC. Ten patients were unclassifiable by LPD analysis. LPD1 CRPC patients had significantly poorer overall survival (median 10.7 months, CI-95% 4.2-17.2) than CRPC patients in LPD2 to 4 (median 26.5 months, CI-95% 18.1-34.9, p=0.00007). LPD 1 membership remained the strongest prognostic factor in a multivariate analysis (HR 5.0, CI-95% 2.1-11.9, p=0.0002). Gene signatures in the poor prognosis LPD group 1 were associated with increased CD71+ early erythroid cells and decreased B-cell and T-cell immune response. A 9-gene signature, that was validated by RT-PCR studies, classified patients as group LPD 1 with a very low misclassification rate (1.2%). Interpretation: Poor PrCa outcome can be predicted using gene expression signatures from whole blood and merits further evaluation in predictive and pharmacodynamic biomarker studies for novel anticancer drugs including immune therapies. 107 blood samples were collected in paxgene tubes from 94 prostate cancer patients (31 good prognosis & 63 advanced castration resistant PrCa). Replicates include 9 biological replicates and four technical replicates

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