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Gene signatures distinguish stage-specific prostate cancer stem cells isolated from transgenic adenocarcinoma of the mouse prostate lesions and predict the malignancy of human tumors.

ABSTRACT: The relevant social and economic impact of prostate adenocarcinoma, one of the leading causes of death in men, urges critical improvements in knowledge of the pathogenesis and cure of this disease. These can also be achieved by implementing in vitro and in vivo preclinical models by taking advantage of prostate cancer stem cells (PCSCs). The best-characterized mouse model of prostate cancer is the transgenic adenocarcinoma of the mouse prostate (TRAMP) model. TRAMP mice develop a progressive lesion called prostatic intraepithelial neoplasia that evolves into adenocarcinoma (AD) between 24 and 30 weeks of age. ADs often metastasize to lymph nodes, lung, bones, and kidneys. Eventually, approximately 5% of the mice develop an androgen-independent neuroendocrine adenocarcinoma. Here we report the establishment of long-term self-renewing PCSC lines from the different stages of TRAMP progression by application of the neurosphere assay. Stage-specific prostate cell lines were endowed with the critical features expected from malignant bona fide cancer stem cells, namely, self-renewal, multipotency, and tumorigenicity. Notably, transcriptome analysis of stage-specific PCSCs resulted in the generation of well-defined, meaningful gene signatures, which identify distinct stages of human tumor progression. As such, TRAMP-derived PCSCs represent a novel and valuable preclinical model for elucidating the pathogenetic mechanisms leading to prostate adenocarcinoma and for the identification of molecular mediators to be pursued as therapeutic targets.

SUBMITTER: Mazzoleni S

PROVIDER: S-EPMC3754468 | biostudies-literature | 2013 Sep

REPOSITORIES: biostudies-literature

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Gene signatures distinguish stage-specific prostate cancer stem cells isolated from transgenic adenocarcinoma of the mouse prostate lesions and predict the malignancy of human tumors.

Mazzoleni Stefania S Jachetti Elena E Morosini Sara S Grioni Matteo M Piras Ignazio Stefano IS Pala Mauro M Bulfone Alessandro A Freschi Massimo M Bellone Matteo M Galli Rossella R

Stem cells translational medicine 20130724 9

The relevant social and economic impact of prostate adenocarcinoma, one of the leading causes of death in men, urges critical improvements in knowledge of the pathogenesis and cure of this disease. These can also be achieved by implementing in vitro and in vivo preclinical models by taking advantage of prostate cancer stem cells (PCSCs). The best-characterized mouse model of prostate cancer is the transgenic adenocarcinoma of the mouse prostate (TRAMP) model. TRAMP mice develop a progressive les ...[more]

PMID: 23884639

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Project description:BackgroundDistinguishing men with aggressive from indolent prostate cancer is critical to decisions in the management of clinically localized prostate cancer. Molecular signatures of aggressive disease could help men overcome this major clinical challenge by reducing unnecessary treatment and allowing more appropriate treatment of aggressive disease.MethodsWe performed a mass spectrometry-based proteomic analysis of normal and malignant prostate tissues from 22 men who underwent surgery for prostate cancer. Prostate cancer samples included Grade Groups (3-5), with 8 patients experiencing recurrence and 14 without evidence of recurrence with a mean of 6.8 years of follow-up. To better understand the biological pathways underlying prostate cancer aggressiveness, we performed a systems biology analysis and gene enrichment analysis. Proteins that distinguished recurrent from nonrecurrent cancer were chosen for validation by immunohistochemical analysis on tissue microarrays containing samples from a larger cohort of patients with recurrent and nonrecurrent prostate cancer.ResultsIn all, 24,037 unique peptides (false discovery rate < 1%) corresponding to 3,313 distinct proteins were identified with absolute abundance ranges spanning seven orders of magnitude. Of these proteins, 115 showed significantly (p < 0.01) different levels in tissues from recurrent versus nonrecurrent cancers. Analysis of all differentially expressed proteins in recurrent and nonrecurrent cases identified several protein networks, most prominently one in which approximately 24% of the proteins in the network were regulated by the YY1 transcription factor (adjusted p < 0.001). Strong immunohistochemical staining levels of three differentially expressed proteins, POSTN, CALR, and CTSD, on a tissue microarray validated their association with shorter patient survival.ConclusionsThe protein signatures identified could improve understanding of the molecular drivers of aggressive prostate cancer and be used as candidate prognostic biomarkers.

Project description:Current NCCN guidelines do not recommend the use of adjuvant chemotherapy for stage IA lung adenocarcinoma patients with R0 surgery. However, 25% to 40% of patients with stage IA disease experience recurrence. Stratifying patients according to the recurrence risk may tailor adjuvant therapy and surveillance imaging for those with a higher risk. However, prognostic markers are often identified by comparing high-risk and low-risk cases which might introduce bias due to the widespread interpatient heterogeneity. Here, we developed a scoring system quantifying the degree of field cancerization in adjacent normal tissues and revealed its association with disease-free survival (DFS). Methods: We recruited a cohort of 44 patients with resected stage IA lung adenocarcinoma who did not receive adjuvant therapy. Both tumor and adjacent normal tissues were obtained from each patient and subjected to capture-based targeted genomic and epigenomic profiling. A novel methylome-based scoring system namely malignancy density ratio (MD ratio) was developed based on 39 patients by comparing tumor and corresponding adjacent normal tissues of each patient. A MD score was then obtained by Wald statistics. The correlations of MD ratio, MD score, and genomic features with clinical outcome were investigated. Results: Patients with a high-risk MD ratio showed a significantly shorter postsurgical DFS compared with those with a low-risk MD ratio (HR=4.47, P=0.01). The MD ratio was not associated with T stage (P=1), tumor cell fraction (P=0.748) nor inflammatory status (p=0.548). Patients with a high-risk MD score also demonstrated an inferior DFS (HR=4.69, P=0.039). In addition, multivariate analysis revealed EGFR 19 del (HR=5.39, P=0.012) and MD score (HR= 7.90, P=0.01) were independent prognostic markers. Conclusion: The novel methylome-based scoring system, developed by comparing the signatures between tumor and corresponding adjacent normal tissues of individual patients, largely minimizes the bias of interpatient heterogeneity and reveals a robust prognostic value in patients with resected lung adenocarcinoma.

Dataset Information

Gene signatures distinguish stage-specific prostate cancer stem cells isolated from transgenic adenocarcinoma of the mouse prostate lesions and predict the malignancy of human tumors.

Publications

Gene signatures distinguish stage-specific prostate cancer stem cells isolated from transgenic adenocarcinoma of the mouse prostate lesions and predict the malignancy of human tumors.

Similar Datasets

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