151
|
Ruggero K, Farran-Matas S, Martinez-Tebar A, Aytes A. Epigenetic Regulation in Prostate Cancer Progression. ACTA ACUST UNITED AC 2018; 4:101-115. [PMID: 29888169 PMCID: PMC5976687 DOI: 10.1007/s40610-018-0095-9] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Purpose of Review An important number of newly identified molecular alterations in prostate cancer affect gene encoding master regulators of chromatin biology epigenetic regulation. This review will provide an updated view of the key epigenetic mechanisms underlying prostate cancer progression, therapy resistance, and potential actionable mechanisms and biomarkers. Recent Findings Key players in chromatin biology and epigenetic master regulators has been recently described to be crucially altered in metastatic CRPC and tumors that progress to AR independency. As such, epigenetic dysregulation represents a driving mechanism in the reprograming of prostate cancer cells as they lose AR-imposed identity. Summary Chromatin integrity and accessibility for transcriptional regulation are key features altered in cancer progression, and particularly relevant in nuclear hormone receptor-driven tumors like prostate cancer. Understanding how chromatin remodeling dictates prostate development and how its deregulation contributes to prostate cancer onset and progression may improve risk stratification and treatment selection for prostate cancer patients.
Collapse
Affiliation(s)
- Katia Ruggero
- Programs of Molecular Mechanisms and Experimental Therapeutics in Oncology (ONCOBell), Catalan Institute of Oncology, Bellvitge Institute for Biomedical Research, Granvia de l'Hopitalet, 199 08908, L'Hospitalet de Llobregat, 08907 Barcelona, Spain
| | - Sonia Farran-Matas
- Programs of Molecular Mechanisms and Experimental Therapeutics in Oncology (ONCOBell), Catalan Institute of Oncology, Bellvitge Institute for Biomedical Research, Granvia de l'Hopitalet, 199 08908, L'Hospitalet de Llobregat, 08907 Barcelona, Spain
| | - Adrian Martinez-Tebar
- Programs of Molecular Mechanisms and Experimental Therapeutics in Oncology (ONCOBell), Catalan Institute of Oncology, Bellvitge Institute for Biomedical Research, Granvia de l'Hopitalet, 199 08908, L'Hospitalet de Llobregat, 08907 Barcelona, Spain
| | - Alvaro Aytes
- Programs of Molecular Mechanisms and Experimental Therapeutics in Oncology (ONCOBell), Catalan Institute of Oncology, Bellvitge Institute for Biomedical Research, Granvia de l'Hopitalet, 199 08908, L'Hospitalet de Llobregat, 08907 Barcelona, Spain.,Programs of Cancer Therapeutics Resistance (ProCURE), Catalan Institute of Oncology, Bellvitge Institute for Biomedical Research, L'Hospitalet de Llobregat, 08907 Barcelona, Spain
| |
Collapse
|
152
|
Ding H, Douglass EF, Sonabend AM, Mela A, Bose S, Gonzalez C, Canoll PD, Sims PA, Alvarez MJ, Califano A. Quantitative assessment of protein activity in orphan tissues and single cells using the metaVIPER algorithm. Nat Commun 2018; 9:1471. [PMID: 29662057 PMCID: PMC5902599 DOI: 10.1038/s41467-018-03843-3] [Citation(s) in RCA: 68] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2017] [Accepted: 03/13/2018] [Indexed: 12/30/2022] Open
Abstract
We and others have shown that transition and maintenance of biological states is controlled by master regulator proteins, which can be inferred by interrogating tissue-specific regulatory models (interactomes) with transcriptional signatures, using the VIPER algorithm. Yet, some tissues may lack molecular profiles necessary for interactome inference (orphan tissues), or, as for single cells isolated from heterogeneous samples, their tissue context may be undetermined. To address this problem, we introduce metaVIPER, an algorithm designed to assess protein activity in tissue-independent fashion by integrative analysis of multiple, non-tissue-matched interactomes. This assumes that transcriptional targets of each protein will be recapitulated by one or more available interactomes. We confirm the algorithm's value in assessing protein dysregulation induced by somatic mutations, as well as in assessing protein activity in orphan tissues and, most critically, in single cells, thus allowing transformation of noisy and potentially biased RNA-Seq signatures into reproducible protein-activity signatures.
Collapse
Affiliation(s)
- Hongxu Ding
- Department of Systems Biology, Columbia University, New York, NY, 10032, USA
- Department of Biological Sciences, Columbia University, New York, NY, 10027, USA
| | - Eugene F Douglass
- Department of Systems Biology, Columbia University, New York, NY, 10032, USA
| | - Adam M Sonabend
- Department of Pathology and Cell Biology, Columbia University, New York, NY, 10032, USA
| | - Angeliki Mela
- Department of Pathology and Cell Biology, Columbia University, New York, NY, 10032, USA
| | - Sayantan Bose
- Department of Systems Biology, Columbia University, New York, NY, 10032, USA
- GlaxoSmithKline, King of Prussia, PA, 19406, USA
| | - Christian Gonzalez
- Department of Systems Biology, Columbia University, New York, NY, 10032, USA
- Amsterdam Neuroscience, Amsterdam, 1081, The Netherlands
| | - Peter D Canoll
- Department of Pathology and Cell Biology, Columbia University, New York, NY, 10032, USA
| | - Peter A Sims
- Department of Systems Biology, Columbia University, New York, NY, 10032, USA
| | - Mariano J Alvarez
- Department of Systems Biology, Columbia University, New York, NY, 10032, USA.
- DarwinHealth Inc, New York, NY, 10032, USA.
| | - Andrea Califano
- Department of Systems Biology, Columbia University, New York, NY, 10032, USA.
- DarwinHealth Inc, New York, NY, 10032, USA.
- Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, 10032, USA.
- J.P. Sulzberger Columbia Genome Center, Columbia University, New York, NY, 10032, USA.
- Department of Biomedical Informatics, Columbia University, New York, NY, 10032, USA.
- Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY, 10032, USA.
| |
Collapse
|
153
|
LSD1 activates a lethal prostate cancer gene network independently of its demethylase function. Proc Natl Acad Sci U S A 2018; 115:E4179-E4188. [PMID: 29581250 DOI: 10.1073/pnas.1719168115] [Citation(s) in RCA: 142] [Impact Index Per Article: 23.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Medical castration that interferes with androgen receptor (AR) function is the principal treatment for advanced prostate cancer. However, clinical progression is universal, and tumors with AR-independent resistance mechanisms appear to be increasing in frequency. Consequently, there is an urgent need to develop new treatments targeting molecular pathways enriched in lethal prostate cancer. Lysine-specific demethylase 1 (LSD1) is a histone demethylase and an important regulator of gene expression. Here, we show that LSD1 promotes the survival of prostate cancer cells, including those that are castration-resistant, independently of its demethylase function and of the AR. Importantly, this effect is explained in part by activation of a lethal prostate cancer gene network in collaboration with LSD1's binding protein, ZNF217. Finally, that a small-molecule LSD1 inhibitor-SP-2509-blocks important demethylase-independent functions and suppresses castration-resistant prostate cancer cell viability demonstrates the potential of LSD1 inhibition in this disease.
Collapse
|
154
|
Li L, Wu D, Yu Q, Li L, Wu P. Prognostic value of FOXM1 in solid tumors: a systematic review and meta-analysis. Oncotarget 2018; 8:32298-32308. [PMID: 28427178 PMCID: PMC5458285 DOI: 10.18632/oncotarget.15764] [Citation(s) in RCA: 51] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2016] [Accepted: 02/20/2017] [Indexed: 12/21/2022] Open
Abstract
Accumulated studies have provided controversial evidences of the association between Forkhead Box M1 (FOXM1) expression and survival of human solid tumors. To address this inconsistency, we performed a meta-analysis with 23 studies identified from PubMed and Medline. We found elevated FOXM1-protein expression was significantly associated with worse 3-year overall survival (OS) (OR = 3.30, 95% CI = 2.56 to 4.25, P < 0.00001) 5-year OS (OR =3.35, 95% CI = 2.64 to 4.26, P < 0.00001) and 10-year OS (OR = 5.24, 95% CI = 2.61 to 10.52, P < 0.00001) of human solid tumors. Similar results were observed when disease free survival (DFS) were analyzed. Subgroup analysis showed that FOXM1 overexpression was associated with poor prognosis of colorectal cancer, gastric cancer, hepatic cancer, lung cancer and ovarian cancer. High expression level of FOXM1 was also associated with advanced tumor stage. In conclusion, elevated FOXM1 expression is associated with poor survival in most solid tumors. FOXM1 is a potential biomarker for prognosis prediction and a promising therapeutic target in human solid tumors.
Collapse
Affiliation(s)
- Lijun Li
- Department of Surgery, Hangzhou Xixi Hospital, Hangzhou, China
| | - Dang Wu
- Department of Radiation Oncology, Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
| | - Qun Yu
- Fourth Ward of Neurosurgery, Division of Nursing, Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
| | - Lingdi Li
- Department of Oncology, Hangzhou Cancer Hospital, Hangzhou, China
| | - Pin Wu
- Department of Thoracic Surgery, Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
| |
Collapse
|
155
|
Jurmeister S, Ramos-Montoya A, Sandi C, Pértega-Gomes N, Wadhwa K, Lamb AD, Dunning MJ, Attig J, Carroll JS, Fryer LG, Felisbino SL, Neal DE. Identification of potential therapeutic targets in prostate cancer through a cross-species approach. EMBO Mol Med 2018; 10:e8274. [PMID: 29437778 PMCID: PMC5840539 DOI: 10.15252/emmm.201708274] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2017] [Revised: 01/01/2018] [Accepted: 01/08/2018] [Indexed: 12/14/2022] Open
Abstract
Genetically engineered mouse models of cancer can be used to filter genome-wide expression datasets generated from human tumours and to identify gene expression alterations that are functionally important to cancer development and progression. In this study, we have generated RNAseq data from tumours arising in two established mouse models of prostate cancer, PB-Cre/PtenloxP/loxP and p53loxP/loxPRbloxP/loxP, and integrated this with published human prostate cancer expression data to pinpoint cancer-associated gene expression changes that are conserved between the two species. To identify potential therapeutic targets, we then filtered this information for genes that are either known or predicted to be druggable. Using this approach, we revealed a functional role for the kinase MELK as a driver and potential therapeutic target in prostate cancer. We found that MELK expression was required for cell survival, affected the expression of genes associated with prostate cancer progression and was associated with biochemical recurrence.
Collapse
Affiliation(s)
- Sarah Jurmeister
- Uro-oncology Research Group, CRUK Cambridge Institute, Cambridge, UK
| | | | - Chiranjeevi Sandi
- Uro-oncology Research Group, CRUK Cambridge Institute, Cambridge, UK
| | - Nelma Pértega-Gomes
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - Karan Wadhwa
- Uro-oncology Research Group, CRUK Cambridge Institute, Cambridge, UK
| | - Alastair D Lamb
- Uro-oncology Research Group, CRUK Cambridge Institute, Cambridge, UK
- Department of Urology, University of Cambridge, Cambridge, UK
- Department of Oncology, Addenbrooke's Hospital, Cambridge, UK
| | - Mark J Dunning
- Bioinformatics Core Facility, CRUK Cambridge Institute, Cambridge, UK
| | - Jan Attig
- Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK
- MRC-Laboratory of Molecular Biology, Cambridge, UK
| | - Jason S Carroll
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
| | - Lee Gd Fryer
- Uro-oncology Research Group, CRUK Cambridge Institute, Cambridge, UK
| | - Sérgio L Felisbino
- Department of Morphology, Institute of Biosciences of Botucatu, Sao Paulo State University (UNESP), Sao Paulo, Brazil
| | - David E Neal
- Uro-oncology Research Group, CRUK Cambridge Institute, Cambridge, UK
- Department of Urology, University of Cambridge, Cambridge, UK
- Department of Oncology, Addenbrooke's Hospital, Cambridge, UK
| |
Collapse
|
156
|
Li P, You S, Nguyen C, Wang Y, Kim J, Sirohi D, Ziembiec A, Luthringer D, Lin SC, Daskivich T, Wu J, Freeman MR, Saouaf R, Li D, Kim HL. Genes involved in prostate cancer progression determine MRI visibility. Am J Cancer Res 2018; 8:1752-1765. [PMID: 29556354 PMCID: PMC5858498 DOI: 10.7150/thno.23180] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2017] [Accepted: 01/01/2018] [Indexed: 01/08/2023] Open
Abstract
MRI is used to image prostate cancer and target tumors for biopsy or therapeutic ablation. The objective was to understand the biology of tumors not visible on MRI that may go undiagnosed and untreated. Methods: Prostate cancers visible or invisible on multiparametric MRI were macrodissected and examined by RNAseq. Differentially expressed genes (DEGs) based on MRI visibility status were cross-referenced with publicly available gene expression databases to identify genes associated with disease progression. Genes with potential roles in determining MRI visibility and disease progression were knocked down in murine prostate cancer xenografts, and imaged by MRI. Results: RNAseq identified 1,654 DEGs based on MRI visibility status. Comparison of DEGs based on MRI visibility and tumor characteristics revealed that Gleason score (dissimilarity test, p<0.0001) and tumor size (dissimilarity test, p<0.039) did not completely determine MRI visibility. Genes in previously reported prognostic signatures significantly correlated with MRI visibility suggesting that MRI visibility was prognostic. Cross-referencing DEGs with external datasets identified four genes (PHYHD1, CENPF, ALDH2, GDF15) that predict MRI visibility, progression free survival and metastatic deposits. Genetic modification of a human prostate cancer cell line to induce miR-101 and suppress CENPF decreased cell migration and invasion. As prostate cancer xenografts in mice, these cells had decreased visibility on diffusion weighted MRI and decreased perfusion, which correlated with immunostaining showing decreased cell density and proliferation. Conclusions: Genes involved in prostate cancer prognosis and metastasis determine MRI visibility, indicating that MRI visibility has prognostic significance. MRI visibility was associated with genetic features linked to poor prognosis.
Collapse
|
157
|
Barros-Silva D, Costa-Pinheiro P, Duarte H, Sousa EJ, Evangelista AF, Graça I, Carneiro I, Martins AT, Oliveira J, Carvalho AL, Marques MM, Henrique R, Jerónimo C. MicroRNA-27a-5p regulation by promoter methylation and MYC signaling in prostate carcinogenesis. Cell Death Dis 2018; 9:167. [PMID: 29415999 PMCID: PMC5833437 DOI: 10.1038/s41419-017-0241-y] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2017] [Revised: 12/10/2017] [Accepted: 12/18/2017] [Indexed: 12/14/2022]
Abstract
Upregulation of MYC and miRNAs deregulation are common in prostate cancer (PCa). Overactive MYC may cause miRNAs’ expression deregulation through transcriptional and post-transcriptional mechanisms and epigenetic alterations are also involved in miRNAs dysregulation. Herein, we aimed to elucidate the role of regulatory network between MYC and miRNAs in prostate carcinogenesis. MYC expression was found upregulated in PCa cases and matched precursor lesions. MicroRNA’s microarray analysis of PCa samples with opposed MYC levels identified miRNAs significantly overexpressed in high-MYC PCa. However, validation of miR-27a-5p in primary prostate tissues disclosed downregulation in PCa, instead, correlating with aberrant promoter methylation. In a series of castration-resistant PCa (CRPC) cases, miR-27a-5p was upregulated, along with promoter hypomethylation. MYC and miR-27a-5p expression levels in LNCaP and PC3 cells mirrored those observed in hormone-naíve PCa and CRPC, respectively. ChIP analysis showed that miR-27a-5p expression is only regulated by c-Myc in the absence of aberrant promoter methylation. MiR-27a-5p knockdown in PC3 cells promoted cell growth, whereas miRNA forced expression in LNCaP and stable MYC-knockdown PC3 cells attenuated the malignant phenotype, suggesting a tumor suppressive role for miR-27a-5p. Furthermore, miR-27a-5p upregulation decreased EGFR/Akt1/mTOR signaling. We concluded that miR-27a-5p is positively regulated by MYC, and its silencing due to aberrant promoter methylation occurs early in prostate carcinogenesis, concomitantly with loss of MYC regulatory activity. Our results further suggest that along PCa progression, miR-27a-5p promoter becomes hypomethylated, allowing for MYC to resume its regulatory activity. However, the altered cellular context averts miR-27a-5p from successfully accomplishing its tumor suppressive function at this stage of disease.
Collapse
Affiliation(s)
- Daniela Barros-Silva
- Cancer Biology and Epigenetics Group, IPO Porto Research Center (CI-IPOP), Portuguese Oncology Institute of Porto (IPO Porto), Porto, Portugal.,Master in Oncology, Institute of Biomedical Sciences Abel Salazar-University of Porto (ICBAS-UP), Porto, Portugal
| | - Pedro Costa-Pinheiro
- Cancer Biology and Epigenetics Group, IPO Porto Research Center (CI-IPOP), Portuguese Oncology Institute of Porto (IPO Porto), Porto, Portugal
| | - Henrique Duarte
- Cancer Biology and Epigenetics Group, IPO Porto Research Center (CI-IPOP), Portuguese Oncology Institute of Porto (IPO Porto), Porto, Portugal
| | - Elsa Joana Sousa
- Cancer Biology and Epigenetics Group, IPO Porto Research Center (CI-IPOP), Portuguese Oncology Institute of Porto (IPO Porto), Porto, Portugal
| | | | - Inês Graça
- Cancer Biology and Epigenetics Group, IPO Porto Research Center (CI-IPOP), Portuguese Oncology Institute of Porto (IPO Porto), Porto, Portugal
| | - Isa Carneiro
- Cancer Biology and Epigenetics Group, IPO Porto Research Center (CI-IPOP), Portuguese Oncology Institute of Porto (IPO Porto), Porto, Portugal.,Master in Oncology, Institute of Biomedical Sciences Abel Salazar-University of Porto (ICBAS-UP), Porto, Portugal
| | - Ana Teresa Martins
- Cancer Biology and Epigenetics Group, IPO Porto Research Center (CI-IPOP), Portuguese Oncology Institute of Porto (IPO Porto), Porto, Portugal.,Master in Oncology, Institute of Biomedical Sciences Abel Salazar-University of Porto (ICBAS-UP), Porto, Portugal
| | - Jorge Oliveira
- Department of Urology, Portuguese Oncology Institute of Porto (IPO Porto), Rua Dr. António Bernardino de Almeida, 4200-072, Porto, Portugal
| | - André L Carvalho
- Molecular Oncology Research Center, Barretos Cancer Hospital, Barretos, São Paulo, Brazil
| | - Márcia M Marques
- Molecular Oncology Research Center, Barretos Cancer Hospital, Barretos, São Paulo, Brazil.,Barretos School of Health Sciences, Barretos, São Paulo, Brazil
| | - Rui Henrique
- Cancer Biology and Epigenetics Group, IPO Porto Research Center (CI-IPOP), Portuguese Oncology Institute of Porto (IPO Porto), Porto, Portugal.,Department of Pathology, Portuguese Oncology Institute of Porto (IPO Porto), Porto, Portugal.,Department of Pathology and Molecular Immunology, Institute of Biomedical Sciences Abel Salazar (ICBAS)-University of Porto, Porto, Portugal
| | - Carmen Jerónimo
- Cancer Biology and Epigenetics Group, IPO Porto Research Center (CI-IPOP), Portuguese Oncology Institute of Porto (IPO Porto), Porto, Portugal. .,Department of Pathology and Molecular Immunology, Institute of Biomedical Sciences Abel Salazar (ICBAS)-University of Porto, Porto, Portugal.
| |
Collapse
|
158
|
Sang M, Hulsurkar M, Zhang X, Song H, Zheng D, Zhang Y, Li M, Xu J, Zhang S, Ittmann M, Li W. GRK3 is a direct target of CREB activation and regulates neuroendocrine differentiation of prostate cancer cells. Oncotarget 2018; 7:45171-45185. [PMID: 27191986 PMCID: PMC5216714 DOI: 10.18632/oncotarget.9359] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2015] [Accepted: 04/23/2016] [Indexed: 01/22/2023] Open
Abstract
Neuroendocrine prostate cancer (NEPC) is an aggressive subtype of prostate cancer that commonly arises through neuroendocrine differentiation (NED) of prostate adenocarcinoma (PAC) after therapy, such as radiation therapy and androgen deprivation treatment (ADT). No effective therapeutic is available for NEPC and its molecular mechanisms remain poorly understood. We have reported that G protein-coupled receptor kinase 3 (GRK3, also called ADRBK2) promotes prostate cancer progression. In this study, we demonstrate that the ADT-activated cAMP response element binding protein (CREB) directly targets and induces GRK3. We show GRK3 expression is higher in NEPC than in PAC cells and mouse models, and it positively correlates with the expression and activity of CREB in human prostate cancers. Notably, overexpression of GRK3 in PAC cells increased the expression of NE markers in a kinase activity dependent manner. Conversely, silencing GRK3 blocked CREB-induced NED in PAC cells, reversed NE phenotypes and inhibited proliferation of NEPC cells. Taken together, these results indicate that GRK3 is a new critical activator of NE phenotypes and mediator of CREB activation in promoting NED of prostate cancer cells.
Collapse
Affiliation(s)
- Meixiang Sang
- Texas Therapeutics Institute, Brown Foundation Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA.,Tumor Research Institute, the Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | - Mohit Hulsurkar
- Texas Therapeutics Institute, Brown Foundation Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA.,Graduate School of Biomedical Sciences, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Xiaochong Zhang
- Texas Therapeutics Institute, Brown Foundation Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA.,Tumor Research Institute, the Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | - Haiping Song
- Texas Therapeutics Institute, Brown Foundation Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA.,Breast and Thyroid surgery center, The Union Hospital of Tongji Medical College, Huazhong University of science and technology, Wuhan, China
| | - Dayong Zheng
- Texas Therapeutics Institute, Brown Foundation Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA.,Department of Medical Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Yan Zhang
- Texas Therapeutics Institute, Brown Foundation Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA.,The Union Hospital of Tongji Medical College, Huazhong University of science and technology, Wuhan, China
| | - Min Li
- Department of Pathology and Laboratory Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Jianming Xu
- Department of Molecular and Cell Biology, Baylor College of Medicine, Houston, TX, USA
| | - Songlin Zhang
- Department of Pathology and Laboratory Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Michael Ittmann
- Department of Pathology and Immunology, Baylor College of Medicine, and Michael E. DeBakey VAMC, Houston, TX, USA
| | - Wenliang Li
- Texas Therapeutics Institute, Brown Foundation Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA.,Graduate School of Biomedical Sciences, University of Texas Health Science Center at Houston, Houston, TX, USA.,Division of Oncology, Department of Internal Medicine, and Memorial Herman Cancer Center, University of Texas Health Science Center at Houston, Houston, TX, USA
| |
Collapse
|
159
|
Treatment with docetaxel in combination with Aneustat leads to potent inhibition of metastasis in a patient-derived xenograft model of advanced prostate cancer. Br J Cancer 2018; 118:802-812. [PMID: 29381682 PMCID: PMC5877435 DOI: 10.1038/bjc.2017.474] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2017] [Revised: 11/30/2017] [Accepted: 12/01/2017] [Indexed: 01/09/2023] Open
Abstract
Background: Docetaxel used for first-line treatment of advanced prostate cancer (PCa) is only marginally effective. We previously showed, using the LTL-313H subrenal capsule patient-derived metastatic PCa xenograft model, that docetaxel combined with Aneustat (OMN54), a multivalent plant-derived therapeutic, led to marked synergistic tumour growth inhibition. Here, we investigated the effect of docetaxel+Aneustat on metastasis. Methods: C4-2 cells were incubated with docetaxel, Aneustat and docetaxel+Aneustat to assess effects on cell migration. The LTL-313H model, similarly treated, was analysed for effects on lung micro-metastasis and kidney invasion. The LTL-313H gene expression profile was compared with profiles of PCa patients (obtained from Oncomine) and subjected to IPA to determine involvement of cancer driver genes. Results: Docetaxel+Aneustat markedly inhibited C4-2 cell migration and LTL-313H lung micro-metastasis/kidney invasion. Oncomine analysis indicated that treatment with docetaxel+Aneustat was associated with improved patient outcome. The drug combination markedly downregulated expression of cancer driver genes such as FOXM1 (and FOXM1-target genes). FOXM1 overexpression reduced the anti-metastatic activity of docetaxel+Aneustat. Conclusions: Docetaxel+Aneustat can inhibit PCa tissue invasion and metastasis. This activity appears to be based on reduced expression of cancer driver genes such as FOXM1. Use of docetaxel+Aneustat may provide a new, more effective regimen for therapy of metastatic PCa.
Collapse
|
160
|
Zhou Z, Cheng Y, Jiang Y, Liu S, Zhang M, Liu J, Zhao Q. Ten hub genes associated with progression and prognosis of pancreatic carcinoma identified by co-expression analysis. Int J Biol Sci 2018; 14:124-136. [PMID: 29483831 PMCID: PMC5821034 DOI: 10.7150/ijbs.22619] [Citation(s) in RCA: 110] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2017] [Accepted: 12/21/2017] [Indexed: 12/16/2022] Open
Abstract
Since the five-year survival rate is less than 5%, pancreatic ductal adenocarcinoma (PDAC) remains the 4th cause of cancer-related death. Although PDAC has been repeatedly researched in recent years, it is still predicted to be the second leading cause of cancer death by year 2030. In our study, the differentially expressed genes in dataset GSE62452 were used to construct a co-expression network by WGCNA. The yellow module related to grade of PDAC was screened. Combined with co-expression network and PPI network, 36 candidates were screened. After survival and regression analysis by using GSE62452 and TCGA dataset, we identified 10 real hub genes (CCNA2, CCNB1, CENPF, DLGAP5, KIF14, KIF23, NEK2, RACGAP1, TPX2 and UBE2C) tightly related to progression of PDAC. According to Oncomine database and The Human Protein Atlas (HPA), we found that all real hub genes were overexpressed in pancreatic carcinoma compared with normal tissues on transcriptional and translational level. ROC curve was plotted and AUC was calculated to distinguish recurrent and non-recurrent PDAC and every AUC of the real hub gene was greater than 0.5. Finally, functional enrichment analysis and gene set enrichment (GSEA) was performed and both of them showed the cell cycle played a vital role in PDAC.
Collapse
Affiliation(s)
- Zhou Zhou
- Department of Gastroenterology, Hubei Clinical Center and Key Lab of Intestinal and Colorectal Diseases, Zhongnan Hospital of Wuhan University
| | - Yian Cheng
- Department of Gastroenterology, Renming Hospital of Wuhan University
| | - Yinan Jiang
- Department of Gastrointestinal Surgery, Zhongnan Hospital of Wuhan University
| | - Shi Liu
- Department of Gastroenterology, Hubei Clinical Center and Key Lab of Intestinal and Colorectal Diseases, Zhongnan Hospital of Wuhan University
| | - Meng Zhang
- Department of Gastroenterology, Hubei Clinical Center and Key Lab of Intestinal and Colorectal Diseases, Zhongnan Hospital of Wuhan University
| | - Jing Liu
- Department of Gastroenterology, Hubei Clinical Center and Key Lab of Intestinal and Colorectal Diseases, Zhongnan Hospital of Wuhan University
| | - Qiu Zhao
- Department of Gastroenterology, Hubei Clinical Center and Key Lab of Intestinal and Colorectal Diseases, Zhongnan Hospital of Wuhan University
| |
Collapse
|
161
|
Regulation of UHRF1 by dual-strand tumor-suppressor microRNA-145 (miR-145-5p and miR-145-3p): Inhibition of bladder cancer cell aggressiveness. Oncotarget 2017; 7:28460-87. [PMID: 27072587 PMCID: PMC5053739 DOI: 10.18632/oncotarget.8668] [Citation(s) in RCA: 92] [Impact Index Per Article: 13.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2016] [Accepted: 03/28/2016] [Indexed: 12/11/2022] Open
Abstract
In microRNA (miRNA) biogenesis, the guide-strand of miRNA integrates into the RNA induced silencing complex (RISC), whereas the passenger-strand is inactivated through degradation. Analysis of our miRNA expression signature of bladder cancer (BC) by deep-sequencing revealed that microRNA (miR)-145-5p (guide-strand) and miR-145-3p (passenger-strand) were significantly downregulated in BC tissues. It is well known that miR-145-5p functions as a tumor suppressor in several types of cancer. However, the impact of miR-145-3p on cancer cells is still ambiguous. The aim of the present study was to investigate the functional significance of miR-145-3p and BC oncogenic pathways and targets regulated by miR-145-5p/miR-145-3p. Ectopic expression of either miR-145-5p or miR-145-3p in BC cells significantly suppressed cancer cell growth, migration and invasion and it also induced apoptosis. The gene encoding ubiquitin-like with PHD and ring finger domains 1 (UHRF1) was a direct target of these miRNAs. Silencing of UHRF1 induced apoptosis and inhibited cancer cell proliferation, migration, and invasion in BC cells. In addition, overexpressed UHRF1 was confirmed in BC clinical specimens, and the high UHRF1 expression group showed a significantly poorer cause specific survival rate in comparison with the low expression group. Taken together, our present data demonstrated that both strands of miR-145 (miR-145-5p: guide-strand and miR-145-3p: passenger-strand) play pivotal roles in BC cells by regulating UHRF1. The identification of the molecular target of a tumor suppressive miRNAs provides novel insights into the potential mechanisms of BC oncogenesis and suggests novel therapeutic strategies.
Collapse
|
162
|
Newton Y, Novak AM, Swatloski T, McColl DC, Chopra S, Graim K, Weinstein AS, Baertsch R, Salama SR, Ellrott K, Chopra M, Goldstein TC, Haussler D, Morozova O, Stuart JM. TumorMap: Exploring the Molecular Similarities of Cancer Samples in an Interactive Portal. Cancer Res 2017; 77:e111-e114. [PMID: 29092953 DOI: 10.1158/0008-5472.can-17-0580] [Citation(s) in RCA: 49] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2017] [Revised: 06/14/2017] [Accepted: 08/07/2017] [Indexed: 01/15/2023]
Abstract
Vast amounts of molecular data are being collected on tumor samples, which provide unique opportunities for discovering trends within and between cancer subtypes. Such cross-cancer analyses require computational methods that enable intuitive and interactive browsing of thousands of samples based on their molecular similarity. We created a portal called TumorMap to assist in exploration and statistical interrogation of high-dimensional complex "omics" data in an interactive and easily interpretable way. In the TumorMap, samples are arranged on a hexagonal grid based on their similarity to one another in the original genomic space and are rendered with Google's Map technology. While the important feature of this public portal is the ability for the users to build maps from their own data, we pre-built genomic maps from several previously published projects. We demonstrate the utility of this portal by presenting results obtained from The Cancer Genome Atlas project data. Cancer Res; 77(21); e111-4. ©2017 AACR.
Collapse
Affiliation(s)
- Yulia Newton
- Department of Biomolecular Engineering and Bioinformatics, University of California, Santa Cruz, California
| | - Adam M Novak
- Department of Biomolecular Engineering and Bioinformatics, University of California, Santa Cruz, California
| | - Teresa Swatloski
- Department of Biomolecular Engineering and Bioinformatics, University of California, Santa Cruz, California
| | - Duncan C McColl
- Department of Biomolecular Engineering and Bioinformatics, University of California, Santa Cruz, California
| | - Sahil Chopra
- Department of Biomolecular Engineering and Bioinformatics, University of California, Santa Cruz, California.,Stanford University, Stanford, California
| | - Kiley Graim
- Department of Biomolecular Engineering and Bioinformatics, University of California, Santa Cruz, California
| | - Alana S Weinstein
- Department of Biomolecular Engineering and Bioinformatics, University of California, Santa Cruz, California
| | - Robert Baertsch
- Department of Biomolecular Engineering and Bioinformatics, University of California, Santa Cruz, California
| | - Sofie R Salama
- Department of Biomolecular Engineering and Bioinformatics, University of California, Santa Cruz, California
| | - Kyle Ellrott
- Department of Biomolecular Engineering and Bioinformatics, University of California, Santa Cruz, California.,Oregon Health and Science University, Portland, Oregon
| | - Manu Chopra
- Department of Biomolecular Engineering and Bioinformatics, University of California, Santa Cruz, California.,Pacific Collegiate School, Santa Cruz, California
| | - Theodore C Goldstein
- Department of Biomolecular Engineering and Bioinformatics, University of California, Santa Cruz, California.,Hematology-oncology Department, University of California, San Francisco, California
| | - David Haussler
- Department of Biomolecular Engineering and Bioinformatics, University of California, Santa Cruz, California
| | - Olena Morozova
- Department of Biomolecular Engineering and Bioinformatics, University of California, Santa Cruz, California
| | - Joshua M Stuart
- Department of Biomolecular Engineering and Bioinformatics, University of California, Santa Cruz, California.
| |
Collapse
|
163
|
Deconvolution of Transcriptional Networks in Post-Traumatic Stress Disorder Uncovers Master Regulators Driving Innate Immune System Function. Sci Rep 2017; 7:14486. [PMID: 29101382 PMCID: PMC5670244 DOI: 10.1038/s41598-017-15221-y] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2017] [Accepted: 10/23/2017] [Indexed: 01/05/2023] Open
Abstract
Post-Traumatic Stress Disorder (PTSD) is a psychiatric disorder that develops in individuals experiencing a shocking incident, but the underlying disease susceptibility gene networks remain poorly understood. Breen et al. conducted a Weighted Gene Co-expression Network Analysis on PTSD, and identified a dysregulated innate immune module associated with PTSD development. To further identify the Master Regulators (MRs) driving the network function, here we deconvoluted the transcriptional networks on the same datasets using ARACNe (Algorithm for Reconstruction of Accurate Cellular Networks) followed by protein activity analysis. We successfully identified several MRs including SOX3, TNFAIP3, TRAFD1, POU3F3, STAT2, and PML that govern the expression of a large collection of genes. Transcription factor binding site enrichment analysis verified the binding of these MRs to their predicted targets. Notably, the sub-networks regulated by TNFAIP3, TRAFD1 and PML are involved in innate immune response, suggesting that these MRs may correlate with the innate immune module identified by Breen et al. These findings were replicated in an independent dataset generated on expression microarrays. In conclusion, our analysis corroborated previous findings that innate immunity may be involved in the progression of PTSD, yet also identified candidate MRs driving the disease progression in the innate immunity pathways.
Collapse
|
164
|
Yeganeh PN, Richardson C, Bahrani-Mostafavi Z, Tait DL, Mostafavi MT. Dysregulation of AKT3 along with a small panel of mRNAs stratifies high-grade serous ovarian cancer from both normal epithelia and benign tumor tissues. Genes Cancer 2017; 8:784-798. [PMID: 29321820 PMCID: PMC5755724 DOI: 10.18632/genesandcancer.164] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2017] [Accepted: 12/01/2017] [Indexed: 01/14/2023] Open
Abstract
Screening methods of High-Grade Serous Ovarian Cancer (HGSOC) lack specificity and sensitivity, partly due to benign tumors producing false-positive findings. We utilized a differential expression analysis pipeline on malignant tumor (MT) and normal epithelial (NE) samples, and also filtered the results to discriminate between MT and benign tumor (BT). We report that a panel of 26 dysregulated genes stratifies MT from both BT and NE. We further validated our findings by utilizing unsupervised clustering methods on two independent datasets. We show that the 26-genes panel completely distinguishes HGSOC from NE, and produces a more accurate classification between HGSOC and BT. Pathway analysis reveals that AKT3 is of particular significance, because of its high fold change and appearance in the majority of the dysregulated pathways. mRNA patterns of AKT3 suggest essential connections with tumor growth and metastasis, as well as a strong biomarker potential when used with 3 other genes (PTTG1, MND1, CENPF). Our results show that dysregulation of the 26-mRNA signature panel provides an evidence of malignancy and contribute to the design of a high specificity biomarker panel for detection of HGSOC, potentially in an early more curable stage.
Collapse
Affiliation(s)
- Pourya Naderi Yeganeh
- College of Computing and Informatics, University of North Carolina at Charlotte, Charlotte, NC, USA
| | - Christine Richardson
- Department of Biological Sciences, University of North Carolina at Charlotte, Charlotte, NC, USA
| | - Zahra Bahrani-Mostafavi
- College of Health and Human Services, University of North Carolina at Charlotte, Charlotte, NC, USA
| | - David L. Tait
- Division of Gynecological Oncology and Obstetrics, Levine Cancer Institute, Carolinas Medical Center, Charlotte, NC, USA
| | - M. Taghi Mostafavi
- College of Computing and Informatics, University of North Carolina at Charlotte, Charlotte, NC, USA
| |
Collapse
|
165
|
Zhang J, Guo F, Wei J, Xian M, Tang S, Zhao Y, Liu M, Song L, Geng Y, Yang H, Ding C, Huang L. An integrated approach to identify critical transcription factors in the protection against hydrogen peroxide-induced oxidative stress by Danhong injection. Free Radic Biol Med 2017; 112:480-493. [PMID: 28822748 DOI: 10.1016/j.freeradbiomed.2017.07.002] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2017] [Revised: 06/07/2017] [Accepted: 07/04/2017] [Indexed: 12/18/2022]
Abstract
Oxidative stress plays a vital role in many pathological processes of the cardiovascular diseases. However, the underlying mechanism remains unclear, especially on a transcription factor (TF) level. In this study, a new method, concatenated tandem array of consensus transcription factor response elements (catTFREs), and an Illumina-based RNA-seq technology were integrated to systematically investigate the role of TFs in hydrogen peroxide (H2O2)-induced oxidative stress in cardiomyocytes; the damage was then rescued by Danhong injection (DHI), a Chinese standardized product approved for cardiovascular diseases treatment. The overall gene expression revealed cell apoptosis and DNA repair were vital for cardiomyocytes in resisting oxidative stress. By comprehensively integrating the transcription activity of TFs and their downstream target genes, an important TFs-target network were constructed and 13 TFs were identified as critical TFs in DHI-mediated protection in H2O2-induced oxidative stress. By using the integrated approach, seven TFs of these 13 TFs were also identified in melatonin-mediated protection in H2O2-induced damage. Furthermore, the transcription activity of DNA-(apurinic or apyrimidinic site) lyase (Apex1), Myocyte-specific enhancer factor 2D (Mef2d) and Pre B-cell leukemia transcription factor 3 (Pbx3) was further verified in pluripotent stem cell-derived cardiomyocytes. This research offers a new understanding of cardiomyocytes in response to H2O2-induced oxidative stress and reveals additional potential therapeutic targets. The combination of two parallel omics datasets (corresponding to the transcriptome and proteome) can reduce the noise in high-throughput data and reveal the fundamental changes of the biological process, making it suitable and reliable for investigation of critical targets in many other complicated pathological processes.
Collapse
Affiliation(s)
- Jingjing Zhang
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing 100700, China
| | - Feifei Guo
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing 100700, China
| | - Junying Wei
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing 100700, China
| | - Minghua Xian
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing 100700, China
| | - Shihuan Tang
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing 100700, China
| | - Ye Zhao
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing 100700, China
| | - Mingwei Liu
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, Beijing 102206, China
| | - Lei Song
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, Beijing 102206, China
| | - Ya Geng
- School of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan 250355, China
| | - Hongjun Yang
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing 100700, China.
| | - Chen Ding
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, Beijing 102206, China; State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Institute of Biomedical Sciences, Fudan University, Shanghai 200433, China.
| | - Luqi Huang
- State Key Laboratory Breeding Base of Dao-di Herbs, National Resource Center for Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing 100700, China.
| |
Collapse
|
166
|
Zhang J, Geng Y, Guo F, Zhang F, Liu M, Song L, Ma Y, Li D, Zhang Y, Xu H, Yang H. Screening and identification of critical transcription factors involved in the protection of cardiomyocytes against hydrogen peroxide-induced damage by Yixin-shu. Sci Rep 2017; 7:13867. [PMID: 29066842 PMCID: PMC5655617 DOI: 10.1038/s41598-017-10131-5] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2017] [Accepted: 08/04/2017] [Indexed: 01/12/2023] Open
Abstract
Oxidative stress initiates harmful cellular responses, such as DNA damage and protein denaturation, triggering a series of cardiovascular disorders. Systematic investigations of the transcription factors (TFs) involved in oxidative stress can help reveal the underlying molecular mechanisms and facilitate the discovery of effective therapeutic targets in related diseases. In this study, an integrated strategy which integrated RNA-seq-based transcriptomics techniques and a newly developed concatenated tandem array of consensus TF response elements (catTFREs)-based proteomics approach and then combined with a network pharmacology analysis, was developed and this integrated strategy was used to investigate critical TFs in the protection of Yixin-shu (YXS), a standardized medical product used for ischaemic heart disease, against hydrogen peroxide (H2O2)-induced damage in cardiomyocytes. Importantly, YXS initiated biological process such as anti-apoptosis and DNA repair to protect cardiomyocytes from H2O2-induced damage. By using the integrated strategy, DNA-(apurinic or apyrimidinic site) lyase (Apex1), pre B-cell leukemia transcription factor 3 (Pbx3), and five other TFs with their functions involved in anti-oxidation, anti-apoptosis and DNA repair were identified. This study offers a new understanding of the mechanism underlying YXS-mediated protection against H2O2-induced oxidative stress in cardiomyocytes and reveals novel targets for oxidative stress-related diseases.
Collapse
Affiliation(s)
- Jingjing Zhang
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, 100700, China
| | - Ya Geng
- College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, 250355, China
| | - Feifei Guo
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, 100700, China
| | - Fangbo Zhang
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, 100700, China
| | - Mingwei Liu
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, Beijing, 102206, China
| | - Lei Song
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, Beijing, 102206, China
| | - Yuexiang Ma
- College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, 250355, China
| | - Defeng Li
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, 100700, China
| | - Yi Zhang
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, 100700, China
| | - Haiyu Xu
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, 100700, China.
| | - Hongjun Yang
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, 100700, China.
| |
Collapse
|
167
|
Nam S. Cancer Transcriptome Dataset Analysis: Comparing Methods of Pathway and Gene Regulatory Network-Based Cluster Identification. OMICS-A JOURNAL OF INTEGRATIVE BIOLOGY 2017; 21:217-224. [PMID: 28388297 PMCID: PMC5393410 DOI: 10.1089/omi.2016.0169] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Cancer transcriptome analysis is one of the leading areas of Big Data science, biomarker, and pharmaceutical discovery, not to forget personalized medicine. Yet, cancer transcriptomics and postgenomic medicine require innovation in bioinformatics as well as comparison of the performance of available algorithms. In this data analytics context, the value of network generation and algorithms has been widely underscored for addressing the salient questions in cancer pathogenesis. Analysis of cancer trancriptome often results in complicated networks where identification of network modularity remains critical, for example, in delineating the "druggable" molecular targets. Network clustering is useful, but depends on the network topology in and of itself. Notably, the performance of different network-generating tools for network cluster (NC) identification has been little investigated to date. Hence, using gastric cancer (GC) transcriptomic datasets, we compared two algorithms for generating pathway versus gene regulatory network-based NCs, showing that the pathway-based approach better agrees with a reference set of cancer-functional contexts. Finally, by applying pathway-based NC identification to GC transcriptome datasets, we describe cancer NCs that associate with candidate therapeutic targets and biomarkers in GC. These observations collectively inform future research on cancer transcriptomics, drug discovery, and rational development of new analysis tools for optimal harnessing of omics data.
Collapse
Affiliation(s)
- Seungyoon Nam
- 1 Department of Genome Medicine and Science, College of Medicine, Gachon University , Incheon, Korea.,2 Department of Life Sciences, Gachon University , Seongnam, Korea.,3 Gachon Institute of Genome Medicine and Science, Gachon University Gil Medical Center , Incheon, Korea
| |
Collapse
|
168
|
Molecular Subgroup of Primary Prostate Cancer Presenting with Metastatic Biology. Eur Urol 2017; 72:509-518. [DOI: 10.1016/j.eururo.2017.03.027] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2016] [Accepted: 03/17/2017] [Indexed: 12/24/2022]
|
169
|
Shen Y, Alvarez MJ, Bisikirska B, Lachmann A, Realubit R, Pampou S, Coku J, Karan C, Califano A. Systematic, network-based characterization of therapeutic target inhibitors. PLoS Comput Biol 2017; 13:e1005599. [PMID: 29023443 PMCID: PMC5638208 DOI: 10.1371/journal.pcbi.1005599] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2016] [Accepted: 05/27/2017] [Indexed: 12/14/2022] Open
Abstract
A large fraction of the proteins that are being identified as key tumor dependencies represent poor pharmacological targets or lack clinically-relevant small-molecule inhibitors. Availability of fully generalizable approaches for the systematic and efficient prioritization of tumor-context specific protein activity inhibitors would thus have significant translational value. Unfortunately, inhibitor effects on protein activity cannot be directly measured in systematic and proteome-wide fashion by conventional biochemical assays. We introduce OncoLead, a novel network based approach for the systematic prioritization of candidate inhibitors for arbitrary targets of therapeutic interest. In vitro and in vivo validation confirmed that OncoLead analysis can recapitulate known inhibitors as well as prioritize novel, context-specific inhibitors of difficult targets, such as MYC and STAT3. We used OncoLead to generate the first unbiased drug/regulator interaction map, representing compounds modulating the activity of cancer-relevant transcription factors, with potential in precision medicine.
Collapse
Affiliation(s)
- Yao Shen
- Department of Systems Biology, Columbia University, New York, New York, United States of America
- DarwinHealth Inc, New York, New York, United States of America
| | - Mariano J. Alvarez
- Department of Systems Biology, Columbia University, New York, New York, United States of America
- DarwinHealth Inc, New York, New York, United States of America
| | - Brygida Bisikirska
- Department of Systems Biology, Columbia University, New York, New York, United States of America
| | - Alexander Lachmann
- Department of Systems Biology, Columbia University, New York, New York, United States of America
| | - Ronald Realubit
- JP Sulzberger Columbia Genome Center, Columbia University, New York, New York, United States of America
| | - Sergey Pampou
- JP Sulzberger Columbia Genome Center, Columbia University, New York, New York, United States of America
| | - Jorida Coku
- Department of Systems Biology, Columbia University, New York, New York, United States of America
| | - Charles Karan
- JP Sulzberger Columbia Genome Center, Columbia University, New York, New York, United States of America
| | - Andrea Califano
- Department of Systems Biology, Columbia University, New York, New York, United States of America
- DarwinHealth Inc, New York, New York, United States of America
- JP Sulzberger Columbia Genome Center, Columbia University, New York, New York, United States of America
- Department of Biomedical Informatics, Columbia University, New York, New York, United States of America
- Department of Biochemistry & Molecular Biophysics, Columbia University, New York, New York, United States of America
- Institute for Cancer Genetics and Herbert Irving Comprehensive Cancer Center, Columbia University, New York, New York, United States of America
- Motor Neuron Center and Columbia Initiative in Stem Cells, Columbia University, New York, New York, United States of America
| |
Collapse
|
170
|
He J, Zhou Z, Reed M, Califano A. Accelerated parallel algorithm for gene network reverse engineering. BMC SYSTEMS BIOLOGY 2017; 11:83. [PMID: 28950860 PMCID: PMC5615246 DOI: 10.1186/s12918-017-0458-5] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Background The Algorithm for the Reconstruction of Accurate Cellular Networks (ARACNE) represents one of the most effective tools to reconstruct gene regulatory networks from large-scale molecular profile datasets. However, previous implementations require intensive computing resources and, in some cases, restrict the number of samples that can be used. These issues can be addressed elegantly in a GPU computing framework, where repeated mathematical computation can be done efficiently, but requires extensive redesign to apply parallel computing techniques to the original serial algorithm, involving detailed optimization efforts based on a deep understanding of both hardware and software architecture. Result Here, we present an accelerated parallel implementation of ARACNE (GPU-ARACNE). By taking advantage of multi-level parallelism and the Compute Unified Device Architecture (CUDA) parallel kernel-call library, GPU-ARACNE successfully parallelizes a serial algorithm and simplifies the user experience from multi-step operations to one step. Using public datasets on comparable hardware configurations, we showed that GPU-ARACNE is faster than previous implementations and is able to reconstruct equally valid gene regulatory networks. Conclusion Given that previous versions of ARACNE are extremely resource demanding, either in computational time or in hardware investment, GPU-ARACNE is remarkably valuable for researchers who need to build complex regulatory networks from large expression datasets, but with limited budget on computational resources. In addition, our GPU-centered optimization of adaptive partitioning for Mutual Information (MI) estimation provides lessons that are applicable to other domains. Electronic supplementary material The online version of this article (doi:10.1186/s12918-017-0458-5) contains supplementary material, which is available to authorized users.
Collapse
Affiliation(s)
- Jing He
- Department of Biomedical Informatics, Columbia University, 168th Street, New York, 10032, NY, USA.,Department of Systems Biology, 1130 St Nicholas Street, New York, 10032, NY, USA
| | - Zhou Zhou
- Department of Computer Science, New York, 10027, NY, USA
| | - Michael Reed
- Department of Computer Science, New York, 10027, NY, USA
| | - Andrea Califano
- Department of Systems Biology, 1130 St Nicholas Street, New York, 10032, NY, USA.
| |
Collapse
|
171
|
Ketola K, Munuganti RSN, Davies A, Nip KM, Bishop JL, Zoubeidi A. Targeting Prostate Cancer Subtype 1 by Forkhead Box M1 Pathway Inhibition. Clin Cancer Res 2017; 23:6923-6933. [PMID: 28899970 DOI: 10.1158/1078-0432.ccr-17-0901] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2017] [Revised: 07/27/2017] [Accepted: 08/31/2017] [Indexed: 11/16/2022]
Abstract
Purpose: Prostate cancer was recently classified to three clinically relevant subtypes (PCS) demarcated by unique pathway activation and clinical aggressiveness. In this preclinical study, we investigated molecular targets and therapeutics for PCS1, the most aggressive and lethal subtype, with no treatment options available in the clinic.Experimental Design: We utilized the PCS1 gene set and our model of enzalutamide (ENZR) castration-resistant prostate cancer (CRPC) to identify targetable pathways and inhibitors for PCS1. The findings were evaluated in vitro and in the ENZR CRPC xenograft model in vivoResults: The results revealed that ENZR CRPC cells are enriched with PCS1 signature and that Forkhead box M1 (FOXM1) pathway is the central driver of this subtype. Notably, we identified Monensin as a novel FOXM1-binding agent that selectively targets FOXM1 to reverse the PCS1 signature and its associated stem-like features and reduces the growth of ENZR CRPC cells and xenograft tumors.Conclusions: Our preclinical data indicate FOXM1 pathway as a master regulator of PCS1 tumors, namely in ENZR CRPC, and targeting FOXM1 reduces cell growth and stemness in ENZR CRPC in vitro and in vivo These preclinical results may guide clinical evaluation of targeting FOXM1 to eradicate highly aggressive and lethal PCS1 prostate cancer tumors. Clin Cancer Res; 23(22); 6923-33. ©2017 AACR.
Collapse
Affiliation(s)
- Kirsi Ketola
- Vancouver Prostate Centre, Vancouver, British Columbia, Canada
| | | | - Alastair Davies
- Vancouver Prostate Centre, Vancouver, British Columbia, Canada
| | - Ka Mun Nip
- Vancouver Prostate Centre, Vancouver, British Columbia, Canada
| | | | - Amina Zoubeidi
- Vancouver Prostate Centre, Vancouver, British Columbia, Canada. .,Department of Urology, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| |
Collapse
|
172
|
Nandi D, Cheema PS, Jaiswal N, Nag A. FoxM1: Repurposing an oncogene as a biomarker. Semin Cancer Biol 2017; 52:74-84. [PMID: 28855104 DOI: 10.1016/j.semcancer.2017.08.009] [Citation(s) in RCA: 75] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2017] [Revised: 08/08/2017] [Accepted: 08/23/2017] [Indexed: 12/16/2022]
Abstract
The past few decades have witnessed a tremendous progress in understanding the biology of cancer, which has led to more comprehensive approaches for global gene expression profiling and genome-wide analysis. This has helped to determine more sophisticated prognostic and predictive signature markers for the prompt diagnosis and precise screening of cancer patients. In the search for novel biomarkers, there has been increased interest in FoxM1, an extensively studied transcription factor that encompasses most of the hallmarks of malignancy. Considering the attractive potential of this multifarious oncogene, FoxM1 has emerged as an important molecule implicated in initiation, development and progression of cancer. Bolstered with the skill to maneuver the proliferation signals, FoxM1 bestows resistance to contemporary anti-cancer therapy as well. This review sheds light on the large body of literature that has accumulated in recent years that implies that FoxM1 neoplastic functions can be used as a novel predictive, prognostic and therapeutic marker for different cancers. This assessment also highlights the key features of FoxM1 that can be effectively harnessed to establish FoxM1 as a strong biomarker in diagnosis and treatment of cancer.
Collapse
Affiliation(s)
- Deeptashree Nandi
- Department of Biochemistry, University of Delhi South Campus, New Delhi, 110021, India
| | - Pradeep Singh Cheema
- Department of Biochemistry, University of Delhi South Campus, New Delhi, 110021, India
| | - Neha Jaiswal
- Department of Biochemistry, University of Delhi South Campus, New Delhi, 110021, India
| | - Alo Nag
- Department of Biochemistry, University of Delhi South Campus, New Delhi, 110021, India.
| |
Collapse
|
173
|
Kalender Atak Z, Imrichova H, Svetlichnyy D, Hulselmans G, Christiaens V, Reumers J, Ceulemans H, Aerts S. Identification of cis-regulatory mutations generating de novo edges in personalized cancer gene regulatory networks. Genome Med 2017; 9:80. [PMID: 28854983 PMCID: PMC5575942 DOI: 10.1186/s13073-017-0464-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2017] [Accepted: 08/02/2017] [Indexed: 01/05/2023] Open
Abstract
The identification of functional non-coding mutations is a key challenge in the field of genomics. Here we introduce μ-cisTarget to filter, annotate and prioritize cis-regulatory mutations based on their putative effect on the underlying "personal" gene regulatory network. We validated μ-cisTarget by re-analyzing the TAL1 and LMO1 enhancer mutations in T-ALL, and the TERT promoter mutation in melanoma. Next, we re-sequenced the full genomes of ten cancer cell lines and used matched transcriptome data and motif discovery to identify master regulators with de novo binding sites that result in the up-regulation of nearby oncogenic drivers. μ-cisTarget is available from http://mucistarget.aertslab.org .
Collapse
Affiliation(s)
- Zeynep Kalender Atak
- Laboratory of Computational Biology, VIB Center for Brain & Disease Research, Leuven, Belgium
- Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Hana Imrichova
- Laboratory of Computational Biology, VIB Center for Brain & Disease Research, Leuven, Belgium
- Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Dmitry Svetlichnyy
- Laboratory of Computational Biology, VIB Center for Brain & Disease Research, Leuven, Belgium
- Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Gert Hulselmans
- Laboratory of Computational Biology, VIB Center for Brain & Disease Research, Leuven, Belgium
- Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Valerie Christiaens
- Laboratory of Computational Biology, VIB Center for Brain & Disease Research, Leuven, Belgium
- Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Joke Reumers
- Discovery Sciences, Janssen Research & Development, Turnhoutseweg 30, 2340, Beerse, Belgium
| | - Hugo Ceulemans
- Discovery Sciences, Janssen Research & Development, Turnhoutseweg 30, 2340, Beerse, Belgium
| | - Stein Aerts
- Laboratory of Computational Biology, VIB Center for Brain & Disease Research, Leuven, Belgium.
- Department of Human Genetics, KU Leuven, Leuven, Belgium.
| |
Collapse
|
174
|
Robertson AG, Shih J, Yau C, Gibb EA, Oba J, Mungall KL, Hess JM, Uzunangelov V, Walter V, Danilova L, Lichtenberg TM, Kucherlapati M, Kimes PK, Tang M, Penson A, Babur O, Akbani R, Bristow CA, Hoadley KA, Iype L, Chang MT, Cherniack AD, Benz C, Mills GB, Verhaak RGW, Griewank KG, Felau I, Zenklusen JC, Gershenwald JE, Schoenfield L, Lazar AJ, Abdel-Rahman MH, Roman-Roman S, Stern MH, Cebulla CM, Williams MD, Jager MJ, Coupland SE, Esmaeli B, Kandoth C, Woodman SE. Integrative Analysis Identifies Four Molecular and Clinical Subsets in Uveal Melanoma. Cancer Cell 2017; 32:204-220.e15. [PMID: 28810145 PMCID: PMC5619925 DOI: 10.1016/j.ccell.2017.07.003] [Citation(s) in RCA: 549] [Impact Index Per Article: 78.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2016] [Revised: 04/24/2017] [Accepted: 07/09/2017] [Indexed: 12/17/2022]
Abstract
Comprehensive multiplatform analysis of 80 uveal melanomas (UM) identifies four molecularly distinct, clinically relevant subtypes: two associated with poor-prognosis monosomy 3 (M3) and two with better-prognosis disomy 3 (D3). We show that BAP1 loss follows M3 occurrence and correlates with a global DNA methylation state that is distinct from D3-UM. Poor-prognosis M3-UM divide into subsets with divergent genomic aberrations, transcriptional features, and clinical outcomes. We report change-of-function SRSF2 mutations. Within D3-UM, EIF1AX- and SRSF2/SF3B1-mutant tumors have distinct somatic copy number alterations and DNA methylation profiles, providing insight into the biology of these low- versus intermediate-risk clinical mutation subtypes.
Collapse
Affiliation(s)
- A Gordon Robertson
- Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, BC V5Z 4S6, Canada
| | - Juliann Shih
- The Eli and Edythe L. Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02142, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - Christina Yau
- Buck Institute for Research on Aging, Novato, CA 94945, USA
| | - Ewan A Gibb
- Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, BC V5Z 4S6, Canada
| | - Junna Oba
- Department of Melanoma Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Karen L Mungall
- Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, BC V5Z 4S6, Canada
| | - Julian M Hess
- The Eli and Edythe L. Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02142, USA
| | - Vladislav Uzunangelov
- Department of Biomolecular Engineering, Center for Biomolecular Sciences and Engineering, University of California, Santa Cruz, CA 95064, USA
| | - Vonn Walter
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Department of Public Health Sciences, Penn State College of Medicine, 500 University Drive, Hershey, PA 17033, USA
| | - Ludmila Danilova
- The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins University, Baltimore, MD 21287, USA
| | - Tara M Lichtenberg
- The Research Institute at Nationwide Children's Hospital, Columbus, OH 43205, USA
| | - Melanie Kucherlapati
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA; Division of Genetics, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Patrick K Kimes
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Ming Tang
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Alexander Penson
- Human Oncology and Pathogenesis Program, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY 10021, USA; Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY 10021, USA
| | - Ozgun Babur
- Molecular and Medical Genetics, Computational Biology, Oregon Health and Science University, Portland, OR 97239, USA
| | - Rehan Akbani
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Christopher A Bristow
- Institute for Applied Cancer Science, Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Katherine A Hoadley
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Lisa Iype
- Institute for Systems Biology, Seattle, WA 98109, USA
| | - Matthew T Chang
- Human Oncology and Pathogenesis Program, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY 10021, USA; Departments of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA 94122, USA
| | | | - Andrew D Cherniack
- The Eli and Edythe L. Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02142, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | | | - Gordon B Mills
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Roel G W Verhaak
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Klaus G Griewank
- Department of Dermatology, University Hospital Essen, 45157 Essen, Germany
| | - Ina Felau
- Center for Cancer Genomics, National Cancer Institute, Bethesda, MD 20892, USA
| | - Jean C Zenklusen
- Center for Cancer Genomics, National Cancer Institute, Bethesda, MD 20892, USA
| | - Jeffrey E Gershenwald
- Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Lynn Schoenfield
- Department of Pathology, The Ohio State University, Wexner Medical Center, Columbus, OH 43210, USA
| | - Alexander J Lazar
- Department of Pathology, Dermatology and Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Mohamed H Abdel-Rahman
- Departments of Ophthalmology and Internal Medicine, Division of Human Genetics, The Ohio State University, Columbus, OH 43210, USA
| | - Sergio Roman-Roman
- Department of Translational Research, Institut Curie, PSL Research University, Paris 75248, France
| | - Marc-Henri Stern
- Department of Translational Research, Institut Curie, PSL Research University, Paris 75248, France
| | - Colleen M Cebulla
- Havener Eye Institute, The Ohio State University Wexner Medical Center, Columbus, OH 43212, USA
| | - Michelle D Williams
- Department of Pathology, Dermatology and Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Martine J Jager
- Department of Ophthalmology, Leiden University Medical Center, Leiden, the Netherlands
| | - Sarah E Coupland
- Department of Molecular & Clinical Cancer Medicine, Institute of Translational Medicine, University of Liverpool, Liverpool L7 8TX, UK; Department of Cellular Pathology, Royal Liverpool University Hospital, Liverpool, L69 3GA, UK
| | - Bita Esmaeli
- Orbital Oncology & Ophthalmic Plastic Surgery, Department of Plastic Surgery, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
| | - Cyriac Kandoth
- Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY 10021, USA.
| | - Scott E Woodman
- Department of Melanoma Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
| |
Collapse
|
175
|
Shukla S, Zhang X, Niknafs YS, Xiao L, Mehra R, Cieślik M, Ross A, Schaeffer E, Malik B, Guo S, Freier SM, Bui HH, Siddiqui J, Jing X, Cao X, Dhanasekaran SM, Feng FY, Chinnaiyan AM, Malik R. Identification and Validation of PCAT14 as Prognostic Biomarker in Prostate Cancer. Neoplasia 2017; 18:489-99. [PMID: 27566105 PMCID: PMC5018094 DOI: 10.1016/j.neo.2016.07.001] [Citation(s) in RCA: 51] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2016] [Revised: 07/06/2016] [Accepted: 07/06/2016] [Indexed: 12/15/2022] Open
Abstract
Rapid advances in the discovery of long noncoding RNAs (lncRNAs) have identified lineage- and cancer-specific biomarkers that may be relevant in the clinical management of prostate cancer (PCa). Here we assembled and analyzed a large RNA-seq dataset, from 585 patient samples, including benign prostate tissue and both localized and metastatic PCa to discover and validate differentially expressed genes associated with disease aggressiveness. We performed Sample Set Enrichment Analysis (SSEA) and identified genes associated with low versus high Gleason score in the RNA-seq database. Comparing Gleason 6 versus 9+ PCa samples, we identified 99 differentially expressed genes with variable association to Gleason grade as well as robust expression in prostate cancer. The top-ranked novel lncRNA PCAT14, exhibits both cancer and lineage specificity. On multivariate analysis, low PCAT14 expression independently predicts for BPFS (P = .00126), PSS (P = .0385), and MFS (P = .000609), with trends for OS as well (P = .056). An RNA in-situ hybridization (ISH) assay for PCAT14 distinguished benign vs malignant cases, as well as high vs low Gleason disease. PCAT14 is transcriptionally regulated by AR, and endogenous PCAT14 overexpression suppresses cell invasion. Thus, Using RNA-sequencing data we identify PCAT14, a novel prostate cancer and lineage-specific lncRNA. PCAT14 is highly expressed in low grade disease and loss of PCAT14 predicts for disease aggressiveness and recurrence.
Collapse
Affiliation(s)
- Sudhanshu Shukla
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, USA; Department of Pathology, University of Michigan, Ann Arbor, USA
| | - Xiang Zhang
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, USA; Department of Urology, Qilu Hospital of Shandong University, Jinan, China
| | - Yashar S Niknafs
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, USA
| | - Lanbo Xiao
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, USA; Department of Pathology, University of Michigan, Ann Arbor, USA
| | - Rohit Mehra
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, USA; Department of Pathology, University of Michigan, Ann Arbor, USA
| | - Marcin Cieślik
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, USA; Department of Pathology, University of Michigan, Ann Arbor, USA
| | - Ashley Ross
- James Buchanan Brady Urological Institute, Johns Hopkins University, USA
| | - Edward Schaeffer
- James Buchanan Brady Urological Institute, Johns Hopkins University, USA
| | - Bhavna Malik
- Department of Radiation Oncology, University of Michigan, Ann Arbor, USA
| | | | | | | | - Javed Siddiqui
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, USA; Department of Pathology, University of Michigan, Ann Arbor, USA
| | - Xiaojun Jing
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, USA; Department of Pathology, University of Michigan, Ann Arbor, USA
| | - Xuhong Cao
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, USA; Department of Pathology, University of Michigan, Ann Arbor, USA
| | - Saravana M Dhanasekaran
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, USA; Department of Pathology, University of Michigan, Ann Arbor, USA
| | - Felix Y Feng
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, USA; Department of Radiation Oncology, University of Michigan, Ann Arbor, USA
| | - Arul M Chinnaiyan
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, USA; Department of Pathology, University of Michigan, Ann Arbor, USA; Howard Hughes Medical Institute, University of Michigan, Ann Arbor, USA; Department of Urology, University of Michigan Medical School, Ann Arbor, MI, USA; Comprehensive Cancer Center, University of Michigan, Ann Arbor, USA.
| | - Rohit Malik
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, USA; Department of Pathology, University of Michigan, Ann Arbor, USA
| |
Collapse
|
176
|
Guo L, Ding Z, Huang N, Huang Z, Zhang N, Xia Z. Forkhead Box M1 positively regulates UBE2C and protects glioma cells from autophagic death. Cell Cycle 2017; 16:1705-1718. [PMID: 28767320 PMCID: PMC5602297 DOI: 10.1080/15384101.2017.1356507] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
Ubiquitin-conjugating enzyme E2C (UBE2C) is characterized as a crucial molecule in cancer cell growth that plays an essential role in the development of gliomas, but the detailed mechanisms have not been fully elucidated. In this study, we found that Forkhead box transcription factor M1 (FoxM1) overexpression increased UBE2C expression, whereas FoxM1 suppression inhibited UBE2C expression in glioma cells. In addition, high FoxM1/UBE2C expression was significantly correlated with poor prognosis in glioma. We subsequently demonstrated that UBE2C was a direct transcriptional target of FoxM1, and site-directed mutations markedly down-regulated UBE2C promoter activity. Moreover, UBE2C siRNA (si-UBE2C) significantly induced glioma cell autophagy and increased both mCherry-LC3 punctate fluorescence and LC3B-II/LC3-I expression. Notably, the si-UBE2C-induced decrease in cell viability was markedly inhibited by the autophagy inhibitor bafilomycin A1. The silencing of UBE2C resulted in a distinct inhibition of the PI3K-Akt-mTOR pathway, which functions in the negative modulation of autophagy. Collectively, our findings provide clinical and molecular evidence that FoxM1 promotes glioma progression by enhancing UBE2C transcription and that the inhibition of UBE2C partially induces autophagic glioma cell death. Thus, targeting the FoxM1-UBE2C axis has therapeutic potential in the treatment of gliomas.
Collapse
Affiliation(s)
- Liang Guo
- a Department of Neurosurgery , The First Affiliated Hospital of Sun Yat-sen University , Guangzhou , Guangdong Province , China
| | - Zhiming Ding
- a Department of Neurosurgery , The First Affiliated Hospital of Sun Yat-sen University , Guangzhou , Guangdong Province , China
| | - Nunu Huang
- a Department of Neurosurgery , The First Affiliated Hospital of Sun Yat-sen University , Guangzhou , Guangdong Province , China
| | - Zhengsong Huang
- a Department of Neurosurgery , The First Affiliated Hospital of Sun Yat-sen University , Guangzhou , Guangdong Province , China
| | - Nu Zhang
- a Department of Neurosurgery , The First Affiliated Hospital of Sun Yat-sen University , Guangzhou , Guangdong Province , China
| | - Zhibo Xia
- a Department of Neurosurgery , The First Affiliated Hospital of Sun Yat-sen University , Guangzhou , Guangdong Province , China
| |
Collapse
|
177
|
FOXM1 promotes the progression of prostate cancer by regulating PSA gene transcription. Oncotarget 2017; 8:17027-17037. [PMID: 28199985 PMCID: PMC5370019 DOI: 10.18632/oncotarget.15224] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2016] [Accepted: 01/09/2017] [Indexed: 12/30/2022] Open
Abstract
Androgen/AR is the primary contributor to prostate cancer (PCa) progression by regulating Prostate Specific Antigen (PSA) gene transcription. The disease inevitably evolves to androgen-independent (AI) status. Other mechanisms by which PSA is regulated and develops to AI have not yet been fully determined. FOXM1 is a cell proliferation-specific transcription factor highly expressed in PCa cells compared to non-malignant prostate epithelial cells, suggesting that the aberrant overexpression of FOXM1 contributes to PCa development. In addition to regulating AR gene transcription and cell cycle-regulatory genes, FOXM1 selectively regulates the gene transcription of KLK2 and PSA, typical androgen responsive genes. Screening the potential FOXM1-binding sites by ChIP-PCR, we found that FOXM1 directly binds to the FHK binding motifs in the PSA promoter/enhancer regions. AI C4-2 cells have more FOXM1 binding sites than androgen dependent LNCaP cells. The depletion of FOXM1 by small molecular inhibitors significantly improves the suppression of PSA gene transcription by the anti-AR agent Cadosax. This is the first report showing that FOXM1 promotes PCa progression by regulating PSA gene transcription, particularly in AI PCa cells. The combination of anti-AR agents and FOXM1 inhibitors has the potential to greatly improve therapy for late-stage PCa patients by suppressing PSA levels.
Collapse
|
178
|
Dhingra P, Martinez-Fundichely A, Berger A, Huang FW, Forbes AN, Liu EM, Liu D, Sboner A, Tamayo P, Rickman DS, Rubin MA, Khurana E. Identification of novel prostate cancer drivers using RegNetDriver: a framework for integration of genetic and epigenetic alterations with tissue-specific regulatory network. Genome Biol 2017; 18:141. [PMID: 28750683 PMCID: PMC5530464 DOI: 10.1186/s13059-017-1266-3] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2016] [Accepted: 06/27/2017] [Indexed: 11/22/2022] Open
Abstract
We report a novel computational method, RegNetDriver, to identify tumorigenic drivers using the combined effects of coding and non-coding single nucleotide variants, structural variants, and DNA methylation changes in the DNase I hypersensitivity based regulatory network. Integration of multi-omics data from 521 prostate tumor samples indicated a stronger regulatory impact of structural variants, as they affect more transcription factor hubs in the tissue-specific network. Moreover, crosstalk between transcription factor hub expression modulated by structural variants and methylation levels likely leads to the differential expression of target genes. We report known prostate tumor regulatory drivers and nominate novel transcription factors (ERF, CREB3L1, and POU2F2), which are supported by functional validation.
Collapse
Affiliation(s)
- Priyanka Dhingra
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York, 10065, USA
- Institute for Computational Biomedicine, Weill Cornell Medical College, New York, New York, 10021, USA
| | - Alexander Martinez-Fundichely
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York, 10065, USA
- Institute for Computational Biomedicine, Weill Cornell Medical College, New York, New York, 10021, USA
| | - Adeline Berger
- Department of Pathology and Laboratory Medicine, Weill Cornell Medical College, New York, New York, 10065, USA
| | - Franklin W Huang
- Department of Medical Oncology, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA, 02215, USA
- Department of Medicine, Harvard Medical School, 25 Shattuck Street, Boston, MA, 02115, USA
- Cancer Program, The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA, 02142, USA
| | - Andre Neil Forbes
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York, 10065, USA
- Institute for Computational Biomedicine, Weill Cornell Medical College, New York, New York, 10021, USA
| | - Eric Minwei Liu
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York, 10065, USA
- Institute for Computational Biomedicine, Weill Cornell Medical College, New York, New York, 10021, USA
| | - Deli Liu
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York, 10065, USA
- Department of Urology, Weill Cornell Medical College, New York, New York, 10065, USA
| | - Andrea Sboner
- Institute for Computational Biomedicine, Weill Cornell Medical College, New York, New York, 10021, USA
- Department of Pathology and Laboratory Medicine, Weill Cornell Medical College, New York, New York, 10065, USA
- Caryl and Israel Englander Institute for Precision Medicine, New York Presbyterian Hospital-Weill Cornell Medicine, New York, NY, 10065, USA
| | - Pablo Tamayo
- Cancer Program, The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA, 02142, USA
- Department of Medicine, University of California San Diego, La Jolla, California, USA
- Moores Cancer Center, University of California San Diego, La Jolla, California, USA
| | - David S Rickman
- Department of Pathology and Laboratory Medicine, Weill Cornell Medical College, New York, New York, 10065, USA.
- Caryl and Israel Englander Institute for Precision Medicine, New York Presbyterian Hospital-Weill Cornell Medicine, New York, NY, 10065, USA.
- Meyer Cancer Center, Weill Cornell Medical College, New York, New York, 10065, USA.
| | - Mark A Rubin
- Department of Pathology and Laboratory Medicine, Weill Cornell Medical College, New York, New York, 10065, USA
- Caryl and Israel Englander Institute for Precision Medicine, New York Presbyterian Hospital-Weill Cornell Medicine, New York, NY, 10065, USA
- Meyer Cancer Center, Weill Cornell Medical College, New York, New York, 10065, USA
| | - Ekta Khurana
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York, 10065, USA.
- Institute for Computational Biomedicine, Weill Cornell Medical College, New York, New York, 10021, USA.
- Caryl and Israel Englander Institute for Precision Medicine, New York Presbyterian Hospital-Weill Cornell Medicine, New York, NY, 10065, USA.
- Meyer Cancer Center, Weill Cornell Medical College, New York, New York, 10065, USA.
| |
Collapse
|
179
|
Goto Y, Kurozumi A, Arai T, Nohata N, Kojima S, Okato A, Kato M, Yamazaki K, Ishida Y, Naya Y, Ichikawa T, Seki N. Impact of novel miR-145-3p regulatory networks on survival in patients with castration-resistant prostate cancer. Br J Cancer 2017; 117:409-420. [PMID: 28641312 PMCID: PMC5537499 DOI: 10.1038/bjc.2017.191] [Citation(s) in RCA: 85] [Impact Index Per Article: 12.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2017] [Revised: 05/31/2017] [Accepted: 06/01/2017] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Despite recent advancements, metastatic castration-resistant prostate cancer (CRPC) is not considered curative. Novel approaches for identification of therapeutic targets of CRPC are needed. METHODS Next-generation sequencing revealed 945-1248 miRNAs from each lethal mCRPC sample. We constructed miRNA expression signatures of CRPC by comparing the expression of miRNAs between CRPC and normal prostate tissue or hormone-sensitive prostate cancer (HSPC). Genome-wide gene expression studies and in silico analyses were carried out to predict miRNA regulation and investigate the functional significance and clinical utility of the novel oncogenic pathways regulated by these miRNAs in prostate cancer (PCa). RESULTS Based on the novel miRNA expression signature of CRPC, miR-145-5p and miR-145-3p were downregulated in CRPC. By focusing on miR-145-3p, which is a passenger strand and has not been well studied in previous reports, we showed that miR-145-3p targeted 4 key molecules, i.e., MELK, NCAPG, BUB1, and CDK1, in CPRC. These 4 genes significantly predicted survival in patients with PCa. CONCLUSIONS Small RNA sequencing for lethal CRPC and in silico analyses provided novel therapeutic targets for CRPC.
Collapse
Affiliation(s)
- Yusuke Goto
- Department of Functional Genomics, Chiba University Graduate School of Medicine, Chiba, Japan
- Department of Urology, Chiba University Graduate School of Medicine, Chiba, Japan
| | - Akira Kurozumi
- Department of Functional Genomics, Chiba University Graduate School of Medicine, Chiba, Japan
- Department of Urology, Chiba University Graduate School of Medicine, Chiba, Japan
| | - Takayuki Arai
- Department of Functional Genomics, Chiba University Graduate School of Medicine, Chiba, Japan
- Department of Urology, Chiba University Graduate School of Medicine, Chiba, Japan
| | - Nijiro Nohata
- Moores Cancer Center, University of California, San Diego, La Jolla, CA 92093, USA
| | - Satoko Kojima
- Department of Urology, Teikyo University Chiba Medical Center, Ichihara, Japan
| | - Atsushi Okato
- Department of Functional Genomics, Chiba University Graduate School of Medicine, Chiba, Japan
- Department of Urology, Chiba University Graduate School of Medicine, Chiba, Japan
| | - Mayuko Kato
- Department of Functional Genomics, Chiba University Graduate School of Medicine, Chiba, Japan
- Department of Urology, Chiba University Graduate School of Medicine, Chiba, Japan
| | - Kazuto Yamazaki
- Department of Pathology, Teikyo University Chiba Medical Center, Ichihara, Japan
| | - Yasuo Ishida
- Department of Pathology, Teikyo University Chiba Medical Center, Ichihara, Japan
| | - Yukio Naya
- Department of Urology, Teikyo University Chiba Medical Center, Ichihara, Japan
| | - Tomohiko Ichikawa
- Department of Urology, Chiba University Graduate School of Medicine, Chiba, Japan
| | - Naohiko Seki
- Department of Functional Genomics, Chiba University Graduate School of Medicine, Chiba, Japan
| |
Collapse
|
180
|
Bush EC, Ray F, Alvarez MJ, Realubit R, Li H, Karan C, Califano A, Sims PA. PLATE-Seq for genome-wide regulatory network analysis of high-throughput screens. Nat Commun 2017; 8:105. [PMID: 28740083 PMCID: PMC5524642 DOI: 10.1038/s41467-017-00136-z] [Citation(s) in RCA: 70] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2016] [Revised: 06/01/2017] [Accepted: 06/05/2017] [Indexed: 02/08/2023] Open
Abstract
Pharmacological and functional genomic screens play an essential role in the discovery and characterization of therapeutic targets and associated pharmacological inhibitors. Although these screens affect thousands of gene products, the typical readout is based on low complexity rather than genome-wide assays. To address this limitation, we introduce pooled library amplification for transcriptome expression (PLATE-Seq), a low-cost, genome-wide mRNA profiling methodology specifically designed to complement high-throughput screening assays. Introduction of sample-specific barcodes during reverse transcription supports pooled library construction and low-depth sequencing that is 10- to 20-fold less expensive than conventional RNA-Seq. The use of network-based algorithms to infer protein activity from PLATE-Seq data results in comparable reproducibility to 30 M read sequencing. Indeed, PLATE-Seq reproducibility compares favorably to other large-scale perturbational profiling studies such as the connectivity map and library of integrated network-based cellular signatures. Despite the importance of pharmacological and functional genomic screens the readouts are of low complexity. Here the authors introduce PLATE-Seq, a low-cost genome-wide mRNA profiling method to complement high-throughput screening.
Collapse
Affiliation(s)
- Erin C Bush
- Department of Systems Biology, Columbia University Medical Center, New York, NY, 10032, USA.,Sulzberger Columbia Genome Center, Columbia University Medical Center, New York, NY, 10032, USA
| | - Forest Ray
- Department of Systems Biology, Columbia University Medical Center, New York, NY, 10032, USA
| | - Mariano J Alvarez
- Department of Systems Biology, Columbia University Medical Center, New York, NY, 10032, USA.,DarwinHealth Inc., New York, NY, 10032, USA
| | - Ronald Realubit
- Department of Systems Biology, Columbia University Medical Center, New York, NY, 10032, USA.,Sulzberger Columbia Genome Center, Columbia University Medical Center, New York, NY, 10032, USA
| | - Hai Li
- Department of Systems Biology, Columbia University Medical Center, New York, NY, 10032, USA.,Sulzberger Columbia Genome Center, Columbia University Medical Center, New York, NY, 10032, USA
| | - Charles Karan
- Department of Systems Biology, Columbia University Medical Center, New York, NY, 10032, USA.,Sulzberger Columbia Genome Center, Columbia University Medical Center, New York, NY, 10032, USA
| | - Andrea Califano
- Department of Systems Biology, Columbia University Medical Center, New York, NY, 10032, USA. .,Sulzberger Columbia Genome Center, Columbia University Medical Center, New York, NY, 10032, USA. .,Department of Biochemistry & Molecular Biophysics, Columbia University Medical Center, New York, NY, 10032, USA. .,Institute for Cancer Genetics, Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, NY, 10032, USA.
| | - Peter A Sims
- Department of Systems Biology, Columbia University Medical Center, New York, NY, 10032, USA. .,Sulzberger Columbia Genome Center, Columbia University Medical Center, New York, NY, 10032, USA. .,Department of Biochemistry & Molecular Biophysics, Columbia University Medical Center, New York, NY, 10032, USA.
| |
Collapse
|
181
|
G2/M checkpoint plays a vital role at the early stage of HCC by analysis of key pathways and genes. Oncotarget 2017; 8:76305-76317. [PMID: 29100313 PMCID: PMC5652707 DOI: 10.18632/oncotarget.19351] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2017] [Accepted: 06/29/2017] [Indexed: 01/14/2023] Open
Abstract
The present study was designed to explore the molecular mechanism at the early stage of hepatocarcinoma (HCC) and identify the candidate genes and pathways changed significantly. We downloaded the gene expression file dataset GSE6764 from GEO, adopted the Robust Multi-array Average (RMA) algorithm to preprocess the raw file. 797 differentially expressed genes (DEGs) were screened out based on the SAM method using R language. Ingenuity Pathway Analysis (IPA) was used to perform canonical pathway analysis in order to calculate the most significantly changed pathways and predict the upstream regulators. In order to confirm the results from the DEGs which based on the individual gene level, the gene set enrichment analysis (GSEA) was done from the gene set level and the leading edge analysis was performed to find out the most appeared genes in several gene sets. The PPI network was built using GeneMANIA and the key genes were calculated using cytoHubba plugin based on cytoscape 3.4.0. We found that the Cell Cycle: G2/M DNA damage checkpoint regulation is the top-ranked pathways at the early stage of HCC by IPA. The high expression of several genes including CCNB1, CDC25B, XPO1, GMPS, KPNA2 and MELK is correlated with high risk, poor prognosis and shorter overall survival time in HCC patients by use of Kaplan-Meier Survival analysis. Taken together, our study showed that the G2/M checkpoint plays a vital role at the early HCC and the genes participate in the process may serve as biomarkers for the diagnosis and prognosis.
Collapse
|
182
|
Oxidative Stress Gene Expression Profile Correlates with Cancer Patient Poor Prognosis: Identification of Crucial Pathways Might Select Novel Therapeutic Approaches. OXIDATIVE MEDICINE AND CELLULAR LONGEVITY 2017; 2017:2597581. [PMID: 28770020 PMCID: PMC5523271 DOI: 10.1155/2017/2597581] [Citation(s) in RCA: 76] [Impact Index Per Article: 10.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/15/2017] [Accepted: 05/30/2017] [Indexed: 12/17/2022]
Abstract
The role of altered redox status and high reactive oxygen species (ROS) is still controversial in cancer development and progression. Intracellular levels of ROS are elevated in cancer cells suggesting a role in cancer initiation and progression; on the contrary, ROS elevated levels may induce programmed cell death and have been associated with cancer suppression. Thus, it is crucial to consider the double-face of ROS, for novel therapeutic strategies targeting redox regulatory mechanisms. In this review, in order to derive cancer-type specific oxidative stress genes' profile and their potential prognostic role, we integrated a publicly available oxidative stress gene signature with patient survival data from the Cancer Genome Atlas database. Overall, we found several genes statistically significant associated with poor prognosis in the examined six tumor types. Among them, FoxM1 and thioredoxin reductase1 expression showed the same pattern in four out of six cancers, suggesting their specific critical role in cancer-related oxidative stress adaptation. Our analysis also unveiled an enriched cellular network, highlighting specific pathways, in which many genes are strictly correlated. Finally, we discussed novel findings on the correlation between oxidative stress and cancer stem cells in order to define those pathways to be prioritized in drug development.
Collapse
|
183
|
Zou M, Toivanen R, Mitrofanova A, Floch N, Hayati S, Sun Y, Le Magnen C, Chester D, Mostaghel EA, Califano A, Rubin MA, Shen MM, Abate-Shen C. Transdifferentiation as a Mechanism of Treatment Resistance in a Mouse Model of Castration-Resistant Prostate Cancer. Cancer Discov 2017; 7:736-749. [PMID: 28411207 PMCID: PMC5501744 DOI: 10.1158/2159-8290.cd-16-1174] [Citation(s) in RCA: 262] [Impact Index Per Article: 37.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2016] [Revised: 11/14/2016] [Accepted: 04/12/2017] [Indexed: 11/16/2022]
Abstract
Current treatments for castration-resistant prostate cancer (CRPC) that target androgen receptor (AR) signaling improve patient survival, yet ultimately fail. Here, we provide novel insights into treatment response for the antiandrogen abiraterone by analyses of a genetically engineered mouse (GEM) model with combined inactivation of Trp53 and Pten, which are frequently comutated in human CRPC. These NPp53 mice fail to respond to abiraterone and display accelerated progression to tumors resembling treatment-related CRPC with neuroendocrine differentiation (CRPC-NE) in humans. Cross-species computational analyses identify master regulators of adverse response that are conserved with human CRPC-NE, including the neural differentiation factor SOX11, which promotes neuroendocrine differentiation in cells derived from NPp53 tumors. Furthermore, abiraterone-treated NPp53 prostate tumors contain regions of focal and/or overt neuroendocrine differentiation, distinguished by their proliferative potential. Notably, lineage tracing in vivo provides definitive and quantitative evidence that focal and overt neuroendocrine regions arise by transdifferentiation of luminal adenocarcinoma cells. These findings underscore principal roles for TP53 and PTEN inactivation in abiraterone resistance and progression from adenocarcinoma to CRPC-NE by transdifferentiation.Significance: Understanding adverse treatment response and identifying patients likely to fail treatment represent fundamental clinical challenges. By integrating analyses of GEM models and human clinical data, we provide direct genetic evidence for transdifferentiation as a mechanism of drug resistance as well as for stratifying patients for treatment with antiandrogens. Cancer Discov; 7(7); 736-49. ©2017 AACR.See related commentary by Sinha and Nelson, p. 673This article is highlighted in the In This Issue feature, p. 653.
Collapse
Affiliation(s)
- Min Zou
- Departments of Medicine and Urology, Institute of Cancer Genetics, Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, New York
| | - Roxanne Toivanen
- Departments of Medicine and Genetics and Developmental Biology, Institute of Cancer Genetics, Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, New York
| | - Antonina Mitrofanova
- Department of Systems Biology, Columbia University Medical Center, New York, New York; and Department of Health Informatics, Rutgers, The State University of New Jersey, Newark, New Jersey
| | - Nicolas Floch
- Department of Urology, Columbia University Medical Center, New York, New York
| | - Sheida Hayati
- Department of Health Informatics, Rutgers, The State University of New Jersey, Newark, New Jersey
| | - Yanping Sun
- Department of Medicine, Columbia University Medical Center, New York, New York
| | - Clémentine Le Magnen
- Departments of Medicine and Urology, Institute of Cancer Genetics, Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, New York
| | - Daniel Chester
- Department of Urology, Columbia University Medical Center, New York, New York
| | - Elahe A Mostaghel
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Andrea Califano
- Departments of Systems Biology, Biomedical Informatics, and Biochemistry and Molecular Biophysics, Center for Computational Biology and Bioinformatics, Institute of Cancer Genetics, Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, New York
| | - Mark A Rubin
- Englander Institute for Precision Medicine and Department of Pathology and Laboratory Medicine, Weil Cornell Medical College and New York-Presbyterian Hospital, New York, New York
| | - Michael M Shen
- Departments of Medicine, Genetics and Development, Urology, and Systems Biology, Institute of Cancer Genetics, Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, New York.
| | - Cory Abate-Shen
- Departments of Urology, Medicine, Systems Biology, and Pathology and Cell Biology, Institute of Cancer Genetics, Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, New York.
| |
Collapse
|
184
|
Gartel AL. FOXM1 in Cancer: Interactions and Vulnerabilities. Cancer Res 2017; 77:3135-3139. [PMID: 28584182 DOI: 10.1158/0008-5472.can-16-3566] [Citation(s) in RCA: 163] [Impact Index Per Article: 23.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2016] [Revised: 03/09/2017] [Accepted: 04/20/2017] [Indexed: 12/21/2022]
Abstract
FOXM1 is a transcription factor of the Forkhead family that is required for cell proliferation of normal cells. However, FOXM1 is repeatedly overexpressed in a variety of human cancers, and it has been implicated in all major hallmarks of cancer delineated by Hanahan and Weinberg. It has been postulated that the oncogenic potential of FOXM1 is determined by its capacity to transactivate target genes that are implicated in different phases of cancer development. However, FOXM1 may also play an oncogenic role by interacting with other proteins, such as β-catenin or SMAD3 to induce oncogenic WNT and TGFβ signaling pathways, respectively. In this review, I will discuss the protein-protein interactions of FOXM1 that are critical for cancer development and may represent novel targets for anticancer drugs. Cancer Res; 77(12); 3135-9. ©2017 AACR.
Collapse
Affiliation(s)
- Andrei L Gartel
- Department of Medicine, University of Illinois at Chicago, Chicago, Illinois.
| |
Collapse
|
185
|
Hamilton MP, Rajapakshe KI, Bader DA, Cerne JZ, Smith EA, Coarfa C, Hartig SM, McGuire SE. The Landscape of microRNA Targeting in Prostate Cancer Defined by AGO-PAR-CLIP. Neoplasia 2017; 18:356-70. [PMID: 27292025 PMCID: PMC4909715 DOI: 10.1016/j.neo.2016.04.008] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2016] [Revised: 04/08/2016] [Accepted: 04/23/2016] [Indexed: 01/13/2023] Open
Abstract
MicroRNA (miRNA) deregulation in prostate cancer (PCa) contributes to PCa initiation and metastatic progression. To comprehensively define the cancer-associated changes in miRNA targeting and function in commonly studied models of PCa, we performed photoactivatable ribonucleoside-enhanced cross-linking immunoprecipitation of the Argonaute protein in a panel of PCa cell lines modeling different stages of PCa progression. Using this comprehensive catalogue of miRNA targets, we analyzed miRNA targeting on known drivers of PCa and examined tissue-specific and stage-specific pathway targeting by miRNAs. We found that androgen receptor is the most frequently targeted PCa oncogene and that miR-148a targets the largest number of known PCa drivers. Globally, tissue-specific and stage-specific changes in miRNA targeting are driven by homeostatic response to active oncogenic pathways. Our findings indicate that, even in advanced PCa, the miRNA pool adapts to regulate continuing alterations in the cancer genome to balance oncogenic molecular changes. These findings are important because they are the first to globally characterize miRNA changes in PCa and demonstrate how the miRNA target spectrum responds to staged tumorigenesis.
Collapse
Affiliation(s)
- Mark P Hamilton
- Department of Molecular and Cell Biology, Baylor College of Medicine Hospital, Houston, TX, USA
| | - Kimal I Rajapakshe
- Department of Molecular and Cell Biology, Baylor College of Medicine Hospital, Houston, TX, USA; Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, TX, USA
| | - David A Bader
- Department of Molecular and Cell Biology, Baylor College of Medicine Hospital, Houston, TX, USA
| | - Jasmina Z Cerne
- Department of Molecular and Cell Biology, Baylor College of Medicine Hospital, Houston, TX, USA
| | - Eric A Smith
- Department of Molecular and Cell Biology, Baylor College of Medicine Hospital, Houston, TX, USA
| | - Cristian Coarfa
- Department of Molecular and Cell Biology, Baylor College of Medicine Hospital, Houston, TX, USA; Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, TX, USA
| | - Sean M Hartig
- Department of Molecular and Cell Biology, Baylor College of Medicine Hospital, Houston, TX, USA
| | - Sean E McGuire
- Department of Molecular and Cell Biology, Baylor College of Medicine Hospital, Houston, TX, USA; Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, TX, USA; Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
| |
Collapse
|
186
|
Tassi RA, Todeschini P, Siegel ER, Calza S, Cappella P, Ardighieri L, Cadei M, Bugatti M, Romani C, Bandiera E, Zanotti L, Tassone L, Guarino D, Santonocito C, Capoluongo ED, Beltrame L, Erba E, Marchini S, D'Incalci M, Donzelli C, Santin AD, Pecorelli S, Sartori E, Bignotti E, Odicino F, Ravaggi A. FOXM1 expression is significantly associated with chemotherapy resistance and adverse prognosis in non-serous epithelial ovarian cancer patients. JOURNAL OF EXPERIMENTAL & CLINICAL CANCER RESEARCH : CR 2017; 36:63. [PMID: 28482906 PMCID: PMC5422964 DOI: 10.1186/s13046-017-0536-y] [Citation(s) in RCA: 55] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/23/2016] [Accepted: 04/19/2017] [Indexed: 12/16/2022]
Abstract
BACKGROUND Epithelial ovarian cancer (EOC) is a spectrum of different diseases, which makes their treatment a challenge. Forkhead box M1 (FOXM1) is an oncogene aberrantly expressed in many solid cancers including serous EOC, but its role in non-serous EOCs remains undefined. We examined FOXM1 expression and its correlation to prognosis across the three major EOC subtypes, and its role in tumorigenesis and chemo-resistance in vitro. METHODS Gene signatures were generated by microarray for 14 clear-cell and 26 endometrioid EOCs, and 15 normal endometrium snap-frozen biopsies. Validation of FOXM1 expression was performed by RT-qPCR and immunohistochemistry in the same samples and additionally in 50 high-grade serous EOCs and in their most adequate normal controls (10 luminal fallopian tube and 20 ovarian surface epithelial brushings). Correlations of FOXM1 expression to clinic-pathological parameters and patients' prognosis were evaluated by Kaplan-Meier and Cox proportional-hazards analyses. OVCAR-3 and two novel deeply characterized EOC cell lines (EOC-CC1 and OSPC2, with clear-cell and serous subtype, respectively) were employed for in vitro studies. Effects of FOXM1 inhibition by transient siRNA transfection were evaluated on cell-proliferation, cell-cycle, colony formation, invasion, and response to conventional first- and second-line anticancer agents, and to the PARP-inhibitor olaparib. Gene signatures of FOXM1-silenced cell lines were generated by microarray and confirmed by RT-qPCR. RESULTS A significant FOXM1 mRNA up-regulation was found in EOCs compared to normal controls. FOXM1 protein overexpression significantly correlated to serous histology (p = 0.001) and advanced FIGO stage (p = 0.004). Multivariate analyses confirmed FOXM1 protein overexpression as an independent indicator of worse disease specific survival in non-serous EOCs, and of shorter time to progression in platinum-resistant cases. FOXM1 downregulation in EOC cell lines inhibited cell growth and clonogenicity, and promoted the cytotoxic effects of platinum compounds, doxorubicin hydrochloride and olaparib. Upon FOXM1 knock-down in EOC-CC1 and OSPC2 cells, microarray and RT-qPCR analyses revealed the deregulation of several common and other unique subtype-specific FOXM1 putative targets involved in cell cycle, metastasis, DNA repair and drug response. CONCLUSIONS FOXM1 is up-regulated in all three major EOCs subtypes, and is a prognostic biomarker and a potential combinatorial therapeutic target in platinum resistant disease, irrespective of tumor histology.
Collapse
Affiliation(s)
- Renata A Tassi
- Department of Obstetrics and Gynecology, "Angelo Nocivelli" Institute of Molecular Medicine, University of Brescia, Brescia, Italy.
| | - Paola Todeschini
- Department of Obstetrics and Gynecology, "Angelo Nocivelli" Institute of Molecular Medicine, University of Brescia, Brescia, Italy
| | - Eric R Siegel
- Department of Biostatistics, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Stefano Calza
- Department of Molecular and Translational Medicine, Unit of Biostatistics, University of Brescia, Brescia, Italy
| | | | - Laura Ardighieri
- Department of Molecular and Translational Medicine, Section of Pathology, University-ASST Spedali Civili of Brescia, Brescia, Italy
| | - Moris Cadei
- Department of Molecular and Translational Medicine, Section of Pathology, University-ASST Spedali Civili of Brescia, Brescia, Italy
| | - Mattia Bugatti
- Department of Molecular and Translational Medicine, Section of Pathology, University-ASST Spedali Civili of Brescia, Brescia, Italy
| | - Chiara Romani
- Department of Obstetrics and Gynecology, "Angelo Nocivelli" Institute of Molecular Medicine, University of Brescia, Brescia, Italy
| | - Elisabetta Bandiera
- Department of Obstetrics and Gynecology, "Angelo Nocivelli" Institute of Molecular Medicine, University of Brescia, Brescia, Italy
| | - Laura Zanotti
- Department of Obstetrics and Gynecology, "Angelo Nocivelli" Institute of Molecular Medicine, University of Brescia, Brescia, Italy
| | - Laura Tassone
- Department of Obstetrics and Gynecology, "Angelo Nocivelli" Institute of Molecular Medicine, University of Brescia, Brescia, Italy
| | - Donatella Guarino
- Laboratory of Clinical Molecular and Personalized Diagnostics, Institute of Biochemistry and Clinical Biochemistry, Catholic University and Foundation Gemelli Hospital, Rome, Italy
| | - Concetta Santonocito
- Laboratory of Clinical Molecular and Personalized Diagnostics, Institute of Biochemistry and Clinical Biochemistry, Catholic University and Foundation Gemelli Hospital, Rome, Italy
| | - Ettore D Capoluongo
- Laboratory of Clinical Molecular and Personalized Diagnostics, Institute of Biochemistry and Clinical Biochemistry, Catholic University and Foundation Gemelli Hospital, Rome, Italy
| | - Luca Beltrame
- Department of Oncology, IRCCS - "Mario Negri" Institute for Pharmacological Research, Milan, Italy
| | - Eugenio Erba
- Department of Oncology, IRCCS - "Mario Negri" Institute for Pharmacological Research, Milan, Italy
| | - Sergio Marchini
- Department of Oncology, IRCCS - "Mario Negri" Institute for Pharmacological Research, Milan, Italy
| | - Maurizio D'Incalci
- Department of Oncology, IRCCS - "Mario Negri" Institute for Pharmacological Research, Milan, Italy
| | - Carla Donzelli
- Department of Molecular and Translational Medicine, Section of Pathology, University-ASST Spedali Civili of Brescia, Brescia, Italy
| | - Alessandro D Santin
- Department of Obstetrics, Gynecology and Reproductive Sciences, Yale University School of Medicine, New Haven, CT, USA
| | - Sergio Pecorelli
- Department of Obstetrics and Gynecology, "Angelo Nocivelli" Institute of Molecular Medicine, University of Brescia, Brescia, Italy
| | - Enrico Sartori
- Department of Obstetrics and Gynecology, University of Brescia, Brescia, Italy
| | - Eliana Bignotti
- Division of Obstetrics and Gynecology, ASST Spedali Civili di Brescia, Brescia, Italy
| | - Franco Odicino
- Department of Obstetrics and Gynecology, University of Brescia, Brescia, Italy
| | - Antonella Ravaggi
- Department of Obstetrics and Gynecology, "Angelo Nocivelli" Institute of Molecular Medicine, University of Brescia, Brescia, Italy
| |
Collapse
|
187
|
Gu P, Chen X, Xie R, Han J, Xie W, Wang B, Dong W, Chen C, Yang M, Jiang J, Chen Z, Huang J, Lin T. lncRNA HOXD-AS1 Regulates Proliferation and Chemo-Resistance of Castration-Resistant Prostate Cancer via Recruiting WDR5. Mol Ther 2017; 25:1959-1973. [PMID: 28487115 DOI: 10.1016/j.ymthe.2017.04.016] [Citation(s) in RCA: 145] [Impact Index Per Article: 20.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2017] [Revised: 04/07/2017] [Accepted: 04/12/2017] [Indexed: 02/01/2023] Open
Abstract
Castration-resistant prostate cancer (CRPC) that occurs after the failure of androgen deprivation therapy is the leading cause of deaths in prostate cancer patients. Thus, there is an obvious and urgent need to fully understand the mechanism of CRPC and discover novel therapeutic targets. Long noncoding RNAs (lncRNAs) are crucial regulators in many human cancers, yet their potential roles and molecular mechanisms in CRPC are poorly understood. In this study, we discovered that an lncRNA HOXD-AS1 is highly expressed in CRPC cells and correlated closely with Gleason score, T stage, lymph nodes metastasis, and progression-free survival. Knockdown of HOXD-AS1 inhibited the proliferation and chemo-resistance of CRPC cells in vitro and in vivo. Furthermore, we identified several cell cycle, chemo-resistance, and castration-resistance-related genes, including PLK1, AURKA, CDC25C, FOXM1, and UBE2C, that were activated transcriptionally by HOXD-AS1. Further investigation revealed that HOXD-AS1 recruited WDR5 to directly regulate the expression of target genes by mediating histone H3 lysine 4 tri-methylation (H3K4me3). In conclusion, our findings indicate that HOXD-AS1 promotes proliferation, castration resistance, and chemo-resistance in prostate cancer by recruiting WDR5. This sheds a new insight into the regulation of CRPC by lncRNA and provides a potential approach for the treatment of CRPC.
Collapse
Affiliation(s)
- Peng Gu
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China; Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China
| | - Xu Chen
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China; Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China
| | - Ruihui Xie
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China; Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China
| | - Jinli Han
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China
| | - Weibin Xie
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China
| | - Bo Wang
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China; Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China
| | - Wen Dong
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China
| | - Changhao Chen
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China; Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China
| | - Meihua Yang
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China; Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China
| | - Junyi Jiang
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China; Department of Clinical Laboratory, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China
| | - Ziyue Chen
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China; Department of Pediatric Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China
| | - Jian Huang
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China.
| | - Tianxin Lin
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China; Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China.
| |
Collapse
|
188
|
Talos F, Mitrofanova A, Bergren SK, Califano A, Shen MM. A computational systems approach identifies synergistic specification genes that facilitate lineage conversion to prostate tissue. Nat Commun 2017; 8:14662. [PMID: 28429718 PMCID: PMC5413950 DOI: 10.1038/ncomms14662] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2016] [Accepted: 01/21/2017] [Indexed: 12/19/2022] Open
Abstract
To date, reprogramming strategies for generating cell types of interest have been facilitated by detailed understanding of relevant developmental regulatory factors. However, identification of such regulatory drivers often represents a major challenge, as specific gene combinations may be required for reprogramming. Here we show that a computational systems approach can identify cell type specification genes (master regulators) that act synergistically, and demonstrate its application for reprogramming of fibroblasts to prostate tissue. We use three such master regulators (FOXA1, NKX3.1 and androgen receptor, AR) in a primed conversion strategy starting from mouse fibroblasts, resulting in prostate tissue grafts with appropriate histological and molecular properties that respond to androgen-deprivation. Moreover, generation of reprogrammed prostate does not require traversal of a pluripotent state. Thus, we describe a general strategy by which cell types and tissues can be generated even with limited knowledge of the developmental pathways required for their specification in vivo.
Collapse
Affiliation(s)
- Flaminia Talos
- Department of Medicine, Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, New York 10032, USA.,Department of Systems Biology, Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, New York 10032, USA.,Department of Genetics and Development, Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, New York 10032, USA.,Department of Urology, Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, New York 10032, USA
| | - Antonina Mitrofanova
- Department of Systems Biology, Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, New York 10032, USA
| | - Sarah K Bergren
- Department of Medicine, Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, New York 10032, USA.,Department of Systems Biology, Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, New York 10032, USA.,Department of Genetics and Development, Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, New York 10032, USA.,Department of Urology, Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, New York 10032, USA
| | - Andrea Califano
- Department of Systems Biology, Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, New York 10032, USA
| | - Michael M Shen
- Department of Medicine, Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, New York 10032, USA.,Department of Systems Biology, Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, New York 10032, USA.,Department of Genetics and Development, Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, New York 10032, USA.,Department of Urology, Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, New York 10032, USA
| |
Collapse
|
189
|
Moran B, Rahman A, Palonen K, Lanigan FT, Gallagher WM. Master Transcriptional Regulators in Cancer: Discovery via Reverse Engineering Approaches and Subsequent Validation. Cancer Res 2017; 77:2186-2190. [PMID: 28428271 DOI: 10.1158/0008-5472.can-16-1813] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2016] [Revised: 09/08/2016] [Accepted: 02/22/2017] [Indexed: 11/16/2022]
Abstract
Reverse engineering of transcriptional networks using gene expression data enables identification of genes that underpin the development and progression of different cancers. Methods to this end have been available for over a decade and, with a critical mass of transcriptomic data in the oncology arena having been reached, they are ever more applicable. Extensive and complex networks can be distilled into a small set of key master transcriptional regulators (MTR), genes that are very highly connected and have been shown to be involved in processes of known importance in disease. Interpreting and validating the results of standardized bioinformatic methods is of crucial importance in determining the inherent value of MTRs. In this review, we briefly describe how MTRs are identified and focus on providing an overview of how MTRs can and have been validated for use in clinical decision making in malignant diseases, along with serving as tractable therapeutic targets. Cancer Res; 77(9); 2186-90. ©2017 AACR.
Collapse
Affiliation(s)
- Bruce Moran
- Cancer Biology and Therapeutics Laboratory, UCD School of Biomolecular and Biomedical Research, UCD Conway Institute, University College Dublin, Dublin, Ireland.,OncoMark Limited, NovaUCD, Belfield Innovation Park, Belfield, Dublin, Ireland
| | - Arman Rahman
- Cancer Biology and Therapeutics Laboratory, UCD School of Biomolecular and Biomedical Research, UCD Conway Institute, University College Dublin, Dublin, Ireland.,OncoMark Limited, NovaUCD, Belfield Innovation Park, Belfield, Dublin, Ireland
| | - Katja Palonen
- Cancer Biology and Therapeutics Laboratory, UCD School of Biomolecular and Biomedical Research, UCD Conway Institute, University College Dublin, Dublin, Ireland.,OncoMark Limited, NovaUCD, Belfield Innovation Park, Belfield, Dublin, Ireland
| | - Fiona T Lanigan
- Cancer Biology and Therapeutics Laboratory, UCD School of Biomolecular and Biomedical Research, UCD Conway Institute, University College Dublin, Dublin, Ireland
| | - William M Gallagher
- Cancer Biology and Therapeutics Laboratory, UCD School of Biomolecular and Biomedical Research, UCD Conway Institute, University College Dublin, Dublin, Ireland. .,OncoMark Limited, NovaUCD, Belfield Innovation Park, Belfield, Dublin, Ireland
| |
Collapse
|
190
|
Abstract
Gene expression changes, the driving forces for cellular diversity in multicellular organisms, are regulated by a diverse set of gene regulatory elements that direct transcription in specific cells. Mutations in these elements, ranging from chromosomal aberrations to single-nucleotide polymorphisms, are a major cause of human disease. However, we currently have a very limited understanding of how regulatory element genotypes lead to specific phenotypes. In this review, we discuss the various methods of regulatory element identification, the different types of mutations they harbor, and their impact on human disease. We highlight how these variations can affect transcription of multiple genes in gene regulatory networks. In addition, we describe how novel technologies, such as massively parallel reporter assays and CRISPR/Cas9 genome editing, are beginning to provide a better understanding of the functional roles that these elements have and how their alteration can lead to specific phenotypes.
Collapse
Affiliation(s)
- Sumantra Chatterjee
- Center for Complex Disease Genomics, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205;
| | - Nadav Ahituv
- Department of Bioengineering and Therapeutic Sciences and Institute for Human Genetics, University of California, San Francisco, California 94158;
| |
Collapse
|
191
|
Dutta A, Panja S, Virk RK, Kim JY, Zott R, Cremers S, Golombos DM, Liu D, Mosquera JM, Mostaghel EA, Barbieri CE, Mitrofanova A, Abate-Shen C. Co-clinical Analysis of a Genetically Engineered Mouse Model and Human Prostate Cancer Reveals Significance of NKX3.1 Expression for Response to 5α-reductase Inhibition. Eur Urol 2017; 72:499-506. [PMID: 28385453 DOI: 10.1016/j.eururo.2017.03.031] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2016] [Accepted: 03/21/2017] [Indexed: 12/30/2022]
Abstract
BACKGROUND Although men on active surveillance for prostate cancer (PCa) may benefit from intervention with 5α-reductase inhibitors (5-ARIs), it has not been resolved whether 5-ARIs are effective for delaying disease progression and, if so, whether specific patients are more likely to benefit. OBJECTIVE To identify molecular features predictive of patient response to 5-ARIs. DESIGN, SETTING, AND PARTICIPANTS Nkx3.1 mutant mice, a model of early-stage PCa, were treated with the 5-ARI finasteride, and histopathological and molecular analyses were performed. Cross-species computational analyses were used to compare expression profiles for treated mice with those of patients who had received 5-ARIs before prostatectomy. INTERVENTION Finasteride administered to Nkx3.1 mutant mice. 5-ARI-treated patient specimens obtained retrospectively. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS Endpoints in mice included histopathology, immunohistochemistry, and molecular profiling. GraphPad Prism software, R-studio, and Matlab were used for statistical and data analyses. RESULTS AND LIMITATIONS Finasteride treatment of Nkx3.1 mutant mice resulted in a significant reduction in prostatic intraepithelial neoplasia (PIN), as evident from histopathological and expression profiling analyses. Cross-species computational analysis comparing finasteride-treated mice with two independent 5-ARI-treated patient cohorts showed that reduced NKX3.1 expression is predictive of response to 5-ARI. A limitation of the study is that these retrospective human cohorts have relatively few patients with limited clinical outcome data. Future prospective clinical trials are needed to validate whether stratifying patients on the basis of NKX3.1 expression improves the benefit of 5-ARIs during active surveillance. CONCLUSIONS This co-clinical study implicates NKX3.1 status as a predictor of response to 5-ARIs, and suggests that molecular features, including NKX3.1 expression, may help to identify PCa patients most likely to benefit from 5-ARIs during active surveillance. PATIENT SUMMARY The aim of precision cancer prevention is to tailor interventions on the basis of individualized patient characteristics. We propose that patients with low NKX3.1 expression are optimal candidates for intervention with 5α-reductase inhibitors as an adjunct to active surveillance.
Collapse
Affiliation(s)
- Aditya Dutta
- Departments of Medicine and Urology, Institute of Cancer Genetics, Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, NY, USA
| | - Sukanya Panja
- Department of Health Informatics, Rutgers School of Health Professions, Rutgers Biomedical and Health Sciences, Newark, NJ, USA
| | - Renu K Virk
- Department of Pathology and Cell Biology, Columbia University Medical Center, NY, USA
| | - Jaime Yeji Kim
- Department of Medicine, Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, NY, USA
| | - Roseann Zott
- The Irving Institute for Clinical and Translational Medicine, Columbia University Medical Center, New York, NY, USA
| | - Serge Cremers
- Departments of Pathology & Cell Biology and Medicine, The Irving Institute for Clinical and Translational Medicine, Columbia University Medical Center, New York, NY, USA
| | - David M Golombos
- Department of Urology, Weill Cornell Medicine, New York, NY, USA
| | - Deli Liu
- Department of Urology, HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, New York, USA
| | - Juan Miguel Mosquera
- Department of Pathology and Laboratory Medicine, Englander Institute for Precision Medicine, Weill Cornell Medicine and New York-Presbyterian Hospital, New York, NY, USA
| | - Elahe A Mostaghel
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Christopher E Barbieri
- Department of Urology, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Antonina Mitrofanova
- Department of Health Informatics, Rutgers School of Health Professions, Rutgers Biomedical and Health Sciences, Newark, NJ, USA.
| | - Cory Abate-Shen
- Departments of Urology, Medicine, Pathology & Cell Biology, and Systems Biology, Institute of Cancer Genetics, Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, NY, USA.
| |
Collapse
|
192
|
Federico L, Chong Z, Zhang D, McGrail DJ, Zhao W, Jeong KJ, Vellano CP, Ju Z, Gagea M, Liu S, Mitra S, Dennison JB, Lorenzi PL, Cardnell R, Diao L, Wang J, Lu Y, Byers LA, Perou CM, Lin SY, Mills GB. A murine preclinical syngeneic transplantation model for breast cancer precision medicine. SCIENCE ADVANCES 2017; 3:e1600957. [PMID: 28439535 PMCID: PMC5397135 DOI: 10.1126/sciadv.1600957] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/01/2016] [Accepted: 03/01/2017] [Indexed: 05/05/2023]
Abstract
We previously demonstrated that altered activity of lysophosphatidic acid in murine mammary glands promotes tumorigenesis. We have now established and characterized a heterogeneous collection of mouse-derived syngeneic transplants (MDSTs) as preclinical platforms for the assessment of personalized pharmacological therapies. Detailed molecular and phenotypic analyses revealed that MDSTs are the most heterogeneous group of genetically engineered mouse models (GEMMs) of breast cancer yet observed. Response of MDSTs to trametinib, a mitogen-activated protein kinase (MAPK) kinase inhibitor, correlated with RAS/MAPK signaling activity, as expected from studies in xenografts and clinical trials providing validation of the utility of the model. Sensitivity of MDSTs to talazoparib, a poly(adenosine 5'-diphosphate-ribose) polymerase (PARP) inhibitor, was predicted by PARP1 protein levels and by a new PARP sensitivity predictor (PSP) score developed from integrated analysis of drug sensitivity data of human cell lines. PSP score-based classification of The Cancer Genome Atlas breast cancer suggested that a subset of patients with limited therapeutic options would be expected to benefit from PARP-targeted drugs. These results indicate that MDSTs are useful models for studies of targeted therapies, and propose novel potential biomarkers for identification of breast cancer patients likely to benefit from personalized pharmacological treatments.
Collapse
Affiliation(s)
- Lorenzo Federico
- Department of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- Corresponding author.
| | - Zechen Chong
- Department of Bioinformatics and Computational Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77230, USA
| | - Dong Zhang
- Department of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Daniel J. McGrail
- Department of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Wei Zhao
- Department of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Kang Jin Jeong
- Department of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Christopher P. Vellano
- Department of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Zhenlin Ju
- Department of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Mihai Gagea
- Department of Veterinary Medicine and Surgery, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Shuying Liu
- Department of Breast Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX 77230, USA
| | - Shreya Mitra
- Department of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Jennifer B. Dennison
- Department of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Philip L. Lorenzi
- Department of Bioinformatics and Computational Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77230, USA
| | - Robert Cardnell
- Department of Thoracic Head and Neck Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Lixia Diao
- Department of Bioinformatics and Computational Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77230, USA
| | - Jing Wang
- Department of Bioinformatics and Computational Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77230, USA
| | - Yiling Lu
- Department of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Lauren A. Byers
- Department of Thoracic Head and Neck Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Charles M. Perou
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA
| | - Shiaw-Yih Lin
- Department of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Gordon B. Mills
- Department of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| |
Collapse
|
193
|
Puig-Butille JA, Vinyals A, Ferreres JR, Aguilera P, Cabré E, Tell-Martí G, Marcoval J, Mateo F, Palomero L, Badenas C, Piulats JM, Malvehy J, Pujana MA, Puig S, Fabra À. AURKA Overexpression Is Driven by FOXM1 and MAPK/ERK Activation in Melanoma Cells Harboring BRAF or NRAS Mutations: Impact on Melanoma Prognosis and Therapy. J Invest Dermatol 2017; 137:1297-1310. [PMID: 28188776 DOI: 10.1016/j.jid.2017.01.021] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2016] [Revised: 01/04/2017] [Accepted: 01/16/2017] [Indexed: 12/31/2022]
Abstract
The cell cycle-related genes AURKA and FOXM1 are overexpressed in melanoma. We show here that AURKA overexpression is associated with poor prognosis in three independent cohorts of melanoma patients and correlates with the presence of genomic amplification of AURKA locus and BRAFV600E mutation. AURKA overexpression may also be driven by increased promoter activation through elements such as ETS and FOXM1 found within the 5' proximal promoter region. Activated MAPK/ERK signaling pathway mediates robust AURKA promoter activation, thereby knockdown of BRAFV600E and ERK inhibition results in reduced AURKA transcription and expression. We show a positive correlation between FOXM1 and AURKA expression in three independent cohorts of melanoma patients. FOXM1 silencing decreases expression of AURKA and late cell cycle genes in melanoma cells. We further found that FOXM1 expression levels are significantly higher in tumors carrying the BRAFV600E mutation compared with the wild-type BRAF (BRAFwt). Accordingly, the knockdown of BRAFV600E also reduces the expression of FOXM1 in BRAFV600E cells. Moreover, Aurora kinase A and FOXM1 inhibition by either genetic knockdown or pharmacologic inhibitors impair melanoma growth and survival both in culture and in vivo, underscoring their therapeutic value for melanoma patients who fail to benefit from BRAF/MEK signaling inhibition.
Collapse
Affiliation(s)
- Joan Anton Puig-Butille
- Biochemistry and Molecular Genetics Service, Melanoma Unit, Hospital Clínic, IDIBAPS, CIBERER, Barcelona, Spain
| | - Antònia Vinyals
- IDIBELL (Bellvitge Biomedical Research Institute), Centre d' Oncologia Molecular, Barcelona, Spain
| | - Josep R Ferreres
- Dermatology Service, IDIBELL-Hospital Universitari de Bellvitge, Barcelona, Spain
| | - Paula Aguilera
- Dermatology Department, Melanoma Unit, Hospital Clínic, IDIBAPS, CIBERER, Barcelona, Spain
| | - Eduard Cabré
- IDIBELL (Bellvitge Biomedical Research Institute), Centre d' Oncologia Molecular, Barcelona, Spain
| | - Gemma Tell-Martí
- Dermatology Department, Melanoma Unit, Hospital Clínic, IDIBAPS, CIBERER, Barcelona, Spain
| | - Joaquim Marcoval
- Dermatology Service, IDIBELL-Hospital Universitari de Bellvitge, Barcelona, Spain
| | - Francesca Mateo
- Program Against Cancer Therapeutic Resistance (ProCURE), Catalan Institute of Oncology (ICO), IDIBELL, Barcelona, Spain
| | - Luís Palomero
- Program Against Cancer Therapeutic Resistance (ProCURE), Catalan Institute of Oncology (ICO), IDIBELL, Barcelona, Spain
| | - Celia Badenas
- Biochemistry and Molecular Genetics Service, Melanoma Unit, Hospital Clínic, IDIBAPS, CIBERER, Barcelona, Spain
| | - Josep M Piulats
- Program Against Cancer Therapeutic Resistance (ProCURE), Catalan Institute of Oncology (ICO), IDIBELL, Barcelona, Spain
| | - Josep Malvehy
- Dermatology Department, Melanoma Unit, Hospital Clínic, IDIBAPS, CIBERER, Barcelona, Spain
| | - Miquel A Pujana
- Program Against Cancer Therapeutic Resistance (ProCURE), Catalan Institute of Oncology (ICO), IDIBELL, Barcelona, Spain
| | - Susana Puig
- Dermatology Department, Melanoma Unit, Hospital Clínic, IDIBAPS, CIBERER, Barcelona, Spain
| | - Àngels Fabra
- IDIBELL (Bellvitge Biomedical Research Institute), Centre d' Oncologia Molecular, Barcelona, Spain.
| |
Collapse
|
194
|
Abstract
Recent studies across multiple tumour types are starting to reveal a recurrent regulatory architecture in which genomic alterations cluster upstream of functional master regulator (MR) proteins, the aberrant activity of which is both necessary and sufficient to maintain tumour cell state. These proteins form small, hyperconnected and autoregulated modules (termed tumour checkpoints) that are increasingly emerging as optimal biomarkers and therapeutic targets. Crucially, as their activity is mostly dysregulated in a post-translational manner, rather than by mutations in their corresponding genes or by differential expression, the identification of MR proteins by conventional methods is challenging. In this Opinion article, we discuss novel methods for the systematic analysis of MR proteins and of the modular regulatory architecture they implement, including their use as a valuable reductionist framework to study the genetic heterogeneity of human disease and to drive key translational applications.
Collapse
Affiliation(s)
- Andrea Califano
- Department of Systems Biology, Columbia University, and the Departments of Biomedical Informatics, Biochemistry and Molecular Biophysics, JP Sulzberger Columbia Genome Center, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, New York 10032, USA
| | - Mariano J Alvarez
- DarwinHealth, Inc., 3960 Broadway, Suite 540, New York, New York 10032, USA
| |
Collapse
|
195
|
Transcriptomic analysis of gene expression profiles of stomach carcinoma reveal abnormal expression of mitotic components. Life Sci 2017; 170:41-49. [DOI: 10.1016/j.lfs.2016.12.001] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2016] [Revised: 11/24/2016] [Accepted: 12/01/2016] [Indexed: 12/16/2022]
|
196
|
Fused Regression for Multi-source Gene Regulatory Network Inference. PLoS Comput Biol 2016; 12:e1005157. [PMID: 27923054 PMCID: PMC5140053 DOI: 10.1371/journal.pcbi.1005157] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2016] [Accepted: 09/20/2016] [Indexed: 12/03/2022] Open
Abstract
Understanding gene regulatory networks is critical to understanding cellular differentiation and response to external stimuli. Methods for global network inference have been developed and applied to a variety of species. Most approaches consider the problem of network inference independently in each species, despite evidence that gene regulation can be conserved even in distantly related species. Further, network inference is often confined to single data-types (single platforms) and single cell types. We introduce a method for multi-source network inference that allows simultaneous estimation of gene regulatory networks in multiple species or biological processes through the introduction of priors based on known gene relationships such as orthology incorporated using fused regression. This approach improves network inference performance even when orthology mapping and conservation are incomplete. We refine this method by presenting an algorithm that extracts the true conserved subnetwork from a larger set of potentially conserved interactions and demonstrate the utility of our method in cross species network inference. Last, we demonstrate our method’s utility in learning from data collected on different experimental platforms. Gene regulatory networks describing related biological processes are thought to share conserved interaction structure. This assumption motivates a great deal of work in model systems–where discovery of gene regulation may be more experimentally tractable–but is difficult to directly evaluate using existing methods. The presence of shared structure in a well studied model system or process should make the problem of network inference in a related process easier, but this information is not often applied to the discovery of global gene regulatory networks. Further, to be able to successfully translate findings between different organisms, it is important to be able to identify where regulatory structure is different. We provide a method based on penalized fused regression for inferring gene regulatory networks given prior knowledge about the similarity of interactions in each network. This method is demonstrated on synthetic data, and applied to the problem of inferring networks in distantly related bacterial organisms. We then introduce an extension of the method to deal with the condition of uncertainty over the degree of regulatory conservation by simultaneously inferring gene conservation and interaction weights.
Collapse
|
197
|
Winter JM, Gildea DE, Andreas JP, Gatti DM, Williams KA, Lee M, Hu Y, Zhang S, Mullikin JC, Wolfsberg TG, McDonnell SK, Fogarty ZC, Larson MC, French AJ, Schaid DJ, Thibodeau SN, Churchill GA, Crawford NPS. Mapping Complex Traits in a Diversity Outbred F1 Mouse Population Identifies Germline Modifiers of Metastasis in Human Prostate Cancer. Cell Syst 2016; 4:31-45.e6. [PMID: 27916600 DOI: 10.1016/j.cels.2016.10.018] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2016] [Revised: 09/08/2016] [Accepted: 10/20/2016] [Indexed: 01/02/2023]
Abstract
It is unclear how standing genetic variation affects the prognosis of prostate cancer patients. To provide one controlled answer to this problem, we crossed a dominant, penetrant mouse model of prostate cancer to Diversity Outbred mice, a collection of animals that carries over 40 million SNPs. Integration of disease phenotype and SNP variation data in 493 F1 males identified a metastasis modifier locus on Chromosome 8 (LOD = 8.42); further analysis identified the genes Rwdd4, Cenpu, and Casp3 as functional effectors of this locus. Accordingly, analysis of over 5,300 prostate cancer patient samples revealed correlations between the presence of genetic variants at these loci, their expression levels, cancer aggressiveness, and patient survival. We also observed that ectopic overexpression of RWDD4 and CENPU increased the aggressiveness of two human prostate cancer cell lines. In aggregate, our approach demonstrates how well-characterized genetic variation in mice can be harnessed in conjunction with systems genetics approaches to identify and characterize germline modifiers of human disease processes.
Collapse
Affiliation(s)
- Jean M Winter
- Genetics and Molecular Biology Branch, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Derek E Gildea
- Computational and Statistical Genomics Branch, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Jonathan P Andreas
- Genetics and Molecular Biology Branch, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | | | - Kendra A Williams
- Genetics and Molecular Biology Branch, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Minnkyong Lee
- Genetics and Molecular Biology Branch, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Ying Hu
- Center for Biomedical Informatics and Information Technology, National Cancer Institute, NIH, Rockville, MD 20892, USA
| | - Suiyuan Zhang
- Computational and Statistical Genomics Branch, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | -
- NIH Intramural Sequencing Center, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - James C Mullikin
- NIH Intramural Sequencing Center, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Tyra G Wolfsberg
- Computational and Statistical Genomics Branch, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Shannon K McDonnell
- Department of Health Sciences Research, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN 55905, USA
| | - Zachary C Fogarty
- Department of Health Sciences Research, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN 55905, USA
| | - Melissa C Larson
- Department of Health Sciences Research, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN 55905, USA
| | - Amy J French
- Department of Laboratory Medicine and Pathology, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN 55905, USA
| | - Daniel J Schaid
- Department of Health Sciences Research, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN 55905, USA
| | - Stephen N Thibodeau
- Department of Laboratory Medicine and Pathology, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN 55905, USA
| | | | - Nigel P S Crawford
- Genetics and Molecular Biology Branch, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA.
| |
Collapse
|
198
|
Abstract
Genomic and transcriptional studies have identified discrete molecular subtypes of bladder cancer. These observations could be the starting point to identify new treatments. Several members of the forkhead box (FOX) superfamily of transcription factors have been found to be differentially expressed in the different bladder cancer subtypes. In addition, the FOXA protein family are key regulators of embryonic bladder development and patterning. Both experimental and clinical data support a role for FOXA1 and FOXA2 in urothelial carcinoma. FOXA1 is expressed in embryonic and adult urothelium and its expression is altered in urothelial carcinomas and across disparate molecular bladder cancer subtypes. FOXA2 is normally absent from the adult urothelium, but developmental studies identified FOXA2 as a marker of a transient urothelial progenitor cell population during bladder development. Studies also implicate FOXA2 in bladder cancer and several other FOX proteins might be involved in development and/or progression of this disease; for example, FOXA1 and FOXO3A have been associated with clinical patient outcomes. Future studies should investigate to what extent and by which mechanisms FOX proteins might be directly involved in bladder cancer pathogenesis and treatment responses.
Collapse
|
199
|
Jeter CR, Liu B, Lu Y, Chao HP, Zhang D, Liu X, Chen X, Li Q, Rycaj K, Calhoun-Davis T, Yan L, Hu Q, Wang J, Shen J, Liu S, Tang DG. NANOG reprograms prostate cancer cells to castration resistance via dynamically repressing and engaging the AR/FOXA1 signaling axis. Cell Discov 2016; 2:16041. [PMID: 27867534 PMCID: PMC5109294 DOI: 10.1038/celldisc.2016.41] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2016] [Accepted: 10/18/2016] [Indexed: 12/24/2022] Open
Abstract
The pluripotency transcription factor NANOG has been implicated in tumor development, and NANOG-expressing cancer cells manifest stem cell properties that sustain tumor homeostasis, mediate therapy resistance and fuel tumor progression. However, how NANOG converges on somatic circuitry to trigger oncogenic reprogramming remains obscure. We previously reported that inducible NANOG expression propels the emergence of aggressive castration-resistant prostate cancer phenotypes. Here we first show that endogenous NANOG is required for the growth of castration-resistant prostate cancer xenografts. Genome-wide chromatin immunoprecipitation sequencing coupled with biochemical assays unexpectedly reveals that NANOG co-occupies a distinctive proportion of androgen receptor/Forkhead box A1 genomic loci and physically interacts with androgen receptor and Forkhead box A1. Integrative analysis of chromatin immunoprecipitation sequencing and time-resolved RNA sequencing demonstrates that NANOG dynamically alters androgen receptor/Forkhead box A1 signaling leading to both repression of androgen receptor-regulated pro-differentiation genes and induction of genes associated with cell cycle, stem cells, cell motility and castration resistance. Our studies reveal global molecular mechanisms whereby NANOG reprograms prostate cancer cells to a clinically relevant castration-resistant stem cell-like state driven by distinct NANOG-regulated gene clusters that correlate with patient survival. Thus, reprogramming factors such as NANOG may converge on and alter lineage-specific master transcription factors broadly in somatic cancers, thereby facilitating malignant disease progression and providing a novel route for therapeutic resistance.
Collapse
Affiliation(s)
- Collene R Jeter
- Department of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center , Smithville, TX, USA
| | - Bigang Liu
- Department of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center , Smithville, TX, USA
| | - Yue Lu
- Department of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center , Smithville, TX, USA
| | - Hsueh-Ping Chao
- Department of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center , Smithville, TX, USA
| | - Dingxiao Zhang
- Department of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Smithville, TX, USA; Department of Pharmacology and Therapeutics, Roswell Park Cancer Institute, Buffalo, NY, USA
| | - Xin Liu
- Department of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center , Smithville, TX, USA
| | - Xin Chen
- Department of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Smithville, TX, USA; Department of Pharmacology and Therapeutics, Roswell Park Cancer Institute, Buffalo, NY, USA
| | - Qiuhui Li
- Department of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Smithville, TX, USA; Department of Pharmacology and Therapeutics, Roswell Park Cancer Institute, Buffalo, NY, USA
| | - Kiera Rycaj
- Department of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Smithville, TX, USA; Department of Pharmacology and Therapeutics, Roswell Park Cancer Institute, Buffalo, NY, USA
| | - Tammy Calhoun-Davis
- Department of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center , Smithville, TX, USA
| | - Li Yan
- Department of Biostatistics and Bioinformatics, Roswell Park Cancer Institute , Buffalo, NY, USA
| | - Qiang Hu
- Department of Biostatistics and Bioinformatics, Roswell Park Cancer Institute , Buffalo, NY, USA
| | - Jianmin Wang
- Department of Biostatistics and Bioinformatics, Roswell Park Cancer Institute , Buffalo, NY, USA
| | - Jianjun Shen
- Department of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center , Smithville, TX, USA
| | - Song Liu
- Department of Biostatistics and Bioinformatics, Roswell Park Cancer Institute , Buffalo, NY, USA
| | - Dean G Tang
- Department of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Smithville, TX, USA; Department of Pharmacology and Therapeutics, Roswell Park Cancer Institute, Buffalo, NY, USA; Cancer Stem Cell Institute, Research Center for Translational Medicine, East Hospital, Tongji University School of Medicine, Shanghai, China; Centers for Cancer Epigenetics, Stem Cell and Developmental Biology, RNA Interference and Non-coding RNAs and Molecular Carcinogenesis, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| |
Collapse
|
200
|
Osako Y, Seki N, Kita Y, Yonemori K, Koshizuka K, Kurozumi A, Omoto I, Sasaki K, Uchikado Y, Kurahara H, Maemura K, Natsugoe S. Regulation of MMP13 by antitumor microRNA-375 markedly inhibits cancer cell migration and invasion in esophageal squamous cell carcinoma. Int J Oncol 2016; 49:2255-2264. [PMID: 27779648 PMCID: PMC5117997 DOI: 10.3892/ijo.2016.3745] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2016] [Accepted: 09/28/2016] [Indexed: 02/06/2023] Open
Abstract
Esophageal squamous cell carcinoma (ESCC) is one of the most aggressive malignancies. Recently developed molecular targeted therapies are not available for patients with ESCC. After curative surgical resection, patients frequently suffer distant metastasis and recurrence. Exploration of novel ESCC metastatic pathways may lead to the development of new treatment protocols for this disease. Accordingly, we have sequentially identified microRNA (miRNA)-mediated metastatic pathways in several cancers. Our past studies of miRNA expression signatures have shown that microRNA-375 (miR-375) is frequently reduced in several types of cancers, including ESCC. In the present study, we aimed to investigate novel miR-375-mediated metastatic pathways in ESCC cells. The expression of miR-375 was downregulated in ESCC tissues, and ectopic expression of this miRNA markedly inhibited cancer cell migration and invasion, suggesting that miR-375 acted as an antimetastatic miRNA in ESCC cells. Our strategies for miRNA target searching demonstrated that matrix metalloproteinase 13 (MMP13) was directly regulated by miR-375 in ESCC cells. Overexpression of MMP13 was observed in ESCC clinical tissues, and the expression of MMP13 promoted cancer cell aggressiveness. Moreover, oncogenic genes, including CENPF, KIF14 and TOP2A, were shown to be regulated downstream of MMP13. Taken together, these findings demonstrated that the antitumor miR-375/oncogenic MMP13 axis had a pivotal role in ESCC aggressiveness. These results provide novel insights into the potential mechanisms of ESCC pathogenesis.
Collapse
Affiliation(s)
- Yusaku Osako
- Department of Digestive Surgery, Breast and Thyroid Surgery, Graduate School of Medical Sciences, Kagoshima University, Sakuragaoka, Kagoshima 890-8520, Japan
| | - Naohiko Seki
- Department of Functional Genomics, Chiba University Graduate School of Medicine, Chuo-ku, Chiba 260-8670, Japan
| | - Yoshiaki Kita
- Department of Digestive Surgery, Breast and Thyroid Surgery, Graduate School of Medical Sciences, Kagoshima University, Sakuragaoka, Kagoshima 890-8520, Japan
| | - Keiichi Yonemori
- Department of Digestive Surgery, Breast and Thyroid Surgery, Graduate School of Medical Sciences, Kagoshima University, Sakuragaoka, Kagoshima 890-8520, Japan
| | - Keiichi Koshizuka
- Department of Functional Genomics, Chiba University Graduate School of Medicine, Chuo-ku, Chiba 260-8670, Japan
| | - Akira Kurozumi
- Department of Functional Genomics, Chiba University Graduate School of Medicine, Chuo-ku, Chiba 260-8670, Japan
| | - Itaru Omoto
- Department of Digestive Surgery, Breast and Thyroid Surgery, Graduate School of Medical Sciences, Kagoshima University, Sakuragaoka, Kagoshima 890-8520, Japan
| | - Ken Sasaki
- Department of Digestive Surgery, Breast and Thyroid Surgery, Graduate School of Medical Sciences, Kagoshima University, Sakuragaoka, Kagoshima 890-8520, Japan
| | - Yasuto Uchikado
- Department of Digestive Surgery, Breast and Thyroid Surgery, Graduate School of Medical Sciences, Kagoshima University, Sakuragaoka, Kagoshima 890-8520, Japan
| | - Hiroshi Kurahara
- Department of Digestive Surgery, Breast and Thyroid Surgery, Graduate School of Medical Sciences, Kagoshima University, Sakuragaoka, Kagoshima 890-8520, Japan
| | - Kosei Maemura
- Department of Digestive Surgery, Breast and Thyroid Surgery, Graduate School of Medical Sciences, Kagoshima University, Sakuragaoka, Kagoshima 890-8520, Japan
| | - Shoji Natsugoe
- Department of Digestive Surgery, Breast and Thyroid Surgery, Graduate School of Medical Sciences, Kagoshima University, Sakuragaoka, Kagoshima 890-8520, Japan
| |
Collapse
|