Structural and molecular analysis of the cancer prostate cell line PC3: Oocyte zona pellucida glycoproteins

Costa, J. Pinto da; Pereira, Rute; Oliveira, Jorge; Alves, Ângela; Marques-Magalhães, Ângela; Frutuoso, Amaro; Leal, Carla Bianca de Matos; Barros, Nuno; Fernandes, Rui; Almeida, Diogo Queiroz; Barreiro, Márcia; Barros, Alberto; Sousa, Mário; Sá, Rosália

doi:10.1016/j.tice.2018.11.001

Cited by 10 publications

(8 citation statements)

References 26 publications

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“…Interestingly, the majority of those 201 peaks are in enhancer regions (i.e., 173 peaks corresponding to 77 unique genes). The 77 genes with enhancers that gained DNMT3B binding upon PTS fell into several functional categories: (1) oncogenes such as PITPNC1 [ 46 ], NOTCH2NL [ 40 ], TNNT2 [ 47 ], and ZP4 [ 48 ], (2) long noncoding RNAs (lncRNAs) such as DANT2 , LINC00910 , and LOC102724511 , (3) microRNAs miR4477A and miR4477B , (4) small noncoding RNAs RNVU1-18 and SNAR-A14 ), (5) pseudogenes LOC100130331 , LOC102724580 , and (6) epigenetic regulator SMARCA4 , which is the ATPase of the chromatin-remodeling SWI/SNF complexes [ 49 ]. Many of those genes are linked to functions and processes that drive cancer.…”

Section: Resultsmentioning

confidence: 99%

“…We next focused on the 17 genes for further analysis and refer to these genes as ‘candidate genes with epigenetically targeted enhancers in response to PTS’ ( Figure 2 B). Among them, there were known oncogenes, PITPNC1 [ 46 ], TNNT2 [ 47 ], and ZP4 [ 48 ], and lncRNAs with a putative oncogenic role, such as DANT2 and LINC00910 , that we mentioned in the previous paragraph. We also found several genes that may function as oncogenes within the context of breast cancer.…”

Section: Resultsmentioning

confidence: 99%

“…Genes assigned to the 17 enhancers included oncogenes and pro-metastatic genes ( PITPNC1 [ 46 ], TNNT2 [ 47 ], ZP4 [ 48 ], CUX1 [ 55 ], RYR2 [ 57 , 58 ]), and putative oncogenes ( DANT2 and LINC00910 ). Indeed, enrichment of ectopic H3K36me3 at oncogenes has previously been reported in different cancers, including breast cancer, and associated with gene upregulation [ 73 , 74 , 75 , 76 , 77 ].…”

Section: Discussionmentioning

confidence: 99%

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Pterostilbene Changes Epigenetic Marks at Enhancer Regions of Oncogenes in Breast Cancer Cells

et al. 2021

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Epigenetic aberrations are linked to sporadic breast cancer. Interestingly, certain dietary polyphenols with anti-cancer effects, such as pterostilbene (PTS), have been shown to regulate gene expression by altering epigenetic patterns. Our group has proposed the involvement of DNA methylation and DNA methyltransferase 3B (DNMT3B) as vital players in PTS-mediated suppression of candidate oncogenes and suggested a role of enhancers as target regions. In the present study, we assess a genome-wide impact of PTS on epigenetic marks at enhancers in highly invasive MCF10CA1a breast cancer cells. Following chromatin immunoprecipitation (ChIP)-sequencing in MCF10CA1a cells treated with 7 μM PTS for 9 days, we discovered that PTS leads to increased binding of DNMT3B at enhancers of 77 genes, and 17 of those genes display an overlapping decrease in the occupancy of trimethylation at lysine 36 of histone 3 (H3K36me3), a mark of active enhancers. We selected two genes, PITPNC1 and LINC00910, and found that their enhancers are hypermethylated in response to PTS. These changes coincided with the downregulation of gene expression. Of importance, we showed that 6 out of 17 target enhancers, including PITPNC1 and LINC00910, are bound by an oncogenic transcription factor OCT1 in MCF10CA1a cells. Indeed, the six enhancers corresponded to genes with established or putative cancer-driving functions. PTS led to a decrease in OCT1 binding at those enhancers, and OCT1 depletion resulted in PITPNC1 and LINC00910 downregulation, further demonstrating a role for OCT1 in transcriptional regulation. Our findings provide novel evidence for the epigenetic regulation of enhancer regions by dietary polyphenols in breast cancer cells.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Pterostilbene Changes Epigenetic Marks at Enhancer Regions of Oncogenes in Breast Cancer Cells

et al. 2021

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“…ZP4 , a component of the oocyte zona pellucida, has not been implicated as a driver gene or in the prognosis of any cancer but ranks first in four samples. ZP4 has recently been detected in a prostate cell line and prostatic adenocarcinoma with the suggestion that it might be useful as a prognostic marker or be part of tumor immunosurveillance processes [53]. CRX ranks first in four samples; CRX is a cone-rod homoeobox transcription factor which plays a role in the differentiation program of photoreceptor cells and has been strongly implicated in the growth and differentiation of an aggressive sub-class of medulloblastoma [54].…”

Section: Discussionmentioning

confidence: 99%

DeepMOCCA: A pan-cancer prognostic model identifies personalized prognostic markers through graph attention and multi-omics data integration

Althubaiti

Kulmanov

Liu

et al. 2021

Preprint

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Combining multiple types of genomic, transcriptional, proteomic, and epigenetic datasets has the potential to reveal biological mechanisms across multiple scales, and may lead to more accurate models for clinical decision support. Developing efficient models that can derive clinical outcomes from high-dimensional data remains problematical; challenges include the integration of multiple types of omics data, inclusion of biological background knowledge, and developing machine learning models that are able to deal with this high dimensionality while having only few samples from which to derive a model. We developed DeepMOCCA, a framework for multi-omics cancer analysis. We combine different types of omics data using biological relations between genes, transcripts, and proteins, combine the multi-omics data with background knowledge in the form of protein-protein interaction networks, and use graph convolution neural networks to exploit this combination of multi-omics data and background knowledge. DeepMOCCA predicts survival time for individual patient samples for 33 cancer types and outperforms most existing survival prediction methods. Moreover, DeepMOCCA includes a graph attention mechanism which prioritizes driver genes and prognostic markers in a patient-specific manner; the attention mechanism can be used to identify drivers and prognostic markers within cohorts and individual patients.

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“…ZP3 has been described to be the primary sperm receptor [ 13 ]. This protein has already been detected in normal and cancerous tissues, particularly investigated in prostate cancer cells [ 14 ]. A treatment strategy in mice for ovarian cancer that is based upon immunization against murine ZP3 has also been published [ 15 ].…”

Section: Introductionmentioning

confidence: 99%

Neoexpression of JUNO in Oral Tumors Is Accompanied with the Complete Suppression of Four Other Genes and Suggests the Application of New Biomarker Tools

Kraus

Weider

Probstmeier

et al. 2022

JPM

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Background. Our study describes the neoexpression (Juno) and suppression (catsperD, dysferlin, Fer1L5 and otoferlin) of selected genes in oral squamous cell carcinomas (OSCCs). As the expression pattern of these genes allows a “yes” or “no” statement by exhibiting an inverse expression pattern in malignant versus benign tissues, they represent potential biomarkers for the characterization of oral malignancies, particularly OSCCs. Methods. Differential expression analyses of selected genes of interest were examined by quantitative PCR of oral cancer tissues compared to normal. Results. Five candidates out of initially nine genes were examined, demonstrating Juno as a putative new tumor marker selectively expressed in OSCCs. Interestingly, the expression of four other genes in benign tissues was completely repressed in tumor tissues with a specificity and sensitivity of 100%. No correlation was observed regarding patients’ sex, tumor staging and grading, and tumor site. Conclusion. The present study shows novel candidates that might be useful tools for oral cancer diagnosis. The neoexpression of Juno in cancerous tissues makes it a promising target molecule regarding its potential in diagnosis as well a therapeutic tool. Moreover, our observations suggest that also the repression of gene expression can be used for diagnosing—at least—OSCCs.

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Structural and molecular analysis of the cancer prostate cell line PC3: Oocyte zona pellucida glycoproteins

Cited by 10 publications

References 26 publications

Pterostilbene Changes Epigenetic Marks at Enhancer Regions of Oncogenes in Breast Cancer Cells

Pterostilbene Changes Epigenetic Marks at Enhancer Regions of Oncogenes in Breast Cancer Cells

DeepMOCCA: A pan-cancer prognostic model identifies personalized prognostic markers through graph attention and multi-omics data integration

Neoexpression of JUNO in Oral Tumors Is Accompanied with the Complete Suppression of Four Other Genes and Suggests the Application of New Biomarker Tools

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