Active vitamin D induces gene-specific hypomethylation in prostate cancer cells developing vitamin D resistance

2020 ◽  
Vol 318 (5) ◽  
pp. C836-C847 ◽  
Author(s):  
Guan-Rong Lai ◽  
Yi-Fen Lee ◽  
Shian-Jang Yan ◽  
Huei-Ju Ting
Keyword(s):  
Prostate Cancer ◽  
Vitamin D ◽  
Cancer Progression ◽  
Transcriptional Activation ◽  
Cell Model ◽  
In Silico Analysis ◽  
Dna Methyltransferases ◽  
The Cancer Genome Atlas ◽  
Data Set ◽  
Cancer Data

Prostate cancer (PCa) is a leading cause of cancer death in men. Despite the antiproliferative effects of 1α,25-dihydroxyvitamin D3 [1,25(OH)2D3] on PCa, accumulating evidence indicates that 1,25(OH)2D3 promotes cancer progression by increasing genome plasticity. Our investigation of epigenetic changes associated with vitamin D insensitivity found that 1,25(OH)2D3 treatment reduced the expression levels and activities of DNA methyltransferases 1 and 3B (DNMT1 and DNMT3B, respectively). In silico analysis and reporter assay confirmed that 1,25(OH)2D3 downregulated transcriptional activation of the DNMT3B promoter and upregulated microRNAs targeting the 3′-untranslated regions of DNMT3B. We then profiled DNA methylation in the vitamin D-resistant PC-3 cells and a resistant PCa cell model generated by long-term 1,25(OH)2D3 exposure. Several candidate genes were found to be hypomethylated and overexpressed in vitamin D-resistant PCa cells compared with vitamin D-sensitive cells. Most of the identified genes were associated with mammalian target of rapamycin (mTOR) signaling activation, which is known to promote cancer progression. Among them, we found that inhibition of ribosomal protein S6 kinase A1 (RPS6KA1) promoted vitamin D sensitivity in PC-3 cells. Furthermore, The Cancer Genome Atlas (TCGA) prostate cancer data set demonstrated that midline 1 ( MID1) expression is positively correlated with tumor stage. Overall, our study reveals an inhibitory mechanism of 1,25(OH)2D3 on DNMT3B, which may contribute to vitamin D resistance in PCa.

scholarly journals Differential Expression of a Panel of Ten CNTN1-Associated Genes during Prostate Cancer Progression and the Predictive Properties of the Panel towards Prostate Cancer Relapse

Genes ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 257
Author(s):  
Yan Gu ◽  
Mathilda Jing Chow ◽  
Anil Kapoor ◽  
Xiaozeng Lin ◽  
Wenjuan Mei ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Differential Expression ◽  
Cancer Progression ◽  
Lncap Cell ◽  
Endocrine Resistance ◽  
Gene Panel ◽  
The Cancer Genome Atlas ◽  
Cancer Center ◽  
Poor Overall Survival ◽  
Cell Renal Cell Carcinoma

Contactin 1 (CNTN1) is a new oncogenic protein of prostate cancer (PC); its impact on PC remains incompletely understood. We observed CNTN1 upregulation in LNCaP cell-derived castration-resistant PCs (CRPC) and CNTN1-mediated enhancement of LNCaP cell proliferation. CNTN1 overexpression in LNCaP cells resulted in enrichment of the CREIGHTON_ENDOCRINE_THERAPY_RESISTANCE_3 gene set that facilitates endocrine resistance in breast cancer. The leading-edge (LE) genes (n = 10) of this enrichment consist of four genes with limited knowledge on PC and six genes novel to PC. These LE genes display differential expression during PC initiation, metastatic progression, and CRPC development, and they predict PC relapse following curative therapies at hazard ratio (HR) 2.72, 95% confidence interval (CI) 1.96–3.77, and p = 1.77 × 10−9 in The Cancer Genome Atlas (TCGA) PanCancer cohort (n = 492) and HR 2.72, 95% CI 1.84–4.01, and p = 4.99 × 10−7 in Memorial Sloan Kettering Cancer Center (MSKCC) cohort (n = 140). The LE gene panel classifies high-, moderate-, and low-risk of PC relapse in both cohorts. Additionally, the gene panel robustly predicts poor overall survival in clear cell renal cell carcinoma (ccRCC, p = 1.13 × 10−11), consistent with ccRCC and PC both being urogenital cancers. Collectively, we report multiple CNTN1-related genes relevant to PC and their biomarker values in predicting PC relapse.

scholarly journals Transcriptomics Signature from Next-Generation Sequencing Data Reveals New Transcriptomic Biomarkers Related to Prostate Cancer

2019 ◽  
Vol 18 ◽  
pp. 117693511983552 ◽  
Author(s):  
Abedalrhman Alkhateeb ◽  
Iman Rezaeian ◽  
Siva Singireddy ◽  
Dora Cavallo-Medved ◽  
Lisa A Porter ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Next Generation Sequencing ◽  
Cancer Progression ◽  
Machine Learning Techniques ◽  
Next Generation Sequencing Data ◽  
Prognostic Indicators ◽  
Next Generation ◽  
Sequencing Data ◽  
Cancer Data ◽  
Generation Sequencing

Prostate cancer is one of the most common types of cancer among Canadian men. Next-generation sequencing using RNA-Seq provides large amounts of data that may reveal novel and informative biomarkers. We introduce a method that uses machine learning techniques to identify transcripts that correlate with prostate cancer development and progression. We have isolated transcripts that have the potential to serve as prognostic indicators and may have tremendous value in guiding treatment decisions. Analysis of normal versus malignant prostate cancer data sets indicates differential expression of the genes HEATR5B, DDC, and GABPB1-AS1 as potential prostate cancer biomarkers. Our study also supports PTGFR, NREP, SCARNA22, DOCK9, FLVCR2, IK2F3, USP13, and CLASP1 as potential biomarkers to predict prostate cancer progression, especially between stage II and subsequent stages of the disease.

Vitamin D and prostate cancer: The role of membrane initiated signaling pathways in prostate cancer progression

2010 ◽  
Vol 121 (1-2) ◽  
pp. 413-416 ◽  
Author(s):  
Sandra Karlsson ◽  
Josefin Olausson ◽  
Dan Lundh ◽  
Peter Sögård ◽  
Abul Mandal ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Vitamin D ◽  
Signaling Pathways ◽  
Cancer Progression ◽  
Prostate Cancer Progression

Are prostate cancer patients with BRCA1 and BRCA2 mutations safe for active surveillance?

2019 ◽  
Vol 37 (7_suppl) ◽  
pp. 19-19
Author(s):  
Marc Dall'era ◽  
Christopher P. Evans ◽  
Chong-Xian Pan ◽  
Mamta Parikh ◽  
Primo Lara ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Active Surveillance ◽  
Genetic Alterations ◽  
The Cancer Genome Atlas ◽  
Secondary Outcome ◽  
Sequencing Data ◽  
Brca1 And Brca2 ◽  
Data Set ◽  
Entire Cohort ◽  
Cancer Pathogenesis

19 Background: Active surveillance (AS) is recommended as a treatment option for men presenting with low risk (Gleason 3+3) and some intermediate risk (Gleason 3+4) prostate cancer. BRCA1 or 2 germline mutations have been implicated in prostate cancer pathogenesis. It is unknown if germline BRCA1/2 mutations in AS candidacy are associated with more aggressive histologic grade, higher stage or other worse genetic alterations, such as RB1 and p53 deletions. Methods: We analyzed sequencing data from 498 men who underwent radical prostatectomy from The Cancer Genome Atlas (TCGA) data set. The primary outcome was the difference in the proportions of AS candidates among subjects with and without BRCA homodeletions. Tests for differences in the proportions were conducted using Fisher’s Exact Test. Equivalence tests for proportions of AS candidates were conducted using the two-one sided tests (TOST) method. As a secondary outcome we studied the associated coincident mutations in the men with BRCA1 and BRCA2 homodeletions. Results: Forty-one men (8%) of the cohort had homodeletion of BRCA1 or BRCA2. Ten men (2%) had complete loss of BRCA1 while 31 (6%) had loss of BRCA2. Rates of candidacy for AS based on histology and stage (defined as stage T2, Gleason 6) are not different between subjects with and without BRCA 1 or 2 homodeletions, within an equivalence margin of 10 percentage points. These findings are similar when the AS criteria are modified to add Gleason 3+4 subjects. Fifty percent of men with organ confined (pT2), 3+3 and 3+4 prostate cancer with BRCA1 or BRCA2 homodeletions had concomitant RB1 deletions compared with 16.5% of the entire cohort (p = 0.002). This was primarily driven by BRCA2 deletions co-occurrent with RB1 deletions (log OR: 2.4, p < 0.001). Twenty-nine percent of men from this group had concomitant p53 deletions compared to 7.5% of the entire cohort (p = 0.004). Conclusions: Men with prostate cancer and BRCA1 or BRCA2 homodeletions present with similar stage and grade tumors than men without these deletions. Despite having low or low intermediate grade histology, BRCA1 and BRCA2 deleted tumors are enriched with deletions in RB1 and TP53, both of which are associated with more aggressive phenotypes and treatment resistance.

scholarly journals Prediction of Biochemical Recurrence-Free Survival of Prostate Cancer Patients Leveraging Multiple Gene Expression Profiles in Tumor Microenvironment

2021 ◽  
Vol 11 ◽  
Author(s):  
Rui Zhou ◽  
Yuanfa Feng ◽  
Jianheng Ye ◽  
Zhaodong Han ◽  
Yuxiang Liang ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Tumor Microenvironment ◽  
Cancer Patients ◽  
Cancer Progression ◽  
Biochemical Recurrence ◽  
Expression Profiles ◽  
The Cancer Genome Atlas ◽  
Cell Contact ◽  
Recurrence Free Survival ◽  
Free Survival

Tumor-adjacent normal (TAN) tissues, which constitute tumor microenvironment and are different from healthy tissues, provide critical information at molecular levels that can be used to differentiate aggressive tumors from indolent tumors. In this study, we analyzed 52 TAN samples from the Cancer Genome Atlas (TCGA) prostate cancer patients and developed a 10-gene prognostic model that can accurately predict biochemical recurrence-free survival based on the profiles of these genes in TAN tissues. The predictive ability was validated using TAN samples from an independent cohort. These 10 prognostic genes in tumor microenvironment are different from the prognostic genes detected in tumor tissues, indicating distinct progression-related mechanisms in two tissue types. Bioinformatics analysis showed that the prognostic genes in tumor microenvironment were significantly enriched by p53 signaling pathway, which may represent the crosstalk tunnels between tumor and its microenvironment and pathways involving cell-to-cell contact and paracrine/endocrine signaling. The insight acquired by this study has advanced our knowledge of the potential role of tumor microenvironment in prostate cancer progression.

scholarly journals Identification of a novel Protein Disulfide-isomerase A3 (PDIA3) transcript variant as a potential biomarker associated with late stage prostate cancer

2019 ◽  
Author(s):  
Maria Araceli Diaz Cruz ◽  
Pontus Karlsson ◽  
Gustav Högberg ◽  
Sandra Karlsson ◽  
Ferenc Szekeres ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Vitamin D ◽  
Cancer Progression ◽  
Vitamin D Receptor ◽  
Digital Pcr ◽  
Droplet Digital Pcr ◽  
Receptor Protein ◽  
Lncap Cells ◽  
Transcript Isoforms ◽  
Potential Biomarker

Abstract Background Prostate cancer (PC) is a heterogeneous and unpredictable disease and becomes untreatable when the tumor progress to castrate-resistant (CR) or androgen independent (AI). A major clinical challenge in prostate cancer is the lack of diagnostic and prognostic tests that distinguish between benign and aggressive tumors. Isoforms of gene transcripts are emerging as suitable candidates to represent disease progression. Vitamin D receptor (VDR and PDIA3) transcript isoforms could be the target candidates of study since they have been related with anti-tumoral effects and carcinogenesis in several cancer types. Methods The current study investigates the role of vitamin D receptor transcript isoforms in prostate cancer progression by using Next Generation Sequencing (NGS), Droplet Digital PCR (ddPCR) and several functional prediction tools. Results The NGS analysis revealed a novel PDIA3 transcript isoform (PDIA3N) that is higher expressed than the PDIA3 isoform that codifies for the receptor protein, in prostate cells. The expression of PDIA3N was validated by droplet digital PCR (ddPCR) absolute quantification, which confirmed the findings from the NGS analyses. The PDIA3N isoform was present in higher levels than PDIA3, in the metastatic androgen dependent LNCaP cells. Furthermore, analysis of the novel PDIA3 isoform sequence indicate that the variations present in its sequence are altering the original protein function and structure as well as the predicted subcellular localization of the protein. Conclusions We conclude that, PDIA3N due to the high expression in LNCaP cells and its abnormality in predicted structure, localization and function, is a potential biomarker for prostate cancer disease that needs to be further investigated in prostate cancer samples.

scholarly journals A hierarchical clustering and data fusion approach for disease subtype discovery

2020 ◽  
Author(s):  
Bastian Pfeifer ◽  
Michael G. Schimek
Keyword(s):  
Data Fusion ◽  
Cancer Patients ◽  
Hierarchical Clustering ◽  
Cancer Progression ◽  
The Cancer Genome Atlas ◽  
Superior Performance ◽  
Clustering Methods ◽  
Cancer Data ◽  
Disease Subtype ◽  
Fusion Approach

AbstractRecent advances in multi-omics clustering methods enable a more fine-tuned separation of cancer patients into clinical relevant clusters. These advancements have the potential to provide a deeper understanding of cancer progression and may facilitate the treatment of cancer patients. Here, we present a simple hierarchical clustering and data fusion approach, named HC-fused, for the detection of disease subtypes. Unlike other methods, the proposed approach naturally reports on the individual contribution of each single-omic to the data fusion process. We perform multi-view simulations with disjoint and disjunct cluster elements across the views to highlight fundamentally different data integration behaviour of various state-of-the-art methods. HC-fused combines the strengths of some recently published methods and shows superior performance on real world cancer data from the TCGA (The Cancer Genome Atlas) database. An R implementation of our method is available on GitHub (pievos101/HC-fused).

scholarly journals Random forest-based modelling to detect biomarkers for prostate cancer progression

2019 ◽  
Author(s):  
Reka Toth ◽  
Heiko Schiffmann ◽  
Claudia Hube-Magg ◽  
Franziska Büscheck ◽  
Doris Höflmayer ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Dna Methylation ◽  
Random Forest ◽  
Candidate Genes ◽  
Cancer Progression ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Classification Model ◽  
Gleason Grade ◽  
Tissue Micro Array

AbstractThe clinical course of prostate cancer (PCa) is highly variable, demanding an individualized approach to therapy and robust prognostic markers for treatment decisions. We present a random forest-based classification model to predict aggressive behaviour of PCa. DNA methylation changes between PCa cases with good or poor prognosis (discovery cohort with n=70) were used as input. The model was validated with data from two large independent PCa cohorts from the “International Cancer Genome Consortium” (ICGC) and “The Cancer Genome Atlas” (TCGA). Ranking of cancer progression-related DNA methylation changes allowed selection of candidate genes for additional validation by immunohistochemistry. We identified loss of ZIC2 protein expression, mediated by alterations in DNA methylation, as a promising novel prognostic biomarker for PCa in >12,000 tissue micro-array tumors. The prognostic value of ZIC2 proved to be independent from established clinico-pathological variables including Gleason grade, tumor stage, nodal stage and PSA. In summary, we have developed a PCa classification model, which either directly orviaexpression analyses of the identified top ranked candidate genes might help in decision making related to the treatment of prostate cancer patients.

scholarly journals Identification of prostate cancer specific methylation biomarkers from a multi-cancer analysis

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yiyi Pu ◽  
Chao Li ◽  
Haining Yuan ◽  
Xiaoju Wang
Keyword(s):  
Prostate Cancer ◽  
Dna Methylation ◽  
In Silico ◽  
Prostate Cancer Screening ◽  
Methylation Status ◽  
The Cancer Genome Atlas ◽  
Translation Rate ◽  
Normal Prostate ◽  
Cancer Data ◽  
Significant Difference

Abstract Background Detecting prostate cancer at a non-aggressive stage is the main goal of prostate cancer screening. DNA methylation has been widely used as biomarkers for cancer diagnosis and prognosis, however, with low clinical translation rate. By taking advantage of multi-cancer data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), we aimed to identify prostate cancer specific biomarkers which can separate between non-aggressive and aggressive prostate cancer based on DNA methylation patterns. Results We performed a comparison analysis of DNA methylation status between normal prostate tissues and prostate adenocarcinoma (PRAD) samples at different Gleason stages. The candidate biomarkers were selected by excluding the biomarkers existing in multiple cancers (pan-cancer) and requiring significant difference between PRAD and other urinary samples. By least absolute shrinkage and selection operator (LASSO) selection, 8 biomarkers (cg04633600, cg05219445, cg05796128, cg10834205, cg16736826, cg23523811, cg23881697, cg24755931) were identified and in-silico validated by model constructions. First, all 8 biomarkers could separate PRAD at different stages (Gleason 6 vs. Gleason 3 + 4: AUC = 0.63; Gleason 6 vs. Gleason 4 + 3 and 8–10: AUC = 0.87). Second, 5 biomarkers (cg04633600, cg05796128, cg23523811, cg23881697, cg24755931) effectively detected PRAD from normal prostate tissues (AUC ranged from 0.88 to 0.92). Last, 6 biomarkers (cg04633600, cg05219445, cg05796128, cg23523811, cg23881697, cg24755931) completely distinguished PRAD with other urinary samples (AUC = 1). Conclusions Our study identified and in-silico validated a panel of prostate cancer specific DNA methylation biomarkers with diagnosis value.

scholarly journals LBX2-AS1 Activates FSTL3 by Binding to Transcription Factor RARα to Foster Proliferation, Migration, and Invasion of Thyroid Cancer

2021 ◽  
Vol 12 ◽  
Author(s):  
Jia Li ◽  
Jie Shen ◽  
Lan Qin ◽  
Dongyan Lu ◽  
Enci Ding
Keyword(s):  
Thyroid Cancer ◽  
Cancer Progression ◽  
Cell Function ◽  
Differential Expression Analysis ◽  
Endocrine Tumor ◽  
The Cancer Genome Atlas ◽  
Migration And Invasion ◽  
Cancer Tissue ◽  
Data Set ◽  
Rna Immunoprecipitation

Background: Thyroid cancer is a frequent endocrine tumor in women. It is of great significance to investigate the molecular mechanism of progression of thyroid cancer.Methods: Gene expression data set and clinical data were downloaded from The Cancer Genome Atlas database for differential expression analysis. The triplet of downstream transcription factors (TFs) and modulatory genes of target lncRNA in thyroid cancer was predicted by the lncMAP database. mRNA and protein expression of lncRNA LBX2-AS1, RARα, and FSTL3 were detected by qRT-PCR and western blot. The localization of lncRNA LBX2-AS1 in cells was tested by Fluorescence in situ hybridization assay. The RNA immunoprecipitation assay was applied to verify the binding relationship between lncRNA LBX2-AS1 and FSTL3. ChIP and dual-luciferase assays were used to prove the binding relationship between RARα and FSTL3. Cell function experiments were used to test cell proliferation, migration and invasion in each treatment group. The role of lncRNA LBX2-AS1 in thyroid cancer progression was also confirmed in nude mice.Results: Bioinformatics analysis indicated that lncRNA LBX2-AS1, RARα, FSTL3 were remarkably fostered in thyroid cancer tissue, and LBX2-AS1 was evidently correlated with clinical features. The LncMAP triplet prediction showed that LBX2-AS1 recruited TF RARα to modulate FSTL3. RIP assay confirmed that LBX2-AS1 was prominently enriched on RARα. ChIP and dual-luciferase report assays unveiled that RARα bound to the promoter region of FSTL3 and functioned as a TF. Cell function experiments uncovered that LBX2-AS1 boosted the progression of thyroid cancer. The rescue experiments showed that LBX2-AS1 recruited the TF RARα to hasten the transcription activity of FSTL3 and thus promoted the development of thyroid cancer.Conclusion: The integrative results demonstrated that LBX2-AS1 activated FSTL3 by binding to TF RARα to hasten proliferation, migration and invasion of thyroid cancer.

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