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.

Presence of myeloid-derived suppressor cells (MDSC) in patients with metastatic castration-sensitive and castration-resistant prostate cancer.

2015 ◽  
Vol 33 (7_suppl) ◽  
pp. 222-222 ◽  
Author(s):  
Karen A. Autio ◽  
Phillip Wong ◽  
Angel Rabinowitz ◽  
Jianda Yuan ◽  
Lauryn Michelle Slavin ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Cancer Progression ◽  
Whole Blood ◽  
Geometric Mean ◽  
Suppressor Cells ◽  
Current Treatment ◽  
Clinical State ◽  
Cancer Center ◽  
Castration Resistant Prostate Cancer ◽  
Castration Resistant

222 Background: MDSC contribute to an immune suppressive environment and have been implicated in cancer progression. Measurement (identification and enumeration) is challenged by the lack of analytically valid assays limiting data interpretation between groups. This impacts our understanding of rationale immune targets and design of clinical trials. We employed a novel biomarker based assay in whole blood to enumerate MDSC from patients with metastatic castration sensitive (CSPC) and castration resistant prostate cancer (CRPC). Methods: Whole blood was collected in Cyto-Chex (Streck) tubes. A published computational algorithm-based approach (developed by Memorial Sloan Kettering Cancer Center and commercialized by Serametrix) was employed to determine the %MDSC-monocytic and coefficient of variance (CV=ratio of SD and geometric mean fluorescence intensity) to assess HLA-DR spread on CD14+CD11b cells. Samples were performed in duplicate. Clinical variables including clinical state, past and current treatment, metastatic sites, PSA, and standard prognostic markers were collected. Results: 36 pts with metastatic prostate cancer (29 CRPC; 7 CSPC) were included. Median (SD) %MDSC in 29 CRPC pts was 21.15 (5.33) and median (SD) CV was1.29 (0.25); 7 CSPC demonstrated a median (SD) %MDSC 19.15 (4.86) and median (SD) CV 1.22 (0.25). MDSC did not differ between chemotherapy exposed (n=13) and chemotherapy naive (n=16) CRPC (23.3 vs 19.5, p=ns). MDSC were not significantly higher in those with visceral mets, though a trend existed (20.3 vs 24.0, p=0.076). PSA did not appear to correlate with MDSC or CV. Conclusions: Understanding the distribution and characterization of MDSC in various clinical states in prostate cancer is relevant to the development of immune targets in this disease. MDSC were quantifiable in both CSPC and CRPC. There was a trend for higher MDSC values in patients with visceral metastases, which historically are associated with worse prognoses. Presence of MDSC in metastatic CSPC and CRPC has important therapeutic and trial implications. Further discovery in larger cohorts and earlier disease states is underway.

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 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.

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 Let-7i-5p enhances cell proliferation, migration and invasion of ccRCC by targeting HABP4

BMC Urology ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yujie Liu ◽  
Xing Hu ◽  
Liang Hu ◽  
Changjing Xu ◽  
Xuemei Liang
Keyword(s):  
Cell Proliferation ◽  
Target Genes ◽  
The Cancer Genome Atlas ◽  
Tumor Promoter ◽  
Luciferase Reporter ◽  
Migration And Invasion ◽  
Poor Overall Survival ◽  
Cell Renal Cell Carcinoma ◽  
Bioinformatics Analyses ◽  
Gene Assay

Abstract Background Clear cell renal cell carcinoma (ccRCC) is one of the best-characterized and most pervasive renal cancers. The present study aimed to explore the effects and potential mechanisms of let-7i-5p in ccRCC cells. Methods Using bioinformatics analyses, we investigated the expression of let-7i-5p in The Cancer Genome Atlas (TCGA) database and predicted biological functions and possible target genes of let-7i-5p in ccRCC cells. Cell proliferation assay, wound healing assay and transwell invasion assay were conducted to characterize the effects of let-7i-5p in ccRCC cells. To verify the interactions between let-7i-5p and HABP4, dual-luciferase reporter assay, quantitative real-time polymerase chain reaction, and western blotting were conducted. Rescue experiments were used to investigate the relationship between let-7i-5p and HABP4. Results TCGA data analysis revealed that ccRCC tissues had significantly increased let-7i-5p expression, which was robustly associated with poor overall survival. Further verification showed that ccRCC cell proliferation, migration and invasion were inhibited by let-7i-5p inhibitor but enhanced by let-7i-5p mimics. Subsequently, HABP4 was predicted to be the target gene of let-7i-5p. TCGA data showed that ccRCC tissues had decreased expression of HABP4 and that HABP4 expression was negatively correlated with let-7i-5p. Further verification showed that downregulation of HABP4 expression promoted cell proliferation, migration and invasion. The dual-luciferase reporter gene assay suggested that the let-7i-5p/HABP4 axis was responsible for the development of ccRCC. Conclusion Our results provide evidence that let-7i-5p functions as a tumor promoter in ccRCC and facilitates cell proliferation, migration and invasion by targeting HABP4. These results clarify the pathogenesis of ccRCC and offer a potential target for its treatment.

scholarly journals Identification of ARHGEF38, NETO2, GOLM1, and SAPCD2 Associated With Prostate Cancer Progression by Bioinformatic Analysis and Experimental Validation

2021 ◽  
Vol 9 ◽  
Author(s):  
Zhuolun Sun ◽  
Yunhua Mao ◽  
Xu Zhang ◽  
Shuo Lu ◽  
Hua Wang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Prostate Cancer ◽  
Cancer Progression ◽  
Cox Regression ◽  
Prognostic Indicator ◽  
Bioinformatic Analysis ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Prognostic Signature ◽  
Tcga Dataset

Prostate cancer (PCa) represents one of the most prevalent types of cancers and is a large health burden for men. The pathogenic mechanisms of PCa still need further investigation. The aim of this study was to construct an effective signature to predict the prognosis of PCa patients and identify the biofunctions of signature-related genes. First, we screened differentially expressed genes (DEGs) between PCa and normal control tissues in The Cancer Genome Atlas (TCGA) and GSE46602 datasets, and we performed weighted gene co-expression network analysis (WGCNA) to determine gene modules correlated with tumors. In total, 124 differentially co-expressed genes were retained. Additionally, five genes (ARHGEF38, NETO2, PRSS21, GOLM1, and SAPCD2) were identified to develop the prognostic signature based on TCGA dataset. The five-gene risk score was verified as an independent prognostic indicator through multivariate Cox regression analyses. The expression of the five genes involved in the signature was detected in the Gene Expression Omnibus (GEO), Gene Expression Profiling Interactive Analysis (GEPIA), and Oncomine databases. In addition, we utilized DiseaseMeth 2.0 and MEXPRESS for further analysis and found that abnormal methylation patterns may be a potential mechanism for these five DEGs in PCa. Finally, we observed that these genes, except PRSS21, were highly expressed in tumor samples and PCa cells. Functional experiments revealed that silencing ARHGEF38, NETO2, GOLM1, and SAPCD2 suppressed the proliferation, migration, and invasiveness of PCa cells. In summary, this prognostic signature had significant clinical significance for treatment planning and prognostic evaluation of patients with PCa. Thus, ARHGEF38, NETO2, GOLM1, and SAPCD2 may serve as oncogenes in PCa.

scholarly journals Prognostic values of GMPS, PR, CD40, and p21 in ovarian cancer

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6301 ◽  
Author(s):  
Ping Wang ◽  
Zengli Zhang ◽  
Yujie Ma ◽  
Jun Lu ◽  
Hu Zhao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Ovarian Cancer ◽  
Cancer Patients ◽  
Differential Expression ◽  
Cancer Progression ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Progression Model ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Early detection and prediction of prognosis and treatment responses are all the keys in improving survival of ovarian cancer patients. This study profiled an ovarian cancer progression model to identify prognostic biomarkers for ovarian cancer patients. Mouse ovarian surface epithelial cells (MOSECs) can undergo spontaneous malignant transformation in vitro cell culture. These were used as a model of ovarian cancer progression for alterations in gene expression and signaling detected using the Illumina HiSeq2000 Next-Generation Sequencing platform and bioinformatical analyses. The differential expression of four selected genes was identified using the gene expression profiling interaction analysis (http://gepia.cancer-pku.cn/) and then associated with survival in ovarian cancer patients using the Cancer Genome Atlas dataset and the online Kaplan–Meier Plotter (http://www.kmplot.com) data. The data showed 263 aberrantly expressed genes, including 182 up-regulated and 81 down-regulated genes between the early and late stages of tumor progression in MOSECs. The bioinformatic data revealed four genes (i.e., guanosine 5′-monophosphate synthase (GMPS), progesterone receptor (PR), CD40, and p21 (cyclin-dependent kinase inhibitor 1A)) to play an important role in ovarian cancer progression. Furthermore, the Cancer Genome Atlas dataset validated the differential expression of these four genes, which were associated with prognosis in ovarian cancer patients. In conclusion, this study profiled differentially expressed genes using the ovarian cancer progression model and identified four (i.e., GMPS, PR, CD40, and p21) as prognostic markers for ovarian cancer patients. Future studies of prospective patients could further verify the clinical usefulness of this four-gene signature.

scholarly journals miR-221-3p Regulates VEGFR2 Expression in High-Risk Prostate Cancer and Represents an Escape Mechanism from Sunitinib In Vitro

2020 ◽  
Vol 9 (3) ◽  
pp. 670 ◽  
Author(s):  
Markus Krebs ◽  
Antonio Giovanni Solimando ◽  
Charis Kalogirou ◽  
André Marquardt ◽  
Torsten Frank ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
High Risk ◽  
Kinase Inhibitors ◽  
The Cancer Genome Atlas ◽  
Luciferase Reporter ◽  
Cell Renal Cell Carcinoma ◽  
Cancer Specific Survival ◽  
Escape Mechanism ◽  
Pc3 Cells

Downregulation of miR-221-3p expression in prostate cancer (PCa) predicted overall and cancer-specific survival of high-risk PCa patients. Apart from PCa, miR-221-3p expression levels predicted a response to tyrosine kinase inhibitors (TKI) in clear cell renal cell carcinoma (ccRCC) patients. Since this role of miR-221-3p was explained with a specific targeting of VEGFR2, we examined whether miR-221-3p regulated VEGFR2 in PCa. First, we confirmed VEGFR2/KDR as a target gene of miR-221-3p in PCa cells by applying Luciferase reporter assays and Western blotting experiments. Although VEGFR2 was mainly downregulated in the PCa cohort of the TCGA (The Cancer Genome Atlas) database, VEGFR2 was upregulated in our high-risk PCa cohort (n = 142) and predicted clinical progression. In vitro miR-221-3p acted as an escape mechanism from TKI in PC3 cells, as displayed by proliferation and apoptosis assays. Moreover, we confirmed that Sunitinib induced an interferon-related gene signature in PC3 cells by analyzing external microarray data and by demonstrating a significant upregulation of miR-221-3p/miR-222-3p after Sunitinib exposure. Our findings bear a clinical perspective for high-risk PCa patients with low miR-221-3p levels since this could predict a favorable TKI response. Apart from this therapeutic niche, we identified a partially oncogenic function of miR-221-3p as an escape mechanism from VEGFR2 inhibition.

scholarly journals Steroid Receptor Signallings as Targets for Resveratrol Actions in Breast and Prostate Cancer

2019 ◽  
Vol 20 (5) ◽  
pp. 1087 ◽  
Author(s):  
Francesca De Amicis ◽  
Adele Chimento ◽  
Francesca Montalto ◽  
Ivan Casaburi ◽  
Rosa Sirianni ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Cancer Progression ◽  
Molecular Mechanisms ◽  
Steroid Receptors ◽  
Endocrine Resistance ◽  
Bioactive Compound ◽  
Therapy Resistance ◽  
Specific Gene ◽  
Resistant Disease ◽  
Combination Strategies

Extensive research over the past 25 years in hormone-dependent cancers, such as breast cancer and prostate cancer, has identified the molecular mechanisms driven by steroid receptors, elucidating the interplay between genomic and non-genomic steroid receptors mechanism of action. Altogether, these mechanisms create the specific gene expression programs that contribute to endocrine therapy resistance and cancer progression. These findings, on the bidirectional molecular crosstalk between steroid and growth factor receptors pathways in endocrine resistance, suggest the use of multi-target inhibitors together with endocrine therapies, for treating resistant disease. In this review we will discuss the novel understanding on the chemopreventive and anti-cancer activities of Resveratrol (3,5,4′-trihydroxy-stilbene) (RSV), a phytoalexin found in grapes acting on a plethora of targets. We will highlight Resveratrol effect on steroid receptors signalling and its potential use in the treatment of hormone-dependent cancer. Understanding the molecular mechanisms by which the bioactive compound influences cancer cell behaviour, by interfering with steroid receptors functional activity, will help to advance the design of combination strategies to increase the rate of complete and durable clinical response in patients.

scholarly journals Prognostic Gene Signature Identification Using Causal Structure Learning: Applications in Kidney Cancer

2015 ◽  
Vol 14s1 ◽  
pp. CIN.S14873
Author(s):  
Min Jin Ha ◽  
Veerabhadran Baladandayuthapani ◽  
Kim-Anh Do
Keyword(s):  
Cancer Progression ◽  
Gene Selection ◽  
Structure Learning ◽  
Causal Structure ◽  
Gene Signature ◽  
Directed Acyclic Graphs ◽  
The Cancer Genome Atlas ◽  
Survival Times ◽  
Cell Renal Cell Carcinoma ◽  
Prognostic Gene

Identification of molecular-based signatures is one of the critical steps toward finding therapeutic targets in cancer. In this paper, we propose methods to discover prognostic gene signatures under a causal structure learning framework across the whole genome. The causal structures are represented by directed acyclic graphs (DAGs), wherein we construct gene-specific network modules that constitute a gene and its corresponding regulators. The modules are then subsequently used to correlate with survival times, thus, allowing for a network-oriented approach to gene selection to adjust for potential confounders, as opposed to univariate (gene-by-gene) approaches. Our methods are motivated by and applied to a clear cell renal cell carcinoma (ccRCC) study from The Cancer Genome Atlas (TCGA) where we find several prognostic genes associated with cancer progression - some of which are novel while others confirm existing findings.

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