A Four-Gene Promoter Methylation Marker Panel Consisting of GREM1, NEURL, LAD1, and NEFH Predicts Survival of Clear Cell Renal Cell Cancer Patients

Tumor-Derived Sarcopenia Factors Are Diverse in Different Tumor Types: A Pan-Cancer Analysis

Cancer-associated muscle wasting is a widespread syndrome in people with cancer and is characterized by weight loss and muscle atrophy, leading to increased morbidity and mortality. However, the tumor-derived factors that affect the development of muscle wasting and the mechanism by which they act remain unknown. To address this knowledge gap, we aimed to delineate differences in tumor molecular characteristics (especially secretion characteristics) between patients with and without sarcopenia across 10 tumor types from The Cancer Genome Atlas (TCGA). We integrated radiological characteristics from CT scans of TCGA cancer patients, which allowed us to calculate skeletal muscle area (SMA) to confirm sarcopenia. We combined TCGA and GTEx (The Genotype-Tissue Expression) data to analyze upregulated secretory genes in 10 tumor types compared with normal tissues. Upregulated secretory genes in the tumor microenvironment and their relation to SMA were analyzed to identify potential muscle wasting biomarkers (560 samples). Meanwhile, their predictive values for patient survival was validated in 3530 samples in 10 tumor types. A total of 560 participants with transcriptomic data and SMA were included. Among those, 136 participants (24.28%) were defined as having sarcopenia based on SMA. Enrichment analysis for upregulated secretory genes in cancers revealed that pathways associated with muscle wasting were strongly enriched in tumor types with a higher prevalence of sarcopenia. A series of SMA-associated secretory protein-coding genes were identified in cancers, which showed distinct gene expression profiles according to tumor type, and could be used to predict prognosis in cancers (p value ≤ 0.002). Unfortunately, those genes were different and rarely overlapped across tumor types. Tumor secretome characteristics were closely related to sarcopenia. Highly expressed secretory mediators in the tumor microenvironment were associated with SMA and could affect the overall survival of cancer patients, which may provide a valuable starting point for the further understanding of the molecular basis of muscle wasting in cancers. More importantly, tumor-derived pro-sarcopenic factors differ across tumor types and genders, which implies that mechanisms of cancer-associated muscle wasting are complex and diverse across tumors, and may require individualized treatment approaches.

Histone demethylase KDM4B contributes to advanced clear cell renal carcinoma and association with copy number variations and cell cycle progression

Advanced renal cell carcinoma (RCC) poses a threat to patient survival. Epigenetic remodelling is the pathogenesis of renal cancer. Histone demethylase 4B (KDM4B) is overexpressed in many cancers through various pathways. However, the role of KDM4B in clear cell renal carcinoma has not yet been elucidated. The differential expression of KDM4B was first verified by analysing public databases. The expression of KDM4B in fresh tissues and pathology slides was further analysed by western blotting and immunohistochemical staining. KDM4B overexpression and knockdown cell lines were also established. Cell Counting Kit-8 (CCK-8) assay was used to detect cell growth. Transwell assays were performed to assess cell migration. Xenografts were used to evaluate tumour growth and metastasis in vivo. Finally, KDM4B expression levels associated with copy number variation (CNV) and cell cycle stage were evaluated based on single-cell RNA sequencing data. KDM4B was expressed at higher levels in tumour tissues than in the adjacent normal tissues. High levels of KDM4B are associated with worse pathological features and poorer prognosis. KDM4B also promotes cell proliferation and migration in vitro, as well as tumour growth and metastasis in vivo. Tumour cells with high KDM4B expression exhibited higher CNV levels and a greater proportion of cells in the G1/S transition phase. Our results confirm that KDM4B promotes the progression of clear cell renal carcinoma, is correlated with poor prognosis, and may be related to high levels of CNV and cell cycle progression.

Anchoring Filament Protein Ladinin-1 is an Immunosuppressive Microenvironment and Cold Tumor Correlated Prognosticator in Lung Adenocarcinoma

Anchoring filament protein ladinin-1 (LAD1) codes for an anchor filament protein in the basement membrane. Here, we have aimed to determine its potential role in LUAD. According to the comprehensive analyses conducted in this study, we studied the expression, prognostic significance, function, methylation, copy number variations, and the immune cell infiltration of LAD1 in LUAD. A higher level of LAD1 gene expression was observed in the LUAD tumor tissues compared to the normal lung tissues (p < 0.001). Furthermore, the multivariate analysis indicated that a higher LAD1 gene expression level was the independent prognostic factor. Additionally, the DNA methylation level of the LAD1 was inversely linked to its expression (p < 0.001). We noted that the patients affected due to LAD1 hypomethylation showed a very low overall survival rate compared to the patients with a higher LAD1 methylation score (p < 0.05). Moreover, the results of the immunity analysis indicated that the LAD1 expression might be inversely linked to the immune cell infiltration degree, expression of the infiltrated immune cells, and the PD-L1 levels. Lastly, we supplemented some verification to increase the rigor of the study. The results suggested that high expression of LAD1 may be related to cold tumors. Hence, this indirectly reflects that the immunotherapy effect of LUAD patients with high LAD1 expression might be worse. Based on the role played by the LAD1 in the tumor immune microenvironment, it can be considered a potential biomarker for predicting the immunotherapy response to LUAD.

Identification and validation of a DNA methylation-driven gene-based prognostic model for clear cell renal cell carcinoma

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is a malignant tumor with heterogeneous morphology and poor prognosis. This study aimed to establish a DNA methylation (DNAm)-driven gene-based prognostic model for ccRCC.

METHODS

Reduced representation bisulfite sequencing (RRBS) was performed on the DNA extracts from ccRCC patients. We analyzed the RRBS data from 10 pairs of patient samples to screen the candidate CpG sites, then trained and validated an 18-CpG site model, and integrated the clinical characters to establish a Nomogram model for the prognosis or risk evaluation of ccRCC.

RESULTS

We identified 2261 DMRs in the promoter region. After DMR selection, 578 candidates were screened, and was correspondence with 408 CpG dinucleotides in the 450 K array. We collected the DNAm profiles of 478 ccRCC samples from TCGA dataset. Using the training set with 319 samples, a prognostic panel of 18 CpGs was determined by univariate Cox regression, LASSO regression, and multivariate Cox proportional hazards regression analyses. We constructed a prognostic model by combining the clinical signatures. In the test set (159 samples) and whole set (478 samples), the Kaplan-Meier plot showed significant differences; and the ROC curve and survival analyses showed AUC greater than 0.7. The Nomogram integrated with clinicopathological characters and methylation risk score had better performance, and the decision curve analyses also showed a beneficial effect.

CONCLUSIONS

This work provides insight into the role of hypermethylation in ccRCC. The targets identified might serve as biomarkers for early ccRCC diagnosis and prognosis biomarkers for ccRCC. We believe our findings have implications for better risk stratification and personalized management of this disease.

The autocrine glycosylated-GREM1 interacts with TGFB1 to suppress TGFβ/BMP/SMAD-mediated EMT partially by inhibiting MYL9 transactivation in urinary carcinoma

PURPOSE

Urothelial carcinoma (UC) is a common disease in developed counties. This study aimed to identify autocrine roles and signaling pathways of gremlin 1, DAN family BMP antagonist (GREM1), which inhibits tumor growth and epithelial-mesenchymal transition (EMT) in UC.

METHODS

Systematic in vitro and in vivo studies using genetic engineering, different urinary bladder urothelial carcinoma (UBUC)-derived cell lines, and mouse models were performed, respectively. Further, primary upper tract urothelial carcinoma (UTUC) and UBUC specimens were evaluated by immunohistochemistry.

RESULTS

GREM1 protein levels conferred better disease-specific and metastasis-free survival rates and played an independent prognostic factor in UTUC and UBUC. Hypermethylation is the primary cause of low GREM1 levels. In different UBUC-derived cell lines, the autocrine/secreted and glycosylated GREM1 interacted with transforming growth factor beta 1 (TGFB1) and inhibited TGFβ/BMP/SMAD signaling and myosin light chain 9 (MYL9) transactivation, subsequently cell proliferation and epithelial-mesenchymal transition (EMT). Secreted and glycosylated GREM1 also suppressed tumor growth, metastasis, and MYL9 levels in the mouse model. Instead, cytosolic GREM1 promoted cell proliferation and EMT by activating the tumor necrosis factor (TNF)/AKT/nuclear factor kappa B (NFκB) axis.

CONCLUSIONS

Clinical associations, animal models, and in vitro indications provided solid evidence to show that the epithelial autocrine GREM1 is a novel tumor suppressor in UCs. The glycosylated-GREM1 hampered cell proliferation, migration, invasion, and in vitro angiogenesis through interaction with TGFB1 to inactivate TGFβ/BMP/SMAD-mediated EMT in an autocrine manner.

DNA methylation-mediated low expression of ZNF582 promotes the proliferation, migration, and invasion of clear cell renal cell carcinoma

OBJECTIVE

The methylation of DNA promoter region mediates the low expression of many tumor suppressor genes and plays an essential part in cancer progression. We investigated methylation and expression of ZNF582 in clear cell renal cell carcinoma (ccRCC), and to study the function of ZNF582 in ccRCC cells.

METHODS

Methylation data and mRNA expression data of TCGA-KIRC were obtained from TCGA database to screen methylation-driven genes. Survival analysis and gene set enrichment analysis (GSEA) were done for the target gene. The methylation degree and mRNA level of ZNF582 in ccRCC cell line were detected by methylation-specific PCR (MSP) and qRT-PCR, respectively. Effects of overexpression of ZNF582 on ccRCC cells were assessed via CCK-8, flow cytometry, wound healing, Transwell, and cell adhesion assays.

RESULTS

Eighteen methylation-driven genes were identified via bioinformatics methods. Among them, ZNF582 was noticeably hypermethylated and lowly expressed in tumor tissue, and ZNF582 methylation and expression levels were pronouncedly associated with prognosis and clinical stage. MSP also displayed that the ZNF582 DNA promoter region was hypermethylated in ccRCC cells, and the mRNA expression of ZNF582 was dramatically elevated after demethylation. In vitro cell experiments disclosed that overexpression of ZNF582 markedly hindered cell proliferation, invasion, migration, and fostered cell apoptosis and adhesion of ccRCC.

CONCLUSION

ZNF582 was hypermethylated in ccRCC, which mediated its low level. Overexpression of ZNF582 inhibited tumor cell proliferation, migration and invasion. This study generates novel ideas for ccRCC diagnosis and treatment.

Identification of a Novel Renal Metastasis Associated CpG-Based DNA Methylation Signature (RMAMS)

Approximately 21% of patients with renal cell cancer (RCC) present with synchronous metastatic disease at the time of diagnosis, and metachronous metastatic disease occurs in 20–50% of cases within 5 years. Recent advances in adjuvant treatment of aggressive RCC following surgery suggest that biomarker-based prediction of risk for distant metastasis could improve patient selection. Biometrical analysis of TCGA-KIRC data identified candidate loci in the NK6 homeobox 2 gene (NKX6-2) that are hypermethylated in primary metastatic RCC. Analyses of NKX6-2 DNA methylation in three gene regions including a total of 16 CpG sites in 154 tumor-adjacent normal tissue, 189 RCC, and 194 metastatic tissue samples from 95 metastasized RCC patients revealed highly significant tumor-specific, primary metastatic-specific, and metastatic tissue-specific hypermethylation of NKX6-2. Combined CpG site methylation data for NKX6-2 and metastasis-associated genes (INA, NHLH2, and THBS4) demonstrated similarity between metastatic tissues and metastatic primary RCC tissues. The random forest method and evaluation of an unknown test cohort of tissues using receiver operator characteristic curve analysis revealed that metastatic tissues can be differentiated by a median area under the curve of 0.86 (p = 1.7 × 10−8–7.5 × 10−3) in 1000 random runs. Analysis of variable importance demonstrated an above median contribution for decision-making of at least one CpG site in each of the genes, suggesting superior informativity for sites annotated to NHLH2 and NKX6-2. Thus, DNA methylation of NKX6-2 is associated with the metastatic state of RCC tissues and contributes to a four-gene-based statistical predictor of tumoral and metastatic renal tissues.

Identification of epigenetic dysregulation gene markers and immune landscape in kidney renal clear cell carcinoma by comprehensive genomic analysis

Kidney cancer is one the most lethal cancers of the urinary system, but current treatments are limited and its prognosis is poor. This study focused on kidney renal clear cell carcinoma (KIRC) and analyzed the relationship between epigenetic alterations and KIRC prognosis, and explored the prognostic significance of these findings in KIRC patients. Based on multi-omics data, differentially expressed histone-modified genes were identified using the R package limma package. Gene enhancers were detected from data in the FANTOM5 database. Gene promoters were screened using the R package ChIPseeker, and the Bumphunter in the R package CHAMP was applied to screen differentially methylated regions (DMR). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and Gene Ontology (GO) functional enrichment analysis of genes was performed using the R package clusterProfiler. We identified 51 dysregulated epigenetic protein coding genes (epi-PCGs) from 872 epi-PCGs, and categorized three molecular subtypes (C1, C2, and C3) of KIRC samples with significantly different prognosis. Notably, among the three molecular subtypes, we found a markedly differential immune features in immune checkpoints, cytokines, immune signatures, and immune cell distribution. C2 subtype had significantly lower enrichment score of IFNγ, cytotoxic score (CYT), and angiogenesis. In addition, an 8-gene signature containing 8 epi-PCGs (ETV4, SH2B3, FATE1, GRK5, MALL, HRH2, SEMA3G, and SLC10A6) was developed for predicting KIRC prognosis. Prognosis of patients with a high 8-gene signature score was significantly worse than those with a low 8-gene signature score, which was also validated by the independent validation data. The 8-gene signature had a better performance compared with previous signatures of KIRC. Overall, this study highlighted the important role of epigenetic regulation in KIRC development, and explored prognostic epi-PCGs, which may provide a guidance for exploiting further pathological mechanisms of KIRC and for developing novel drug targets.

Methylation of PCDH17 and NEFH as prognostic biomarker for nonmetastatic RCC: A cohort study

DNA methylation makes up a main part of the molecular mechanism of cancer evolution and has shown promising results in the prognosis of renal cell cancer (RCC). In this study, we investigated the possible association of promoter methylation of PCDH17, NEFH, RASSF1A, and FHIT, genes with the prognosis of nonmetastatic RCC patients. Cancerous and normal adjacent tissues from surgical specimens of 41 patients with long follow-up were treated for DNA isolation and bisulfite conversion. The gene promoter methylation was determined with quantitative methylation-specific PCR (qMSP). Wilcoxon signed-rank test was used for paired methylation comparisons, while univariate linear regression and Mann-Whitney test were applied for associating methylation status with clinical and disease characteristics. Cox regression proportional hazards models and Kaplan-Meier plots were used for survival analyses in reference to methylation status. Paired comparisons showed tissue-specific hypermethylation for PCDH17 (P < .001), NEFH (P < .001), RASSF1A (P = .032), while a positive association of methylation in normal tissues with age was demonstrated for PCDH17 (P < .001), RASSF1A (P < .001), FHIT (P < .001). PCDH17 was more methylated in cases with clear cell RCC (P = .015) and high-grade tumor (P = .013), while NEFH methylation was higher in locally advanced cases (P = .032). PCDH17 hypermethylation in cancerous and normal tissues was linked to shorter disease-specific survival (DSS, P = .026, P = .004), disease-free survival (DFS, P = .004, P = .019) while NEFH hypermethylation in cancerous tissues was related to shorter DSS (P = .032). Increased methylation difference of NEFH was also associated with shorter DSS (P = .041) and DFS (P = .020), while the corresponding parameter for PCDH17 was associated with poor DFS (P = .014). Kaplan-Meier curves for hypermethylation in cancer tissues demonstrated different clinical courses for PCDH17 (P = .017), NEFH (P = .023) regarding DSS, and PCDH17 (P = .001) regarding DFS. Our study not only highlights the prognostic value of promoter methylation of PCDH17 and NEFH in cancer tissues but also is the first report of the prognostic value of methylation alterations in normal tissues. Our findings are the first report of the prognostic value of methylation alterations in normal tissues, which can contribute to improved assessment of recurrence risk.

DNA Methylation in INA, NHLH2, and THBS4 Is Associated with Metastatic Disease in Renal Cell Carcinoma

The detection of DNA methylation in primary tumor tissues could be relevant for early stratification of aggressive renal cell carcinomas (RCCs) as a basis for future personalized adjuvant therapy. Methylated TCGA KIRC based candidate CpG loci in INA, NHLH2, and THBS4 that are possibly associated with RCC metastasis were evaluated by pyrosequencing in 154 paired normal adjacent and primary tumor tissues, as well as in 202 metastatic tissues. Statistical analysis was carried out by bivariate logistic regression for group comparisons, log rank survival analysis, and unsupervised and supervised analysis for the classification of tumors. Increased methylation of INA, NHLH2, and THBS4 loci were significantly associated with distant metastasis in primary tumors (p < 0.05), tissue-specific hypermethylation in metastatic (p = 7.88 × 10^-8, 5.57 × 10^-10, 2.06 × 10^-7) and tumor tissues (p = 3.72 × 10^-24, 3.17 × 10^-13, 1.58 × 10^-19), and shortened progression free survival in patients (p = 0.03). Combined use of CpG site-specific methylation permits the discrimination of tissues with metastatic disease and reveals a significant contribution of CpG sites in all genes to the statistical classification model. Thus, metastasis in RCC is significantly associated with methylation alterations in INA, NHLH2, and THBS4 loci, providing independent information for the potential early detection of aggressive renal cancers as a rationale for stratifying patients to adjuvant therapies.

Clinical Significance of ADAMTS19, BMP7, SIM1, and SFRP1 Promoter Methylation in Renal Clear Cell Carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of kidney tumors, accounting for the majority of deaths from genitourinary cancers. The currently used nomograms for predicting patient outcomes are based on clinical-pathological characteristics only; however, a significant number of ccRCC survivors with similar radiological and histological features still demonstrate a different clinical course of the disease. This study aimed at the identification of novel DNA methylation biomarkers for the monitoring of patients with ccRCC.

Methods

Gene expression profiling by SurePrint G3 Human GE 8×60K Microarrays was performed in 4 ccRCC tissues and adjacent non-cancerous renal tissue (NRT) samples. Four down-regulated genes were selected for further DNA methylation status analysis in 123 ccRCC and 45 NRT samples using methylation-specific PCR (MSP).

Results

DNA methylation changes of ADAMTS19, BMP7, SIM1, and SFRP1 were cancer-specific with significantly (P<0.050) higher methylation frequency (37%, 20%, 18%, and 42%, respectively) in tumor tissues. The methylated status of at least one gene was significantly related to various clinical-pathological parameters, including tumor size, Fuhrman and WHO/ISUP grades, intravascular invasion, and necrosis. Moreover, the methylated status of multimarker panel ADAMTS19, BMP7 & SFRP1 was predictive for poorer overall survival (HR, 4.11; 95% CI, 1.22–13.86).

Conclusion

In conclusion, DNA methylation of the three-gene panel consisting of ADAMTS19, BMP7 & SFRP1 supposedly predicts the outcome of patients diagnosed with ccRCC and possibly might be used to enrich the current prognostic tools.

Clinical significance of novel DNA methylation biomarkers for renal clear cell carcinoma

OBJECTIVE

Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney tumor characterized by the highest mortality rate of the genitourinary cancers, and, therefore, new diagnostic and/or prognostic biomarkers are urgently needed.

METHODS

Based on genome-wide DNA methylation profiling in 11 pairs of ccRCC and non-cancerous renal tissues (NRT), the methylation at regulatory regions of ZNF677, FBN2, PCDH8, TFAP2B, TAC1, and FLRT2 was analyzed in 168 renal tissues and 307 urine samples using qualitative and quantitative methylation-specific PCR (MSP).

RESULTS

Significantly higher methylation frequencies for all genes were found in ccRCC tissues compared to NRT (33-60% vs. 0-11%). The best diagnostic performance demonstrated a panel of ZNF677, FBN2, PCDH8, TFAP2B & TAC1 with 82% sensitivity and 96% specificity. Hypermethylation of ZNF677 and PCDH8 in the tissue samples was significantly related to numerous adverse clinicopathologic parameters. For the urine-based ccRCC detection, the highest diagnostic power (AUC = 0.78) was observed for a panel of ZNF677 & PCDH8 (with or without FBN2 or FLRT2) with 69-78% sensitivity and 69-80% specificity, albeit with lower values in the validation cohort. Besides, methylation of PCDH8 was significantly related to higher tumor stage and fat invasion in the study and validation cohorts. Moreover, PCDH8 was strongly predictive for OS (HR, 5.7; 95% CI 1.16-28.12), and its prognostic power considerably increased in combination with ZNF677 (HR, 12.5; 95% CI 1.47-105.58).

CONCLUSION

In summary, our study revealed novel, potentially promising DNA methylation biomarkers of ccRCC with the possibility to be applied for non-invasive urine-based ccRCC detection and follow-up.

Promising Epigenetic Biomarkers Associated With Cancer-Associated-Fibroblasts for Progression of Kidney Renal Clear Cell Carcinoma

Kidney renal clear cell carcinoma (KIRC) is the most common malignant kidney tumor as its characterization of highly metastatic potential. Patients with KIRC are associated with poor clinical outcomes with limited treatment options. Up to date, the underlying molecular mechanisms of KIRC pathogenesis and progression are still poorly understood. Instead, particular features of Cancer-Associated Fibroblasts (CAFs) are highly associated with adverse outcomes of patients with KIRC, while the precise regulatory mechanisms at the epigenetic level of KIRC in governing CAFs remain poorly defined. Therefore, explore the correlations between epigenetic regulation and CAFs infiltration may help us better understand the molecular mechanisms behind KIRC progression, which may improve clinical outcomes and patients quality of life. In the present study, we identified a set of clinically relevant CAFs-related methylation-driven genes, NAT8, TINAG, and SLC17A1 in KIRC. Our comprehensive in silico analysis revealed that the expression levels of NAT8, TINAG, and SLC17A1 are highly associated with outcomes of patients with KIRC. Meanwhile, their methylation levels are highly correlates with the severity of KIRC. We suggest that the biomarkers might contribute to CAFs infiltration in KIRC. Taken together, our study provides a set of promising biomarkers which could predict the progression and prognosis of KIRC. Our findings could have potential prognosis and therapeutic significance in the progression of KIRC.

The protein inputs of an ultra-predictive aging clock represent viable anti-aging drug targets

Machine learning models capable of predicting age given a set of inputs are referred to as aging clocks. We recently developed an aging clock that utilizes 491 plasma protein inputs, has an exceptional accuracy, and is capable of measuring biological age. Here, we demonstrate that this clock is extremely predictive (r = 0.95) when used to measure age in a novel plasma proteomic dataset derived from 370 human subjects aged 18-69 years. Over-representation analyses of the proteins that make up this clock in the Gene Ontology and Reactome databases predominantly implicated innate and adaptive immune system processes. Immunological drugs and various age-related diseases were enriched in the DrugBank and GLAD4U databases. By performing an extensive literature review, we find that at least 269 (54.8 %) of these inputs regulate lifespan and/or induce changes relevant to age-related disease when manipulated in an animal model. We also show that, in a large plasma proteomic dataset, the majority (57.2 %) of measurable clock proteins significantly change their expression level with human age. Different subsets of proteins were overlapped with distinct epigenetic, transcriptomic, and proteomic aging clocks. These findings indicate that the inputs of this age predictor likely represent a rich source of anti-aging drug targets.

Development of a prognostic risk model for clear cell renal cell carcinoma by systematic evaluation of DNA methylation markers

BACKGROUND

Current risk models for renal cell carcinoma (RCC) based on clinicopathological factors are sub-optimal in accurately identifying high-risk patients. Here, we perform a head-to-head comparison of previously published DNA methylation markers and propose a potential prognostic model for clear cell RCC (ccRCC).

PATIENTS AND METHODS

Promoter methylation of PCDH8, BNC1, SCUBE3, GREM1, LAD1, NEFH, RASSF1A, GATA5, SFRP1, CDO1, and NEURL was determined by nested methylation-specific PCR. To identify clinically relevant methylated regions, The Cancer Genome Atlas (TCGA) was used to guide primer design. Formalin-fixed paraffin-embedded (FFPE) tissue samples from 336 non-metastatic ccRCC patients from the prospective Netherlands Cohort Study (NLCS) were used to develop a Cox proportional hazards model using stepwise backward elimination and bootstrapping to correct for optimism. For validation purposes, FFPE ccRCC tissue of 64 patients from the University Hospitals Leuven and a series of 232 cases from The Cancer Genome Atlas (TCGA) were used.

RESULTS

Methylation of GREM1, GATA5, LAD1, NEFH, NEURL, and SFRP1 was associated with poor ccRCC-specific survival, independent of age, sex, tumor size, TNM stage or tumor grade. Moreover, the association between GREM1, NEFH, and NEURL methylation and outcome was shown to be dependent on the genomic region. A prognostic biomarker model containing GREM1, GATA5, LAD1, NEFH and NEURL methylation in combination with clinicopathological characteristics, performed better compared to the model with clinicopathological characteristics only (clinical model), in both the NLCS and the validation population with a c-statistic of 0.71 versus 0.65 and a c-statistic of 0.95 versus 0.86 consecutively. However, the biomarker model had limited added prognostic value in the TCGA series with a c-statistic of 0.76 versus 0.75 for the clinical model.

CONCLUSION

In this study we performed a head-to-head comparison of potential prognostic methylation markers for ccRCC using a novel approach to guide primers design which utilizes the optimal location for measuring DNA methylation. Using this approach, we identified five methylation markers that potentially show prognostic value in addition to currently known clinicopathological factors.

Exploring effects of DNA methylation and gene expression on pan-cancer drug response by mathematical models

Since genetic alteration only accounts for 20%-30% in the drug effect-related factors, the role of epigenetic regulation mechanisms in drug response is gradually being valued. However, how epigenetic changes and abnormal gene expression affect the chemotherapy response remains unclear. Therefore, we constructed a variety of mathematical models based on the integrated DNA methylation, gene expression, and anticancer drug response data of cancer cell lines from pan-cancer levels to identify genes whose DNA methylation is associated with drug response and then to assess the impact of epigenetic regulation of gene expression on the sensitivity of anticancer drugs. The innovation of the mathematical models lies in: Linear regression model is followed by logistic regression model, which greatly shortens the calculation time and ensures the reliability of results by considering the covariates. Second, reconstruction of prediction models based on multiple dataset partition methods not only evaluates the model stability but also optimizes the drug-gene pairs. For 368,520 drug-gene pairs with P < 0.05 in linear models, 999 candidate pairs with both AUC ≥ 0.8 and P < 0.05 were obtained by logistic regression models between drug response and DNA methylation. Then 931 drug-gene pairs with 45 drugs and 491 genes were optimized by model stability assessment. Integrating both DNA methylation and gene expression markedly increased predictive power for 732 drug-gene pairs where 598 drug-gene pairs including 44 drugs and 359 genes were prioritized. Several drug target genes were enriched in the modules of the drug-gene-weighted interaction network. Besides, for cancer driver genes such as EGFR, MET, and TET2, synergistic effects of DNA methylation and gene expression can predict certain anticancer drugs' responses. In summary, we identified potential drug sensitivity-related markers from pan-cancer levels and concluded that synergistic regulation of DNA methylation and gene expression affect anticancer drug response.

The Role of Epigenetics in the Progression of Clear Cell Renal Cell Carcinoma and the Basis for Future Epigenetic Treatments

Simple Summary

The accumulated evidence on the role of epigenetic markers of prognosis in clear cell renal cell carcinoma (ccRCC) is reviewed, as well as state of the art on epigenetic treatments for this malignancy. Several epigenetic markers are likely candidates for clinical use, but still have not passed the test of prospective validation. Development of epigenetic therapies, either alone or in combination with tyrosine-kinase inhibitors of immune-checkpoint inhibitors, are still in their infancy.

Abstract

Clear cell renal cell carcinoma (ccRCC) is curable when diagnosed at an early stage, but when disease is non-confined it is the urologic cancer with worst prognosis. Antiangiogenic treatment and immune checkpoint inhibition therapy constitute a very promising combined therapy for advanced and metastatic disease. Many exploratory studies have identified epigenetic markers based on DNA methylation, histone modification, and ncRNA expression that epigenetically regulate gene expression in ccRCC. Additionally, epigenetic modifiers genes have been proposed as promising biomarkers for ccRCC. We review and discuss the current understanding of how epigenetic changes determine the main molecular pathways of ccRCC initiation and progression, and also its clinical implications. Despite the extensive research performed, candidate epigenetic biomarkers are not used in clinical practice for several reasons. However, the accumulated body of evidence of developing epigenetically-based biomarkers will likely allow the identification of ccRCC at a higher risk of progression. That will facilitate the establishment of firmer therapeutic decisions in a changing landscape and also monitor active surveillance in the aging population. What is more, a better knowledge of the activities of chromatin modifiers may serve to develop new therapeutic opportunities. Interesting clinical trials on epigenetic treatments for ccRCC associated with well established antiangiogenic treatments and immune checkpoint inhibitors are revisited.

DNA Methylation Haplotype Block Markers Efficiently Discriminate Follicular Thyroid Carcinoma from Follicular Adenoma

CONTEXT

Follicular thyroid carcinoma (FTC) is the second most common type of thyroid carcinoma and must be pathologically distinguished from benign follicular adenoma (FA). Additionally, the clinical assessment of thyroid tumors with uncertain malignant potential (TT-UMP) demands effective indicators.

OBJECTIVE

We aimed to identify discriminating DNA methylation markers between FA and FTC.

METHODS

DNA methylation patterns were investigated in 33 FTC and 33 FA samples using reduced representation bisulfite sequencing and methylation haplotype block-based analysis. A prediction model was constructed and validated in an independent cohort of 13 FTC and 13 FA samples. Moreover, 36 TT-UMP samples were assessed using this model.

RESULTS

A total of 70 DNA methylation markers, approximately half of which were located within promoters, were identified to be significantly different between the FTC and FA samples. All the Gene Ontology terms enriched among the marker-associated genes were related to "DNA binding," implying that the inactivation of DNA binding played a role in FTC development. A random forest model with an area under the curve of 0.994 was constructed using those markers for discriminating FTC from FA in the validation cohort. When the TT-UMP samples were scored using this model, those with fewer driver mutations also exhibited lower scores.

CONCLUSION

An FTC-predicting model was constructed using DNA methylation markers, which distinguished between FA and FTC tissues with a high degree of accuracy. This model can also be used to help determine the potential of malignancy in TT-UMP.

DNA Methylation-Based Panel Predicts Survival of Patients With Clear Cell Renal Cell Carcinoma and Its Correlations With Genomic Metrics and Tumor Immune Cell Infiltration

DNA methylation based prognostic factor for patients with clear cell renal cell carcinoma (ccRCC) remains unclear. In the present study, we identified survival-related DNA methylation sites based on the differentially methylated DNA CpG sites between normal renal tissue and ccRCC. Then, these survival-related DNA methylation sites were included into an elastic net regularized Cox proportional hazards regression (CoxPH) model to build a DNA methylation-based panel, which could stratify patients into different survival groups with excellent accuracies in the training set and test set. External validation suggested that the DNA methylation-based panel could effectively distinguish normal controls from tumor samples and classify patients into metastasis group and non-metastasis group. The nomogram containing DNA methylation-based panel was reliable in clinical settings. Higher total mutation number, SCNA level, and MATH score were associated with higher methylation risk. The innate immune, ratio between CD8⁺T cell versus Treg cell as well as Th17 cell versus Th2 cell were significantly decreased in high methylation risk group. In inclusion, we developed a DNA methylation-based panel which might be independent prognostic factor in ccRCC. Patients with higher methylation risk were associated genomic alteration and poor immune microenvironment.

Combining epigenetic and clinicopathological variables improves specificity in prognostic prediction in clear cell renal cell carcinoma

BACKGROUND

Metastasized clear cell renal cell carcinoma (ccRCC) is associated with a poor prognosis. Almost one-third of patients with non-metastatic tumors at diagnosis will later progress with metastatic disease. These patients need to be identified already at diagnosis, to undertake closer follow up and/or adjuvant treatment. Today, clinicopathological variables are used to risk classify patients, but molecular biomarkers are needed to improve risk classification to identify the high-risk patients which will benefit most from modern adjuvant therapies. Interestingly, DNA methylation profiling has emerged as a promising prognostic biomarker in ccRCC. This study aimed to derive a model for prediction of tumor progression after nephrectomy in non-metastatic ccRCC by combining DNA methylation profiling with clinicopathological variables.

METHODS

A novel cluster analysis approach (Directed Cluster Analysis) was used to identify molecular biomarkers from genome-wide methylation array data. These novel DNA methylation biomarkers, together with previously identified CpG-site biomarkers and clinicopathological variables, were used to derive predictive classifiers for tumor progression.

RESULTS

The "triple classifier" which included both novel and previously identified DNA methylation biomarkers together with clinicopathological variables predicted tumor progression more accurately than the currently used Mayo scoring system, by increasing the specificity from 50% in Mayo to 64% in our triple classifier at 85% fixed sensitivity. The cumulative incidence of progress (_pCIP_5yr) was 7.5% in low-risk vs 44.7% in high-risk in M0 patients classified by the triple classifier at diagnosis.

CONCLUSIONS

The triple classifier panel that combines clinicopathological variables with genome-wide methylation data has the potential to improve specificity in prognosis prediction for patients with non-metastatic ccRCC.

Identification and Comprehensive Validation of a DNA Methylation-Driven Gene-Based Prognostic Model for Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most prevalent renal malignancy in adults with generally poor prognosis. This study aimed to establish a DNA methylation-driven gene-based prognostic model for ccRCC. We collected DNA methylation and gene expression profiles of over 1500 ccRCC samples from The Cancer Genome Atlas (TCGA) dataset, four Gene Expression Omnibus (GEO) datasets, the Genotype-Tissue Expression (GTEx) dataset, and cancer cell lines from Cancer Cell Line Encyclopedia database and performed comprehensive bioinformatics analysis. As a result, a total of 31 differentially expressed methylation-driven genes (DEMDGs) were identified. After univariate Cox regression, least absolute shrinkage and selection operator, and multivariate Cox regression analyses, four (NFE2L3, HHLA2, IFI16, and ZNF582) were finally selected to construct a risk score prognostic model. The high-risk group demonstrated significantly poor prognosis than the low-risk group did in TCGA training (hazard ratio [HR] = 3.533, p < 0.001), TCGA internal, and GEO external validation datasets. Furthermore, the nomogram, including the prognostic model and clinical factors, showed promising prognostic value (HR = 5.756, p < 0.001, and area under the curve at 1 year = 0.856). In addition, the model was found to be significantly associated with drug sensitivity of eight targeted agents. These findings provided a novel and reliable four DEMDG-based prognostic model for ccRCC.

Identification of methylation-driven genes related to prognosis in clear-cell renal cell carcinoma

With the participation of the existing treatment methods, the prognosis of advanced clear‐cell renal cell carcinoma (ccRCC) is poor. More evidence indicates the presence of methylation in ccRCC cancer cells, but there is a lack of studies on methylation‐driven genes in ccRCC. We analyzed the open data of ccRCC in The Cancer Genome Atlas database to obtain ccRCC‐related methylation‐driven genes, and then carried out pathway enrichment, survival, and joint survival analyses. More important, we deeply explored the correlation between differential methylation sites and the expression of these driving genes. Finally, we screened 29 methylation‐driven genes via MethylMix, of which six were significantly associated with the survival of ccRCC patients. This study demonstrated that the effect of hypermethylation or hypomethylation on prognosis is different, and the level of methylation of key methylation sites is associated with gene expression. We identified methylation‐driven genes independently predicting prognosis in ccRCC, which offers theoretical support in bioinformatics for the study of methylation in ccRCC and a new perspective for the epigenetic study of ccRCC.

Downregulation of DACT-2 by Promoter Methylation and its Clinicopathological Significance in Prostate Cancer

Backgrounds: Dapper homolog (DACT) 2, a member of DACT gene family, is frequently down-regulated in various malignancies and linked to tumor progression. However, the regulatory mechanism of DACT-2 expression and its biological role in human prostate cancer (PCa) remains elusive. Here, we investigated the expression and an epigenetic change of DACT-2 in prostate cancer, and determined if these findings were correlated with clinicopathologic characteristics of PCa.

Methods: The expression profile of DACT-2 of was detected by qRT-PCR, Western blotting, and immunohistochemistry in four prostate cell lines (RWPE-1, LNCaP, PC-3 and DU145), 56 cases of frozen prostate tissues (forty-seven primary prostate carcinomas, nine paired noncancerous and cancerous prostate tissues) and a tissue microarray sets including 100 paraffin-embedded prostate samples (3 normal tissues, 2 cases of adjacent tissues and 95 cases of cancer). Subsequently, the regulatory mechanism of DACT-2 down-regulation was investigated through methylation-specific PCR (MSP) and bisulfite sequencing (BSP). The role of DACT-2 in prostate cancer cell migration and invasion was respectively examined by wound healing and transwell assay. After 5-aza-2'-deoxycytidine treatment of prostate cancer cells, qRT-PCR was used to detect whether the expression of DACT-2 gene mRNA in the cells recovered.

Results: Immunohistochemical results shown that the DACT-2 protein was strongly (3+) expressed in the cytoplasm of all 5 noncancerous tissues and 12.7% (12/95) prostate cancer (PCa) tissues. Whereas 68.4% (65/95) PCa samples and 18.9% (18/95) PCa tissues respectively displayed weakly (1+) expressed and moderately (2+) expressed. In addition, DACT-2 expression was negatively associated with Gleason score in tumor specimens (p=0.029). What's more, down-regulation and promoter methylation of DACT-2 were observed in 68.1% (32/47) frozen PCa tissues and all three prostate cancer cell lines. And, the expression of DACT-2 mRNA was restored by the treatment of demethylated drug 5-aza-2'-deoxycytidine in all prostate cancer lines. Prostate cancer cells invasion and migration were significantly suppressed by ectopic expression of DACT-2 in vitro.

Conclusions: Our study provides evidence that DACT-2 may be a useful biomarker for distinguishing prostate tumor tissues from non-cancerous samples and a potential target for epigenetic silencing in primary prostate Cancer.

Overexpression of mircoRNA-137 inhibits cervical cancer cell invasion, migration and epithelial-mesenchymal transition by suppressing the TGF-β/smad pathway via binding to GREM1

Background

Accumulating evidence has highlighted the tumor suppressive roles of microRNA (miRNAs) in cervical cancer (CC). In the present study, we aim to delineate the functional relevance of microRNA-137 (miR-137) in influencing epithelial-mesenchymal transition (EMT), and other CC cell biological activities via the TGF-β/smad pathway by binding to GREM1.

Methods

Microarray analysis was initially adopted to predict the differentially expressed genes and the miRNAs related to CC, followed by the measurement of the expression patterns of GREM1, EMT-related factors in the CC tissues and the adjacent tissues. Dual luciferase reporter gene assay was conducted to determine the relationship between miR-137 and GREM1. Gain-of- and loss-of-function experiments were conducted to characterize the effects of miR-137 and GREM1 on the colony formation, proliferation, apoptosis, migration, and invasion of CC cells in vitro, and the tumorigenicity of the CC cells in nude mice. The TGF-β/smad pathway was subsequently blocked with si-TGF-β to investigate its involvement.

Results

Reduced miR-137 expression and increased GREM1 expression were predicted in CC, which was subsequently observed in the CC tissues and cells. Notably, GREM1 was a target gene of miR-137. The overexpressed miR-137 was found to inhibit EMT, cell proliferation, colony formation, invasion, migration and tumorigenesis in nude mice. In addition, miR-137 was noted to inhibit the activation of the TGF-β/smad pathway by binding to GREM1. The silencing of TGF-β1 was shown to reverse the effects induced by downregulated expression of miR-137.

Conclusions

This study suggests that upregulated miR-137 suppresses the tumor progression in CC via blocking the TGF-β/smad pathway by binding to and negatively regulating GREM1.

Identification of a 4-mRNA metastasis-related prognostic signature for patients with breast cancer

Metastasis‐related mRNAs have showed great promise as prognostic biomarkers in various types of cancers. Therefore, we attempted to develop a metastasis‐associated gene signature to enhance prognostic prediction of breast cancer (BC) based on gene expression profiling. We firstly screened and identified 56 differentially expressed mRNAs by analysing BC tumour tissues with and without metastasis in the discovery cohort (GSE102484, n = 683). We then found 26 of these differentially expressed genes were associated with metastasis‐free survival (MFS) in the training set (GSE20685, n = 319). A metastasis‐associated gene signature built using a LASSO Cox regression model, which consisted of four mRNAs, can classify patients into high‐ and low‐risk groups in the training cohort. Patients with high‐risk scores in the training cohort had shorter MFS (hazard ratio [HR] 3.89, 95% CI 2.53‐5.98; P < 0.001), disease‐free survival (DFS) (HR 4.69, 2.93‐7.50; P < 0.001) and overall survival (HR 4.06, 2.56‐6.45; P < 0.001) than patients with low‐risk scores. The prognostic accuracy of mRNAs signature was validated in the two independent validation cohorts (GSE21653, n = 248; GSE31448, n = 246). We then developed a nomogram based on the mRNAs signature and clinical‐related risk factors (T stage and N stage) that predicted an individual's risk of disease, which can be assessed by calibration curves. Our study demonstrated that this 4‐mRNA signature might be a reliable and useful prognostic tool for DFS evaluation and will facilitate tailored therapy for BC patients at different risk of disease.

Exploratory analysis of the human breast DNA methylation profile upon soymilk exposure

Upon soy consumption, isoflavone metabolites attain bioactive concentrations in breast tissue possibly affecting health. Though in vitro epigenetic activity of soy metabolites has been described, the in vivo impact on the epigenome is largely unknown. Therefore, in this case-control study, the breast glandular tissue DNA methylome was explored in women undergoing an aesthetic breast reduction. After a run-in phase, 10 generally healthy Belgian or Dutch women received soymilk for 5 days. MethylCap-seq methylation profiles were compared with those of 10 matched controls. Isoflavones and their microbial metabolites were quantified in urine, serum, and glandular breast tissue (liquid chromatography-mass spectrometry) and 17β-estradiol in glandular breast tissue (immunoassay). Global DNA methylation levels were obtained for 6 cases and 5 controls using liquid chromatography-mass spectrometry. Although lower MethylCap-seq coverages were observed, mass spectrometry results and computational LINE-1 methylation analysis did not provide evidence supporting global methylation alterations upon treatment. At a false discovery rate of 0.05, no differentially methylated loci were identified. Moreover, a set of previously identified loci was specifically tested, but earlier reported results could not be validated. In conclusion, after a 5-day soymilk treatment, no major general epigenetic reprogramming in breast tissue could be found in this exploratory study.

The Role of DNA Methylation in Renal Cell Carcinoma

Renal cell carcinoma (RCC) is the most common kidney cancer and includes several molecular and histological subtypes with different clinical characteristics. While survival rates are high if RCC is diagnosed when still confined to the kidney and treated definitively, there are no specific diagnostic screening tests available and symptoms are rare in early stages of the disease. Management of advanced RCC has changed significantly with the advent of targeted therapies, yet survival is usually increased by months due to acquired resistance to these therapies. DNA methylation, the covalent addition of a methyl group to a cytosine, is essential for normal development and transcriptional regulation, but becomes altered commonly in cancer. These alterations result in broad transcriptional changes, including in tumor suppressor genes. Because DNA methylation is one of the earliest molecular changes in cancer and is both widespread and stable, its role in cancer biology, including RCC, has been extensively studied. In this review, we examine the role of DNA methylation in RCC disease etiology and progression, the preclinical use of DNA methylation alterations as diagnostic, prognostic and predictive biomarkers, and the potential for DNA methylation-directed therapies.

Clinical utility of the S3-score for molecular prediction of outcome in non-metastatic and metastatic clear cell renal cell carcinoma

BACKGROUND

Stratification of cancer patients to identify those with worse prognosis is increasingly important. Through in silico analyses, we recently developed a gene expression-based prognostic score (S3-score) for clear cell renal cell carcinoma (ccRCC), using the cell type-specific expression of 97 genes within the human nephron. Herein, we verified the score using whole-transcriptome data of independent cohorts and extend its application for patients with metastatic disease receiving tyrosine kinase inhibitor treatment. Finally, we sought to improve the signature for clinical application using qRT-PCR.

METHODS

A 97 gene-based S3-score (S3₉₇) was evaluated in a set of 52 primary non-metastatic and metastatic ccRCC patients as well as in 53 primary metastatic tumors of sunitinib-treated patients. Gene expression data of The Cancer Genome Atlas (n = 463) was used for platform transfer and development of a simplified qRT-PCR-based 15-gene S3-score (S3₁₅). This S3₁₅-score was validated in 108 metastatic and non-metastatic ccRCC patients and ccRCC-derived metastases including in part several regions from one metastasis. Univariate and multivariate Cox regression stratified by T, N, M, and G were performed with cancer-specific and progression-free survival as primary endpoints.

RESULTS

The S3₉₇-score was significantly associated with cancer-specific survival (CSS) in 52 ccRCC patients (HR 2.9, 95% Cl 1.0-8.0, P_Log-rank = 3.3 × 10^-2) as well as progression-free survival in sunitinib-treated patients (2.1, 1.1-4.2, P_Log-rank = 2.2 × 10^-2). The qRT-PCR based S3₁₅-score performed similarly to the S3₉₇-score, and was significantly associated with CSS in our extended cohort of 108 patients (5.0, 2.1-11.7, P_Log-rank = 5.1 × 10^-5) including metastatic (9.3, 1.8-50.0, P_Log-rank = 2.3 × 10^-3) and non-metastatic patients (4.4, 1.2-16.3, P_Log-rank = 1.6 × 10^-2), even in multivariate Cox regression, including clinicopathological parameters (7.3, 2.5-21.5, P_Wald = 3.3 × 10^-4). Matched primary tumors and metastases revealed similar S3₁₅-scores, thus allowing prediction of outcome from metastatic tissue. The molecular-based qRT-PCR S3₁₅-score significantly improved prediction of CSS by the established clinicopathological-based SSIGN score (P = 1.6 × 10^-3).

CONCLUSION

The S3-score offers a new clinical avenue for ccRCC risk stratification in the non-metastatic, metastatic, and sunitinib-treated setting.

MicroRNA-203 Inhibits Long Noncoding RNA HOTAIR and Regulates Tumorigenesis through Epithelial-to-mesenchymal Transition Pathway in Renal Cell Carcinoma

This study aims to investigate the role of miR-203-HOTAIR interaction in the suppression of renal cell carcinoma (RCC). We employed series of in vitro assays such as proliferation, invasion, migration, and colony formation along with in vivo tumor xenograft model. Profiling of miR-203 and HOTAIR expression revealed that miR-203 was significantly underexpressed, whereas HOTAIR was overexpressed in RCC cell lines and clinical specimens compared with normal cell line and tissue. Both miR-203 and HOTAIR expression significantly distinguished malignant from normal tissues and significantly correlated with clinicopathologic characteristics of patients. Overexpression of miR-203 significantly inhibited proliferation, migration, and invasion with an induction of apoptosis and cell-cycle arrest. However, HOTAIR suppression resulted in the similar functional effects in the same RCC cell lines. In silico, RNA-22 algorithm showed a binding site for miR-203 in HOTAIR. We observed a direct interaction between miR-203 and HOTAIR by RNA-immunoprecipitation (RIP) and luciferase reporter assays. We show that miR-203-HOTAIR interaction resulted in the inhibition of epithelial-to-mesenchymal transition (EMT) and metastatic genes as indicated by induction of key metastasis-suppressing proteins E-cadherin, claudin (epithelial markers), and PTEN along with induction of tumor suppressor genes p21 and p27. A significant decrease in vimentin (mesenchymal marker), KLF4, and Nanog (stemness markers) was also observed. This is the first report demonstrating miR-203-mediated regulation of HOTAIR induces tumor suppressor effects in RCC by regulating EMT and metastatic pathway genes. Thus, the study suggests that therapeutic regulation of HOTAIR by miR-203 overexpression may provide an opportunity to regulate RCC growth and metastasis. Mol Cancer Ther; 17(5); 1061-9. ©2018 AACR.

MicroRNA-720 Regulates E-cadherin-αE-catenin Complex and Promotes Renal Cell Carcinoma

miRNAs are implicated in regulating cancer progression and metastasis. Here, we show that miR-720 is positively associated with renal cell carcinoma (RCC). Elevated levels of miR-720 were observed in a panel of RCC cell lines and clinical tissues compared with nonmalignant cell line and normal samples. Loss of miR-720 function inhibited proliferation, migration, and invasion and induced apoptosis in RCC cell lines in vitro and repressed tumor growth in xenograft mouse models. Conversely, gain of miR-720 function in nonmalignant HK-2 cells induced procancerous characteristics. Silencing of miR-720 caused a marked induction in the levels of endogenous αE-catenin and E-cadherin protein levels in anti720 transfected cells compared with control, whereas miR-720 overexpression in RCC cell lines reduced activity of a luciferase reporter gene fused to the wild-type αE-catenin or E-cadherin 3'UTR compared with nonspecific 3'UTR control, indicating that αE-catenin-E-cadherin complex is a direct and functional target of miR-720 in RCC. We also observed attenuation of β-catenin, CD44, and Akt expression in RCC cells transfected with miR-720 inhibitor compared with control. Furthermore, miR-720 exhibited clinical significance in RCC. Expression of miR-720 significantly distinguished malignant from normal samples. Elevated miR-720 levels positively correlated with higher Fuhrman grade, pathologic stage, and poor overall survival of RCC patients. These findings uncover a new regulatory network in RCC involving metastasis-promoting miR-720 that directly targets expression of key metastasis-suppressing proteins E-cadherin and αE-catenin complex. These results suggest that therapeutic regulation of miR-720 may provide an opportunity to regulate EMT and metastasis in RCC. Mol Cancer Ther; 16(12); 2840-8. ©2017 AACR.

Relationship between RAS Association Domain Family Protein 1A Promoter Methylation and the Clinicopathological Characteristics in Patients with Ovarian Cancer: A Systematic Meta-Analysis

BACKGROUND

To investigate the relationship between RAS association domain family protein 1A (RASSF1A) promoter methylation and the clinical features, and the survival of ovarian cancer patients.

METHODS

A comprehensive literature search was conducted in the PubMed, Embase, EBSCO, and Cochrane Library databases. The overall ORs with their 95% CIs were calculated in this meta-analysis.

RESULTS

Finally 17 relevant publications with 1,108 ovarian cancer samples were available for the current meta-analysis. RASSF1A promoter methylation had a significantly higher level in ovarian cancer than in low malignant potential (LMP) tumors. No significant relationship was observed between RASSF1A promoter methylation and the clinicopathological characteristics in ovarian cancer. Two studies reported that RASSF1A promoter methylation was not correlated with the survival of patients with ovarian cancer.

CONCLUSIONS

Our findings suggest that the use of RASSF1A promoter methylation could distinguish ovarian cancer and LMP tumors. -RASSF1A promoter methylation may not be correlated with the clinical features and the survival of ovarian cancer patients. More studies with large sample sizes are essential in the future.

Prognostic DNA methylation markers for renal cell carcinoma: a systematic review

AIM

Despite numerous published prognostic methylation markers for renal cell carcinoma (RCC), none of these have yet changed patient management. Our aim is to systematically review and evaluate the literature on prognostic DNA methylation markers for RCC.

MATERIALS & METHODS

We conducted an exhaustive search of PubMed, EMBASE and MEDLINE up to April 2017 and identified 49 publications. Studies were reviewed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, assessed for their reporting quality using the Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK) criteria, and were graded to determine the level of evidence (LOE) for each biomarker.

RESULTS

We identified promoter methylation of BNC1, SCUBE3, GATA5, SFRP1, GREM1, RASSF1A, PCDH8, LAD1 and NEFH as promising prognostic markers. Extensive methodological heterogeneity across the included studies was observed, which hampers comparability and reproducibility of results, providing a possible explanation why these biomarkers do not reach the clinic.

CONCLUSION

Potential prognostic methylation markers for RCC have been identified, but they require further validation in prospective studies to determine their true clinical value.

Prognostic significance of promoter CpG island methylation of obesity-related genes in patients with nonmetastatic renal cell carcinoma

BACKGROUND

Greater than 40% of renal cell carcinoma (RCC) cases in the United States are attributed to excessive body weight. Moreover, obesity also may be linked to RCC prognosis. However, the molecular mechanisms underlying these associations are unclear. In the current study, the authors evaluated the role of promoter methylation in obesity-related genes in RCC tumorigenesis and disease recurrence.

METHODS

Paired tumors (TU) and normal adjacent (N-Adj) tissues from 240 newly diagnosed and previously untreated white patients with RCC were examined. For the discovery phase, 63 RCC pairs were analyzed. An additional 177 RCC pairs were evaluated for validation. Pyrosequencing was used to determine CpG methylation in 20 candidate obesity-related genes. An independent data set from The Cancer Genome Atlas also was analyzed for functional validation. The association between methylation and disease recurrence was analyzed using multivariate Cox proportional hazards models and Kaplan-Meier survival analysis.

RESULTS

Methylation in neuropeptide Y (NPY), leptin (LEP), and leptin receptor (LEPR) was significantly higher in TU compared with N-Adj tissues (P<.0001) in both the discovery and validation groups. High methylation in LEPR was associated with an increased risk of disease recurrence (hazard ratio, 3.15; 95% confidence interval, 1.23-8.07 [P = .02]). Patients with high methylation in LEPR had a shorter recurrence-free survival compared with patients in the low-methylation group (log-rank P = 2.25 × 10^-3 ). In addition, high LEPR methylation in TU was associated with more advanced features (P≤.05). Consistent with the findings of the current study, lower LEPR expression in TU compared with N-Adj tissues (P = 1.00 × 10^-3 ) was found in data from The Cancer Genome Atlas.

CONCLUSIONS

Somatic alterations of promoter methylation in the NPY, LEP, and LEPR genes are involved in RCC tumorigenesis. Furthermore, LEPR methylation appears to be associated with RCC recurrence. Future research to elucidate the biology underlying this association is warranted. Cancer 2017;123:3617-27. © 2017 American Cancer Society.