Tumor-specific hypermethylation of epigenetic biomarkers, including SFRP1, predicts for poorer survival in patients from the TCGA Kidney Renal Clear Cell Carcinoma (KIRC) project

Alternative Polyadenylation Regulatory Factors Signature for Survival Prediction in Kidney Renal Cell Carcinoma

Background

Alternative polyadenylation (APA) plays a vital regulatory role in various diseases. It is widely accepted that APA is regulated by APA regulatory factors.

Objective

Whether APA regulatory factors affect the prognosis of renal cell carcinoma remains unclear, and this is the main topic of this study.

Methods

We downloaded the transcriptome and clinical data from The Cancer Genome Atlas (TCGA) database. We used the Lasso regression system to construct an APA model for analyzing the relationship between common APA regulatory factors and renal cell carcinoma. We also validated our APA model using independent GEO datasets (GSE29609, GSE76207).

Results

It was found that the expression levels of 5 APA regulatory factors (CPSF1, CPSF2, CSTF2, PABPC1, and PABPC4) were significantly associated with tumor gene mutation burden (TMB) score in renal clear cell carcinoma, and the risk score constructed using the expression level of 5 key APA regulatory factors could be used to predict the outcome of renal clear cell carcinoma. The TMB score is associated with the remodeling of the immune microenvironment.

Conclusions

By identifying key APA regulatory factors in renal cell carcinoma and constructing risk scores for key APA regulatory factors, we showed that key APA regulators affect prognosis of renal clear cell carcinoma patients. In addition, the risk score level is associated with TMB, indicating that APA may affect the efficacy of immunotherapy through immune microenvironment-related genes. This helps us better understand the mRNA processing mechanism of renal clear cell carcinoma.

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.

Alteration of Cadherin 3 Expression and DNA Methylation in Association with Aggressive Renal Cell Carcinoma

Cadherins (calcium-dependent adhesion proteins) are important in cellular adhesion and may play a role in the development and progression of renal cell carcinoma (RCC). This study investigated changes in cadherin 3 (CDH3; P-cadherin) mRNA expression, DNA methylation, and protein expression in RCC and compared the results with the histopathological and clinical characteristics of patients. The possible contribution of CDH3 to tumor cell invasiveness was tested in a functional assay using siRNA-based suppression of CDH3 expression and subsequent real-time impedance analysis using a Matrigel invasion model. Our analyses revealed a tumor-specific loss of CDH3 mRNA expression, CDH3 DNA hypermethylation, and loss of distal tubular and collecting duct CDH3 protein expression in RCC. A relatively higher methylation level in tumors was associated with a loss of cell differentiation and higher clinical stage. siRNA-induced suppression of CDH3 expression modulated the invasion characteristics of tumor cells in the impedance-based real-time cellular analysis. Our results indicate that loss of CDH3 expression is common in RCC and may contribute to the pathogenesis of a subset of RCC. Further studies to reveal the mechanisms of loss of expression and its effects on the invasive behavior of renal tumor cells are required.

Promoter hypermethylation of SFRP1 as a prognostic and potentially predictive blood-based biomarker in patients with localized pancreatic ductal adenocarcinoma

Introduction

Current prognostic blood-based biomarkers for pancreatic adenocarcinoma (PDAC) are limited. Recently, promoter hypermethylation of SFRP1 (phSFRP1) has been linked to poor prognosis in patients with gemcitabine-treated stage IV PDAC. This study explores the effects of phSFRP1 in patients with lower stage PDAC.

Methods

Based on a bisulfite treatment process, the promoter region of the SFRP1 gene was analyzed with methylation-specific PCR. Kaplan-Meier curves, log-rank tests, and generalized linear regression analysis were used to assess restricted mean survival time survival at 12 and 24 months.

Results

The study included 211 patients with stage I-II PDAC. The median overall survival of patients with phSFRP1 was 13.1 months, compared to 19.6 months in patients with unmethylated SFRP1 (umSFRP1). In adjusted analysis, phSFRP1 was associated with a loss of 1.15 months (95%CI -2.11, -0.20) and 2.71 months (95%CI -2.71, -0.45) of life at 12 and 24 months, respectively. There was no significant effect of phSFRP1 on disease-free or progression-free survival. In stage I-II PDAC, patients with phSFRP1 have worse prognoses than patients with umSFRP1.

Discussion

Results could indicate that the poor prognosis may be caused by reduced benefit from adjuvant chemotherapy. SFRP1 may help guide the clinician and be a possible target for epigenetically modifying drugs.

Recent advances in understanding DNA methylation of prostate cancer

Epigenetic modifications, such as DNA methylation, is widely studied in cancer. DNA methylation patterns have been shown to distinguish between benign and malignant tumors in various cancers, including prostate cancer. It may also contribute to oncogenesis, as it is frequently associated with downregulation of tumor suppressor genes. Aberrant patterns of DNA methylation, in particular the CpG island hypermethylator phenotype (CIMP), have shown associative evidence with distinct clinical features and outcomes, such as aggressive subtypes, higher Gleason score, prostate-specific antigen (PSA), and overall tumor stage, overall worse prognosis, as well as reduced survival. In prostate cancer, hypermethylation of specific genes is significantly different between tumor and normal tissues. Methylation patterns could distinguish between aggressive subtypes of prostate cancer, including neuroendocrine prostate cancer (NEPC) and castration resistant prostate adenocarcinoma. Further, DNA methylation is detectable in cell-free DNA (cfDNA) and is reflective of clinical outcome, making it a potential biomarker for prostate cancer. This review summarizes recent advances in understanding DNA methylation alterations in cancers with the focus on prostate cancer. We discuss the advanced methodology used for evaluating DNA methylation changes and the molecular regulators behind these changes. We also explore the clinical potential of DNA methylation as prostate cancer biomarkers and its potential for developing targeted treatment of CIMP subtype of prostate cancer.

Expression and clinical significance of DOK3 in renal clear cell carcinoma

OBJECTIVES

Docking Protein 3 (DOK3) is an adapter protein that has been implicated in various cellular processes relevant to diseases, such as cancer. In this study, we aimed to evaluate the role of DOK3 in kidney renal clear cell carcinoma (KIRC) by examining how its expression levels are correlated with patient characteristics and prognosis.

METHODS

We analyzed KIRC-related data from The Cancer Genome Atlas and used several bioinformatics tools, such as LinkedOmics and Oncomine, to evaluate DOK3 mRNA expression in KIRC. DOK3 protein expression was examined in 150 clinical KIRC samples and 100 non-cancerous renal tissues with immunohistochemistry assays. The prognostic value of DOK3 mRNA expression on patient overall survival was analyzed retrospectively using Kaplan-Meier survival and Cox regression analyses.

RESULTS

DOK3 mRNA expression was notably higher in KIRC samples compared with normal tissues. Significant correlations were found between DOK3 mRNA expression levels and tumor size, lymph node metastasis, distant metastasis, and pathological grade using the bioinformatics data. This was confirmed at the protein level with immunohistochemistry data. Survival analyses indicated that elevated DOK3 expression is linked to a lower overall survival rate in KIRC patients.

CONCLUSIONS

DOK3 is a potential biomarker for determining KIRC patient clinical prognosis.

HIGD1A inactivated by DNA hypermethylation promotes invasion of kidney renal clear cell carcinoma

Hypoxia contributes to the tumorigenesis and metastasis of the tumor. However, the detailed mechanisms underlying hypoxia and kidney renal clear cell carcinoma (KIRC) development and progression remain unclear. Here, we investigated the role of the system HIG1 hypoxia inducible domain family member 1 A (HIGD1A) in the proliferation and metastasis of KIRC and elucidated the underlying molecular mechanisms. The expression of HIGD1A is significantly downregulated in KIRC due to promoter hypermethylation. HIGD1A could serve as a valuable diagnostic biomarker in KIRC. In addition, ectopic overexpression of HIGD1A significantly suppressed the growth and invasive capacity of KIRC cells in vitro under normal glucose conditions. Interestingly, the suppressive efficacy in invasion is much more significant when depleted glucose, but not in proliferation. Furthermore, mRNA expression of HIGD1A positively correlates with CDH1 and EPCAM, while negatively correlated with VIM and SPARC, indicating that HIGD1A impedes invasion of KIRC by regulating epithelial-mesenchymal transition (EMT). Our data suggest that HIGD1A is a potential diagnostic biomarker and tumor suppressor in KIRC.

Bioinformatics analysis of markers based on m6 A related to prognosis combined with immune invasion of renal clear cell carcinoma

The incidence rate of renal cell carcinoma (RCC) is about 3% of all adult cancers. Of these, the Kidney clear cell renal cell carcinoma (KIRC) is the most common type, accounting for about 70%-75% of RCC. KIRC is difficult to be detected in time clinically. KIRC still has no effective treatment at this stage. We combined high-throughput bioinformatics analysis to obtained the structural sequence transcriptome data, relevant clinical information, and m⁶ A gene map of KIRC patients from genomics TCGA database. Pearson's correlation analysis was used to explore m⁶ A related gene long noncoding RNAs (lncRNAs), and then univariate Cox regression analysis was performed to screen the prognostic role of KIRC patients. Lasso-Cox regression was performed to establish the lncRNAs risk model associated with m⁶ A.LINC02154 and AC016773.2, Z98200.2, AL161782.1, EMX2OS, AC021483.2, CD27-AS1, AC006213.3 were iidentif. Compared with the low-risk group, the overall survival of patients in the high-risk group was significantly worse. Analyzing whether there are differences in immune cells between high-risk and low-risk subgroups. There were CD4 memory resting, Monocytes, Macrophages M1, Dendritic cells activated, Mast cells resting, which had higher infiltrations in the low-risk group. We performed Go enrichment analysis, Kyoto Encyclopedia of Genes and Genomes enrichment analysis and gene set enrichment analysis enrichment analysis. Overall, our results suggest that the component of m6A-related lncRNAs in the prognostic signal may be a key mediator in the immune microenvironment of KIRC, which represents a promising therapeutic effect.

Kidney tumors associated with germline mutations of FH and SDHB show a CpG island methylator phenotype (CIMP)

Germline mutations within the Krebs cycle enzyme genes fumarate hydratase (FH) or succinate dehydrogenase (SDHB, SDHC, SDHD) are associated with an increased risk of aggressive and early metastasizing variants of renal cell carcinoma (RCC). These RCCs express significantly increased levels of intracellular fumarate or succinate that inhibit 2-oxoglutarate-dependent dioxygenases, such as the TET enzymes that regulate DNA methylation. This study evaluated the genome-wide methylation profiles of 34 RCCs from patients with RCC susceptibility syndromes and 11 associated normal samples using the Illumina HumanMethylation450 BeadChip. All the HLRCC (FH mutated) and SDHB-RCC (SDHB mutated) tumors demonstrated a distinct CpG island methylator phenotype (CIMP). HLRCC tumors demonstrated an extensive and relatively uniform level of hypermethylation that showed some correlation with tumor size. SDHB-RCC demonstrated a lesser and more varied pattern of hypermethylation that overlapped in part with the HLRCC hypermethylation. Combined methylation and mRNA expression analysis of the HLRCC tumors demonstrated hypermethylation and transcription downregulation of genes associated with the HIF pathway, HIF3A and CITED4, the WNT pathway, SFRP1, and epithelial-to-mesenchymal transition and MYC expression, OVOL1. These observations were confirmed in the TCGA CIMP-RCC tumors. A selected panel of probes could identify the CIMP tumors and differentiate between HLRCC and SDHB-RCC tumors. This panel accurately detected all CIMP-RCC tumors within the TCGA RCC cohort, identifying them as HLRCC -like, and could potentially be used to create a liquid biopsy-based screening tool. The CIMP signature in these aggressive tumors could provide both a useful biomarker for diagnosis and a target for novel therapies.

Diagnostic and Prognostic Biomarkers in Renal Clear Cell Carcinoma

Renal clear cell carcinoma (ccRCC) comprises over 75% of all renal tumors and arises in the epithelial cells of the proximal convoluted tubule. Molecularly ccRCC is characterized by copy number alterations (CNAs) such as the loss of chromosome 3p and VHL inactivation. Additional driver mutations (SETD2, PBRM1, BAP1, and others) promote genomic instability and tumor cell metastasis through the dysregulation of various metabolic and immune-response pathways. Many researchers identified mutation, gene expression, and proteomic signatures for early diagnosis and prognostics for ccRCC. Despite a tremendous influx of data regarding DNA alterations, gene expression, and protein expression, the incorporation of these analyses for diagnosis and prognosis of RCC into the clinical application has not been implemented yet. In this review, we focused on the molecular changes associated with ccRCC development, along with gene expression and protein signatures, to emphasize the utilization of these molecular profiles in clinical practice. These findings, in the context of machine learning and precision medicine, may help to overcome some of the barriers encountered for implementing molecular profiles of tumors into the diagnosis and treatment of ccRCC.

The Next Paradigm Shift in the Management of Clear Cell Renal Cancer: Radiogenomics—Definition, Current Advances, and Future Directions

With improved molecular characterization of clear cell renal cancer and advances in texture analysis as well as machine learning, diagnostic radiology is primed to enter personalized medicine with radiogenomics: the identification of relationships between tumor image features and underlying genomic expression. By developing surrogate image biomarkers, clinicians can augment their ability to non-invasively characterize a tumor and predict clinically relevant outcomes (i.e., overall survival; metastasis-free survival; or complete/partial response to treatment). It is thus important for clinicians to have a basic understanding of this nascent field, which can be difficult due to the technical complexity of many of the studies. We conducted a review of the existing literature for radiogenomics in clear cell kidney cancer, including original full-text articles until September 2021. We provide a basic description of radiogenomics in diagnostic radiology; summarize existing literature on relationships between image features and gene expression patterns, either computationally or by radiologists; and propose future directions to facilitate integration of this field into the clinical setting.

Clinicopathological significance and underlying molecular mechanism of downregulation of basonuclin 1 expression in ovarian carcinoma

In this study, we aim to identify the clinical significance of basonuclin 1 (BNC1) expression in ovarian carcinoma (OV) and to explore its latent mechanisms. Via integrating in-house tissue microarrays, gene chips, and RNA-sequencing data, we explored the expression and clinical value of BNC1 in OV. Immunohistochemical staining was utilized to confirm the protein expression status of BNC1. A combined SMD of -2.339 (95% CI: -3.649 to -1.028, P < 0.001) identified that BNC1 was downregulated based on 1346 samples, and the sROC (AUC = 0.93) showed a favorable discriminatory ability of BNC1 in OV patients. We used univariate and multivariate Cox regulation to evaluate the prognostic role of BNC1 for OV patients, and a combined hazard ratio of 0.717 (95% CI: 0.445-0.989, P < 0.001) revealed that BNC1 was a protective factor for OV. Furthermore, the fraction of infiltrating naive B cells, memory B cells, and other immune cells showed statistical differences between the high- and low-BNC1 expression groups through cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm. Enrichment analysis showed that BNC1 may have a relationship with immune-related items in OV. By predicting the potential regulatory transcription factors (TFs) of BNC1, friend leukemia virus integration 1 (FLI1) may be a potential upstream TF of BNC1. Corporately, a decreasing trend of BNC1 may serve as a tumor suppressor and prognostic biomarker in OV patients. Moreover, BNC1 may take part in immune-related pathways and influence the fraction of tumor-infiltrating immune cells.

Validation of SFRP1 Promoter Hypermethylation in Plasma as a Prognostic Marker for Survival and Gemcitabine Effectiveness in Patients with Stage IV Pancreatic Adenocarcinoma

Simple Summary

Pancreatic adenocarcinoma (PDAC) is a disease with an incredibly grim prognosis. Most patients die within one year of receiving the diagnosis. There are currently very few tools to help the clinician decide between treatment options and evaluate prognosis at an individual level. The aim of the current study was to assess the effect of promoter hypermethylation of secreted frizzled-related protein 1 (phSFRP1) as an independent prognostic blood-based biomarker in gemcitabine-treated patients with advanced PDAC. The study was conducted as a combined discovery and validation study. Analysis in both cohorts confirmed that patients with phSFRP1 had overall poorer survival compared to those without hypermethylation. Thus, phSFRP1 shows promise as an independent prognostic biomarker in this patient group and can hopefully aid the clinician and patient find the correct balance between quantity and quality of life.

Abstract

No reliable predictive blood-based biomarkers are available for determining survival from pancreatic adenocarcinoma (PDAC). This combined discovery and validation study examines promoter hypermethylation (ph) of secreted frizzled-related protein 1 (SFRP1) in plasma-derived cell-free DNA as an independent prognostic marker for survival and Gemcitabine effectiveness in patients with stage IV PDAC. We conducted methylation-specific polymerase chain reaction analysis of the promoter region of the SFRP1 gene, based on bisulfite treatment. Survival was analyzed with Kaplan–Meier curves, log-rank test, and Cox regression. The discovery cohort included 40 patients, 25 receiving Gem. Gem-treated patients with phSFRP1 had a shorter median overall survival (mOS) (4.4 months) than unmethylated patients (11.6 months). Adjusted Cox-regression yielded a hazard rate (HR) of 3.48 (1.39–8.70). The validation cohort included 58 Gem-treated patients. Patients with phSFRP1 had a shorter mOS (3.2 months) than unmethylated patients (6.3 months). Adjusted Cox regression yielded an HR of 3.53 (1.85–6.74). In both cohorts, phSFRP1 was associated with poorer survival in Gem-treated patients. This may indicate that tumors with phSFRP1 are more aggressive and less sensitive to Gem treatment. This knowledge may facilitate tailored treatment of patients with stage IV PDAC. Further studies are planned to examine phSFRP1 in more intensive chemotherapy regimens.

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.

Molecular characterisation of sporadic endolymphatic sac tumours and comparison to von Hippel-Lindau disease-related tumours

AIMS

Although inactivation of the von Hippel-Lindau gene (VHL) on chromosome 3p25 is considered to be the major cause of hereditary endolymphatic sac tumours (ELSTs), the genetic background of sporadic ELST is largely unknown. The aim of this study was to determine the prevalence of VHL mutations in sporadic ELSTs and compare their characteristics to VHL-disease-related tumours.

METHODS

Genetic and epigenetic alterations were compared between 11 sporadic and 11 VHL-disease-related ELSTs by targeted sequencing and DNA methylation analysis.

RESULTS

VHL mutations and small deletions detected by targeted deep sequencing were identified in 9/11 sporadic ELSTs (82%). No other cancer-related genetic pathway was altered except for TERT promoter mutations in two sporadic ELST and one VHL-disease-related ELST (15%). Loss of heterozygosity of chromosome 3 was found in 6/10 (60%) VHL-disease-related and 10/11 (91%) sporadic ELSTs resulting in biallelic VHL inactivation in 8/10 (73%) sporadic ELSTs. DNA methylation profiling did not reveal differences between sporadic and VHL-disease-related ELSTs but reliably distinguished ELST from morphological mimics of the cerebellopontine angle. VHL patients were significantly younger at disease onset compared to sporadic ELSTs (29 vs. 52 years, p < 0.0001, Fisher's exact test). VHL-disease status was not associated with an increased risk of recurrence, but the presence of clear cells was found to be associated with shorter progression-free survival (p = 0.0002, log-rank test).

CONCLUSION

Biallelic inactivation of VHL is the main mechanism underlying ELSTs, but unknown mechanisms beyond VHL may rarely be involved in the pathogenesis of sporadic ELSTs.

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.

SOX17 Antagonizes the WNT Signaling Pathway and is Epigenetically Inactivated in Clear-Cell Renal Cell Carcinoma

Background

SRY-box containing gene 17 (SOX17) was reported to be a candidate tumor suppressor gene in multiple tumors. Little is known about its role in clear-cell renal cell carcinoma (ccRCC). This study aims to identify the epigenetic regulation and tumor-suppressive function of SOX17 in ccRCC.

Patients and Methods

Fifty-five human ccRCC tissue samples, ten adjacent non-malignant kidney tissue samples, 20 paired paraffin section tissues and seven RCC cell lines were obtained. Immunohistochemistry (IHC) and real-time PCR were used to examine the expression of the target genes at the mRNA and protein levels. The methylation of SOX17 was analyzed using methylation-specific PCR (MSP) and bisulfite genomic sequencing (BGS) assay. The functions of SOX17 were examined by using CCK8, colony formation, wound healing assay and Matrigel invasion assays. Luciferase assay was used to analyze the function of SOX17 in the WNT signaling pathway.

Results

We investigated the SOX17 expression in ccRCC tissues and adjacent non-malignant kidney tissues using PCR and IHC. The expression of SOX17 was lower in ccRCC tissues. Next, we analyzed the DNA promoter methylation of SOX17 in 55 human ccRCC tissues, 10 adjacent non-malignant kidney tissues and RCC cell lines using MSP. DNA methylation of the SOX17 promoter region occurred in 60% of ccRCC tissues and 10% of adjacent non-malignant kidney tissues. In vitro experiments showed that SOX17 suppressed the proliferation of RCC cells. Furthermore, SOX17 inhibited the migration of RCC cells as shown in the wound healing and migration assays. In addition, we found that SOX17 overexpression affected the WNT signaling pathway by downregulating c-myc and cyclinD1.

Conclusion

In summary, our study showed that SOX17 is downregulated in ccRCC and the loss of SOX17 expression is regulated via epigenetic mechanisms in ccRCC. In addition, SOX17 negatively regulates the WNT signaling pathway and function as a tumor suppressor in ccRCC.

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.

Radiomic profiling of clear cell renal cell carcinoma reveals subtypes with distinct prognoses and molecular pathways

•

Radiomics profile of clear cell renal cell carcinoma is heterogeneity.

•

Multi-scale Radiogenomics could link molecular features and images.

•

Radiomic subtypes could be used for risk stratification.

Background

To identify radiomic subtypes of clear cell renal cell carcinoma (ccRCC) patients with distinct clinical significance and molecular characteristics reflective of the heterogeneity of ccRCC.

Methods

Quantitative radiomic features of ccRCC were extracted from preoperative CT images of 160 ccRCC patients. Unsupervised consensus cluster analysis was performed to identify robust radiomic subtypes based on these features. The Kaplan–Meier method and chi-square test were used to assess the different clinicopathological characteristics and gene mutations among the radiomic subtypes. Subtype-specific marker genes were identified, and gene set enrichment analyses were performed to reveal the specific molecular characteristics of each subtype. Moreover, a gene expression-based classifier of radiomic subtypes was developed using the random forest algorithm and tested in another independent cohort (n = 101).

Results

Radiomic profiling revealed three ccRCC subtypes with distinct clinicopathological features and prognoses. VHL, MUC16, FBN2, and FLG were found to have different mutation frequencies in these radiomic subtypes. In addition, transcriptome analysis revealed that the dysregulation of cell cycle-related pathways may be responsible for the distinct clinical significance of the obtained subtypes. The prognostic value of the radiomic subtypes was further validated in another independent cohort (log-rank P = 0.015).

Conclusion

In the present multi-scale radiogenomic analysis of ccRCC, radiomics played a central role. Radiomic subtypes could help discern genomic alterations and non-invasively stratify ccRCC patients.

Cell-Free DNA Methylation as Blood-Based Biomarkers for Pancreatic Adenocarcinoma—A Literature Update

Pancreatic adenocarcinoma has a horrible prognosis, which is partly due to difficulties in diagnosing the disease in an early stage. Additional blood-born biomarkers for pancreatic adenocarcinoma are needed. Epigenetic modifications, as changes in DNA methylation, is a fundamental part of carcinogenesis. The aim of this paper is to do an update on cell-free DNA methylation as blood-based biomarkers for pancreatic adenocarcinoma. The current literature including our studies clearly indicates that cell-free DNA methylation has the potential as blood-based diagnostic and prognostic biomarkers for pancreatic adenocarcinoma. However, still no clinical applicable biomarker for pancreatic adenocarcinoma based on DNA methylation do exist. Further well-designed validation studies are needed.

Silencing of the TRIM58 Gene by Aberrant Promoter Methylation is Associated with a Poor Patient Outcome and Promotes Cell Proliferation and Migration in Clear Cell Renal Cell Carcinoma

To investigate the underlying molecular mechanism of tripartite motif-containing 58 (TRIM58) in the development of clear cell renal cell carcinoma (ccRCC), we explored TRIM58 expression and methylation in tumor tissues and the association with clinicopathological features and prognosis of tissue samples; Moreover, we examined the direct gene transcription of TRIM58-specific DNA demethyltransferase (TRIM58-TET1) by the CRISPR-dCas9 fused with the catalytic domain of TET1 and the biological functions in RCC cells. In this study, we demonstrate that TRIM58 is frequently downregulated by promoter methylation in ccRCC tissues, associated significantly with tumor nuclear grade and poor patient survival. TRIM58-TET1 directly induces demethylation of TRIM58 CpG islands, and activates TRIM58 transcription in RCC cell lines. Besides, DNA demethylation of TRIM58 by TRIM58-TET1 significantly inhibits cell proliferation and migration Overall, our results demonstrate that TRIM58 is inactivated by promoter methylation, associates with tumor nuclear grade and poor survival, and TRIM58 DNA demethylation could directly activate TRIM58 transcription and inhibit cell proliferation and migration in RCC cell lines.

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.

Reduction of SCUBE3 by a new marine-derived asterosaponin leads to arrest of glioma cells in G1/S

Many saponins are characterized as exhibiting a wide spectrum of antitumor activities at low concentrations. Most of the previous studies that aimed to understand the mechanisms underlying anticancer saponins have focused on numerous classical signaling pathways. However, at the oncogene level, little is known about the action of saponins, especially asterosaponin. In this study, CN-3, a new asterosaponin isolated from the starfish Culcita novaeguineae, decreased the proliferation of U87 and U251 cells at low doses in a dose- and time-dependent manner. Microarray analysis revealed CN-3 significantly induced the differential expression of 661 genes that are related to its antiglioma effect in U251. Nine downregulated genes (SCUBE3, PSD4, PGM2L1, ACSL3, PRICKLE1, ABI3BP, STON1, EDIL3, and KCTD12) were selected, for further verification of their low expression. Then, shRNA transfection and high-content screening were performed and significantly decreased U251 cell proliferation rate was only observed for the SCUBE3 knockdown. qPCR confirmed SCUBE3 was highly expressed in U251 and U87 cells, and had medium expression levels in U373 cells. Real-time cellular analysis using iCELLigence demonstrated that SCUBE3 is an oncogene in U251 and U87 cells, with knockdown of SCUBE3 inhibiting U251 and U87 cell proliferation while, conversely, SCUBE3 overexpression promoted their proliferation. Afterward, SCUBE3 protein was found to have high expression in primary glioma specimens from patients examined by immunohistochemistry but low expression in normal brain. PathScan ELISA analysis in conjunction with TEM observation demonstrated that the effect of SCUBE3 knockdown in U251 does not appear to be related to the induction of apoptosis. Employing CCK-8, iCELLigence, flow cytometry, western blotting, and shRNA transfection (knockdown and overexpression) experiments, we reveal that the reduction of SCUBE3 expression, induced by CN-3, mediated both inhibition and G1/S arrest of U251 via the Akt/p-Akt/p53/p21/p27/E2F1 pathway.

Role of fibrillin-2 in the control of TGF-β activation in tumor angiogenesis and connective tissue disorders

Fibrillins constitute a family of large extracellular glycoproteins which multimerize to form microfibrils, an important structure in the extracellular matrix. It has long been assumed that fibrillin-2 was barely present during postnatal life, but it is now clear that fibrillin-2 molecules form the structural core of microfibrils, and are masked by an outer layer of fibrillin-1. Mutations in fibrillins give rise to heritable connective tissue disorders, including Marfan syndrome and congenital contractural arachnodactyly. Fibrillins also play an important role in matrix sequestering of members of the transforming growth factor-β family, and in context of Marfan syndrome excessive TGF-β activation has been observed. TGF-β activation is highly dependent on integrin binding, including integrin αvβ8 and αvβ6, which are upregulated upon TGF-β exposure. TGF-β is also involved in tumor progression, metastasis, epithelial-to-mesenchymal transition and tumor angiogenesis. In several highly vascularized types of cancer such as hepatocellular carcinoma, a positive correlation was found between increased TGF-β plasma concentrations and tumor vascularity. Interestingly, fibrillin-1 has a higher affinity to TGF-β and, therefore, has a higher capacity to sequester TGF-β compared to fibrillin-2. The previously reported downregulation of fibrillin-1 in tumor endothelium affects the fibrillin-1/fibrillin-2 ratio in the microfibrils, exposing the normally hidden fibrillin-2. We postulate that fibrillin-2 exposure in the tumor endothelium directly stimulates tumor angiogenesis by influencing TGF-β sequestering by microfibrils, leading to a locally higher active TGF-β concentration in the tumor microenvironment. From a therapeutic perspective, fibrillin-2 might serve as a potential target for future anti-cancer therapies.

A Gene Signature of Survival Prediction for Kidney Renal Cell Carcinoma by Multi-Omic Data Analysis

Kidney renal cell carcinoma (KIRC), which is the most common subtype of kidney cancer, has a poor prognosis and a high mortality rate. In this study, a multi-omics analysis is performed to build a multi-gene prognosis signature for KIRC. A combination of a DNA methylation analysis and a gene expression data analysis revealed 863 methylated differentially expressed genes (MDEGs). Seven MDEGs (BID, CCNF, DLX4, FAM72D, PYCR1, RUNX1, and TRIP13) were further screened using LASSO Cox regression and integrated into a prognostic risk score model. Then, KIRC patients were divided into high- and low-risk groups. A univariate cox regression analysis revealed a significant association between the high-risk group and a poor prognosis. The time-dependent receiver operating characteristic (ROC) curve shows that the risk group performs well in predicting overall survival. Furthermore, the risk group is contained in the best multivariate model that was obtained by a multivariate stepwise analysis, which further confirms that the risk group can be used as a potential prognostic biomarker. In addition, a nomogram was established for the best multivariate model and shown to perform well in predicting the survival of KIRC patients. In summary, a seven-MDEG signature is a powerful prognosis factor for KIRC patients and may provide useful suggestions for their personalized therapy.

DNA methylation associates with survival in non-metastatic clear cell renal cell carcinoma

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is the most common subtype among renal cancer and is associated with poor prognosis if metastasized. Up to one third of patients with local disease at diagnosis will develop metastasis after nephrectomy, and there is a need for new molecular markers to identify patients with high risk of tumor progression. In the present study, we performed genome-wide promoter DNA methylation analysis at diagnosis to identify DNA methylation profiles associated with risk for progress.

METHOD

Diagnostic tissue samples from 115 ccRCC patients were analysed by Illumina HumanMethylation450K arrays and methylation status of 155,931 promoter associated CpGs were related to genetic aberrations, gene expression and clinicopathological parameters.

RESULTS

The ccRCC samples separated into two clusters (cluster A/B) based on genome-wide promoter methylation status. The samples in these clusters differed in tumor diameter (p < 0.001), TNM stage (p < 0.001), morphological grade (p < 0.001), and patients outcome (5 year cancer specific survival (pCSS5yr) p < 0.001 and cumulative incidence of progress (pCIP5yr) p < 0.001. An integrated genomic and epigenomic analysis in the ccRCCs, revealed significant correlations between the total number of genetic aberrations and total number of hypermethylated CpGs (R = 0.435, p < 0.001), and predicted mitotic age (R = 0.407, p < 0.001). We identified a promoter methylation classifier (PMC) panel consisting of 172 differently methylated CpGs accompanying progress of disease. Classifying non-metastatic patients using the PMC panel showed that PMC high tumors had a worse prognosis compared with the PMC low tumors (pCIP5yr 38% vs. 8%, p = 0.001), which was confirmed in non-metastatic ccRCCs in the publically available TCGA-KIRC dataset (pCIP5yr 39% vs. 16%, p < 0.001).

CONCLUSION

DNA methylation analysis at diagnosis in ccRCC has the potential to improve outcome-prediction in non-metastatic patients at diagnosis.

MicroRNA Biomarkers for Patients With Muscle-Invasive Bladder Cancer Undergoing Selective Bladder-Sparing Trimodality Treatment

PURPOSE

Trimodality therapy with maximal transurethral resection of bladder tumor and definitive chemoradiation reserving cystectomy for salvage of local recurrence is an accepted treatment alternative to upfront cystectomy for selected patients with muscle-invasive bladder cancer. There is a need for molecular biomarkers to predict which patients will respond to bladder preservation therapy.

METHODS AND MATERIALS

We sought to identify biomarkers with the ability to predict response to chemoradiation and survival after selective bladder preservation therapy in a cohort of 40 patients using a microRNA profiling approach. In vitro experiments were performed using transitional cell carcinoma lines CRL1749, HTB5, and HTB4.

RESULTS

We identified a panel of microRNAs associated with overall survival in our bladder preservation cohort and in the TCGA cohort. We also identified several microRNAs, including miR-23a and miR-27a, microRNAs of the miR-23a cluster, to be suggestively associated with complete response to chemoradiation therapy. The microRNAs were significantly associated with overall survival in The Cancer Genome Atlas cohort. In vitro studies suggest that the functional roles of miR-23a and miR-27a involve targeting the SFRP1 protein, a negative regulator of the Wnt signaling pathway. The upregulation of β-catenin in the Wnt signaling pathway mediated proliferation, migration, invasion, and sensitivity to radiation and cisplatin treatment in bladder cancer cells.

CONCLUSIONS

Our results indicate that miR-23a and miR-27a act as oncomirs, and once independently validated, they may help appropriately triage selected bladder cancer patients to individualize treatment.

The Cancer Genome Atlas Comprehensive Molecular Characterization of Renal Cell Carcinoma

Renal cell carcinoma (RCC) is not a single disease, but several histologically defined cancers with different genetic drivers, clinical courses, and therapeutic responses. The current study evaluated 843 RCC from the three major histologic subtypes, including 488 clear cell RCC, 274 papillary RCC, and 81 chromophobe RCC. Comprehensive genomic and phenotypic analysis of the RCC subtypes reveals distinctive features of each subtype that provide the foundation for the development of subtype-specific therapeutic and management strategies for patients affected with these cancers. Somatic alteration of BAP1, PBRM1, and PTEN and altered metabolic pathways correlated with subtype-specific decreased survival, while CDKN2A alteration, increased DNA hypermethylation, and increases in the immune-related Th2 gene expression signature correlated with decreased survival within all major histologic subtypes. CIMP-RCC demonstrated an increased immune signature, and a uniform and distinct metabolic expression pattern identified a subset of metabolically divergent (MD) ChRCC that associated with extremely poor survival.

MethSurv: a web tool to perform multivariable survival analysis using DNA methylation data

Aim: To develop a web tool for survival analysis based on CpG methylation patterns. Materials & methods: We utilized methylome data from ‘The Cancer Genome Atlas’ and used the Cox proportional-hazards model to develop an interactive web interface for survival analysis. Results: MethSurv enables survival analysis for a CpG located in or around the proximity of a query gene. For further mining, cluster analysis for a query gene to associate methylation patterns with clinical characteristics and browsing of top biomarkers for each cancer type are provided. MethSurv includes 7358 methylomes from 25 different human cancers. Conclusion: The MethSurv tool is a valuable platform for the researchers without programming skills to perform the initial assessment of methylation-based cancer biomarkers.

Cell-free DNA promoter hypermethylation in plasma as a predictive marker for survival of patients with pancreatic adenocarcinoma

Introduction

Few prognostic biomarkers are available for pancreatic cancer. The aim of this study is to examine the correlation between the survival of pancreatic adenocarcinoma patients and hypermethylated genes in plasma-derived cell-free DNA.

Methods

Consecutive patients with pancreatic adenocarcinoma were prospectively included and staged according to the TNM classification. Methylation-specific PCR of 28 genes was conducted. A survival prediction model independent of cancer stage and stage-specific survival prediction models were developed by multivariable Cox regression analysis using backward stepwise selection.

Results

Ninety-five patients with pancreatic adenocarcinoma were included. Patients with more than 10 hypermethylated genes had a HR of 2.03 (95% CI; 1.15-3.57) compared to patients with fewer hypermethylated genes. Three survival prediction models were developed: Total group; (American Society of Anesthesiologists score (ASA)=3, GSTP1, SFRP2, BNC1, SFRP1, TFPI2, and WNT5A) Risk groups 2, 3 and 4 had a HR of 2.65 (95% CI; 1.24-5.66), 4.34 (95% CI; 1.98-9.51) and 21.19 (95% CI; 8.61-52.15), respectively, compared to risk group 1. Stage I-II; (ASA=3, SFRP2, and MESTv2) Risk groups 2, 3 and 4 had a HR of 4.83 (95% CI; 2.01-11.57), 9.12 (95% CI; 2.18-38.25) and 70.90 (95% CI; 12.63-397.96), respectively, compared to risk group 1. Stage IV; (BMP3, NPTX2, SFRP1, and MGMT) Risk group 2 had a HR of 5.23 (95% CI; 2.13-12.82) compared to risk group 1.

Conclusion

Prediction models based on cell-free DNA hypermethylation stratified pancreatic adenocarcinoma patients into risk groups according to survival. The models have the potential to work as prognostic biomarkers. However, further validation of the results is required to substantiate the findings.

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.

UALCAN: A Portal for Facilitating Tumor Subgroup Gene Expression and Survival Analyses

Genomics data from The Cancer Genome Atlas (TCGA) project has led to the comprehensive molecular characterization of multiple cancer types. The large sample numbers in TCGA offer an excellent opportunity to address questions associated with tumo heterogeneity. Exploration of the data by cancer researchers and clinicians is imperative to unearth novel therapeutic/diagnostic biomarkers. Various computational tools have been developed to aid researchers in carrying out specific TCGA data analyses; however there is need for resources to facilitate the study of gene expression variations and survival associations across tumors. Here, we report UALCAN, an easy to use, interactive web-portal to perform to in-depth analyses of TCGA gene expression data. UALCAN uses TCGA level 3 RNA-seq and clinical data from 31 cancer types. The portal's user-friendly features allow to perform: 1) analyze relative expression of a query gene(s) across tumor and normal samples, as well as in various tumor sub-groups based on individual cancer stages, tumor grade, race, body weight or other clinicopathologic features, 2) estimate the effect of gene expression level and clinicopathologic features on patient survival; and 3) identify the top over- and under-expressed (up and down-regulated) genes in individual cancer types. This resource serves as a platform for in silico validation of target genes and for identifying tumor sub-group specific candidate biomarkers. Thus, UALCAN web-portal could be extremely helpful in accelerating cancer research. UALCAN is publicly available at http://ualcan.path.uab.edu.

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.

The epigenetic landscape of renal cancer

The majority of kidney cancers are associated with mutations in the von Hippel-Lindau gene and a small proportion are associated with infrequent mutations in other well characterized tumour-suppressor genes. In the past 15 years, efforts to uncover other key genes involved in renal cancer have identified many genes that are dysregulated or silenced via epigenetic mechanisms, mainly through methylation of promoter CpG islands or dysregulation of specific microRNAs. In addition, the advent of next-generation sequencing has led to the identification of several novel genes that are mutated in renal cancer, such as PBRM1, BAP1 and SETD2, which are all involved in histone modification and nucleosome and chromatin remodelling. In this Review, we discuss how altered DNA methylation, microRNA dysregulation and mutations in histone-modifying enzymes disrupt cellular pathways in renal cancers.

Renal Carcinogenesis, Tumor Heterogeneity, and Reactive Oxygen Species: Tactics Evolved

SIGNIFICANCE

The number of kidney cancers is growing 3-5% each year due to unknown etiologies. Intra- and inter-tumor mediators increase oxidative stress and drive tumor heterogeneity. Recent Advances: Technology advancement in state-of-the-art instrumentation and methodologies allows researchers to detect and characterize global landscaping modifications in genes, proteins, and pathophysiology patterns at the single-cell level.

CRITICAL ISSUES

We postulate that the sources of reactive oxygen species (ROS) and their activation within subcellular compartments will change over a timeline of tumor evolvement and contribute to tumor heterogeneity. Therefore, the complexity of intracellular changes within a tumor and ROS-induced tumor heterogeneity coupled to the advancement of detecting these events globally are limited at the level of data collection, organization, and interpretation using software algorithms and bioinformatics.

FUTURE DIRECTIONS

Integrative and collaborative research, combining the power of numbers with careful experimental design, protocol development, and data interpretation, will translate cancer biology and therapeutics to a heightened level or leave the abundant raw data as stagnant and underutilized. Antioxid. Redox Signal. 25, 685-701.

DNA methylation status defines clinicopathological parameters including survival for patients with clear cell renal cell carcinoma (ccRCC)

Epigenetic alterations in the methylome have been associated with tumor development and progression in renal cell carcinoma (RCC). In this study, 45 tumor samples, 12 tumor-free kidney cortex tissues, and 24 peripheral blood samples from patients with clear cell RCC (ccRCC) were analyzed by genome-wide promoter-directed methylation arrays and related to clinicopathological parameters. Unsupervised hierarchical clustering separated the tumors into two distinct methylation groups (clusters A and B), where cluster B had higher average methylation and increased number of hypermethylated CpG sites (CpGs). Furthermore, tumors in cluster B had, compared with cluster A, a larger tumor diameter (p = 0.033), a higher morphologic grade (p < 0.001), a higher tumor-node-metastasis (TNM) stage (p < 0.001), and a worse prognosis (p = 0.005). Higher TNM stage was correlated to an increase in average methylation level (p = 0.003) and number of hypermethylated CpGs (p = 0.003), whereas a number of hypomethylated CpGs were mainly unchanged. However, the predicted age of the tumors based on methylation profile did not correlate with TNM stage, morphological grade, or methylation cluster. Differently methylated (DM) genes (n = 840) in ccRCC samples compared with tumor-free kidney cortex samples were predominantly hypermethylated and a high proportion were identified as polycomb target genes. The DM genes were overrepresented by transcription factors, ligands, and receptors, indicating functional alterations of significance for ccRCC progression. To conclude, increased number of hypermethylated genes was associated with increased TNM stage of the tumors. DNA methylation classification of ccRCC tumor samples at diagnosis can serve as a clinically applicable prognostic marker in ccRCC.

CrossHub: a tool for multi-way analysis of The Cancer Genome Atlas (TCGA) in the context of gene expression regulation mechanisms

The contribution of different mechanisms to the regulation of gene expression varies for different tissues and tumors. Complementation of predicted mRNA–miRNA and gene–transcription factor (TF) relationships with the results of expression correlation analyses derived for specific tumor types outlines the interactions with functional impact in the current biomaterial. We developed CrossHub software, which enables two-way identification of most possible TF–gene interactions: on the basis of ENCODE ChIP-Seq binding evidence or Jaspar prediction and co-expression according to the data of The Cancer Genome Atlas (TCGA) project, the largest cancer omics resource. Similarly, CrossHub identifies mRNA–miRNA pairs with predicted or validated binding sites (TargetScan, mirSVR, PicTar, DIANA microT, miRTarBase) and strong negative expression correlations. We observed partial consistency between ChIP-Seq or miRNA target predictions and gene–TF/miRNA co-expression, demonstrating a link between these indicators. Additionally, CrossHub expression-methylation correlation analysis can be used to identify hypermethylated CpG sites or regions with the greatest potential impact on gene expression. Thus, CrossHub is capable of outlining molecular portraits of a specific gene and determining the three most common sources of expression regulation: promoter/enhancer methylation, miRNA interference and TF-mediated activation or repression. CrossHub generates formatted Excel workbooks with the detailed results. CrossHub is freely available at https://sourceforge.net/projects/crosshub/.

Imaging-genomic pipeline for identifying gene mutations using three-dimensional intra-tumor heterogeneity features

This paper presents an imaging-genomic pipeline to derive three-dimensional intra-tumor heterogeneity features from contrast-enhanced CT images and correlates them with gene mutation status. The pipeline has been demonstrated using CT scans of patients with clear cell renal cell carcinoma (ccRCC) from The Cancer Genome Atlas. About 15% of ccRCC cases reported have BRCA1-associated protein 1 (BAP1) gene alterations that are associated with high tumor grade and poor prognosis. We hypothesized that BAP1 mutation status can be detected using computationally derived image features. The molecular data pertaining to gene mutation status were obtained from the cBioPortal. Correlation of the image features with gene mutation status was assessed using the Mann-Whitney-Wilcoxon rank-sum test. We also used the random forests classifier in the Waikato Environment for Knowledge Analysis software to assess the predictive ability of the computationally derived image features to discriminate cases with BAP1 mutations for ccRCC. Receiver operating characteristics were obtained using a leave-one-out-cross-validation procedure. Our results show that our model can predict BAP1 mutation status with a high degree of sensitivity and specificity. This framework demonstrates a methodology for noninvasive disease biomarker detection from contrast-enhanced CT images.

Combined HSP90 and kinase inhibitor therapy: Insights from The Cancer Genome Atlas

The merging of knowledge from genomics, cellular signal transduction and molecular evolution is producing new paradigms of cancer analysis. Protein kinases have long been understood to initiate and promote malignant cell growth and targeting kinases to fight cancer has been a major strategy within the pharmaceutical industry for over two decades. Despite the initial success of kinase inhibitors (KIs), the ability of cancer to evolve resistance and reprogram oncogenic signaling networks has reduced the efficacy of kinase targeting. The molecular chaperone HSP90 physically supports global kinase function while also acting as an evolutionary capacitor. The Cancer Genome Atlas (TCGA) has compiled a trove of data indicating that a large percentage of tumors overexpress or possess mutant kinases that depend on the HSP90 molecular chaperone complex. Moreover, the overexpression or mutation of parallel activators of kinase activity (PAKA) increases the number of components that promote malignancy and indirectly associate with HSP90. Therefore, targeting HSP90 is predicted to complement kinase inhibitors by inhibiting oncogenic reprogramming and cancer evolution. Based on this hypothesis, consideration should be given by both the research and clinical communities towards combining kinase inhibitors and HSP90 inhibitors (H90Ins) in combating cancer. The purpose of this perspective is to reflect on the current understanding of HSP90 and kinase biology as well as promote the exploration of potential synergistic molecular therapy combinations through the utilization of The Cancer Genome Atlas.

Transmembrane 6 superfamily 1 (Tm6sf1) is a novel lysosomal transmembrane protein

The lysosome is a membrane-bound organelle involved in the turnover of various intracellular and extracellular macromolecules. These are degraded by acidic hydrolases in the lumen of lysosome. The lysosomal membrane is important not only in retaining the acidic hydrolases to protect cells against cytosolic proteolysis, but it also facilitates protein trafficking though organelle fusion. In this study, we report on a novel lysosomal membrane protein transmembrane 6 superfamily 1 (Tm6sf1). Expression of Tm6sf1-DsRed fusion proteins in HEK293A cells displayed punctate or ringlike vesicles, which colocalized with conventional lysosome markers including LAMP1/2, RAB7, and Rnf167. Using fluorescence time-lapse live cell imaging, we demonstrated the fusion of Tm6sf1 vesicles with lysosomes and the integration of Tm6sf1 into the lysosomal membrane. We also examined the expression of Tm6sf1 in mouse tissues and found immunopositive signals in major organs such as the cerebellum, kidney, and intestine. These data suggest that Tm6sf1 is a widely expressed lysosomal transmembrane protein and can be used as a novel marker of lysosome.