Downregulation of ATP1A1 promotes cancer development in renal cell carcinoma

The natural compound periplogenin suppresses the growth of prostate carcinoma cells by directly targeting ATP1A1

Natural compounds constitute a major resource for the development of medicines for multiple diseases. While many natural compounds show strong biological activity, the mechanisms that confer clinical benefits are often elusive and have been attributed to multiple pathways. Periplogenin (PPG), a natural compound isolated from Cortex periplocae, exhibits strong anti-tumor activities in several human cancer cell lines. However, its molecular mode of action remained unclear. In this study, we leveraged a forward genetic screening approach in DU145 prostate cancer cells to uncover the molecular target of PPG using chemical mutagenesis. Next generation sequencing revealed that a single amino acid substitution at amino acid 804 in ATP1A1 (ATPase Na + /K + Transporting Subunit Alpha 1) confers resistance to the cytotoxic activity of PPG. Mechanistically, ATP1A1 T804 forms a hydrogen bond with PPG which is abolished by the T804A substitution in ATP1A1, resulting in resistance to PPG treatment in vitro. Importantly, in vivo, PPG strongly suppressed tumor development in a DU145 xenograft model whereas DU145 xenograft tumors carrying a ATP1A1-T804A mutation were largely unaffected by the treatment. These findings demonstrate that PPG suppresses the growth of DU145 prostate cancer cells in vitro and in vivo by directly binding to ATP1A1 and highlight the power of our unbiased forward genetic screening approach to uncover direct drug target structures at single amino acid resolution.

Novel inhibitors targeting the PGK1 metabolic enzyme in glycolysis exhibit effective antitumor activity against kidney renal clear cell carcinoma in vitro and in vivo

Our previous research has revealed phosphoglycerate kinase 1 (PGK1) enhances tumorigenesis and sorafenib resistance of kidney renal clear cell carcinoma (KIRC) by regulating glycolysis, so that PGK1 is a promising drug target. Herein we performed structure-based virtual screening and series of anticancer pharmaceutical experiments in vitro and in vivo to identify novel small-molecule PGK1-targeted compounds. As results, the compounds CHR-6494 and Z57346765 were screened and confirmed to specifically bind to PGK1 and significantly reduced the metabolic enzyme activity of PGK1 in glycolysis, which inhibited KIRC cell proliferation in a dose-dependent manner. While CHR-6494 showed greater anti-KIRC efficacy and fewer side effects than Z57346765 on nude mouse xenograft model. Mechanistically, CHR-9464 impeded glycolysis by decreasing the metabolic enzyme activity of PGK1 and suppressed histone H3T3 phosphorylation to inhibit KIRC cell proliferation. Z57346765 induced expression changes of genes related to cell metabolism, DNA replication and cell cycle. Overall, we screened two novel PGK1 inhibitors, CHR-6494 and Z57346765, for the first time and discovered their potent anti-KIRC effects by suppressing PGK1 metabolic enzyme activity in glycolysis.

Comprehensive analysis of disulfidptosis-related genes: a prognosis model construction and tumor microenvironment characterization in clear cell renal cell carcinoma

BACKGROUND

Disulfidptosis, a form of cell death induced by abnormal intracellular accumulation of disulfides, is a newly recognized variety of cell death. Clear cell renal cell carcinoma (ccRCC) is a usual urological tumor that poses serious health risks. There are few studies of disulfidptosis-related genes (DRGs) in ccRCC so far.

METHODS

The expression, transcriptional variants, and prognostic role of DRGs were assessed. Based on DRGs, consensus unsupervised clustering analysis was performed to stratify ccRCC patients into various subtypes and constructed a DRG risk scoring model. Patients were stratified into high or low-risk groups by this model. We focused on assessing the discrepancy in prognosis, TME, chemotherapeutic susceptibility, and landscape of immune between the two risk groups. Finally, we validated the expression and explored the biological function of the risk scoring gene FLRT3 through in vitro experiments.

RESULTS

The different subtypes had significantly different gene expression, immune, and prognostic landscapes. In the two risk groups, the high-risk group had higher TME scores, more significant immune cell infiltration, and a higher probability of benefiting from immunotherapy, but had a worse prognosis. There were also remarkable differences in chemotherapeutic susceptibility between the two risk groups. In ccRCC cells, the expression of FLRT3 was shown to be lower and its overexpression caused a decrease in cell proliferation and metastatic capacity.

CONCLUSIONS

Starting from disulfidptosis, we established a new risk scoring model which can provide new ideas for doctors to forecast patient survival and determine clinical treatment plans.

Editing of HSF-1 and Na/K-ATPase α1 subunit by CRISPR/Cas9 reduces thermal tolerance of bovine skin fibroblasts to heat shock in vitro

A follow-up to our previous findings, the present study was planned to evaluate the role of Na/K-ATPase alpha1-subunit (ATP1A1) gene in heat shock tolerance. The primary fibroblast culture was established using ear pinna tissue samples of Sahiwal cattle (Bos indicus). The knockout cell lines of Na/K-ATP1A1 and HSF-1 (heat shock factor-1, as a positive control) genes were developed by CRISPR/Cas9 method and the gene-editing was confirmed by the genomic cleavage detection assay. The two knockout cell lines (ATP1A1 and HSF-1) and wild-type fibroblasts were exposed to heat shock at 42 °C in vitro and different cellular parameters viz., apoptosis, proliferation, mitochondrial membrane potential (ΔΨm), oxidative stress, along with expression pattern of heat-responsive genes were studied. The results showed that in vitro heat shock given to knockout fibroblast cells of both ATP1A1 and HSF-1 genes resulted in decreased cell viability, while increasing the apoptosis rate, membrane depolarization, and ROS levels. However, the overall impact was more in HSF-1 knockout cells as compared to ATP1A1 knockout cells. Taken together, these results indicated that the ATP1A1 gene plays a critical role as HSF-1 under heat stress and helps cells to cope with heat shock.

ReGeNNe: genetic pathway-based deep neural network using canonical correlation regularizer for disease prediction

MOTIVATION

Common human diseases result from the interplay of genes and their biologically associated pathways. Genetic pathway analyses provide more biological insight as compared to conventional gene-based analysis. In this article, we propose a framework combining genetic data into pathway structure and using an ensemble of convolutional neural networks (CNNs) along with a Canonical Correlation Regularizer layer for comprehensive prediction of disease risk. The novelty of our approach lies in our two-step framework: (i) utilizing the CNN's effectiveness to extract the complex gene associations within individual genetic pathways and (ii) fusing features from ensemble of CNNs through Canonical Correlation Regularization layer to incorporate the interactions between pathways which share common genes. During prediction, we also address the important issues of interpretability of neural network models, and identifying the pathways and genes playing an important role in prediction.

RESULTS

Implementation of our methodology into three real cancer genetic datasets for different prediction tasks validates our model's generalizability and robustness. Comparing with conventional models, our methodology provides consistently better performance with AUC improvement of 11% on predicting early/late-stage kidney cancer, 10% on predicting kidney versus liver cancer type and 7% on predicting survival status in ovarian cancer as compared to the next best conventional machine learning model. The robust performance of our deep learning algorithm indicates that disease prediction using neural networks in multiple functionally related genes across different pathways improves genetic data-based prediction and understanding molecular mechanisms of diseases.

AVAILABILITY AND IMPLEMENTATION

https://github.com/divya031090/ReGeNNe.

Na/K‑ATPase subunit α3 expression is associated with the efficacy of digitoxin treatment in pancreatic cancer cells

The alpha subunits (ATP1A1-3) of Na⁺/K⁺-ATPase binds digitoxin with varying affinity. The expression levels of these subunits dictate the anticancer effects of digitoxin. In the present study, three pancreatic cancer cell lines, AsPC-1, Panc-1 and CFPAC-1, were used to investigate the effects of digitoxin in relation to the expression of the subunits ATP1A1 and ATP1A3. Cell viability and intracellular calcium concentrations was measured in relation to the gene and protein expression of ATP1A1 and ATP1A3. Digitoxin was used to treat the cells at concentrations of 1-100 nM, and the intracellular calcium concentrations increased in a concentration-dependent manner in the Panc-1 and in the CFPAC-1 cells with treatment at 100 nM. In the AsPC-1 cells only the supraphysiological concentration of digitoxin (100 nM) resulted in a decrease in the number of viable cells (unviable cells increased to 22%), whereas it had no effect on intracellular calcium levels. The number of viable Panc-1 and CFPAC-1 cells decreased after digitoxin treatment at 25-100 nM (unviable Panc-1 cells increased to 33-59%; unviable CFPAC-1 cells increased to 22-56%). Digitoxin treatment also affected the transcriptional expression of the ATP1A1 and ATP1A3 subunits. In Panc-1 cells, ATP1A3 gene expression was negatively associated with the digitoxin concentration (25-100 nM). In the AsPC-1 and CFPAC-1 cells, the expression of the ATP1A1 gene increased in the cells treated with the 100 nM digitoxin concentration. The protein expression of ATP1A1 and ATP1A3 was not altered with digitoxin treatment. The basal protein expression of ATP1A1 was high in the AsPC-1 and CFPAC-1 cells, compared to the Panc-1 cells, in contrast to the basal expression of ATP1A3, which was higher in the Panc-1 cells, compared to the other pancreatic cancer cells used. On the whole, the present study demonstrates that the high expression of ATP1A3 renders pancreatic cancer cells more susceptible to digitoxin-induced cell death. The findings suggest that the expression of ATP1A3 may be used as a marker for tumor sensitivity to digitoxin treatment, where a high expression of ATP1A3 is favorable for the anticancer effects of digitoxin.

Single-Cell Transcriptomics Reveals Killing Mechanisms of Antitumor Cytotoxic CD4+ TCR-T Cells

T cell receptor-engineered T cells (TCR-Ts) have emerged as potent cancer immunotherapies. While most research focused on classical cytotoxic CD8⁺ T cells, the application of CD4⁺ T cells in adoptive T cell therapy has gained much interest recently. However, the cytotoxic mechanisms of CD4⁺ TCR-Ts have not been fully revealed. In this study, we obtained an MHC class I-restricted MART-1_27-35-specific TCR sequence based on the single-cell V(D)J sequencing technology, and constructed MART-1_27-35-specific CD4⁺ TCR-Ts and CD8⁺ TCR-Ts. The antitumor effects of CD4⁺ TCR-Ts were comparable to those of CD8⁺ TCR-Ts in vitro and in vivo. To delineate the killing mechanisms of cytotoxic CD4⁺ TCR-Ts, we performed single-cell RNA sequencing and found that classical granule-dependent and independent cytolytic pathways were commonly used in CD4⁺ and CD8⁺ TCR-Ts, while high expression of LTA and various costimulatory receptors were unique features for cytotoxic CD4⁺ TCR-Ts. Further signaling pathway analysis revealed that transcription factors Runx3 and Blimp1/Tbx21 were crucial for the development and killing function of cytotoxic CD4⁺ T cells. Taken together, we report the antitumor effects and multifaceted killing mechanisms of CD4⁺ TCR-Ts, and also indicate that MHC class I-restricted CD4⁺ TCR-Ts could serve as potential adoptive T cell therapies.

PGK1 contributes to tumorigenesis and sorafenib resistance of renal clear cell carcinoma via activating CXCR4/ERK signaling pathway and accelerating glycolysis

Phosphoglycerate kinase 1 (PGK1) has complicated and multiple functions in cancer occurrence, tumor progression and drug resistance. Sorafenib is the first-line treatment targeted drug for patients with kidney renal clear cell carcinoma (KIRC) as a tyrosine kinase inhibitor, but sorafenib resistance is extremely common to retard therapy efficiency. So far, it is unclear whether and how PGK1 is involved in the pathogenesis and sorafenib resistance of KIRC. Herein, the molecular mechanisms of PGK1-mediated KIRC progression and sorafenib resistance have been explored by comprehensively integrative studies using biochemical approaches, mass spectrometry (MS) identification, microarray assay, nude mouse xenograft model and bioinformatics analysis. We have confirmed PGK1 is specifically upregulated in KIRC based on the transcriptome data generated by our own gene chip experiment, proteomics identification and the bioinformatics analysis for five online transcriptome datasets, and PGK1 upregulation in tumor tissues and serum is indicative with poor prognosis of KIRC patients. In the KIRC tissues, a high expression of PGK1 is often accompanied with an increase of glycolysis-related enzymes and CXCR4. PGK1 exhibits pro-tumorigenic properties in vitro and in a xenograft tumor model by accelerating glycolysis and inducing CXCR4-mediated phosphorylation of AKT and ERK. Moreover, PGK1 promotes sorafenib resistance via increasing CXCR4-mediated ERK phosphorylation. In conclusion, PGK1-invovled metabolic reprogramming and activation of CXCR4/ERK signaling pathway contributes to tumor growth and sorafenib resistance of KIRC.

Quantitative ubiquitylomics reveals the ubiquitination regulation landscape in oral adenoid cystic carcinoma

Adenoid cystic carcinoma (ACC) is an extremely rare salivary gland tumor with a poor prognosis and needs attention on molecular mechanisms. Protein ubiquitination is an evolutionarily conserved post-translational modification (PTM) for substrates degradation and controls diverse cellular functions. The broad cellular function of ubiquitination network holds great promise to detect potential targets and identify respective receptors. Novel technologies are discovered for in-depth research and characterization of the precise and dynamic regulation of ubiquitylomics in multiple cellular processes during cancer initiation, progression and treatment. In the present study, 4D label-free quantitative techniques of ubiquitination proteomics were used and we identified a total of 4152 ubiquitination sites in 1993 proteins. We also performed a systematic bioinformatics analysis for differential modified proteins and peptides containing quantitative information through the comparation between oral ACC (OACC) tumor with adjacent normal tissues, as well as the identification of eight protein clusters with motif analysis. Our findings offered an important reference of potential biomarkers and effective therapeutic targets for ACC.

Integrated analysis of miRNA and mRNA transcriptomic reveals antler growth regulatory network

The growth of antler is driven by endochondral ossification in the growth center of the apical region. Antler grows faster than cancer tissues, but it can be stably regulated and regenerated periodically. To elucidate the molecular mechanisms of how antler grows rapidly without carcinogenesis, in this study, we used RNA-seq technology to evaluate the changes of miRNA and mRNA profiles in antler at four different developmental stages, including 15, 60, 90, and 110 days. We identified a total of 55004 unigenes and 246 miRNAs of which, 10182, 13258, 10740 differentially expressed (DE) unigenes and 35, 53, 27 DE miRNAs were identified in 60-day vs. 15-day, 90-day vs. 60-day, and 110-day vs. 90-day. GO and KEGG pathway analysis indicated that DE unigenes and DE miRNA were mainly associated with chondrogenesis, osteogenesis and inhibition of oncogenesis, that were closely related to antler growth. The interaction networks of mRNA-mRNA and miRNA-mRNA related to chondrogenesis, osteogenesis and inhibition of oncogenesis of antler were constructed. The results indicated that mRNAs (COL2A1, SOX9, WWP2, FGFR1, SPARC, LOX, etc.) and miRNAs (miR-145, miR-199a-3p, miR-140, miR-199a-5p, etc.) might have key roles in chondrogenesis and osteogenesis of antler. As well as mRNA (TP53, Tpm3 and ATP1A1, etc.) and miRNA (miR-106a, miR-145, miR-1260b and miR-2898, etc.) might play important roles in inhibiting the carcinogenesis of antler. In summary, we constructed the mRNA-mRNA and miRNA-mRNA regulatory networks related to chondrogenesis, osteogenesis and inhibition of oncogenesis of antler, and identified key candidate mRNAs and miRNAs among them. Further developments and validations may provide a reference for in-depth analysis of the molecular mechanism of antler growth without carcinogenesis.

Tumour blood flow for prediction of human prostate cancer aggressiveness: a study with Rubidium-82 PET, MRI and Na+/K+-ATPase-density

PURPOSE

Tumour blood flow (TBF) is a crucial determinant of cancer growth. Recently, we validated Rubidium-82 (82Rb) positron emission tomography (PET) for TBF measurement in prostate cancer (PCa) and found TBF and cancer aggressiveness positively correlated. The aims of the present study were to determine the ability of TBF for separating significant from insignificant PCa and to examine the relation to underlying Na+/K+-ATPase density, which is relevant as 82Rb is transported intracellularly via the Na+/K+-ATPase.

METHODS

One hundred and two patients were included for pelvic 82Rb PET scan prior to magnetic resonance imaging (MRI)-guided prostate biopsy. Findings constituted 100 PCa lesions (86 patients) and 25 benign lesions (16 patients). Tumours were defined on MRI and transferred to 82Rb PET for TBF measurement. Immunohistochemical Na+/K+-ATPase staining was subsequently performed on biopsies.

RESULTS

TBF was the superior predictor (rho = 0.68, p < 0.0001, inflammatory lesions excluded) of MRI-guided biopsy grade group (GG) over lowest apparent diffusion coefficient (ADC) value (rho = -0.23, p = 0.01), independent of ADC value and tumour volume (p < 0.0001). PET could separate GG-2-5 from GG-1 and benign lesions with an area under the curve (AUC), sensitivity, and specificity of 0.79, 96%, and 59%, respectively. For separating GG-3-5 from GG-1-2 and benign lesions the AUC, sensitivity, and specificity were 0.82, 95%, and 63%, respectively. Na+/K+-ATPase density per PCa cell profile was 38% lower compared with that of the benign prostate cell profiles. Neither cell density nor Na+/K+-ATPase density determined tumour 82Rb uptake.

CONCLUSION

TBF is an independent predictor of PCa aggressiveness and deserves more attention, as it may be valuable in separating clinically significant from insignificant PCa.

A single-cell transcriptomic atlas characterizes ageing tissues in the mouse

Ageing is characterized by a progressive loss of physiological integrity, leading to impaired function and increased vulnerability to death1. Despite rapid advances over recent years, many of the molecular and cellular processes that underlie the progressive loss of healthy physiology are poorly understood2. To gain a better insight into these processes, here we generate a single-cell transcriptomic atlas across the lifespan of Mus musculus that includes data from 23 tissues and organs. We found cell-specific changes occurring across multiple cell types and organs, as well as age-related changes in the cellular composition of different organs. Using single-cell transcriptomic data, we assessed cell-type-specific manifestations of different hallmarks of ageing-such as senescence3, genomic instability4 and changes in the immune system2. This transcriptomic atlas-which we denote Tabula Muris Senis, or 'Mouse Ageing Cell Atlas'-provides molecular information about how the most important hallmarks of ageing are reflected in a broad range of tissues and cell types.

Prognostic significance of proteomics and multi-omics studies in renal carcinoma

INTRODUCTION

Renal carcinoma, and in particular its most common variant, the clear cell subtype, is often diagnosed incidentally through abdominal imaging and frequently, the tumor is discovered at an early stage. However, 20% to 40% of patients undergoing nephrectomy for clinically localized renal cancer, even after accurate histological and clinical classification, will develop metastasis or recurrence, justifying the associated mortality rate. Therefore, even if renal carcinoma is not among the most frequent nor deadly cancers, a better prognostication is needed.

AREAS COVERED

Recently proteomics or other omics combinations have been applied to both cancer tissues, on the neoplasia itself and surrounding microenvironment, cultured cells, and biological fluids (so-called liquid biopsy) generating a list of prognostic molecular tools that will be reviewed in the present paper.

EXPERT OPINION

Although promising, none of the approaches listed above has been yet translated in clinics. This is likely due to the peculiar genetic and phenotypic heterogeneity of this cancer, which makes nearly each tumor different from all the others. Attempts to overcome this issue will be also revised. In particular, we will discuss how the application of omics-integrated approaches could provide the determinants of response to the different targeted drugs.

In Silico Analysis Identifies Differently Expressed lncRNAs as Novel Biomarkers for the Prognosis of Thyroid Cancer

Background

Thyroid cancer (TC) is one of the most common type of endocrine tumors. Long noncoding RNAs had been demonstrated to play key roles in TC. Material and Methods. The lncRNA expression data were downloaded from Co-lncRNA database. The raw data was normalized using the limma package in R software version 3.3.0. The differentially expressed mRNA and lncRNAs were identified by the linear models for the microarray analysis (Limma) method. The DEGs were obtained with thresholds of ∣logFC∣ > 1.5 and P < 0.001. The hierarchical cluster analysis of differentially expressed mRNAs and lncRNAs was performed using CLUSTER 3.0, and the hierarchical clustering heat map was visualized by Tree View.

Results

In the present study, we identified 6 upregulated and 85 downregulated lncRNAs in TC samples. Moreover, we for the first time identified 16 downregulated lncRNAs was correlated to longer disease-free survival time in patients with TC, including ATP1A1-AS1, CATIP-AS1, FAM13A-AS1, LINC00641, LINC00924, MIR22HG, NDUFA6-AS1, RP11-175K6.1, RP11-727A23.5, RP11-774O3.3, RP13-895J2.2, SDCBP2-AS1, SLC26A4-AS1, SNHG15, SRP14-AS1, and ZNF674-AS1.

Conclusions

Bioinformatics analysis revealed these lncRNAs were involved in regulating the RNA metabolic process, cell migration, organelle assembly, tRNA modification, and hormone levels. This study will provide useful information to explore the potential candidate biomarkers for diagnosis, prognosis, and drug targets for TC.

A Humanized Yeast Phenomic Model of Deoxycytidine Kinase to Predict Genetic Buffering of Nucleoside Analog Cytotoxicity

Knowledge about synthetic lethality can be applied to enhance the efficacy of anticancer therapies in individual patients harboring genetic alterations in their cancer that specifically render it vulnerable. We investigated the potential for high-resolution phenomic analysis in yeast to predict such genetic vulnerabilities by systematic, comprehensive, and quantitative assessment of drug–gene interaction for gemcitabine and cytarabine, substrates of deoxycytidine kinase that have similar molecular structures yet distinct antitumor efficacy. Human deoxycytidine kinase (dCK) was conditionally expressed in the Saccharomyces cerevisiae genomic library of knockout and knockdown (YKO/KD) strains, to globally and quantitatively characterize differential drug–gene interaction for gemcitabine and cytarabine. Pathway enrichment analysis revealed that autophagy, histone modification, chromatin remodeling, and apoptosis-related processes influence gemcitabine specifically, while drug–gene interaction specific to cytarabine was less enriched in gene ontology. Processes having influence over both drugs were DNA repair and integrity checkpoints and vesicle transport and fusion. Non-gene ontology (GO)-enriched genes were also informative. Yeast phenomic and cancer cell line pharmacogenomics data were integrated to identify yeast–human homologs with correlated differential gene expression and drug efficacy, thus providing a unique resource to predict whether differential gene expression observed in cancer genetic profiles are causal in tumor-specific responses to cytotoxic agents.

SAE1 promotes human glioma progression through activating AKT SUMOylation-mediated signaling pathways

BACKGROUND

The SUMO-activating enzyme SAE1 is indispensable for protein SUMOylation. A dysregulation of SAE1 expression involves in progression of several human cancers. However, its biological roles of SAE1 in glioma are unclear by now.

METHODS

The differential proteome between human glioma tissues and para-cancerous brain tissues were identified by LC-MS/MS. SAE1 expression was further assessed by immunohistochemistry. The patient overall survival versus SAE1 expression level was evaluated by Kaplan-Meier method. The glioma cell growth and migration were evaluated under SAE1 overexpression or inhibition by the CCK8, transwell assay and wound healing analysis. The SUMO1 modified target proteins were enriched from total cellular or tissue proteins by incubation with the anti-SUMO1 antibody on protein-A beads overnight, then the SUMOylated proteins were detected by Western blot. Cell apoptosis and cell cycle were analyzed by flow cytometry. The nude mouse xenograft was determined glioma growth and tumorigenicity in vivo.

RESULTS

SAE1 is identified to increase in glioma tissues by a quantitative proteomic dissection, and SAE1 upregulation indicates a high level of tumor malignancy grade and a poor overall survival for glioma patients. SAE1 overexpression induces an increase of the SUMOylation and Ser473 phosphorylation of AKT, which promotes glioma cell growth in vitro and in nude mouse tumor model. On the contrary, SAE1 silence induces an obvious suppression of the SUMOylation and Ser473 phosphorylation of Akt, which inhibits glioma cell proliferation and the tumor xenograft growth through inducing cell cycle arrest at G2 phase and cell apoptosis driven by serial biochemical molecular events.

CONCLUSION

SAE1 promotes glioma cancer progression via enhancing Akt SUMOylation-mediated signaling pathway, which indicates targeting SUMOylation is a promising therapeutic strategy for human glioma.

Integrative Epigenetic and Gene Expression Analysis of Renal Tumor Progression to Metastasis

The Cancer Genome Atlas (TCGA) and other large-scale genomic data pipelines have been integral to the current understanding of the molecular events underlying renal cell carcinoma (RCC). These data networks have focused mostly on primary RCC, which often demonstrates indolent behavior. However, metastatic disease is the major cause of mortality associated with RCC and data sets examining metastatic tumors are sparse. Therefore, a more comprehensive analysis of gene expression and DNA methylome profiling of metastatic RCC in addition to primary RCC and normal kidney was performed. Integrative analysis of the methylome and transcriptome identified over 30 RCC-specific genes whose mRNA expression inversely correlated with promoter methylation, including several known targets of hypoxia inducible factors. Notably, genes encoding several metabolism-related proteins were identified as differentially regulated via methylation including hexokinase 2, aldolase C, stearoyl-CoA desaturase, and estrogen-related receptor-γ (ESRRG), which has a known role in the regulation of nuclear-encoded mitochondrial metabolism genes. Several gene expression changes could portend prognosis in the TCGA cohort. Mechanistically, ESRRG loss occurs via DNA methylation and histone repressive silencing mediated by the polycomb repressor complex 2. Restoration of ESRRG in RCC lines suppresses migratory and invasive phenotypes independently of its canonical role in mitochondrial metabolism. IMPLICATIONS: Collectively, these data provide significant insight into the biology of aggressive RCC and demonstrate a novel role for DNA methylation in the promotion of HIF signaling and invasive phenotypes in renal cancer.

SILAC-based quantitative MS approach for real-time recording protein-mediated cell-cell interactions

In tumor microenvironment, interactions among multiple cell types are critical for cancer progression. To understand the molecular mechanisms of these complex interplays, the secreted protein analysis between malignant cancer cells and the surrounding nonmalignant stroma is a good viewpoint to investigate cell-cell interactions. Here, we developed two stable isotope labeling of amino acids in cell culture (SILAC)-based mass spectrometry (MS)/MS approaches termed spike-in SILAC and triple-SILAC to quantify changes of protein secretion level in a cell co-cultured system. Within the co-culture system of CT26 and Ana-1 cells, the spike-in SILAC and triple-SILAC MS approaches are sensitive to quantitatively measure protein secretion changes. Three representative quantified proteins (Galectin-1, Cathepsin L1 and Thrombospondin-1) by two SILAC-based MS methods were further validated by Western blotting, and the coming result matched well with SILACs’. We further applied these two SILACs to human cell lines, NCM460 and HT29 co-culture system, for evaluating the feasibility, which confirmed the spike-in and triple SILAC were capable of monitoring the changed secreted proteins of human cell lines. Considering these two strategies in time consuming, sample complexity and proteome coverage, the triple-SILAC way shows more efficiency and economy for real-time recording secreted protein levels in tumor microenvironment.