Downregulation of CLDN7 due to promoter hypermethylation is associated with human clear cell renal cell carcinoma progression and poor prognosis

Identification and expression of prognostic-related genes in kidney renal clear cell carcinoma and their possible regulatory mechanisms

Background

Many factors affect the prognosis of kidney renal clear cell carcinoma (KIRC). Early diagnosis can significantly improve the prognosis of KIRC patients. Therefore, a method needs to be developed to diagnose KIRC early, predict patient prognosis, and improve personalized treatments. The objective of this study is to utilize bioinformatics tools and public database resources to identify differentially expressed genes (DEGs) between renal cancer tissues and adjacent normal tissues, and to further screen for prognostic-related genes (PRGs) of KIRC.

Methods

KIRC was studied using R language and FunRich software and several databases, including the Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), the University of Alabama at Birmingham cancer data analysis Portal (UALCAN), and Tumor Immune Estimation Resource (TIMER) databases. Moreover, quantitative real-time polymerase chain reaction (qRT-PCR) was used to validate the expression of multiple genes in KIRC and adjacent normal tissues.

Results

There were substantial differences in immune cell infiltration between the KIRC and adjacent normal tissues in the GSE40435 and GSE46699 datasets. In addition, we screened multiple PRGs of KIRC by combining the GEO and TCGA data. The UALCAN database verified that some representative PRGs were differently expressed depending on the lymph node metastasis status, grade, and stage of KIRC. The qRT-PCR results confirmed the expression of the PRGs in KIRC and adjacent normal tissues. Through the GO and KEGG analyses, interaction analysis, and TIMER database, we found that the prognosis of KIRC was closely related to immune microenvironment and vascular endothelial growth factor (VEGF)/VEGF receptor (VEGFR) signaling.

Conclusions

Our findings could contribute to the prognosis prediction of KIRC, the selection of personalized treatments, and the early diagnosis of KIRC.

Comprehensive analysis of a tryptophan metabolism-related model in the prognostic prediction and immune status for clear cell renal carcinoma

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is characterized as one of the most common types of urological cancer with high degrees of malignancy and mortality. Due to the limited effectiveness of existing traditional therapeutic methods and poor prognosis, the treatment and therapy of advanced ccRCC patients remain challenging. Tryptophan metabolism has been widely investigated because it significantly participates in the malignant traits of multiple cancers. The functions and prognostic values of tryptophan metabolism-related genes (TMR) in ccRCC remain virtually obscure.

METHODS

We employed the expression levels of 40 TMR genes to identify the subtypes of ccRCC and explored the clinical characteristics, prognosis, immune features, and immunotherapy response in the subtypes. Then, a model was constructed for the prediction of prognosis based on the differentially expressed genes (DEGs) in the subtypes from the TCGA database and verified using the ICGC database. The prediction performance of this model was confirmed by the receiver operating characteristic (ROC) curves. The relationship of Risk Score with the infiltration of distinct tumor microenvironment cells, the expression profiles of immune checkpoint genes, and the treatment benefits of immunotherapy and chemotherapy drugs were also investigated.

RESULTS

The two subtypes revealed dramatic differences in terms of clinical characteristics, prognosis, immune features, and immunotherapy response. The constructed 6-gene-based model showed that the high Risk Score was significantly connected to poor overall survival (OS) and advanced tumor stages. Furthermore, increased expression of CYP1B1, KMO, and TDO2 was observed in ccRCC tissues at the translation levels, and an unfavorable prognosis for these patients was also found.

CONCLUSION

We identified 2 molecular subtypes of ccRCC based on the expression of TMR genes and constructed a prognosis-related model that may be used as a powerful tool to guide the prediction of ccRCC prognosis and personalized therapy. In addition, CYP1B1, KMO, and TDO2 can be regarded as the risk prognostic genes for ccRCC.

Claudins in genitourinary tract neoplasms: mechanisms, prognosis, and therapeutic prospects

Genitourinary (GU) cancers are among the most prevalent neoplasms in the world, with bladder cancers constituting 3% of global cancer diagnoses. However, several pathogenetic mechanisms remain controversial and unclear. Claudins, for example, have been shown to play a significant role in several cancers of the human body. Their role in GU cancers has not been extensively studied. Aberrant expression of claudins -1, -2, -3, -4, -7, and -11 has been expressed in urothelial cell carcinomas. In prostate cancers, altered levels of claudins -1, -2, -3, -4, and -5 have been reported. Furthermore, the levels of claudins -1, -2, -3, -4, -6, -7, -8, and -10 have been studied in renal cell carcinomas. Specifically, claudins -7 and -8 have proven especially useful in differentiating between chromophobe renal cell carcinomas and oncocytomas. Several of these claudins also correlate with clinicopathologic parameters and prognosis in GU cancers. Although mechanisms underpinning aberrant expression of claudins in GU cancers are unclear, epigenetic changes, tumor necrosis factor-ɑ, and the p63 protein have been implicated. Claudins also provide therapeutic value through tailored immunotherapy via molecular subtyping and providing therapeutic targets, which have shown positive outcomes in preclinical studies. In this review, we aim to summarize the literature describing aberrant expression of claudins in urothelial, prostatic, and renal cell carcinomas. Then, we describe the mechanisms underlying these changes and the therapeutic value of claudins. Understanding the scope of claudins in GU cancers paves the way for several diagnostic, prognostic, and therapeutic innovations.

Web-based nomogram and risk stratification system constructed for predicting the overall survival of older adults with primary kidney cancer after surgical resection

BACKGROUND

Kidney cancer (KC) is one of the most common malignant tumors in adults which particularly affects the survival of elderly patients. We aimed to construct a nomogram to predict overall survival (OS) in elderly KC patients after surgery.

METHODS

Information on all primary KC patients aged more than 65 years and treated with surgery between 2010 and 2015 was downloaded from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox regression analysis was used to identify the independent prognostic factors. Consistency index (C-index), receiver operating characteristic curve (ROC), the area under curve (AUC), and calibration curve were used to assess the accuracy and validity of the nomogram. Comparison of the clinical benefits of nomogram and the TNM staging system is done by decision curve analysis (DCA) and time-dependent ROC.

RESULTS

A total of 15,989 elderly KC patients undergoing surgery were included. All patients were randomly divided into training set (N = 11,193, 70%) and validation set (N = 4796, 30%). The nomogram produced C-indexes of 0.771 (95% CI 0.751-0.791) and 0.792 (95% CI 0.763-0.821) in the training and validation sets, respectively, indicating that the nomogram has excellent predictive accuracy. The ROC, AUC, and calibration curves also showed the same excellent results. In addition, DCA and time-dependent ROC showed that the nomogram outperformed the TNM staging system with better net clinical benefits and predictive efficacy.

CONCLUSIONS

Independent influencing factors for postoperative OS in elderly KC patients were sex, age, histological type, tumor size, grade, surgery, marriage, radiotherapy, and T-, N-, and M-stage. The web-based nomogram and risk stratification system could assist surgeons and patients in clinical decision-making.

DNA methylation-based subtypes of acute myeloid leukemia with distinct prognosis and clinical features

Acute myeloid leukemia (AML) is a malignancy of the stem cell precursors of the myeloid lineage. DNA methylation is an important DNA modification that regulates gene expression. Investigating AML heterogeneity based on DNA methylation could be clinically informative for improving clinical diagnosis and prognosis. The AML subtypes based on DNA methylation were identified by unsupervised consensus clustering. The association of these subtypes with gene mutation, copy number variations, immune infiltration and clinical features were further explored. Finally, univariate, LASSO and multivariate cox regression analyses were used to identify prognosis-associated genes and construct risk model for AML patients. In addition, we validated this model by using other datasets and explored the involved biological functions and pathways of its related genes. Three CpG island methylator phenotypes (CIMP-H, CIMP-M and CIMP-L) were identified using the 91 differential CpG sites. Overall survival, morphology, macrophages M0 and monocytes were distinct from each other. The most frequently mutated gene in CIMP-L was DNMT3A while which in CIMP-M that was RUNX1. In addition, the TIDE scores, used to predict the response to immune checkpoint inhibitors, were significantly different among CIMPs. The CIMP-associated prognosis risk model (CPM) using 32 key genes had convinced accuracy of prediction to forecast 0.5-year, 1-year, 3-year and 5-year survival rates. Moreover, the risk score-related genes were significantly enriched in pattern specification process, regionalization, embryonic organ morphogenesis and other critical cancer-related biological functions. We systematically and comprehensively analyzed the DNA methylation in AML. The risk model we constructed is an independent predictor of overall survival in AML and could be used as prognostic factor for AML treatment.

OCLN as a novel biomarker for prognosis and immune infiltrates in kidney renal clear cell carcinoma: an integrative computational and experimental characterization

Background

Occludin (OCLN) is an important tight junction protein and has been reported to be abnormally expressed in the development of malignant tumors. However, its biomarker and carcinogenic roles in kidney renal clear cell carcinoma (KIRC) are less investigated.

Methods

The Cancer Genome Atlas database and Human Protein Atlas database were used to analyze the expression of OCLN in KIRC. UALCAN database and methylation-specific PCR assay were used to evaluate the methylation level of OCLN in KIRC. Univariate and multivariate Cox regression analyses were performed to model the prognostic significance of OCLN in KIRC patient cohorts. The correlation between OCLN expression and the immune cell infiltration, immune-related function and immune checkpoints were explored. Finally, EdU, scratch assay and transwell experiments were conducted to validate the role of OCLN in KIRC development.

Results

The expression of OCLN was significantly downregulated in KIRC, compared with normal renal tissues (p<0.001). Patients with low OCLN expression showed a worse prognosis and poorer clinicopathological characteristics. Functional enrichment analysis revealed that OCLN was mainly involved in biological processes such as immune response, immunoglobulin complex circulating and cytokine and chemokine receptor to mediate KIRC development. Immune-related analysis indicated that OCLN could potentially serve as a candidate target for KIRC immunotherapy. OCLN overexpression inhibited proliferation, migration and invasion of KIRC cells in vitro.

Conclusion

OCLN was validated as a candidate prognostic biomarker and therapeutic target of KIRC based both on computational and experimental approaches. More in vivo experiments will be conducted to decode its molecular mechanism in KIRC carcinogenesis in the future work.

Claudin expression in pulmonary adenoid cystic carcinoma and mucoepidermoid carcinoma

Background: Although the expression of tight junction protein claudins (CLDNs) is well known in common histological subtypes of lung cancer, it has not been investigated in rare lung cancers. The aim of our study was to examine the expression of different CLDNs in pulmonary salivary gland tumors. Methods: 35 rare lung cancers including pathologically confirmed 12 adenoid cystic carcinomas (ACCs) and 23 mucoepidermoid carcinomas (MECs) were collected retrospectively. Immunohistochemical (IHC) staining was performed on formalin fixed paraffin embedded (FFPE) tumor tissues, and CLDN1, -2, -3, -4, -5, -7, and -18 protein expressions were analyzed. The levels of immunopositivity were determined with H-score. Certain pathological characteristics of ACC and MEC samples (tumor grade, presence of necrosis, presence of blood vessel infiltration, and degree of lymphoid infiltration) were also analyzed. Results: CLDN overexpression was observed in both tumor types, especially in CLDN2, -7, and -18 IHC. Markedly different patterns of CLDN expression were found for ACC and MEC tumors, especially for CLDN1, -2, -4, and -7, although none of these trends remained significant after correction for multiple testing. Positive correlations between expressions of CLDN2 and -5, CLDN3 and -4, and CLDN5 and -18 were also demonstrated. Tumors of never-smokers presented lower levels of CLDN18 than tumors of current smokers (p-value: 0.003). Conclusion: This is the first study to comprehensively describe the expression of different CLDNs in lung ACC and MEC. Overexpression of certain CLDNs may pave the way for targeted anti-claudin therapy in these rare histological subtypes of lung cancer.

I kappa B kinase interacting protein as a promising biomarker in pan-cancer: A multi-omics analysis

Background: Human chromosome 12 contains I kappa B kinase interacting protein (IKBIP) is also commonly known as IKIP. The involvement of IKBIP in the growth of tumors has only been discussed in a small number of publications.

Purpose: To explore the role that IKBIP plays in the development of a wide variety of neoplasms, as well as the tumor immunological microenvironment.

Methods: UALCAN, HPA, Genotype Tissue Expression, Cancer Genome Maps, and other datasets were used to analyze IKBIP expression. We thoroughly investigated the predictive importance of IKBIP in pan-cancer, clinical traits, and genetic anomalies. We studied whether there is a link between IKBIP and immune-related genes, microsatellite instability (MSI), and the incidence of tumor mutational burden (TMB). The link between immune cell infiltration and IKBIP expression was examined using data on immune cell infiltration from ImmuCellAI, TIMER2, and earlier studies. Finally, gene set enrichment analysis (GSEA) was performed to determine the signaling pathways associated with IKBIP.

Results: IKBIP is highly expressed in most cancers and is negatively associated with the prognosis of several major cancer types. Furthermore, IKBIP expression was linked to TMB in 13 cancers and MSI in seven cancers. Additionally, IKBIP is associated with numerous immunological and cancer-promoting pathways. Simultaneously, various cancer types have unique tumor-infiltrating immune cell profiles.

Conclusion: IKBIP has the potential to act as a pan-cancer oncogene and is crucial for both carcinogenesis and cancer immunity. Elevated IKBIP expression implies an immunosuppressive environment and may be used as a prognostic biomarker and therapeutic target.

The role and mechanism of claudins in cancer

Claudins are a tetraspan membrane protein multigene family that plays a structural and functional role in constructing tight junctions. Claudins perform crucial roles in maintaining cell polarity in epithelial and endothelial cell sheets and controlling paracellular permeability. In the last two decades, increasing evidence indicates that claudin proteins play a major role in controlling paracellular permeability and signaling inside cells. Several types of claudins are dysregulated in various cancers. Depending on where the tumor originated, claudin overexpression or underexpression has been shown to regulate cell proliferation, cell growth, metabolism, metastasis and cell stemness. Epithelial-to-mesenchymal transition is one of the most important functions of claudin proteins in disease progression. However, the exact molecular mechanisms and signaling pathways that explain why claudin proteins are so important to tumorigenesis and progression have not been determined. In addition, claudins are currently being investigated as possible diagnostic and treatment targets. Here, we discuss how claudin-related signaling pathways affect tumorigenesis, tumor progression, and treatment sensitivity.

Identification of a claudin-low subtype in clear cell renal cell carcinoma with implications for the evaluation of clinical outcomes and treatment efficacy

Background

In bladder and breast cancer, the claudin-low subtype is widely identified, revealing a distinct tumor microenvironment (TME) and immunological feature. Although we have previously identified individual claudin members as prognostic biomarkers in clear cell renal cell carcinoma (ccRCC), the existence of an intrinsic claudin-low subtype and its interplay with TME and clinical outcomes remains unclear.

Methods

Transcriptomic and clinical data from The Cancer Genome Atlas (TCGA)- kidney clear cell carcinoma (KIRC) cohort and E-MTAB-1980 were derived as the training and validation cohorts, respectively. In addition, GSE40435, GSE53757, International Cancer Genome Consortium (ICGC) datasets, and RNA-sequencing data from local ccRCC patients were utilized as validation cohorts for claudin clustering based on silhouette scores. Using weighted correlation network analysis (WGCNA) and multiple machine learning algorithms, including least absolute shrinkage and selection operator (LASSO), CoxBoost, and random forest, we constructed a claudin-TME related (CTR) risk signature. Furthermore, the CTR associated genomic characteristics, immunity, and treatment sensitivity were evaluated.

Results

A claudin-low phenotype was identified and associated with an inferior survival and distinct TME and cancer immunity characteristics. Based on its interaction with TME, a risk signature was developed with robust prognostic prediction accuracy. Moreover, we found its association with a claudin-low, stem-like phenotype and advanced clinicopathological features. Intriguingly, it was also effective in kidney chromophobe and renal papillary cell carcinoma. The high CTR group exhibited genomic characteristics similar to those of claudin-low phenotype, including increased chromosomal instability (such as deletions at 9p) and risk genomic alterations (especially BAP1 and SETD2). In addition, a higher abundance of CD8 T cells and overexpression of immune checkpoints, such as LAG3, CTLA4 and PDCD1, were identified in the high CTR group. Notably, ccRCC patients with high CTR were potentially more sensitive to immune checkpoint inhibitors; their counterparts could have more clinical benefits when treated with antiangiogenic drugs, mTOR, or HIF inhibitors.

Conclusion

We comprehensively evaluated the expression features of claudin genes and identified a claudin-low phenotype in ccRCC. In addition, its related signature could robustly predict the prognosis and provide guide for personalizing management strategies.

Serum albumin to globulin ratio prior to treatment as a potential non-invasive prognostic indicator for urological cancers

Background

Numerous clinical studies have reported an association between the pretreatment albumin to globulin ratio (AGR) and survival outcomes of urological cancers. However, these conclusions remain controversial. Therefore, we performed a meta-analysis to explore the prognostic value of the AGR in urinary system tumors.

Methods

We retrieved eligible studies published up to June 2022 through a comprehensive search of multiple databases. Pooled hazard ratios (HRs) with 95% confidence intervals (CI) for overall survival (OS), cancer-specific survival (CSS), recurrence-free survival (RFS), progression-free survival (PFS), and biochemical recurrence-free survival (BRFS) were used to evaluated the predictive effect of the AGR before treatment in urinary system tumors. Heterogeneity test, random-effects models, fixed-effects models and sensitivity tests were used for analyses.

Results

A total of 21 studies with 18,269 patients were enrolled in our meta-analysis. We found that patients with urinary system cancer with low AGR prior to treatment had poor OS [HR = 1.93, 95% CI (1.56–2.39), p < 0.001], CSS [HR = 2.22, 95% CI (1.67–2.96), p < 0.001], RFS [HR = 1.69, 95% CI (1.29–2.22), p < 0.001], and PFS [HR = 1.29, 95% CI (0.54–3.07), p < 0.001]. For prostate cancer (PCa), a low pretreatment AGR was associated with poor BRFS [HR = 1.46, 95% CI (1.28–1.67), p < 0.001]. Also, a subgroup analysis, stratified by ethnicity, cancer type, cutoff value, sample size and publication year, was conducted. The results showed that worse OS and CSS were significantly associated with these factors.

Conclusion

Our meta-analysis revealed that the AGR before treatment could be used as a non-invasive predictive biomarker to evaluate the prognosis of urological cancer patients in clinical practice.

Kidney Cancer Prediction Empowered with Blockchain Security Using Transfer Learning

Kidney cancer is a very dangerous and lethal cancerous disease caused by kidney tumors or by genetic renal disease, and very few patients survive because there is no method for early prediction of kidney cancer. Early prediction of kidney cancer helps doctors start proper therapy and treatment for the patients, preventing kidney tumors and renal transplantation. With the adaptation of artificial intelligence, automated tools empowered with different deep learning and machine learning algorithms can predict cancers. In this study, the proposed model used the Internet of Medical Things (IoMT)-based transfer learning technique with different deep learning algorithms to predict kidney cancer in its early stages, and for the patient's data security, the proposed model incorporates blockchain technology-based private clouds and transfer-learning trained models. To predict kidney cancer, the proposed model used biopsies of cancerous kidneys consisting of three classes. The proposed model achieved the highest training accuracy and prediction accuracy of 99.8% and 99.20%, respectively, empowered with data augmentation and without augmentation, and the proposed model achieved 93.75% prediction accuracy during validation. Transfer learning provides a promising framework with the combination of IoMT technologies and blockchain technology layers to enhance the diagnosing capabilities of kidney cancer.

Analyses of the expression and prognosis of ILDR1 in human gastric cancer

The worldwide mortality rate of gastric cancer worldwide remains high. Immunoglobulin-like domain containing receptor 1 (ILDR1) belongs to an evolutionarily conserved protein family, and little is known about this gene in gastric cancer. In this paper, we analyzed the expression of ILDR1 and its relationship with clinical outcomes in gastric cancer using publicly available databases. ONCOMINE, GEPIA2, UALCAN, Kaplan–Meier Plotter, cBioPortal, GeneMANIA and LinkedOmics databases were used to analyze the expression, prognostic values, mutations and functional networks of ILDR1 in gastric cancer. We observed that ILDR1 was overexpressed in gastric cancer than in normal tissues. ILDR1 expression was significantly higher in patients with gastric cancer than in normal controls during subgroup analysis based on cancer stage, patient’s race, sex, age, tumor grade, H. pylori infection, histological subtype, and nodal metastasis status. Survival analysis showed that upregulation of ILDR1 expression was significantly associated with poor prognosis. Genomic alterations in ILDR1 were analyzed using cBioPortal, protein–protein interaction (PPI) networks were constructed using GeneMANIA and the co-expressed genes, gene ontology, and pathways of ILDR1 were determined using the LinkedOmics web tool. ILDR1 showed significant differences in expression between gastric cancer and normal tissues and, thus, may be a promising prognostic biomarker for gastric cancer.

An epithelial-mesenchymal plasticity signature identifies two novel LncRNAs with the opposite regulation

The epithelial to mesenchymal transition (EMT) is crucial for cancer progression and chemoresistance. EMT is a dynamic process with multiple phases that change cell migration and invasion activity. We used pan-cancer expression data to find 14-LncRNAs that had a high correlation with the EMT markers VIM, CDH1, FN1, SNAI1, and SNAI2. The expression of 14 EMT-associated LncRNA, which also showed high cancer specificity, was used to calculate the pan-cancer EMT score. The EMT score was then applied to the 32 cancer types to classify them as epithelial, epithelial-mesenchymal, mesenchymal-epithelial, or mesenchymal tumors. We discovered that the EMT score is a poor prognostic predictor and that as tumor mesenchymal nature increased, patient survival decreased. We also showed that the cell of origin did not influence the EMT nature of tumors. Pathway analysis employing protein expression data revealed that the PI3K pathway is the most crucial in determining the EMTness of tumors. Further, we divided CCLE-cell lines into EMT classes and discovered that mesenchymal cells, which exhibited higher PI3K pathway activation, were more sensitive to PI3K inhibitors than epithelial cells. We identified Linc01615 as a mesenchymal LncRNA whose expression significantly correlated with survival in several cancer types. We showed that Linc01615 is regulated by the TGFβ-STAT3 pathway in a feedback loop. Knockdown of Linc01615 inhibited cell proliferation and migration by regulating the PI3K pathway and mesenchymal markers. We also identified RP4-568C11.4 as an epithelial cancer marker. We showed that knocking down RP4-568C11.4 decreased cell growth but not migration. In addition, we discovered that ESR1 regulates RP4-5681C11.4 in breast cancer. Taken together, we have developed a pan-cancer EMT signature. Also, we found two new LncRNAs that have different effects on cancer development and EMT.

Epigenetic activation of RBM15 promotes clear cell renal cell carcinoma growth, metastasis and macrophage infiltration by regulating the m6A modification of CXCL11

Clear cell renal cell carcinoma (ccRCC) is a common kidney malignancy that is characterized by poor prognosis. RNA-binding motif protein 15 (RBM15) has been identified as an oncogene in multiple tumors. Nevertheless, the function and mechanism of RBM15 in ccRCC are not clear. In this study, RBM15 was found to be upregulated in ccRCC cells and tissues. RBM15 enhanced the proliferation, clone formation, migration, invasion and epithelial-interstitial transition of ccRCC cells. Enhanced RBM15 was caused by the abundant histone 3 acetylation modification of the RBM15 promoter induced by EP300/CBP. RBM15 enhanced the stability of CXCL11 mRNA in an m6A-dependent manner. Moreover, RBM15 was found to promote macrophage infiltration and M2 polarization by promoting the secretion of CXCL11 in ccRCC cells in vitro and in vivo. Our findings highlight the function of RBM15 in ccRCC and reveal a novel identified EP300/CBP-RBM15-CXCL11 signaling axis, which promotes ccRCC progression and provides new insight into ccRCC therapy.

Using a Machine Learning Approach to Identify Key Biomarkers for Renal Clear Cell Carcinoma

Background

The most common and deadly subtype of renal carcinoma is kidney renal clear cell carcinoma (KIRC), which accounts for approximately 75% of renal carcinoma. However, the main cause of death in KIRC patients is tumor metastasis. There are no obvious clinical features in the early stage of kidney cancer, and 25–30% of patients have already metastasized when they are first diagnosed. Moreover, KIRC patients whose local tumors have been removed by nephrectomy are still at high risk of metastasis and recurrence and are not sensitive to chemotherapy and radiotherapy, leading to poor prognosis. Therefore, early diagnosis and treatment of this disease are very important.

Methods

KIRC-related patient datasets were downloaded from the GEO database and TCGA database. DEG screening and GO, KEGG and GSEA enrichment analysis was firstly conducted and then the LASSO and support vector machine (SVM) RFE algorithms were adopted to identify KIRC-associated key genes in training sets and validate them in the test set. The clinical prognostic analysis including the association between the expression of key genes and the overall survival, stage, grade across KIRC, the immune infiltration difference between normal samples and cancer samples, the correlation between the key genes and immune cells, immunomodulator, immune subtypes of KIRC were investigated in this research.

Results

We finally screened out 4 key genes, including ACPP, ANGPTL4, SCNN1G, SLC22A7. The expression of key genes show difference among normal samples and tumor samples, SCNN1G and SLC22A7 could be predictor of prognosis of patients. The expression of key genes was related with the abundance of tumor infiltration immune cells and the gene expression of immune checkpoint.

Conclusion

This study screened the 4 key genes, which contributed to early diagnosis, prognosis assessment and immune target treatment of patients with KIRC.

Comprehensive analysis of PTEN-related ceRNA network revealing the key pathways WDFY3-AS2 - miR-21-5p/miR-221-3p/miR-222-3p - TIMP3 as potential biomarker in tumorigenesis and prognosis of kidney renal clear cell carcinoma

Kidney renal clear cell carcinoma (KIRC) is one of the most common malignancies, and there is still a lack of effective biomarkers for early detection and prognostic prediction. In here, we compared the characteristics of RNA sequencing data sets of KIRC samples based on the tumor suppressor gene phosphatase and tensin homolog (PTEN). The 1016 long noncoding RNAs, 48 microRNAs (miRNAs), and 2104 messenger RNAs associated with PTEN were identified and these genes were differentially expressed between tumor and paracancerous tissues. The most relevant pathway was found to be WDFY3-AS2 - miR-21-5p/miR-221-3p/miR-222-3p - TIMP3 according to the rules of competing endogenous RNA (ceRNA) regulation. WDFY3-AS2 and TIMP3 expression were positively correlated and reduced in KIRC samples, while miR-21-5p, miR-221-3p, and miR-222-3p were relatively highly expressed. The relatively low expression of WDFY3-AS2 and TIMP3 in KIRC were associated with poor prognosis in KIRC patients, while higher expression of miR-21-5p, miR-221-3p, and miR-222-3p predicted reduced survival (p < 0.05). Univariate and multivariate Cox regression analysis showed that lower expression of WDFY3-AS2 and TIMP3 was significantly related to tumor grade, tumor size, lymph node metastasis, distant metastasis, and TNM stage. The expression of TIMP3 in KIRC tissues was also verified by immunohistochemistry, and the results were consistent with our analytical data. In summary, this study constructed a new model with clinical predictive value and identified the WDFY3-AS2/TIMP3 pathway that was closely associated with the prognosis of KIRC, which could serve as a promising biomarker for the diagnosis and treatment of KIRC.

SMAD4 contributes to chondrocyte and osteocyte development

Different cellular and molecular mechanisms contribute to chondrocyte and osteocyte development. Although vital roles of the mothers against decapentaplegic homolog 4 (also called 'SMAD4') have been discussed in different cancers and stem cell-related studies, there are a few reviews summarizing the roles of this protein in the skeletal development and bone homeostasis. In order to fill this gap, we discuss the critical roles of SMAD4 in the skeletal development. To this end, we review the different signalling pathways and also how SMAD4 defines stem cell features. We also elaborate how the epigenetic factors-ie DNA methylation, histone modifications and noncoding RNAs-make a contribution to the chondrocyte and osteocyte development. To better grasp the important roles of SMAD4 in the cartilage and bone development, we also review the genotype-phenotype correlation in animal models. This review helps us to understand the importance of the SMAD4 in the chondrocyte and bone development and the potential applications for therapeutic goals.

Identification of Mast Cell-Based Molecular Subtypes and a Predictive Signature in Clear Cell Renal Cell Carcinoma

Background: Kidney renal clear cell carcinoma (KIRC) is a common malignant tumor of the urinary system. Surgery is the preferred treatment option; however, the rate of distant metastasis is high. Mast cells in the tumor microenvironment promote or inhibit tumorigenesis depending on the cancer type; however, their role in KIRC is not well-established. Here, we used a bioinformatics approach to evaluate the roles of mast cells in KIRC.

Methods: To quantify mast cell abundance based on gene sets, a single-sample gene set enrichment analysis (ssGSEA) was utilized to analyze three datasets. Weighted correlation network analysis (WGCNA) was used to identify the genes most closely related to mast cells. To identify new molecular subtypes, the nonnegative matrix factorization algorithm was used. GSEA and least absolute shrinkage and selection operator (LASSO) Cox regression were used to identify genes with high prognostic value. A multivariate Cox regression analysis was performed to establish a prognostic model based on mast cell-related genes. Promoter methylation levels of mast cell-related genes and relationships between gene expression and survival were evaluated using the UALCAN and GEPIA databases.

Results: A prolonged survival in KIRC was associated with a high mast cell abundance. KIRC was divided into two molecular subtypes (cluster 1 and cluster 2) based on mast cell-related genes. Genes in Cluster 1 were enriched for various functions related to cancer development, such as the TGFβ signaling pathway, renal cell carcinoma, and mTOR signaling pathway. Based on drug sensitivity predictions, sensitivity to doxorubicin was higher for cluster 2 than for cluster 1. By a multivariate Cox analysis, we established a clinical prognostic model based on eight mast cell-related genes.

Conclusion: We identified eight mast cell-related genes and constructed a clinical prognostic model. These results improve our understanding of the roles of mast cells in KIRC and may contribute to personalized medicine.

DNA methylation-based profiling reveals distinct clusters with survival heterogeneity in high-grade serous ovarian cancer

High-grade serous ovarian cancer (HGSOC) is the most common type of epigenetically heterogeneous ovarian cancer. Methylation typing has previously been used in many tumour types but not in HGSOC. Methylation typing in HGSOC may promote the development of personalized care. The present study used DNA methylation data from The Cancer Genome Atlas database and identified four unique methylation subtypes of HGSOC. With the poorest prognosis and high frequency of residual tumours, cluster 4 featured hypermethylation of a panel of genes, which indicates that demethylation agents may be tested in this group and that neoadjuvant chemotherapy may be used to reduce the possibility of residual lesions. Cluster 1 and cluster 2 were significantly associated with metastasis genes and metabolic disorders, respectively. Two feature CpG sites, cg24673765 and cg25574024, were obtained through Cox proportional hazards model analysis of the CpG sites. Based on the methylation level of the two CpG sites, the samples were classified into high- and low-risk groups to identify the prognostic information. Similar results were obtained in the validation set. Taken together, these results explain the epigenetic heterogeneity of HGSOC and provide guidance to clinicians for the prognosis of HGSOC based on DNA methylation sites.

Establishment of a novel CNV-related prognostic signature predicting prognosis in patients with breast cancer

BACKGROUND

Copy number variation (CNVs) is a key factor in breast cancer development. This study determined prognostic molecular characteristics to predict breast cancer through performing a comprehensive analysis of copy number and gene expression data.

METHODS

Breast cancer expression profiles, CNV and complete information from The Cancer Genome Atlas (TCGA) dataset were collected. Gene Expression Omnibus (GEO) chip data sets (GSE20685 and GSE31448) containing breast cancer samples were used as external validation sets. Univariate survival COX analysis, multivariate survival COX analysis, least absolute shrinkage and selection operator (LASSO), Chi square, Kaplan-Meier (KM) survival curve and receiver operating characteristic (ROC) analysis were applied to build a gene signature model and assess its performance.

RESULTS

A total of 649 CNV related-differentially expressed gene obtained from TCGA-breast cancer dataset were related to several cancer pathways and functions. A prognostic gene sets with 9 genes were developed to stratify patients into high-risk and low-risk groups, and its prognostic performance was verified in two independent patient cohorts (n = 327, 246). The result uncovered that 9-gene signature could independently predict breast cancer prognosis. Lower mutation of PIK3CA and higher mutation of TP53 and CDH1 were found in samples with high-risk score compared with samples with low-risk score. Patients in the high-risk group showed higher immune score, malignant clinical features than those in the low-risk group. The 9-gene signature developed in this study achieved a higher AUC.

CONCLUSION

The current research established a 5-CNV gene signature to evaluate prognosis of breast cancer patients, which may innovate clinical application of prognostic assessment.

Ubiquitin-specific peptidase 53 inhibits the occurrence and development of clear cell renal cell carcinoma through NF-κB pathway inactivation

Background

Clear cell renal cell carcinoma (ccRCC) is one of the most prevalent malignant diseases in the urinary system with more than 140,000 related deaths annually. Ubiquitination–deubiquitination homeostasis is an important factor in ccRCC progression; ubiquitin‐specific peptidase 53 (USP53) belongs to the family of deubiquitinating enzymes, but its functions are rarely reported.

Methods

Databases obtained from GEO and TCGA were analyzed to reveal the role of USP53 in ccRCC. CCK‐8/BrdU and EDU assays were used to detect the proliferation of ccRCC after USP53 overexpression or knockdown. A tumor xenograft experiment was used to verify the effect of the proliferation of ccRCC after USP53 knockdown. Transwell assays were used to detect the metastasis of ccRCC after USP53 overexpression or knockdown. RNA sequencing and western blot analysis were employed to detect the change in genes after USP53 overexpression and knockdown. Then we tested the effect of USP53 on IκBα protein stability through western blot analysis. Detect the effect of USP53 on IκBα ubiquitination in vitro by immunoprecipitation method.

Results

USP53 expression was downregulated in ccRCC tissues and USP53 expression was significantly negatively correlated with the tumor progression and clinical prognosis. The ability of growth and metastasis of ccRCC was inhibited after USP53 overexpression. In addition, USP53 knockdown promoted ccRCC growth and metastasis. Moreover, USP53 knockdown promoted the ability of clone formation of ccRCC in vivo. NF‐κB signaling pathway significantly enriched and downregulated in USP53 overexpressed cells, and genes in the NF‐κB pathway (such as IL1B, CXCL1‐3, RELA, RELB, etc.) were obviously downregulated in USP53 overexpressed cells. USP53 overexpression decreased the phosphorylation of IKKβ and P65 in both Caki‐1 and 786‐O cells, and the expression of IκBα was increased. Phosphorylation of IKKβ and P65 was increased in both Caki‐1 and 786‐O cells after USP53 knockdown. As the expression of USP53 increases, the protein expression of IκBα was also gradually increased and USP53 reduced the ubiquitination of IκBα.

Conclusion

In summary, our data indicate that USP53 inhibits the inactivation of the NF‐κB pathway by reducing the ubiquitination of IκBα to further inhibit ccRCC proliferation and metastasis. These findings may help understand the pathogenesis of ccRCC and introduce new potential therapeutic targets for kidney cancer patients.

The CSRNP Gene Family Serves as a Prognostic Biomarker in Clear Cell Renal Cell Carcinoma

The cysteine-serine-rich nuclear protein (CSRNP) family has prognostic value for various cancers. However, the association between this proteins and prognosis of clear cell renal cell carcinoma (ccRCC) remains unclear. This study aimed to determine the prognostic value of the CSRNP family for patients with ccRCC. Therefore, the gene expression profiling interactive analysis database was used to analyze the mRNA expression of CSRNP family members (CSRNPs) in relation with survival. Combined and independent prognostic values of CSRNPs were evaluated using SurvExpress and multivariate Cox regression analyses, respectively. Potential signaling pathways impacted by CSRNPs were evaluated using Metascape. Associations between the CSRNP family and immunocyte infiltration were determined from single-sample gene set enrichment analysis. Both cBioPortal and MethSurv were used to explore whether genomic and epidemic alterations might influence prognosis. We found that when both CSRNP1 and CSRNP3 had a low expression, patients with ccRCC had a worse overall survival (OS). Therefore, a prognostic signature was constructed as follows: risk score = -0.224 × exp_{mRNA of CSRNP1} + 0.820 × exp_{mRNA of CSRNP2} - 1.428 × exp_{mRNA of CSRNP3} . We found that OS was worse in patients from the high- than from the low-risk groups (AUC = 0.69). Moreover, this signature was an independent predictor after adjusting for clinical features. Functional enrichment analysis positively associated CSRNPs with the acute inflammatory response and humoral immune response pathways. This was validated by correlating each CSRNP with 28 types of immunocytes in tumor and normal tissues. A higher expression of CSRNP1 and CSRNP3 was associated with a better prognosis in both the high- and low-mutant burden groups. Cg19538674, cg07772537, and cg07811002 of CSRNP1, CSRNP2, and CSRNP3, respectively, were the predominant DNA methylation sites affecting OS. The CSRNP gene family signature may serve as a prognostic biomarker for predicting OS in patients with ccRCC. The association between CSRNPs and immune infiltration might offer future clinical treatment options.

Epigenetic signature predicts overall survival clear cell renal cell carcinoma

BACKGROUND

Recently, increasing study have found that DNA methylation plays an important role in tumor, including clear cell renal cell carcinoma (ccRCC).

METHODS

We used the DNA methylation dataset of The Cancer Genome Atlas (TCGA) database to construct a 31-CpG-based signature which could accurately predict the overall survival of ccRCC. Meanwhile, we constructed a nomogram to predict the prognosis of patients with ccRCC.

RESULT

Through LASSO Cox regression analysis, we obtained the 31-CpG-based epigenetic signature which were significantly related to the prognosis of ccRCC. According to the epigenetic signature, patients were divided into two groups with high and low risk, and the predictive value of the epigenetic signature was verified by other two sets. In the training set, hazard ratio (HR) = 13.0, 95% confidence interval (CI) 8.0-21.2, P < 0.0001; testing set: HR = 4.1, CI 2.2-7.7, P < 0.0001; entire set: HR = 7.2, CI 4.9-10.6, P < 0.0001, Moreover, combined with clinical indicators, the prediction of 5-year survival of ccRCC reached an AUC of 0.871.

CONCLUSIONS

Our study constructed a 31-CpG-based epigenetic signature that could accurately predicted overall survival of ccRCC and staging progression of ccRCC. At the same time, we constructed a nomogram, which may facilitate the prediction of prognosis for patients with ccRCC.

Genome-wide methylation sequencing identifies progression-related epigenetic drivers in myelodysplastic syndromes

The potential mechanism of myelodysplastic syndromes (MDS) progressing to acute myeloid leukemia (AML) remains poorly elucidated. It has been proved that epigenetic alterations play crucial roles in the pathogenesis of cancer progression including MDS. However, fewer studies explored the whole-genome methylation alterations during MDS progression. Reduced representation bisulfite sequencing was conducted in four paired MDS/secondary AML (MDS/sAML) patients and intended to explore the underlying methylation-associated epigenetic drivers in MDS progression. In four paired MDS/sAML patients, cases at sAML stage exhibited significantly increased methylation level as compared with the matched MDS stage. A total of 1090 differentially methylated fragments (DMFs) (441 hypermethylated and 649 hypomethylated) were identified involving in MDS pathogenesis, whereas 103 DMFs (96 hypermethylated and 7 hypomethylated) were involved in MDS progression. Targeted bisulfite sequencing further identified that aberrant GFRA1, IRX1, NPY, and ZNF300 methylation were frequent events in an additional group of de novo MDS and AML patients, of which only ZNF300 methylation was associated with ZNF300 expression. Subsequently, ZNF300 hypermethylation in larger cohorts of de novo MDS and AML patients was confirmed by real-time quantitative methylation-specific PCR. It was illustrated that ZNF300 methylation could act as a potential biomarker for the diagnosis and prognosis in MDS and AML patients. Functional experiments demonstrated the anti-proliferative and pro-apoptotic role of ZNF300 overexpression in MDS-derived AML cell-line SKM-1. Collectively, genome-wide DNA hypermethylation were frequent events during MDS progression. Among these changes, ZNF300 methylation, a regulator of ZNF300 expression, acted as an epigenetic driver in MDS progression. These findings provided a theoretical basis for the usage of demethylation drugs in MDS patients against disease progression.

CLDN10 associated with immune infiltration is a novel prognostic biomarker for clear cell renal cell carcinoma

Aims: To identify the clinical roles of CLDN10 in clear cell renal cell carcinoma (ccRCC). Materials & methods: Using data from TCGA-KIRC, GEO DataSets and laboratory experiments to determine the prognostic and clinicopathological characteristics of CLDN10. Results: CLDN10 expression was remarkably reduced in ccRCC. Downregulated CLDN10 was related to metastasis and poor prognosis. Multivariate Cox analysis determined that elevated CLDN10 expression was independently correlated with longer OS and DFS. Moreover, CLDN10 expression was negatively associated with the methylation levels of cg10305311 and cg16275739. CLDN10 expression was also associated with naive CD4 and memory T-cell and dendritic cell infiltration. Conclusions: Immune-related CLDN10 is an independent prognostic biomarker of ccRCC. DNA hypermethylation plays an important role in decreased CLDN10 expression.

The p53-inducible CLDN7 regulates colorectal tumorigenesis and has prognostic significance

Most colorectal cancer (CRC) are characterized by allele loss of the genes located on the short arm of chromosome 17 (17p13.1), including the tumor suppressor p53 gene. Although important, p53 is not the only driver of chromosome 17p loss. In this study, we explored the biological and prognostic significance of genes around p53 on 17p13.1 in CRC. The Cancer Genome Atlas (TCGA) were used to identify differentially expressed genes located between 1000 kb upstream and downstream of p53 gene. The function of CLDN7 was evaluated by both in vitro and in vivo experiments. Quantitative real-time PCR, western blot, and promoter luciferase activity, immunohistochemistry were used to explore the molecular drivers responsible for the development and progression of CRC. The results showed that CLDN7, located between 1000 kb upstream and downstream of p53 gene, were remarkably differentially expressed in tumor and normal tissues. CLDN7 expression also positively associated with p53 level in different stages of the adenoma-carcinoma sequence. Both in vitro and in vivo assays showed that CLDN7 inhibited cell proliferation in p53 wild type CRC cells, but had no effects on p53 mutant CRC cells. Mechanistically, p53 could bind to CLDN7 promoter region and regulate its expression. Clinically, high CLDN7 expression was negatively correlated with tumor size, invasion depth, lymphatic metastasis and AJCC III/IV stage, but was positively associated with favorable prognosis of CRC patients. Collectively, our work uncovers the tumor suppressive function for CLDN7 in a p53-dependent manner, which may mediate colorectal tumorigenesis induced by p53 deletion or mutation.

Current Opinion on Molecular Characterization for GBM Classification in Guiding Clinical Diagnosis, Prognosis, and Therapy

Glioblastoma (GBM) is highly invasive and the deadliest brain tumor in adults. It is characterized by inter-tumor and intra-tumor heterogeneity, short patient survival, and lack of effective treatment. Prognosis and therapy selection is driven by molecular data from gene transcription, genetic alterations and DNA methylation. The four GBM molecular subtypes are proneural, neural, classical, and mesenchymal. More effective personalized therapy heavily depends on higher resolution molecular subtype signatures, combined with gene therapy, immunotherapy and organoid technology. In this review, we summarize the principal GBM molecular classifications that guide diagnosis, prognosis, and therapeutic recommendations.

Low Expression of Claudin-7 as Potential Predictor of Distant Metastases in High-Grade Serous Ovarian Carcinoma Patients

High-grade serous ovarian carcinoma (HGSOC) usually spreads directly into the peritoneal cavity following a transcoelomic dissemination route, although distant hematogenous metastasis exist and have been reported. However, no tumor markers can currently predict the risk of distant metastases in HGSOC. Claudins, belonging to tight-junction proteins, are dysregulated in HGSOC and functionally related to cancer progression. Here we analyzed claudin-3, -4, and -7 expression as potential markers of distant metastases. Using quantitative RT-PCR and immunohistochemistry we assessed the expression of claudins in primary HGSOC tissues, normal ovarian, and normal fallopian tube epithelia and correlated it with clinicopathological features, including the site of metastasis and the route of dissemination. Gene set enrichment analysis was performed on microarray-generated gene expression data to investigate key pathways in patients with distant metastases. We found the overall expression level of claudin-3, -4, and -7 mRNA decreased in HGSOC compared to normal tubal epithelium, currently considered the potential site of origin of many HGSOC. The reduced expression of claudin-7 is significantly associated with the development of distant metastases (p = 0.016), mainly by hematogenous route (p = 0.025). In patients with diminished expression of claudin-7, immunohistochemical staining revealed a heterogeneous pattern of membranous staining with discontinuous expression of claudin-7 along the cell border, indicative of a dischoesive architecture. The estimated reduction in the probability of distant disease is of 39% per unit increase in the level of claudin-7 (p = 0.03). Genes involved in epithelial to mesenchymal transition, hypoxia, and angiogenesis processes resulted strongly associated to hematogenous recurrence. Our data suggest a potential role of claudin-7 in discriminating distant metastatic events in HGSOC patients. The quantification of its expression levels could be a useful tool to identify patient deserving a personalized follow-up in terms of clinical and radiological assessment.

E7 oncoprotein from human papillomavirus 16 alters claudins expression and the sealing of epithelial tight junctions

Tight junctions (TJs) are cell-cell adhesion structures frequently altered by oncogenic transformation. In the present study the role of human papillomavirus (HPV) 16 E7 oncoprotein on the sealing of TJs was investigated and also the expression level of claudins in mouse cervix and in epithelial Madin-Darby Canine Kidney (MDCK) cells. It was found that there was reduced expression of claudins -1 and -10 in the cervix of 7-month-old transgenic K14E7 mice treated with 17β-estradiol (E₂), with invasive cancer. In addition, there was also a transient increase in claudin-1 expression in the cervix of 2-month-old K14E7 mice, and claudin-10 accumulated at the border of cells in the upper layer of the cervix in FvB mice treated with E₂, and in K14E7 mice treated with or without E₂. These changes were accompanied by an augmented paracellular permeability of the cervix in 2- and 7-monthold FvB mice treated with E₂, which became more pronounced in K14E7 mice treated with or without E₂. In MDCK cells the stable expression of E7 increased the space between adjacent cells and altered the architecture of the monolayers, induced the development of an acute peak of transepithelial electrical resistance accompanied by a reduced expression of claudins -1, -2 and -10, and an increase in claudin-4. Moreover, E7 enhances the ability of MDCK cells to migrate through a 3D matrix and induces cell stiffening and stress fiber formation. These observations revealed that cell transformation induced by HPV16 E7 oncoprotein was accompanied by changes in the pattern of expression of claudins and the degree of sealing of epithelial TJs.

VHL mutation-mediated SALL4 overexpression promotes tumorigenesis and vascularization of clear cell renal cell carcinoma via Akt/GSK-3β signaling

Background

Although ongoing development of therapeutic strategies contributes to the improvements in clinical management, clear cell renal cell carcinoma (ccRCC) deaths originate mainly from radiochemoresistant and metastatic disease. Transcription factor SALL4 has been implicated in tumorigenesis and metastasis of multiple cancers. However, it is not known whether SALL4 is involved in the pathogenesis of ccRCC.

Methods

Analyses of clinical specimen and publicly available datasets were performed to determine the expression level and clinical significance of SALL4 in ccRCC. The influence of SALL4 expression on ccRCC tumor growth, metastasis and vascularity was evaluated through a series of in vitro and in vivo experiments. Western blotting, immunofluorescence staining and integrative database analysis were carried out to investigate the underlying mechanism for SALL4-mediated oncogenic activities in ccRCC.

Results

SALL4 expression was increased in ccRCC and positively correlated with tumor progression and poor prognosis. SALL4 could promote ccRCC cell proliferation, colony formation, cell cycle progression, migration, invasion and tumorigenicity and inhibit cell senescence. Further investigation revealed a widespread association of SALL4 with individual gene transcription and the involvement of SALL4 in endothelium development and vasculogenesis. In the context of ccRCC, SALL4 promoted tumor vascularization by recruiting endothelial cells. In addition, we found that SALL4 could exert its tumor-promoting effect via modulating Akt/GSK-3β axis and VEGFA expression. VHL mutation and DNA hypomethylation may be involved in the upregulation of SALL4 in ccRCC.

Conclusions

Overall, our results provide evidence that upregulated SALL4 can function as a crucial regulator of tumor pathogenesis and progression in ccRCC, thus offering potential therapeutic strategies for future treatment.

Evaluation of clinical significance of claudin 7 and construction of prognostic grading system for stage II colorectal cancer

BACKGROUND

Claudin 7 is often abnormally expressed in cancers and promotes the progression of some malignancies. However, the role of claudin 7 in stage II colorectal cancer (CRC) has not been studied.

AIM

To assess the expression and prognostic value of claudin 7 in stage II CRC.

METHODS

We retrospectively studied 231 stage II CRC patients who underwent radical surgery at our hospital from 2013 to 2014. The protein expression level of claudin 7 was assessed and its relationship with clinicopathological features and prognosis was statistically analyzed. The independent prognostic factors were identified by Cox proportional hazards models. A prognostic grading system was constructed to stratify the survival of CRC patients.

RESULTS

The expression of claudin 7 was significantly reduced in cancer tissues compared with normal tissues (P < 0.001), and its low expression was closely related to recurrence of the disease (P = 0.017). Multivariate analysis confirmed that claudin 7 low expression (claudin 7-low) (P = 0.028) and perineural invasion positivity (PNI+) (P = 0.026) were independent predictors of poor disease-free survival (DFS). A prognostic grading system based on the status of claudin 7 and PNI classified the patients into three prognostic grades: grade A (claudin 7-high and PNI-), grade B (claudin 7-low and PNI-, claudin 7-high and PNI+), and grade C (claudin 7-low and PNI+). The DFS was significantly different among the three grades (grade B vs grade A, P = 0.032; grade C vs grade A, P < 0.001; grade C vs grade B, P = 0.040).

CONCLUSION

Claudin 7 can be used as a new prognostic marker to predict the DFS of patients with stage II CRC. The prognostic grading system with the addition of claudin 7 can further improve prognosis stratification of patients.

Relationship between apical junction proteins, gene expression and cancer

The apical junctional complex (AJC) is a cell-cell adhesion system present at the upper portion of the lateral membrane of epithelial cells integrated by the tight junction (TJ) and the adherens junction (AJ). This complex is crucial to initiate and stabilize cell-cell adhesion, to regulate the paracellular transit of ions and molecules and to maintain cell polarity. Moreover, we now consider the AJC as a hub of signal transduction that regulates cell-cell adhesion, gene transcription and cell proliferation and differentiation. The molecular components of the AJC are multiple and diverse and depending on the cellular context some of the proteins in this complex act as tumor suppressors or as promoters of cell transformation, migration and metastasis outgrowth. Here, we describe these new roles played by TJ and AJ proteins and their potential use in cancer diagnostics and as targets for therapeutic intervention.

Discovery and validation of the prognostic value of the lncRNAs encoding snoRNAs in patients with clear cell renal cell carcinoma

Some lncRNAs can encode small nucleolar RNAs (snoRNAs), called small nucleolar RNA host genes (SNHGs), which have exerted certain predictive values for the prognosis of some cancer patients. In this study, using RNA-seq and survival data in TCGA-KIRC, we examined the expression profile of 20 SNHGs and explored their prognostic values in ccRCC. Results showed that SNHG1, GAS5, SNHG3-8, SNHG11, SNHG12, SNHG15-17, SNHG20, SNHG22 and SNHG25 were significantly upregulated in ccRCC tissues compared with adjacent normal tissues. After adjustment for confounding factors, the multivariate analysis confirmed that increased SNHG3 expression was independently associated with shorter OS, while increased SNHG15 expression was an independent predictor of shorter RFS. Using the methylation data, the methylation status of 2 CpG sites (cg07807470 and cg15161854) and 2 CpG sites (cg00953154 and cg16459265) were negatively correlated with SNHG3 and SNHG15 expression, respectively. Moreover, low methylation levels of the 4 CpG sites were significantly associated with shorter OS. Furthermore, we validated the expression patterns, methylation status and prognostic value of SNHG3 and SNHG15 using clinical ccRCC samples. Taken together, SNHG3 and SNHG15 might be valuable prognostic markers in ccRCC, and DNA hypomethylation might play an important role in elevated SNHG3 and SNHG15 transcription in ccRCC.

A SUMOylation-dependent HIF-1α/CLDN6 negative feedback mitigates hypoxia-induced breast cancer metastasis

Background

We have previously described CLDN6 as a tumor suppressor gene in breast cancer. Here, a new finding is that CLDN6 was upregulated under hypoxia, a commonly recognized factor that promotes tumor metastasis. In this study, we aim to explain this confusing finding and delineate the role of CLDN6 in the breast cancer metastasis induced by hypoxia.

Methods

RNAi and ChIP assays were used to confirm that CLDN6 is transcriptional regulated by HIF-1α. mRNA seq and KEGG analysis were performed to define the downstream pathways of CLDN6. The roles of the CLDN6/SENP1/HIF-1α signaling on tumor metastasis were evaluated by function experiments and clinical samples. Finally, the possible transcription factor of SENP1 was suspected and then validated by ChIP assay.

Results

We demonstrated a previously unrecognized negative feedback loop exists between CLDN6 and HIF-1α. CLDN6 was transcriptionally up-regulated by HIF-1α under hypoxia. On the other hand, in cytoplasm CLDN6 combines and retains β-catenin, a transcription factor of SENP1, causing β-catenin degradation and preventing its nuclear translocation. This process reduced SENP1 expression and prevented the deSUMOylation of HIF-1α, ultimately leading to HIF-1α degradation and breast cancer metastasis suppression.

Conclusions

Our data provide a molecular mechanistic insight indicating that CLDN6 loss may lead to elevated HIF-1α-driven breast cancer metastasis in a SUMOylation-dependent manner.

MTDH promotes metastasis of clear cell renal cell carcinoma by activating SND1-mediated ERK signaling and epithelial-mesenchymal transition

BACKGROUND

Metastasis is the principal cause of renal cell carcinoma-associated mortality. Metadherin (MTDH) was identified as a vital metastasis driver involved in the metastatic progression of various types of tumors, suggesting that MTDH is a prognostic metastatic biomarker and potential therapeutic target. The role and mechanism of MTDH in the metastatic progression of ccRCC have not yet been adequately explored.

RESULTS

MTDH was remarkably elevated in ccRCC tissues, especially in metastatic ccRCC tissues, compared with normal kidney tissues and correlated with advanced clinicopathological features and poor prognosis. MTDH activated ERK signaling and EMT, thus promoting the migration and invasion of ccRCC cells. The interaction between MTDH and SND1 at the protein level was confirmed using immunoprecipitation and immunofluorescence. Based on the analysis of datasets from GEO and TCGA, SND1 was remarkably increased in ccRCC, especially in metastatic ccRCC, and associated with advanced clinicopathological features and poor prognosis. Knockdown of SND1 mainly abolished the migration and invasion of ccRCC cells by blocking MTDH-mediated ERK and EMT signaling activation.

CONCLUSION

These results revealed that MTDH may be a prognostic metastatic biomarker of ccRCC that promotes ccRCC metastasis by activating SND1-mediated the ERK and EMT signaling pathways. MTDH may serve as an anti-tumor therapeutic target that can be applied for the clinical treatment of metastatic ccRCC.

METHODS

MTDH/SND1 mRNA expression in clear cell renal cell carcinoma (ccRCC) was comprehensively estimated by analysis of GEO-ccRCC and TCGA-KIRC datasets with R software and packages. MTDH protein expression was assessed in a total of 111 ccRCC patients from Peking University First Hospital by immunohistochemistry (IHC). In vitro migration and invasion assays were carried out, and an in vivo metastatic mouse model was developed to investigate the biological functions of MTDH in ccRCC cells. Correlation analysis, immunoprecipitation, western blotting and immunofluorescence were applied to explore the molecular mechanisms of MTDH in ccRCC.

Identification of Key Genes and Prognostic Analysis between Chromophobe Renal Cell Carcinoma and Renal Oncocytoma by Bioinformatic Analysis

The present techniques of clinical and histopathological diagnosis hardly distinguish chromophobe renal cell carcinoma (ChRCC) from renal oncocytoma (RO). To identify differentially expressed genes (DEGs) as effective biomarkers for diagnosis and prognosis of ChRCC and RO, three mRNA microarray datasets (GSE12090, GSE19982, and GSE8271) were downloaded from the GEO database. Functional enrichment analysis of DEGs was performed by DAVID. STRING and Cytoscape were applied to construct the protein-protein interaction (PPI) network and key modules of DEGs. Visualized plots were conducted by the R language. We downloaded clinical data from the TCGA database and the influence of key genes on the overall survival of ChRCC was performed by Kaplan–Meier and Cox analyses. Gene set enrichment analysis (GSEA) was utilized in exploring the function of key genes. A total of 79 DEGs were identified. Enrichment analyses revealed that the DEGs are closely related to tissue invasion and metastasis of cancer. Subsequently, 14 hub genes including ESRP1, AP1M2, CLDN4, and CLDN7 were detected. Kaplan–Meier analysis indicated that the low expression of CLDN7 and GNAS was related to the worse overall survival in patients with ChRCC. Univariate Cox analysis showed that CLDN7 might be a helpful biomarker for ChRCC prognosis. Subgroup analysis revealed that the expression of CLDN7 showed a downtrend with the development of the clinical stage, topography, and distant metastasis of ChRCC. GSEA analysis identified that cell adhesion molecules cams, B cell receptor signaling pathway, T cell receptor signaling pathway, RIG-I like receptor signaling pathway, Toll-like receptor signaling pathway, and apoptosis pathway were associated with the expression of CLDN7. In conclusion, ESRP1, AP1M2, CLDN4, PRSS8, and CLDN7 were found to distinguish ChRCC from RO. Besides, the low expression of CLDN7 was closely related to ChRCC progression and could serve as an independent risk factor for the overall survival in patients with ChRCC.

DOCK1 Regulates Growth and Motility through the RRP1B-Claudin-1 Pathway in Claudin-Low Breast Cancer Cells

Dedicator of cytokinesis 1 (DOCK1) is a critical regulator of cancer metastasis. Claudins are transmembrane proteins that play a role in epithelial barrier integrity. Due to a loss or low expression of claudins (CLDN), the claudin-low type of triple-negative breast cancer (TNBC) is characterized by a mesenchymal-like phenotype with strong metastatic potential. In order to elucidate the mechanism of DOCK1 in cancer metastasis, we first analyzed the transcriptomic changes using a clinical database of human TNBC and found that the increase in DOCK1 expression was highly correlated with the poor survival rate of TNBC patients. Interference with DOCK1 expression by shRNA resulted in re-expression of claudin-1 in conjunction with significant inhibition of cell viability and motility of claudin-low breast cancer cells. Accordingly, overexpression of claudin-1 suppressed cell viability and migration. Genetic knockdown and pharmacological blockade of Rac1/Rac2 up-regulated claudin-1. DOCK1 knockdown also caused a decrease in DNA methyltransferase (DNMT) expression and an increase in claudin-1 transcript and promoter activity. Furthermore, RRP1B mediated DOCK1 depletion, which up-regulated claudin-1 expression, cell viability, and motility in claudin-low breast cancer cells. This study demonstrated that DOCK1 mediates growth and motility through down-regulated claudin-1 expression via the RRP1B–DNMT–claudin-1 pathway and that claudin-1 serves as an important effector in DOCK1-mediated cancer progression and metastasis in claudin-low breast cancer cells.

Specific glioblastoma multiforme prognostic-subtype distinctions based on DNA methylation patterns

DNA methylation is an important regulator of gene expression, and plays a significant role in carcinogenesis in the brain. Here, we explored specific prognosis-subtypes based on DNA methylation status using 138 Glioblastoma Multiforme (GBM) samples from The Cancer Genome Atlas (TCGA) database. The methylation profiles of 11,637 CpG sites that significantly correlated with survival in the training set were employed for consensus clustering. We identified three GBM molecular subtypes, and their survival curves were distinct from each other. Furthermore, ten feature CpG sites were obtained on conducting a weighted gene co-expression network analysis (WGCNA) of the CpG sites. We were able to classify the samples into high- and low-methylation groups, and classified the prognosis information of the samples after cluster analysis of the training set samples using the hierarchical clustering algorithm. Similar results were obtained in the test set and clinical GBM specimens. Finally, we found that a positive relationship existed between methylation level and sensitivity to temozolomide (or radiotherapy) or anti-migration ability of GBM cells. Taken together, these results suggest that the model constructed in this study could help explain the heterogeneity of previous molecular subgroups in GBM and can provide guidance to clinicians regarding the prognosis of GBM.