Modeling clear cell renal cell carcinoma and therapeutic implications

Alpha-2-Heremans-Schmid-glycoprotein (AHSG) a potential biomarker associated with prognosis of chromophobe renal cell carcinoma: The PROPOLIS study

Background and Aims

Chromophobe renal cell carcinoma (chRCC) is the third common pathological subtype in renal cancers. However, the underlying mechanisms of specific genetic characteristics of chRCC are currently unclear. In this study, protein expression profiles, gene ontology (GO), and survival plots were provided by integrated bioinformatics analysis to investigate key genes associated with the mechanism of tumorigenesis and prognosis of chRCC.

Methods

The chRCC data set of gene expression profiles and clinical data were obtained from the gdc-client (https://portal.gdc.cancer.gov) deposited on The Cancer Genome Atlas (TCGA) data portal. Differentially expressed genes (DEGs) in chRCC, compared with normal samples, were analyzed by R packages "DESeq2," "edgeR," and "limma." Heat maps, volcano plots, and principal component analysis (PCA) were performed for integrated analyses. GUniGO, mutant analysis, and survival plots were performed by R packages. A protein-protein interaction (PPI) network was generated and analyzed by R packages, online String software, and Cytoscape software. Survival analysis and gene expressing comparison in tumor and normal samples were used to detect the core genes of chRCC. Furthermore, the top interacting proteins were reanalyzed.

Results

A total of 306 upregulated genes and 678 downregulated genes were identified by a Venn diagram. Ten hub genes were extracted from PPI network. Furthermore, Alpha-2-Heremans-Schmid-glycoprotein (AHSG), one of 10 hub genes, was found to be associated with chRCC, and had a big difference in expression between survival and dead events. AHSG could predict potential prognostic and may be a diagnostic biomarker in chRCC.

Conclusion

This study illustrated that AHSG may be a potential therapeutic target and prognostic genetic marker for chRCC.

Clinical significance and immune landscape of cuproptosis-related lncRNAs in kidney renal clear cell carcinoma: a bioinformatical analysis

Background

Kidney renal clear cell carcinoma (KIRC) is considered an immunogenic tumor. Cuproptosis is a newly identified copper-induced regulated cell death that relies on mitochondria respiration. Long noncoding RNAs (lncRNAs) have emerged as significant players in tumorigenesis and metastasis. However, there is a huge knowledge gap on the prognostic role of cuproptosis-related lncRNAs in KIRC. And, the clinical value of them is still unknown. Here, we aimed to develop a cuproptosis-related lncRNA prognostic signature in KIRC.

Methods

The messenger RNA (mRNA)/lncRNA expression profiles and the clinical information including age, gender, tumor stage, grade, and overall survival (OS) were acquired from The Cancer Genome Atlas (TCGA) database. The included KIRC samples were further randomly assigned into training (n=258) or testing (n=257) data sets. We performed Pearson correlation analysis to identify the cuproptosis-related lncRNAs and then constructed the prognostic signature using Cox regression analysis and LASSO algorithm. Subsequently, Kaplan-Meier survival analysis, a nomogram, and receiver operating characteristic (ROC) curve were performed to assess the predictive performance of the signature. Moreover, the immune characteristics and drug sensitivity related to the signature were also explored.

Results

The signature comprised 7 cuproptosis-related lncRNAs. The patients with a low-risk score had superior OS compared with those with a high-risk score. The survival rates of the high- and low-risk groups were 44.96% and 83.72% (P<0.001). The area under the curve (AUC) value for 1-, 3-, 5-year survival rate reached 0.814, 0.762 and 0.825, respectively. In addition, a nomogram was also generated; the AUC was 0.785 for risk score, higher than that for age (0.593), gender (0.489), grade (0.679), and stage (0.721). The high-risk group had more enriched immune- and tumor-related genes. Patients with low-risk scores were more sensitive to immunotherapy and the small molecular drugs GSK1904529A, tipifarnib, BX-912, FR-180204, and GSK1070916. Meanwhile, the high-risk group tended to be more sensitive to pyrimethamine, MS-275, and CGP-60474.

Conclusions

Collectively, we constructed a cuproptosis-related lncRNA prognostic signature with a higher predictive accuracy compared to multiple clinicopathological parameters, which may provide vital guidance for therapeutic strategies in KIRC. Combination of more prognostic biomarkers may further improve the accuracy.

Establishment of a ccRCC patient-derived chick chorioallantoic membrane model for drug testing

Clear cell renal cell carcinoma (ccRCC) is an aggressive subtype of renal cell carcinoma accounting for the majority of deaths in kidney cancer patients. Advanced ccRCC has a high mortality rate as most patients progress and develop resistance to currently approved targeted therapies, highlighting the ongoing need for adequate drug testing models to develop novel therapies. Current animal models are expensive and time-consuming. In this study, we investigated the use of the chick chorioallantoic membrane (CAM), a rapid and cost-effective model, as a complementary drug testing model for ccRCC. Our results indicated that tumor samples from ccRCC patients can be successfully cultivated on the chick chorioallantoic membrane (CAM) within 7 days while retaining their histopathological characteristics. Furthermore, treatment of ccRCC xenografts with sunitinib, a tyrosine kinase inhibitor used for the treatment of metastatic RCC, allowed us to evaluate differential responses of individual patients. Our results indicate that the CAM model is a complementary in vivo model that allows for rapid and cost-effective evaluation of ccRCC patient response to drug therapy. Therefore, this model has the potential to become a useful platform for preclinical evaluation of new targeted therapies for the treatment of ccRCC.

An Integrated Study on the Differential Expression of the FOX Gene Family in Cancer and Their Response to Chemotherapy Drugs

The Forkhead-box (FOX) transcription factors, as one of the largest gene families in humans, play key roles in cancer. Although studies have suggested that several FOX transcription factors have a significant impact on cancer, the functions of most of the FOX genes in cancer remain elusive. In the study, the expression of 43 FOX genes in 63 kinds of cancer diseases (including many subtypes of same cancer) and in response to 60 chemical substances was obtained from the Gene Expression Atlas database of the European Bioinformatics Institute. Based on the high degree of overlap in FOXO family members differentially expressed in various cancers and their particular responses to chemotherapeutic drugs, our data disclosed the FOX genes that played an important role in the development and progression of cancer. More importantly, we predicted the role of one or several combinatorial FOX genes in the diagnosis and prognostic assessment of a specific cancer and evaluated the potential of a certain anticancer drug therapy for this type of cancer by integrating patterns of FOX genes expression with anticancer drugs sensitivity.

GLUD1 suppresses renal tumorigenesis and development via inhibiting PI3K/Akt/mTOR pathway

Growing cancer cells are addicted to glutamine. Glutamate dehydrogenase 1 (GLUD1) is one of key enzymes in glutamine metabolism and plays a critical role in the malignancy of diverse tumors. However, its role and molecular mechanism in clear cell renal cell carcinoma (ccRCC) development and progression remain unknown. In this study, analysis results of the GEO/TCGA/UALCAN database showed that GLUD1 level was downregulated in ccRCC tissues. Immunohistochemistry and western blotting results further validated the downregulation of GLUD1 level in ccRCC tissues. GLUD1 level was gradually decreased as ccRCC stage and grade progressed. Low GLUD1 level was associated with a shorter survival and higher IC50 value for tyrosine kinase inhibitors (TKIs) in ccRCC, reminding that GLUD1 level could predict the prognosis and TKIs sensitivity of ccRCC patients. High level of methylation in GLUD1 promoter was positively correlated with the downregulation of GLUD1 level and was negatively correlated with survival of ccRCC patients. GLUD1 overexpression suppressed RCC cell proliferation, colony formation and migration by inhibiting PI3K/Akt/mTOR pathway activation. Low GLUD1 level correlated with suppressive immune microenvironment (TIME) in ccRCC. Together, we found a novel tumor-suppressing role of GLUD1 in ccRCC which was different from that in other tumors and a new mechanism for inhibiting PI3K/Akt/mTOR activation and TIME in ccRCC. These results provide a theoretical basis for GLUD1 as a therapeutic target and prognostic marker in ccRCC.

Comprehensive analysis of cellular senescence-related genes in the prognosis, tumor microenvironment, and immunotherapy/chemotherapy of clear cell renal cell carcinoma

Background

The transcriptome public database and advances in biological discoveries contributed to significant progresses in identifying the drivers of cancer progression. Cellular senescence (CS) is considered as a leading factor resulting in cancer development. The purpose of this study was to explore the significance of CS-related genes in the molecular classification and survival outcome of clear cell renal cell carcinoma (ccRCC).

Methods

CS-related genes were obtained from the CellAge database, and patients from TCGA-KIRC dataset and ICGC dataset were clustered by ConsesusClusterPlus. The characteristics of overall survival (OS), genomic variation, and tumor microenvironment (TME) of each cluster were analyzed. Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analysis was conducted to develop a CS-related risk model to score ccRCC patients and assess the risk scores in predicting patients’ response to immunotherapy and chemotherapy. A nomogram based on the risk model was established to improve the risk stratification of patients.

Results

CcRCC was divided into three molecular subtypes based on CS-related genes. The three molecular phenotypes showed different OS and clinical manifestations, mutation patterns, and TME states. Five genes were obtained from nine differentially expressed CS-related genes in the three molecular subtypes to develop a risk model. Patients with ccRCC were divided into high- and low-risk subgroups. The former showed an unfavorable OS, with a significantly higher genomic variation rate, TME score, and numerous immune checkpoint expressions when compared to the low-risk subgroup. Risk score reflected the response of patients to axitinib, bortezomib, sorafenib, sunitinib, and temsirolimus.

Conclusions

In general, CS-related genes divided ccRCC into three molecular subtypes with distinct OS, mutation patterns, and TME states. The risk model based on the five CS-related genes can predict the prognosis and therapeutic outcome of ccRCC patients, providing a theoretical basis for further study on the molecular mechanism of CS-related ccRCC.

Annexin A2 and Kidney Diseases

Annexin A2 is a Ca²⁺- and phospholipid-binding protein which is widely expressed in various types of cells and tissues. As a multifunctional molecule, annexin A2 is found to be involved in diverse cell functions and processes, such as cell exocytosis, endocytosis, migration and proliferation. As a receptor of plasminogen and tissue plasminogen activator, annexin A2 promotes plasmin generation and regulates the homeostasis of blood coagulation, fibrinolysis and matrix degradation. As an antigen expressed on cell membranes, annexin A2 initiates local inflammation and damage through binding to auto-antibodies. Annexin A2 also mediates multiple signaling pathways induced by various growth factors and oxidative stress. Aberrant expression of annexin A2 has been found in numerous kidney diseases. Annexin A2 has been shown to act as a co-receptor of integrin CD11b mediating NF-kB-dependent kidney inflammation, which is further amplified through annexin A2/NF-kB-triggered macrophage M2 to M1 phenotypic change. It also modulates podocyte cytoskeleton rearrangement through Cdc42 and Rac1/2/3 Rho pathway causing proteinuria. Thus, annexin A2 is implicated in the pathogenesis and progression of various kidney diseases. In this review, we focus on the current understanding of the role of annexin A2 in kidney diseases.

Expression and prognosis analysis of PAQR5 in kidney cancer

Progestin and adipoQ receptor 5 (PAQR5) affects the development of various malignancies and is specifically expressed in kidney. However, the role of PAQR5 in renal carcinoma remains unclear. We assessed the state of PAQR5 expression in kidney renal clear cell carcinoma (KIRC) by The Cancer Genome Atlas and Gene Expression Omnibus datasets. Moreover, immunohistochemistry was performed to observe the expressions of PAQR5 protein in tumor tissues. The relationships between PAQR5 expression and clinical characteristics were investigated by UALCAN. Gene Expression Profiling Interactive Analysis (GEPIA) and Kaplan–Meier plotter were used to analyze the effect of PAQR5 expression levels on overall survival and relapse-free survival (RFS). The re lationships between clinical characteristics and survival were also evaluated by univariate and multifactorial Cox regression. Gene Ontology term analysis, Kyoto Encyclopedia of Genes and Genomes analysis, and gene set enrichment analysis were performed on PAQR5 to explain the enrichment pathways and functions. Protein and protein interactions were explained by GeneMANIA and STRING. We also explored the relevance of PAQR5 to tumor immune cell infiltration and immunomodulatory molecules by TIMER and GEPIA. Finally, we explored the correlation of PAQR5 with the pathway proteins STATs, HIF-1α, and mTOR using the GSE40435 dataset. PAQR5 expression was low in KIRC and correlated significantly with clinical characteristics including cancer stage, tumor grade, and nodal metastasis status. Low PAQR5 expression was significantly associated with poorer survival. Cox regression analysis indicated that upregulation of PAQR5 was an independent factor for a good prognosis of KIRC. PAQR5 downregulation was associated mainly with STAT3 target upregulation, tumorigenesis, and poor differentiation. PAQR5 expression also correlated positively with B cells, neutrophils, macrophages, and dendritic cells and negatively with the infiltration of FOXP3⁺ Treg cells and the immune checkpoint molecules PD-1, CTLA4, and LAG3. Moreover, PAQR5 expression in KIRC was negatively correlated with the pathway proteins STAT1/2/3/4/5A, HIF-1α, and mTOR. PAQR5 is an excellent predictor of KIRC prognosis and may be a potential molecular therapeutic target.

The Extracellular Matrix Environment of Clear Cell Renal Cell Carcinoma

Simple Summary

The extracellular matrix (ECM) controls fundamental properties of tumors, including growth, blood vessel investment, and invasion. The ECM defines rigidity of tumor tissue and individual ECM proteins have distinct biological effects on tumor cells. This article reviews the composition and biological functions of the ECM of clear cell renal cell carcinoma (ccRCC). The most frequent initiating genetic mutation in ccRCC inactivates the VHL gene, which plays a direct role in organizing the ECM. This is predicted to result in local ECM modification, which promotes the growth of tumor cells and the invasion of blood vessels. Later in tumor growth, connective tissue cells are recruited, which are predicted to produce large amounts of ECM, affecting the growth and invasive behaviors of tumor cells. Strategies to therapeutically control the ECM are under active investigation and a better understanding of the ccRCC ECM will determine the applicability of ECM-modifying drugs to this type of cancer.

Abstract

The extracellular matrix (ECM) of tumors is a complex mix of components characteristic of the tissue of origin. In the majority of clear cell renal cell carcinomas (ccRCCs), the tumor suppressor VHL is inactivated. VHL controls matrix organization and its loss promotes a loosely organized and angiogenic matrix, predicted to be an early step in tumor formation. During tumor evolution, cancer-associated fibroblasts (CAFs) accumulate, and they are predicted to produce abundant ECM. The ccRCC ECM composition qualitatively resembles that of the healthy kidney cortex in which the tumor arises, but there are important differences. One is the quantitative difference between a healthy cortex ECM and a tumor ECM; a tumor ECM contains a higher proportion of interstitial matrix components and a lower proportion of basement membrane components. Another is the breakdown of tissue compartments in the tumor with mixing of ECM components that are physically separated in healthy kidney cortex. Numerous studies reviewed in this work reveal effects of specific ECM components on the growth and invasive behaviors of ccRCCs, and extrapolation from other work suggests an important role for ECM in controlling ccRCC tumor rigidity, which is predicted to be a key determinant of invasive behavior.

A Causal Framework for Making Individualized Treatment Decisions in Oncology

Simple Summary

Physicians routinely make individualized treatment decisions by accounting for the joint effects of patient prognostic covariates and treatments on clinical outcomes. Ideally, this is performed using historical randomized clinical trial (RCT) data. Randomization ensures that unbiased estimates of causal treatment effect parameters can be obtained from the historical RCT data and used to predict each new patient’s outcome based on the joint effect of their baseline covariates and each treatment being considered. However, this process becomes problematic if a patient seen in the clinic is very different from the patients who were enrolled in the RCT. That is, if a new patient does not satisfy the entry criteria of the RCT, then the patient does not belong to the population represented by the patients who were studied in the RCT. In such settings, it still may be possible to utilize the RCT data to help choose a new patient’s treatment. This may be achieved by combining the RCT data with data from other clinical trials, or possibly preclinical experiments, and using the combined dataset to predict the patient’s expected outcome for each treatment being considered. In such settings, combining data from multiple sources in a way that is statistically reliable is not entirely straightforward, and correctly identifying and estimating the effects of treatments and patient covariates on clinical outcomes can be complex. Causal diagrams provide a rational basis to guide this process. The first step is to construct a causal diagram that reflects the plausible relationships between treatment variables, patient covariates, and clinical outcomes. If the diagram is correct, it can be used to determine what additional data may be needed, how to combine data from multiple sources, how to formulate a statistical model for clinical outcomes as a function of treatment and covariates, and how to compute an unbiased treatment effect estimate for each new patient. We use adjuvant therapy of renal cell carcinoma to illustrate how causal diagrams may be used to guide these steps.

Abstract

We discuss how causal diagrams can be used by clinicians to make better individualized treatment decisions. Causal diagrams can distinguish between settings where clinical decisions can rely on a conventional additive regression model fit to data from a historical randomized clinical trial (RCT) to estimate treatment effects and settings where a different approach is needed. This may be because a new patient does not meet the RCT’s entry criteria, or a treatment’s effect is modified by biomarkers or other variables that act as mediators between treatment and outcome. In some settings, the problem can be addressed simply by including treatment–covariate interaction terms in the statistical regression model used to analyze the RCT dataset. However, if the RCT entry criteria exclude a new patient seen in the clinic, it may be necessary to combine the RCT data with external data from other RCTs, single-arm trials, or preclinical experiments evaluating biological treatment effects. For example, external data may show that treatment effects differ between histological subgroups not recorded in an RCT. A causal diagram may be used to decide whether external observational or experimental data should be obtained and combined with RCT data to compute statistical estimates for making individualized treatment decisions. We use adjuvant treatment of renal cell carcinoma as our motivating example to illustrate how to construct causal diagrams and apply them to guide clinical decisions.

Prognostic value, DNA variation and immunologic features of a tertiary lymphoid structure-related chemokine signature in clear cell renal cell carcinoma

BACKGROUND

The tumor microenvironment (TME) and tertiary lymphoid structures (TLS) affect the occurrence and development of cancers. How the immune contexture interacts with the phenotype of clear cell renal cell carcinoma (ccRCC) remains unclear.

METHODS

We identified and evaluated TLS clusters in ccRCC using machine learning algorithms and the 12-chemokine gene signature for TLS. Analyses for functional enrichment, DNA variation, immune cell distribution, association with independent clinicopathological features and predictive value of CXCL13 in ccRCC were performed.

RESULTS

We found a prominently enrichment of the 12-chemokine gene signature for TLS in patients with ccRCC compared with other types of renal cell carcinoma. We identified a prognostic value of CCL4, CCL5, CCL8, CCL19 and CXCL13 expression in ccRCC. DNA deletion of the TLS gene signature significantly predicted poor outcome in ccRCC compared with amplification and wild-type gene signature. We established TLS clusters (C1-4) and observed distinct differences in survival, stem cell-like characteristics, immune cell distribution, response to immunotherapies and VEGF-targeted therapies among the clusters. We found that elevated CXCL13 expression significantly predicted aggressive progression and poor prognosis in 232 patients with ccRCC in a real-world validation cohort.

CONCLUSION

This study described a 12-chemokine gene signature for TLS in ccRCC and established TLS clusters that reflected different TME immune status and corresponded to prognosis of ccRCC. We confirmed the dense presence of TILs aggregation and TLS in ccRCC and demonstrated an oncogenic role of CXCL13 expression of ccRCC, which help develop immunotherapies and provide novel insights on the long-term management of ccRCC.

Immune checkpoint inhibitor-based therapy for advanced clear cell renal cell carcinoma: A narrative review

The prognosis for advanced clear cell renal cell carcinoma (ccRCC) is not satisfactory, even though its treatment has evolved rapidly over the past 20 years. Systemic ccRCC treatment options mainly involve antiangiogenic therapy, immune checkpoint blockade, or a combination of these therapies, and as more clinical evidence becomes available, immune checkpoint inhibitors (ICIs) are increasingly dominant. Conventional ICIs lead to the restoration of T-cell activation and a reduction in T-cell depletion by specifically blocking programmed cell death 1 (PD-1), programmed cell death 1 ligand 1 (PD-L1) or cytotoxic T lymphocyte antigen 4 (CTLA-4), ultimately enhancing the antitumor immune response. There is no doubt that these therapies have achieved some clinical efficacy in the overall ccRCC population, but response rates and durability remain a great challenge. Therefore, novel immune checkpoints or new combination therapeutic strategies based on ICIs continue to be sought and developed. This review will provide a comprehensive overview of ICI-based therapeutic strategies in advanced ccRCC, including their mechanisms of action and the latest clinical evidence.

A Molecularly Characterized Preclinical Platform of Subcutaneous Renal Cell Carcinoma (RCC) Patient-Derived Xenograft Models to Evaluate Novel Treatment Strategies

Renal cell carcinoma (RCC) is a kidney cancer with an onset mainly during the sixth or seventh decade of the patient’s life. Patients with advanced, metastasized RCC have a poor prognosis. The majority of patients develop treatment resistance towards Standard of Care (SoC) drugs within months. Tyrosine kinase inhibitors (TKIs) are the backbone of first-line therapy and have been partnered with an immune checkpoint inhibitor (ICI) recently. Despite the most recent progress, the development of novel therapies targeting acquired TKI resistance mechanisms in advanced and metastatic RCC remains a high medical need. Preclinical models with high translational relevance can significantly support the development of novel personalized therapies. It has been demonstrated that patient-derived xenograft (PDX) models represent an essential tool for the preclinical evaluation of novel targeted therapies and their combinations. In the present project, we established and molecularly characterized a comprehensive panel of subcutaneous RCC PDX models with well-conserved molecular and pathological features over multiple passages. Drug screening towards four SoC drugs targeting the vascular endothelial growth factor (VEGF) and PI3K/mTOR pathway revealed individual and heterogeneous response profiles in those models, very similar to observations in patients. As unique features, our cohort includes PDX models from metastatic disease and multi-tumor regions from one patient, allowing extended studies on intra-tumor heterogeneity (ITH). The PDX models are further used as basis for developing corresponding in vitro cell culture models enabling advanced high-throughput drug screening in a personalized context. PDX models were subjected to next-generation sequencing (NGS). Characterization of cancer-relevant features including driver mutations or cellular processes was performed using mutational and gene expression data in order to identify potential biomarker or treatment targets in RCC. In summary, we report a newly established and molecularly characterized panel of RCC PDX models with high relevance for translational preclinical research.

A Novel Biomarker, FKBP10, for Poor Prognosis Prediction in Patients with Clear Cell Renal Cell Carcinoma

Objective

To screen genes associated with poor prognosis of clear cell renal cell carcinoma (CcRCC) from the public databases HPA (Human Protein Atlas), UALCAN, and GEPIA (Gene Expression Profiling Interactive Analysis) and to investigate the expression of FKBP10 in CcRCC and the effect on prognosis of the patients and the biological behavior of CcRCC cells.

Methods

The tumor tissues and adjacent noncancerous tissues of 42 patients with CcRCC diagnosed and treated in our hospital were collected, and the general information of the patients was recorded. FKBP10 expression in the tissues was determined by qRT-PCR and western blot, and its relationship with general information and prognosis of patients was analyzed. Knockdown or overexpression experiments were carried out with the human proximal tubule epithelial cell line HK-2 and CcRCC cell lines Caki-1, 786-O, ACHN, and A498 to verify the relationship between FKBP10 expression and cell proliferation and adhesion ability using MTT assay and fibronectin adhesion assay, respectively. Western blot was utilized to examine the protein expression level of c-Myc, cyclin D1, and Bcl-2 in the cells.

Results

FKBP10 was highly expressed in CcRCC tissues and cells and was correlated with poor prognosis. In addition, FKBP10 expression was positively correlated with CcRCC tumor size and staging and negatively correlated with tumor differentiation. Moreover, knockdown of FKBP10 significantly inhibited the proliferation of CcRCC cells, notably declined the protein expression of c-Myc, cyclin D1, and Bcl-2, and promoted cell adhesion.

Conclusion

FKBP10 is highly expressed in CcRCC tissues and cells and is associated with poor prognosis in patients. FKBP10 participated in the occurrence and development of CcRCC by promoting cell proliferation and inhibiting apoptosis and adhesion.

Multi-Omics Analysis of the Prognosis and Biological Function for TRPV Channel Family in Clear Cell Renal Cell Carcinoma

Background

The transient receptor potential vanilloid (TRPV) channels family, TRPV1-6, has been identified to profoundly affect a wide spectrum of pathological processes in various cancers. However, the biological function and prognostic value of TRPVs in clear cell renal cell carcinoma (ccRCC) are still largely unknown.

Methods

We obtained the gene expression data and clinical information of 539 ccRCC patients from The Cancer Genome Atlas (TCGA) database. A series of databases were used for data processing and visualization, including GEPIA, GeneMANIA, MethSurv, GSCA, TIMER, and starBase databases.

Results

The mRNA expression of TRPV2/3 was upregulated while the expression of TRPV5/6 was downregulated in ccRCC tumor tissues. TRPV family members in ccRCC were rarely mutated (nearly 7 frequencies). The ROC curve showed that TRPV2/5/6 had a high diagnostic ability in discriminating ccRCC from the control samples (AUC>0.9). Higher levels of TRPV3 expression were associated with poor prognosis of ccRCC patients, while higher expression of TRPV4 was associated with favorable prognosis. The expression of TRPV3 in normal and ccRCC tissues was validated by Immunohistochemistry, and its expression was remarkably related to high histologic grade and advanced stage. Besides, TRPV3 exhibit a reduction of DNA methylation level with tumor progression, and 12 CpGs of TRPV3 were associated with a significant prognosis. In addition, TRPV3 expression was significantly associated with the accumulation of several tumor-infiltrating immune cells, especially regulatory T cells. Furthermore, high levels of TRPV3 induced the expression of immune checkpoints such as LAG3, CTLA4, PDCD1, and TIGIT. Finally, we predicted a key SNHG3/AL513497.1-miR-10b-5p-TRPV3 axis linking to carcinogenesis and progression of ccRCC.

Conclusion

Our study may uncover TRPV channels–associated molecular mechanisms involved in the tumorigenesis and progression of ccRCC. TRPV family members might be diagnosed and prognostic markers and potential therapeutic targets for ccRCC patients.

LncRNA LNCOC1 is Upregulated in Melanoma and Serves as a Potential Regulatory Target of miR-124 to Suppress Cancer Cell Invasion and Migration

Background

A cascade of genes and pathways have been reported in the precise regulation of malignant melanoma (MM). Previous study has demonstrated that lncRNA LNCOC1 is an oncogenic factor in the pathogenesis and development of various cancers. The present study explored the functionalities of LNCOC1 and its interactions with miR-124 in MM.

Methods

A total of 65 melanoma patients were enrolled in this study. The expression of LNCOC1 and miR-124 after cell transfection were detected by RT-qPCR. The migration rates of SK-MEL-3 and A375 cells after transient transfection with LNCOC1 expression vector and miR-124 mimic was detected by trans-well assay.

Results

LNCOC1 was accumulated to high levels in melanoma, and it was significantly correlated with the low survival rate of melanoma patients. Our bioinformatics data showed that miR-124 could target LNCOC1. Overexpression of miR-124 could downregulate LNCOC1. However, up-regulated the expression of LNCOC1 did not affect the expression of miR-124. Our correlation analysis also revealed that the expression of LNCOC1 and miR-124 were inversely correlated in both melanoma tissues and non-tumor tissues. The trans-well invasion and migration assays indicated that overexpression of miR-124 inhibited the melanoma cell invasion and migration. However, overexpression of LNCOC1 promoted melanoma cell invasion and migration.

Conclusion

LNCOC1 is upregulated in melanoma, which can be considered as a potential target of miR-124 in modulating melanoma cell invasion and migration. LNCOC1 may also be an interfering target of MM therapy.

Models of Renal Cell Carcinoma Used to Investigate Molecular Mechanisms and Develop New Therapeutics

Modeling renal cell carcinoma is critical to investigating tumor biology and therapeutic mechanisms. Multiple systems have been developed to represent critical components of the tumor and its surrounding microenvironment. Prominent in vitro models include traditional cell cultures, 3D organoid models, and microphysiological devices. In vivo models consist of murine patient derived xenografts or genetically engineered mice. Each system has unique advantages as well as limitations and researchers must thoroughly understand each model to properly investigate research questions. This review addresses common model systems for renal cell carcinoma and critically evaluates their performance and ability to measure tumor characteristics.

Crosstalk Between Metabolism and Immune Activity Reveals Four Subtypes With Therapeutic Implications in Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is characterized by metabolic dysregulation and distinct immunological signatures. The interplay between metabolic and immune processes in the tumor microenvironment (TME) causes the complexity and heterogeneity of immunotherapy responses observed during ccRCC treatment. Herein, we initially identified two distinct metabolic subtypes (C1 and C2 subtypes) and immune subtypes (I1 and I2 subtypes) based on the occurrence of differentially expressed metabolism-related prognostic genes and immune-related components. Notably, we observed that immune regulators with upregulated expression actively participated in multiple metabolic pathways. Therefore, we further delineated four immunometabolism-based ccRCC subtypes (M1, M2, M3, and M4 subtypes) according to the results of the above classification. Generally, we found that high metabolic activity could suppress immune infiltration. Immunometabolism subtype classification was associated with immunotherapy response, with patients possessing the immune-inflamed, metabolic-desert subtype (M3 subtype) that benefits the most from immunotherapy. Moreover, differences in the shifts in the immunometabolism subtype after immunotherapy were observed in the responder and non-responder groups, with patients from the responder group transferring to subtypes with immune-inflamed characteristics and less active metabolic activity (M3 or M4 subtype). Immunometabolism subtypes could also serve as biomarkers for predicting immunotherapy response. To decipher the genomic and epigenomic features of the four subtypes, we analyzed multiomics data, including miRNA expression, DNA methylation status, copy number variations occurrence, and somatic mutation profiles. Patients with the M2 subtype possessed the highest VHL gene mutation rates and were more likely to be sensitive to sunitinib therapy. Moreover, we developed non-invasive radiomic models to reveal the status of immune activity and metabolism. In addition, we constructed a radiomic prognostic score (PRS) for predicting ccRCC survival based on the seven radiomic features. PRS was further demonstrated to be closely linked to immunometabolism subtype classification, immune score, and tumor mutation burden. The prognostic value of the PRS and the association of the PRS with immune activity and metabolism were validated in our cohort. Overall, our study established four immunometabolism subtypes, thereby revealing the crosstalk between immune and metabolic activities and providing new insights into personal therapy selection.

Dissection of PD-L1 promoter reveals differential transcriptional regulation of PD-L1 in VHL mutant clear cell renal cell carcinoma

Programmed death-ligand 1 (PD-L1) is constitutively expressed by hypoxia-inducible factor 2α (HIF2α). It can be induced by interferon gamma (IFNγ) signaling in clear cell renal cell carcinoma (ccRCC). Clinical trials of metastatic ccRCCs have suggested that a canonical IFNγ signature is a better biomarker for therapeutic response to immune checkpoint inhibitors (ICIs) than PD-L1 expression levels in tumor cells. To understand the therapeutic response to ICIs according to PD-L1 expression levels, we analyzed transcriptional regulation of the PD-L1 promoter by HIF2α and IFNγ-inducible interferon regulatory factor-1 (IRF-1) in ccRCC cells. Here, we present two ccRCC cell models showing differential PD-L1 expression levels in response to IFNγ and hypoxia. Analysis of The Cancer Genome Atlas RNA-sequencing data revealed that PD-L1 expression correlated with JAK2 and STAT1 expression of the canonical IFNγ signature in ccRCC tissues. Upon IFNγ stimulation, PD-L1 was induced by sequential activation of JAK2/STAT1/IRF-1 signaling in both WT- and Mut- VHL ccRCC cells. IFNγ activated the IRF-1α site of the PD-L1 promoter. The IFNγ-mediated increase of PD-L1 expression in Mut-VHL cells was 4.8-fold greater than that in WT-VHL cells. Under normoxia condition, PD-L1 expression in Mut-VHL cells was significantly higher than that in WT-VHL cells due to high basal HIF2α expression. Under hypoxia condition, PD-L1 expression in WT-VHL cells was induced up to 1.8-fold through activation of hypoxia-response elements 2 and 3. In contrast, although PD-L1 in Mut-VHL cells was already highly expressed in the basal state through activation of hypoxia-response elements 2, 3, and 4, it was no longer induced by hypoxia. In conclusion, Mut-VHL ccRCC cells displayed higher PD-L1 expression due to high basal HIF2α expression and a stronger response to IFNγ stimulation than WT-VHL cells. The fact that HIF2α antagonists can potentially reduce PD-L1 expression levels should be considered in ICI combination therapy.

A Novel Pyroptosis-Related Prognostic Signature for Risk Stratification and Clinical Prognosis in Clear Cell Renal Cell Carcinoma

Emerging research has substantiated that pyroptosis-related biomarkers were mightily related to the clinical outcome of patients with clear cell renal cell carcinoma (ccRCC). However, a single-gene biomarker's moderate predictive power is insufficient, and more accurate prognostic models are urgently needed. We conducted this investigation in order to develop a robust pyroptosis-related gene signature for use in risk stratification and survival prognosis in colorectal cancer. We downloaded transcriptomic data and survival information of ccRCC patients from TCGA. Bioinformatic methods were used to generate a pyroptosis-related gene signature based on data from TCGA training cohort. ROC curve, uni- and multivariate regression analyses were used for the prognostic assays. What is more, we explored the relationship between model-based risk score and the tumor microenvironment. Herein, 11 pyroptosis-related hub genes (CASP9, TUBB6, NFKB1, BNIP3, CAPN1, CD14, PRDM1, BST2, SDHB, TFAM, and GSDMB) were determined as risk signature for risk stratification and prognosis prediction for ccRCC. Kaplan-Meier curves, ROC curves, and risk plots were employed to analyze and verify its performance in all groups. Multivariate assays exhibited that risk score could be an independent prognostic factor for patients' OS. ESTIMATE algorithm showed a higher immune score in the group of high-risk. Overall, a novel pyroptosis-related gene signature generated can be employed for prognosis prediction of ccRCC patients. This may assist in individual treatment of clinical decision-making.

Current Advances in RNA Therapeutics for Human Diseases

Following the discovery of nucleic acids by Friedrich Miescher in 1868, DNA and RNA were recognized as the genetic code containing the necessary information for proper cell functioning. In the years following these discoveries, vast knowledge of the seemingly endless roles of RNA have become better understood. Additionally, many new types of RNAs were discovered that seemed to have no coding properties (non-coding RNAs), such as microRNAs (miRNAs). The discovery of these new RNAs created a new avenue for treating various human diseases. However, RNA is relatively unstable and is degraded fairly rapidly once administered; this has led to the development of novel delivery mechanisms, such as nanoparticles to increase stability as well as to prevent off-target effects of these molecules. Current advances in RNA-based therapies have substantial promise in treating and preventing many human diseases and disorders through fixing the pathology instead of merely treating the symptomology similarly to traditional therapeutics. Although many RNA therapeutics have made it to clinical trials, only a few have been FDA approved thus far. Additionally, the results of clinical trials for RNA therapeutics have been ambivalent to date, with some studies demonstrating potent efficacy, whereas others have limited effectiveness and/or toxicity. Momentum is building in the clinic for RNA therapeutics; future clinical care of human diseases will likely comprise promising RNA therapeutics. This review focuses on the current advances of RNA therapeutics and addresses current challenges with their development.

RNA-binding protein MEX3A controls G1/S transition via regulating the RB/E2F pathway in clear cell renal cell carcinoma

MEX3A is an RNA-binding protein that mediates mRNA decay through binding to 3′ untranslated regions. However, its role and mechanism in clear cell renal cell carcinoma remain unknown. In this study, we found that MEX3A expression was transcriptionally activated by ETS1 and upregulated in clear cell renal cell carcinoma. Silencing MEX3A markedly reduced clear cell renal cell carcinoma cell proliferation in vitro and in vivo. Inhibiting MEX3A induced G1/S cell-cycle arrest. Gene set enrichment analysis revealed that E2F targets are the central downstream pathways of MEX3A. To identify MEX3A targets, systematic screening using enhanced cross-linking and immunoprecipitation sequencing, and RNA-immunoprecipitation sequencing assays were performed. A network of 4,000 genes was identified as potential targets of MEX3A. Gene ontology analysis of upregulated genes bound by MEX3A indicated that negative regulation of the cell proliferation pathway was highly enriched. Further assays indicated that MEX3A bound to the CDKN2B 3′ untranslated region, promoting its mRNA degradation. This leads to decreased levels of CDKN2B and an uncontrolled cell cycle in clear cell renal cell carcinoma, which was confirmed by rescue experiments. Our findings revealed that MEX3A acts as a post-transcriptional regulator of abnormal cell-cycle progression in clear cell renal cell carcinoma.

MCM3AP-AS1: A LncRNA Participating in the Tumorigenesis of Cancer Through Multiple Pathways

Background:

More and more shreds of evidence show that the occurrence and development of tumors are closely related to the abnormal expression of LncRNA. A large number of experiments have found that overexpression or under-expression of MCM3AP-AS1 can affect the occurrence and development of cancer cells in varying degrees, such as proliferation, invasion, and translocation. Besides, MCM3AP-AS1 may become a promising target for many tumor biotherapies. This article reviews the pathophysiological functions and molecular mechanisms of MCM3AP-AS1 in various tumors.

Methods:

This paper systematically summarizes the published literatures in PubMed. The molecular mechanism of MCM3AP-AS1 in a variety of tumors is reviewed.

Results:

The abnormal expression of MCM3AP-AS1 in different tumors is closely related to tumor proliferation, invasion, and migration. MCM3AP-AS1 mediates or participates in related signaling pathways to regulate the expression of targeted miRNAs and proteins. MCM3AP-AS1 plays a vital role in tumor diagnosis and treatment.

Conclusion:

LncRNA MCM3AP-AS1 is a feasible tumor marker and a potential therapeutic target for many kinds of tumors.

YAP1 activation promotes epithelial-mesenchymal transition and cell survival of renal cell carcinoma cells under shear stress

Renal cell carcinoma (RCC) is characterized by substantial vasculatures and increased fluid movement in tumor microenvironment, and the fluid shear stress modulates malignance, extravasation and metastatic seeding of tumor cells. However, the precise mechanism remains largely unclear. In this study, we found that low shear stress induced the Yes-associated protein (YAP1) activation and nuclear localization in RCC cells, as well as the downregulation of phosphorylated YAP1 at Ser127. Moreover, inhibition of ROCK or RhoA partially abolished YAP1 accumulation in the nucleus, and targeting YAP1 activation by small molecular inhibitor or genetic manipulation decreased the low shear stress-induced epithelial-mesenchymal transition (EMT) of RCC cells, and led to a decreased expression of N-cadherin as accompanied by downregulation of Snail1 and Twist, accompanied by high shear stress-induced cell apoptosis. Salvianolic acid B, an aqueous component of danshen (Salvia miltiorrhiza), inhibited YAP1 and Hippo signaling activation, and abrogated low shear stress-induced EMT as a consequence. Taken together, our study suggests YAP1 is a fluid mechanosensor that transforms mechanical stimuli to cell signals, thereby facilitates anoikis resistance and tumor metastasis.

Clinical Study on the Efficacy of Microwave Ablation (MA) in the Treatment of Stage I Renal Clear Cell Carcinoma by CT and MRI Imaging

We have proposed an effective mechanism to corroborate the efficacy of microwave ablation (MA) in the treatment of stage I renal clear cell carcinoma in this paper. For this purpose, a total of 96 patients with stage I renal clear cell carcinoma presented in our hospital from May 2018 to January 2021 were randomly divided into CT group (n = 48) and MRI group (n = 48). Patients in both groups were treated with microwave ablation after pathological diagnosis. Patients in the CT group received enhanced CT examination to monitor the therapeutic effect; in contrast, patients in the MRI group received MRI examination to monitor their therapeutic effect. The focus areas before and after tumor microwave ablation were compared between the two groups. The patients were followed up to 1 year after the operation, and the microwave ablation inactivation rates of the two groups were compared according to the postoperative follow-up results. There was no significant difference between CT and MRI in the levels of long and short diameter before and after microwave ablation of renal clear cell carcinoma (P > 0.05). In the CT group, CT examination was performed within 24 hours after microwave ablation treatment, and 44 of 48 ablation lesions showed complete ablation. The remaining 4 lesions showed nodular heterogeneous enhancement in the arterial phase, indicating that the tumor remained. Microwave ablation was performed on the residual lesions during the operation, and then enhanced CT was performed again to show that the lesions were ablated completely. In the MRI group, MRI examination was performed within 24 hours after microwave ablation treatment, and 45 of 48 ablation lesions showed complete ablation. The remaining 3 lesions showed nodular heterogeneous enhancement in the arterial phase, indicating that the tumor remained. Microwave ablation was performed on the residual lesions during the operation, and MRI examination showed that the lesions were ablated completely. The patients were followed up to 1 year after the operation, and the microwave ablation inactivation rate of the two groups was compared according to the postoperative follow-up results as the gold standard. The inactivation rate of microwave ablation in the CT group was 89.58 (43/48). The inactivation rate of microwave ablation in the MRI group was 100.00% (48/48). The inactivation rate of microwave ablation in the MRI group was higher than that in the CT group (χ² = 5.275, P = 0.021).

Inflammation-Related Gene Signature: An Individualized Risk Prediction Model for Kidney Renal Clear Cell Carcinoma

Background. There is much evidence that confirms the inextricable link between inflammation and malignancy. Inflammation-related regulators were involved in the progression of kidney renal clear cell carcinoma (KIRC). However, the predictive role of single gene biomarkers is inadequate, and more accurate prognostic models are necessary. We undertook the current research to construct a robust inflammation-related gene signature that could stratify patients with KIRC. Methods. The transcriptome sequencing data along with clinicopathologic information of KIRC were obtained from TCGA. A list of inflammation-related genes was acquired from the Molecular Signatures Database. Using the RNA-seq and survival time data from the TCGA training cohort, an inflammation-related gene signature was built using bioinformatic methods, and its performance in predicting patient prognosis was assessed by Kaplan–Meier and ROC curve analyses. Furthermore, we explored the association of risk score with immune score, stromal score, tumor immune-infiltrating cells (TIICs), immunosuppressive molecules, m6A regulators, and autophagy-related biomarkers. Results. Herein, nine inflammation-related hub genes (ROS1, PLAUR, ACVR2A, KLF6, GABBR1, APLNR, SPHK1, PDPN, and ADORA2B) were determined and used to build a predictive model. All sets, including training set, four testing sets, and the entire TCGA group, were divided into two groups (low and high risk), and Kaplan–Meier curves all showed an adverse prognosis for patients in the high-risk group. ESTIMATE algorithm revealed a higher immune score in the high-risk subgroup. CIBERSORT algorithm illustrated that the high-risk group showed higher-level immune infiltrates. Furthermore, LAG3, TIGIT, and CTLA4 were overexpressed in the high-risk subgroup and positively associated with risk scores. Moreover, except for METTL3 and ALKBH5, the other m6A regulators decreased in the high-risk subgroup. Conclusions. In conclusion, a novel inflammation-related gene signature comprehensively constructed in the current study may help stratify patients with KIRC.

HIF-1α Induces HECTD2 Up-Regulation and Aggravates the Malignant Progression of Renal Cell Cancer via Repressing miR-320a

Renal cell carcinoma (RCC) is a frequent malignancy of the urinary system. It has been found that hypoxia mediates the malignant evolvement of RCC. Here, we probe the impact and potential mechanism of HECT domain E3 ubiquitin-protein ligase 2 (HECTD2) and HIF-1α on regulating RCC evolvement. RCC tissues and adjacent normal tissues were collected, and the association between the expression profiles of HECTD2 and HIF-1α and the clinicopathological features was analyzed. Additionally, we constructed HECTD2/HIF-1α overexpression and knockdown models in RCC cell lines to ascertain the impacts of HECTD2 and HIF-1α on RCC cell proliferation, apoptosis, migration, and growth in vivo. We applied bioinformatics to predict the upstream miRNA targets of HECTD2. Meanwhile, RNA immunoprecipitation (RIP), and the dual-luciferase reporter assays were employed to clarify the targeting association between HECTD2 and miR-320a. The effect of miR-320a on HECTD2-mediated RCC progression was investigated. The results suggested that both HIF-1α and HECTD2 were up-regulated in RCC (compared with adjacent non-tumor tissues), and they had positive relationship. Moreover, higher level of HECTD2 and HIF-1α is associated with poorer overall survival of RCC patients. HECTD2 overexpression heightened RCC cell proliferation and migration, and weakened cell apoptosis. On the other hand, the malignant phenotypes of RCC cells were signally impeded by HECTD2 or HIF-1α knockdown. Moreover, miR-320a targeted the 3'-untranslated region of HECTD2 and suppressed HECTD2 expression. The rescue experiments showed that miR-320a restrained HECTD2-mediated malignant progression in RCC, while up-regulation of HIF-1α hampered miR-320a expression. Collectively, HIF-1α mediated HECTD2 up-regulation and aggravated RCC progression by attenuating miR-320a.

ZNF668: a new diagnostic predictor of kidney renal clear cell carcinoma

The most common pathological subtype of renal carcinoma is RCC, and its development is closely related to immune infiltration. In our study, we investigated the relationship between zinc finger protein 668 and the prognostic risk, clinical characteristics, overall survival and related pathways. We analyzed the association between ZNF668 and immune cell infiltration through the TIMER database. The results showed that the expression of ZNF668 in RCC was higher than that in normal tissues (P < 0.001). The high expression of ZNF668 is clinically relevant, such as tumor stage (P = 0.001) and TNM classification (T: P = 7.37 e-04; N: P = 0.008; M: P < 0.001). Survival analysis showed that patients with high ZNF668 expression had a significantly poor prognosis (P = 0.023). Univariate analysis showed a significant decrease in overall survival in RCC patients with high ZNF668 expression (P = 0.023). Immuno-cell infiltration showed a significant decrease in CD4+ T cell and dendritic cell infiltration in RCC patients with high expression of ZNF668. GO/KEGG analysis showed that multiple pathways were differentially enriched in the high expression pathway of ZNF668, such as complement activation, and estrogen signaling pathway. In conclusion, high ZNF668 expression is a predictor in RCC.

Microenvironment-associated gene HSD11B1 may serve as a prognostic biomarker in clear cell renal cell carcinoma: a study based on TCGA, RT‑qPCR, Western blotting, and immunohistochemistry

Clear cell renal cell carcinoma (ccRCC) is one of the most common malignant tumors worldwide. The clinical treatment of ccRCC is strongly associated with the tumor microenvironment (TME). Identifying potential markers of ccRCC is important to improve prognosis. Therefore, in the present study, the levels of immune/stromal components and the proportion of tumor-infiltrating immune cells (TIICs) were determined in 611 ccRCC samples using the ESTIMATE and CIBERSORT analytical tools. Subsequently, hydroxysteroid 11-beta dehydrogenase-1 (HSD11B1) was identified by univariate Cox regression analysis, protein-protein interaction (PPI) networks and clinical survival analysis to be associated with ccRCC prognosis. At the same time, the abundance of HSD11B1 increased significantly in ccRCC was verified by western blotting, RT‑qPCR and immunostaining analysis. Furthermore, Gene Set Enrichment Analysis (GSEA) and TME suggested that HSD11B1 was involved in TME immune-related status. Taken together, the results of the present study demonstrated that HSD11B1 is a potential prognostic biomarker associated with immune cell infiltration in ccRCC.

LINC01232 serves as a novel biomarker and promotes tumour progression by sponging miR-204-5p and upregulating RAB22A in clear cell renal cell carcinoma

BACKGROUND

Long non-coding RNAs (lncRNAs) are involved in the progression of various cancers, including clear cell renal cell carcinoma (ccRCC). This study aimed to investigate the expression and prognostic value of long intergenic non-protein coding RNA (LINC) 01232 in ccRCC and preliminary explore the molecular mechanism underlying the role of LINC01232 in ccRCC progression.

METHODS

Tumour tissues and adjacent normal tissues of 122 patients with ccRCC were collected in this study. The levels of LINC01232, microRNA (miR)-204-5p and RAB22A were measured by quantitative real-time PCR. The proliferation, migration and invasion of ccRCC cells were detected by cell counting kit-8 assay and Transwell assay, respectively. The interaction among LINC01232, miR-204-5p and RAB22A was confirmed by bioinformatics analysis, dual-luciferase reporter assay and Pearson correlation analysis. The association of LINC01232 and miR-204-5p with ccRCC patient survival was verified by the Kaplan-Meier method and log-rank test. The prognostic value of LINC01232 in ccRCC was confirmed by Cox regression analysis.

RESULTS

LINC01232 expression was increased in ccRCC tumour tissues and ccRCC cells and independently predicted the prognosis of ccRCC patients. In addition, LINC01232 silencing inhibited ccRCC cell proliferation, migration and invasion. Moreover, LINC01232 served as a sponge for miR-204-5p, and miR-204-5p reduction reversed the inhibitory effect of LINC01232 silencing on ccRCC cell function. Furthermore, LINC01232 could sponge miR-204-5p, causing the elevation of RAB22A in ccRCC, thereby promoting ccRCC cell function.

CONCLUSION

LINC01232 may be an independent prognostic biomarker in ccRCC and plays an oncogenic role in ccRCC progression by sponging miR-204-5p and upregulating RAB22A.

Characteristics of contrast-enhanced ultrasound for diagnosis of solid clear cell renal cell carcinomas ≤4 cm: A meta-analysis

Now solid renal tumors ≤4 cm is the most common, especially the subtype of clear cell renal cell carcinoma (ccRCC) of malignant kidney tumors in clinical. However, there is not specific characteristics of contrast‐enhanced ultrasound (CEUS) be recommended by the EFSUMB Guidelines in distinguish the essence of the kidney tumor with different sizes. Therefore, this meta‐analysis aimed to assess the ability of CEUS to diagnose solid ccRCC (sccRCC) ≤4 cm. We comprehensively searched the Cochrane Library, Embase, PubMed, and Web of Science databases from their inception to 28 July 2020, for studies reporting the CEUS features of sccRCC lesions ≤4 cm. Additional articles were identified through the Chinese National Knowledge Infrastructure database. Studies were selected independently by two investigators and the relevant data were extracted. Discrepancies were resolved via discussion with the senior author. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies‐2 tool, and the sensitivity and specificity of each study were determined and plotted as a receiver operating characteristic curve. Ten studies were included in this meta‐analysis. Hyperenhancement showed medium sensitivity (67%–89%) and specificity (42%–75%) for diagnosing sccRCC ≤4 cm, fast‐in contrast agent and heterogeneous enhancement showed high diagnostic abilities (area under curve (AUC) 0.74–0.84), but the presence of a pseudocapsule and fast‐out contrast agent had poor diagnostic ability (AUC <0.70). The combination of hyperenhancement and iso‐enhancement showed high sensitivity (98%) for diagnosing sccRCC ≤4 cm. Hyperenhancement, fast‐in contrast agent, and heterogeneous enhancement may be specific features that could help to identify sccRCC ≤4 cm, while the presence of a pseudocapsule and fast‐out of contrast agent may have low diagnostic values. The combination of multiple indexes may improve the diagnostic value of CEUS for sccRCC ≤4 cm.

A five-gene methylation signature predicts overall survival of patients with clear cell renal cell carcinoma

BACKGROUND

In this study, we aimed to screen methylation signatures associated with the prognosis of patients with clear cell renal cell carcinoma (ccRCC).

METHODS

Gene expression and methylation profiles of ccRCC patients were downloaded from publicly available databases, and differentially expressed genes (DEGs)-differentially methylated genes (DMGs) were obtained. Subsequently, gene set enrichment and transcription factor (TF) regulatory network analyses were performed. In addition, a prognostic model was constructed and the relationship between disease progression and immunity was analyzed.

RESULTS

A total of 23 common DEGs-DMGs were analyzed, among which 14 DEGs-DMGs were obtained with a cutoff value of PCC < 0 and p < 0.05. The enrichment analysis showed that the 14 DEGs-DMGs were enriched in three GO terms and three KEGG pathways. In addition, a total of six TFs were shown to be associated with the 14 DEGs-DMGs, including RP58, SOX9, NF-κB65, ATF6, OCT, and IK2. A prognostic model using five optimized DEGs-DMGs which efficiently predicted survival was constructed and validated using the GSE105288 dataset. Additionally, four types of immune cells (NK cells, macrophages, neutrophils, and cancer-associated fibroblasts), as well as ESTIMATE, immune, and stromal scores were found to be significantly correlated with ccRCC progression (normal, primary, and metastasis) in addition to the five optimized DEGs-DMGs.

CONCLUSION

A five-gene methylation signature with the predictive ability for ccRCC prognosis was investigated in this study, consisting of CCNB2, CDKN1C, CTSH, E2F2, and ERMP1. In addition, potential targets for methylation-mediated immunotherapy were highlighted.

Long non-coding RNA SNHG3 promotes the progression of clear cell renal cell carcinoma via regulating BIRC5 expression

Background

Research has shown that the progression of clear cell renal cell carcinoma (ccRCC) is modulated by long non-coding RNAs (lncRNAs). However, the roles of specific lncRNAs in the malignancy of ccRCC are still unknown.

Methods

TCGA and GSE66272 datasets were used to predict differentially expressed genes (DEGs) in ccRCC. ENCORI database was employed to display BIRC5 miRNA network and potential lncRNA interactions for miRNAs. KM plotter and correlation analyses were performed to identify the overall survival (OS)- and BIRC5-related miRNAs. Quantitative real-time PCR (qRT-PCR) was used to verify the BIRC5 mRNA in the seventy paired clinical samples of ccRCC tissues. The ccRCC A498 and 786-O were individually transfected with lncRNA SNHG3 and LINC00997 and then western blotting was used to detect the BIRC5 protein expression. The Dual-luciferase reporter assay was used to examine the regulatory interaction between lncRNA SNHG3 and microRNA (miRNA/miR)-10b-5p.

Results

BICR5 is associated with the progression of ccRCC. The two novel lncRNAs (LINC00997, SNHG3) were up-regulated in ccRCC tissues and positively with the BICR5 protein expression. However, Suppressing SNHG3 expression reduced BIRC5 protein expression compared with the LINC00997, most importantly, Suppressing SNHG3 expression suppressed tumor progression in vitro. In addition, SNHG3 promotes the expression of BIRC5 protein by sponging microRNA-10b-5p.

Conclusions

Our findings suggest that SNHG3 plays a vital role in promoting ccRCC via the microRNA-10b-5p/BIRC5 axis and may serve as a novel therapeutic target for the treatment of patients with ccRCC.

The significance of SMARCB1 in the pathogenesis of renal cell carcinoma with rhabdoid features

BACKGROUND

Renal cell carcinoma with rhabdoid features (RCC-RF) is an aggressive histologic variant in the adults and is usually unresponsive to standard chemotherapy.

METHODS

Expression of SMARCB1/INI1 was examined in primary RCC-RF (n = 5). Stable INI1 with/without prostaglandin E2 receptor 1 (EP1) knockdown cell lines were created in the ACHN and 786-O RCC cell lines and measured for epidermal growth factor receptor (EGFR)-related signaling pathways. Chemosensitivity to targeted drugs in vitro was tested after knocking down of INI1 in both cell lines. The outcome of co-targeting of INI1 and EP1 in RCC was examined using a tumorigenicity assay.

RESULTS

Expression of INI1 was markedly reduced at both transcriptional and translational levels in primary RCC-RF. Immunohistochemical expression of INI1 protein was lost in the nuclei of rhabdoid cells compared with conventional RCC (n = 8). Using two cell lines with different genetic background, we showed that knocking down of INI1 activates the EGFR signaling with up-regulated AKT and ERK pathways and sensitizes cancer cells to Erlotinib treatment in vitro. However, cell-line dependent effects were also demonstrated with reference to impact of INI1 or EP1 on cell growth, migration and response to Gefitinib or Everolimus treatment in vitro.

CONCLUSION

Inactivation of INI1 may play a role in the pathogenesis of RCC-RF. Erlotinib is recommended in the management of patients with INI1-related RCC.

Comprehensive Genomic Landscape in Chinese Clear Cell Renal Cell Carcinoma Patients

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcinoma (RCC). The genomic landscape in Chinese ccRCC needs to be elucidated. Herein, we investigated the molecular features of Chinese ccRCC patients. Genomic profiling of DNA was performed through next-generation sequencing (NGS) in Chinese patients with ccRCC between January 2017 and March 2020. Clinical information including age, gender, and tumor histology was collected. Immunohistochemistry (IHC) staining for PD-L1 expression was performed using PD-L1 IHC 22C3 pharmDx assay or Ventana PD-L1 SP263 assay. Data analyses were performed using R 3.6.1. A total of 880 Chinese ccRCC patients who have undergone NGS were included in this study. The most common somatic alterations were detected in VHL (59.7%), PBRM1 (18.0%), SETD2 (12.2%), BAP1 (10.2%), and TP53 (9.4%). Compared with The Cancer Genome Atlas (TCGA) database, a higher mutation frequency of VHL (59.7% vs. 50.0%, p < 0.001) and TP53 (9.4% vs. 3.5%, p < 0.001) and a lower mutation frequency of PBRM1 (18.0% vs. 31.0%, p < 0.001) were found in the Chinese cohort. Of the 460 patients who were evaluated for PD-L1 expression, 139 (30.2%) had positive PD-L1 expression. The median tumor mutational burden (TMB) value was 4.5 muts/Mb (range, 0–46.0). Five (0.7%) patients were identified as microsatellite instability-high (MSI-H). Furthermore, 52 (5.9%) patients were identified to carry pathogenic or likely pathogenic germline mutations in 22 cancer predisposition genes. This is the first large-scale comprehensive genomic analysis for Chinese ccRCC patients, and these results might provide a better understanding of molecular features in Chinese ccRCC patients, which can lead to an improvement in the personalized treatment for these patients.

RRM2 Regulates Sensitivity to Sunitinib and PD-1 Blockade in Renal Cancer by Stabilizing ANXA1 and Activating the AKT Pathway

Renal cell carcinoma (RCC) is a malignant tumor of the kidneys. Approximately 70% of RCC cases are clear cell renal cell carcinoma with von Hippel-Lindau (VHL) gene mutation and activation of the vascular endothelial growth factor (VEGF) pathway. Tyrosine kinase inhibitors (TKIs) targeting VEGF have emerged as promising agents for RCC treatment. Apart from primary resistance, acquired resistance to TKIs after initial tumor regression is common in RCC. Recently, immune checkpoint inhibition, including PD-1/PD-L1 blockade, alone or in combination with TKIs has improved the overall survival of patients with RCC. Ribonucleotide reductase subunit M2 (RRM2) has been reported in many types of cancer and has been implicated in tumor progression. However, the role of RRM2 in TKIs resistance in RCC remains unclear. In this study, the authors have demonstrated that RRM2 is upregulated in sunitinib-resistant RCC cells and patient tissues. They also find that RRM2 stabilizes ANXA1 and activates the AKT pathway independent of its ribonucleotide reductase activity, promoting sunitinib resistance in RCC. Moreover, RRM2 regulated antitumor immune responses, and knockdown of RRM2 enhance the anti-tumor efficiency of PD-1 blockade in renal cancer. Collectively, these results suggest that aberrantly expressed RRM2 may be a promising therapeutic target for RCC.

Characterization of Renal Cell Carcinoma Heterotypic 3D Co-Cultures with Immune Cell Subsets

Two-dimensional cell culture-based platforms are easy and reproducible, however, they do not resemble the heterotypic cell-cell interactions or the complex tumor microenvironment. These parameters influence the treatment response and the cancer cell fate. Platforms to study the efficacy of anti-cancer treatments and their impact on the tumor microenvironment are currently being developed. In this study, we established robust, reproducible, and easy-to-use short-term spheroid cultures to mimic clear cell renal cell carcinoma (ccRCC). These 3D co-cultures included human endothelial cells, fibroblasts, immune cell subsets, and ccRCC cell lines, both parental and sunitinib-resistant. During spheroid formation, cells induce the production and secretion of the extracellular matrix. We monitored immune cell infiltration, surface protein expression, and the response to a treatment showing that the immune cells infiltrated the spheroid co-cultures within 6 h. Treatment with an optimized drug combination or the small molecule-based targeted drug sunitinib increased immune cell infiltration significantly. Assessing the therapeutic potential of this drug combination in this platform, we revealed that the expression of PD-L1 increased in 3D co-cultures. The cost- and time-effective establishment of our 3D co-culture model and its application as a pre-clinical drug screening platform can facilitate the treatment validation and clinical translation.

SDHB Suppresses the Tumorigenesis and Development of ccRCC by Inhibiting Glycolysis

Metabolic reprogramming is the prominent feature of clear cell renal cell carcinoma (ccRCC). Succinate dehydrogenase subunit B (SDHB) is one of subunits of mitochondrial respiratory chain complex II. The loss of SDHB function is closely related with metabolic changes in kidney cancer cells. However, the role and molecular mechanism of SDHB in ccRCC occurrence and progression are still unclear. In this study, the results of bioinformatics analyses on GEO, TCGA and oncomine databases and immunohistochemistry showed that the expression level of SDHB was downregulated in ccRCC tissues. SDHB level was gradually downregulated as ccRCC stage and grade progressed. The low level of SDHB was associated with poor prognosis of ccRCC patients, especially for advanced ccRCC patients. Increased methylation levels in SDHB gene promoter led to the downregulation of SDHB level in ccRCC tissues. SDHB was correlated with many metabolism related genes and its interacting proteins were enriched in metabolic pathways. SDHB overexpression suppressed the proliferation, colony formation and migration of ccRCC cells by inhibiting aerobic glycolysis. SDHB may be a potential prognostic marker and therapeutic target for ccRCC.

Development of a mechanically matched silk scaffolded 3D clear cell renal cell carcinoma model

Development of a 3D, biomaterials-based model for clear cell renal cell carcinoma (ccRCC) would be advantageous for understanding disease progression in vitro. This study demonstrated the development of lyophilized silk scaffolds that mechanically match the experimentally determined Young's modulus for ex vivo ccRCC samples and normal kidney tissue. Scaffolds fabricated from silk solutions ranging from 3 to 12% (w/v) were evaluated through mechanical testing. Following mechanical characterization of ccRCC samples, it was demonstrated that 6% silk scaffolds mechanically matched ccRCC samples. No impact of pathological grade and stage on the calculated ccRCC modulus was observed and all tumors evaluated mechanically matched the 6% silk scaffold formulation. Stratifying tissue specimens based upon histological observations (e.g. evidence of high levels of collagen deposition) resulted in no significant differences between groups. To investigate the impact of a mechanically matched culturing environment on in vitro ccRCC disease characteristics a model ccRCC cell line, 786-O, was utilized. Scaffolded 786-O cells demonstrated increased lipid droplet accumulation, a hallmark of ccRCC, compared to standard two-dimensional (2D) culture conditions. Additionally, scaffolded 786-O cells demonstrated increased expression of genes associated with ccRCC aggressiveness (ex. VEGFA, TNF, and IL-6) or immune markers under investigation as therapeutic targets (ex. PDL1, CTLA4). Comparison with 786-O cells grown on non-mechanically matched scaffolds demonstrated that these improved ccRCC characteristics were driven by scaffold modulus. Overall, our findings support the use of silk scaffolds in replicating physiologic tumor behavior for clear cell renal cell carcinoma and provide a platform for investigating disease progression.

Modeling Neoplastic Growth in Renal Cell Carcinoma and Polycystic Kidney Disease

Renal cell carcinoma (RCC) and autosomal dominant polycystic kidney disease (ADPKD) share several characteristics, including neoplastic cell growth, kidney cysts, and limited therapeutics. As well, both exhibit impaired vasculature and compensatory VEGF activation of angiogenesis. The PI3K/AKT/mTOR and Ras/Raf/ERK pathways play important roles in regulating cystic and tumor cell proliferation and growth. Both RCC and ADPKD result in hypoxia, where HIF-α signaling is activated in response to oxygen deprivation. Primary cilia and altered cell metabolism may play a role in disease progression. Non-coding RNAs may regulate RCC carcinogenesis and ADPKD through their varied effects. Drosophila exhibits remarkable conservation of the pathways involved in RCC and ADPKD. Here, we review the progress towards understanding disease mechanisms, partially overlapping cellular and molecular dysfunctions in RCC and ADPKD and reflect on the potential for the agile Drosophila genetic model to accelerate discovery science, address unresolved mechanistic aspects of these diseases, and perform rapid pharmacological screens.

Association between visceral adiposity and DDX11 as a predictor of aggressiveness of small clear-cell renal-cell carcinoma: a prospective clinical trial

Background

Visceral fat produces several hormones and cytokines associated with carcinogenesis and tumor progression. Herein, we investigated the association between visceral adiposity and target-gene mRNA expression in patients with localized small clear-cell renal-cell carcinoma (ccRCC).

Methods

We included 200 patients with localized clinical T1a stage ccRCC who had undergone nephrectomy from November 2018 to November 2020 in a prospective clinical trial (NCT03694912). Visceral, subcutaneous, and total adipose tissue in these patients was measured via preoperative computerized tomography of the mid-third lumbar vertebra region. We then examined the association between adiposity and the mRNA levels of PBRM1, BAP1, SETD2, KDM5C, FOXC2, CLIP4, AQP1, DDX11, BAIAP2L1, and TMEM38B in matched frozen tumor tissues and plasma samples.

Results

Upon the stratification of patients into quartiles according to their relative visceral adiposity, high visceral adiposity was found to be significantly associated with low ISUP grade (P = 0.004). Multivariate logistic regression analysis revealed a significant association between frozen tissue DDX11 expression and high visceral adiposity (OR 0.676, 95% CI 0.587–0.779, P < 0.001). Moreover, frozen tissue DDX11 expression was significantly associated with high ISUP grade (OR 1.556, 95% CI 1.223–1.981, P < 0.001). The frozen tissue mRNA expression of DDX11 was identified as a biomarker for visceral adiposity and cancer aggressiveness.

Conclusions

The results obtained herein will aid in inferring the aggressiveness of small ccRCCs, represented by ISUP nuclear grade, in clinical practice. Our findings indicated that DDX11 and visceral fat play active roles in small ccRCC. These roles should be examined in future studies for the possible use of DDX11 and visceral fat as prognostic biomarkers in the treatment of patients with ccRCC.

Trial registration

ClinicalTrials.gov, NCT03694912, Registered 3 October 2018.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40170-021-00251-y.

Oncogenic miR-27a delivered by exosomes binds to SFRP1 and promotes angiogenesis in renal clear cell carcinoma

Exosomes derived from cancer cells have emerged as important mediators of malignant phenotypes of tumors, being involved in the transmission of biological signals between cells. Herein, we intended to clarify the role of exosome-mediated transfer of oncogenic microRNA-27a (miR-27a) in angiogenesis of renal clear cell carcinoma (RCCC). Through bioinformatics analysis, we identified the differentially expressed genes of RCCC and predicted miRNAs targeting SFRP1. We manipulated the expression of miR-27a and/or SFRP1 in RCCC cells to explore their roles in angiogenesis through Cell Counting Kit-8 (CCK-8), Transwell, and Matrigel tubule formation assays. miR-27a loaded in exosomes was overexpressed and downregulated in vitro and in vivo to verify its effect on angiogenesis. SFRP1 was poorly expressed and miR-27a was highly expressed in RCCC tissues, showing a negative correlation. Dual-luciferase assay verified that miR-27a targeted and downregulated SFRP1 expression. Notably, miR-27a enhanced angiogenesis by downregulating SFRP1 expression. miR-27a-loaded exosomes can be delivered from RCCC cells to human umbilical vein endothelial cells (HUVECs). In vitro and in vivo experiments substantiated that miR-27a-loaded exosomes from RCCC cells repressed SFRP1, augmenting the viability, migration, and angiogenesis of RCCC cells. Together, RCCC-derived miR-27a-loaded exosomes inhibit SFRP1 expression and accelerate tumor angiogenesis in RCCC.

Overexpression of PKMYT1 Facilitates Tumor Development and Is Correlated with Poor Prognosis in Clear Cell Renal Cell Carcinoma

BACKGROUND Protein kinase membrane-associated tyrosine/threonine (PKMYT1) has been found in many tumors, but its association with clear cell renal cell carcinoma (ccRCC) remains unclear. MATERIAL AND METHODS PKMYT1 expression in ccRCC was examined in the Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Tumor Immune Estimation Resource databases. The correlation between PKMYT1 expression and clinicopathological parameters was explored via the chi-square test. Receiver operating characteristic curves were used to estimate the diagnostic performance of PKMYT1. Kaplan-Meier curves, a Cox model, nomogram, time-dependent receiver operating characteristic curves, and decision curve analysis (DCA) were used to evaluate the prognostic value and clinical utility of PKMYT1. Genes coexpressed with PKMYT1 in ccRCC were identified based on TCGA, the gene expression profiling interactive, and cBioPortal. Gene Set Enrichment Analysis revealed biological pathways associated with PKMYT1 in ccRCC. RESULTS Weighted gene coexpression network analysis identified PKMYT1 as one of the genes most significantly correlated with progression of histological grade. PKMYT1 was significantly upregulated in ccRCC compared with normal tissue (P<0.001), with a trend toward differentiating between individuals with ccRCC and those who were healthy (area under the curve=0.942). High PKMYT1 expression was correlated with unsatisfactory survival (hazard ratio=1.67, P=0.001), indicating that it is a risk factor for ccRCC. A nomogram incorporating PKMYT1 level was created and showed a clinical net benefit. PKMYT1 was strongly positively correlated with the anti-silencing function of 1B histone chaperone (ASF1B) gene in ccRCC. CONCLUSIONS PKMYT1 is upregulated in ccRCC and its presence indicates poor prognosis, making it a potential therapeutic target for ccRCC.

Exploiting the circuit breaker cancer evolution model in human clear cell renal cell carcinoma

The incessant interactions between susceptible humans and their respective macro/microenvironments registered throughout their lifetime result in the ultimate manifestation of individual cancers. With the average lifespan exceeding 50 years of age in humans since the beginning of 20th century, aging - the "time" factor - has played an ever-increasing role alongside host and environmental factors in cancer incidences. Cancer is a genetic/epigenetic disease due to gain-of-function mutations in cancer-causing genes (oncogene; OG) and/or loss-of-function mutations in tumor-suppressing genes (tumor suppressor genes; TSG). In addition to their integral relationship with cancer, a timely deployment of specific OG and/or TSG is in fact needed for higher organisms like human to cope with respective physiological and pathological conditions. Over the past decade, extensive human kidney cancer genomics have been performed and novel mouse models recapitulating human kidney cancer pathobiology have been generated. With new genomic, genetic, mechanistic, clinical and therapeutic insights accumulated from studying clear cell renal cell carcinoma (ccRCC)-the most common type of kidney cancer, we conceived a cancer evolution model built upon the OG-TSG signaling pair analogous to the electrical circuit breaker (CB) that permits necessary signaling output and at the same time prevent detrimental signaling overdrive. Hence, this viewpoint aims at providing a step-by-step mechanistic explanation/illustration concerning how inherent OG-TSG CBs intricately operate in concert for the organism's wellbeing; and how somatic mutations, the essential component for genetic adaptability, inadvertently triggers a sequential outage of specific sets of CBs that normally function to maintain and protect and individual tissue homeostasis.