New mechanistic insights of clear cell renal cell carcinoma from integrated miRNA and mRNA expression profiling studies

Integrated Bioinformatics Analysis for the Identification of Key lncRNAs, mRNAs, and Potential Drugs in Clear Cell Renal Cell Carcinomas

Purpose

The overall survival of clear cell renal cell carcinoma (ccRCC) is poor. Markers for early detection and progression could improve disease outcomes. This study aims to reveal the potential pathogenesis of ccRCC by integrative bioinformatics analysis and to further develop new therapeutic strategies.

Patients and Methods

RNA-seq data of 530 ccRCC cases in TCGA were downloaded, and a comprehensive analysis was carried out using bioinformatics tools. Another 14 tissue samples were included to verify the expression of selected lncRNAs by qRT-PCR. DGIdb database was used to screen out potential drugs, and molecular docking was used to explore the interaction and mechanism between candidate drugs and targets.

Results

A total of 58 differentially expressed lncRNAs (DElncRNAs) and 660 differentially expressed mRNAs (DEmRNAs) were identified in ccRCC. LINC02038, FAM242C, LINC01762, and PVT1 were identified as the optimal diagnostic lncRNAs, of which PVT1 was significantly correlated with the survival rate of ccRCC. GO analysis of cell components showed that DEmRNAs co-expressed with 4 DElncRNAs were mainly distributed in the extracellular area and the plasma membrane, involved in the transport of metal ions, the transport of proteins across membranes, and the binding of immunoglobulins. Immune infiltration analysis showed that MDSC was the most correlated immune cells with PVT1 and key mRNA SIGLEC8. Validation analysis showed that GABRD, SIGLEC8 and CDKN2A were significantly overexpressed, while ESRRB, ELF5 and UMOD were significantly down-regulated, which was consistent with the expression in our analysis. Furthermore, 84 potential drugs were screened by 6 key mRNAs, of which ABEMACICLIB and RIBOCICLIB were selected for molecular docking with CDKN2A, with stable binding affinity.

Conclusion

In summary, 4 key lncRNAs and key mRNAs of ccRCC were identified by integrative bioinformatics analysis. Potential drugs were screened for the treatment of ccRCC, providing a new perspective for disease diagnosis and treatment.

miR-378a-3p promotes renal cell carcinoma proliferation, migration, and invasion by targeting TOB2

PURPOSE

Renal cell carcinoma (RCC) is one of the most common malignant tumors of the urinary system, which has high metastasis. MicroRNAs (miRNAs) have been reported to participate in RCC progression. The present study aimed to understand the biological role and mechanism of miR-378a-3p in RCC.

METHODS

RT-qPCR assay was used to assess miR-378a-3p and transducer of ERBB2 (TOB2) expression in RCC tissues and cell lines. CCK-8, clone formation, scratch, and transwell assays were carried out to evaluate cell proliferation, migration, and invasion. Furthermore, the target genes of miR-378a-3p were predicted by the online bioinformatics databases. Dual-luciferase reporter assay was used to validate the relationship between miR-378a-3p and TOB2.

RESULTS

miR-378a-3p was highly expressed in RCC tissues and RCC cell lines. Besides, miR-378a-3p accelerated the progression of RCC by mediating cell proliferation, migration and invasion. More importantly, TOB2 was confirmed as a potential target gene of miR-378a-3p. The results of loss-of-function experiments showed that inhibition of TOB2 reversed the inhibitory roles of miR-378a-3p inhibitor on RCC progression.

CONCLUSIONS

miR-378a-3p promoted cell proliferation, migration and invasion through regulating TOB2 in RCC, which indicated a promising target for the treatment of RCC.

Identification of key genes of the ccRCC subtype with poor prognosis

Clear cell renal carcinoma has been reported in many research studies as a rather heterogeneous disease. Identification of different subtypes and their molecular characteristics can help in choosing a more effective treatment and predicting a response to it. In this study, using multi-omics clustering of RNA-Seq data of patients with clear cell renal carcinoma from TCGA. Specific genes were identified for the most aggressive ccRCC subtype associated with metastasis and a subtype associated with a more favorable course of the disease. Among them were genes associated with blood clotting (FGA, FGG) and genes associated with changes in the immune characteristics of a tumor (ENAM, IGFBP1, IL6). In addition, an association of hub genes of poor survival ccRCC subtype with the levels of infiltration of endothelial cells, hematopoietic stem cells, T cells NK and mast cells was revealed. It was shown that MFI2, CP, FGA, and FGG expression can predict the response to sunitinib, while the APOB, ENAM, IGFBP1, and MFI2 expression predict the response to nivolumab. The results obtained provide insight into the genetic characteristics underlying the aggressive subtype of ccRCC and may help develop new approaches to the treatment of this disease.

Three LHPP gene-targeting co-expressed microRNAs (microRNA-765, microRNA-21, and microRNA-144) promote proliferation, epithelial-mesenchymal transition, invasion, and are independent prognostic biomarkers in renal cell carcinomas patients

Background

Renal cell carcinoma (RCC) is one of the highly malignant tumors in the world. Global Cancer Statistics 2020 estimated that there were 179,368 deaths from kidney tumors. Therefore, exploring the prognostic biomarkers of RCC is of great significance for RCC patients. This study aims to explore the potential mechanism and prognostic value of phospholysine phosphohistidine inorganic pyrophosphate phosphatase (LHPP) gene‐targeting co‐expression microRNAs in RCC patients.

Methods

A total of 60 RCC patients were included. Quantitative real‐time PCR (qRT‐PCR), western blotting, and immunohistochemistry were used for LHPP, microRNA‐765, microRNA‐21, and microRNA‐144 levels evaluation. Cell Counting Kit‐8 assay, dual‐luciferase reporter gene assay, invasion assay, and RNA fluorescence in situ hybridization were used for functional analyses.

Results

Compared with adjacent tissues, LHPP levels in cancer tissues were significantly increased (p < .001). Herein, we confirmed that microRNA‐765, microRNA‐21, and microRNA‐144 were direct biological targets of LHPP. MicroRNA‐765 (r = −0.570, p < 0.001), microRNA‐21 (r = −0.495, p < .001), and microRNA‐144 (r = −0.463, p < .001) expression levels were negatively correlated with LHPP expression levels. The high expression levels of microRNA‐765, microRNA‐21, and microRNA‐144 in RCC tissues were associated with poor differentiation, recurrence, and poor prognosis (p < .05). In vitro, microRNA‐765, microRNA‐21, and microRNA‐144 act as oncogenes to promote proliferation, invasion, and epithelial‐mesenchymal transition (EMT) through targeting LHPP.

Conclusions

MicroRNA‐765, microRNA‐21, and microRNA‐144 are independent risk biomarkers for RCC patients. Inhibiting the expression levels of microRNA‐765, microRNA‐21, and microRNA‐144 can reduce the proliferation, EMT, and invasion of RCC cells. Therefore, the above three microRNAs are expected to become molecular biomarkers for RCC therapy.

MicroRNAs in Body Fluids: A More Promising Biomarker for Clear Cell Renal Cell Carcinoma

Renal cell carcinoma (RCC) is the second most common cancer of the urinary system, accounting for approximately 10–15% of kidney cancers in the world. Clear cell renal cell carcinoma (ccRCC) is the most common RCC subtype with the highest mortality. Surgical resection or puncture of tumor tissue is still an important clinical treatment and diagnosis of ccRCC, but its high recurrence rate and poor prognosis often lead to the short survival period of patients. Hence, the development of novel molecular biomarkers is of great clinical importance. miRNAs are endogenous non-coding small RNAs with a length of 19–24 nt. A growing number of studies have reported that miRNAs, as proto-oncogenes or tumor suppressor genes, play a key role in the development of ccRCC and might be effective diagnostic and prognostic biomarkers. In addition, miRNAs can also predict the efficacy of treatment drug, thus improving the accuracy of clinical medication. Furthermore, non-invasive detection of miRNAs or extracellular vesicles (EV) in body fluids has better convenience and repeatability, which shows remarkable advantages compared with tissue detection. In this review, we summarized the typical miRNAs reported in recent years and place emphasis on evaluating miRNAs in different body fluids to provide reference for the clinical diagnosis and prognosis of ccRCC in the future.

Potential diagnostic and prognostic value and regulatory relationship of long noncoding RNA CCAT1 and miR-130a-3p in clear cell renal cell carcinoma

Background

MicroRNAs (miRNAs) and long non-coding RNAs (lncRNAs) could interact with each other to play a vital role in the pathogenesis of cancers. We aimed to examine the expression profile, clinical significance and regulatory relationship of miR-130a-3p and its predicted interactive lncRNA in clear cell renal cell carcinoma (ccRCC).

Methods

Bioinformatics analysis was used to predict lncRNAs binding with miR-130a-3p. qRT-PCR was employed to detect the expression levels of miR-130a-3p and the miRNA-targeted lncRNA, and their clinical values in ccRCC were clarified. The lncRNA sponge potential of miR-130a-3p was assessed through dual-luciferase reporter assay and the biological effects of them were observed.

Results

Colon cancer associated transcript 1 (CCAT1) directly interacted with miR-130a-3p and negatively regulated miR-130a-3p expression. CCAT1 was upregulated and miR-130a-3p was downregulated in ccRCC cell line and tissues (all P < 0.05). High CCAT1 and low miR-130a-3p expression was correlated with larger tumor size and advanced TNM stage in ccRCC patients. High CCAT1 level suggested a poor survival prognosis. There was a negative association between CCAT1 and miR-130a-3p expression (r = − 0.373, P = 0.010). MiR-130a-3p mimic and si-CCAT1 inhibited ccRCC cell proliferation and invasion, and induced apoptosis.

Conclusions

CCAT1/miR-130a-3p axis may have potential to serve as a novel diagnostic and prognostic target of ccRCC patients.

The emerging role of small non-coding RNA in renal cell carcinoma

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SncRNAs contribute to the progress of renal cell carcinoma.

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SncRNAs are promising biomarkers for diagnosis and prognosis of renal cell carcinoma.

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Despite the potential of sncRNA-based cancer therapy, some obstacles remain, including several severe adverse effect.

Noncoding RNAs are transcribed in the most regions of the human genome, divided into small noncoding RNAs (less than 200 nt) and long noncoding RNAs (more than 200 nt) according to their size. Compelling evidences suggest that small noncoding RNAs play critical roles in tumorigenesis and tumor progression, especially in renal cell carcinoma. MiRNA, the most famous small noncoding RNA, has been comprehensively explored for its fundamental role in cancer. And several miRNA-based therapeutic strategies have been applied to several ongoing clinical trials. However, piRNAs and tsRNAs, have not received as much research attention, because of several technological limitations. Nevertheless, some studies have revealed the presence of aberration of piRNAs and tsRNAs in renal cell carcinoma, highlighting a potentially novel mechanism for tumor onset and progression. In this review, we provide an overview of three classes of small noncoding RNA: miRNAs, piRNAs and tsRNAs, that have been reported dysregulation in renal cell carcinoma and have the potential for advancing diagnosis, prognosis and therapeutic applications of this disease.

Identification of the miRNA-mRNA regulatory pathways and a miR-21-5p based nomogram model in clear cell renal cell carcinoma

Background

The purpose of this study was to determine the key microRNAs (miRNAs) and their regulatory networks in clear cell renal cell carcinoma (ccRCC).

Methods

Five mRNA and three microRNA microarray datasets were downloaded from the Gene Expression Omnibus database and used to screen the differentially expressed miRNAs (DEMs) and differentially expressed genes (DEGs). Gene ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis were performed with Metascape. A miRNA-mRNA network was mapped with the Cytoscape tool. The results were validated with data from The Cancer Genome Atlas (TCGA) and qRT-PCR. A nomogram model based on independent prognostic key DEMs, stage and grade was constructed for further investigation.

Results

A total of 26 key DEMs and 307 DEGs were identified. Dysregulation of four key DEMs (miR-21-5p, miR-142-3p, miR-155-5p and miR-342-5p) was identified to correlate with overall survival. The results were validated with TCGA data and qRT-PCR. The nomogram model showed high accuracy in predicting the prognosis of patients with ccRCC.

Conclusion

We identified 26 DEMs that may play vital roles in the regulatory networks of ccRCC. Four miRNAs (miR-21-5p, miR-142-3p, miR-155-5p and miR-342-5p) were considered as potential biomarkers in the prognosis of ccRCC, among which only miR-21-5p was found to be an independent prognostic factor. A nomogram model was then created on the basis of independent factors for better prediction of prognosis for patients with ccRCC. Our results suggest a need for further experimental validation studies.

A Three-microRNA Panel in Serum: Serving as a Potential Diagnostic Biomarker for Renal Cell Carcinoma

PURPOSE

Renal cell carcinoma (RCC) accounts for about 120,000 death each year. Although surgery is a routine treatment, RCC could be fatal if not diagnosed at an early stage. This study aims to search for suitable serum biomarkers and construct a miRNA panel with high diagnostic sensitivity or specificity.

METHODS

Totally 146 RCC patients and 150 normal control were involved in this three-stage study. Serum expression levels of 30 miRNAs selected from literature were tested by reverse transcription quantitative PCR (RT-qPCR) in the screening stage, the testing stage, and the validation stage. The diagnostic efficiency of miRNAs was evaluated by receiver operating characteristic (ROC) curve and area under curve (AUC) analysis. A panel with the highest diagnostic efficiency was constructed by backward stepwise logistic regression analysis. Additionally, bioinformatics analysis was used to investigate potential biological functions and mechanisms of candidate miRNAs.

RESULTS

MiR-224-5p, miR-34b-3p, miR-129-2-3p and miR-182-5p with low to moderate diagnostic ability (AUC = 0.692, 0.778, 0.687 and 0.745, respectively) were selected as candidate miRNAs after the three-stage study. The final diagnostic panel was consisted by miR-224-5p, miR-34b-3p and miR-182-5p with AUC = 0.855. No significance has been found between these four miRNAs and tumor location, Fuhrman Grade and AJCC clinical stages of RCC. Bioinformatic analysis suggested that the three-miRNAs panel may participate in tumorigenesis of RCC by targeting CORO1C.

CONCLUSIONS

The three-miRNA panel in serum could serve as a non-invasive diagnostic biomarker of RCC.

Identification of potential key genes and key pathways related to clear cell renal cell carcinoma through bioinformatics analysis

Clear cell renal cell carcinoma (ccRCC) is a common malignancy of the genitourinary system and is associated with high mortality rates. However, the molecular mechanism of ccRCC pathogenesis is still unclear, which translates to few effective diagnostic and prognostic biomarkers. In this study, we conducted a bioinformatics analysis on three Gene Expression Omnibus datasets and identified 437 differentially expressed genes (DEGs) related to ccRCC development and prognosis, of which 311 and 126 genes are respectively down-regulated and up-regulated. The protein-protein interaction network of these DEGs consists of 395 nodes and 1872 interactions and 2 prominent modules. The Staphylococcus aureus infection and complement and coagulation cascades are significantly enriched in module 1 and are likely involved in ccRCC progression. Forty-two hub genes were screened, of which von Willebrand factor, TIMP metallopeptidase inhibitor 1, plasminogen, formimidoyltransferase cyclodeaminase, solute carrier family 34 member 1, hydroxyacid oxidase 2, alanine-glyoxylate aminotransferase 2, phosphoenolpyruvate carboxykinase 1, and 3-hydroxy-3-methylglutaryl-CoA synthase 2 are possibly related to the prognosis of ccRCC. The differential expression of all nine genes was confirmed by quantitative real-time polymerase chain reaction analysis of the ccRCC and normal renal tissues. These key genes are potential biomarkers for the diagnosis and prognosis of ccRCC and warrant further investigation.

Observations on Solitary Versus Multiple Isolated Pancreatic Metastases of Renal Cell Carcinoma: Another Indication of a Seed and Soil Mechanism?

Isolated pancreas metastases are a rare type of metastasis of renal cell carcinoma, characterized by the presence of pancreatic metastases, while all other organs remain unaffected. In a previous study, we determined arguments from the literature which (a) indicate a systemic-haematogenic metastasis route (uniform distribution of the metastases across the pancreas and independence of the metastatic localization in the pancreas of the side of the renal carcinoma); and (b) postulate a high impact of a seed and soil mechanism (SSM) on isolated pancreatic metastasis of renal cell carcinoma (isPM) as an explanation for exclusive pancreatic metastases, despite a systemic haematogenous tumor cell embolization. The objective of the study presented was to search for further arguments in favor of an SSM with isPM. For that purpose, the factor's histology, grading, and singular/multiple pancreas metastases were analyzed on the basis of 814 observations published up to 2018. While histology and grading allowed for no conclusions regarding the importance of an SSM, the comparison of singular/multiple pancreas metastases produced arguments in favor of an SSM: 1. The multiple pancreas metastases observed in 38.1% prove that multiple tumor cell embolisms occur with isPM, the exclusive "maturation" of which in the pancreas requires an SSM; 2. The survival rates (SVR), which are consistent with singular and multiple pancreas metastases (despite the higher total tumor load with the latter), prove that the metastasized tumor cells are not able to survive in all other organs because of an SSM, which results in identical SVR when the pancreatic foci are treated adequately.