Nucleolar Proteins and Non-Coding RNAs: Roles in Renal Cancer

Construction of a prognostic risk model for clear cell renal cell carcinomas based on centrosome amplification-related genes

Clear cell renal cell carcinoma (ccRCC) is the urological malignancy with the highest incidence, centrosome amplification-associated genes (CARGs) have been suggested to be associated with carcinogenesis, but their roles in ccRCC are still incompletely understood. This study utilizes bioinformatics to explore the role of CARGs in the pathogenesis of ccRCC and to establish a prognostic model for ccRCC related to CARGs. Based on publicly available ccRCC datasets, 2312 differentially expressed genes (DEGs) were identified (control vs. ccRCC). Disease samples were classified into high and low scoring groups based on CARG scores and analysed for differences to obtain 345 DEGs associated with CARG scores (S-DEGs). 137 candidate genes were obtained by taking the intersection of DEGs and S-DEGs. Six prognostic genes (PCP4, SLN, PI3, PROX1, VAT1L, and KLK2) were then screened by univariate Cox, LASSO, and multifactorial Cox regression. These genes exhibit a high degree of enrichment in ribosome-associated pathways. Both risk score and age were independent prognostic factors, and the Nomogram constructed based on them had a good predictive performance (AUC > 0.7). In addition, immunological analyses identified 6 different immune cells and 23 immune checkpoints between the high- and low-risk groups, whereas mutational analyses identified frequent VHL mutations in both high- and low-risk groups. Finally, 93 potentially sensitive drugs were identified. In conclusion, this study identified six CARGs as prognostic genes for ccRCC and established a risk model with predictive value. These findings provide insights for prognostic prediction of ccRCC, optimisation of clinical management and development of targeted therapeutic strategies.

Non-coding transcriptome profiles in clear-cell renal cell carcinoma

Clear-cell renal cell carcinoma (ccRCC) is a common urological malignancy with an increasing incidence. The development of molecular biomarkers that can predict the response to treatment and guide personalized therapy selection would substantially improve patient outcomes. Dysregulation of non-coding RNA (ncRNA) has been shown to have a role in the pathogenesis of ccRCC. Thus, an increasing number of studies are being carried out with a focus on the identification of ncRNA biomarkers in ccRCC tissue samples and the connection of these markers with patients' prognosis, pathological stage and grade (including metastatic potential), and therapy outcome. RNA sequencing analysis led to the identification of several ncRNA biomarkers that are dysregulated in ccRCC and might have a role in ccRCC development. These ncRNAs have the potential to be prognostic and predictive biomarkers for ccRCC, with prospective applications in personalized treatment selection. Research on ncRNA biomarkers in ccRCC is advancing, but clinical implementation remains preliminary owing to challenges in validation, standardization and reproducibility. Comprehensive studies and integration of ncRNAs into clinical trials are essential to accelerate the clinical use of these biomarkers.

LncRNA Genes of the SNHG Family: Co-methylation and Common Functions in Ovarian Cancer

Genes of the small nucleolar RNA host gene (SNHG) family may participate in oncogenesis through the regulatory functions of encoded long non-coding RNAs (lncRNAs) and by influencing formation of small nucleolar RNAs and ribosome biogenesis. The aim of this work was to evaluate changes in the methylation levels and extent of co-methylation of the SNHG family lncRNA genes (SNHG1, GAS5/SNHG2, SNHG6, SNHG12, SNHG17) in clinical samples of ovarian cancer (OC) as an indication for the similarity of their roles in oncogenesis. Analysis of a representative set of 122 OC samples by quantitative methylation-specific PCR showed a statistically significant (p < 0.01-0.0001) increase in the methylation level of all five studied lncRNA genes. There was also a correlation between the increased methylation levels of GAS5, SNHG6, and SNHG12 and OC progression (clinical stage, tumor size, and metastasis), indicating possible functional significance of hypermethylation of these genes. For four genes (SNHG1, GAS5, SNHG6, and SNHG12), a statistically significant pairwise positive correlation of methylation levels (co-methylation) was observed (rs > 0.35; p ≤ 0.001), which was in agreement with the GEPIA 2.0 data (426 OC samples) showing co-expression of these genes (rs > 0.5; p < 0.001). The correlation between the expression levels of GAS5 and SNHG6 was confirmed by RT-qPCR (rs = 0.46; p = 0.007). Bioinformatics analysis predicted miRNAs common for the SNHG1, GAS5, SNHG6, and SNHG12 lncRNA and potentially capable of interacting with one or more of these lncRNAs via competing endogenous RNA mechanism, as well as mRNAs, whose expression might be affected by the studied lncRNAs. We also investigated a possible involvement of genes for these mRNAs in oncogenesis-related processes, such as RNA processing and splicing and epithelial-mesenchymal transition. As a result of this work, four SNHG family lncRNAs with coregulation and joint putative biological functions in the pathogenesis of OC were identified.

Integrated mendelian randomization analyses highlight AFF3 as a novel eQTL-mediated susceptibility gene in renal cancer and its potential mechanisms

BACKGROUNDS

A growing number of expression quantitative trait loci (eQTLs) have been found to be linked with tumorigenesis. In this article, we employed integrated Mendelian randomization (MR) analyses to identify novel susceptibility genes in renal cancer (RC) and reveal their potential mechanisms.

METHODS

Two-sample MR analyses were performed to infer causal relationships between eQTLs, metabolites, and RC risks through the "TwoSampleMR" R package. Sensitivity analyses, such as heterogeneity, pleiotropy, and leave-one-out analysis, were used to assess the stability of our outcomes. Summary-data-based MR (SMR) analyses were used to verify the causal relationships among cis-eQTLs and RC risks via the SMR 1.3.1 software.

RESULTS

Our results provided the first evidence for AFF3 eQTL elevating RC risks, suggesting its oncogenic roles (IVW method; odds ratio (OR) = 1.0005; 95% confidence interval (CI) = 1.0001-1.0010; P = 0.0285; heterogeneity = 0.9588; pleiotropy = 0.8397). Further SMR analysis validated the causal relationships among AFF3 cis-eQTLs and RC risks (P < 0.05). Moreover, the TCGA-KIRC, the ICGC-RC, and the GSE159115 datasets verified that the AFF3 gene was more highly expressed in RC tumors than normal control via scRNA-sequencing and bulk RNA-sequencing (P < 0.05). Gene set enrichment analysis (GSEA) analysis identified six potential biological pathways of AFF3 involved in RC. As for the potential mechanism of AFF3 in RC, we concluded in this article that AFF3 eQTL could negatively modulate the levels of the X-11,315 metabolite (IVW method; OR = 0.9127; 95% CI = 0.8530-0.9765; P = 0.0081; heterogeneity = 0.4150; pleiotropy = 0.8852), exhibiting preventive effects against RC risks (IVW method; OR = 0.9987; 95% CI = 0.9975-0.9999; P = 0.0380; heterogeneity = 0.5362; pleiotropy = 0.9808).

CONCLUSIONS

We concluded that AFF3 could serve as a novel eQTL-mediated susceptibility gene in RC and reveal its potential mechanism of elevating RC risks via negatively regulating the X-11,315 metabolite levels.

Identification of novel snoRNA-based biomarkers for clear cell renal cell carcinoma from urine-derived extracellular vesicles

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of RCC with high rates of metastasis. Targeted therapies such as tyrosine kinase and checkpoint inhibitors have improved treatment success, but therapy-related side effects and tumor recurrence remain a challenge. As a result, ccRCC still have a high mortality rate. Early detection before metastasis has great potential to improve outcomes, but no suitable biomarker specific for ccRCC is available so far. Therefore, molecular biomarkers derived from body fluids have been investigated over the past decade. Among them, RNAs from urine-derived extracellular vesicles (EVs) are very promising.

METHODS

RNA was extracted from urine-derived EVs from a cohort of 78 subjects (54 ccRCC patients, 24 urolithiasis controls). RNA-seq was performed on the discovery cohort, a subset of the whole cohort (47 ccRCC, 16 urolithiasis). Reads were then mapped to the genome, and expression was quantified based on 100 nt long contiguous genomic regions. Cluster analysis and differential region expression analysis were performed with adjustment for age and gender. The candidate biomarkers were validated by qPCR in the entire cohort. Receiver operating characteristic, area under the curve and odds ratios were used to evaluate the diagnostic potential of the models.

RESULTS

An initial cluster analysis of RNA-seq expression data showed separation by the subjects' gender, but not by tumor status. Therefore, the following analyses were done, adjusting for gender and age. The regions differentially expressed between ccRCC and urolithiasis patients mainly overlapped with small nucleolar RNAs (snoRNAs). The differential expression of four snoRNAs (SNORD99, SNORD22, SNORD26, SNORA50C) was validated by quantitative PCR. Confounder-adjusted regression models were then used to classify the validation cohort into ccRCC and tumor-free subjects. Corresponding accuracies ranged from 0.654 to 0.744. Models combining multiple genes and the risk factors obesity and hypertension showed improved diagnostic performance with an accuracy of up to 0.811 for SNORD99 and SNORA50C (p = 0.0091).

CONCLUSIONS

Our study uncovered four previously unrecognized snoRNA biomarkers from urine-derived EVs, advancing the search for a robust, easy-to-use ccRCC screening method.

Non-Coding RNAs in Kidney Stones

Nephrolithiasis is a major public health concern associated with high morbidity and recurrence. Despite decades of research, the pathogenesis of nephrolithiasis remains incompletely understood, and effective prevention is lacking. An increasing body of evidence suggests that non-coding RNAs, especially microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), play a role in stone formation and stone-related kidney injury. MiRNAs have been studied quite extensively in nephrolithiasis, and a plethora of specific miRNAs have been implicated in the pathogenesis of nephrolithiasis, involving remarkable changes in calcium metabolism, oxalate metabolism, oxidative stress, cell-crystal adhesion, cellular autophagy, apoptosis, and macrophage (Mp) polarization and metabolism. Emerging evidence suggests a potential for miRNAs as novel diagnostic biomarkers of nephrolithiasis. LncRNAs act as competing endogenous RNAs (ceRNAs) to bind miRNAs, thereby modulating mRNA expression to participate in the regulation of physiological mechanisms in kidney stones. Small interfering RNAs (siRNAs) may provide a novel approach to kidney stone prevention and treatment by treating related metabolic conditions that cause kidney stones. Further investigation into these non-coding RNAs will generate novel insights into the mechanisms of renal stone formation and stone-related renal injury and might lead to new strategies for diagnosing and treating this disease.

The Prognostic Value and Clinical Significance of lncRNA SNHG5 Expression in Patients with Multiple Malignancies: A Bioinformatic and Meta-analysis

BACKGROUND

Long non-coding RNA small nucleolar RNA host gene 5 (lncRNA SNHG5) has been identified as both a promising target for treatment and a predictor of prognosis in diverse types of cancer. The objective of this study was to assess whether lncRNA SNHG5 expression can be utilized as a prognostic biomarker for human cancer.

METHODS

To ensure a thorough search of the literature for relevant English studies published before July 2023, several databases were searched, including PubMed, Web of Science, ProQuest, Cochrane Library, and Google Scholar. The study evaluated the impact of lncRNA SNHG5 on the overall survival (OS) of cancer by calculating the pooled hazard ratio (HR) and odds ratio (OR) with 95% confidence intervals (CIs). To further confirm the accuracy of the findings, the study investigated the expression profile and prognostic significance of lncRNA SNHG5 through the use of GenomicScape, OncoLnc, Kaplan-Meier plotter, and GEPIA databases.

RESULTS

In this study, 995 patients were examined across a total of fourteen original studies. The findings indicated that there was a significant relationship between heightened lncRNA SNHG5 expression and reduced OS, as evidenced by both univariate and multivariate analyses (HR = 1.89; 95% CI, 1.44-2.49; p < 0.001; HR = 3.97; 95% CI, 1.80-8.73; p < 0.001, respectively). Pooled OR analysis showed a significant association between over-expression of lncRNA SNHG5 with advanced histological grade (OR = 0.28; 95% CI, 0.11-0.71; p = 0.007), present lymph node metastasis (LNM; OR = 4.28; 95% CI, 2.47-7.43; p < 0.001), and smoking history (OR = 0.27; 95% CI, 0.15-0.49; p < 0.001). Bioinformatic databases confirmed that elevated SNHG5 expression was significantly linked to poor prognosis in cancer patients, including colorectal cancer (CRC), acute myeloid leukemia (AML), and esophageal adenocarcinoma (ESAD), and a longer OS in patients with uterine corpus endometrial carcinoma (UCEC).

CONCLUSION

These results suggest that lncRNA SNHG5 may serve as an adverse prognostic biomarker in several human cancers. Further investigations are needed to better understand the underlying mechanisms that link lncRNA SNHG5 to multiple malignancies.

A comprehensive prognostic and immunological analysis of telomere-related lncRNAs in kidney renal clear cell carcinoma

Kidney renal clear cell carcinoma (KIRC) is one of the most prevalent malignant tumors of the urinary system, with a high recurrence and metastasis rate. Telomeres and long non-coding RNAs (lncRNAs) have been documented playing critical roles in cancer progression. However, the prognostic significance of telomere-related lncRNA (TRLs) in KIRC is less well-defined. The Cancer Genome Atlas database was applied to retrieve the expression profiles and corresponding clinical information of KIRC patients. To create the TRLs prognostic signature, univariate Cox regression, least absolute shrinkage and selection operator analyses were performed. The prognostic signature, comprised of nine prognostic TRLs, was developed and demonstrated superior prognostic ability for KIRC patients. Additionally, the risk score acted as an independent prognostic indicator. A nomogram incorporating age, grade, stage, and signature-based risk scores was also developed and exhibited excellent predictive accuracy. Several immune activities were associated with the signature, as determined by gene function analysis. Further analysis revealed differences in the status of immunity and the tumor microenvironment between low- and high-risk groups. Notably, KIRC patients with high-risk scores were more responsive to immunotherapy and chemotherapy. To summarize, our study developed a new prognostic signature consisting of nine telomere-related lncRNA that can precisely predict the prognosis of KIRC patients. The signature was shown to be of substantial value for the tumor microenvironment and tumor mutation burden, thereby contributing to a framework for the individualized treatment of patients.

The Role of Methylation of a Group of microRNA Genes in the Pathogenesis of Metastatic Renal Cell Carcinoma

The role of methylation of 9 miRNA genes in the pathogenesis of metastatic clear cell renal cell carcinoma was determined by quantitative methylation-specific PCR (MS-PCR). For 5 genes (MIR125B-1, MIR137, MIR193A, MIR34B/C, and MIR375), a significant correlation of high methylation level with late (III-IV) stages, large size (T3+T4) of the tumor, and metastasis to lymph nodes and/or distant organs was revealed. For another group of genes (MIR125B-1, MIR1258, MIR193A, MIR34B/C, and MIR375), a statistically significant correlation of high methylation level with loss of differentiation in the tumor (G3-G4) was found, and the opposite pattern was found for MIR203A. A total of 7 microRNA genes (MIR125B-1, MIR1258, MIR137, MIR193A, MIR203A, MIR34B/C, and MIR375) were identified, the methylation of which is associated with the progression of metastatic clear cell renal cell carcinoma. For 6 of them (except MIR34B/C) these data were obtained for the first time. Thus, new factors of the development and progression of clear cell renal cell carcinoma were identified as potential biomarkers for the early diagnosis and prognosis of metastatic clear cell renal cell carcinoma.

Non-coding RNAs in renal cell carcinoma: Implications for drug resistance

Renal cell carcinoma (RCC) represents a malignant tumor of the urinary system. Individuals with early-stage RCC could be cured by surgical treatment, but a considerable number of cases of advanced RCC progress to drug resistance. Recently, numerous reports have demonstrated that a variety of non-coding RNAs (ncRNAs) contribute to tumor occurrence and development. ncRNAs can act as oncogenic or tumor suppressor genes to regulate proliferation, migration, drug resistance and other processes in RCC cells through a variety of signaling pathways. Considering the lack of treatment options for advanced RCC after drug resistance, ncRNAs may be a good choice as biomarkers of drug resistance in RCC and targets to overcome drug resistance. In this review, we discussed the effects of ncRNAs on drug resistance in RCC and the great potential of ncRNAs as a biomarker of or a new therapeutic method in RCC.

Quantification of structural heterogeneity in H&E stained clear cell renal cell carcinoma using refractive index tomography

Clear cell renal cell carcinoma (ccRCC) is a common histopathological subtype of renal cancer and is notorious for its poor prognosis. Its accurate diagnosis by histopathology, which relies on manual microscopic inspection of stained slides, is challenging. Here, we present a correlative approach to utilize stained images and refractive index (RI) tomography and demonstrate quantitative assessments of the structural heterogeneities of ccRCC slides obtained from human patients. Machine-learning-assisted segmentation of nuclei and cytoplasm enabled the quantification at the subcellular level. Compared to benign regions, malignant regions exhibited a considerable increase in structural heterogeneities. The results demonstrate that RI tomography provides quantitative information in synergy with stained images on the structural heterogeneities in ccRCC.

Midsize noncoding RNAs in cancers: a new division that clarifies the world of noncoding RNA or an unnecessary chaos?

Most of the human genome is made out of noncoding RNAs (ncRNAs). These ncRNAs do not code for proteins but carry a vast number of important functions in human cells such as: modification and processing other RNAs (tRNAs, rRNAs, snRNAs, snoRNAs, miRNAs), help in the synthesis of ribosome proteins, initiation of DNA replication, regulation of transcription, processing of pre-messenger mRNA during its maturation and much more. The ncRNAs also have a significant impact on many events that occur during carcinogenesis in cancer cells, such as: regulation of cell survival, cellular signaling, apoptosis, proliferation or even influencing the metastasis process. The ncRNAs may be divided based on their length, into short and long, where 200 nucleotides is the "magic" border. However, a new division was proposed, suggesting the creation of the additional group called midsize noncoding RNAs, with the length ranging from 50-400 nucleotides. This new group may include: transfer RNA (tRNA), small nuclear RNAs (snRNAs) with 7SK and 7SL, small nucleolar RNAs (snoRNAs), small Cajal body-specific RNAs (scaRNAs) and YRNAs. In this review their structure, biogenesis, function and influence on carcinogenesis process will be evaluated. What is more, a question will be answered of whether this new division is a necessity that clears current knowledge or just creates an additional misunderstanding in the ncRNA world?

The clinical significance, immune infiltration, and tumor mutational burden of angiogenesis-associated lncRNAs in kidney renal clear cell carcinoma

Background

Poor prognosis of kidney renal clear cell carcinoma (KIRC) is often related to angiogenesis. The lncRNAs that regulate angiogenesis could also affect the prognosis of KIRC. It is meaningful for us to use lncRNAs related to angiogenesis to construct a generic, individualized prognostic signature for patients with KIRC.

Methods

We identified eight angiogenesis-associated genes (AAGs) by differential expression analysis and univariate Cox regression from The Cancer Genome Atlas dataset, including 537 KIRC samples and 72 normal samples. In total, 23 prognostic lncRNAs were screened out after Pearson correlation analysis and univariate Cox regression analysis. Then, we performed least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression to establish a four-AAG-related lncRNA prognostic signature.

Results

The risk score was calculated for each KIRC patients by using a four-AAG-related lncRNA prognostic signature. We divided the KIRC patients into high- and low-risk groups by the median of the risk score. It was confirmed that the AAG-related lncRNA prognostic signature has good prognostic value for KIRC patients by time-dependent receiver operating characteristic and Kaplan–Meier survival analysis. We identified 3,399 differentially expressed genes between the high- and low-risk groups and performed their functional enrichment analyses. The AAG-related lncRNA prognostic signature was an independent prognostic predictor for KIRC patients and was used to perform a combined nomogram. We reevaluated them in terms of survival, clinic characteristics, tumor-infiltrating immune cells and tumor mutation burden.

Conclusion

Our research indicates that the AAG-related lncRNA prognostic signature is a promising and potential independent prognostic indicator for KIRC patients. Then, it could offer new insights into the prognosis assessment and potential treatment strategies of KIRC patients.

A Double-Negative Feedback Interaction between miR-21 and PPAR-α in Clear Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is the main histotype of kidney cancer, which is typically highly resistant to conventional therapies and known for abnormal lipid accumulation. In this context, we focused our attention on miR-21, an oncogenic miRNA overexpressed in ccRCC, and peroxysome proliferator-activated receptor-α (PPAR- α), one master regulator of lipid metabolism targeted by miR-21. First, in a cohort of 52 primary ccRCC samples, using RT-qPCR and immunohistochemistry, we showed that miR-21 overexpression was correlated with PPAR-α downregulation. Then, in ACHN and 786-O cells, using RT-qPCR, the luciferase reporter gene, chromatin immunoprecipitation, and Western blotting, we showed that PPAR-α overexpression (i) decreased miR-21 expression, AP-1 and NF-κB transcriptional activity, and the binding of AP-1 and NF-κB to the miR-21 promoter and (ii) increased PTEN and PDCD4 expressions. In contrast, using pre-miR-21 transfection, miR-21 overexpression decreased PPAR-α expression and transcriptional activity mediated by PPAR-α, whereas the anti-miR-21 (LNA-21) strategy increased PPAR-α expression, but also the expression of its targets involved in fatty acid oxidation. In this study, we showed a double-negative feedback interaction between miR-21 and PPAR-α. In ccRCC, miR-21 silencing could be therapeutically exploited to restore PPAR-α expression and consequently inhibit the oncogenic events mediated by the aberrant lipid metabolism of ccRCC.