Understanding pathologic variants of renal cell carcinoma: distilling therapeutic opportunities from biologic complexity

AURKB/CDC37 complex promotes clear cell renal cell carcinoma progression via phosphorylating MYC and constituting an AURKB/E2F1-positive feedforward loop

As the second most common malignant tumor in the urinary system, renal cell carcinoma (RCC) is imperative to explore its early diagnostic markers and therapeutic targets. Numerous studies have shown that AURKB promotes tumor development by phosphorylating downstream substrates. However, the functional effects and regulatory mechanisms of AURKB on clear cell renal cell carcinoma (ccRCC) progression remain largely unknown. In the current study, we identified AURKB as a novel key gene in ccRCC progression based on bioinformatics analysis. Meanwhile, we observed that AURKB was highly expressed in ccRCC tissue and cell lines and knockdown AURKB in ccRCC cells inhibit cell proliferation and migration in vitro and in vivo. Identified CDC37 as a kinase molecular chaperone for AURKB, which phenocopy AURKB in ccRCC. AURKB/CDC37 complex mediate the stabilization of MYC protein by directly phosphorylating MYC at S67 and S373 to promote ccRCC development. At the same time, we demonstrated that the AURKB/CDC37 complex activates MYC to transcribe CCND1, enhances Rb phosphorylation, and promotes E2F1 release, which in turn activates AURKB transcription and forms a positive feedforward loop in ccRCC. Collectively, our study identified AURKB as a novel marker of ccRCC, revealed a new mechanism by which the AURKB/CDC37 complex promotes ccRCC by directly phosphorylating MYC to enhance its stability, and first proposed AURKB/E2F1-positive feedforward loop, highlighting AURKB may be a promising therapeutic target for ccRCC.

The potential of organoids in renal cell carcinoma research

Renal cell carcinoma, a leading cause of death in urological malignancies, arises from the nephron. Its characteristics include diversity in disease biology, varied clinical behaviors, different prognoses, and diverse responses to systemic therapies. The term 'organoids' is used to describe structures resembling tissues created through the three-dimensional cultivation of stem cells in vitro. These organoids, when derived from tumor tissues, can retain the diversity of the primary tumor, mirror its spatial tissue structure, and replicate similar organ-like functions. In contrast to conventional two-dimensional cell cultures and the transplantation of tumor tissues into other organisms, organoids derived from tumors maintain the complexity and microenvironment of the original tumor tissue. This fidelity makes them a more reliable model for the development of cancer drugs, potentially accelerating the translation of these drugs to clinical use and facilitating personalized treatment options for patients. This review aims to summarize the recent advancements in the use of organoids for studying renal cell carcinoma, focusing on their cultivation, potential applications, and inherent limitations.

Investigating adherence to tyrosine kinase inhibitors in renal cancer

INTRODUCTION

Tyrosine kinase inhibitors (TKIs) have been used as the first-line treatment for many patients with renal cell carcinoma (RCC), the seventh most common cancer in the United Kingdom. However, suboptimal adherence to TKIs can result in poor clinical prognosis. This study quantified RCC patients' adherence to TKIs and explored factors associated with suboptimal adherence.

METHOD

This retrospective cohort study was conducted at a specialist oncology tertiary hospital in Northwest England, using pharmacy dispensing records between November 2021 and March 2022. TKI prescriptions dispensed to patients with RCC were extracted to calculate the persistency gaps (≥7 or ≥14 days) and medication possession ratio (MPR). Multilevel regression analysis was conducted to associate MPR and persistency gaps with specific patient-related and TKI-related factors. This study did not require ethics approval.

RESULTS

Of the 2225 prescriptions dispensed to 109 patients, 469 (23.4%) and 274 (13.7%) persistency gaps of ≥7 and ≥14 days were identified. About 75% and 92% of patients had a persistency gap of ≥7 days within the first 90 days and 180 days. The length of time since the first TKI prescription (p < 0.001) and the use of sunitinib(p = 0.003) were significantly associated with the number of prescription gaps of ≥7 days. Moreover, the median MPR was 95.6% (interquartile range: 90.7%, 100.1%). Similarly, the length of time since the first TKI prescription was dispensed (p < 0.001) and the use of sunitinib (p = 0.034) were significantly associated with MPR.

DISCUSSION AND CONCLUSION

This single-centre study found that patients with RCC generally adhere to TKIs (MPR > 90%), but many patients experienced a persistency gap. The crucial window to mitigate TKI utilisation is within 180 days after the initial dispensing of TKIs. Further large-scale studies are required to comprehensively investigate other factors associated with adherence to TKIs and develop interventions to improve adherence and medication use problems.

Utilizing a novel model of PANoptosis-related genes for enhanced prognosis and immune status prediction in kidney renal clear cell carcinoma

Kidney renal clear cell carcinoma (KIRC) is the most common histopathologic type of renal cell carcinoma. PANoptosis, a cell death pathway that involves an interplay between pyroptosis, apoptosis and necroptosis, is associated with cancer immunity and development. However, the prognostic significance of PANoptosis in KIRC remains unclear. RNA-sequencing expression and mutational profiles from 532 KIRC samples and 72 normal samples with sufficient clinical data were retrieved from the Cancer Genome Atlas (TCGA) database. A prognostic model was constructed using differentially expressed genes (DEGs) related to PANoptosis in the TCGA cohort and was validated in a Gene Expression Omnibus (GEO) cohorts. Incorporating various clinical features, the risk model remained an independent prognostic factor in multivariate analysis, and it demonstrated superior performance compared to unsupervised clustering of the 21 PANoptosis-related genes alone. Further mutational analysis showed fewer VHL and more BAP1 alterations in the high-risk group, with alterations in both genes also associated with patient prognosis. The high-risk group was characterized by an unfavorable immune microenvironment, marked by reduced levels of CD4 + T cells and natural killer cells, but increased M2 macrophages and regulatory T cells. Finally, the risk model was predictive of response to immune checkpoint blockade, as well as sensitivity to sunitinib and paclitaxel. The PANoptosis-related risk model developed in this study enables accurate prognostic prediction in KIRC patients. Its associations with the tumor immune microenvironment and drug efficacy may offer potential therapeutic targets and inform clinical decisions.

miR-4429 inhibits ccRCC proliferation, migration, and invasion by directly targeting CD274

Clear cell renal cell carcinoma (ccRCC) is one of the most aggressive urological malignancies and a highly immunogenic cancer. Yet, its pathogenesis is still not fully understood. This study analyzed the role of the miR-320 family in ccRCC using bioinformatics algorithms and a series of in vitro experiments. miR-4429 was found to be significantly down-regulated in ccRCC tissues and cell lines, while overexpression of miR-4429 significantly inhibited renal cancer cell proliferation, migration, and invasion in vitro. In addition, the UALCAN database, immunohistochemistry, and protein blotting results showed that CD274 expression was up-regulated in ccRCC tissues and correlated with higher histologic grading. Dual luciferase assay indicated that CD274 was a direct target of miR-4429. Overexpression of miR-4429 in 786-O, Caki-2 cells significantly inhibited CD274 expression. KEGG results indicated that the potential target function of miR-4429 was associated with the PI3K/AKT signaling pathway, and protein blotting verified the results. In summary, this data shows that miR-4429 targets CD274 and inhibits ccRCC proliferation, migration, and invasion by regulating PI3K/AKT signaling, thus potentially providing a promising therapeutic target and prognostic biomarker for renal cell carcinoma patients.

Acetylation- and ubiquitination-regulated SFMBT2 acts as a tumor suppressor in clear cell renal cell carcinoma

BACKGROUND

Clear cell renal cell carcinoma (RCC) is the most common kidney tumor. The analysis from medical database showed that Scm-like with four MBT domains protein 2 (SFMBT2) was decreased in advanced clear cell RCC cases, and its downregulation was associated with the poor prognosis. This study aims to investigate the role of SFMBT2 in clear cell RCC.

METHODS

The expression of SFMBT2 in clear cell RCC specimens were determined by immunohistochemistry staining and western blot. The overexpression and knockdown of SFMBT2 was realized by infection of lentivirus loaded with SFMBT2 coding sequence or silencing fragment in 786-O and 769-P cells, and its effects on proliferation and metastasis were assessed by MTT, colony formation, flow cytometry, wound healing, transwell assay, xenograft and metastasis experiments in nude mice. The interaction of SFMBT2 with histone deacetylase 3 (HDAC3) and seven in absentia homolog 1 (SIAH1) was confirmed by co-immunoprecipitation.

RESULTS

In our study, SFMBT2 exhibited lower expression in clear cell RCC specimens with advanced stages than those with early stages. Overexpression of SFMBT2 inhibited the growth and metastasis of clear cell RCC cells, 786-O and 769-P, in vitro and in vivo, and its silencing displayed opposites effects. HDAC3 led to deacetylation of SFMBT2, and the HDAC3 inhibitor-induced acetylation prevented SFMBT2 from SIAH1-mediated ubiquitination modification and proteasome degradation. K687 in SFMBT2 protein molecule may be the key site for acetylation and ubiquitination.

CONCLUSIONS

SFMBT2 exerted an anti-tumor role in clear cell RCC cells, and HDAC3-mediated deacetylation promoted SIAH1-controlled ubiquitination of SFMBT2. SFMBT2 may be considered as a novel clinical diagnostic marker and/or therapeutic target of clear cell RCC, and crosstalk between its post-translational modifications may provide novel insights for agent development.

Genetic study of the CDKN2A and CDKN2B genes in renal cell carcinoma patients

Objectives

While recent studies have demonstrated several genetic alterations are associated with pathogenesis of RCC, the significance of cyclin-dependent kinase inhibitor 2A (CDKN2A) and cyclin-dependent kinase inhibitor 2B (CDKN2B) in tumorigenesis of RCC is less clear. We investigate the distribution of CDKN2A and CDKN2B mutations in patients with RCC and analyze the impact of CDKN2A and CDKN2B mutations on RCC.

Methods

A pathological examination was conducted using thirty fresh renal tissue samples with renal masses that had undergone partial or radical nephrectomy. Multiplex ligation-dependent probe amplification (MLPA) was used to detect genetic aberrations of CDKN2A and CDKN2B in genomic DNA isolated from samples. Subsequently, CDKN2A and CDKN2B mutations were confirmed using chromosomal microarray technique.

Results

Twenty-one patients were diagnosed with RCC, eight with benign diseases, including angiomyolipoma (AML) and oncocytoma, and one with mucinous adenocarcinoma of renal pelvis. Two of twenty-one patients (9.5 %) with clear-cell RCC were positive for CDKN2A and CDKN2B gene deletions. Interestingly, patients with CDKN2A and CDKN2B mutations were associated with sarcomatoid patterns of RCC (2 out of 4, 50 %). In contrast, no CDKN2A or CDKN2B deletions were detected in samples from benign renal tumors, papillary RCC, or other kidney cancers.

Conclusions

This study demonstrated the potential use of CDKN2A and CDKN2B as biomarkers for the prognostic and molecular classification of renal cancer. CDKN2A and CDKN2B mutations may be associated with RCC development and sarcomatoid changes. Further research is needed to understand the underlying molecular mechanisms of CDKN2A and CDKN2B in the pathogenesis of RCC.

Crosstalk of disulfidptosis-related subtypes identifying a prognostic signature to improve prognosis and immunotherapy responses of clear cell renal cell carcinoma patients

BACKGROUND

Disulfidptosis is a novel form of programmed cell death induced by high SLC7A11 expression under glucose starvation conditions, unlike other known forms of cell death. However, the roles of disulfidptosis in cancers have yet to be comprehensively well-studied, particularly in ccRCC.

METHODS

The expression profiles and somatic mutation of DGs from the TCGA database were investigated. Two DGs clusters were identified by unsupervised consensus clustering analysis, and a disulfidptosis-related prognostic signature (DR score) was constructed. Furthermore, the predictive capacity of the DR score in prognosis was validated by several clinical cohorts. We also developed a nomogram based on the DR score and clinical features. Then, we investigated the differences in the clinicopathological information, TMB, tumor immune landscapes, and biological characteristics between the high- and low-risk groups. We evaluated whether the DR score is a robust tool for predicting immunotherapy response by the TIDE algorithm, immune checkpoint genes, submap analysis, and CheckMate immunotherapy cohort.

RESULTS

We identified two DGs clusters with significant differences in prognosis, tumor immune landscapes, and clinical features. The DR score has been demonstrated as an independent risk factor by several clinical cohorts. The high-risk group patients had a more complicated tumor immune microenvironment and suffered from more tumor immune evasion in immunotherapy. Moreover, patients in the low-risk group had better prognosis and response to immunotherapy, particularly in anti-PD1 and anti-CTLA-4 inhibitors, which were verified in the CheckMate immunotherapy cohort.

CONCLUSION

The DR score can accurately predict the prognosis and immunotherapy response and assist clinicians in providing a personalized treatment regime for ccRCC patients.

Well-Paired-Seq2: High-Throughput and High-Sensitivity Strategy for Characterizing Low RNA-Content Cell/Nucleus Transcriptomes

Single-cell RNA sequencing (scRNA-seq) is a transformative technology that unravels the intricate cellular state heterogeneity. However, the Poisson-dependent cell capture and low sensitivity in scRNA-seq methods pose challenges for throughput and samples with a low RNA-content. Herein, to address these challenges, we present Well-Paired-Seq2 (WPS2), harnessing size-exclusion and quasi-static hydrodynamics for efficient cell capture. WPS2 exploits molecular crowding effect, tailing activity enhancement in reverse transcription, and homogeneous enzymatic reaction in the initial bead-based amplification to achieve 3116 genes and 8447 transcripts with an average of ∼20000 reads per cell. WPS2 detected 1420 more genes and 4864 more transcripts than our previous Well-Paired-Seq. It sensitively characterizes transcriptomes of low RNA-content single cells and nuclei, overcoming the Poisson limit for cell and barcoded bead capture. WPS2 also profiles transcriptomes from frozen clinical samples, revealing heterogeneous tumor copy number variations and intercellular crosstalk in clear cell renal cell carcinomas. Additionally, we provide the first single-cell-level characterization of rare metanephric adenoma (MA) and uncover potential specific markers. With the advantages of high sensitivity and high throughput, WPS2 holds promise for diverse basic and clinical research.

RNA-binding protein IGF2BP2 suppresses metastasis of clear cell renal cell carcinoma by enhancing CKB mRNA stability and expression

Clear cell renal cell carcinoma (ccRCC) is the most prevalent kidney cancer, with a highly aggressive phenotype and poor prognosis. RNA binding proteins (RBPs) play crucial roles in post-transcriptional gene regulation and have been implicated in tumorigenesis. RBPs have the potential to become a new therapeutic target for ccRCC. In this study, we screened and validated that insulin-like growth factor 2 mRNA binding protein 2 (IGF2BP2) as an RBP, was down-regulated in ccRCC tissues and cell lines. Functionally, we verified that IGF2BP2 significantly suppressed the migration and invasion ability of ccRCC in vitro and in vivo. Mechanistically, RIP-seq and actinomycin D experiments results showed that IGF2BP2 enhanced the expression of Creatine Kinase B (CKB) by binding to CKB mRNA and enhancing its mRNA stability. Thus, IGF2BP2 inhibited ccRCC metastasis through enhancing the expression of CKB. Taken together, these finding suggests that IGF2BP2 is a novel metastasis suppressor of ccRCC and may serve as a potential therapeutic target.

Neurogenesis-Associated Protein, a Potential Prognostic Biomarker in Anti-PD-1 Based Kidney Renal Clear Cell Carcinoma Patient Therapeutics

The transketolase 1 gene (TKTL1) is an essential factor that contributes to brain development. Some studies have shown the influence of TKTL1 in cancers, but it has been rarely reported in kidney cancer. Furthermore, the role of TKTL1 in the prognosis and tumor infiltration of immune cells in various cancers, particularly kidney cancer, remains unknown. In this study, TKTL1 expression and its clinical characteristics were investigated using a variety of databases. TIMER was used to investigate the relationship between TKTL1 and immune infiltrates in various types of cancer. We also studied the relationship between TKTL1 expression and response to PD-1 blocker immunotherapy in renal cancer. We conducted TKTL1 agonists virtual screening from 13,633 natural compounds (L6020), implemented secondary library construction according to the types of top results, and then conducted secondary virtual screening for 367 alkaloids. Finally, in vitro assays of cell viability assays and colony formation assays were performed to demonstrate the pharmacological potency of the screening of TKTL1 agonists. Using these methods, we determined that TKTL1 significantly affects the prognostic potential in different types of kidney cancer patients. The underlying mechanism might be that the TKTL1 expression level was positively associated with devious immunocytes in kidney renal clear cell carcinoma (KIRC) rather than in kidney renal papillary cell carcinoma (KIRP) and kidney chromophobe (KICH). This recruitment may result from the up-regulation of the mTOR signaling pathway affecting T cell metabolism. We also found that TKTL1 may act as an immunomodulator in KIRC patients' response to anti-PD-1 therapy. Moreover, we also found that piperine and glibenclamide are potent agonists of TKTL1. We have demonstrated, in vitro, that piperine and glibenclamide can inhibit the proliferation and clone formation of Caki-2 cell lines by agonizing the expression of TKTL1. In summary, our discovery implies that TKTL1 may be a promising prognostic biomarker for KIRC patients who respond to anti-PD-1 therapy. Piperine and glibenclamide may be effective therapeutic TKTL1 agonists, providing a theoretical basis for the clinical treatment of kidney cancer.

A pilot study of [68Ga]Ga-fibroblast activation protein inhibitor-04 PET/CT in renal cell carcinoma

OBJECTIVES

As a promising positron emission tomography (PET) tracer, [68Ga]Ga-fibroblast activation protein inhibitor-04([68Ga]Ga-FAPI-04) performs better than 2-[18F]fluoro-2-deoxy-d-glucose ([18F]FDG) at diagnosing primary and metastatic lesions in patients with various types of cancer. We investigated the utility of [68Ga]Ga-FAPI-04 PET/CT for the detection of primary and metastatic lesions in renal cell carcinoma (RCC). [18F]FDG PET/CT were used for comparison.

METHODS

Twenty-two patients with suspected RCC or recurrent RCC were enrolled in our study. Among these patients, 14 were newly diagnosed with RCC, 3 had recurrent RCC, and 5 were excluded from further analysis due to having benign renal tumours. Seventeen patients with RCC underwent [68Ga]Ga-FAPI-04 PET/CT, and 6 of them also received [18F]FDG PET/CT. The positive detection rates were calculated and compared with those in patients who underwent both scans.

RESULTS

Data from 17 patients with RCC (median age: 60.5 years, interquartile range [IQR]: 54-70 years) were evaluated. The positive detection rate of [68Ga]Ga-FAPI-04 PET/CT for RCC was 64.7% (11/17). Lymph node metastases (n = 44), lung metastasis (n = 1), and bone metastasis (n = 1) were detected. Six patients with RCC underwent [68Ga]Ga-FAPI-04 and [18F]FDG PET/CT. [68Ga]Ga-FAPI-04 PET/CT showed a higher positive detection rate than [18F]FDG PET/CT in detecting RCC (83.3% [5/6] vs. 50% [3/6], P = 0.545). Additionally, [68Ga]Ga-FAPI-04 PET/CT has higher SUVmax (3.20 [IQR: 2.91-5.80 vs. 2.71 [IQR: 2.13-3.10], P = 0.116) and tumour-to-background ratio (TBR) values (1.60 [IQR: 1.33-3.67] vs. 0.86 [0.48-1.21], P = 0.028) than [18F]FDG PET/CT.

CONCLUSIONS

These findings suggest that [68Ga]Ga-FAPI-04 PET/CT has potential value in RCC diagnosis. Further studies are warranted to validate these results.

ADVANCES IN KNOWLEDGE

Clinical utility of [68Ga]Ga-FAPI-04 in RCC remains unclear, and there are not many similar studies in the literature. We evaluated the role of [68Ga]Ga-FAPI-04 in diagnosing RCC.

CD3+ and CD8+ T cell-based immune cell score as a prognostic factor in clear-cell renal cell carcinoma

BACKGROUND AND PURPOSE

Immunoscore® is a prognostic parameter based on densities of lymphocyte populations in the tumor center and invasive margin. Immunoscore® is validated in colorectal cancer as a high Immunoscore® is associated with longer survival. Previous studies have suggested that Immunoscore® may also predict oncological outcomes in clear-cell renal cell carcinoma (ccRCC). This study aims to assess the prognostic role of immune cell score in ccRCC.

MATERIAL AND METHODS

All patients with ccRCC undergoing surgery between 2007 and 2020 in Central Finland Central Hospital were retrospectively identified. CD3+ and CD8+ cell densities were calculated from tissue samples to determine the immune cell score using Immunoscore® principles. Receiver-operating characteristic analysis, Kaplan-Meier survival curve, and Cox regression were used to evaluate the association between immune cell score and survival.

RESULTS

A total of 203 patients (mean age 66.5 years) were identified. The median follow-up time was 6.2 years. Based on the immune cell score, the patients were divided into three groups: low, intermediate, and high. In Cox regression analysis, adjusted with age, sex, and Charlson Comorbidity Index, no significant differences in disease-specific mortality were observed among the three groups. The hazard ratios (HRs) for disease-specific mortality were 0.93 (95% confidence interval [CI] 0.48-1.79) and 1.12 (0.52-2.37) for intermediate- and high-immune cell score groups when compared to low-immune cell score group, respectively.

INTERPRETATION

This study found no association between immune cell score and survival. These results indicate that immune cell score may not serve as a prognostic tool in ccRCC.

Arachidonic acid metabolism as a therapeutic target in AKI-to-CKD transition

Arachidonic acid (AA) is a main component of cell membrane lipids. AA is mainly metabolized by three enzymes: cyclooxygenase (COX), lipoxygenase (LOX) and cytochrome P450 (CYP450). Esterified AA is hydrolysed by phospholipase A2 into a free form that is further metabolized by COX, LOX and CYP450 to a wide range of bioactive mediators, including prostaglandins, lipoxins, thromboxanes, leukotrienes, hydroxyeicosatetraenoic acids and epoxyeicosatrienoic acids. Increased mitochondrial oxidative stress is considered to be a central mechanism in the pathophysiology of the kidney. Along with increased oxidative stress, apoptosis, inflammation and tissue fibrosis drive the progressive loss of kidney function, affecting the glomerular filtration barrier and the tubulointerstitium. Recent studies have shown that AA and its active derivative eicosanoids play important roles in the regulation of physiological kidney function and the pathogenesis of kidney disease. These factors are potentially novel biomarkers, especially in the context of their involvement in inflammatory processes and oxidative stress. In this review, we introduce the three main metabolic pathways of AA and discuss the molecular mechanisms by which these pathways affect the progression of acute kidney injury (AKI), diabetic nephropathy (DN) and renal cell carcinoma (RCC). This review may provide new therapeutic targets for the identification of AKI to CKD continuum.

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

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

Decreased expression of TXNIP is associated with poor prognosis and immune infiltration in kidney renal clear cell carcinoma

The most prevalent and insidious type of kidney cancer is kidney clear cell carcinoma (KIRC). Thioredoxin-interacting protein (TXNIP) encodes a thioredoxin-binding protein involved in cellular energy metabolism, redox homeostasis, apoptosis induction and inflammatory responses. However, the relationship between TXNIP, immune infiltration and its prognostic value in KIRC remains unclear. Thus, the present study evaluated the potential for TXNIP as a prognostic marker in patients with KIRC. Data from The Cancer Genome Atlas were used to assess relative mRNA expression levels of TXNIP in different types of cancer. The protein expression levels of TXNIP were evaluated using the Human Protein Atlas. Enrichment analysis of genes co-expressed with TXNIP was performed to assess relevant biological processes that TXNIP may be involved in. CIBERSORT was used to predict the infiltration of 21 tumor-infiltrating immune cells (TIICs). Univariate and multivariate Cox regression analyses were used to assess the relationship between TXNIP expression and prognosis. Single-cell RNA-sequencing datasets were used to evaluate the mRNA expression levels of TXNIP in certain immune cells in KIRC. The CellMiner database was used to analyze the relationship between TXNIP mRNA expression and drug sensitivity in KIRC. The results from the present study demonstrated that TXNIP expression was significantly decreased in KIRC tissue compared with that in normal tissue, as confirmed by western blotting and reverse transcription-quantitative PCR. In addition, downregulated TXNIP expression was significantly associated with poor prognosis, a high histological grade and an advanced stage. The Cell Counting Kit-8 assay demonstrated that TXNIP overexpression significantly suppressed tumor cell proliferation. Univariate and multivariate Cox regression analyses indicated that TXNIP served as a separate prognostic factor in KIRC. Moreover, TXNIP expression was significantly correlated with the accumulation of several TIICs and its overexpression significantly downregulated the mRNA expression levels of CD25 and cytotoxic T-lymphocyte-associated protein 4, immune cell surface markers in CD4+ T lymphocytes. In conclusion, TXNIP may be used as a possible biomarker to assess unfavorable prognostic outcomes and identify immunotherapy targets in KIRC.

Circular RNA AGAP1 Stimulates Immune Escape and Distant Metastasis in Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most representative subtype of renal cancer, with a highly aggressive phenotype and extremely poor prognosis. Immune escape is one of the main reasons for ccRCC growth and metastasis, in which circular RNAs (circRNAs) play critical roles. Therefore, this research studied circAGAP1-associated mechanisms in immune escape and distant metastasis in ccRCC. circAGAP1/miR-216a-3p/MKNK2 was overexpressed or down-regulated by cell transfection. EdU assay, colony formation assay, scratch assay, Transwell assay, immunoblotting, and flow cytometry were used to evaluate cell proliferation, migration, invasion, EMT, and immune escape, respectively. Dual-luciferase reporting assay and RIP assay were used to evaluate the targeting relationship between circAGAP1/miR-216a-3p/MKNK2. Xenotransplantation in nude mice was used to evaluate the growth of ccRCC tumors in vivo. Here, circAGAP1 high expression was positively correlated with higher histological grade and distant metastasis and was a prognostic indicator for ccRCC. Depleting circAGAP1 effectively hampered the proliferative, invasive, and migratory capacities, EMT, and immune escape of ccRCC cells. Correspondingly, silencing circAGAP1 delayed tumor growth, distant metastasis, and immune escape in vivo. Mechanistically, circAGAP1 sponged the tumor suppressor miR-216a-3p, thereby preventing miR-216a-3p from inhibiting MAPK2. Collectively, our findings demonstrate that circAGAP1 exerts a tumor suppressor function through miR-216a-3p/MKNK2 during the immune escape and distant metastasis in ccRCC, and suggest that circAGAP1 may be a novel prognostic marker and therapeutic target for ccRCC.

Diagnostic liquid biopsy biomarkers in renal cell cancer

The clinical presentation of renal cell cancer (RCC) is shifting towards incidental and early detection, creating new challenges in RCC diagnosis. Overtreatment might be reduced with the development of new diagnostic biomarkers to distinguish benign from malignant small renal masses (SRMs). Differently from tissue biopsies, liquid biopsies are obtained from a patient's blood or urine and, therefore, are minimally invasive and suitable for longitudinal monitoring. The most promising types of liquid biopsy biomarkers for RCC diagnosis are circulating tumour cells, extracellular vesicles (EVs) and cell-free DNA. Circulating tumour cell assays have the highest specificity, with low processing time and costs. However, the biological characteristics and low sensitivity limit the use of these markers in SRM diagnostics. Cell-free DNA might complement the diagnosis of high-volume RCC, but the potential for clinical application in SRMs is limited. EVs have the highest biological abundance and the highest sensitivity in identifying low-volume disease; moreover, the molecular characteristics of these markers make EVs suitable for multiple analytical applications. Thus, currently, EV assays have the greatest potential for diagnostic application in RCC (including identification of SRMs). All these liquid biomarkers have potential in clinical practice, pending validation studies. Biomarker implementation will be needed to also improve characterization of RCC subtypes. Last, diagnostic biomarkers might be extended to prognostic or predictive applications.

TBC1D5 reverses the capability of HIF-2α in tumor progression and lipid metabolism in clear cell renal cell carcinoma by regulating the autophagy

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is known for abnormal lipid metabolism and widespread activation of HIF-2α. Recently, the importance of autophagy in ccRCC has been focused, and it has potential connections with HIF-2α and lipid metabolism. However, the specific regulatory mechanism between HIF-2α, autophagy, and lipid metabolism in ccRCC is still unclear.

METHODS

In this study, Bioinformatics Analysis and Sequencing of the whole transcriptome were used to screen our target. The expression of TBC1D5 in renal clear cell carcinoma was confirmed by database analysis, immunohistochemistry, PCR and Western blot. The effects of TBC1D5 on tumor cell growth, migration, invasion and lipid metabolism were examined by CCK8, Transwell and oil red staining, and the mechanism of TBC1D5 on autophagy was investigated by Western blot, fluorescence microscopy and electron microscopy. Chloroquine and rapamycin were used to verified the key role of autophagy in effects of TBC1D5 on tumor cell. The regulatory mechanism of TBC1D5 in renal clear cell carcinoma (RCC) was investigated by shhif-2α, shTBC1D5, mimic, inhibitor, ChIP and Luciferase experiments. The animal model of ccRCC was used to evaluate the biological function of TBC1D5 in vivo.

RESULTS

In this study, TBC1D5 was found to be an important bridge between autophagy and HIF-2α. Specifically, TBC1D5 is significantly underexpressed in ccRCC, serving as a tumor suppressor which inhibits tumor progression and lipid accumulation, and is negatively regulated by HIF-2α. Further research has found that TBC1D5 regulates the autophagy pathway to reverse the biological function of HIF-2α in ccRCC. Mechanism studies have shown that HIF-2α regulates TBC1D5 through hsa-miR-7-5p in ccRCC, thereby affecting tumor progression and lipid metabolism through autophagy.

CONCLUSIONS

Our research reveals a completely new pathway, HIF-2α/hsa-miR-7-5p/TBC1D5 pathway affects ccRCC progression and lipid metabolism by regulating autophagy.

Feature Extraction Based on Local Histogram with Unequal Bins and a Recurrent Neural Network for the Diagnosis of Kidney Diseases from CT Images

Kidney disease remains one of the most common ailments worldwide, with cancer being one of its most common forms. Early diagnosis can significantly increase the good prognosis for the patient. The development of an artificial intelligence-based system to assist in kidney cancer diagnosis is crucial because kidney illness is a global health concern, and there are limited nephrologists qualified to evaluate kidney cancer. Diagnosing and categorising different forms of renal failure presents the biggest treatment hurdle for kidney cancer. Thus, this article presents a novel method for detecting and classifying kidney cancer subgroups in Computed Tomography (CT) images based on an asymmetric local statistical pixel distribution. In the first step, the input image is non-overlapping windowed, and a statistical distribution of its pixels in each cancer type is built. Then, the method builds the asymmetric statistical distribution of the image's gradient pixels. Finally, the cancer type is identified by applying the two built statistical distributions to a Deep Neural Network (DNN). The proposed method was evaluated using a dataset collected and authorised by the Dhaka Central International Medical Hospital in Bangladesh, which includes 12,446 CT images of the whole abdomen and urogram, acquired with and without contrast. Based on the results, it is possible to confirm that the proposed method outperformed state-of-the-art methods in terms of the usual correctness criteria. The accuracy of the proposed method for all kidney cancer subtypes presented in the dataset was 99.89%, which is promising.

Nilotinib in combination with sunitinib renders MCL-1 for degradation and activates autophagy that overcomes sunitinib resistance in renal cell carcinoma

PURPOSE

Sunitinib is a recommended drug for metastatic renal cell carcinoma (RCC). However, the therapeutic potential of sunitinib is impaired by toxicity and resistance. Therefore, we seek to explore a combinatorial strategy to improve sunitinib efficacy of low-toxicity dose for better clinical application.

METHODS

We screen synergistic reagents of sunitinib from a compound library containing 1374 FDA-approved drugs by in vitro cell viability evaluation. The synergistically antiproliferative and proapoptotic effects were demonstrated on in vitro and in vivo models. The molecular mechanism was investigated by phosphoproteomics, co-immunoprecipitation, immunofluorescence and western-blot assays, etc. RESULTS: From the four-step screening, nilotinib stood out as a potential synergistic killer combined with sunitinib. Subsequent functional evaluation demonstrated that nilotinib and sunitinib synergistically inhibit RCC cell proliferation and promote apoptosis in vitro and in vivo. Mechanistically, nilotinib activates E3-ligase HUWE1 and in combination with sunitinib renders MCL-1 for degradation via proteasome pathway, resulting in the release of Beclin-1 from MCL-1/Beclin-1 complex. Subsequently, Beclin-1 induces complete autophagy flux to promote antitumor effect.

CONCLUSION

Our findings revealed that a novel mechanism that nilotinib in combination with sunitinib overcomes sunitinib resistance in RCC. Therefore, this novel rational combination regimen provides a promising therapeutic avenue for metastatic RCC and rationale for evaluating this combination clinically.

Establishment and validation of a novel peroxisome-related gene prognostic risk model in kidney clear cell carcinoma

BACKGROUND

Kidney clear cell carcinoma (KIRC) is the most common subtype of renal cell carcinoma. Peroxisomes play a role in the regulation of tumorigenesis and cancer progression, yet the prognostic significance of peroxisome-related genes (PRGs) remains rarely studied. The study aimed to establish a novel prognostic risk model and identify potential biomarkers in KIRC.

METHODS

The significant prognostic PRGs were screened through differential and Cox regression analyses, and LASSO Cox regression analysis was performed to establish a prognostic risk model in the training cohort, which was validated internally in the testing and entire cohorts, and further assessed in the GSE22541 cohort. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to explore the function and pathway differences between the high-risk and low-risk groups. The relationship between risk score and immune cell infiltration levels was evaluated in the CIBERSORT, ESTIMATE and TIMER databases. Finally, potential biomarkers were identified and validated from model genes, using immunohistochemistry.

RESULTS

Fourteen significant prognostic PRGs were identified using multiple analyses, and 9 genes (ABCD1, ACAD11, ACAT1, AGXT, DAO, EPHX2, FNDC5, HAO1, and HNGCLL1) were obtained to establish a prognostic model via LASSO Cox regression analysis. Combining the risk score with clinical factors to construct a nomogram, which provided support for personalized treatment protocols for KIRC patients. GO and KEGG analyses highlighted associations with substance metabolism, transport, and the PPAR signaling pathways. Tumor immune infiltration indicated immune suppression in the high-risk group, accompanied by higher tumor purity and the expression of 9 model genes was positively correlated with the level of immune cell infiltration. ACAT1 has superior prognostic capabilities in predicting the outcomes of KIRC patients.

CONCLUSIONS

The peroxisome-related prognostic risk model could better predict prognosis in KIRC patients.

Identification of an immune-related eRNA prognostic signature for clear cell renal cell carcinoma

BACKGROUND

Immune-related enhancer RNAs (eRNAs) have garnered significant attention in cancer metabolism research, yet their specific roles in ccRCC have remained elusive.

METHODS

We retrieved eRNA expression profiles from TCGA database and identified immune-related eRNAs (IREs) by assessing their co-expression with immune genes. Utilizing consensus clustering, we organized these IREs into two distinct clusters. The construction of an IREs signature was accomplished through the LASSO and multivariate Cox analysis. Furthermore, we performed Cell Counting Kit-8 and clonogenic assays to assess changes in the proliferative capacity of Caki-1 and 769-P cells.

RESULTS

The existence of two clusters of immune-related eRNAs in ccRCC, each with distinctive prognostic and immunological attributes. Cluster B exhibited immunosuppressive properties and displayed a positive correlation with immunosuppressive cells. Functional enrichment analysis unveiled their involvement in several tumor-promoting pathways, metabolic pathways and immune pathways. The IREs signature demonstrated its potential to accurately predict patient immune and prognostic characteristics. AC003092.1, an eRNA strongly associated with patient survival, emerged as a potential oncogene significantly linked to adverse prognosis and the presence of immunosuppressive cells and checkpoints in ccRCC patients. Notably, AC003092.1 displayed marked upregulation in ccRCC tissues and cell lines, and its knockdown substantially inhibited the proliferation of Caki-1 and 769-P cells.

CONCLUSION

We established a robust predictive model that played a vital role in determining the prognosis, clinicopathological characteristics and immune cell infiltration patterns of ccRCC patients. IRE, particularly AC003092.1, which was strongly associated with survival, hold promise as novel immunotherapeutic targets for ccRCC.

Targeting NPC1 in Renal Cell Carcinoma

Rapidly proliferating cancer cells have a greater requirement for cholesterol than normal cells. Tumor cells are largely dependent on exogenous lipids given that their growth requirements are not fully met by endogenous pathways. Our current study shows that ccRCC cells have redundant mechanisms of cholesterol acquisition. We demonstrate that all major lipoproteins (i.e., LDL, HDL, and VLDL) have a comparable ability to support the growth of ccRCC cells and are equally effective in counteracting the antitumor activities of TKIs. The intracellular trafficking of exogenous lipoprotein-derived cholesterol appears to be distinct from the movement of endogenously synthesized cholesterol. De novo synthetized cholesterol is transported from the endoplasmic reticulum directly to the plasma membrane and to the acyl-CoA: cholesterol acyltransferase, whereas lipoprotein-derived cholesterol is distributed through the NPC1-dependent endosomal trafficking system. Expression of NPC1 is increased in ccRCC at mRNA and protein levels, and high expression of NPC1 is associated with poor prognosis. Our current findings show that ccRCC cells are particularly sensitive to the inhibition of endolysosomal cholesterol export and underline the therapeutic potential of targeting NPC1 in ccRCC.

TIGIT may Serve as a Potential Target for the Immunotherapy of Renal Cell Carcinoma

This study aims to explore whether TIGIT is an effective target for the immunotherapy of renal cell cancer (RCC) with PD-1 as a positive control. The expression of TIGIT and PD-1 in RCC and peripheral blood mononuclear cells (PBMC) and the correlation between TIGIT and PD-1 are evaluated. The expression of TIGIT and PD-1 is inhibited, and then the proliferation, apoptosis, and migration are assessed. TIGIT expression is positively related to the expression of PDCD1, BTLA, ICOS, and FOXP3 (p < 0.05). TIGIT expression in the PBMC, TIL, RCC, and adjacent normal tissues is higher than PD-1 expression. Blocking the TIGIT and PD-1 signaling pathways significantly inhibits the proliferation, migration, and invasion of RCC cells and promotes their apoptosis. These effects are more evident in TIGIT inhibitors than in PD-1 inhibitors. TIGIT inhibitor mainly regulates the expression of differential genes to achieve the reconstruction of immune killing and restore the killing effect on the RCC, and its mechanism by which TIGIT functions overlap that of PD-1 inhibitor. TIGIT may become a target for the immunotherapy of RCC, and there is a theoretical basis for the combination of TIGIT inhibitors and PD-1 inhibitors for the treatment of RCC.

Mechanisms of sunitinib resistance in renal cell carcinoma and associated opportunities for therapeutics

Sunitinib is the first-line drug for renal cell carcinoma (RCC) treatment. However, patients who received sunitinib treatment will ultimately develop drug resistance after 6-15 months, creating a huge obstacle to the current treatment of renal cell carcinoma. Therefore, it is urgent to clarify the mechanisms of sunitinib resistance and develop new strategies to overcome it. In this review, the mechanisms of sunitinib resistance in renal cell carcinoma have been summarized based on five topics: activation of bypass or alternative pathway, inadequate drug accumulation, tumour microenvironment, metabolic reprogramming and epigenetic regulation. Furthermore, present and potential biomarkers, as well as potential treatment strategies for overcoming sunitinib resistance in renal cell carcinoma, are also covered.

What is the benefit of gadolinium-chelate injection for the diagnosis of local recurrence of clear cell renal cell carcinoma after percutaneous thermal ablation with MRI?

PURPOSE

The purpose of this study was to compare the diagnostic capabilities of contrast-enhanced (CE)-MRI to those of non-CE-MRI to diagnose local recurrence of clear cell renal cell carcinoma (ccRCC) after percutaneous thermal ablation (TA).

MATERIALS AND METHODS

This institutional, review board-approved, case-control, single-center retrospective study included all consecutive adult patients with at least two post-TA MRIs showing local recurrence of ccRCC after TA validated by multidisciplinary board. 'Control' patients without recurrence were randomly-selected with a case:control ratio of 2/3. Four senior radiologists reviewed in a double-blinded fashion non-CE sequences of last two consecutive MRI examinations (non-CE-MRIs), assessed the presence of recurrence of ccRCC, then reviewed the CE sequences (CE-MRI) and determined again the presence of a recurrence. Area under the receiver operating characteristic curve (AUROC), sensitivity, specificity and accuracy were compared for each reader for non-CE-MRI and CE-MRI.

RESULTS

Fifty-one patients (41 men; mean age, 77.5 years) who underwent percutaneous TA for ccRCC were included. There were a total of 21 recurrences and 35 scars. Whoever the reader, AUROC was not significantly different (mean, 0.86 with-CE-MRI vs. 0.81 with non-CE-MRI; P values ranging between 0.08 and 0.98), neither sensitivity (mean, 76.2% with CE-MRI vs. 71.4% with non-CE-MRI; P values ranging between 0.06 and >0.99), nor accuracy (85.8% with CE-MRI vs. 80.8% with non-CE-MRI; P values ranging between 0.07 and >0.99). Change in specificity depended on the reader with a significant increase for one reader (+20%; P = 0.02) and a significant decrease for another reader (-17.2%; P = 0.03).

CONCLUSION

Non-CE MRI has good diagnostic performance for the follow-up of patients with ccRCC treated using percutaneous TA, questioning the systematic use of GBCA injection.

Analysis of the Tumor Immune Microenvironment (TIME) in Clear Cell Renal Cell Carcinoma (ccRCC) Reveals an M0 Macrophage-Enriched Subtype: An Exploration of Prognostic and Biological Characteristics of This Immune Phenotype

There is a need to optimize the treatment of clear cell renal cell carcinoma (ccRCC) patients at high recurrence risk after nephrectomy. We sought to elucidate the tumor immune microenvironment (TIME) of localized ccRCC and understand the prognostic and predictive characteristics of certain features. The discovery cohort was clinically localized patients in the TCGA-Kidney Renal Clear Cell Carcinoma (KIRC) project (n = 382). We identified an M0 macrophage-enriched cluster (n = 25) in the TCGA-KIRC cohort. This cluster's median progression-free survival (PFS) and overall survival (OS) were 40.4 and 45.3 months, respectively, but this was not reached in the others (p = 0.0003 and <0.0001, respectively). Gene set enrichment (GSEA) analysis revealed an enrichment of epithelial to mesenchymal transition and cell cycle progression genes within this cluster, and these patients also had a lower predicted response to immune checkpoint blockade (ICB) (4% vs. 20-34%). An M0-enriched cluster (n = 9) with shorter PFS (p = 0.0006) was also identified in the Clinical Proteomics Tumor Analysis Consortium (CPTAC) cohort (n = 94). Through this characterization of the TIME in ccRCC, a cluster of patients defined by enrichment in M0 macrophages was identified that demonstrated poor prognosis and lower predicted ICB response. Pending further validation, this signature can identify localized ccRCC patients at high risk of recurrence after nephrectomy and who may require therapeutic approaches beyond ICB monotherapy.

Multiomics characterization and verification of clear cell renal cell carcinoma molecular subtypes to guide precise chemotherapy and immunotherapy

Clear cell renal cell carcinoma (ccRCC) is a heterogeneous tumor with different genetic and molecular alterations. Schemes for ccRCC classification system based on multiomics are urgent, to promote further biological insights. Two hundred and fifty-five ccRCC patients with paired data of clinical information, transcriptome expression profiles, copy number alterations, DNA methylation, and somatic mutations were collected for identification. Bioinformatic analyses were performed based on our team's recently developed R package "MOVICS." With 10 state-of-the-art algorithms, we identified the multiomics subtypes (MoSs) for ccRCC patients. MoS1 is an immune exhausted subtype, presented the poorest prognosis, and might be caused by an exhausted immune microenvironment, activated hypoxia features, but can benefit from PI3K/AKT inhibitors. MoS2 is an immune "cold" subtype, which represented more mutation of VHL and PBRM1, favorable prognosis, and is more suitable for sunitinib therapy. MoS3 is the immune "hot" subtype, and can benefit from the anti-PD-1 immunotherapy. We successfully verified the different molecular features of the three MoSs in external cohorts GSE22541, GSE40435, and GSE53573. Patients that received Nivolumab therapy helped us to confirm that MoS3 is suitable for anti-PD-1 therapy. E-MTAB-3267 cohort also supported the fact that MoS2 patients can respond more to sunitinib treatment. We also confirm that SETD2 is a tumor suppressor in ccRCC, along with the decreased SETD2 protein level in advanced tumor stage, and knock-down of SETD2 leads to the promotion of cell proliferation, migration, and invasion. In summary, we provide novel insights into ccRCC molecular subtypes based on robust clustering algorithms via multiomics data, and encourage future precise treatment of ccRCC patients.

Integrated analyses reveal the prognostic, immunological features and mechanisms of cuproptosis critical mediator gene FDX1 in KIRC

The ferredoxin 1 (FDX1) gene had been recently reported as a critical mediator of cuproptosis, and without doubt, its roles in KIRC would be of importance. Hence, this paper was to explore the roles of FDX1 in kidney renal clear cell carcinoma (KIRC) and its potential molecular mechanisms via scRNA-sequencing and bulk RNA-sequencing analyses. FDX1 was lowly expressed in KIRC and validated both at the protein and mRNA levels (all p < 0.05). Moreover, its elevated expression was linked with a better overall survival (OS) prognosis in KIRC (p < 0.01). The independent impact of FDX1 on KIRC prognosis was demonstrated by univariate/multivariate regression analysis (p < 0.01). Gene set enrichment analysis (GSEA) identified seven pathways strongly associated with FDX1 in KIRC. Furthermore, FDX1 was also revealed to be significantly related with immunity (p < 0.05). In addition, patients with low expression of FDX1 might be more sensitive to immunotherapies. ScRNA-seq analysis found that FDX1 could be expressed in immune cells and was mainly differently expressed in Mono/Macro cells. Ultimately, we also identified several LncRNA/RBP/FDX1 mRNA networks to reveal its underlying mechanisms in KIRC. Taken together, FDX1 was closely related to prognosis and immunity in KIRC, and its RBP-involved mechanisms of LncRNA/RBP/FDX1 networks were also revealed by us.

TOPK mediates immune evasion of renal cell carcinoma via upregulating the expression of PD-L1

Although anti-PD-L1 therapy has been used in the clinical treatment of renal cell carcinoma (RCC), a proportion of patients are not sensitive to it, which may be attributed to the heterogeneity of PD-L1 expression. Here, we demonstrated that high TOPK (T-LAK cell-originated Protein Kinase) expression in RCC promoted PD-L1 expression by activating ERK2 and TGF-β/Smad pathways. TOPK was positively correlated with PD-L1 expression levels in RCC. Meanwhile, TOPK significantly inhibited the infiltration and function of CD8⁺ T cells and promoted the immune escape of RCC. Moreover, inhibition of TOPK significantly enhanced CD8⁺ T cell infiltration, promoted CD8⁺ T cell activation, enhanced anti-PD-L1 therapeutic efficacy, and synergistically enhanced anti-RCC immune response. In conclusion, this study proposes a new PD-L1 regulatory mechanism that is expected to improve the effectiveness of immunotherapy for RCC.

Prognostic prediction and immunotherapy response analysis of the fatty acid metabolism-related genes in clear cell renal cell carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) is a common urinary cancer. Although diagnostic and therapeutic approaches for ccRCC have been improved, the survival outcomes of patients with advanced ccRCC remain unsatisfactory. Fatty acid metabolism (FAM) has been increasingly recognized as a critical modulator of cancer development. However, the significance of the FAM in ccRCC remains unclear. Herein, we explored the function of a FAM-related risk score in the stratification and prediction of treatment responses in patients with ccRCC.

Methods

First, we applied an unsupervised clustering method to categorize patients from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets into subtypes and retrieved FAM-related genes from the MSigDB database. We discern differentially expressed genes (DEGs) among different subtypes. Then, we applied univariate Cox regression analysis followed by least absolute shrinkage and selection operator (LASSO) linear regression based on DEGs expression to establish a FAM-related risk score for ccRCC.

Results

We stratified the three ccRCC subtypes based on FAM-related genes with distinct overall survival (OS), clinical features, immune infiltration patterns, and treatment sensitivities. We screened nine genes from the FAM-related DEGs in the three subtypes to establish a risk prediction model for ccRCC. Nine FAM-related genes were differentially expressed in the ccRCC cell line ACHN compared to the normal kidney cell line HK2. High-risk patients had worse OS, higher genomic heterogeneity, a more complex tumor microenvironment (TME), and elevated expression of immune checkpoints. This phenomenon was validated in the ICGC cohort.

Conclusion

We constructed a FAM-related risk score that predicts the prognosis and therapeutic response of ccRCC. The close association between FAM and ccRCC progression lays a foundation for further exploring FAM-related functions in ccRCC.

Investigation of Underlying Biological Association and Targets between Rejection of Renal Transplant and Renal Cancer

Background

Post-renal transplant patients have a high likelihood of developing renal cancer. However, the underlying biological mechanisms behind the development of renal cancer in post-kidney transplant patients remain to be elucidated. Therefore, this study aimed to investigate the underlying biological mechanism behind the development of renal cell carcinoma in post-renal transplant patients.

Methods

Next-generation sequencing data and corresponding clinical information of patients with clear cell renal cell carcinoma (ccRCC) were obtained from The Cancer Genome Atlas Program (TCGA) database. The microarray data of kidney transplant patients with or without rejection response was obtained from the Gene Expression Omnibus (GEO) database. In addition, statistical analysis was conducted in R software.

Results

We identified 55 upregulated genes in the transplant patients with rejection from the GEO datasets (GSE48581, GSE36059, and GSE98320). Furthermore, we conducted bioinformatics analyses, which showed that all of these genes were upregulated in ccRCC tissue. Moreover, a prognosis model was constructed based on four rejection-related genes, including PLAC8, CSTA, AIM2, and LYZ. The prognosis model showed excellent performance in prognosis prediction in a ccRCC cohort. In addition, the machine learning algorithms identified 19 rejection-related genes, including PLAC8, involved in ccRCC occurrence. Finally, the PLAC8 was selected for further research, including its clinical and biological role.

Conclusion

In all, our study provides novel insight into the transition from the rejection of renal transplant to renal cancer. Meanwhile, PLAC8 could be a potential biomarker for ccRCC diagnosis and prognosis in post-kidney transplant patients.

Tumor infiltrating lymphocytes and radiological picture of the tumor

Tumor microenvironment (TME) is a complex entity that includes besides the tumor cells also a whole range of immune cells. Among various populations of immune cells infiltrating the tumor, tumor infiltrating lymphocytes (TILs) are a population of lymphocytes characterized by high reactivity against the tumor component. As, TILs play a key role in mediating responses to several types of therapy and significantly improve patient outcomes in some cancer types including for instance breast cancer and lung cancer, their assessment has become a good predictive tool in the evaluation of potential treatment efficacy. Currently, the evaluation of the density of TILs infiltration is performed by histopathological. However, recent studies have shed light on potential utility of several imaging methods, including ultrasonography, magnetic resonance imaging (MRI), positron emission tomography-computed tomography (PET-CT), and radiomics, in the assessment of TILs levels. The greatest attention concerning the utility of radiology methods is directed to breast and lung cancers, nevertheless imaging methods of TILs are constantly being developed also for other malignancies. Here, we focus on reviewing the radiological methods used to assess the level of TILs in different cancer types and on the extraction of the most favorable radiological features assessed by each method.

Construction and validation of programmed cell death-based molecular clusters for prognostic and therapeutic significance of clear cell renal cell carcinoma

As the dominant histological subtype of kidney cancer, clear cell renal cell carcinoma (ccRCC) poorly responds to conventional chemotherapy and radiotherapy. Although novel immunotherapies such as immune checkpoint inhibitors could have a durable effect in treating ccRCC patients, the limited availability of dependable biomarkers has restricted their application in clinic. In the study of carcinogenesis and cancer therapies, there has been a recent emphasis on researching programmed cell death (PCD). In the current study, we discovered the enriched and prognostic PCD in ccRCC utilizing gene set enrichment analysis (GSEA) and investigate the functional status of ccRCC patients with different PCD risks. Then, genes related to PCD that had prognostic value in ccRCC were identified for the conduction of non-negative matrix factorization to cluster ccRCC patients. Next, the tumor microenvironment, immunogenicity, and therapeutic response in different molecular clusters were analyzed. Among PCD, apoptosis and pyroptosis were enriched in ccRCC and correlated with prognosis. Patients with high PCD levels were related to poor prognosis and a rich but suppressive immune microenvironment. PCD-based molecular clusters were identified to differentiate the clinical status and prognosis of ccRCC. Moreover, the molecular cluster with high PCD levels may correlate with high immunogenicity and a favorable therapeutic response to ccRCC. Furthermore, a simplified PCD-based gene classifier was established to facilitate clinical application and used transcriptome sequencing data from clinical ccRCC samples to validate the applicability of the gene classifier. We thoroughly extended the understanding of PCD in ccRCC and constructed a PCD-based gene classifier for differentiation of the prognosis and therapeutic efficacy in ccRCC.

Learning to predict RNA sequence expressions from whole slide images with applications for search and classification

Deep learning methods are widely applied in digital pathology to address clinical challenges such as prognosis and diagnosis. As one of the most recent applications, deep models have also been used to extract molecular features from whole slide images. Although molecular tests carry rich information, they are often expensive, time-consuming, and require additional tissue to sample. In this paper, we propose tRNAsformer, an attention-based topology that can learn both to predict the bulk RNA-seq from an image and represent the whole slide image of a glass slide simultaneously. The tRNAsformer uses multiple instance learning to solve a weakly supervised problem while the pixel-level annotation is not available for an image. We conducted several experiments and achieved better performance and faster convergence in comparison to the state-of-the-art algorithms. The proposed tRNAsformer can assist as a computational pathology tool to facilitate a new generation of search and classification methods by combining the tissue morphology and the molecular fingerprint of the biopsy samples.

APPL1 Is a Prognostic Biomarker and Correlated with Treg Cell Infiltration via Oxygen-Consuming Metabolism in Renal Clear Cell Carcinoma

Kidney renal clear cell carcinoma (KIRC) is one of the most hazardous tumors in the urinary system. The regulation of oxygen consumption in renal clear cell carcinoma is a consequence of adaptive reprogramming of oxidative metabolism in tumor cells. APPL1 is a signaling adaptor involved in cell survival, oxidative stress, inflammation, and energy metabolism. However, the correlation of APPL1 with regulatory T cell (Treg) infiltration and prognostic value in KIRC remain unclear. In this study, we comprehensively predicted the potential function and prognostic value of APPL1 in KIRC. For KIRC patients, relatively low expression of APPL1 was associated with high degree of metastasis, pathological stage, and shorter overall time or poor prognosis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses suggested that low expression of APPL1 may be adapted to the malignant progression of tumors via affecting oxygen-consuming metabolism. In addition, the expression level of APPL1 was negatively correlated with Treg cell infiltration and chemotherapy sensitivity, which indicated that APPL1 may regulate the tumor immune infiltration and chemotherapy resistance by decrease oxygen-consuming metabolic process in KIRC. Therefore, APPL1 may become one of the important prognostic factors, and it may serve as a candidate prognostic biomarker in KIRC.

ANO4 Expression Is a Potential Prognostic Biomarker in Non-Metastasized Clear Cell Renal Cell Carcinoma

Background: Over the past decade, transcriptome profiling has elucidated many pivotal pathways involved in oncogenesis. However, a detailed comprehensive map of tumorigenesis remains an enigma to solve. Propelled research has been devoted to investigating the molecular drivers of clear cell renal cell carcinoma (ccRCC). To add another piece to the puzzle, we evaluated the role of anoctamin 4 (ANO4) expression as a potential prognostic biomarker in non-metastasized ccRCC. Methods: A total of 422 ccRCC patients with the corresponding ANO4 expression and clinicopathological data were obtained from The Cancer Genome Atlas Program (TCGA). Differential expression across several clinicopathological variables was performed. The Kaplan-Meier method was used to assess the impact of ANO4 expression on the overall survival (OS), progression-free interval (PFI), disease-free interval (DFI), and disease-specific survival (DSS). Univariate and multivariate Cox logistic regression analyses were conducted to identify independent factors modulating the aforementioned outcomes. Gene set enrichment analysis (GSEA) was used to discern a set of molecular mechanisms involved in the prognostic signature. Tumor immune microenvironment was estimated using xCell. Results: ANO4 expression was upregulated in tumor samples compared to normal kidney tissue. Albeit the latter finding, low ANO4 expression is associated with advanced clinicopathological variables such as tumor grade, stage, and pT. In addition, low ANO4 expression is linked to shorter OS, PFI, and DSS. Multivariate Cox logistic regression analysis identified ANO4 expression as an independent prognostic variable in OS (HR: 1.686, 95% CI: 1.120-2.540, p = 0.012), PFI (HR: 1.727, 95% CI: 1.103-2.704, p = 0.017), and DSS (HR: 2.688, 95% CI: 1.465-4.934, p = 0.001). GSEA identified the following pathways to be enriched within the low ANO4 expression group: epithelial-mesenchymal transition, G2-M checkpoint, E2F targets, estrogen response, apical junction, glycolysis, hypoxia, coagulation, KRAS, complement, p53, myogenesis, and TNF-α signaling via NF-κB pathways. ANO4 expression correlates significantly with monocyte (ρ = -0.1429, p = 0.0033) and mast cell (ρ = 0.1598, p = 0.001) infiltration. Conclusions: In the presented work, low ANO4 expression is portrayed as a potential poor prognostic factor in non-metastasized ccRCC. Further experimental studies should be directed to shed new light on the exact molecular mechanisms involved.

Ginsenoside Rg3 inhibits renal cell carcinoma cell migration, invasion, colony formation, and tube formation and enhances apoptosis through promoting the DNA demethylation and histone acetylation

OBJECTIVES

This study explored the effect and mechanism of Rg3 on renal cell carcinoma (RCC) progression.

METHODS

RCC cells were treated with different concentrations of Rg3, 5-Aza-dc (a methyltransferase inhibitor) or TSA (a deacetylase inhibitor). Rg3-induced cytotoxicity, migration, invasion, colony formation, tube formation and apoptosis of RCC cells were evaluated by CCK-8, wound healing, Transwell, colony formation, tube formation and flow cytometry assays, respectively. Methylation and expressions of p53, p21 and p16, and expressions of methylation-related genes and histone deacetylases and histone acetylation-related genes (H3 (acetyl K14), H3 (acetyl K9), H4 (acetyl K12), H4 (acetyl K5) and H4 (acetyl K16)) were analysed by qRT-PCR and western blot.

KEY FINDINGS

Rg3 dose-dependently decreased the viability, inhibited migration, invasion, colony formation and tube formation, and enhanced apoptosis of RCC cells. Rg3 enhanced the demethylation levels and expressions of p53, p21 and p16 as well as the expressions of histone acetylation-related genes, but repressed the expressions of methylation-related genes and histone deacetylases. Rg3 had the same effect as 5-Aza-dc and TSA did on the above-mentioned cellular changes.

CONCLUSION

Rg3 restrains RCC cell migration, invasion, colony formation and tube formation, yet enhances apoptosis through promoting demethylation of p53, p21 and p16, and histone acetylation.

Computational Gene Expression and Network Analysis of Myc Reveal Insights into Its Diagnostic and Prognostic Role in Subtypes of Renal Cancer

In this study, we analysed the Myc expression in the pan-kidney cohort (KIPAN) and kidney renal clear cell carcinoma (KIRC) in human tumour tissues compared to normal tissues. Myc is overexpressed and associated with poor overall survival (OS) in the KIPAN and KIRC. It shows that Myc plays a crucial role in the growth and maintenance of these malignancies. Additionally, we explored coexpressed genes, gene-set enrichment analysis of coexpressed genes, proteins and regulatory partners directly linked with Myc in KIPAN and KIRC and their role in cancer-specific events. Pathway enrichment analysis concluded that Myc-related genes are involved in many cancer-related pathways. Furthermore, we studied that among KIPAN, mutant forms of tumour suppressor genes have a poor prognosis and are associated with higher Myc expression but not in KIRC. This paper also investigates the correlation between Myc expression and promoter methylation, tumour-infiltrating lymphocytes, and the interaction of Myc with drugs. Our study indicates that Myc can be used as a diagnostic and prognostic biomarker in patients with KIPAN and KIRC with diverse clinical and pathological characteristics.

GBP2 promotes clear cell renal cell carcinoma progression through immune infiltration and regulation of PD‑L1 expression via STAT1 signaling

Guanylate‑binding protein 2 (GBP2) has been widely studied in cancer, however, its potential role in clear cell renal cell carcinoma (ccRCC) is not fully elucidated. The present study aimed to explore the effect of GBP2 on tumor progression and its possible underlying molecular mechanisms in ccRCC. The Cancer Genome Atlas, Gene Expression Omnibus, Cancer Cell Line Encyclopedia databases, and several bioinformatics analysis tools, such as Gene Expression Profiling Interactive Analysis 2, Kaplan‑Meier plotter, UALCAN, LinkedOmics, Metascape, GeneMANIA and Tumor Immune Estimation Resource, were used to characterize the functional relationship between GBP2 and ccRCC. Focusing on the association between GBP2 and programmed death ligand 1 (PD‑L1) in vitro, the regulatory mechanism was investigated by knockdown and overexpression of GBP2 in Caki‑1 and 786‑O cells using reverse transcription‑quantitative PCR, western blotting and co‑immunoprecipitation techniques. The results indicated that GBP2 was commonly upregulated in ccRCC, correlating with worse prognosis. In addition, GBP2 expression levels were positively associated with different patterns of immune cell infiltration, suggesting that the GBP2 gene regulates PD‑L1 expression via the signal transducer and activator of transcription 1 (STAT1) pathway. The present study suggested that GBP2 regulates tumor immune infiltration and promotes tumor immune escape through PD‑L1 expression, revealing a potential immunotherapeutic target for ccRCC.

A nomogram for predicting cancer-specific survival and overall survival in elderly patients with nonmetastatic renal cell carcinoma

Background

Renal cell carcinoma (RCC) is a common malignant tumor in the elderly, with an increasing trend in recent years. We aimed to construct a nomogram of cancer-specific survival (CSS) and overall survival (OS) in elderly patients with nonmetastatic renal cell carcinoma (nmRCC).

Methods

Clinicopathological information was downloaded from the Surveillance, Epidemiology, and End Results (SEER) program in elderly patients with nmRCC from 2010 to 2015. All patients were randomly assigned to a training cohort (70%) or a validation cohort (30%). Univariate and multivariate Cox regression analyses were used to identify independent risk factors for patient outcomes in the training cohort. A nomogram was constructed based on these independent risk factors to predict the 1-, 3-, and 5-year CSS and OS in elderly patients with nmRCC. We used a range of methods to validate the accuracy and reliability of the model, including the calibration curve, consistency index (C-index), and the area under the receiver operating curve (AUC). Decision curve analysis (DCA) was used to test the clinical utility of the model.

Results

A total of 12,116 patients were enrolled in the study. Patients were randomly assigned to the training cohort (N = 8,514) and validation cohort (N = 3,602). In the training cohort, univariate and multivariate Cox regression analysis showed that age, marriage, tumor histological type, histological tumor grade, TN stage, tumor size, and surgery are independent risk factors for prognosis. A nomogram was constructed based on independent risk factors to predict CSS and OS at 1-, 3-, and 5- years in elderly patients with nmRCC. The C-index of the training and validation cohorts in CSS were 0.826 and 0.831; in OS, they were 0.733 and 0.734, respectively. The AUC results of the training and validation cohort were similar to the C-index. The calibration curve indicated that the observed value is highly consistent with the predicted value, meaning the model has good accuracy. DCA results suggest that the clinical significance of the nomogram is better than that of traditional TNM staging.

Conclusions

We built a nomogram prediction model to predict the 1-, 3- and 5-year CSS and OS of elderly nmRCC patients. This model has good accuracy and discrimination and can help doctors and patients make clinical decisions and active monitoring.

Association Between Glycemic Status and the Risk of Kidney Cancer in Men and Women: A Nationwide Cohort Study

OBJECTIVE

Kidney cancer predominantly affects men, suggesting a biological protection against kidney cancer in women. We investigated the dose-response association between glycemic status and kidney cancer risk in men and women.

RESEARCH DESIGN AND METHODS

In this nationwide cohort study, 9,492,331 adults without cancer who underwent national health screening in 2009 were followed up until 31 December 2018. We estimated kidney cancer risk using multivariable Cox proportional hazard regression models after adjusting for potential confounders.

RESULTS

During the 78.1 million person-years of follow-up, incident kidney cancer occurred in 8,834 men and 3,547 women. The male-to-female ratio of the incidence rate was 2.1:1 in never-smokers with normoglycemia (17.8 vs. 8.5/100,000 person-years). Among never-smokers, men with diabetes, but not prediabetes, had an increased risk of kidney cancer (adjusted hazard ratio [aHR] 1.25 [95% CI 1.12-1.38] and 1.06 [0.97-1.15], respectively). Among never-smokers, women with both diabetes and prediabetes had an increased risk (aHR 1.34 [95% CI 1.21-1.49] and 1.19 [1.10-1.29], respectively) (Ptrend <0.01). Among smokers, men and women with diabetes had 49% and 85% increased kidney cancer risk (aHR 1.49 [95% CI 1.37-1.61] and 1.85 [1.26-2.73], respectively).

CONCLUSIONS

Glycemic status and kidney cancer risk exhibited a dose-response association in women. Diabetes, but not prediabetes, was associated with an increased risk in men. Although women have a lower risk of kidney cancer than men, women with even prediabetes have an increased risk. These findings should not be overlooked when monitoring for kidney complications.

Whole-Lesion CT Texture Analysis as a Quantitative Biomarker for the Identification of Homogeneous Renal Tumors

Renal tumors are very common in the urinary system, and the preoperative differential diagnosis of homogeneous renal tumors remains a challenge. This study aimed to evaluate the feasibility of the whole-lesion CT texture analysis for the identification of homogeneous renal tumors including clear cell renal cell carcinoma (ccRCC), chromophobe RCC (chRCC), and renal oncocytoma (RO). This retrospective study was approved by our local IRB. Contrast-enhanced CT examination was performed in 128 patients and histopathologically confirmed ccRCC, chRCC, and RO. The one-way ANOVA test with Bonferroni corrections was used to compare the differences, and the receiver operating characteristic (ROC) curve analysis was applied to determine the diagnostic efficiency. The whole-lesion CT histogram analysis was used to demonstrate significant differences between ccRCC and chRCC in both arterial and venous phases, and the entropy demonstrated excellent performance in discriminating these two types of tumors (AUCs = 0.95, 0.91). The inhomogeneity of ccRCC was significantly higher than that of RO both in arterial and venous phases. The entropy of chRCC was significantly lower than that of RO, and the kurtosis and entropy yielded high sensitivity (91%) and moderate specificity (74%) in the arterial phase. The whole-lesion CT histogram analysis could be useful for the differential diagnosis of homogeneous ccRCC, chRCC, and RO.

CircNTNG1 inhibits renal cell carcinoma progression via HOXA5-mediated epigenetic silencing of Slug

BACKGROUND

Recent studies have identified that circular RNAs (circRNAs) have an important role in cancer via their well-recognized sponge effect on miRNAs, which regulates a large variety of cancer-related genes. However, only a few circRNAs have been well-studied in renal cell carcinoma (RCC) and their regulatory function remains largely elusive.

METHODS

Bioinformatics approaches were used to characterize the differentially expressed circRNAs in our own circRNA-sequencing dataset, as well as two public circRNA microarray datasets. CircNTNG1 (hsa_circ_0002286) was identified as a potential tumor-suppressing circRNA. Transwell assay and CCK-8 assay were used to assess phenotypic changes. RNA pull-down, luciferase reporter assays and FISH experiment were used to confirm the interactions among circNTNG1, miR-19b-3p, and HOXA5 mRNA. GSEA was performed to explore the downstream pathway regulated by HOXA5. Immunoblotting, chromatin immunoprecipitation, and methylated DNA immunoprecipitation were used to study the mechanism of HOXA5.

RESULTS

In all three circRNA datasets, circNTNG1, which was frequently deleted in RCC, showed significantly low expression in the tumor group. The basic properties of circNTNG1 were characterized, and phenotype studies also demonstrated the inhibitory effect of circNTNG1 on RCC cell aggressiveness. Clinically, circNTNG1 expression was associated with RCC stage and Fuhrman grade, and it also served as an independent predictive factor for both OS and RFS of RCC patients. Next, the sponge effect of circNTNG1 on miR-19b-3p and the inhibition of HOXA5 by miR-19b-3p were validated. GSEA analysis indicated that HOXA5 could inactivate the epithelial-mesenchymal transition (EMT) process, and this inactivation was mediated by HOXA5-induced SNAI2 (Slug) downregulation. Finally, it was confirmed that the Slug downregulation was caused by HOXA5, along with the DNA methyltransferase DNMT3A, binding to its promoter region and increasing the methylation level.

CONCLUSIONS

Based on the experimental data, in RCC, circNTNG1/miR-19b-3p/HOXA5 axis can regulate the epigenetic silencing of Slug, thus interfering EMT and metastasis of RCC. Together, our findings provide potential biomarkers and novel therapeutic targets for future study in RCC.

Markers of local kidney cancer recurrence: A surgeon's mistake or a pattern? Review

The influence of various morphological, anatomical, genetic and other factors on the local recurrence-free survival of patients who have undergone different renal cell cancer (RCC) treatment is still a rather complex, ambiguous and controversial issue for practicing oncourologists. This review evaluates the effect of several factors on both recurrence-free survival and local recurrence-free survival. The review includes articles, clinical cases, literature reviews, and meta-analyses highlighting the analysis of independent and interrelated predisposing factors for developing local recurrence of RCC from 1984 to 2020. The PubMed, Web of Science, and Scopus databases were searched in English, Spanish, and German. A review of the literature showed the role of the following indices in the local recurrence RCC: microvascular invasion (p = 0.001), tumor necrosis (p = 0.0001), high malignancy (Fuhrman III or IV) (HR = 38.3, 95% CI 3.1-467, p = 0.004) as histological factors, tumor size as an anatomical factor. Thus, the authors state that every centimeter of the tumor increases the risk of local recurrence (p < 0.05). A group from the Mayo Clinic showed the equivalence of different treatment methods in local RCC recurrence. Thus, in the group of patients with cT1a stage kidney cancer, the 5-year local recurrence-free survival rates were 97.7% (96.7-98.6), 95.9% (92.3-99.6), and 95.9% (92.3-99.6) for renal resection, RFA, and cryoablation, respectively. Surgical margin status is the most studied and controversial marker of local renal cell carcinoma recurrence. Researchers found a direct effect of PSM on the risk of local RCC recurrence (p < 0.01). The personalized approach with the search and evaluation of predisposing factors for the local recurrence, as well as further selection of the most optimal treatment, will allow oncourologists to improve both the effectiveness of primary treatment and the recurrence-free survival of patients.

circPLIN2 promotes clear cell renal cell carcinoma progression by binding IGF2BP proteins and miR-199a-3p

Recent evidence has indicated that circular RNAs (circRNAs), a novel type of regulatory RNA, play important roles in the development and progression of various cancers. However, the potential regulatory roles and molecular mechanisms of circRNAs in clear cell renal cell carcinoma (ccRCC) remain largely unclear. Here, we explored circRNA expression profiles in 10 paired samples of RCC (including cancer tissues and surrounding tissues) from the Gene Expression Omnibus (GEO) datasets GSE124453 and GSE108735. We initially identified hsa_circ_0086457, designated circPLIN2, derived from exons 4 to 5 of the PLIN2 gene. We observed that circPLIN2 was preferentially located in the cytoplasm and was more stable than its linear counterpart PLIN2. circPLIN2 was significantly upregulated in ccRCC cells and tissues, and its overexpression was correlated with higher clinical stage and worse prognosis for ccRCC patients. Moreover, gain- and loss-of-function assays indicated that circPLIN2 promoted ccRCC cell proliferation, migration, and invasion in vitro and ccRCC tumor growth and metastasis in vivo. Mechanistically, circPLIN2 not only increased the stability of the c-Myc and MARCKSL1 mRNAs by binding to the KH domains of IGF2BP proteins but also competitively sponged miR-199a-3p to abolish the repressive effect of miR-199a-3p on ZEB1 expression, which ultimately resulted in ccRCC tumorigenesis and progression. Collectively, our results suggest that circPLIN2 may represent a promising diagnostic and prognostic biomarker and a potential therapeutic target for ccRCC patients.

Divulging a Pleiotropic Role of Succinate Receptor SUCNR1 in Renal Cell Carcinoma Microenvironment

The succinate receptor, SUCNR1, has been attributed to tumor progression, metastasis, and immune response modulation upon its activation via the oncometabolite succinate. Nonetheless, little is known about the prognostic relevance of SUCNR1 and its association with tumor immune infiltrates and microbiota in renal cell carcinoma (RCC). Herein, publicly available platforms including Human Protein Atlas, cBioPortal, TIMER2.0, and TISIDB were utilized to depict a divergent implication of SUCNR1 in the immune microenvironment of clear cell RCC (KIRC) and papillary RCC (KIRP); the two major subtypes of RCC. Our results showed that the SUCNR1 expression level was augmented in RCC compared to other solid cancers, yet with opposite survival rate predictions in RCC subtypes. Consequently, a higher expression level of SUCNR1 was associated with a good disease-specific survival rate (p = 5.797 × 10^-5) in KIRC patients albeit a poor prognostic prediction in KIRP patients (p = 1.9282 × 10^-3). Intriguingly, SUCNR1 was mainly correlated to immunomodulators and diverse immune infiltrates in KIRP. Additionally, the SUCNR1 was mostly associated with a repertoire of microbes including beneficial bacteria that likely influenced a better disease-specific survival rate in KIRC. Our findings illustrate a significant novel subtype-specific role of SUCNR1 in RCC which potentially modulates tumor immune infiltration and microbiome signature, hence altering the prognosis of cancer patients.

Molecular mechanisms of resistance to tyrosine kinase inhibitor in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcinoma (RCC). Loss of von Hippel-Lindau tumor suppressor gene is frequently observed in ccRCC and increases the expression of hypoxia-inducible factors and their targets, including epidermal growth factor, vascular endothelial growth factor, and platelet-derived growth factor. Tyrosine kinase inhibitors (TKIs) offer a survival benefit in metastatic renal cell carcinoma (mRCC). Recently, immune checkpoint inhibitors have been introduced in mRCC. Combination therapy with TKIs and immune checkpoint inhibitors significantly improved patient outcomes. Therefore, TKIs still play an essential role in mRCC treatment. However, the clinical utility of TKIs is compromised when primary and acquired resistance are encountered. The mechanism of resistance to TKI is not fully elucidated. Here, we comprehensively reviewed the molecular mechanisms of resistance to TKIs and a potential strategy to overcome this resistance. We outlined the involvement of angiogenesis, non-angiogenesis, epithelial-mesenchymal transition, activating bypass pathways, lysosomal sequestration, non-coding RNAs, epigenetic modifications and tumor microenvironment factors in the resistance to TKIs. Deep insight into the molecular mechanisms of resistance to TKIs will help to better understand the biology of RCC and can ultimately help in the development of more effective therapies.

Tat-hspb1 Suppresses Clear Cell Renal Cell Carcinoma (ccRCC) Growth via Lysosomal Membrane Permeabilization

Clear cell renal cell carcinoma (ccRCC) is the most prevalent kidney cancer, of which the incidence is increasing worldwide with a high mortality rate. Bioactive peptides are considered a significant class of natural medicines. We applied mass spectrometry-based peptidomic analysis to explore the peptide profile of human renal clear cell carcinoma and adjacent normal tissues. A total of 18,031 peptides were identified, of which 105 unique peptides were differentially expressed (44 were up-regulated and 61 were down-regulated in ccRCC tissues). Through bioinformatic analysis, we finally selected one peptide derived from the HSPB1 protein (amino acids 12-35 of the N-terminal region of HSPB1). Next, we fused this peptide to the HIV-Tat, generated a novel peptide named Tat-hspb1, and found that Tat-hspb1 inhibited ccRCC cells' viability while being less cytotoxic to normal epithelial cells. Furthermore, Tat-hspb1 induced apoptosis and inhibited the proliferation and migration of ccRCC cells. Furthermore, we demonstrated that Tat-hspb1 was predominantly localized in lysosomes after entering the ccRCC cell and induced lysosomal membrane permeabilization (LMP) and the release of cathepsin D from lysosomes. Taken together, Tat-hspb1 has the potential to serve as a new anticancer drug candidate.