Cellular milieu in clear cell renal cell carcinoma

KIF14 plays a role in the regulation of the cell cycle and has implications for prognosis in clear cell renal cell carcinoma

BACKGROUND

Kinesin family member 14 (KIF14) is a significant multifunctional protein that has been linked to several malignancies. However, the varied expression profiles of KIF14 and its prognostic relevance in Clear cell renal cell carcinoma (ccRCC) have yet to be elucidated.

METHODS

Patients with ccRCC were obtained from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and ArrayExpress databases. A comparison of KIF14 expression levels between ccRCC and normal tissues was conducted using the Wilcoxon rank sum test. Logistic regression analysis was subsequently employed to evaluate the relationship between KIF14 expression and clinicopathological features. Furthermore, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) term analysis, gene set enrichment analysis (GSEA) and single sample gene set enrichment analysis (ssGSEA), as well as CIBERSORT, were utilized to elucidate the enriched pathways and functions linked to KIF14 and to quantify the level of immune cell infiltration. Kaplan-Meier analysis was conducted to assess the correlation between KIF14 expression and survival. Additionally, KIF14 expression was downregulated in A498 ccRCC cells, and their proliferation, expansion capacity, cell cycle, and apoptosis were assessed through CCK-8 assays, colony formation assays, 7-AAD staining, and Annexin V/PI staining, respectively.

RESULTS

The findings of this study demonstrate that KIF14 mRNA levels are notably increased in ccRCC. Furthermore, a positive association was observed between KIF14 expression and cancer stage, nodal metastasis, and the infiltration of various immune cells in ccRCC. High levels of KIF14 were also found to be indicative of poor survival outcomes among ccRCC patients. Knockdown of KIF14 in A498 cells resulted in reduced proliferation, diminished colony formation capacity, cell cycle arrest, increased apoptosis, and downregulation of CyclinD1 and CDK4.

CONCLUSIONS

KIF14 down-regulates cell cycle proteins CyclinD1 and CDK4 to facilitate the proliferation of ccRCC cells, suggesting its potential as a therapeutic target and prognostic biomarker in ccRCC.

Prognostic factors and nomogram development for survival in renal cell carcinoma patients with multiple primary cancers: a retrospective study

Background

Patients with renal cell cancer have an increased risk of developing multiple primary cancers (MPCs) due to improved survival rates. The purpose of this study was to evaluate the clinicopathological features of MPCs and to generate a useful tool for predicting cancer-specific survival (CSS) in these patients.

Methods

A retrospective analysis was conducted on data from renal cell carcinoma (RCC) who were diagnosed with MPCs between 2001 and 2021 from the Surveillance, Epidemiology, and End Results (SEER) database. Patients with RCC meeting the criteria were selected for Kaplan-Meier (KM) survival analysis. The main outcome of this study was CSS, defined as the time from the initial diagnosis to either death due to cancer or the last follow-up. The Cox regression model was used to analyze the CSS factors of MPCs, the results of the multivariate analysis were displayed in a forest map, and the significant variables identified in the multivariate Cox analysis were used to construct the nomogram. Area under the curve (AUC) and calibration plots were used to evaluate the predictive performance of the nomogram.

Results

A total of 2,078 cases of renal cancer with MPCs diagnosed between 2001 and 2021 were included. Age and grade were determined through both univariate and multivariate analyses to be independent prognostic factors affecting CSS. Based on clinical practice, the final nomogram was constructed using the variables: sex, age, grade, summary stage, tumor-node-metastasis (TNM) stage and tumor size to predict CSS at 60, 120, and 180 months. The concordance index (C-index) for the CSS nomogram was 0.670 [95% confidence interval (CI): 0.642-0.698]. The model demonstrated a good predictive performance. To assess the consistency between observed and predicted values, a calibration curve was developed.

Conclusions

This study identified risk factors for CSS in patients with clear cell RCC (ccRCC) with MPCs and developed a nomogram to predict CSS in these patients. The model demonstrates strong clinical applicability and can serve as a valuable clinical decision-making tool for physicians and patients.

Identification of miRNAs and Their Target Genes Associated with Sunitinib Resistance in Clear Cell Renal Cell Carcinoma Patients

Sunitinib has greatly improved the survival of clear cell renal cell carcinoma (ccRCC) patients in recent years. However, 20-30% of treated patients do not respond. To identify miRNAs and genes associated with a response, comparisons were made between biopsies from responder and non-responder ccRCC patients. Using integrated transcriptomic analyses, we identified 37 miRNAs and 60 respective target genes, which were significantly associated with the NF-kappa B, PI3K-Akt and MAPK pathways. We validated expression of the miRNAs (miR-223, miR-155, miR-200b, miR-130b) and target genes (FLT1, PRDM1 and SAV1) in 35 ccRCC patients. High levels of miR-223 and low levels of FLT1, SAV1 and PRDM1 were associated with worse overall survival (OS), and combined miR-223 + SAV1 levels distinguished responders from non-responders (AUC = 0.92). Using immunohistochemical staining of 170 ccRCC patients, VEGFR1 (FLT1) expression was associated with treatment response, histological grade and RECIST (Response Evaluation Criteria in Solid Tumors) score, whereas SAV1 and BLIMP1 (PRDM1) were associated with metachronous metastatic disease. Using in situ hybridisation (ISH) to detect miR-155 we observed higher tumoural cell expression in non-responders, and non-tumoural cell expression with increased histological grade. In summary, our preliminary analysis using integrated miRNA-target gene analyses identified several novel biomarkers in ccRCC patients that surely warrant further investigation.

VHL-dependence of EHHADH Expression in a Human Renal Cell Carcinoma Cell Line

The von Hippel-Lindau tumor suppressor gene (VHL) is mutated in up to 90% of clear cell renal cell carcinoma (ccRCC) cases, thus playing a key role in ccRCC pathogenesis. ccRCC can be classified as a metabolic disease in which alterations in fatty acid metabolism facilitate cancer cell proliferation. Enoyl-CoA hydratase and 3-hydroxyacyl CoA dehydrogenase (EHHADH) is an enzyme involved in peroxisomal fatty acid degradation. It is primarily expressed in renal proximal tubule cells, presumably the origin of ccRCC. Although EHHADH is still a relatively unexplored gene, it is known to be differentially expressed in several tumors. In this study, analysis of several databases revealed that EHHADH expression is downregulated in ccRCC samples compared to healthy kidney samples. Moreover, cell culture experiments were performed to investigate the relationship between EHHADH and VHL at the gene and protein level. qPCR and Western blot analyses using the human ccRCC cell line RCC4 revealed that EHHADH is expressed in a VHL-dependent manner. RCC4 cells reconstituted with VHL show significantly higher EHHADH mRNA and protein levels than VHL-deficient RCC4 control cells. These results indicate that the downregulation of EHHADH in ccRCC reported may be due to the loss of VHL function. This study is the first to molecularly characterize EHHADH, a key enzyme in peroxisomal ß-oxidation, in relation to VHL, suggesting a potential pathogenic interaction that is worthy of further investigation.

Dysregulated ANLN reveals immune cell landscape and promotes carcinogenesis by regulating the PI3K/Akt/mTOR pathway in clear cell renal cell carcinoma

Background

Abnormal anillin (ANLN) expression has been observed in multiple tumours and is closely associated with patient prognosis and clinical features. In this study, we systematically elucidated the clinical significance and biological roles of ANLN in patients with clear cell renal cell carcinoma (ccRCC).

Methods

We obtained transcriptome and clinical data of patients with ccRCC from public databases. Multi-omics data and clinical samples were combined to analyse the correlation between ANLN expression and the clinical characteristics of patients with renal cancer. Additionally, the immune cell landscape of ANLN expression was evaluated using different immune algorithms in the tumour microenvironment. The tumour-promoting potential of ANLN was confirmed using in vitro assays, including CCK8 and Transwell assays.

Results

Bioinformatics analysis showed that ANLN is over-expressed in patients with ccRCC, as validated by clinical samples. Publicly available clinical data suggest that high ANLN expression may indicate poor outcomes in patients with ccRCC. Moreover, biological function analysis revealed a marked enrichment of the cell cycle and PI3K-Akt pathways. The distribution of immune cells, particularly M2 macrophages, differed in patients with ccRCC. Furthermore, ANLN silencing inhibited the proliferation, migration, and invasion of renal cancer cells in vitro. After ANLN expression was knocked down in 786-O cells, the protein levels of important PI3K signalling pathway components, including PI3K, Akt, and mTOR, drastically decreased.

Conclusions

These findings suggest that ANLN is dysregulated in renal cancer tissues and promotes tumour progression by activating the PI3K/Akt/mTOR signalling pathway.

High risk clear cell renal cell carcinoma microenvironments contain protumour immunophenotypes lacking specific immune checkpoints

Perioperative immune checkpoint inhibitor (ICI) trials for intermediate high-risk clear cell renal cell carcinoma (ccRCC) have failed to consistently demonstrate improved patient outcomes. These unsuccessful ICI trials suggest that the tumour infiltrating immunophenotypes, termed here as the immune cell types, states and their spatial location within the tumour microenvironment (TME), were unfavourable for ICI treatment. Defining the tumour infiltrating immune cells may assist with the identification of predictive immunophenotypes within the TME that are favourable for ICI treatment. To define the immunophenotypes within the ccRCC TME, fresh para-tumour (pTME, n = 2), low-grade (LG, n = 4, G1-G2) and high-grade (HG, n = 4, G3-G4) tissue samples from six patients with ccRCC presenting at a tertiary referral hospital underwent spatial transcriptomics sequencing (ST-seq). Within the generated ST-seq datasets, immune cell types and states, termed here as exhausted/pro-tumour state or non-exhausted/anti-tumour state, were identified using multiple publicly available single-cell RNA and T-cell receptor sequencing datasets as references. HG TMEs revealed abundant exhausted/pro-tumour immune cells with no consistent increase in expression of PD-1, PD-L1 and CTLA4 checkpoints and angiogenic genes. Additional HG TME immunophenotype characteristics included: pro-tumour tissue-resident monocytes with consistently increased expression of HAVCR2 and LAG3 checkpoints; an exhausted CD8+ T cells sub-population with stem-like progenitor gene expression; and pro-tumour tumour-associated macrophages and monocytes within the recurrent TME with the expression of TREM2. Whilst limited by a modest sample size, this study represents the largest ST-seq dataset on human ccRCC. Our study reveals that high-risk ccRCC TMEs are infiltrated by exhausted/pro-tumour immunophenotypes lacking specific checkpoint gene expression confirming that HG ccRCC TME are immunogenic but not ICI favourable.

Integrating scRNA and bulk-RNA sequencing develops a cell senescence signature for analyzing tumor heterogeneity in clear cell renal cell carcinoma

Introduction

Cellular senescence (CS) plays a critical role in cancer development, including clear cell renal cell carcinoma (ccRCC). Traditional RNA sequencing cannot detect precise molecular composition changes within tumors. This study aimed to analyze cellular senescence's biochemical characteristics in ccRCC using single RNA sequencing (ScRNA-seq) and traditional RNA sequencing (Bulk RNA-seq).

Methods

Researchers analyzed the biochemical characteristics of cellular senescence in ccRCC using ScRNA-seq and Bulk RNA-seq. They combined these approaches to identify differences between malignant and non-malignant phenotypes in ccRCC across three senescence-related pathways. Genes from these pathways were used to identify molecular subtypes associated with senescence, and a new risk model was constructed. The function of the gene DUSP1 in ccRCC was validated through biological experiments.

Results

The combined analysis of ScRNA-seq and Bulk RNA-seq revealed significant differences between malignant and non-malignant phenotypes in ccRCC across three senescence-related pathways. Researchers identified genes from these pathways to identify molecular subtypes associated with senescence, constructing a new risk model. Different subgroups showed significant differences in prognosis level, clinical stage and grade, immune infiltration, immunotherapy, and drug sensitivity.

Discussion

Senescence signature markers are practical biomarkers and predictors of molecular typing in ccRCC. Differences in prognosis level, clinical stage and grade, immune infiltration, immunotherapy, and drug sensitivity between different subgroups indicate that this approach could provide valuable insights into senescence-related treatment options and prognostic assessment for patients with ccRCC. The function of the gene DUSP1 in ccRCC was validated through biological experiments, confirming its feasibility as a novel biomarker for ccRCC. These findings suggest that targeted therapies based on senescence-related mechanisms could be an effective treatment option for ccRCC.

Cellular and Molecular Players in the Tumor Microenvironment of Renal Cell Carcinoma

Globally, clear-cell renal cell carcinoma (ccRCC) represents the most prevalent type of kidney cancer. Surgery plays a key role in the treatment of this cancer, although one third of patients are diagnosed with metastatic ccRCC and about 25% of patients will develop a recurrence after nephrectomy with curative intent. Molecular-target-based agents, such as tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs), are recommended for advanced cancers. In addition to cancer cells, the tumor microenvironment (TME) includes non-malignant cell types embedded in an altered extracellular matrix (ECM). The evidence confirms that interactions among cancer cells and TME elements exist and are thought to play crucial roles in the development of cancer, making them promising therapeutic targets. In the TME, an unfavorable pH, waste product accumulation, and competition for nutrients between cancer and immune cells may be regarded as further possible mechanisms of immune escape. To enhance immunotherapies and reduce resistance, it is crucial first to understand how the immune cells work and interact with cancer and other cancer-associated cells in such a complex tumor microenvironment.

Inflammatory Networks in Renal Cell Carcinoma

Cancer-associated inflammation has been established as a hallmark feature of almost all solid cancers. Tumor-extrinsic and intrinsic signaling pathways regulate the process of cancer-associated inflammation. Tumor-extrinsic inflammation is triggered by many factors, including infection, obesity, autoimmune disorders, and exposure to toxic and radioactive substances. Intrinsic inflammation can be induced by genomic mutation, genome instability and epigenetic remodeling in cancer cells that promote immunosuppressive traits, inducing the recruitment and activation of inflammatory immune cells. In RCC, many cancer cell-intrinsic alterations are assembled, upregulating inflammatory pathways, which enhance chemokine release and neoantigen expression. Furthermore, immune cells activate the endothelium and induce metabolic shifts, thereby amplifying both the paracrine and autocrine inflammatory loops to promote RCC tumor growth and progression. Together with tumor-extrinsic inflammatory factors, tumor-intrinsic signaling pathways trigger a Janus-faced tumor microenvironment, thereby simultaneously promoting or inhibiting tumor growth. For therapeutic success, it is important to understand the pathomechanisms of cancer-associated inflammation, which promote cancer progression. In this review, we describe the molecular mechanisms of cancer-associated inflammation that influence cancer and immune cell functions, thereby increasing tumor malignancy and anti-cancer resistance. We also discuss the potential of anti-inflammatory treatments, which may provide clinical benefits in RCCs and possible avenues for therapy and future research.