Current Landscape of Genomic Biomarkers in Clear Cell Renal Cell Carcinoma

Metabolic reprogramming and immune microenvironment profiling in clear cell renal cell carcinoma: implications for prognosis, targeted therapy, and drug resistance

Clear cell renal cell carcinoma (ccRCC) is the most prevalent form of kidney cancer, distinguished by intricate interactions between metabolic reprogramming, immune microenvironment dynamics, and genetic mutations. In this detailed investigation, we analyzed the ccRCC cohort from The Cancer Genome Atlas (TCGA) alongside 81 metabolic signaling pathways from the KEGG database. By utilizing Gene Set Variation Analysis (GSVA), we performed hierarchical clustering of patients based on their metabolic pathway activity profiles, identifying three distinct clusters with notable differences in pathway activity and survival outcomes. Cluster 1 displayed high metabolic activity and more favorable survival outcomes, while Cluster 3 was characterized by low metabolic activity and poorer prognosis. Clinical comparisons revealed significant disparities in gender, histological stage, and survival status, with Cluster 3 exhibiting a higher proportion of patients at advanced stages and those who had passed away. Genetically, Cluster 1 showed the highest mutation burden, with prominent mutations in genes such as VHL and PBRM1. Biological process analysis indicated that pathways like organic carboxylic acid metabolism and ATP synthesis were upregulated in Cluster 1 but suppressed in Cluster 3. Machine learning models (GBM, CoxBoost, and LASSO regression) enabled the identification of four pivotal genes-BCAT1, IL4I1, ACADM, and ACADSB-which were subsequently used to construct a multifactorial Cox regression model. This model successfully stratified patients into high- and low-risk groups, correlating with marked differences in immune activities. The high-risk group showed elevated expression of chemokines, TNF, and HLA molecules. Drug sensitivity analysis suggested that AKT inhibitor III was more effective in the low-risk cohort, while Bortezomib might be more beneficial for high-risk patients. Additionally, a clinical prediction model integrating risk scores and clinical factors demonstrated strong predictive power for patient survival. Methylation profiling of the core genes via the UALCAN platform revealed distinct epigenetic signatures in ccRCC, providing deeper insight into the disease's molecular mechanisms. This study contributes to a more comprehensive understanding of ccRCC and proposes valuable directions for personalized treatment strategies and enhanced patient management.

Biomimetic Copper Nanozyme Reprograms Cold Tumor via Cuproptosis-Pyroptosis Crosstalk for Potent Renal Carcinoma Immunotherapy

Immune checkpoint blockade (ICB) therapy is an emerging strategy for renal cell carcinoma (RCC). However, its clinical efficacy remains constrained by its inherently poor immunogenicity and insufficient cytotoxic T lymphocyte (CTL) infiltration. Herein, we engineer a biomimetic copper nanozyme (Cu2O-OMV) by integrating Cu2O nanoparticles with bacterial outer-membrane vesicles (OMVs) to activate the antitumor immune response and synergize with ICB therapy. The Cu2O-OMV nanozyme exhibits peroxidase (POD)-like catalytic activity and releases Cu+ to exert Fenton-like activity, generating cytotoxic hydroxyl radicals (·OH) for tumor inhibition. Furthermore, Cu+ accumulation promotes the occurrence of cuproptosis, leading to the mitochondrial aggregation of lipoylated dihydrolipoamide S-acetyltransferase and depletion of ferredoxin 1. Notably, Cu2O-OMV concurrently activates pyroptosis via the noncanonical inflammasome pathway through its intrinsic lipopolysaccharide cargo, directly inhibiting tumor growth and inducing inflammatory cytokine release. The coordinated induction of cuproptosis and pyroptosis synergistically amplifies immunogenic cell death to enhance tumor immunogenicity, thereby promoting dendritic cell maturation and CTL infiltration. After combining with αPD-L1, it effectively destroys tumor cells to activate the antitumor immune response, thereby inhibiting tumor metastasis. Our study demonstrates a biomimetic nanozyme-driven strategy that harnesses dual cuproptosis-pyroptosis pathways to enhance the tumor immunogenicity and amplify the ICB efficacy, offering a transformative approach for RCC immunotherapy.

The pathogenesis and therapeutic implications of metabolic reprogramming in renal cell carcinoma

Renal cell carcinoma (RCC), a therapeutically recalcitrant genitourinary malignancy, exemplifies the profound interplay between oncogenic signaling and metabolic adaptation. Emerging evidence positions metabolic reprogramming as a central axis of RCC pathogenesis, characterized by dynamic shifts in nutrient utilization that transcend canonical Warburg physiology to encompass lipid anabolism, glutamine auxotrophy, and microenvironment-driven metabolic plasticity. This orchestrated rewiring of cellular energetics sustains tumor proliferation under hypoxia while fostering immunosuppression through metabolite-mediated T cell exhaustion and myeloid-derived suppressor cell activation. Crucially, RCC exhibits metabolic heterogeneity across histological subtypes and intratumoral regions-a feature increasingly recognized as a determinant of therapeutic resistance. Our review systematically deciphers the molecular architecture of RCC metabolism, elucidating how VHL/HIF axis mutations, mTOR pathway dysregulation, and epigenetic modifiers converge to reshape glucose flux, lipid droplet biogenesis, and amino acid catabolism. We present novel insights into spatial metabolic zonation within RCC tumors, where pseudohypoxic niches engage in lactate shuttling and cholesterol efflux to adjacent vasculature, creating pro-angiogenic and immunosuppressive microdomains. Therapeutically, we evaluate first-in-class inhibitors targeting rate-limiting enzymes in de novo lipogenesis and glutamine metabolism, while proposing biomarker-driven strategies to overcome compensatory pathway activation. We highlight the synergy between glutaminase inhibitors and PD-1 blockade in reinvigorating CD8+ T cell function, and the role of lipid-loaded cancer-associated fibroblasts in shielding tumors from ferroptosis. Finally, we outline a translational roadmap integrating multi-omics profiling, functional metabolomics, and spatial biology to match metabolic vulnerabilities with precision therapies.

The biological function and prognostic significance of ferroptosis-related genes in clear cell renal cell carcinoma

Background

Ferroptosis-related genes are essential in cancer development. However, the specific roles of ferroptosis-related genes in clear cell renal cell carcinoma (ccRCC) remain largely unexplored. This study aims to elucidate the biological functions and potential therapeutic implications of ferroptosis-related genes in ccRCC.

Methods

A model integrating the Cancer Genome Atlas (TCGA) database and the GEO dataset was established based on ferroptosis-related genes and clinical data. To determine the proliferative function of ferroptosis-related genes in ccRCC cells, CCK-8 kit assays and colony formation experiments were conducted. Additionally, wound-healing experiments were performed to evaluate the migratory capabilities of these cells.

Results

We identified eight ferroptosis-related genes that are significantly associated with the prognosis of ccRCC patients. The expression levels of these genes exhibited marked differences between tumor tissues and normal tissues, and they were shown to influence both the proliferation and metastasis of ccRCC cells. Subsequently, a model combining ferroptosis-related genes model constructed with gene data and clinical characteristics was constructed, and classified the patients into high- and low-risk groups. The area under the curve (AUC) for this model in diagnosing ccRCC was 0.937. In terms of survival prediction, the AUC values were 0.875, 0.818, and 0.790 at 1, 3, and 5 years, respectively. Notably, high-risk patients exhibited significantly poorer survival outcomes compared to those in the low-risk group. Furthermore, high-risk individuals demonstrated elevated expression of immune checkpoint genes and enhanced antitumor immunity, suggesting that these patients may benefit from immunotherapy.

Conclusion

Ferroptosis-related genes play a critical role in the biological functions of ccRCC cells. Our prognostic model has the potential to be applied in predicting patient outcomes and assessing antitumor immunity in ccRCC.

Clear Cell Renal Cell Carcinoma: Characterizing the Phenotype of Von Hippel-Lindau Mutation Using MRI

BACKGROUND

The von Hippel-Lindau (VHL) mutation is an important alteration in clear cell renal cell carcinoma (ccRCC); however, its imaging phenotype remains unclear.

PURPOSE

To investigate whether MRI features can reflect the VHL mutation status.

STUDY TYPE

Retrospective.

FIELD STRENGTH/SEQUENCE

3 T/fast spin echo T2-weighted, spin-echo echo planar diffusion-weighted, gradient recalled echo T1-weighted, gradient recalled echo chemical-shift T1-weighted, and contrast-enhanced gradient recalled echo T1-weighted sequences.

POPULATION

One hundred five patients with ccRCC who underwent preoperative contrast-enhanced MRI and subsequent genomic sequencing: 59 consecutive patients from our institution (38 [64.41%] with VHL mutations) formed a training cohort, and 46 from The Cancer Genome Atlas (TCGA) database (24 [52.17%] with VHL mutations) formed an independent test cohort.

ASSESSMENT

Two radiologists, with 23 and 33 years of experience respectively, jointly evaluated the semantic MRI features of the primary lesion in ccRCCs to propose potential features related to VHL mutations in both cohorts. Three additional readers, with 5, 7, and 10 years of experience respectively, independently reviewed all lesions to assess the interobserver agreement of MRI features. A VHL mutational likelihood score (VHL-MULIS) system was constructed using the training cohort and validated using the independent test cohort.

STATISTICAL TESTS

Fisher's test or chi-square test, t-test or Mann-Whitney U test, logistic regression, Cohen's kappa (κ), area under the receiver operating characteristic curve (AUC). A two-sided P value <0.05 was considered statistically significant.

RESULTS

In both the local and public cohorts, T2-weighted signal intensity and presence of microscopic fat from primary lesions were significantly associated with VHL mutation status. The VHL-MULIS incorporated maximum diameter, T2-weighted signal intensity, and presence of microscopic fat in the training cohort and demonstrated promising diagnostic ability (AUC, 0.82; sensitivity, 0.79; specificity, 0.82) and substantial interobserver agreement (κ, 0.787) in the test cohort.

DATA CONCLUSION

The VHL mutation exhibited a distinct MRI phenotype. Integrating multiple semantic MRI features has potential to reflect the mutation status in patients with ccRCC.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 2.

Advances in Adjuvant Therapy for Renal Cell Carcinoma: Perspectives on Risk Stratification and Treatment Outcomes

Radical surgery is effective for localized renal cell carcinoma (RCC). However, recurrence occurs in up to 40% of patients, underscoring the need for adjuvant therapy to improve the prognosis. Historically, adjuvant treatments, including tyrosine kinase inhibitors, have shown limited success, failing to improve overall survival. The introduction of the immune checkpoint inhibitor pembrolizumab, as demonstrated in the KEYNOTE-564 trial, has revolutionized the field by showing significant overall survival benefits and prompting updates to RCC treatment guidelines. Accurate risk assessment is critical for identifying high-risk patients most likely to benefit from adjuvant therapy. Established risk models, such as the UCLA Integrated Staging System and the Leibovich score, incorporate clinical and pathological factors to stratify recurrence risk. Recent enhancements in these models have improved predictive accuracy, enabling better optimization of inclusion criteria for clinical trials targeting high-risk recurrence and the development of individualized surveillance protocols to refine patient selection for adjuvant treatment. This review examines the evolution of risk stratification models and adjuvant therapy for RCC, highlighting the potential of innovative biomarkers, such as liquid biopsies, to further enhance patient selection and optimize treatment outcomes. Ongoing clinical trials investigating new combinations of immune checkpoint inhibitors hold promise, and integrating accurate risk assessment with advanced immunotherapy will be key to improving postoperative survival rates for patients with RCC.

A novel multigene panel (Sig27) robustly predicts poor prognosis of renal cell carcinoma via high-level associations with immunosuppressive features

BACKGROUND

We investigated a 27-gene panel (Sig27), derived from prostate cancer, for risk stratification of RCC (clear cell RCC/ccRCC, papillary RCC/pRCC, and chromophobe RCC/chRCC).

METHODS

Sig27 gene expressions were examined in 960 RCC and 201 kidney tissues. Sig27 was evaluated for predicting overall survival (OS), association with immune checkpoints (IC), regulatory T cells (Tregs), myeloid-derived suppressor cells (MDSC), and tumor-associated macrophages (TAM) in RCC.

RESULTS

Sig27 robustly predicts OS of ccRCC, pRCC, and chRCC. Sig27 stratifies high-risk ccRCCs: median survival month (MSM) 19.3 and 80.4% of deaths and high-risk pRCCs (MSM 19.6 and 58.6% of death) compared to low-risk ccRCCs (2.9% of death) and pRCCs (2.7% of fatality). Sig27 contains several novel genes related to the RCC immunosuppressive features. FPR3, NOD2, MCTP1, LAMP3, TFEC, and FAM65B are highly correlated with MDSC, Treg, TAM and multiple (≥12) ICs in RCCs. FPR3 and NOD2 are pattern recognition receptors and initiate proinflammatory responses via sensing pathogen-associated molecular patterns and damage-associated molecular patterns; their upregulations may contribute to chronic inflammation in RCC. The Sig27 metagene is expressed in ccRCC-associated immune cells: exhausted CD8T cells, TAM, Treg, and others.

CONCLUSIONS

Sig27 is a novel and effective pan-RCC biomarker with high-level associations with RCC immunosuppressive features.

Integrated multi-omics analysis identifies a machine learning-derived signature for predicting prognosis and therapeutic vulnerability in clear cell renal cell carcinoma

AIMS

Clear cell renal cell carcinoma (ccRCC) shows considerable variation within and between tumors, presents varying treatment responses among patients, possibly due to molecular distinctions. This study utilized a multi-center and multi-omics analysis to establish and validate a prognosis and treatment vulnerability signature (PTVS) capable of effectively predicting patient prognosis and drug responsiveness.

MATERIALS AND METHODS

To address this complexity, we constructed an integrative multi-omics analysis using 10 clustering algorithms on ccRCC patient data. Afterwards, we applied bootstrapping in univariate Cox regression and the Boruta algorithm to pinpoint clinically relevant genes. Based on this, we developed a robust PTVS using seven machine learning algorithms.

KEY FINDINGS

Our analysis revealed two distinct ccRCC subtypes with differential prognostic implications, notably identifying subtype 2 with poorer outcomes. Patients in the low PTVS group exhibited superior prognosis statistics and an augmented sensitivity to immunotherapy, features consistent with a 'hot tumor' phenotype. Conversely, individuals within the high PTVS group exhibited diminished prognosis statistic and restricted advantages from immunotherapy. Importantly, the PTVS holds future potential as a notable biomarker for guiding personalized treatment strategies, with four prospective targets (CTSK, XDH, PKMYT1, and EGLN2) indicating therapeutic promise in patients scoring high on PTVS.

SIGNIFICANCE

The integrative analysis of multi-omics data profoundly enhances the molecular stratification of ccRCC, underscoring far-reaching impact of such comprehensive profiling on its therapeutic strategies.

Zebularine showed anti-tumor efficacy in clear cell renal cell carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) has the highest morbidity among renal cell carcinoma (RCC) subtypes. While existing clinical pharmacological intervention strategies have achieved certain efficacy, challenges including inevitable drug resistance and intricate immune heterogeneity of ccRCC continue to hinder their biomedical application. Therefore, developing novel immunotherapeutic agents and identifying patients who can gain the greatest benefits from these therapies are urgent issues.

Methods

To address these challenges, mRNA expression profile and clinical data of ccRCC were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. These data were integrated and randomly allocated into training and test sets. Immune-related differentially expressed genes (IRDEGs) were used to construct an immune-related gene prognostic index (IRGPI). Both prognostic performance metrics and immune phenotyping were employed to evaluate the effectiveness of the model. Furthermore, model IRDEGs (mIRDEGs) in two risk subgroups were leveraged to select potential therapeutic compounds. Afterwards, network pharmacology and molecular docking techniques were used to elucidate the anti-cancer mechanisms of Zebularine (Zeb). Finally, the anti-cancer efficacy of Zeb was validated through in vivo and in vitro experiments.

Results

Our constructed IRGPI exhibited superior prognostic performance. The drug screening revealed Zeb potentially targets the PI3K-Akt signaling pathway to exert its anti-cancer effects. Subsequent experimental validation corroborated these theoretical findings.

Conclusion

This study presents a prognostic model to evaluate immune cell infiltration and predict the prognosis of ccRCC patients. The identified small molecule compound provides a novel therapeutic avenue for treating ccRCC patients.

Differences in mutations across tumour sizes in clear-cell renal cell carcinoma

OBJECTIVE

To assess the distribution of key mutations across tumour sizes in clear-cell renal cell carcinoma (ccRCC), and secondarily to examine the prognostic impact of aggressive mutations in smaller ccRCCs.

PATIENT AND METHODS

The distribution of mutations (VHL, PBRM1, SETD2, BAP1 and CDKN2A loss) across tumour sizes was assessed in 1039 ccRCCs treated with nephrectomy in cohorts obtained from the Tracking Cancer Evolution (TRACERx), The Cancer Genome Atlas (TCGA) and the Cancer Genomics of the Kidney (CAGEKID) projects. Logistic regression was used to model the presence of each mutation against size. In our secondary analysis, we assessed a subset of ccRCCs ≤7 cm for associations of key aggressive mutations (SETD2, BAP1, and CDKN2A loss) with metastasis, invasive disease and overall survival, while controlling for size. A subset of localised tumours ≤7 cm was also used to assess associations with recurrence after nephrectomy.

RESULTS

On logistic regression, each 1-cm increase in tumour size was associated with aggressive mutations, SETD2, BAP1, and CDKN2A loss, at odds ratios (ORs) of 1.09, 1.10 and 1.19 (P < 0.001), whereas no significant association was observed between tumour size and PBRM1 (OR 1.02; P = 0.23). VHL was mildly negatively associated with a 1-cm increase in size (OR 0.95; P = 0.01). Among tumours ≤7 cm, SETD2 and CDKN2A loss were associated with metastatic disease at ORs of 3.86 and 3.84 (P < 0.05) while controlling for tumour size. CDKN2A loss was associated with worse overall survival, with a hazard ratio (HR) of 2.19 (P = 0.03). Among localised tumours ≤7 cm, SETD2 was associated with worse recurrence-free survival (HR 2.00; P = 0.03).

CONCLUSION

Large and small ccRCCs are genomically different. Aggressive mutations, namely, SETD2, BAP1, and CDKN2A loss, are rarely observed in small ccRCCs and are observed more frequently in larger tumours. However, when present in tumours ≤7 cm, SETD2 mutations and CDKN2A loss were still independently associated with invasive disease, metastasis, worse survival, and recurrence after resection, after controlling for size.

The molecular code of kidney cancer: A path of discovery for gene mutation and precision therapy

Renal cell carcinoma (RCC) is a malignant tumor with highly heterogeneous and complex molecular mechanisms. Through systematic analysis of TCGA, COSMIC and other databases, 24 mutated genes closely related to RCC were screened, including VHL, PBRM1, BAP1 and SETD2, which play key roles in signaling pathway transduction, chromatin remodeling and DNA repair. The PI3K/AKT/mTOR signaling pathway is particularly important in the pathogenesis of RCC. Mutations in genes such as PIK3CA, MTOR and PTEN are closely associated with metabolic abnormalities and tumor cell proliferation. Clinically, mTOR inhibitors and VEGF-targeted drugs have shown significant efficacy in personalized therapy. Abnormal regulation of metabolic reprogramming, especially glycolysis and glutamine metabolic pathways, provides tumor cells with continuous energy supply and survival advantages, and GLS1 inhibitors have shown promising results in preclinical studies. This paper also explores the potential of immune checkpoint inhibitors in combination with other targeted drugs, as well as the promising application of nanotechnology in drug delivery and targeted therapy. In addition, unique molecular mechanisms are revealed and individualized therapeutic strategies are explored for specific subtypes such as TFE3, TFEB rearrangement type and SDHB mutant type. The review summarizes the common gene mutations in RCC and their molecular mechanisms, emphasizes their important roles in tumor diagnosis, treatment and prognosis, and looks forward to the application prospects of multi-pathway targeted therapy, metabolic targeted therapy, immunotherapy and nanotechnology in RCC treatment, providing theoretical support and clinical guidance for individualized treatment and new drug development.

EGR1 inhibits clear cell renal cell carcinoma proliferation and metastasis via the MAPK15 pathway

Background

Clear cell renal carcinoma (ccRCC), the leading histological subtype of RCC, lacks any targeted therapy options. Although some studies have shown that early growth response factor 1 (EGR1) has a significant role in cancer development and progression, its role and underlying mechanisms in ccRCC remain poorly understood.

Methods

The Cancer Genome Atlas (TCGA) database was utilized to examine the expression of EGR1 in ccRCC. The expression of EGR1 in 55 ccRCC tissues was evaluated using immunohistochemistry. The link between EGR1 expression and clinicopathological variables was examined through an analysis. Gain-of-function assays were employed to investigate EGR1's biological functions in ccRCC cells, involving proliferation, colony formation, invasion assays, and tumorigenesis in nude mice. In order to assess the protein expression of mitogen-activated protein kinase 15 (MAPK15), E-cadherin, matrix metalloproteinase-9/-2 (MMP-9 and MMP-2), Western blot technique was applied.

Results

The results revealed a decrease in EGR1 expression in ccRCC tissues. This decrease was strongly linked to TNM stage, lymphatic metastasis, tumor size, histological grade, and unfavorable prognosis in ccRCC patients. It has been demonstrated that overexpressing EGR1 inhibits the growth of xenograft tumors in vivo and inhibits cell colony formation, motility, and invasion in vitro. Furthermore, EGR1 can prevent the development and movement of ccRCC cells by controlling the expression of MMP-2, MMP-9, E-cadherin, and MAPK15.

Conclusions

The EGR1/MAPK15 axis may represent a promising target for drug development, with EGR1 serving as a possible target for ccRCC therapy.

Sex differences in immunotherapy outcomes and tumor-infiltrating immune cell profiles in patients with advanced renal cell carcinoma

Sex differences in the outcomes of advanced renal cell carcinoma (RCC) treated with immune checkpoint inhibitors (ICIs) and the profiles of tumor-infiltrating immune cells (TIICs) remain unclear. We retrospectively evaluated data from 563 patients with RCC receiving systemic therapy, including first-line dual ICI combinations (i.e., immunotherapy [IO]-IO), combinations of ICIs with tyrosine kinase inhibitors (TKIs) (i.e., IO-TKI), TKI monotherapy, and subsequent nivolumab monotherapy. Survival and tumor response were compared between the sexes in each treatment group, and TIIC profiles were compared using 116 RCC tumor samples analyzed by flow cytometry. Progression-free survival (PFS) was shorter in female than in male patients in the IO-IO (p = 0.0227) and nivolumab monotherapy (p = 0.0478) groups. Furthermore, sex remained an independent factor for shorter PFS after adjusting for covariates in the IO-IO (p = 0.0340) and nivolumab monotherapy (p = 0.0322) groups. In contrast, PFS was not significantly different between sexes in the IO-TKI or TKI monotherapy groups (p > 0.05). Overall survival and objective response rates were not significantly different between the sexes in any of the treatment groups (p > 0.05). Some TIIC populations, including that of CD8 + T cells (p = 0.0096), decreased to a greater extent in female than in male patients in the advanced-stage population. In conclusion, the effectiveness of ICIs on PFS was lower in female patients than in male patients, potentially because of the different profiles of the immune microenvironment, particularly the decreased number of CD8 + T cells in females.

Targeting HIF-2α: the role of belzutifan in clear cell renal carcinoma management

INTRODUCTION

Belzutifan is a first-in-class hypoxia-inducible factor-2 alpha (HIF-2α) inhibitor. It targets the von Hippel-Lindau protein (pVHL)-HIF-vascular endothelial growth factor (VEGF) pathway, which is crucial in cellular responses to hypoxia. By inhibiting HIF-2α, belzutifan disrupts the transcription of genes involved in tumor growth and angiogenesis.

AREAS COVERED

In this review, we describe the pVHL-HIF-VEGF pathway and how it led to the development of HIF inhibitors, including belzutifan. A search was conducted for trials involving Belzutifan, including phase I-III trials. We describe the relevant toxicity, with emphasis on hypoxia and anemia.

EXPERT OPINION

Belzutifan is a relatively safe drug, with manageable adverse events, including anemia and hypoxia as on-target toxicity. Ongoing trials are studying its benefit in overall survival for RCC in first-line treatment and its potential in other malignancies. The LITESPARK-005 trial reported the benefit of belzutifan in progression-free survival (PFS) compared to everolimus in later lines of treatment, with improvement in quality-of-life outcomes. Given its different mechanism of action to currently available treatments, belzutifan is expected to play a prominent role in the treatment of clear cell renal carcinoma and other cancers.

Radiogenomics Pilot Study: Association Between Radiomics and Single Nucleotide Polymorphism-Based Microarray Copy Number Variation in Diagnosing Renal Oncocytoma and Chromophobe Renal Cell Carcinoma

RO and ChRCC are kidney tumours with overlapping characteristics, making differentiation between them challenging. The objective of this research is to create a radiogenomics map by correlating radiomic features to molecular phenotypes in ChRCC and RO, using resection as the gold standard. Fourteen patients (6 RO and 8 ChRCC) were included in the prospective study. A total of 1,875 radiomic features were extracted from CT scans, alongside 632 cytobands containing 16,303 genes from the genomic data. Feature selection algorithms applied to the radiomic features resulted in 13 key features. From the genomic data, 24 cytobands highly correlated with histology were selected and cross-correlated with the radiomic features. The analysis identified four radiomic features that were strongly associated with seven genomic features. These findings demonstrate the potential of integrating radiomic and genomic data to enhance the differential diagnosis of RO and ChRCC, paving the way for more precise and non-invasive diagnostic tools in clinical practice.

Long-read RNA sequencing of archival tissues reveals novel genes and transcripts associated with clear cell renal cell carcinoma recurrence and immune evasion

The use of long-read direct RNA sequencing (DRS) and PCR cDNA sequencing (PCS) in clinical oncology remains limited, with no direct comparison between the two methods. We used DRS and PCS to study clear cell renal cell carcinoma (ccRCC), focusing on new transcript and gene discovery. Twelve primary ccRCC archival tumors, six from patients who went on to relapse, were analyzed. Results were validated in an independent cohort of 20 patients by qRT-PCR and compared to DRS analysis of RCC4 cells. In archival clinical samples and due to the long-term storage, the average read length was lower (400-500 nt) than that achieved through DRS of RCC4 cells (>1100 nt). Still, deconvolution analysis showed a loss of immune infiltrate in primary tumors of patients who relapse as reported by others. Differentially expressed genes in patients who went on to relapse were determined with good overlap between DRS and PCS, identifying LINC04216 and the T-cell exhaustion marker TOX as novel candidate recurrence-associated genes. Novel transcript analysis revealed over 10,000 candidate novel transcripts detected by both methods and in ccRCC cells in vitro, including a novel CD274 (PD-L1) transcript encoding for the soluble version of the protein with a longer 3' UTR and lower stability than the annotated transcript. Both methods identified 414 novel genes, also detected in RCC4 cells, including a novel noncoding gene overexpressed in patients who relapse. Overall, we showcase the use of PCS and DRS in archival tumor samples to uncover unmapped features of cancer transcriptomes, linked to disease progression and immune evasion.

Incidence and Pattern of Recurrence after Surgical Resection in Organ-Confined Renal Cell Carcinoma

PURPOSE

To evaluate the incidence and pattern of recurrence after surgery in patients with organ-confined renal cell carcinoma (RCC) to establish an appropriate follow-up plan.

MATERIALS AND METHODS

In this retrospective study, we evaluated data from 2960 patients who underwent radical or partial nephrectomy for stage 1 or 2 RCC. We investigated the location of first recurrence and recurrence-free survival (RFS) by plotting Kaplan-Meier curves and analyzed the associated variables using Cox regression analysis.

RESULTS

During a median follow-up of 59 months, the 10-year RFS rates were 94.5%, 75.0%, and 57.9%, for T1a, T1b, and T2 RCC, respectively. A total of 211 patients experienced recurrence: 67 after 5 years, and 14 after 10 years. The most common sites of the first recurrence were the lungs, bones, and contralateral kidneys. Male sex, older age, higher pathologic T stage, higher nuclear grade, clear-cell RCC, and presence of differentiation were associated with recurrence. Among patients followed up for more than 60 months, higher pathologic T stage and grade, as well as clear cell RCC were predictors of RFS.

CONCLUSION

Late recurrence after surgery is common in patients with organ-confined RCC, with recurrence occurring even after 10 years. Consequently, long-term follow-up, of perhaps 10 years or more, including imaging studies of the abdomen, lungs, and bone, should be considered for the early detection of recurrence.

ZBP1 as a prognostic biomarker correlated with cell proliferation in clear cell renal cell carcinoma

Background

Z-DNA-binding protein 1 (ZBP1) is a critical Z-DNA- and Z-RNA-binding protein. However, its diagnostic and prognostic significance, as well as its functions in clear cell renal cell carcinoma (ccRCC), are not well understood.

Materials and methods

Paired and unpaired differential expression analyses of ZBP1 were performed in pan-cancer cells. Receiver operating characteristic (ROC) curves and survival analyses were used to evaluate the clinical significance of ZBP1. Functional enrichment and immune infiltration analyses were used to explore the mechanisms underlying ZBP1 expression. Western blotting, qRT-PCR, CCK-8, and colony formation assays were used to investigate the potential function of ZBP1 in ccRCC cells. Molecular docking was utilized to identify drugs targeting ZBP1.

Results

ZBP1 was highly expressed in ccRCC, demonstrating significant diagnostic and prognostic value. ZBP1 mRNA expression correlated with TNM stage, pathologic stage, and histologic grade. Functional enrichment analyses indicated that ZBP1 is involved in multiple immune processes. Moreover, ZBP1 mRNA expression was positively correlated with the infiltrating levels of T cells and cytotoxic cells, and negatively correlated with the infiltrating levels of mast cells and Th17 cells in ccRCC. Biological experiments confirmed that ZBP1 promotes ccRCC cell proliferation. Molecular docking studies identified rucaparib as a potential drug targeting ZBP1.

Conclusion

Our research findings suggest that targeting ZBP1 could represent a novel therapeutic approach to inhibit the progression of ccRCC.

Ferroptosis-associated genes and compounds in renal cell carcinoma

As the main type of renal cell carcinoma (RCC), clear cell RCC (ccRCC) is often associated with the deletion or mutation of the von Hippel Lindau (VHL) gene, enhancement of glucose and lipid metabolism, and heterogeneity of the tumor microenvironment. VHL alterations in RCC cells lead to the activation of hypoxia-inducible factors and their downstream target vascular endothelial growth factor, and to the reprogramming of multiple cell death pathways and metabolic weakness, including ferroptosis, which are associated with targeted therapy or immunotherapy. The changes in biological metabolites (e.g., iron and lipids) support ferroptosis as a potential therapeutic strategy for RCC, while iron metabolism and ferroptosis regulation have been examined as anti-RCC agents in numerous studies, and various ferroptosis-related molecules have been shown to be related to the metastasis and prognosis of ccRCC. For example, glutathione peroxidase 4 and glutaminase inhibitors can inhibit pyrimidine synthesis and increase reactive oxygen species levels in VHL-deficient RCC cells. In addition, the release of damage-associated molecular patterns by tumor cells undergoing ferroptosis also mediates antitumor immunity, and immune therapy can synergize with targeted therapy or radiotherapy through ferroptosis. However, Inducing ferroptosis not only suppresses cancer, but also promotes cancer development due to its potential negative effects on anti-cancer immunity. Therefore, ferroptosis and various tumor microenviroment-related molecules may co-occur during the development and treatment of RCC, and further understanding of the interactions, core targets, and related drugs of ferroptosis may provide new combination drug strategies for RCC treatment. Here we summarize the key genes and compounds on ferroptosis and RCC in order to envision future treatment strategies and to provide sufficient information for overcoming RCC resistance through ferroptosis.

CircSP3 encodes SP3-461aa to promote ccRCC progression via stabilizing MYH9 and activating the PI3K-Akt signaling pathway

Clear cell renal cell carcinoma (ccRCC) is a primary kidney cancer with high aggressive phenotype and extremely poor prognosis. Accumulating evidence suggests that circular RNAs (circRNAs) play pivotal roles in the occurrence and development of various human cancers. However, the expression, clinical significance and regulatory role of circRNAs in ccRCC remain largely unclear. Here we report that circSP3 to be increased in tissues from ccRCC patients and ccRCC cells, and to positively correlate with ccRCC malignant features. Knockdown of circSP3 inhibits proliferation, triggers apoptosis, and reduces migration and invasion in different ccRCC cells in vitro. Correspondingly, circSP3 overexpression Promote ccRCC tumorigenicity in a mouse xenograft model. Mechanistically, circSP3 could bind with the ribosome to initiate the translation process to encodes a novel 461-amino acid peptide referred to as SP3-461aa, which protects the MYH9 protein from proteasomal degradation. SP3-461aa played a pivotal role in mediating the oncogenic effects of circSP3 by interacting with the MYH9 protein and activating the PI3K-Akt signaling pathway. These findings suggested that circSP3 plays an important role in ccRCC development and could be a potential biomarker for the treatment and prognosis of ccRCC.

A Scoping Review of Population Diversity in the Common Genomic Aberrations of Clear Cell Renal Cell Carcinoma

INTRODUCTION

Previous literature has shown that clear cell renal cell carcinoma (ccRCC) is becoming a more prevalent diagnosis and that the incidence and mortality differ both regionally and racially. While the molecular profiles for ccRCC are studied regionally through biopsy and sequencing techniques, the genomic landscape and ccRCC diversity data are not well studied. We conducted a review of the known genomic data on 6 of the most clinically relevant DNA biomarkers in ccRCC: von Hippel-Lindau (vHL), Polybromo-1 (PBRM1), Breast Cancer Gene 1-Associated Protein 1 (BAP1), Histone-Lysine N-Methyltransferase Domain-Containing 2 (SETD2), Mammalian Target of Rapamycin (mTOR), and Lysine-Specific Demethylase 5C (KDM5C). The review compiled genomic diversity data, incidence, and risk factor differences by geographical and racial cohorts.

METHODS

The review methodology was created using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) principles from articles on PubMed and Embase through July 31, 2023, written and published in English, with diagnoses of primary or metastatic ccRCC via cytology or pathology, recorded the incidence of one or more of the 6 biomarkers, explored gene aberration via sequencing, were epidemiological in nature, and/or discussed basic science research, cohort studies, or retrospective studies.

RESULTS

Aberrations in vHL, PBRM1, and SETD2 driving ccRCC are studied frequently, but the data are heterogeneous, whereas there is a paucity in the data regarding KDM5C, PBRM1, and mTOR mutations.

CONCLUSION

Studying the genetic aberrations that frequently occur in different regions gives insight into what current research lacks. When more genomic landscape research arises, precision therapy, risk calculators, and artificial intelligence may help better prognosticate and individualize treatment for those at risk for ccRCC. Provided the scarcity of existing data, and the rising prevalence of ccRCC, more studies must be conducted at the clinical level.

INTRODUCTION

Previous literature has shown that clear cell renal cell carcinoma (ccRCC) is becoming a more prevalent diagnosis and that the incidence and mortality differ both regionally and racially. While the molecular profiles for ccRCC are studied regionally through biopsy and sequencing techniques, the genomic landscape and ccRCC diversity data are not well studied. We conducted a review of the known genomic data on 6 of the most clinically relevant DNA biomarkers in ccRCC: von Hippel-Lindau (vHL), Polybromo-1 (PBRM1), Breast Cancer Gene 1-Associated Protein 1 (BAP1), Histone-Lysine N-Methyltransferase Domain-Containing 2 (SETD2), Mammalian Target of Rapamycin (mTOR), and Lysine-Specific Demethylase 5C (KDM5C). The review compiled genomic diversity data, incidence, and risk factor differences by geographical and racial cohorts.

METHODS

The review methodology was created using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) principles from articles on PubMed and Embase through July 31, 2023, written and published in English, with diagnoses of primary or metastatic ccRCC via cytology or pathology, recorded the incidence of one or more of the 6 biomarkers, explored gene aberration via sequencing, were epidemiological in nature, and/or discussed basic science research, cohort studies, or retrospective studies.

RESULTS

Aberrations in vHL, PBRM1, and SETD2 driving ccRCC are studied frequently, but the data are heterogeneous, whereas there is a paucity in the data regarding KDM5C, PBRM1, and mTOR mutations.

CONCLUSION

Studying the genetic aberrations that frequently occur in different regions gives insight into what current research lacks. When more genomic landscape research arises, precision therapy, risk calculators, and artificial intelligence may help better prognosticate and individualize treatment for those at risk for ccRCC. Provided the scarcity of existing data, and the rising prevalence of ccRCC, more studies must be conducted at the clinical level.

Programmed death receptor (PD-)1/PD-ligand (L)1 in urological cancers : the "all-around warrior" in immunotherapy

Programmed death receptor-1 (PD-1) and its ligand, programmed death ligand-1 (PD-L1) are essential molecules that are key in modulating immune responses. PD-L1 is constitutively expressed on various immune cells, epithelial cells, and cancer cells, where it functions as a co-stimulatory molecule capable of impairing T-cell mediated immune responses. Upon binding to PD-1 on activated T-cells, the PD-1/PD-L1 interaction triggers signaling pathways that can induce T-cell apoptosis or anergy, thereby facilitating the immune escape of tumors. In urological cancers, including bladder cancer (BCa), renal cell carcinoma (RCC), and prostate cancer (PCa), the upregulation of PD-L1 has been demonstrated. It is linked to poor prognosis and enhanced tumor immune evasion. Recent studies have highlighted the significant role of the PD-1/PD-L1 axis in the immune escape mechanisms of urological cancers. The interaction between PD-L1 and PD-1 on T-cells further contributes to immunosuppression by inhibiting T-cell activation and proliferation. Clinical applications of PD-1/PD-L1 checkpoint inhibitors have shown promising efficacy in treating advanced urological cancers, significantly improving patient outcomes. However, resistance to these therapies, either intrinsic or acquired, remains a significant challenge. This review aims to provide a comprehensive overview of the role of the PD-1/PD-L1 signaling pathway in urological cancers. We summarize the regulatory mechanism underlying PD-1 and PD-L1 expression and activity, including genetic, epigenetic, post-transcriptional, and post-translational modifications. Additionally, we discuss current clinical research on PD-1/PD-L1 inhibitors, their therapeutic potential, and the challenges associated with resistance. Understanding these mechanisms is crucial for developing new strategies to overcome therapeutic limitations and enhance the efficacy of cancer immunotherapy.

HDAC8 Enhances the Function of HIF-2α by Deacetylating ETS1 to Decrease the Sensitivity of TKIs in ccRCC

Drug resistance after long-term use of Tyrosine kinase inhibitors (TKIs) has become an obstacle for prolonging the survival time of patients with clear cell renal cell carcinoma (ccRCC). Here, genome-wide CRISPR-based screening to reveal that HDAC8 is involved in decreasing the sensitivity of ccRCC cells to sunitinib is applied. Mechanically, HDAC8 deacetylated ETS1 at the K245 site to promote the interaction between ETS1 and HIF-2α and enhance the transcriptional activity of the ETS1/HIF-2α complex. However, the antitumor effect of inhibiting HDAC8 on sensitized TKI is not very satisfactory. Subsequently, inhibition of HDAC8 increased the expression of NEK1, and up-regulated NEK1 phosphorylated ETS1 at the T241 site to promote the interaction between ETS1 and HIF-2α by impeded acetylation at ETS1-K245 site is showed. Moreover, TKI treatment increased the expression of HDAC8 by inhibiting STAT3 phosphorylation in ccRCC cells is also found. These 2 findings highlight a potential mechanism of acquired resistance to TKIs and HDAC8 inhibitors in ccRCC. Finally, HDAC8-in-PROTACs to optimize the effects of HDAC8 inhibitors through degrading HDAC8 and overcoming the resistance of ccRCC to TKIs are synthesized. Collectively, the results revealed HDAC8 as a potential therapeutic candidate for resistance to ccRCC-targeted therapies.

Identification of PI3K-AKT Pathway-Related Genes and Construction of Prognostic Prediction Model for ccRCC

BACKGROUND

Clear cell renal cell carcinoma (ccRCC), the predominate histological type of renal cell carcinoma (RCC), has been extensively studied, with poor prognosis as the stage increases. Research findings consistently indicated that the PI3K-Akt pathway is commonly dysregulated across various cancer types, including ccRCC. Targeting the PI3K-Akt pathway held promise as a potential therapeutic approach for treating ccRCC. Development and validation of PI3K-Akt pathway-related genes related biomarkers can enhance healthcare management of patients with ccRCC.

PURPOSE

This study aimed to identify the key genes in the PI3K-Akt pathway associated with the diagnosis and prognosis of CCRCC using data mining from the Cancer Genome Atlas (TCGA) and Gene Expression Synthesis (GEO) datasets.

METHODS

The purpose of this study is to use bioinformatics methods to screen data sets and clinicopathological characteristics associated with ccRCC patients. The exhibited significantly differential expressed genes (DEGs) associated with the PI3K-Akt pathway were examined by KEGG. In addition, Kaplan-Meier (KM) analysis used to estimate the survival function of the differential genes by using the UALCAN database and graphPad Prism 9.0. And exploring the association between the expression levels of the selected genes and the survival status and time of patients with ccRCC based on SPSS22.0. Finally, a multigene prognostic model was constructed to assess the prognostic risk of ccRCC patients.

RESULTS

A total of 911 genes with common highly expressed were selected based on the GEO and TCGA databases. According to the KEGG pathway analysis, there were 42 genes enriched in PI3K-Akt signalling pathway. And seven of highly expressed genes were linked to a poor prognosis in ccRCC. And a multigene prognostic model was established based on IL2RG, EFNA3, and MTCP1 synergistic expression might be utilized to predict the survival of ccRCC patients.

CONCLUSIONS

Three PI3K-Akt pathway-related genes may be helpful to identify the prognosis and molecular characteristics of ccRCC patients and to improve therapeutic regimens, and these risk characteristics might be further applied in the clinic.

Predicting CTLA4 expression and prognosis in clear cell renal cell carcinoma using a pathomics signature of histopathological images and machine learning

Background

CTLA4, an immune checkpoint, plays an important role in tumor immunotherapy. The purpose of this study was to develop a pathomics signature to evaluate CTLA4 expression and predict clinical outcomes in clear cell renal cell carcinoma (ccRCC) patients.

Methods

A total of 354 patients from the TCGA-KIRC dataset were enrolled in this study. The patients were stratified into two groups based on the level of CTLA4 expression, and overall survival rates were analyzed between groups. Pathological features were identified using machine learning algorithms, and a gradient boosting machine (GBM) was employed to construct the pathomics signatures for predicting prognosis and CTLA4 expression. The predictive performance of the model was subsequently assessed. Enrichment analysis was performed on diferentially expressed genes related to the pathomics score (PS). Additionally, correlations between PS and TMB, as well as immune infiltration profiles associated with different PS values, were explored. In vitro experiments, CTLA4 knockdown was performed to investigate its impact on cell proliferation, migration, invasion, TGF-β signaling pathway, and macrophage polarization.

Results

High expression of CTLA4 was associated with an unfavorable prognosis in ccRCC patients. The pathomics signature displayed good performance in the validation set (AUC = 0.737; P < 0.001 in the log-rank test). The PS was positively correlated with CTLA4 expression. We next explored the underlying mechanism and found the associations between the pathomics signature and TGF-β signaling pathways, TMB, and Tregs. Further in vitro experiments demonstrated that CTLA4 knockdown inhibited cell proliferation, migration, invasion, TGF-β expression, and macrophage M2 polarization.

Conclusion

High expression of CTLA4 was found to correlate with poor prognosis in ccRCC patients. The pathomics signature established by our group using machine learning effectively predicted both patient prognosis and CTLA4 expression levels in ccRCC cases.

Revealing the characteristics of SETD2-mutated clear cell renal cell carcinoma through tumor heterogeneity analysis

Background

Renal cell carcinoma (RCC) is the most prevalent type of malignant kidney tumor in adults, with clear cell renal cell carcinoma (ccRCC) comprising about 75% of all cases. The SETD2 gene, which is involved in the modification of histone proteins, is often found to have alterations in ccRCC. Yet, our understanding of how these SETD2 mutations affect ccRCC characteristics and behavior within the tumor microenvironment is still not fully understood.

Methods

We conducted a detailed analysis of single-cell RNA sequencing (scRNA-seq) data from ccRCC. First, the data was preprocessed using the Python package, "scanpy." High variability genes were pinpointed through Pearson's correlation coefficient. Dimensionality reduction and clustering identification were performed using Principal Component Analysis (PCA) and the Leiden algorithm. Malignant cell identification was conducted with the "InferCNV" R package, while cell trajectories and intercellular communication were depicted using the Python packages "VIA" and "cellphoneDB." We then employed the R package "Deseq2" to determine differentially expressed genes (DEGs) between groups. Using high-dimensional weighted gene correlation network analysis (hdWGCNA), co-expression modules were identified. We intersected these modules with DEGs to establish prognostic models through univariate Cox and the least absolute shrinkage and selection operator (LASSO) method.

Results

We identified 69 and 53 distinctive cell clusters, respectively. These were classified further into 12 unique cell types. This analysis highlighted the presence of an abnormal tumor sub-cluster (MT + group), identified by high mitochondrial-encoded protein gene expression and an indication of unfavorable prognosis. Investigation of cellular interactions spotlighted significant interactions between the MT + group and endothelial cells, macrophaes. In addition, we developed a prognostic model based on six characteristic genes. Notably, risk scores derived from these genes correlated significantly with various clinical features. Finally, a nomogram model was established to facilitate more accurate outcome prediction, incorporating four independent risk factors.

Conclusion

Our findings provide insight into the crucial transcriptomic characteristics of ccRCC associated with SETD2 mutation. We discovered that this mutation-induced subcluster could stimulate M2 polarization in macrophages, suggesting a heightened propensity for metastasis. Moreover, our prognostic model demonstrated effectiveness in forecasting overall survival for ccRCC patients, thus presenting a valuable clinical tool.

DNA alterations in ovarian adult granulosa cell tumours: A scoping review protocol

BACKGROUND

Identifying and describing molecular alterations in tumors has become common with the development of high-throughput sequencing. However, DNA sequencing in rare tumors, such as ovarian adult granulosa cell tumor (aGCT), often lacks statistical power due to the limited number of cases in each study. Questions regarding personalized treatment or prognostic biomarkers for recurrence or other malignancies therefore still need to be elucidated. This scoping review protocol aims to systematically map the current evidence and identify knowledge gaps regarding DNA alterations, actionable variations and prognostic biomarkers in aGCT.

METHODS

This scoping review will be conducted based on Arksey and O'Malley's methodological framework and later modifications by JBI Evidence Synthesis. The protocol complies with Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews. All original publications describing molecular alterations of aGCT will be included. The search will be performed in May 2024 in the following databases: MEDLINE (Ovid), Embase (Ovid), Web of Science Core Collection and Google Scholar (100-top ranked).

DISCUSSION

This scoping review will identify knowledge and gaps in the current understanding of the molecular landscape of aGCT, clinical trials on actionable variations and priorities for future research. As aGCT are rare, a possible limitation will be the small sample sizes and heterogenic study settings.

SCOPING REVIEW REGISTRATION

The review protocol is registered at Open Science Framework under https://doi.org/10.17605/OSF.IO/PX4MF.

Downregulation of UBB potentiates SP1/VEGFA-dependent angiogenesis in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) presents a unique profile characterized by high levels of angiogenesis and robust vascularization. Understanding the underlying mechanisms driving this heterogeneity is essential for developing effective therapeutic strategies. This study revealed that ubiquitin B (UBB) is downregulated in ccRCC, which adversely affects the survival of ccRCC patients. UBB exerts regulatory control over vascular endothelial growth factor A (VEGFA) by directly interacting with specificity protein 1 (SP1), consequently exerting significant influence on angiogenic processes. Subsequently, we validated that DNA methyltransferase 3 alpha (DNMT3A) is located in the promoter of UBB to epigenetically inhibit UBB transcription. Additionally, we found that an unharmonious UBB/VEGFA ratio mediates pazopanib resistance in ccRCC. These findings underscore the critical involvement of UBB in antiangiogenic therapy and unveil a novel therapeutic strategy for ccRCC.

Machine Learning-Based Pathomics Model to Predict the Prognosis in Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is a highly lethal urinary malignancy with poor overall survival (OS) rates. Integrating computer vision and machine learning in pathomics analysis offers potential for enhancing classification, prognosis, and treatment strategies for ccRCC. This study aims to create a pathomics model to predict OS in ccRCC patients. In this study, data from ccRCC patients in the TCGA database were used as a training set, with clinical data serving as a validation set. Pathological features were extracted from H&E-stained slides using PyRadiomics, and a pathomics model was constructed using the non-negative matrix factorization (NMF) algorithm. The model's predictive performance was assessed through Kaplan-Meier (KM) survival curves and Cox regression analysis. Additionally, differential gene expression, gene ontology (GO) enrichment analysis, immune infiltration, and mutational analysis were conducted to investigate the underlying biological mechanisms. A total of 368 pathomics features were extracted from H&E-stained slides of ccRCC patients, and a pathomics model comprising two subtypes (Cluster 1 and Cluster 2) was successfully constructed using the NMF algorithm. KM survival curves and Cox regression analysis revealed that Cluster 2 was associated with worse OS. A total of 76 differential genes were identified between the two subtypes, primarily involving extracellular matrix organization and structure. Immune-related genes, including CTLA4, CD80, and TIGIT, were highly expressed in Cluster 2, while the VHL and PBRM1 genes, along with mutations in the PI3K-Akt, HIF-1, and MAPK signaling pathways, exhibited mutation rates exceeding 40% in both subtypes. The machine learning-based pathomics model effectively predicts the OS of ccRCC patients and differentiates between subtypes. The critical roles of the immune-related gene CTLA4 and the PI3K-Akt, HIF-1, and MAPK signaling pathways offer new insights for further research on the molecular mechanisms, diagnosis, and treatment strategies for ccRCC.

The categorizations of vasculogenic mimicry in clear cell renal cell carcinoma unveil inherent connections with clinical and immune features

Background: Clear cell renal cell carcinoma (ccRCC) stands as the prevailing variant kidney cancer in humans. Unfortunately, patients with disseminated RCC at diagnosis often have a diminished prognosis. Rapid tumor growth necessitates efficient blood supply for oxygen and nutrients, involving the circulation of blood from vessels to tumor tissues, facilitating tumor cell entry into the extracellular matrix. Vasculogenic mimicry (VM) significantly contributes to tumor growth and metastasis. Within this investigation, we identified vasculogenic mimicry-related genes (VMRGs) by analyzing data from 607 cases of kidney renal clear cell carcinoma (KIRC) in The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo/). These findings offer insights into ccRCC progression and metastasis. Method: We identified VMRGs-related subtypes using consistent clustering methods. The signature of the VMRGs was created using univariate Cox regression and LASSO Cox regression analyses. To evaluate differences in immune cell infiltration, we employed ssGSEA. Afterwards, we created an innovative risk assessment model, known as the VM index, along with a nomogram to forecast the prognosis of ccRCC. Additionally, we verified the expression of an important gene related to VM, peroxiredoxin 2 (PRDX2), in tissue samples. Furthermore, we assessed the sensitivity to drugs in various groups by utilizing the pRRophetic R package. Results: Significant predictors of survival rates in both high- and low-risk groups of KIRC patients were identified as VMRGs. The independent prognostic factors for RCC were confirmed by both univariate and multivariate Cox regression analyses, validating VMRG risk signatures. Differences were observed in drug sensitivity, immune checkpoint expression, and responses to immune therapy between patients classified into high- and low-VMRG-risk groups. Our nomograms consistently demonstrated precise predictive capabilities. Finally, we experimentally verified PRDX2 expression levels and their impact on prognosis. Conclusion: The signature predicts patient prognosis and therapy response, laying the groundwork for future clinical strategies in treating ccRCC patients.

Unveiling the hidden AP-1: revealing the crucial role of AP-1 in ccRCC at single-cell resolution

Clear cell renal cell carcinoma (ccRCC), as the most common histological subtype of kidney cancer, has been reported to originate primarily from proximal tubule (PT) cells in the kidney. However, the current research on its associated molecular mechanisms remains relatively limited. In our study, we analyzed multiple single-cell multi-omics datasets obtained from various research teams, revealing the significant role of the activator protein 1 (AP-1) in ccRCC tumorigenesis. The motif activity analysis of transcription factors (TFs) showed a predominant activation of AP-1 in ccRCC cancer cells compared to PT cells. Furthermore, our findings at single-cell resolution revealed a notable absence of AP-1 expression in PT cells when compared to ccRCC cancer cells. In bulk-RNA of discovery cohort, no differential expression of AP-1 was detected in normal kidney and ccRCC samples, which may be attributed to confounding effects in bulk-RNA sequencing. Meanwhile, spatial transcriptomics analysis demonstrated a broader expression range of the AP-1 compared to the ccRCC marker CA9. Moreover, we observed chromatin accessibility of the AP-1 in various cell-types, including PT cells, suggesting that the transcriptional expression of AP-1 in PT cells may be influenced by subsequent transcriptional modifications, reflecting the complex regulatory mechanism of AP-1 transcription. These findings provide important insights for a deeper understanding of the function and regulatory mechanisms of AP-1 in ccRCC, thereby establishing a theoretical foundation for future clinical research and the development of treatment strategies.

P2RY13 is a prognostic biomarker and associated with immune infiltrates in renal clear cell carcinoma: A comprehensive bioinformatic study

Background and Aims

Clear cell renal cell carcinoma (ccRCC) is a common and aggressive form of cancer with a high incidence globally. This study aimed to investigate the role of P2RY13 in the progression of ccRCC and elucidate its mechanism of action.

Methods

Gene Expression Omnibus and The Cancer Genome Atlas databases were used to extract gene expression profiles of ccRCC. These profiles were annotated and visualized by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses, as well as Gene Set Enrichment Analysis (GSEA). The STRING database was used to establish a protein-protein interaction network and to analyze the functional similarity. The GEPIA2 database was used to predict survival associated with hub genes. Meanwhile, the TIMER2.0 database was used to assess immune cell infiltration and its link with the hub genes. Immunohistochemistry (IHC) was used to determine the difference between ccRCC and adjacent normal tissue.

Results

We identified 272 differentially expressed genes (DEGs). GO and KEGG analyses suggested that DEGs were primarily involved in lymphocyte activation, inflammatory response, immunological effector mechanism pathways. By cytohubba, the 20 highest-scoring hub genes were screened to identify critical genes in the protein-protein interaction network linked with ccRCC. Resting dendritic cells, CD8 T cells, and activated mast cells all showed a significant positive correlation with these hub genes. Moreover, a higher immune score was associated with increased prognostic risk scores, which in turn correlated with a poorer prognosis. IHC revealed that P2RY13 was expressed at higher levels in ccRCC compared to para-cancer tissues.

Conclusion

Identifying the DEGs will aid in the understanding of the causes and molecular mechanisms involved in ccRCC. P2RY13 may play a pivotal role in the progression and prognosis of ccRCC, potentially driving carcinogenesis though immune system mechanisms.

Theranostic Lipid Nanoparticles for Renal Cell Carcinoma

Renal cell carcinoma (RCC) is a common urological malignancy and represents a leading threat to healthcare. Recent years have seen a series of progresses in the early diagnosis and management of RCC. Theranostic lipid nanoparticles (LNPs) are increasingly becoming one of the focuses in this field, because of their suitability for tumor targeting and multimodal therapy. LNPs can be precisely fabricated with desirable chemical compositions and biomedical properties, which closely match the physiological characteristics and clinical needs of RCC. Herein, a comprehensive review of theranostic LNPs is presented, emphasizing the generic tool nature of LNPs in developing advanced micro-nano biomaterials. It begins with a brief overview of the compositions and formation mechanism of LNPs, followed with an introduction to kidney-targeting approaches, such as passive, active, and stimulus responsive targeting. With examples provided, a series of modification strategies for enhancing the tumor targeting and functionality of LNPs are discussed. Thereafter, research advances on applications of these LNPs for RCC including bioimaging, liquid biopsy, drug delivery, physical therapy, and gene therapy are summarized and discussed from an interdisciplinary perspective. The final part highlights the milestone achievements of translation medicine, current challenges as well as future development directions of LNPs for the diagnosis and treatment of RCC.