Integration of proteomics and transcriptomics to construct a prognostic signature of renal clear cell carcinoma.

Background: Protein information is often replaced by RNA data in studies to understand cancer-related biological processes or molecular functions, and proteins of prognostic significance in Kidney clear cell carcinoma (KIRC) remain to be mined. Methods: The cancer genome atlas program (TCGA) data was utilized to screen for proteins that are prognostically significant in KIRC. Machine learning algorithms were employed to develop protein prognostic models. Additionally, immune infiltration abundance, somatic mutation differences, and immunotherapeutic responses were analyzed in various protein risk subgroups. Ultimately, the validation of protein-coding genes was confirmed by utilizing an online database and implementing quantitative real-time PCR (qRT-PCR). Results: The patients were divided into two risk categories based on prognostic proteins, and notable disparities in both overall survival (OS) and progression free interval (PFI) were observed between the two groups. The OS was more unfavorable in the high-risk group, and there was a noteworthy disparity in the level of immune infiltration observed between the two groups. In addition, the nomogram showed high accuracy in predicting survival in KIRC patients. Conclusion: In this research, we elucidated the core proteins associated with prognosis in terms of survival prediction, immunotherapeutic response, somatic mutation, and immune microenvironment. Additionally, we have developed a reliable prognostic model with excellent predictive capabilities.

Prediction of clear cell renal cell carcinoma prognosis based on an immunogenomic landscape analysis.

Immune cell infiltration and tumor-related immune molecules play key roles in tumorigenesis and tumor progression. The influence of immune interactions on the molecular characteristics and prognosis of clear cell renal cell carcinoma (ccRCC) remains unclear. A machine learning algorithm was applied to the transcriptome data from The Cancer Genome Atlas database to determine the immunophenotypic and immunological characteristics of ccRCC patients. These algorithms included single-sample gene set enrichment analyses and cell type identification. Using bioinformatics techniques, we examined the prognostic potential and regulatory networks of immune-related genes (IRGs) involved in ccRCC immune interactions. Fifteen IRGs (CCL7, CHGA, CMA1, CRABP2, IFNE, ISG15, NPR3, PDIA2, PGLYRP2, PLA2G2A, SAA1, TEK, TGFA, TNFSF14, and UCN2) were identified as prognostic IRGs associated with overall survival and were used to construct a prognostic model. The area under the receiver operating characteristic curve at 1 year was 0.927; 3 years, 0.822; and 5 years, 0.717, indicating good predictive accuracy. Molecular regulatory networks were found to govern immune interactions in ccRCC. Additionally, we developed a nomogram containing the model and clinical characteristics with high prognostic potential. By systematically examining the sophisticated regulatory mechanisms, molecular characteristics, and prognostic potential of ccRCC immune interactions, we provided an important framework for understanding the molecular mechanisms of ccRCC and identifying new prognostic markers and therapeutic targets for future research.

Vasculogenic mimicry-related gene prognostic index for predicting prognosis, immune microenvironment in clear cell renal cell carcinoma.

Background: Clear cell renal cell carcinoma (ccRCC) is a highly aggressive cancer associated with higher death rates. However, traditional anti-angiogenic therapies have limited effectiveness due to drug resistance. Vascular mimicry (VM) provides a different way for tumors to develop blood vessels without relying on endothelial cells or angiogenesis. However, the intricate mechanisms and interplay between it and the immune microenvironment in ccRCC remain unclear. Methods: A PubMed and GeneCards literature review was conducted to identify VM-related genes (VMRGs). VMRGs expression profiles were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), developing a novel VM risk score model and nomogram for ccRCC. The EBI ArrayExpress database (the validation set) was obtained to validate the prognostic model. The relationship between VMRGs risk score clinical characteristics and immune infiltration was investigated. Finally, the expression of six model VMRGs was validated using single-cell analysis, GEPIA, Human Protein Atlas (HPA), and quantitative Real-time PCR (qRT-PCR). Results: Cox regression analysis and nomogram identified L1CAM, TEK, CLDN4, EFNA1, SERPINF1, and MALAT1 as independent prognostic risk factors, which could be used to stratify the ccRCC population into two risk groups with distinct immune profiles and responsiveness to immunotherapy. The results of single-cell analysis, GEPIA, HPA, and qRT-PCR validated the model genes' expression. Conclusions: Our novel findings constructed a convenient and reliable 6 gene signatures as potential immunologic and prognostic biomarkers of VM in ccRCC.

Shedding light on pancreatic metastasis of clear cell sarcoma: An exceptional journey.

This editorial comments on the study by Liu et al investigating pancreatic metastasis of clear cell sarcoma (CCS) published in the World Journal of Clinical Cases. CCS is a rare and aggressive melanocytic tumor, that typically arises from tendons and aponeuroses of the limbs, and metastasizes to the lungs, bones, and brain. However, pancreatic metastasis has rarely been reported, presenting unique diagnostic and therapeutic challenges. Elucidating the clinical characteristics, imaging features, prognostic factors, and treatment outcomes of patients with pancreatic CCS metastasis is crucial. Surgery remains an effective management strategy for CCS. However, the high recurrence rate and low effectiveness of traditional adjuvant treatments necessitate a shift towards more personalized and targeted treatment plans. Research is needed to investigate and validate novel therapeutic approaches specifically tailored to the distinct genetic and molecular characteristics of rare malignancies like CCS. Additionally, the development of late metastases after a long disease-free interval is common in CCS patients. Therefore, routine postoperative surveillance for metastasis using computed tomography, magnetic resonance imaging, bone scans, and positron emission tomography scans is crucial. Moving forward, enhanced collaboration, investigation, and creative thinking among scientists, medical professionals, and legislators are essential to gain a deeper understanding of these rare presentations.

Clear cell sarcoma of the pancreas, an unusual cancer with unusual metastatic site or unusual primary site?

Clear cell sarcoma (CCS) is a type of malignant tumor that can arise from tendons and aponeuroses. This malignant proliferation of cells with melanocytic lineage normally occurs in young patients, and it is normally identified in extremities. However, different sites including gastrointestinal organs are also described. Due difficulties in the molecular and histopathology evaluation, the diagnosis is often confused with malignant melanoma. Most cases are treated with surgical resection, but overall, the prognosis is poor. In this editorial, we will discuss a very interesting case of CCS identified in the pancreas. We will discuss the literature and controversies in the management of this type of cancer. Furthermore, we will address molecular strategies to be incorporated in those cases to better understand the primary location of the tumor. Finally, future perspectives of the field and new strategies of treatment will be described.

Integrative analysis of bulk and single-cell RNA sequencing reveals sphingolipid metabolism and immune landscape in clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is characterized by its aggressive behavior and complex molecular heterogeneity, posing significant challenges for treatment and prognostication. This study offers a comprehensive analysis of ccRCC by leveraging both bulk and single-cell RNA sequencing data, with a specific aim to unravel the complexities of sphingolipid metabolism and the intricate dynamics within the tumor microenvironment (TME). By examining ccRCC samples sourced from public databases, our investigation delves deep into the genetic and transcriptomic landscape of this cancer type. Employing advanced analytical techniques, we have identified pivotal patterns in gene expression and cellular heterogeneity, with a special focus on the roles and interactions of various immune cells within the TME. Significantly, our research has unearthed insights into the dynamics of sphingolipid metabolism in ccRCC, shedding light on its potential implications for tumor progression and strategies for immune evasion. A novel aspect of this study is the development of a risk score model designed to enhance prognostic predictions for ccRCC patients, which is currently pending external validation to ascertain its clinical utility. Despite its contributions, the study is mindful of its limitations, including a reliance on observational data from public sources and a primary focus on RNA sequencing data, which may constrain the depth and generalizability of the findings. The study does not encompass critical aspects, such as protein expression, posttranslational modifications, and comprehensive metabolic profiles. Moreover, its retrospective design underscores the necessity for future prospective studies to solidify these preliminary conclusions. Our findings illuminate the intricate interplay between genetic alterations, sphingolipid metabolism, and immune responses in ccRCC. This research not only enhances our understanding of the molecular foundations of ccRCC but also paves the way for the development of targeted therapies and personalized treatment modalities. The study underlines the importance of cautious interpretation of results and champions ongoing research using diverse methodologies to thoroughly comprehend and effectively combat this formidable cancer type.

VSIG4 induces the immunosuppressive microenvironment by promoting the infiltration of M2 macrophage and Tregs in clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcinoma and has a poor prognosis. Despite the impressive advancements in treating ccRCC using immune checkpoint (IC) blockade, such as PD-1/PD-L1 inhibitors, a considerable number of ccRCC patients experience adaptive resistance. Therefore, exploring new targetable ICs will provide additional treatment options for ccRCC patients. We comprehensively analyzed multi-omics data and performed functional experiments, such as pathologic review, bulk transcriptome data, single-cell sequencing data, Western blotting, immunohistochemistry and in vitro/in vivo experiments, to explore novel immunotherapeutic targets in ccRCC. It was found that immune-related genes VSIG4, SAA1, CD7, FOXP3, IL21, TNFSF13B, BATF, CD72, MZB1, LTB, CCL25 and KLRK1 were significantly upregulated in ccRCC (Student's t test and p-value < 0.05; 36 normal and 267 ccRCC tissues in raining cohort; 36 normal and 266 ccRCC tissues in validation cohort) and correlated with the poor prognosis of ccRCC patients (Wald test and p-value < 0.05 in univariate cox analysis; log-rank test and p-value < 0.05 in Kaplan-Meier method; 267 patients in training cohort and 266 in validation cohort). In particular, we found the novel IC target VSIG4 was specifically expressed in inhibitory immune cells M2-biased tumor-associated macrophages (TAMs), conventional dendritic cell 2 (cDC2) cells, and cycling myeloid cells in ccRCC microenvironment. Moreover, VSIG4 showed a closely relation with resistance of Ipilimumab/Nivolumab immunotherapy in ccRCC. Furthermore, VSIG4 promoted the infiltration of M2 macrophages, Tregs, and cDC2 in ccRCC tissues. VSIG4+ TAMs and VSIG4+ cDC2s may be a kind of immune cell subtypes related to immunosuppression. VSIG4 may play similar roles with other IC ligands, as it is highly expressed on the surface of antigen-presenting cells and ccRCC cells to inhibit T cells activity and facilitate immune escape. Targeting IC gene VSIG4 may provide a novel immunotherapeutic strategy to ccRCC patients with resistance to existing targeted therapy options.

Reflectance Confocal Microscopy and Dermoscopy for the Diagnosis of Solitary Hypopigmented Pink Lesions: A Narrative Review.

Diagnosing solitary pink skin lesions poses a significant challenge due to the scarcity of specific clinical and dermoscopic criteria. Several benign lesions, such as cherry angioma, clear cell acanthoma, dermal nevus, keloid, hypertrophic scar, and Spitz nevus, often exhibit similar clinical and dermoscopic features. This similarity extends to some malignant lesions, including basal cell carcinoma, actinic keratosis, and amelanotic melanoma, making differentiation difficult. Recent studies highlight the enhanced diagnostic accuracy of reflectance confocal microscopy (RCM), which offers increased sensitivity and specificity compared to dermoscopy alone for diagnosing skin cancer. This study aims to summarize the application of dermoscopy and RCM in distinguishing between benign and malignant pinkish-reddish skin lesions. The integration of RCM with traditional dermoscopic techniques improves the ability to accurately identify and differentiate these lesions. However, it is crucial to note that for any suspicious lesions, a final diagnosis must be confirmed through surgical excision and histopathological evaluation. This comprehensive approach ensures accurate diagnosis and appropriate treatment, highlighting the importance of combining advanced imaging techniques in clinical practice.

Aberrant SWI/SNF Complex Members Are Predominant in Rare Ovarian Malignancies-Therapeutic Vulnerabilities in Treatment-Resistant Subtypes.

SWI/SNF (SWItch/Sucrose Non-Fermentable) is the most frequently mutated chromatin-remodelling complex in human malignancy, with over 20% of tumours having a mutation in a SWI/SNF complex member. Mutations in specific SWI/SNF complex members are characteristic of rare chemoresistant ovarian cancer histopathological subtypes. Somatic mutations in ARID1A, encoding one of the mutually exclusive DNA-binding subunits of SWI/SNF, occur in 42-67% of ovarian clear cell carcinomas (OCCC). The concomitant somatic or germline mutation and epigenetic silencing of the mutually exclusive ATPase subunits SMARCA4 and SMARCA2, respectively, occurs in Small cell carcinoma of the ovary, hypercalcaemic type (SCCOHT), with SMARCA4 mutation reported in 69-100% of SCCOHT cases and SMARCA2 silencing seen 86-100% of the time. Somatic ARID1A mutations also occur in endometrioid ovarian cancer (EnOC), as well as in the chronic benign condition endometriosis, possibly as precursors to the development of the endometriosis-associated cancers OCCC and EnOC. Mutation of the ARID1A paralogue ARID1B can also occur in both OCCC and SCCOHT. Mutations in other SWI/SNF complex members, including SMARCA2, SMARCB1 and SMARCC1, occur rarely in either OCCC or SCCOHT. Abrogated SWI/SNF raises opportunities for pharmacological inhibition, including the use of DNA damage repair inhibitors, kinase and epigenetic inhibitors, as well as immune checkpoint blockade.

Identification of HDAC10 as a candidate oncogene in clear cell renal carcinoma that facilitates tumor proliferation and metastasis.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) remains one of the most lethal urological malignancies even though a great number of improvements in diagnosis and management have achieved over the past few decades. Accumulated evidence revealed that histone deacetylases (HDACs) play vital role in cell proliferation, differentiation and apoptosis. Nevertheless, the biological functions of histone deacetylation modification related genes in ccRCC remains poorly understood. METHOD: Bulk transcriptomic data and clinical information of ccRCC patients were obtained from the TCGA database and collected from the Chinese PLA General Hospital. A total of 36 histone deacetylation genes were selected and studied in our research. Univariate cox regression analysis, least absolute shrinkage and selection operator (LASSO) regression, random forest (RF) analysis, and protein-protein interaction (PPI) network analysis were applied to identify key genes affecting the prognosis of ccRCC. The 'oncoPredict' algorithm was utilized for drug-sensitive analysis. Gene Set Enrichment Analysis (GSEA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was used to explore the potential biological function. The ssGSEA algorithm was used for tumor immune microenvironment analysis. The expression levels of HDAC10 were validated by RT-PCR and immunohistochemistry (IHC). 5-ethynyl-2'-deoxyuridine (EdU assay), CCK-8 assay, cell transwell migration and invasion assay and colony formation assay were performed to detect the proliferation and invasion ability of ccRCC cells. A nomogram incorporating HDAC10 and clinicopathological characteristics was established to predict the prognosis of ccRCC patients. RESULT: Two machine learning algorithms and PPI analysis identified four histone deacetylation genes that have a significant association with the prognosis of ccRCC, with HDAC10 being the key gene among them. HDAC10 is highly expressed in ccRCC and its high expression is associated with poor prognosis for ccRCC patients. Pathway enrichment and the experiments of EdU staining, CCK-8 assay, cell transwell migration and invasion assay and colony formation assay demonstrated that HDAC10 mediated the proliferation and metastasis of ccRCC cells and involved in reshaping the tumor microenvironment (TME) of ccRCC. A clinically reliable prognostic predictive model was established by incorporating HDAC10 and other clinicopathological characteristics ( https://nomogramhdac10.shinyapps.io/HDAC10_Nomogram/ ). CONCLUSION: Our study found the increased expression of HDAC10 was closely associated with poor prognosis of ccRCC patients. HDAC10 showed a pro-tumorigenic effect on ccRCC and promote the proliferation and metastasis of ccRCC, which may provide new light on targeted therapy for ccRCC.

Comprehensive analysis of LD-related genes signature for predicting prognosis and immunotherapy response in clear cell renal cell carcinoma.

BACKGROUND: Lipid droplets (LD) in renal clear cell carcinoma (ccRCC)play a crucial role in lipid metabolism and immune response modulation. The purpose of this study was to create a LD-related signature to predict prognosis and guide the immunotherapy and targeted therapy in ccRCC patients. METHODS: We conducted a comprehensive analysis using transcriptional profiles and clinical data obtained from The Cancer Genome Atlas (TCGA). LD-related genes were identified from existing literature and the GeneCards database, and differentially expressed genes were determined. Sequentially, we conducted Cox regression analysis and Lasso regression analysis, to establish a prognostic risk model. The performance of the risk model was evaluated using Kaplan-Meier (KM) analysis and time-dependent receiver operating characteristic (ROC) analysis. Additionally, gene set enrichment analysis (GSEA), ESTIMATE, CIBERSORT, and immunophenoscore (IPS) algorithm were used to assess the tumor microenvironment (TME) and treatment response. RESULTS: We constructed a risk signature with four LD-related genes in the TCGA dataset, which could be an independent prognostic factor in ccRCC patients. Then, patients were classified into two risk groups and exhibited notable differences in overall survival (OS), progression-free survival (PFS), and TME characteristics. Furthermore, we developed a comprehensive nomogram based on clinical features, which demonstrated good prognostic predictive value. According to the results of GSEA analysis, immune-related pathways were found to be significantly enriched in the high-risk group. Additionally, the high-risk group displayed high levels of immune cell infiltration, TMB and IPS scores, indicating better efficacy of immune checkpoint inhibitors (ICIs). Finally, high-risk demonstrated reduced IC50 values compared to the low-risk counterpart for specific targeted and chemotherapeutic drugs, suggesting that the patients receiving these targeted drugs in high-risk group had better treatment outcomes. CONCLUSIONS: Our findings suggested that the LD-related gene signature could potentially predict the prognosis of ccRCC patients. Additionally, it showed promise for predicting responses to immunotherapy and targeted therapy in ccRCC patients. These insights might potentially have guided the clinical management of these patients, but further validation and broader data analysis are needed to confirm these preliminary observations.

Common progenitor origin for Rosai-Dorfman disease and clear cell sarcoma.

Histiocytic neoplasms (HNs) in adults have been reported to be associated with a high prevalence of coexisting haematological and solid malignancies. While a proportion of coexisting HNs and haematological malignancies share identical genetic alterations, the genetic association between HNs and solid malignancies has scarcely been reported. We report a case of Rosai-Dorfman disease (RDD) complicated by coexisting clear cell sarcoma (CCS). RDD is a rare HN. CCS is an ultrarare soft tissue sarcoma with a poor prognosis. Mutation analysis with whole-exome sequencing revealed six shared somatic alterations including NRAS p.G12S and TP53 c.559+1G>A in both the RDD and CCS tissue. This is the first evidence of a clonal relationship between RDD and solid malignancies using mutational analysis. We hypothesise that neural crest cells, which originate in CCS, are likely the common cells of origin for RDD and CCS. This case helps to unravel the underlying clinicopathological mechanisms of increased association of solid malignancies in HNs. © 2024 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Diagnostic and prognostic potential of the intra-tumoral microbiota profile in HPV-independent endocervical adenocarcinoma.

Background: Microbial community dynamics have been involved in numerous diseases, including cancer. The diversity of intertumoral microbiota in human papillomavirus independent endocervical adenocarcinoma (HPVI ECA) is not well-characterized. Objective: Our objective is to delineate the intratumoral microbiota profile in HPVI ECA and investigate its potential influence on oncogenesis. Methods: We analyzed 45 HPVI ECA cases, comprising 36 gastric-type ECA (GEA) and 9 clear cell carcinomas (CCC). We compared the microbial composition within cancerous and adjacent noncancerous tissue samples using 5R-16S ribosomal DNA sequencing. Further, we investigated the correlation between specific microbes and clinical-pathological metrics as well as patient outcomes. Results: Our findings demonstrate notable differences in the microbial spectra between cancerous and adjacent noncancerous tissues. Amongst HPVI ECA subtypes, GEAs exhibit more microbial variations compared to CCCs. Using the Random Forest algorithm, we identified two distinct microbial signatures that could act as predictive biomarkers for HPVI ECA and differentiate between GEA and CCC. Varied microbial abundances was related to clinical characteristics of HPVI ECA patients. In addition, high levels of Micrococcus and low levels of unknown genus75 from the Comamonadaceae family were associated with poorer outcomes in HPVI ECA patients. Similarly, an abundance of Microbacterium correlated with reduced overall survival (OS), and a high presence of Streptococcaceae family microbes was linked to reduced recurrence-free survival (RFS) in GEA patients. Intriguingly, a high abundance of Micrococcus was also associated with a worse OS in GEA patients. Conclusion: The study reveals distinct microbial signatures in HPVI ECA, which have potential as biomarkers for disease prognosis. The correlation between these tumor-associated microbiota features and clinicopathological characteristics underscores the possibility of microbiome-based interventions. Our research provides a foundation for more in-depth studies into the cervical microbiome's role in HPVI ECA.

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.

Diagnostic value of contrast-enhanced CT in clear cell renal cell carcinoma: a systematic review and meta-analysis.

OBJECTIVE: Contrast-enhanced computed tomography (CECT) improves lesion contrast with surrounding tissues through the injection of contrast agents. This enhancement allows for more precise lesion characterization, aiding in the early diagnosis of clear cell renal cell carcinoma (ccRCC). This meta-analysis aims to assess the diagnostic efficacy of CECT in ccRCC and to provide an ideal imaging examination method for the preoperative diagnosis of ccRCC. METHODS: We conducted a comprehensive search across six major online databases: PubMed, Web of Science, Cochrane Library, WANFANG DATA, China National Knowledge Infrastructure, and Chinese BioMedical Literature Database (CBM). The objective was to collate and analyze studies that evaluate the diagnostic utility of CECT in the identification of ccRCC. Meta-disc 1.4 and Stata 16.0 were used to conduct a meta-analysis and evaluate the diagnostic accuracy of CECT for ccRCC. RESULTS: The meta-analysis included 17 relevant studies investigating the diagnostic value of CECT for ccRCC. The combined sensitivity and specificity of CECT were 0.88 (95% confidence interval: 0.83-0.91) and 0.82 (95%CI: 0.75-0.87), respectively. Positive diagnostic likelihood ratio = 4.87 (95%CI: 3.47-6.84), negative diagnostic likelihood ratio = 0.15 (95%CI: 0.11-0.21), and diagnostic odds ratio = 32.67 (95%CI: 18.21-58.61). In addition, the area under the ROC curve was 0.92 (95%CI: 0.89-0.94), indicating that CECT has a decent discriminative ability in diagnosing ccRCC. CONCLUSIONS: CECT is recognized as a highly effective imaging tool for diagnosing ccRCC. It provides valuable guidance in the preoperative assessment and planning of surgical strategies for patients with ccRCC.

APOBEC family reshapes the immune microenvironment and therapy sensitivity in clear cell renal cell carcinoma.

Emerging evidence suggests that the APOBEC family is implicated in multiple cancers and might be utilized as a new target for cancer detection and treatment. However, the dysregulation and clinical implication of the APOBEC family in clear cell renal cell cancer (ccRCC) remain elusive. TCGA multiomics data facilitated a comprehensive exploration of the APOBEC family across cancers, including ccRCC. Remodeling analysis classified ccRCC patients into two distinct subgroups: APOBEC family pattern cancer subtype 1 (APCS1) and subtype 2 (APCS2). The study investigated differences in clinical parameters, tumor immune microenvironment, therapeutic responsiveness, and genomic mutation landscapes between these subtypes. An APOBEC family-related risk model was developed and validated for predicting ccRCC patient prognosis, demonstrating good sensitivity and specificity. Finally, the overview of APOBEC3B function was investigated in multiple cancers and verified in clinical samples. APCS1 and APCS2 demonstrated considerably distinct clinical features and biological processes in ccRCC. APCS1, an aggressive subtype, has advanced clinical stage and a poor prognosis. APCS1 exhibited an oncogenic and metabolically active phenotype. APCS1 also exhibited a greater tumor mutation load and immunocompromised condition, resulting in immunological dysfunction and immune checkpoint treatment resistance. The genomic copy number variation of APCS1, including arm gain and loss, was much more than that of APCS2, which may help explain the tired immune system. Furthermore, the two subtypes have distinct drug sensitivity patterns in clinical specimens and matching cell lines. Finally, we developed a predictive risk model based on subtype biomarkers that performed well for ccRCC patients and validated the clinical impact of APOBEC3B. Aberrant APOBEC family expression patterns might modify the tumor immune microenvironment by increasing the genome mutation frequency, thus inducing an immune-exhausted phenotype. APOBEC family-based molecular subtypes could strengthen the understanding of ccRCC characterization and guide clinical treatment. Targeting APOBEC3B may be regarded as a new therapeutic target for ccRCC.

HADH suppresses clear cell renal cell carcinoma progression through reduced NRF2-dependent glutathione synthesis.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is a serious threat to human life. It is very important to clarify the pathogenesis of ccRCC. In this study we evaluated the clinical value of HADH and explored its role and mechanism in the malignant progression of ccRCC. METHODS: HADH expression and its relationship with prognosis were analyzed using bioinformatics database. RT-PCR, Western blot and immunohistochemistry were used to examine the expression of HADH in ccRCC tissues and tissue microarrays. To examine the cell proliferation, apoptosis, migration and invasion ability, ccRCC cells with HADH overexpressed were constructed. Xenograft experiments were performed to determine the role of HADH. Non-target metabolomics was applied to explore the potential metabolic pathway by which HADH inhibited ccRCC progression. Plasmid pcDNA3.1-NRF2 was used to confirm whether HADH inhibited the process of ccRCC cells through NRF2-related glutathione (GSH) synthesis. RESULTS: Bioinformatics database analysis showed that HADH expression was significantly decreased in ccRCC tissues, and its low expression predicted a poor prognosis. Both ccRCC tissues and tissue microarrays exhibited a significantly decreased HADH level compared with adjacent normal renal tissues. HADH overexpression inhibited the malignant behaviors of ccRCC cells. Furthermore, HADH overexpression attenuated GSH synthesis and induced oxidative stress damage. Exogenously increased NRF2 effectively attenuated the inhibitive effect of HADH overexpression on ccRCC cells. CONCLUSION: Our data revealed that HADH suppressed the malignant behaviors of ccRCC cells by attenuating GSH synthesis through inhibition of NRF2 nuclear translocation, and HADH might be a novel therapeutic target for ccRCC treatment.

Machine Learning-Enabled Fuhrman Grade in Clear-cell Renal Carcinoma Prediction Using Two-dimensional Ultrasound Images.

OBJECTIVE: Accurate assessment of Fuhrman grade is crucial for optimal clinical management and personalized treatment strategies in patients with clear cell renal cell carcinoma (CCRCC). In this study, we developed a predictive model using ultrasound (US) images to accurately predict the Fuhrman grade. METHODS: Between March 2013 and July 2023, a retrospective analysis was conducted on the US imaging and clinical data of 235 patients with pathologically confirmed CCRCC, including 67 with Fuhrman grades Ⅲ and Ⅳ. This study included 201 patients from Hospital A who were divided into training set (n = 161) and an internal validation set (n = 40) in an 8:2 ratio. Additionally, 34 patients from Hospital B were included for external validation. US images were delineated using ITK software, and radiomics features were extracted using PyRadiomics software. Subsequently, separate models for clinical factors, radiomics features, and their combinations were constructed. The model's performance was assessed by calculating the area under the receiver operating characteristic curve (AUC), calibration curve and decision curve analysis (DCA). RESULTS: In total, 235 patients diagnosed with CCRCC, comprising 168 low-grade and 67 high-grade tumors, were included in this study. A comparison of the predictive performances of different models revealed that the logistic regression model exhibited relatively good stability and robustness. The AUC of the combined model for the training, internal validation and external validation sets were 0.871, 0.785 and 0.826, respectively, which were higher than those of the clinical and imaging histology models. Furthermore, the calibration curve demonstrated excellent concordance between the predicted Fuhrman grade probability of CCRCC using the combined model and the observed values in both the training and validation sets. Additionally, within the threshold range of 0-0.93, the combined model demonstrated substantial clinical utility, as evidenced by DCA. CONCLUSION: The application of US radiomics techniques enabled objective prediction of Fuhrman grading in patients with CCRCC. Nevertheless, certain clinical indicators remain indispensable, underscoring the pressing need for their integrated use in clinical practice. ADVANCES IN KNOWLEDGE: Previous studies have predominantly focused on using computed tomography or magnetic resonance imaging modalities to predict the Fuhrman grade of CCRCC. Our findings demonstrate that a prediction model based on US images is more cost-effective, easily accessible and exhibits commendable performance. Consequently, this study offers a promising approach to maximizing the use of US examinations in future research.

Identification of key ferroptosis genes and subtypes in kidney renal clear cell carcinoma.

Tumour immunity is highly important for the occurrence and development of tumours, and many cancers are resistant to ferroptosis. This study aims to explore the relationship between ferroptosis-related genes (FRGs) and the immunological characteristics of kidney renal clear cell carcinoma (KIRC). We obtained RNA-seq profiles and clinical data of KIRC patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and identified CD44 and GLRX5 as the key FRGs involved in KIRC immune infiltration through Spearman's correlation analysis. Based on the expression of CD44 and GLRX5, the consensus clustering algorithm was used to classify the TCGA-KIRC samples into two clusters. A nomogram was constructed to evaluate the prognosis of KIRC patients. ESTIMATE, CIBERSORT, and single-sample gene set enrichment analysis (ssGSEA) were performed to evaluate immune infiltration between the two clusters. A weighted gene co-expression network analysis (WGCNA) was used to identify the most relevant genes to the clusters and immunity. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed. The external dataset GSE53757 was used to validate the immunological features between the two clusters. Cluster 2 patients had more active immune infiltration and might be more sensitive to immunotherapy; Cluster 2 patients also had a worse prognosis and might be at a more advanced stage of KIRC. We identified key ferroptosis-related genes and subgroups involved in the immune infiltration of KIRC, which is highly important for exploring the molecular mechanisms and treatments of KIRC.

The efficacy of second-line tyrosine kinase inhibitor for patients with metastatic non-clear cell renal cell carcinoma following first-line immune-oncology combination therapy.

PURPOSE: Metastatic non-clear cell renal cell carcinoma (nccRCC) is a heterogeneous disease with a poor prognosis and is treated with immunotherapy (IO)-based combinations according to the clear cell renal cell carcinoma. Tyrosine-kinase inhibitors (TKIs), such as cabozantinib and axitinib, are commonly used as the 2nd line therapy after 1st line IO combination therapy, but their efficacy as 2nd line TKI therapy for nccRCC is unknown. In this study, we performed a retrospective multicenter analysis of nccRCC patients who were previously treated with IO combination therapy and received 2nd line TKIs. METHODS: Among 254 patients enrolled in the Japanese multicenter retrospective study, 52 patients with nccRCC histology who received second-line TKIs were included in this study. Progression-free survival and overall survival (OS) from 2nd line TKIs were analyzed by log-rank test and Cox-proportional hazard model. Objective response rate (ORR) of 2nd line TKIs were analyzed. RESULTS: The 1-year PFS and OS rates were 25.0% (95% CI = 13.1-36.8) and 63.8% (95% CI, 48.0-75.9), respectively. No patients had a complete response, 11 had a partial response, and 18 had stable disease. ORR was 21.1%. IMDC poor risk and sunitinib as the 2nd line therapy were significantly associated with poor PFS. CONCLUSION: The 2nd-line TKI was effective for a small group of nccRCC patients previously treated with IO combination therapy, although this study was retrospectively analyzed with a small number of cases.