Renal Cancer Tissues Research Articles

Prognostic value of miR-190a-5p in renal cell cancer and its regulatory effect on tumor progression.

As a usual malignant tumor in urinary system, renal cell cancer is regulated by microRNAs (miRNAs). This study revealed the prognostic value and regulatory effect of miR-190a-5p in renal cell cancer patients. A total of 253 renal cell cancer patients were included for prognostic value analysis. The target gene of miR-190a-5p was detected by luciferase reporter assay. Cell Counting Kit-8 analysis and Transwell analysis were performed to explore the proliferation, removal capability, and invasiveness of 786-0 and A498 cells. Prognostic value was calculated by Kaplan-Meier curve and Cox regression analysis. miR-190a-5p was more down-regulated in tumor tissues than in adjacent tissues. Renal cell cancer cases were differed as low and high groups ground on mean miR-190a-5p expression in tumor tissues. Overall survival probability was obviously high in patients with high miR-190a-5p level (log-rank test P = 0.011). Cox regression analysis revealed that miR-190a-5p expression (relative risk (RR) = 1.751, 95% confidence interval (CI) = 1.057-2.900, P = 0.030) and tumor node metastasis stage (RR = 1.719, 95% CI = 1.059-2.792, P = 0.028) were specialty indicators for poor renal cell cancer prognosis. GDF11 was directly targeting miR-190a-5p. Overexpressed miR-190a-5p could reduce the GDF11 expression, proliferation, removal capability, and invasiveness of renal cell cancer 786-0 and A498 cells. Elevated GDF11 could lead to a changeover of proliferation, removal capability, and invasiveness inhibition, which is induced by miR-190a-5p. miR-190a-5p was reduced in renal cell cancer tissues, and predicted worse outcomes of renal cell cancer cases. Overexpressed miR-190a-5p could restrain the proliferation, removal capability, and invasiveness of renal cell cancer cells via suppressing GDF11.

MDH2 regulates the sensitivity of clear cell renal cell carcinoma to ferroptosis through its interaction with FSP1

Malate dehydrogenase 2 is a pivotal enzyme in the tricarboxylic acid cycle. Recent studies have highlighted the significant involvement of MDH2 in the pathogenesis and progression of diverse types of tumors, yet its precise mechanistic underpinnings remain elusive. This study revealed a significant decrease in MDH2 expression in renal cancer tissues. And knocking out MDH2 was observed to hinder the proliferation of normal renal tubular epithelial cells but notably enhance the proliferation of ccRCC. Furthermore, mechanistically, we found that MDH2 inhibits the proliferation of ccRCC by promoting ferroptosis, while enhancing the sensitivity of ccRCC to ferroptosis inducers, promoting lipid peroxidation. We also demonstrated that MDH2 regulates the ubiquitination of FSP1 through protein-protein interactions, leading to a decrease in FSP1 protein levels and maintaining high sensitivity of ccRCC to ferroptosis. In conclusion, our study demonstrates that the reduced MDH2 expression in ccRCC results in increased expression of FSP1, thereby reducing its sensitivity to ferroptosis. It unveils a non-metabolic role for the downregulation of MDH2 in ccRCC progression.

Identification and expression of prognostic-related genes in kidney renal clear cell carcinoma and their possible regulatory mechanisms.

Many factors affect the prognosis of kidney renal clear cell carcinoma (KIRC). Early diagnosis can significantly improve the prognosis of KIRC patients. Therefore, a method needs to be developed to diagnose KIRC early, predict patient prognosis, and improve personalized treatments. The objective of this study is to utilize bioinformatics tools and public database resources to identify differentially expressed genes (DEGs) between renal cancer tissues and adjacent normal tissues, and to further screen for prognostic-related genes (PRGs) of KIRC. KIRC was studied using R language and FunRich software and several databases, including the Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), the University of Alabama at Birmingham cancer data analysis Portal (UALCAN), and Tumor Immune Estimation Resource (TIMER) databases. Moreover, quantitative real-time polymerase chain reaction (qRT-PCR) was used to validate the expression of multiple genes in KIRC and adjacent normal tissues. There were substantial differences in immune cell infiltration between the KIRC and adjacent normal tissues in the GSE40435 and GSE46699 datasets. In addition, we screened multiple PRGs of KIRC by combining the GEO and TCGA data. The UALCAN database verified that some representative PRGs were differently expressed depending on the lymph node metastasis status, grade, and stage of KIRC. The qRT-PCR results confirmed the expression of the PRGs in KIRC and adjacent normal tissues. Through the GO and KEGG analyses, interaction analysis, and TIMER database, we found that the prognosis of KIRC was closely related to immune microenvironment and vascular endothelial growth factor (VEGF)/VEGF receptor (VEGFR) signaling. Our findings could contribute to the prognosis prediction of KIRC, the selection of personalized treatments, and the early diagnosis of KIRC.

Prevalence and prognosis of malignancy in THSD7A-associated membranous nephropathy: a systematic literature review and clinical case study

Background This study aims to investigate the incidence and prognosis of malignancy in individuals with thrombospondin type-1 domain-containing 7A (THSD7A)-associated membranous nephropathy (MN). Methods First, we performed a systematic literature review of prevalence of malignancy in THSD7A-associated MN. Then, we conducted a retrospective analysis of 454 patients diagnosed with MN through renal biopsy at our hospital between January 2016 and December 2020. We assessed the presence of serum anti-THSD7A antibodies and performed immunohistochemical staining of renal tissue for THSD7A. Subsequently, we followed patients with THSD7A-associated MN for a minimum of 3–5 years, collecting their clinical, pathological characteristics, and prognosis. Additionally, we conducted a literature review on patients with THSD7A-associated MN in conjunction with malignancy. Results We identified a total of nine articles containing comprehensive data on THSD7A-associated MN and malignancy. Among 235 patients with THSD7A-positive MN, 36 individuals had concurrent malignancies, resulting in a malignancy prevalence of 13.3% (95% CI: 8.9–17.7%). In our center, we followed up with 15 patients diagnosed with THSD7A-associated MN and observed three cases of concomitant tumors: two cases of lung adenocarcinoma and one case of small cell lung cancer with multiple metastases. The prevalence of malignancy in our cohort was 20%. Notably, we detected positive THSD7A staining in both renal and lung cancer tissues in one patient with small cell lung cancer. Conclusions Patients with THSD7A-associated MN should undergo vigilant follow-up assessments, with a particular focus on actively seeking potential tumorigenic lesions to prevent misdiagnosis or oversight.

A novel risk signature based on liquid-liquid phase separation-related genes reveals prognostic and tumour microenvironmental features in clear cell renal cell carcinoma.

Clear cell renal cell carcinoma(ccRCC) is one of the most common malignancies. However, there are still many barriers to its underlying causes, early diagnostic techniques and therapeutic approaches. The Cancer Genome Atlas (TCGA)- Kidney renal clear cell (KIRC) cohort differentially analysed liquid-liquid phase separation (LLPS)-related genes from the DrLLPS website. Univariate and multivariate Cox regression analyses and LASSO regression analyses were used to construct prognostic models. The E-MTAB-1980 cohort was used for external validation. Then, potential functions, immune infiltration analysis, and mutational landscapes were analysed for the high-risk and low-risk groups. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) experiments as well as single-cell analyses validated the genes key to the model. We screened 174 LLPS-related genes in ccRCC and constructed a risk signature consisting of five genes (CLIC5, MXD3, NUF2, PABPC1L, PLK1). The high-risk group was found to be associated with worse prognosis in different subgroups. A nomogram constructed by combining age and tumour stage had a strong predictive power for the prognosis of ccRCC patients. In addition, there were differences in pathway enrichment, immune cell infiltration, and mutational landscapes between the two groups. The results of qRT-PCR in renal cancer cell lines and renal cancer tissues were consistent with the biosignature prediction. Three single-cell data of GSE159115, GSE139555, and GSE121636 were analysed for differences in the presence of these five genes in different cells. We developed a risk signature constructed based on the five LLPS-related genes and can have a high ability to predict the prognosis of ccRCC patients, further providing a strong support for clinical decision-making.

ARRDC3 regulates the targeted therapy sensitivity of clear cell renal cell carcinoma by promoting AXL degradation

ABSTRACT AXL plays crucial roles in the tumorigenesis, progression, and drug resistance of neoplasms; however, the mechanisms associated with AXL overexpression in tumors remain largely unknown. In this study, to investigate these molecular mechanisms, wildtype and mutant proteins of arrestin domain-containing protein 3 (ARRDC3) and AXL were expressed, and co-immunoprecipitation analyses were performed. ARRDC3-deficient cells generated using the CRISPR-Cas9 system were treated with different concentrations of the tyrosine kinase inhibitor sunitinib and subjected to cell biological, molecular, and pharmacological experiments. Furthermore, immunohistochemistry was used to analyze the correlation between ARRDC3 and AXL protein expressions in renal cancer tissue specimens. The experimental results demonstrated that ARRDC3 interacts with AXL to promote AXL ubiquitination and degradation, followed by the negative regulation of downstream signaling mechanisms, including the phosphorylation of protein kinase B and extracellular signal-regulated kinase. Notably, ARRDC3 deficiency decreased the sunitinib sensitivity of clear cell renal cell carcinoma (ccRCC) cells in a manner dependent on the regulation of AXL stability. Overall, our results suggest that ARRDC3 is a negative regulator of AXL and can serve as a novel predictor of sunitinib therapeutic response in patients with ccRCC.

ZNF471 Interacts with BANP to Reduce Tumour Malignancy by Inactivating PI3K/AKT/mTOR Signalling but is Frequently Silenced by Aberrant Promoter Methylation in Renal Cell Carcinoma.

Background: Renal cell carcinoma (RCC) is one of the most common malignant tumours of the urinary system. However, the aetiology and pathogenesis of RCC remain unclear. The C2H2 zinc finger protein (ZNF) family is the largest transcriptional regulatory factor family found in mammals, and Krüppel-associated box domain-containing zinc finger proteins (KRAB-ZFPs) constitute the largest subfamily of the C2H2 zinc finger protein family and play an important role in the occurrence and development of tumours. The aim of this study was to explore the role of abnormal methylation of ZNF471 in the development of renal carcinoma. Methods: In this study, we first used the TCGA and EWAS Data Hub databases to analyse the expression and methylation levels of ZNF471 in renal carcinoma tissues and adjacent normal tissues. Second, we collected samples of renal cancer and adjacent normal tissues at Peking University First Hospital to investigate the expression and methylation level of ZNF471 in renal cancer tissues and the relationships between these levels and the clinicopathological features and prognosis of patients with renal cancer. Next, we investigated the effects of ZNF471 on the proliferation, metastasis, cell cycle progression, and apoptosis of renal cell carcinoma cells by cell biology experiments. Finally, we elucidated the underlying molecular mechanisms of ZNF471 in renal cell carcinoma by transcriptome sequencing, bioinformatics analysis and molecular biology experiments. Results: The expression of ZNF471 in renal carcinoma tissues and cell lines was significantly lower than that in adjacent normal tissues and cell lines due to abnormal promoter CpG methylation. Furthermore, the expression of ZNF471 in renal carcinoma tissues was negatively correlated with tumour stage and grade in patients with renal carcinoma. The results of the cell biology experiments showed that ZNF471 could significantly inhibit the proliferation, migration and cell cycle progression of renal cell carcinoma cells and promote apoptosis in these cells. In addition, ZNF471 could interact with BANP and suppress the malignant phenotype of RCC by inactivating the PI3K/AKT/mTOR signalling pathway. Conclusions: As an important tumour suppressor, ZNF471 can interact with BANP in renal cancer cells and inhibit the activation of the PI3K/AKT/mTOR signalling pathway, thereby inhibiting the occurrence and development of renal cancer.

ΔNp63α promotes cigarette smoke-induced renal cancer stem cell activity via the Sonic Hedgehog pathway.

Cigarette smoke (CS) has been generally recognized as a chief carcinogenic factor in renal cell carcinoma (RCC). The stimulative effect of CS on renal cancer stem cells (RCSCs) has been described previously. The Sonic Hedgehog (SHH) pathway plays an essential role in self-renewal, cell growth, drug resistance, metastasis, and recurrence of cancer stem cells (CSCs). Renal cancer-related gene ΔNp63α is highly expressed in renal epithelial tissues and contributes to the RCSCs characteristics of tumors. The aim of this study was to elucidate the role of ΔNp63α and the SHH pathway on the activity of RCSCs induced by CS through a series of in vivo and in vitro studies. It was shown that in renal cancer tissues, ΔNp63α and RCSCs markers in smokers are expressed higher than that in non-smokers. RCSCs were effectively enriched by tumor sphere formation assay. Besides, CS increased the expression of RCSCs markers and the capability of sphere-forming in vitro and in vivo. Moreover, the SHH pathway was activated, and the specialized inhibitor alleviated the promotion of CS on RCSCs. ΔNp63α activated the SHH pathway and promoted CS-induced enhancement of RCSCs activity. These findings indicate that ΔNp63α positively regulates the activity of CS-induced RCSCs via the SHH pathway.

Altered NCR3 Splice Variants May Result in Deficient NK Cell Function in Renal Cell Carcinoma Patients.

The natural killer (NK) cell function of patients with malignant tumours may be suppressed by deficiency, and the poor prognosis of renal cell carcinoma (RCC) patients may be due to escape from NK cell cytotoxicity, especially with respect to natural cytotoxicity receptors (NCRs) on the NK cell surface. However, the specific mechanism remains unclear. Therefore, in this study, we sought to explore the role of NCR, especially NCR3 splice variants, in the process of NK cell deficiency in RCC patients. We used flow cytometry to analyse the phenotype of NK cells from the peripheral blood and kidney tumour tissue of RCC patients. The NKp30-mediated NK cell killing function was measured by antibody-dependent cell-mediated cytotoxicity (ADCC) in NK and RCC cell coincubation. We extracted RNA from the peripheral blood mononuclear cells (PBMCs) of RCC patients and renal carcinoma tissue and carried out real-time quantitative PCR to detect the mRNA levels of NKp30a, NKp30b and NKp30c. mRNA expression levels of cytokines (IL-6, IL-8, IL-10, IL-18 and TGF-β) based on RNA extracted from renal carcinoma tissue and adjacent normal kidney tissues were also measured by real-time quantitative PCR. Regarding the phenotype of NK cells in RCC patients, the proportion of NK cells in tumour tissue was significantly reduced, with changes in the NK cell proportion being most obvious in NKp30+ NK cells. Furthermore, the results of the ADCC function assay showed limited NKp30+ NK cell-mediated cytotoxicity in RCC patients. Through real-time quantitative PCR, we found lower expression of NKp30a and NKp30b, the immunostimulatory splice variants of NCR3 encoding NKp30, in RCC patients. Moreover, expression of activating cytokines (IL-6 and IL-8) in renal cancer tissue was decreased, though inhibitory cytokine (TGF-β) expression remained unchanged, which may result in an immunosuppressive cytokine microenvironment. Decreased expression of immunostimulatory NCR3 splice variants and the inhibitory cytokine microenvironment in RCC patients may contribute to deficient NK cell cytotoxicity and renal carcinoma cell immune escape from NK cell killing, which may provide a theoretical basis for finding new immunotherapeutic targets for RCC.

Natural small-molecules reverse Xeroderma Pigmentosum Complementation Group C (XPC) deficient-mediated drug-resistance in renal cell carcinoma

BackgroundRenal cancer is insensitive to radiotherapy or most chemotherapies. While the loss of the XPC gene was correlated with drug resistance in colon cancer, the expression of XPC and its role in the drug resistance of renal cancer have not yet been elucidated. With the fact that natural small-molecules have been adopted in combinational therapy with classical chemotherapeutic agents to increase the drug sensitivity and reduce adverse effects, the use of herbal compounds to tackle drug-resistance in renal cancer is advocated. PurposeTo correlate the role of XPC gene deficiency to drug-resistance in renal cancer, and to identify natural small-molecules that can reverse drug-resistance in renal cancer via up-regulation of XPC. MethodsIHC was adopted to analyze the XPC expression in human tumor and adjacent tissues. Clinical data extracted from The Cancer Genome Atlas (TCGA) database were further analysed to determine the relationship between XPC gene expression and tumor staging of renal cancer. Two types of XPC-KD renal cancer cell models were established to investigate the drug-resistant phenotype and screen XPC gene enhancers from 134 natural small-molecules derived from herbal plants. Furthermore, the identified XPC enhancers were verified in single or in combination with FDA-approved chemotherapy drugs for reversing drug-resistance in renal cancer using MTT cytotoxicity assay. Drug resistance gene profiling, ROS detection assay, immunocytochemistry and cell live-dead imaging assay were adopted to characterize the XPC-related drug resistant mechanism. ResultsXPC gene expression was significantly reduced in renal cancer tissue compared with its adjacent tissue. Clinical analysis of TCGA database also identified the downregulated level of XPC gene in renal tumor tissue of stage IV patients with cancer metastasis, which was also correlated with their lower survival rate. 6 natural small-molecules derived from herbal plants including tectorigenin, pinostilbene, d-pinitol, polygalasaponin F, atractylenolide III and astragaloside II significantly enhanced XPC expression in two renal cancer cell types. Combinational treatment of the identified natural compound with the treatment of FDA-approved drug, further confirmed the up-regulation of XPC gene expression can sensitize the two types of XPC-KD drug-resistant renal cancer cells towards the FDA-approved drugs. Mechanistic study confirmed that GSTP1/ROS axis was activated in drug resistant XPC-KD renal cancer cells. ConclusionXPC gene deficiency was identified in patient renal tumor samples, and knockdown of the XPC gene was correlated with a drug-resistant phenotype in renal cancer cells via activation of the GSTP1/ROS axis. The 6 identified natural small molecules were confirmed to have drug sensitizing effects via upregulation of the XPC gene. Therefore, the identified active natural small molecules may work as an adjuvant therapy for circumventing the drug-resistant phenotype in renal cancer via enhancement of XPC expression.

Real-world data on the management of pazopanib-induced liver toxicity in routine care of renal cell cancer and soft tissue sarcoma patients

PurposePazopanib is known to cause liver toxicity. A relationship between pazopanib exposure and alanine transaminase elevations has been described in clinical trials. This study investigated the relation between pazopanib exposure and liver toxicity in real-world patients and evaluated the management of pazopanib-induced liver toxicity in routine care.MethodsA retrospective observational cohort study was performed in patients treated with pazopanib in whom pazopanib exposure was measured. The percentage of patients with and without liver toxicity during treatment with pazopanib was calculated as well as the average pazopanib exposure in both groups. Furthermore, the management of patients with liver toxicity was evaluated.ResultsLiver toxicity was observed in 25 out of the 133 patients included (19%). Pazopanib exposure was comparable in patients with or without liver toxicity (27.7 mg/L versus 28.1 mg/L). Seven patients permanently discontinued pazopanib after the occurrence of liver toxicity. Of the remaining 18 patients, continuation or restart of pazopanib after liver toxicity was successful in 16 patients and half of these patients were able to safely continue pazopanib at the same dose as prior to liver toxicity for the remaining duration of treatment.ConclusionOur study did not demonstrate a clear relationship between pazopanib exposure and the occurrence of pazopanib-induced liver toxicity. Half of the patients were able to safely continue or restart pazopanib treatment after liver toxicity and received the same dose as prior to drug withdrawal. Successful interventions to address pazopanib-induced toxicity in the clinic led to an algorithm for the management of pazopanib-induced liver toxicity.

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

BackgroundAbnormal anillin (ANLN) expression has been observed in multiple tumours and is closely associated with patient prognosis and clinical features. In this study, we systematically elucidated the clinical significance and biological roles of ANLN in patients with clear cell renal cell carcinoma (ccRCC). MethodsWe obtained transcriptome and clinical data of patients with ccRCC from public databases. Multi-omics data and clinical samples were combined to analyse the correlation between ANLN expression and the clinical characteristics of patients with renal cancer. Additionally, the immune cell landscape of ANLN expression was evaluated using different immune algorithms in the tumour microenvironment. The tumour-promoting potential of ANLN was confirmed using in vitro assays, including CCK8 and Transwell assays. ResultsBioinformatics analysis showed that ANLN is over-expressed in patients with ccRCC, as validated by clinical samples. Publicly available clinical data suggest that high ANLN expression may indicate poor outcomes in patients with ccRCC. Moreover, biological function analysis revealed a marked enrichment of the cell cycle and PI3K-Akt pathways. The distribution of immune cells, particularly M2 macrophages, differed in patients with ccRCC. Furthermore, ANLN silencing inhibited the proliferation, migration, and invasion of renal cancer cells in vitro. After ANLN expression was knocked down in 786-O cells, the protein levels of important PI3K signalling pathway components, including PI3K, Akt, and mTOR, drastically decreased. ConclusionsThese findings suggest that ANLN is dysregulated in renal cancer tissues and promotes tumour progression by activating the PI3K/Akt/mTOR signalling pathway.

Basement Membrane-Associated lncRNA Risk Model Predicts Prognosis and Guides Clinical Treatment in Clear Cell Renal Cell Carcinoma.

The basement membrane (BM) affects the invasion and growth of malignant tumors. The role and mechanism of BM-associated lncRNAs in clear cell renal cell carcinoma (ccRCC) are unknown. In this study, we identified biomarkers of ccRCC and developed a risk model to assess patient prognosis. We downloaded transcripts and clinical data from the Cancer Genome Atlas (TCGA). Differential analysis, co-expression analysis, Cox regression analysis, and lasso regression were used to identify BM-associated prognostic lncRNAs and create a risk prediction model. We evaluated and validated the accuracy of the model using multiple methods and constructed a nomogram to predict the prognosis of ccRCC. GO, KEGG, and immunity analyses were used to explore differences in biological function. We constructed a risk model containing six BM-associated lncRNAs (LINC02154, IGFL2-AS1, NFE4, AC112715.1, AC092535.5, and AC105105.3). The risk model has higher diagnostic efficiency compared to clinical characteristics and can be used to forecast patient prognoses. We used renal cancer cells and tissue microarrays to verify the expression of lncRNAs in the risk model. We found that knocking down LINC02154 and AC112715.1 could inhibit the invasion ability of renal cancer cells. The risk model based on BM-associated lncRNAs can well predict ccRCC and guide clinical treatment.

MicroRNAs as Potential Regulators of GSK-3β in Renal Cell Carcinoma.

The prognosis of patients with advanced renal cell carcinoma (RCC) has improved with newer therapies, including molecular-targeted therapies and immuno-oncology agents. Despite these therapeutic advances, many patients with metastatic disease remain uncured. Inhibition of glycogen synthase kinase-3β (GSK-3β) is a promising new therapeutic strategy for RCC; however, the precise regulatory mechanism has not yet been fully elucidated. MicroRNAs (miRNAs) act as post-translational regulators of target genes, and we investigated the potential regulation of miRNAs on GSK-3β in RCC. We selected nine candidate miRNAs from three databases that could potentially regulate GSK-3β. Among these, hsa-miR-4465 (miR-4465) was downregulated in RCC cell lines and renal cancer tissues. Furthermore, luciferase assays revealed that miR-4465 directly interacted with the 3' untranslated region of GSK-3β, and Western blot analysis showed that overexpression of miR-4465 significantly decreased GSK-3β protein expression. Functional assays showed that miR-4465 overexpression significantly suppressed cell invasion of A498 and Caki-1 cells; however, cell proliferation and migration were suppressed only in Caki-1 and A498 cells, respectively, with no effect on cell cycle and apoptosis. In conclusion, miR-4465 regulates GSK-3β expression but does not consistently affect RCC cell function as a single molecule. Further comprehensive investigation of regulatory networks is required in this field.

Prognostic significance and mechanisms of CXCL genes in clear cell renal cell carcinoma.

This study aimed to investigate the clinical significance, biological functions, and underlying mechanisms of CXCL genes in clear cell renal cell carcinoma (ccRcc) based on patient datasets and pan-cancer analysis. The interaction between CXCL genes in ccRcc and immune components, particularly in relation to neutrophil recruitment and polarization mechanisms, was also evaluated. Furthermore, a risk score was developed using a signature for neutrophil polarization. The role of CXCL2 was assessed through in vitro experiments. Results showed that five CXCL genes (CXCL 2, 5, 9, 10, and 11) were upregulated in renal cancer tissue, while seven genes (CXCL 1, 2, 3, 5, 8, 13, and 14) significantly impacted patient survival. Moreover, CXCL 1, 5, and 13 affected progression-free survival. Besides, differences in mRNA expression and immune components affected renal cancer outcomes. Furthermore, three pairs of CXCL gene-immune cell interactions (CXCL13-CD8+ T cells, CXCL9/10-M1 cells, CXCL1/2/3/8-neutrophils) were identified through single-cell and pan-cancer analysis. A TAN risk score with prognostic value for KIRC patients was constructed using 11 genes and a TAN signature. Neutrophil polarization significantly impacted survival. Notably, CXCL2 was involved in neutrophil recruitment and polarization, thus promoting ccRcc progression. In conclusion, seven prognostic CXCL genes (CXCL 1/2/3/5/8/13/14) for ccRcc patients and three pairs of CXCL gene-immune cell interactions were identified. Furthermore, results showed that CXCL 2 promotes ccRcc progression through neutrophil recruitment and polarization.

An improved random forest algorithm for tracing the origin of metastatic renal cancer tissues

IntroductionTracing the histological origin of Metastatic renal cancer (MRC) and locating the pathological root cause, leading to precise treatment and improved prognosis options.Material and methodsThe 3336 patient cases with clear tissue origins from The Cancer Genome Atlas (TCGA) database were screened as experimental data material and feature selection was performed using the differential expression method; the random forest (RF) algorithm was improved to establish a medical retrospective heterogeneous filtered feature selection random forest weighted (ReliefFk_RFw) model to locate tissue origins.ResultsThe differential expression analysis method screened 60 signature genes with good differential expression for tracing tissue origins (kidney renal clear cell carcinoma, kidney renal papillary cell carcinoma, lung adenocarcinoma, lung squamous cell carcinoma, liver hepatocellular carcinoma, pancreatic adenocarcinoma). Compared with traditional machine learning (support vector machine, decision tree, RF) models, the ReliefFk_RFw algorithm increased the average accuracy from 98.65%, 98.79% and 98.57% to 99.53%, the average precision from 95.58%, 96.40% and 96.54% to 99.36%, and the average sensitivity from 97.03%, 96.61% and 96.76% to 98.89%, mean specificity from 99.50%, 99.39% and 99.35% to 99.90%, and mean F1 score from 96.30%, 96.50% and 96.64% to 99.11%. The highest accuracy in localizing the origin of primary pancreatic cancer was achieved with 100.00% for different models of retrospective metrics.ConclusionsThe improved ReliefFk_RFw model is best for comprehensive assessment and can be used to trace the origin of MRC tissue to assist physicians in diagnosis and treatment.

Distinguishing Renal Cell Carcinoma From Normal Kidney Tissue Using Mass Spectrometry Imaging Combined With Machine Learning.

Accurately distinguishing renal cell carcinoma (RCC) from normal kidney tissue is critical for identifying positive surgical margins (PSMs) during partial and radical nephrectomy, which remains the primary intervention for localized RCC. Techniques that detect PSM with higher accuracy and faster turnaround time than intraoperative frozen section (IFS) analysis can help decrease reoperation rates, relieve patient anxiety and costs, and potentially improve patient outcomes. Here, we extended our combined desorption electrospray ionization mass spectrometry imaging (DESI-MSI) and machine learning methodology to identify metabolite and lipid species from tissue surfaces that can distinguish normal tissues from clear cell RCC (ccRCC), papillary RCC (pRCC), and chromophobe RCC (chRCC) tissues. From 24 normal and 40 renal cancer (23 ccRCC, 13 pRCC, and 4 chRCC) tissues, we developed a multinomial lasso classifier that selects 281 total analytes from over 27,000 detected molecular species that distinguishes all histological subtypes of RCC from normal kidney tissues with 84.5% accuracy. On the basis of independent test data reflecting distinct patient populations, the classifier achieves 85.4% and 91.2% accuracy on a Stanford test set (20 normal and 28 RCC) and a Baylor-UT Austin test set (16 normal and 41 RCC), respectively. The majority of the model's selected features show consistent trends across data sets affirming its stable performance, where the suppression of arachidonic acid metabolism is identified as a shared molecular feature of ccRCC and pRCC. Together, these results indicate that signatures derived from DESI-MSI combined with machine learning may be used to rapidly determine surgical margin status with accuracies that meet or exceed those reported for IFS.

Wiskott-Aldrich syndrome gene as a prognostic biomarker correlated with immune infiltrates in clear cell renal cell carcinoma.

The abnormal expression of the Wiskott-Aldrich syndrome protein (WASP) encoded by the Wiskott-Aldrich syndrome (WAS) gene has been implicated in tumor invasion and immune regulation. However, prognostic implications of WAS and its correlation tumor infiltrating in renal clear cell carcinoma (ccRCC) is not clear cut. The correlation between WAS expression, clinicopathological variables and clinical outcomes were evaluated using The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), Tumor Immune Estimation Resource (TIMER), UALCAN, Gene Expression Profiling Interaction Analysis (GEPIA), Kaplan-Meier (KM) plotter and other databases. Furthermore, we assessed the transcription expression of WAS in renal cancer tissues, various renal carcinoma cell lines and human renal tubular cells (HK2) using quantitative polymerase chain reaction (qPCR). A comprehensive analysis of multiple databases including TIMER, GEPIA, TISIDB, ESTIMATE algorithm, and CIBERSORT algorithm were performed to determine the correlation between WAS and tumor infiltrating immune cells in ccRCC. The results displayed an increase in WAS mRNA level in ccRCC compared to normal tissue. WAS protein level was found highly expressed in cancer tissues, particularly within renal tumor cells via the human protein atlas (HPA). Interestingly, we found that elevated WAS expression was significantly positively correlated with the infiltration of CD8+ T cells, B cells, Monocytes, Neutrophils, Macrophages, T cell regulation, NK cells, and Dendritic cells in ccRCC. Bioinformatics demonstrated a strong correlation between WAS expression and 42 immune checkpoints, including the T cell exhaustion gene PD-1, which is critical for exploring immunotherapy for ccRCC. We revealed that patients with high WAS expression were less sensitive to immunotherapy medications. In conclusion, our study identified that WAS was a prognostic biomarker and correlated with immune infiltrates in ccRCC.

SLC14A1 is a new biomarker in renal cancer.

Renal cancer is one of the common malignant tumors of the urinary tract, prone to distant metastasis and drug resistance, with a poor clinical prognosis. SLC14A1 belongs to the solute transporter family, which plays a role in urinary concentration and urea nitrogen recycling in the renal, and is closely associated with the development of a variety of tumors. Transcription data for renal clear cell carcinoma (KIRC) were obtained from the public databases Gene Expression Omnibus database (GEO) and The Cancer Genome Atlas (TCGA), and we investigated the differences in SLC14A1 expression in cancerous and normal tissues of renal cancer, its correlation with the clinicopathological features of renal cancer patients. Then, we verified the expression levels of SLC14A1 in renal cancer tissues and their Paracancerous tissues using RT-PCR, Western-blotting and immunohistochemistry. Finally, we used renal endothelial cell line HEK-293 and renal cancer cell lines 786-O and ACHN to explore the effects of SLC14A1 on the biological behaviors of renal cancer cell proliferation, invasion and metastasis using EDU, MTT proliferation assay, Transwell invasion assay and scratch healing assay. SLC14A1 was lowly expressed in renal cancer tissues and this was further validated by RT-PCR, Western blotting, and immunohistochemistry in our clinical samples. Analysis of KIRC single-cell data suggested that SLC14A1 was mainly expressed in endothelial cells. Survival analysis showed that low levels of SLC14A1 expression were associated with a better clinical prognosis. In biological behavioral studies, we found that upregulation of SLC14A1 expression levels inhibited the proliferation, invasion, and metastatic ability of renal cancer cells. SLC14A1 plays an important role in the progression of renal cancer and has the potential to become a new biomarker for renal cancer.

The novel putative methyltransferase METTL7A as one prognostic biomarker potentially associated with immune infiltration in human renal cancer

Among urological cancers, renal cancer has the highest fatality rate. In a previous pan-cancer study of the METTL family, we observed a stronger association between the METTL family members and the risk of renal cancer compared to other cancers. Among these members, METTL7A, a potential methyltransferase, was identified as a protective factor, although its role and mechanism in renal cancer remain unclear. In this study, we utilized public databases to examine the expression of METTL7A in renal cancer tissues and normal tissues and found that METTL7A expression was much lower in renal cancer tissues. We also noticed a link between low METTL7A expression and poor prognosis for patients. According to the results of our functional enrichment analysis, METTL7A may have a role in immunological functions in renal cancer. METTL7A expression was strongly linked with the degrees of immune cell infiltration and expression of numerous immunological components. METTL7A had significantly different effects on the survival times of renal cancer patients with high or low immune infiltration. Our findings suggest that METTL7A may be used as both a prognostic biomarker and an immunological target for kidney cancer. In conclusion, our study sheds light on the importance of METTL7A in renal cancer and emphasizes the potential of targeting METTL7A as a novel therapeutic strategy for kidney cancer.