CCL5 promotes the epithelial-mesenchymal transition of circulating tumor cells in renal cancer.

BACKGROUND: Circulating tumor cells (CTCs) are pivotal in tumor metastasis across cancers, yet their specific role in renal cancer remains unclear. METHODS: This study investigated C-C motif chemokine ligand 5 (CCL5)'s tumorigenic impact on renal cancer cells and CTCs using bioinformatics, in vivo, and in vitro experiments. It also assessed renal cancer patients' CTCs prognostic value through Lasso regression and Kaplan-Meier survival curves. RESULTS: Bioinformatics analysis revealed differential genes focusing on cellular adhesion and migration between CTCs and tumor cells. CCL5 exhibited high expression in various CTCs, correlating with poor prognosis in renal cancer. In 786-O-CTCs, CCL5 enhanced malignancy, while in renal cell carcinoma cell line CAKI-2 and 786-O, it promoted epithelial-mesenchymal transition (EMT) via smad2/3, influencing cellular characteristics. The nude mouse model suggested CCL5 increased CTCs and intensified EMT, enhancing lung metastasis. Clinical results shown varying prognostic values for different EMT-typed CTCs, with mesenchymal CTCs having the highest value. CONCLUSIONS: In summary, CCL5 promoted EMT in renal cancer cells and CTCs through smad2/3, enhancing the malignant phenotype and facilitating lung metastasis. Mesenchymal-type CTC-related factors can construct a risk model for renal cancer patients, allowing personalized treatment based on metastatic risk prediction.

The association of platelet count, high-density lipoprotein cholesterol, and platelet/high-density lipoprotein cholesterol ratio with serum soluble Klotho.

BACKGROUND AND OBJECTIVE: Klotho is a protein that is closely related to human aging. Soluble Klotho (S-Klotho) is a circulating protein, and its level decreases in response to systemic inflammation. The relationship between the platelet/high-density lipoprotein cholesterol ratio (PHR), an emerging inflammatory index, and S-Klotho concentrations is still unclear. In addition, the mean platelet volume has been confirmed to have a significant negative association with S-Klotho concentrations, but the relationship between the platelet count (PC) and S-Klotho concentrations has not yet been reported. METHODS: Data from individuals who participated in the National Health and Nutrition Examination Survey (NHANES) during the five cycles from 2007 to 2016 were retrieved for analysis. Linear regression, two-piecewise linear regression, and restricted cubic spline (RCS) methods were used to analyze the associations of the PHR index and its components with S-Klotho concentrations. In addition, subgroup analysis and effect modification tests were conducted. RESULTS: A total of 11,123 participants (5463 men (48.17%)), with an average age of 56.2 years, were included. After full adjustment, the S-Klotho levels of participants in the highest quartile group of PHR (ß: -51.19, 95% CI: -75.41 to -26.97, P < 0.001) and the highest quartile group of PC (ß: -72.34, 95% CI: -93.32 to -51.37, P < 0.0001) were significantly lower than those in their respective lowest quartile groups, and a significant downward trend was presented among the four groups (P for trend < 0.05, respectively). However, high-density lipoprotein cholesterol (HDL-C) concentrations were not significantly associated with S-Klotho concentrations. RCS revealed that the PHR and PC were nonlinearly associated with S-Klotho concentrations; two-piecewise linear regression revealed that the inflection points were 175.269 and 152, respectively, and that these associations slightly weakened after the inflection point. According to the subgroup analysis, liver disease status enhanced the association between the PC and S-Klotho concentrations. CONCLUSIONS: Both the PHR and PC were significantly negatively associated with S-Klotho concentrations, and these associations were nonlinear. There was no significant association between HDL-C and S-Klotho concentrations. Liver disease status enhances the negative association between the PC and S-Klotho concentrations, and the specific mechanism deserves further exploration.

Unveiling a pH-Responsive Dual-Androgen-Blocking Magnetic Molecularly Imprinted Polymer for Enhanced Synergistic Therapy of Prostate Cancer.

Prostate cancer is the most common malignancy diagnosed in men. Androgens are directly related to its pathogenesis. Inhibition of the androgen receptor (AR) is considered to be the most promising therapeutic approach for the treatment of prostate cancer. In this study, a new type of pH-responsive dual androgen-blocking nanodrug (FASC MIPs) based on a molecularly imprinted polymer has been designed and synthesized. The nanodrug could selectively sequester testosterone from the prostate tumor through specific molecular imprinting sites and simultaneously deliver the AR inhibitory drug bicalutamide, which ultimately leads to enhanced synergistic therapy of prostate cancer. FASC MIPs demonstrate excellent pH responsiveness in a simulated tumor microenvironment due to the presence of chitosan and significantly inhibit the growth of prostate cancer cells (LNCaP cells) by blocking the G1 phase of cytokinesis. Additionally, the nanodrug also displayed excellent antitumor properties in a xenograft mouse model of prostate cancer without any sign of detrimental effects on healthy tissues and organs. Both in vitro and in vivo studies verified the augmented and synergistic therapeutic effects of FASC MIPs, and the proposed dual-androgen-blocking strategy could explore novel avenues in prostate cancer treatment.

Rectifying disorder of extracellular matrix to suppress urethral stricture by protein nanofilm-controlled drug delivery from urinary catheter.

Urethral stricture secondary to urethral injury, afflicting both patients and urologists, is initiated by excessive deposition of extracellular matrix in the submucosal and periurethral tissues. Although various anti-fibrotic drugs have been applied to urethral stricture by irrigation or submucosal injection, their clinical feasibility and effectiveness are limited. Here, to target the pathological state of the extracellular matrix, we design a protein-based nanofilm-controlled drug delivery system and assemble it on the catheter. This approach, which integrates excellent anti-biofilm properties with stable and controlled drug delivery for tens of days in one step, ensures optimal efficacy and negligible side effects while preventing biofilm-related infections. In a rabbit model of urethral injury, the anti-fibrotic catheter maintains extracellular matrix homeostasis by reducing fibroblast-derived collagen production and enhancing metalloproteinase 1-induced collagen degradation, resulting in a greater improvement in lumen stenosis than other topical therapies for urethral stricture prevention. Such facilely fabricated biocompatible coating with antibacterial contamination and sustained-drug-release functionality could not only benefit populations at high risk of urethral stricture but also serve as an advanced paradigm for a range of biomedical applications.

Corrigendum: A New Prognostic Risk Score: Based on the Analysis of Autophagy-Related Genes and Renal Cell Carcinoma.

[This corrects the article DOI: 10.3389/fgene.2021.820154.].

Tumor mutational burden presents limiting effects on predicting the efficacy of immune checkpoint inhibitors and prognostic assessment in adrenocortical carcinoma.

BACKGROUND: Adrenocortical carcinoma (ACC) is a highly malignant urologic cancer and tends to metastasize. Although immune checkpoint inhibitors (ICIs) bring a glimmer of light to conquer ACC, only a fraction of patients have benefit from ICIs treatment. It is well known that tumor mutational burden (TMB) is closely associated with the efficacy and response rate of immunotherapy. However, its roles in ACC were not investigated. METHODS: Using somatic mutations data of 92 ACC samples in TCGA database, we calculated their TMB values by the 'maftools' package in R software (Ver 3.6.3). To explore the roles of TMB in ICIs therapy, we have addressed this issue from three perspectives. First, the effects of TMB levels on tumor immune microenvironment (TIM) were analyzed through CIBERSORT algorithm, ssGSEA method and TIMER web server. Second, we investigated the expressive correlations between TMB level and five pivotal immune checkpoints based on Pearson coefficient. Third, the difference in TIDE score between high- and low-TMB groups was compared. The prognostic value of TMB was also evaluated. Besides, GSEA was performed to determine the changes in the activities of signaling pathways caused by TMB. RESULTS: TMB values in ACC samples were not high. The average of total mutation counts in each sample was only 21.5. High TMB could lead metabolic reprogramming and poor survival outcomes. However, it was unable to affect the infiltration levels of lymphocytes, and failed to facilitate the activities of immune-related pathways. Regarding immune checkpoints (ICs), only PD-L1 upregulation could result in a good prognosis, and TMB level did not correlate with the expressions of other ICs except for LAG3. There was no significant difference in TIDE score between high- and low-TMB groups. Combining the present results and previous study, we speculated that inadequate stimulation for neoantigens formation, intrinsic immune-resistance and special genomic alterations were three possible reasons for TMB limiting functions in TIM and ICIs. Besides, TMB was toughly applied in clinical practice due to its high cost of determination and non-universal definition of high TMB. CONCLUSIONS: TMB presents limiting effects on prediction for ICIs efficacy and prognostic assessment for ACC patients.

Abnormal expression and the significant prognostic value of aquaporins in clear cell renal cell carcinoma.

Aquaporins (AQPs) are a kind of transmembrane proteins that exist in various organs of the human body. AQPs play an important role in regulating water transport, lipid metabolism and glycolysis of cells. Clear cell renal cell carcinoma (ccRCC) is a common malignant tumor of the kidney, and the prognosis is worse than other types of renal cell cancer (RCC). The impact of AQPs on the prognosis of ccRCC and the potential relationship between AQPs and the occurrence and development of ccRCC are demanded to be investigated. In this study, we first explored the expression pattern of AQPs by using Oncomine, UALCAN, and HPA databases. Secondly, we constructed protein-protein interaction (PPI) network and performed function enrichment analysis through STRING, GeneMANIA, and Metascape. Then a comprehensive analysis of the genetic mutant frequency of AQPs in ccRCC was carried out using the cBioPortal database. In addition, we also analyzed the main enriched biological functions of AQPs and the correlation with seven main immune cells. Finally, we confirmed the prognostic value of AQPs throughGEPIA and Cox regression analysis. We found that the mRNA expression levels of AQP0/8/9/10 were up-regulated in patients with ccRCC, while those of AQP1/2/3/4/5/6/7/11 showed the opposite. Among them, the expression differences of AQP1/2/3/4/5/6/7/8/9/11 were statistically significant. The differences in protein expression levels of AQP1/2/3/4/5/6 in ccRCC and normal renal tissues were consistent with the change trends of mRNA. The biological functions of AQPs were mainly concentrated in water transport, homeostasis maintenance, glycerol transport, and intracellular movement of sugar transporters. The high mRNA expression levels of AQP0/8/9 were significantly correlated with worse overall survival (OS), while those of AQP1/4/7 were correlated with better OS. AQP0/1/4/9 were prognostic-related factors, and AQP1/9 were independent prognostic factors. In general, this research has investigated the values of AQPs in ccRCC, which could become new survival markers for ccRCC targeted therapy.

Prognostic value of circulating tumor cells and immune-inflammatory cells in patients with renal cell carcinoma.

PURPOSE: The relationships among circulating tumor cells (CTCs), inflammatory cells, and platelets in patients with renal cell carcinoma (RCC) are not transparent. We evaluated the correlations among CTCs, blood inflammatory cells, and platelets in patients with RCC and their prognostic value for metastasis-free survival. METHODS: CTC and typical tumor cell chip data were collected and analyzed by the GEO database. The baseline data, survival data, CTCs data, and blood test results were statistically analyzed. RESULTS: Bioinformatics analysis showed that the function of the differentially expressed genes between CTCs and normal tumor cells mainly involved platelets and immune inflammation. A total of 82 patients whose follow-up time was 3 to 68 months were included in the analysis. Clinical data of the patients confirmed that there is a correlation between platelets and mesenchymal CTCs. Simultaneously, there was a correlation between immune inflammatory cells and platelets. The univariate Cox proportional hazards model indicated that staging, mesenchymal CTCs, and the monocyte-to-neutrophil ratio (MNR) had prognostic value. The multivariate Cox proportional hazards model indicated that staging and the MNR had prognostic value and high accuracy. CONCLUSIONS: Bioinformatics analysis showed that CTCs were related to platelets and immune-inflammatory cells. Furthermore, the clinical data confirmed that platelets were correlated with mesenchymal CTCs and immune-inflammatory cells in the blood. By using mesenchymal CTCs, the MNR, or staging respectively, it is possible to predict the risk of postoperative metastasis in RCC patients. As a compound prognostic factor, staging, and the MNR can provide more convenient and accurate condition monitoring.

The roles of ferroptosis regulatory gene SLC7A11 in renal cell carcinoma: A multi-omics study.

BACKGROUND: The ferroptosis inhibitory gene Solute carrier family 7 member 11 (SLC7A11) provides a new strategy for anticancer treatment. However, its function in renal cell carcinoma (RCC) remains elusive. METHODS: The expression and somatic mutation information of SLC7A11 in RCC samples were determined using The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), Gene Expression Omnibus (GEO), Oncomine, and cBioPortal databases. The prognostic value of SLC7A11 was assessed through survival analysis, Receiver operating characteristic curve (ROC) analysis, independent prognostic analysis, clinical subgroup analysis, and nomogram. Its prognostic value was also validated in the ICGC and GSE29607 cohorts. Gene set enrichment analysis (GSEA) was employed to investigate the effects of SLC7A11 on multiple metabolic pathways. The CIBERSORT algorithm and single-sample gene set enrichment analysis (ssGSEA) method were applied to evaluate the effects of SLC7A11 on the tumor immune microenvironment (TIM). SLC7A11's therapeutic correlations were analyzed using the GSE87121, GSE67501, and GSDC datasets. Finally, the biofunctions of SLC7A11 in renal cancer cells and ferroptosis were ascertained by MTT, wound healing, transwell, and western blot assays. RESULTS: Through multiple datasets, SLC7A11 was found to be markedly upregulated in RCC. In terms of prognosis, SLC7A11 overexpression conferred a worse prognosis and was identified as an independent prognostic factor. Its prognostic value was validated in ICGC cohort. Moreover, high SL7CA11 expression could stimulate nucleotides, fatty acids, and amino acid metabolism to meet the proliferative consumption of tumor cells. As for the immune effect, SLC7A11 suppressed antitumor immunity by reducing the abundances of CD8+ T and NK cells. Regarding the therapeutic response, SLC7A11 expression was not correlated with the sensitivities of most chemotherapy and targeted drugs. Finally, SLC7A11 promoted the proliferation, migration, and invasion of renal cancer cells by enhancing GPX4 output, which in turn inhibits ferroptosis. CONCLUSIONS: SLC7A11 not only deeply influences RCC prognosis and TIM, but also promotes RCC progression by inhibiting ferroptosis and inducing metabolic reprogramming. In addition, SLC7A11 weakly affects the therapeutic effect and sensitivities of multiple chemotherapy and targeted drugs.

The prognostic value of circulating tumour cells (CTCs) and CTC white blood cell clusters in patients with renal cell carcinoma.

PURPOSE: Circulating tumour cell (CTC) and CTC-white blood cell (CTC-WBC) clusters are related to the prognosis of tumour patients. However, the relationship between CTC-WBC clusters and prognosis in renal cell carcinoma (RCC) patients is not clear. We evaluated the prognostic value of CTC-WBC clusters using metastasis-free survival (MFS) and overall survival (OS) in patients with RCC. MATERIALS AND METHODS: The baseline, survival, and CTC data of patients with RCC were statistically analysed by R. RESULTS: The Cox risk proportional regression model suggests that the total CTCs, pathology type, and CTC-WBC clusters can be used as prognostic indicators for the MFS of RCC patients. Total CTCs and solid tumour diameter can be used as prognostic indicators for the OS of RCC patients. Using Kaplan-Meier survival analysis, we found that patients with total CTCs, pathology, and CTC-WBC clusters greater than the cut-off value had a worse MFS, and patients with total CTCs greater than the cut-off value had a worse OS. CONCLUSION: The analysis of the clinical sample data in patients with RCC shows that CTC-WBC clusters play an important role in monitoring the prognosis of RCC. Among them, total CTCs, pathology, and CTC-WBC clusters were combined as prognostic factors for the MFS of RCC patients. Total CTCs and solid tumour diameter can be combined as prognostic factors for the OS of RCC patients. These prognostic factors provide more convenient and accurate condition monitoring for renal cancer patients and can be used to actively improve the prognosis of patients.

Expression patterns and prognostic value of RUNX genes in kidney cancer.

Kidney cancer is the third most common malignancy of the urinary system, of which, kidney renal clear cell carcinoma (KIRC) accounts for the vast majority. Runt-related transcription factors (RUNX) are involved in multiple cellular functions. However, the diverse expression patterns and prognostic values of RUNX genes in kidney cancer remained to be elucidated. In our study, we mined the DNA methylation, transcriptional and survival data of RUNX genes in patients with different kinds of kidney cancer through Oncomine, Gene Expression Profiling Interactive Analysis, UALCAN, Kaplan-Meier Plotter, cBioPortal and LinkedOmics. We found that RUNX1 and RUNX3 were upregulated in KIRC tissues compared with those in normal tissues. The survival analysis results indicated a high transcription level of RUNX1 was associated with poor overall survival (OS) in KIRC patients. Furthermore, KIRC tumor tissues had significantly lower levels of RUNX1 promoter methylation than that in paracancerous tissues, with decreased DNA methylation of RUNX1 notably associated with poor OS in KIRC. In conclusion, our results revealed that RUNX1 may be a potential therapeutic target for treating KIRC, and RUNX1 promoter methylation level shows promise as a novel diagnostic and prognostic biomarker, which laid a foundation for further study.

Bioinformatic analyses and experimental validation of the role of m6A RNA methylation regulators in progression and prognosis of adrenocortical carcinoma.

M6A-related genes have been proven to play an important role in many cancers. However, the role of that in adrenocortical carcinoma (ACC) has not been fully elucidated. In the present study, 77 ACC samples from TCGA database were divided into localized (n = 46) and metastatic (n = 31) groups. Three differential expression genes (DEGs) and five prognostic m6A genes were screened out. M6A-related risk signature (RBM15 and HNRNPC) was constructed by the Lasso regression analysis. In TCGA cohort (training cohort), the risk signature was identified as an ACC-independent prognostic factor and can distinguish the prognostic difference of ACC patients with clinical stage I-II, T3-4 and N0 stages. A nomogram combining T stage and m6A risk score was constructed to predict the overall survival rate (OSR) of individual at 1,2,3 year. Meanwhile, its prognostic value was also confirmed in the validation cohort (GSE33371 dataset). The potential associations between m6A risk level and immune checkpoint inhibitors (ICIs) therapy were also investigated via the TISIDB online tool. High m6A risk not only can suppress immunotherapy-related biological processes, but also repress the expressions of immune-checkpoint markers. Moreover, five pairs of clinical specimens were collected to confirm the overexpression of HNRNPC and non-ectopic expression of RBM15 in tumor tissues. HNRNPC was proven to promote the proliferation, migration and invasion of H295R and SW13 cells through MTT and Transwell assays. In conclusion, the m6A-related risk signature was beneficial for prognostic analysis and can affect immune microenvironment in ACC. HNRNPC played a pro-cancer role in ACC progression.

A New Prognostic Risk Score: Based on the Analysis of Autophagy-Related Genes and Renal Cell Carcinoma.

Introduction: Clear cell renal cell carcinoma (ccRCC) patients suffer from its high recurrence and metastasis rate, and a new prognostic risk score to predict individuals with high possibility of recurrence or metastasis is in urgent need. Autophagy has been found to have a dual influence on tumorigenesis. In this study we aim to analyze autophagy related genes (ATGs) and ccRCC patients and find a new prognostic risk score. Method: Analyzing differential expression genes (DEGs) in TCGA-KIRC dataset, and took intersection with ATGs. Through lasso, univariate, and multivariate cox regression, DEGs were chosen, and the coefficients and expression levels of them were components constructing the formula of risk score. We analyzed mRNA expression of DEGs in tumor and normal tissue in ONCOMINE database and TCGA-KIRC dataset. The Human Protein Atlas (HPA) was used to analyze protein levels of DEGs. The protein-protein interaction (PPI) network was examined in STRING and visualized in cytoscape. Functional enrichment analysis was performed in RStudio. To prove the ability and practicibility of risk score, we analyzed univariate and multivariate cox regression, Kaplan-Meier curve (K-M curve), risk factor association diagram, receiver operating characteristic curve (ROC curve) of survival and nomogram, and the performance of nomogram was evaluated by calibration curve. Then we further explored functional enrichment related to risk groups through Gene Set Enrichment Analysis (GSEA), weighted gene co-expression network analysis (WGCNA), and Metascape database. At last, we investigated immune cell infiltration of DEGs and two risk groups through TIMER database and "Cibersort" algorithm. Result: We identified 7 DEGs (BIRC5, CAPS, CLDN7, CLVS1, GMIP, IFI16, and TCIRG1) as components of construction of risk score. All 7 DEGs were differently expressed in ccRCC and normal tissue according to ONCOMINE database and TCGA-KIRC dataset. Functional enrichment analysis indicated DEGs, and their most associated genes were shown to be abundant in autophagy-related pathways and played roles in tumorigenesis and progression processes. A serious analysis proved that this risk score is independent from the risk signature of ccRCC patients. Conclusion: The risk score constructed by 7 DEGs had the ability of predicting prognosis of ccRCC patients and was conducive to the identification of novel prognostic molecular markers. However, further experiment is still needed to verify its ability and practicability.

The effect of a novel glycolysis-related gene signature on progression, prognosis and immune microenvironment of renal cell carcinoma.

BACKGROUND: Glycolysis is a central metabolic pathway for tumor cells. However, the potential roles of glycolysis-related genes in renal cell carcinoma (RCC) have not been investigated. METHODS: Seven glycolysis-related gene sets were selected from MSigDB and were analyzed through GSEA. Using TCGA database, the glycolysis-related gene signature was constructed. Prognostic analyses were based on the Kaplan-Meier method. The cBioPortal database was employed to perform the mutation analyses. The CIBERSORT algorithm and TIMER database were used to determine the immunological effect of glycolytic gene signature. The expressions in protein level of eight glycolytic risk genes were determined by HPA database. Finally, qPCR, MTT and Transwell invasion assays were conducted to validate the roles of core glycolytic risk genes (CD44, PLOD1 and PLOD2) in RCC. RESULTS: Four glycolysis-related gene sets were significantly enriched in RCC samples. The glycolytic risk signature was constructed (including CD44, PLOD2, KIF20A, IDUA, PLOD1, HMMR, DEPDC1 and ANKZF1) and identified as an independent RCC prognostic factor (HR = 1.204). Moreover, genetic alterations of glycolytic risk genes were uncommon in RCC (10.5%) and glycolytic risk signature can partially affect immune microenvironment of RCC. Six glycolytic risk genes (except for IDUA and HMMR) were over-expression in A498 and 786-O renal cancer cells through qPCR test. MTT and Transwell assays revealed that silencing of CD44, PLOD1 and PLOD2 suppressed the proliferation and invasion of renal cancer cells. CONCLUSIONS: The glycolysis-related risk signature is closely associated with RCC prognosis, progression and immune microenvironment. CD44, PLOD1 and PLOD2 may serve as RCC oncogenes.

Identification of key genes and functions of circulating tumor cells in multiple cancers through bioinformatic analysis.

BACKGROUND: Circulating tumor cells (CTCs) play a key role in cancer progression, especially metastasis, due to the rarity and heterogeneity of CTCs, fewer researches have been conducted on them at the molecular level. However, through the Gene Expression Omnibus (GEO) database, this kind of minority researches can be well integrated, the gene expression differences between CTCs and primary tumors can be identified, and molecular targets for CTCs can be found. METHODS: We analyzed 7 sets of gene chips (GSE82198, GSE99394, GSE31023, GSE65505, GSE67982, GSE76250, GSE50746) obtained by GEO. Analysis of differentially expressed genes (DEGs) between CTCs and corresponding primary tumors by NetworkAnalyst. Metascape tool for Gene Ontology (GO) / Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of differential genes and visual display. Cytoscape performs protein-protein interaction (PPI) analysis and obtains the hub genes. Renal cancer patients' clinical specimens to verify the correctness of enrichment results. Prognostic analysis of hub genes in kidney cancer patients using the Kaplan-Meier plotter survival analysis tool. RESULTS: We obtained a total of 589 DEGs. The GO / KEGG enrichment results indicate that the DEGs are mainly concentrated in cell adhesion, epithelial-mesenchymal transition (EMT), and apoptosis. Renal cancer clinical specimens suggest that CTCs have epithelial and mesenchymal types. At the same time, PSMC2 can be used as a poor prognostic indicator for renal cancer patients. CONCLUSIONS: In summary, our study suggests that compared with primary tumors, CTCs mainly change cell adhesion, EMT, and apoptosis. PSMC2 can be used as a poor prognostic factor.

The impact of TNFSF14 on prognosis and immune microenvironment in clear cell renal cell carcinoma.

BACKGROUND: TNFSF14 has been proven to play an important role in various types of tumors. However, its function in renal cell carcinoma (RCC) has not yet been fully elucidated. OBJECTIVE: In order to explore molecular mechanism of RCC, we evaluated the effect of TNFSF14 on RCC progression, prognosis and immune microenvironment. METHODS: Using TCGA database, the differential expression of TNFSF14 and its relationships between clinicopathological features and prognosis were determined. Cox univariate and multivariate analyses were successively performed to identify whether TNFSF14 was an independent prognostic factor. The discriminating ability of TNFSF14 in RCC prognosis analysis was validated under the same clinical subgroups. Tumor mutational burden (TMB) of each RCC samples was calculated and the differential expression of TNFSF14 between high- and low-TMB groups was analyzed. The immune abundances of 22 leukocyte subtypes in each RCC samples were presented through the CIBERSORT algorithm. TIMER database was used to explore the relationships between copy number of TNFSF14 and the infiltration levels of 6 immune cells. RESULTS: Overexpression of TNFSF14 implied adverse clinicopathological features and poor prognosis. Meanwhile, TNFSF14 was identified as an independent prognostic factor (HR = 1.047, P = 0.028) and possessed prevalent applicability in RCC prognostic analysis. TNFSF14 was upregulated in high-TMB group than that in low-TMB group (Log2FC = 0.722). Moreover, overexpression of TNFSF14 brought alteration of immune abundance of 8 leukocyte subtypes. Besides, somatic copy number alteration (SCNA) of TNFSF14 was associated with infiltration levels of 6 immune cells. CONCLUSIONS: TNFSF14 has crucial impact on progression, prognosis and immune microenvironment in RCC. Besides, TNFSF14 may be a potential biomarker for predicting the efficacy and response rate of RCC immunotherapy.

Pathology of circulating tumor cells and the available capture tools (Review).

Circulating tumor cells (CTCs), are tumor cells that diffuse into the circulating blood and serve an important role in the progress of cancer. During the early stages of cancer, CTCs undergo an epithelial­mesenchymal transition and obtain a more invasive phenotype. Subsequently, the tumor cells enter the circulating blood with the aid of immune cells, and enter a dormant state upon reaching distal organs. As the tumor progresses, metastasis may occur under certain conditions. The capture technologies available for CTCs are based on antibody­based capture, or capture based on the physical properties of CTCs, as well as modern technologies that integrate both these methods. Emerging modern technologies have increased the accuracy and efficiency of tumor cell capture, and have thus improved our understanding of tumor cells, and the molecular mechanisms underlying their properties. CTCs serve an important role in disease progression, prediction of patient prognosis and individualized treatment.