Description of 2 angiogenic phenotypes in clear cell renal cell carcinoma

Construction of EMT related prognostic signature for kidney renal clear cell carcinoma, through integrating bulk and single-cell gene expression profiles

Introduction: Kidney renal clear cell carcinoma (KIRC), as a main type of malignant kidney cancers, has a poor prognosis. Epithelial-mesenchymal transformation (EMT) exerts indispensable role in tumor progression and metastasis, including in KIRC. This study aimed to mine more EMT related details and build prognostic signature for KIRC. Methods: The KIRC scRNA-seq data and bulk data were downloaded from GEO and TCGA databases, respectively. The cell composition in KIRC was calculated using CIBERSORT. Univariate Cox regression analysis and LASSO Cox regression analysis were combined to determine the prognostic genes. Gene set variation analysis and cell-cell communication analysis were conducted to obtain more functional information. Additionally, functional analyses were conducted to determine the biological roles of si-LGALS1 in vitro. Results: We totally identified 2,249 significant differentially expressed genes (DEGs) in KIRC samples, meanwhile a significant distinct expression pattern was found in KIRC, involving Epithelial Mesenchymal Transition pathway. Among all cell types, significantly higher proportion of epithelial cells were observed in KIRC, and 289 DEGs were identified in epithelial cells. After cross analysis of all DEGs and 970 EMT related genes, SPARC, TMSB10, LGALS1, and VEGFA were optimal to build prognostic model. Our EMT related showed good predictive performance in KIRC. Remarkably, si-LGALS1 could inhibit migration and invasion ability of KIRC cells, which might be involved in suppressing EMT process. Conclusion: A novel powerful EMT related prognostic signature was built for KIRC patients, based on SPARC, TMSB10, LGALS1, and VEGFA. Of which, si-LGALS1 could inhibit migration and invasion ability of KIRC cells, which might be involved in suppressing EMT process.

Comprehensive analyses of immune tumor microenvironment in papillary renal cell carcinoma

BACKGROUND

Papillary renal cell carcinoma (pRCC) is the most common non-clear cell RCC, and associated with poor outcomes in the metastatic setting. In this study, we aimed to comprehensively evaluate the immune tumor microenvironment (TME), largely unknown, of patients with metastatic pRCC and identify potential therapeutic targets.

METHODS

We performed quantitative gene expression analysis of TME using Microenvironment Cell Populations-counter (MCP-counter) methodology, on two independent cohorts of localized pRCC (n=271 and n=98). We then characterized the TME, using immunohistochemistry (n=38) and RNA-sequencing (RNA-seq) (n=30) on metastatic pRCC from the prospective AXIPAP trial cohort.

RESULTS

Unsupervised clustering identified two "TME subtypes", in each of the cohorts: the "immune-enriched" and the "immune-low". Within AXIPAP trial cohort, the "immune-enriched" cluster was significantly associated with a worse prognosis according to the median overall survival to 8 months (95% CI, 6 to 29) versus 37 months (95% CI, 20 to NA, p=0.001). The two immune signatures, Teff and JAVELIN Renal 101 Immuno signature, predictive of response to immune checkpoint inhibitors (CPI) in clear cell RCC, were significantly higher in the "immune-enriched" group (adjusted p<0.05). Finally, five differentially overexpressed genes were identified, corresponding mainly to B lymphocyte populations.

CONCLUSION

For the first time, using RNA-seq and immunohistochemistry, we have highlighted a specific immune TME subtype of metastatic pRCC, significantly more infiltrated with T and B immune population. This "immune-enriched" group appears to have a worse prognosis and could have a potential predictive value for response to immunotherapy, justifying the confirmation of these results in a cohort of metastatic pRCC treated with CPI and in combination with targeted therapies.

TRIAL REGISTRATION NUMBER

NCT02489695.

Single-cell Deconvolution of a Specific Malignant Cell Population as a Poor Prognostic Biomarker in Low-risk Clear Cell Renal Cell Carcinoma Patients

BACKGROUND

Intratumor heterogeneity (ITH) is a key feature in clear cell renal cell carcinomas (ccRCCs) that impacts outcomes such as aggressiveness, response to treatments, or recurrence. In particular, it may explain tumor relapse after surgery in clinically low-risk patients who did not benefit from adjuvant therapy. Recently, single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool to unravel expression ITH (eITH) and might enable better assessment of clinical outcomes in ccRCC.

OBJECTIVE

To explore eITH in ccRCC with a focus on malignant cells (MCs) and assess its relevance to improve prognosis for low-risk patients.

DESIGN, SETTING, AND PARTICIPANTS

We performed scRNA-seq on tumor samples from five untreated ccRCC patients ranging from pT1a to pT3b. Data were complemented with a published dataset composed of pairs of matched normal and ccRCC samples.

INTERVENTION

Radical or partial nephrectomy on untreated ccRCC patients.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Viability and cell type proportions were determined by flow cytometry. Following scRNA-seq, a functional analysis was performed and tumor progression trajectories were inferred. A deconvolution approach was applied on an external cohort, and Kaplan-Meier survival curves were estimated with respect to the prevalence of malignant clusters.

RESULTS AND LIMITATIONS

We analyzed 54 812 cells and identified 35 cell subpopulations. The eITH analysis revealed that each tumor contained various degrees of clonal diversity. The transcriptomic signatures of MCs in one particularly heterogeneous sample were used to design a deconvolution-based strategy that allowed the risk stratification of 310 low-risk ccRCC patients.

CONCLUSIONS

We described eITH in ccRCCs, and used this information to establish significant cell population-based prognostic signatures and better discriminate ccRCC patients. This approach has the potential to improve the stratification of clinically low-risk patients and their therapeutic management.

PATIENT SUMMARY

We sequenced the RNA content of individual cell subpopulations composed of clear cell renal cell carcinomas and identified specific malignant cells the genetic information of which can be used to predict tumor progression.

A novel endothelial-related prognostic index by integrating single-cell and bulk RNA sequencing data for patients with kidney renal clear cell carcinoma

Background: Endothelial cells in the tumor microenvironment play an important role in the development of kidney renal clear cell carcinoma (KIRC). We wanted to further identify the function of endothelial cells in KIRC patients by integrating single-cell and bulk RNA sequencing data.

Methods: Online databases provide the original data of this study. An endothelial-related prognostic index (ERPI) was constructed and validated by R version 3.6.3 and relative packages.

Results: The ERPI consisted of three genes (CCND1, MALL, and VWF). Patients with high ERPI scores were significantly correlated with worse prognosis than those with low ERPI scores in the TCGA training group, TCGA test group, and GSE29609 group. A positive correlation was identified between the ERPI score and poor clinical features. The results of functional analysis indicated that ERPI was significantly associated with immune-related activities. We suggested that patients with high ERPI scores were more likely to benefit from immunotherapy based on the results of immune checkpoints, tumor microenvironment, stemness index, and TCIA, while patients with low ERPI scores were sensitive to gemcitabine, docetaxel, paclitaxel, axitinib, pazopanib, sorafenib, and temsirolimus according to the results of the “pRRophetic” algorithm. Therefore, this ERPI may help doctors choose the optimal treatment for patients with KIRC.

Conclusion: By integrating single-cell and bulk RNA sequencing data from KIRC patients, we successfully identified the key genes from the perspective of endothelial cells in the tumor microenvironment and constructed ERPIs that had positive implications in precision medicine.

Cell Differentiation Trajectory Predicts Prognosis and Immunotherapeutic Response in Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is the main type of malignancy in kidney related to glucose metabolism. Primary single cell culture and single cell sequencing are novel research technologies. In this study, we explored the differentiation status of ccRCC cells and its significance in prognosis and immunotherapeutic response through bioinformatics. We characterized distinct differentiation states and differentiation-related genes (DRGs) in ccRCC cells through single cell RNA sequencing (scRNA-seq) analysis. Combined with bulk RNA-seq data, we classified patients into two clusters and found that this classification was closely correlated with patient prognosis and immunotherapeutic responses. Based on machine learning, we identified a prognostic risk model composed of 14 DRGs, including BTG2, CDKN1A, COL6A1, CPM, CYB5D2, FOSB, ID2, ISG15, PLCG2, SECISBP2, SOCS3, TES, ZBTB16, and ZNF704, to predict the survival rate of patients and then constructed a nomogram model integrating clinicopathological characteristics and risk score for clinical practice. In the study of immune checkpoints, we found that patients in the high-risk group had a disposition to get worse prognosis and better effects of immune checkpoint blocking therapies. Finally, we found the expression level of model DRGs was associated with a tumor-immune microenvironment (TIME) pattern and the response of 83 compounds or inhibitors was significantly different in the two risk groups. In a word, our study highlights the potential contribution of cell differentiation in prognosis judgment and immunotherapy response and offers promising therapeutic options for ccRCC patients.

Pyroptosis-Related Gene Signature Predicts the Prognosis of ccRCC Using TCGA and Single-Cell RNA Seq Database

Clear cell renal cell carcinoma (ccRCC) is the most prevalent type of renal carcinoma, which is not sensitive to both radiotherapy and chemotherapy. The objective response rate of metastatic renal cancer to targeted drugs and immunotherapy is unsatisfactory. Pyroptosis, proven as an inflammatory form of programmed cell death, could be activated by some inflammasomes, while could create a tumor-suppressing environment by releasing inflammatory factors in the tumor. To explore indicators predicting the prognosis of ccRCC and the effect of antitumor therapy, we constructed a pyroptosis risk model containing 4 genes after 11 pyroptosis-related genes of 516 ccRCC cases in the TCGA database were scanned. Based on the risk score, 516 ccRCC cases were divided into two groups for functional enrichment analysis and immune profile to seek functional pathways and potential therapeutic targets. Besides, those results were verified in GSE29609 and single-cell transcriptomic data. The study suggests that the conducted pyroptosis model could predict the prognosis of ccRCC and reflect the immune microenvironment, which may help in immune checkpoint inhibitor treatment.

Crosstalk of necroptosis and pyroptosis defines tumor microenvironment characterization and predicts prognosis in clear cell renal carcinoma

Pyroptosis and necroptosis are two recently identified forms of immunogenic cell death in the tumor microenvironment (TME), indicating a crucial involvement in tumor metastasis. However, the characteristics of necroptosis and pyroptosis that define tumor microenvironment and prognosis in ccRCC patients remain unknown. We systematically investigated the transcriptional variation and expression patterns of Necroptosis and Pyroptosis related genes (NPRGs). After screening the necroptosis-pyroptosis clusters, the potential functional annotation for clusters was explored by GSVA enrichment analysis. The Necroptosis-Pyroptosis Genes (NPG) scores were used for the prognosis model construction and validation. Then, the correlations of NPG score with clinical features, cancer stem cell (CSC) index, tumor mutation burden (TMB), TME, and Immune Checkpoint Genes (ICGs) were also individually explored to evaluate the prognosis predictive values in ccRCC. Microarray screenings identified 27 upregulated and 1 downregulated NPRGs. Ten overall survival associated NPRGs were filtered to construct the NPG prognostic model indicating a better prognostic signature for ccRCC patients with lower NPG scores (P< 0.001), which was verified using the external cohort. Univariate and multivariate analyses along with Kaplan-Meier survival analysis demonstrated that NPG score prognostic model could be applied as an independent prognostic factor, and AUC values of nomogram from 1- to 5- year overall survival with good agreement in calibration plots suggested that the proposed prognostic signature possessed good predictive capabilities in ccRCC. A high-/sNPG score is proven to be connected with tumor growth and immune-related biological processes, according to enriched GO, KEGG, and GSEA analyses. Comparing patients with a high-NPG score to those with a low-NPG score revealed significant differences in clinical characteristics, growth and recurrence of malignancies (CSC index), TME cell infiltration, and immunotherapeutic response (P< 0.005), potentially making the NPG score multifunctional in the clinical therapeutic setting. Furthermore, AIM2, CASP4, GSDMB, NOD2, and RBCK1 were also found to be highly expressed in ccRCC cell lines and tumor tissues, and GASP4 and GSDMB promote ccRCC cells’ proliferation, migration, and invasion. This study firstly suggests that targeting the NPG score feature for TME characterization may lend novel insights into its clinical applications in the prognostic prediction of ccRCC.

A signature based on chromatin regulation and tumor microenvironment infiltration in clear cell renal cell carcinoma

Aims: This research aimed to construct a signature based on chromatin regulation in localized clear cell renal cell carcinoma (ccRCC). Materials & methods: Non-negative matrix factorization clustering was performed on 438 localized ccRCC cases. The immune infiltration was generated by the single-sample gene set enrichment analysis algorithm. Survival analyses were performed using the Kaplan-Meier method, and the significance of the differences was determined using the log-rank test. The risk score was constructed based on the expression of chromatin regulators to quantify chromatin modification. Results: A score system based on chromatin modification was established. The high-risk subtype was characterized by increased tumor mutation burden, whereas a low-risk score was characterized by an increase in chromatin regulator expression and better overall survival. Conclusion: This research has constructed a signature based on chromatin regulation in localized ccRCC.

m7G regulator-mediated molecular subtypes and tumor microenvironment in kidney renal clear cell carcinoma

Background: RNA methylation modification plays an important role in immune regulation. m7G RNA methylation is an emerging research hotspot in the RNA methylation field. However, its role in the tumor immune microenvironment of kidney renal clear cell carcinoma (KIRC) is still unclear.

Methods: We analyzed the expression profiles of 29 m7G regulators in KIRC, integrated multiple datasets to identify a novel m7G regulator-mediated molecular subtype, and developed the m7G score. We evaluated the immune tumor microenvironments in m7G clusters and analyzed the correlation of the m7G score with immune cells and drug sensitivity. We tested the predictive power of the m7G score for prognosis of patients with KIRC and verified the predictive accuracy of the m7G score by using the GSE40912 and E-MTAB-1980 datasets. The genes used to develop the m7G score were verified by qRT-PCR. Finally, we experimentally analyzed the effects of WDR4 knockdown on KIRC proliferation, migration, invasion, and drug sensitivity.

Results: We identified three m7G clusters. The expression of m7G regulators was higher in cluster C than in other clusters. m7G cluster C was related to immune activation, low tumor purity, good prognosis, and low m7G score. Cluster B was related to drug metabolism, high tumor purity, poor survival, and high m7G score. Cluster A was related to purine metabolism. The m7G score can well-predict the prognosis of patients with KIRC, and its prediction accuracy based on the m7G score nomogram was very high. Patients with high m7G scores were more sensitive to rapamycin, gefitinib, sunitinib, and vinblastine than other patients. Knocking down WDR4 can inhibit the proliferation, migration, and invasion of 786-0 and Caki-1 cells and increase sensitivity to sorafenib and sunitinib.

Conclusion: We proposed a novel molecular subtype related to m7G modification and revealed the immune cell infiltration characteristics of different subtypes. The developed m7G score can well-predict the prognosis of patients with KIRC, and our research provides a basis for personalized treatment of patients with KIRC.

An inflammation-related signature could predict the prognosis of patients with kidney renal clear cell carcinoma

Background: Kidney renal clear cell carcinoma (KIRC) is an inflammation-related carcinoma, and inflammation has been recognized as an important factor in inducing carcinogenesis. To further explore the role of inflammation in KIRC, we developed an inflammation-related signature and verified its correlation with the tumor micro-environment.

Methods: After the differential inflammation-related prognostic genes were screened by Lasso regression, the inflammation-related signature (IRS) was constructed based on the risk score of multivariate Cox regression. Then, the prognostic value of the IRS was evaluated by Kaplan-Meier analysis, receiver operating characteristic (ROC) curve analysis and multivariate Cox regression. Gene set variation analysis (GSVA) was applied to screen out enriched signaling pathways. Infiltrated immune cells, tumor mutational burden (TMB) and immune checkpoints were explored by CIBERSORTx and maftool.

Results: Four genes (TIMP1, PLAUR, CCL22, and IL15RA) were used to construct the IRS in patients with KIRC. Kaplan-Meier analysis and multivariate Cox regression identified that the IRS could independently predict the prognosis of patients with KIRC in the training and validation groups. The diagnostic value of the nomogram increased from 0.811 to 0.845 after adding the IRS to the multiparameter ROC analysis. The GSVA results indicated that IRS was closely related to primary immunodeficiency and antigen processing and presentation. The immune checkpoint LAG3 was highly expressed in patients with high-risk score (p < 0.05), while CD274 (PD-L1) and HAVCR2 were highly expressed in patients with low-risk score (p < 0.001). There was a significant positive correlation between the high-risk score group and CD8⁺ T, activated CD4⁺ memory T, gamma and delta regulatory T and M0 macrophage cells, while the low-risk score group was negatively associated with B memory, plasma, resting CD4⁺ memory T, activated NK, M1 macrophages and resting mast cells.

Conclusion: We found that the IRS might serve as a biomarker to predict the survival of KIRC. Moreover, patients with high or low-risk score might be sensitive to immune drugs at different immune checkpoints.

Up-regulation of SLC27A2 suppresses the proliferation and invasion of renal cancer by down-regulating CDK3-mediated EMT

Clear cell renal cell carcinoma (ccRCC) is one of the most common malignant tumors of the urinary system. Distant metastasis is the leading cause of poor prognosis in ccRCC. However, ccRCC is found poorly responsitive to radiotherapy and chemotherapy. Effective therapeutic strategies for its metastasis remain scarce. We analyzed clinical samples and public database, for differential expression of SLC27A2 and further explored its relationship with clinical prognosis. Biochemistry and functional experiments were carried out to study the potential mechanisms of SLC27A2, CDK3, and EMT. SLC27A2 was significantly downregulated in clinical specimens and renal cancer cell lines and predicted poor prognosis. We found that specific upregulation of SLC27A2 could significantly inhibited the proliferation, migration, and invasion of renal cancer cell lines. SLC27A2 could also influence the Epithelial-mesenchymal transition (EMT) signaling pathway, linked to the progression and metastasis of renal cancer. Using whole transcriptome sequencing of SLC27A2, CDK3 was identified as a regulatory SLC27A2 target. In terms of mechanism, SLC27A2 may further inhibit the epithelial-to-mesenchymal transition by negatively regulating CDK3. Our work suggests that functional inhibition of SLC27A2-CDK3-EMT axis may be an attractive therapeutic target for metastasis of ccRCC.

Exploring synthetic lethal network for the precision treatment of clear cell renal cell carcinoma

The emerging targeted therapies have revolutionized the treatment of advanced clear cell renal cell carcinoma (ccRCC) over the past 15 years. Nevertheless, lack of personalized treatment limits the development of effective clinical guidelines and improvement of patient prognosis. In this study, large-scale genomic profiles from ccRCC cohorts were explored for integrative analysis. A credible method was developed to identify synthetic lethality (SL) pairs and a list of 72 candidate pairs was determined, which might be utilized to selectively eliminate tumors with genetic aberrations using SL partners of specific mutations. Further analysis identified BRD4 and PRKDC as novel medical targets for patients with BAP1 mutations. After mapping these target genes to the comprehensive drug datasets, two agents (BI-2536 and PI-103) were found to have considerable therapeutic potentials in the BAP1 mutant tumors. Overall, our findings provided insight into the overview of ccRCC mutation patterns and offered novel opportunities for improving individualized cancer treatment.

FXYD3 Expression Predicts Poor Prognosis in Renal Cell Carcinoma with Immunosuppressive Tumor Microenvironment

Simple Summary

FXYD3 belongs to the protein-coding gene family associated with Na+/K+-ATPase enzymes and chloride ion channels. Recently, the biological role of FXYD3 has been reported in multiple cancers. Nevertheless, the prognostic value of FXYD3 expression has been undiscovered in clear renal cell carcinoma (KIRC). In this study, we assessed the datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) dataset (GSE29609). We found the FXYD3 high KIRC patients had distinct clinical characteristics, including hypoxia and poor overall survival. Furthermore, the algorithms discovered that FXYD3 mRNA levels were associated with tumor purity, multiple types of the tumor infiltrating lymphocytes (TILs) and several genes related to T cell exhaustion. In conclusion, FXYD3 predicts a poor prognosis associated with hypoxia, pro-tumor TILs, and T cell exhaustion in KIRC.

Abstract

FXYD3 is a protein-coding gene, belonging to the FXYD protein family associated with Na+/K+-ATPase enzymes and chloride ion channels. Accumulating evidence suggests the biological role of FXYD3 in multiple cancers. However, the prognostic value of FXYD3 expression in clear renal cell carcinoma (KIRC) is unclear. Therefore, we evaluated the clinical data with tumor-infiltrating lymphocytes (TILs) and immunoinhibitory gene expression data using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) dataset (GSE29609). First, the FXYD3 high KIRC patients had distinct clinical characteristics, including age, sex, disease stage, histological grade, and hypoxia-related gene expressions. Next, FXYD3 gene expression was correlated with poor overall survival in both TCGA and GSE29609 cohorts. The ESTIMATE algorithm revealed that higher FXYD3 mRNA levels were associated with increased infiltration of immune cells and tumor purity. Moreover, the FXYD3 high KIRC tissue harbored increased TILs such as B cells, CD8+ T cells, and M1 macrophage, whereas NK cells and neutrophils were decreased. In addition, we showed FXYD3 was co-expressed with several immunoinhibitory genes related to T cell exhaustion such as LGALS9, CTLA4, BTLA, PDCD1, and LAG3. In conclusion, FXYD3 is an unfavorable prognostic biomarker associated with hypoxia, pro-tumor TILs, and T cell exhaustion.

Comprehensive Evaluation of the m6A Regulator Prognostic Risk Score in the Prediction of Immunotherapy Response in Clear Cell Renal Cell Carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) is known for its high drug resistance. The tumor-immune crosstalk mediated by the epigenetic regulation of N6-methyladenosine (m6A) modification has been demonstrated in recent studies. Therefore, m6A modification-mediated immune cell infiltration characteristics may be helpful to guide immunotherapy for ccRCC.

Methods

This study comprehensively analyzed m6A modifications using the clinical parameters, single-cell RNA sequencing data, and bulk RNA sequencing data from the TCGA-ccRC cohort and 13 external validation cohorts. A series of bioinformatic approaches were applied to construct an m6A regulator prognostic risk score (MRPRS) to predict survival and immunotherapy response in ccRCC patients. Immunological characteristics, enriched pathways, and mutation were evaluated in high- and low-MRPRS groups.

Results

The expressional alteration landscape of m6A regulators was profiled in ccRCC cell clusters and tissue. The 8 regulator genes with minimal lambda were integrated to build an MRPRS, and it was positively correlated with immunotherapeutic response in extent validation cohorts. The clinicopathological features and immune infiltration characteristics could be distinguished by the high- and low-MRPRS. Moreover, the MRPRS-mediated mutation pattern has an enhanced response to immune checkpoint blockade in the ccRCC and pan-cancer cohorts.

Conclusions

The proposed MRPRS is a promising biomarker to predict clinical outcomes and therapeutic responses in ccRCC patients.

Construction and validation of a prognostic model for kidney renal clear cell carcinoma based on podocyte-associated genes

Background

As the most common renal malignancy, kidney renal clear cell carcinoma (KIRC) has a high prevalence and death rate as well as a poor response to treatment. Developing an efficient prognostic model is essential for accurately predicting the outcome and therapeutic benefit of KIRC patients.

Methods

Gene expression profiles of podocyte‐associated genes (PAGs) were obtained from The Cancer Genome Atlas and GEO datasets. Cox regression and Lasso regression analyses were then used for filtering prognosis‐associated PAGs. Risk score (RS) was computed from these genetic characteristics. Kaplan–Meier analysis and receiver operating characteristic (ROC) curves were applied for ascertaining the prognostic value. Stratified analysis was used to sufficiently validate model performance. Concordance index was used to compare the predictive ability of different models. Immuno‐infiltration analysis and immunophenoscore were utilized for the prediction of patient reaction to immune checkpoint inhibitors (ICIs).

Results

WT1, ANLN, CUBN, OSGEP, and RHOA were significantly associated with KIRC prognosis. Prognostic analysis indicated that high‐RS patients have a significantly poorer outcome. Cox regression analysis demonstrated a potential for RS to be an independent prognostic factor. Pathway enrichment results indicated a lower enrichment of cancer‐related biological pathways in the low‐RS subgroup. Immune infiltration analysis and IPS demonstrated greater responsiveness to ICIs in the high RS group.

Conclusions

This podocyte‐associated KIRC prognostic model can effectively predict KIRC prognosis and immunotherapy response, which may help to provide clinicians with more effective treatment strategies.

Generation and Analysis of Pyroptosis-Based and Immune-Based Signatures for Kidney Renal Clear Cell Carcinoma Patients, and Cell Experiment

Background: Pyroptosis is a programmed cell death caused by inflammasomes, which is closely related to immune responses and tumor progression. The present study aimed to construct dual prognostic indices based on pyroptosis-associated and immune-associated genes and to investigate the impact of the biological signatures of these genes on Kidney Renal Clear Cell Carcinoma (KIRC).

Materials and Methods: All the KIRC samples from the Cancer Genome Atlas (TCGA) were randomly and equally divided into the training and testing datasets. Cox and Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis were used to screen crucial pyroptosis-associated genes (PAGs), and a pyroptosis-associated genes prognostic index (PAGsPI) was constructed. Immune-associated genes (IAGs) related to PAGs were identified, and then screened through Cox and LASSO regression analyses, and an immune-associated genes prognostic index (IAGsPI) was developed. These two prognostic indices were verified by using the testing and the Gene Expression Omnibus (GEO) datasets and an independent cohort. The patients’ response to immunotherapy was analyzed. A nomogram was constructed and calibrated. qRT-PCR was used to detect the expression of PAGs and IAGs in the tumor tissues and normal tissues. Functional experiment was carried out.

Results: 86 PAGs and 1,774 differentially expressed genes (DEGs) were obtained. After intersecting PAGs with DEGs, 22 differentially expressed PAGs (DEPAGs) were included in Cox and LASSO regression analyses, identifying 5 crucial PAGs. The PAGsPI was generated. Patients in the high-PAGsPI group had a poor prognosis. 82 differentially expressed IAGs (DEIAGs) were highly correlated with DEPAGs. 7 key IAGs were screened out, and an IAGsPI was generated. Patients in the high-IAGsPI group had a poor prognosis. PAGsPI and IAGsPI were verified to be robust and reliable. The results revealed patients in low-PAGsPI group and high-IAGsPI group may be more sensitive to immunotherapy. The calibrated nomogram was proved to be reliable. An independent cohort study also proved that PAGsPI and IAGsPI performed well in prognosis prediction. We found that the expression of AIM2 may affect proliferation of KIRC cells.

Conclusion: PAGsPI and IAGsPI could be regarded as potential biomarkers for predicting the prognosis of patients with KIRC.

Prognostic implication and immunotherapy response prediction of a costimulatory molecule signature in kidney renal clear cell carcinoma

Costimulatory molecules were considered to be promising and important targets in immunotherapy for various cancers. The present study was intended for generating a costimulatory molecule signature in kidney renal clear cell carcinoma (KIRC), to investigate prognostic implication, elucidate immune atlas, and predict immunotherapy response. All the KIRC samples from the TCGA were randomly divided into the training dataset and the testing dataset in the ratio of 7:3. The Cox and least absolute shrinkage and selection operator (LASSO) regression analysis were used to identify 7 key costimulatory molecules which were associated with prognosis and construct a costimulatory molecule prognostic index (CMsPI), which was validated by internal and external datasets and an independent cohort. Patients in the high-CMsPI group had high mortality. Mutation analysis showed the most common mutational genes and variant types. Immune analysis demonstrated CD8⁺ T cells were infiltrated at a high level in the high-CMsPI group. In combination of analysis of the immune relevant gene signature and the biomarkers of immunotherapy, we may infer there were more dysfunctional CD8⁺ T cells in the high-CMsPI group, and the patients of this group were less sensitive to immunotherapy. A nomogram was constructed, and the concordance index was 0.77 (95% CI: 0.74-0.79). Three key signaling pathways were identified to facilitate tumor progression. The CMsPI can be regarded as a promising biomarker for predicting individual prognosis and assessing immunotherapy response in KIRC patients.

Systematic Pan-Cancer Analysis of KIF23 and a Prediction Model Based on KIF23 in Clear Cell Renal Cell Carcinoma (ccRCC)

Purpose

This study aims to carry out a pan-cancer analysis of kinesin family member 23 (KIF23) and construct a predictive model for the prognosis of clear cell renal cell carcinoma (ccRCC) patients.

Methods

We evaluated the differential expression of KIF23 in pan-cancer by The Cancer Genome Atlas (TCGA) and Oncomine database. Then, the correlation between KIF23 with prognosis, clinical grade, stage, immune subtype, tumor mutation burden (TMB), microsatellite instability (MSI) and immune microenvironment was explored by TCGA, an integrated repository portal for tumor-immune system interactions (TISIDB) and cBioPortal. Subsequently, we screened out ferroptosis-related genes (FRGs) related to KIF23 and constructed a risk score model. Univariate Cox analysis was used to determine independent prognostic factors for ccRCC overall survival (OS), and a nomogram was established. Furthermore, gene set enrichment analysis (GSEA) was applied to study the biological functions and pathways of KIF23. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) was carried out to evaluate the expression of KIF23.

Results

KIF23 was highly expressed in most tumors. Further, KIF23 was strongly correlated with prognosis, clinical grade, stage, immune subtype, TMB, MSI and immune microenvironment in different tumors. We found that KIF23 was significantly associated with all aspects of ccRCC. Then, 8 FRGs were identified to construct a risk score model together with KIF23. And a prognostic nomogram prediction model of OS was established. After GSEA analysis, cell cycle, condensed chromosome and other physiological processes were screened out. Finally, qRT-PCR verified the high expression of KIF23 in ccRCC cell lines than normal kidney cell line.

Conclusion

KIF23 may act as a pivotal part in occurrence and progression of different tumors. In ccRCC, KIF23 can be a great prognostic biomarker, and the nomogram based on KIF23 may contribute to better treatment plans for ccRCC patients.

Key sunitinib-related biomarkers for renal cell carcinoma

Background

Renal cell carcinoma (RCC) contributed to 403,262 new cases worldwide in 2018, which constitutes 2.2% of global cancer, nevertheless, sunitinib, one of the major targeted therapeutic agent for RCC, often developed invalid due to resistance. Emerging evidences suggested sunitinib can impact tumor environment which has been proven to be a vital factor for tumor progression.

Methods

In the present study, we used ssGSEA to extract the immune infiltrating abundance of clear cell RCC (ccRCC) and normal control samples from GSE65615, TCGA, and GTEx; key immune cells were determined by Student's t‐test and univariable Cox analysis. Co‐expression network combined with differentially expressed analysis was then applied to derive key immune‐related genes for ccRCC, followed by the identification of hub genes using differential expression analysis. Subsequently, explorations and validations of the biological function and the immune‐related and sunitinib‐related characteristics were conducted in KEGG, TISIDB, Oncomine, ICGC, and GEO databases.

Results

We refined immature dendritic cells and central memory CD4 T cells which showed associations with sunitinib and ccRCC. Following, five hub genes (CRYBB1, RIMBP3C, CEACAM4, HAMP, and LYL1) were identified for their strong relationships with sunitinib and immune infiltration in ccRCC. Further validations in external data refined CRYBB1, CEACAM4, and HAMP which play a vital role in sunitinib resistance, immune infiltrations in ccRCC, and the development and progression of ccRCC. In conclusion, our findings could shed light on the resistance of sunitinib in ccRCC and provide novel biomarkers or drug targets for ccRCC.

GNRH1 and LTB4R might be novel immune-related prognostic biomarkers in clear cell renal cell carcinoma (ccRCC)

Background

Clear cell renal cell carcinoma (ccRCC) occupied most of renal cell carcinoma (RCC), which associated with poor prognosis. The purpose of this study is to screen novel and prognostic biomarkers for patients with ccRCC.

Methods and results

Firstly, Gene Expression Omnibus database was used to collect microarray data for weighted gene co-expression network construction. Gene modules related to prognosis which interest us most were picked out. 90 hub genes were further chosen in the key modules, two of which including gonadotropin releasing hormone 1 (GNRH1) and leukotriene B4 receptor (LTB4R) were screened and validated as immune-related prognostic biomarkers. Based on several public databases and ccRCC tissues collected by ourselves, we performed survival analysis, spearman correlation analysis, receiver operating characteristic (ROC) analysis, quantitative real-time PCR (qRT-PCR), western blotting, immunofluorescence (IF) and immunohistochemistry (IHC) staining for the validation of immune-related prognostic biomarkers. We further explored the relationship between immune-related prognostic biomarker expressions and immunocytes. Finally, gene set enrichment analysis (GSEA) demonstrated that the two immune-related prognostic biomarkers were significantly correlated with cell cycle.

Conclusions

Generally speaking, the present study has identified two novel prognostic biomarkers for patients with ccRCC, which showed strong correlation with prognosis of patients with ccRCC, could further be used as potential prognostic biomarkers in ccRCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02052-1.

Genetic Analysis Identifies the Role of HLF in Renal Cell Carcinoma

BACKGROUND/AIM

Circadian rhythm is an internal clock that regulates the cycles of many biological functions. Epidemiological studies have linked aberrant circadian rhythm to an increased susceptibility to cancer and poor patient prognosis. However, there remains a gap in our understanding of genetic variants related to the circadian pathway in renal cell carcinoma (RCC) progression.

PATIENTS AND METHODS

We examined the associations of 150 single nucleotide polymorphisms (SNPs) in 12 core circadian pathway genes with RCC risk and survival in 630 patients with RCC and controls.

RESULTS

After adjusting for multiple comparisons and performing multivariate analyses, we found that the HLF rs6504958 polymorphism was significantly associated with RCC risk (q<0.05), whereas, no SNP association was significant for survival. Furthermore, the rs6504958 G allele was associated with reduced expression of HLF; consequently, a lower HLF expression was correlated with more advanced RCC. Moreover, a meta-analysis of six kidney cancer gene expression datasets demonstrated that an elevated HLF expression was associated with a favorable prognosis in patients with RCC (hazard ratio=0.70, 95% confidence interval=0.65-0.76, p<0.001).

CONCLUSION

These findings implicate the potential protective role of HLF in the progression of RCC.

Prognostic Role of the Ubiquitin Proteasome System in Clear Cell Renal Cell Carcinoma: A Bioinformatic Perspective

Background: Clear cell renal cell carcinoma (ccRCC) is a common malignant tumor of the urinary system. The ubiquitin proteasome system (UPS) plays an important role in the generation, metabolism and survival of tumor. We are aimed to make a comprehensive exploration of the UPS's role in ccRCC with bioinformatic tools, which may contribute to the understanding of UPS in ccRCC, and give insight for further research. Methods: The UPS-related genes (UPSs) were collected by an integrative approach. The expression and clinical data were downloaded from TCGA database. R soft was used to perform the differentially expressed UPSs analysis, functional enrichment analysis. We also estimated prognostic value of each UPS with the help of GEPIA database. Two predicting models were constructed with the differentially expressed UPSs and prognosis-related genes, respectively. The correlations of risk score with clinical characteristics were also evaluated. Data of GSE29609 cohort were obtained from GEO database to validate the prognostic models. Results: We finally identified 91 differentially expressed UPSs, 48 prognosis related genes among them, and constructed a prognostic model with 18 UPSs successfully, the AUC was 0.760. With the help of GEPIA, we found 391 prognosis-related UPSs, accounting for 57.84% of all UPSs. Another prognostic model was constructed with 28 prognosis-related genes of them, and with a better AUC of 0.825. Additionally, our models can also stratify patients into high and low risk groups accurately in GSE29609 cohort. Similar prognostic values of our models were observed in the validated GSE29609 cohort. Conclusions: UPS is dysregulated in ccRCC. UPS related genes have significant prognostic value in ccRCC. Models constructed with UPSs are effective and applicable. An abnormal ubiquitin proteasome system should play an important role in ccRCC and be worthy of further study.

Kidney cancer PDOXs reveal patient-specific pro-malignant effects of antiangiogenics and its molecular traits

An open debate in antiangiogenic therapies is about their consequence on tumor invasiveness and metastasis, which is undoubtedly relevant for patients currently treated with antiangiogenics, such as renal cell carcinoma patients. To address, this we developed an extensive series of 27 patient biopsy‐derived orthotopic xenograft models (Ren‐PDOX) that represent inter‐patient heterogeneity. In specific tumors, antiangiogenics produced increased invasiveness and metastatic dissemination, while in others aggressiveness remained unchanged. Mechanistically, species‐discriminative RNA sequencing identified a tumor cell‐specific differential expression profile associated with tumor progression and aggressivity in TCGA RCC patients. Gene filtering using an invasion‐annotated patient series pinpointed two candidate genes, of which ALDH1A3 differentiated the pro‐invasive subtype of Ren‐PDOXs. Validation in an independent series of 15 antiangiogenic‐treated patients confirmed that pre‐treatment ALDH1A3 can significantly discriminate patients with pro‐aggressive response upon treatment. Overall, results confirm that effects of antiangiogenic drugs on tumor invasion and metastasis are heterogeneous and may profoundly affect the natural progression of tumors and promote malignancy. Furthermore, we identify a specific molecular biomarker that could be used to select patients that better benefit from treatment.

Identification of transforming growth factor beta induced (TGFBI) as an immune-related prognostic factor in clear cell renal cell carcinoma (ccRCC)

Clear cell renal cell carcinoma (ccRCC) is the most common subtype among kidney cancer, which has poor prognosis. The aim of this study was to screen out novel prognostic biomarkers and therapeutic targets for immunotherapy, and some novel molecule drugs for ccRCC treatment. Immune scores ranged from -1109.36 to 2920.81 and stromal scores ranged from -1530.11 to 1955.39 were firstly calculated by applying ESTIMATE algorithm. Then 17 DEGs associated with immune score and stromal score were further identified. 6 candidate hub genes were screened out by performing overall survival (OS) and disease-free survival analyses based on TCGA-KIRC data, one of which including TGFBI was further regarded as hub gene associated with prognosis by calculating the R2 (R2 = 0.011, P = 0.018) and AUC (AUC = 0.874). The prognostic value of TGFBI was validated by performing OS, CSS, and PFS analyses based on GSE29609 and E-MTAB-3267. CMap analysis suggested that 3 molecule drugs might be novel choice for ccRCC treatment. Further analysis demonstrated that CNVs of TGFBI was associated with OS of patients with ccRCC. TGFBI expression was also correlated with histologic grade, pathologic stage, and immune infiltration level, significantly. TGFBI was the most relevant gene with OS among the candidate hub genes, which might be novel DNA methylation biomarkers for ccRCC. In conclusion, our findings indicated that TGFBI was correlated with prognosis of patients with ccRCC, which might be novel prognostic biomarkers, and targets for immunotherapy in ccRCC. Three small molecule drugs were also identified, which showed strong potential for ccRCC treatment.

Immunotherapy in Renal Cell Carcinoma: The Future Is Now

Renal cell carcinoma is the third type of urologic cancer and has a poor prognosis with 30% of metastatic patients at diagnosis. The antiangiogenics and targeted immunotherapies led to treatment remodeling emphasizing the role of the tumour microenvironment. However, long-term responses are rare with a high rate of resistance. New strategies are emerging to improve the efficacy and the emerging drugs are under evaluation in ongoing trials. With the different treatment options, there is an urgent need to identify biomarkers in order to predict the efficacy of drugs and to better stratify patients. Owing to the limitations of programmed death-ligand 1 (PD-L1), the most studied immunohistochemistry biomarkers, and of the tumor mutational burden, the identification of more reliable markers is an unmet need. New technologies could help in this purpose.

OSkirc: a web tool for identifying prognostic biomarkers in kidney renal clear cell carcinoma

Aim: To develop a free and quick analysis online tool that allows users to easily investigate the prognostic potencies of interesting genes in kidney renal clear cell carcinoma (KIRC). Patients & methods: A total of 629 KIRC cases with gene expression profiling data and clinical follow-up information are collected from public Gene Expression Omnibus and The Cancer Genome Atlas databases. Results: One web application called Online consensus Survival analysis for KIRC (OSkirc) that can be used for exploring the prognostic implications of interesting genes in KIRC was constructed. By OSkirc, users could simply input the gene symbol to receive the Kaplan-Meier survival plot with hazard ratio and log-rank p-value. Conclusion: OSkirc is extremely valuable for basic and translational researchers to screen and validate the prognostic potencies of genes for KIRC, publicly accessible at http://bioinfo.henu.edu.cn/KIRC/KIRCList.jsp.

The pVHL172 isoform is not a tumor suppressor and up-regulates a subset of pro-tumorigenic genes including TGFB1 and MMP13

The von Hippel-Lindau (VHL) tumor suppressor gene is often deleted or mutated in ccRCC (clear cell renal cell carcinoma) producing a non-functional protein. The gene encodes two mRNA, and three protein isoforms (pVHL₂₁₃, pVHL₁₆₀ and pVHL₁₇₂). The pVHL protein is part of an E3 ligase complex involved in the ubiquitination and proteasomal degradation of different proteins, particularly hypoxia inducible factors (HIF) that drive the transcription of genes involved in the regulation of cell proliferation, angiogenesis or extracellular matrix remodelling. Other non-canonical (HIF-independent) pVHL functions have been described. A recent work reported the expression of the uncharacterized protein isoform pVHL₁₇₂ which is translated from the variant 2 by alternative splicing of the exon 2. This splice variant is sometimes enriched in the ccRCCs and the protein has been identified in the respective samples of ccRCCs and different renal cell lines. Functional studies on pVHL have only concerned the pVHL₂₁₃ and pVHL₁₆₀ isoforms, but no function was assigned to pVHL₁₇₂. Here we show that pVHL₁₇₂ stable expression in renal cancer cells does not regulate the level of HIF, exacerbates tumorigenicity when 786-O-pVHL₁₇₂ cells were xenografted in mice. The pVHL₁₇₂-induced tumors developed a sarcomatoid phenotype. Moreover, pVHL₁₇₂ expression was shown to up regulate a subset of pro-tumorigenic genes including TGFB1, MMP1 and MMP13. In summary we identified that pVHL₁₇₂ is not a tumor suppressor. Furthermore our findings suggest an antagonistic function of this pVHL isoform in the HIF-independent aggressiveness of renal tumors compared to pVHL₂₁₃.

Clear cell renal cell carcinoma: a comparative study of histological and chromosomal characteristics between primary tumors and their corresponding metastases

Clear cell renal cell carcinoma (ccRCC) has a poor prognosis with a 50% risk of metastases. Little is known about the phenotypic and molecular profiles of metastases regarding their corresponding primary tumors. This study aimed to screen phenotypic and genotypic differences between metastases and their corresponding primary tumors. We selected four cases with available frozen material. The histological, immunohistochemical (VEGFA, CD31, SMA, Ki67, p53, PAR-3), FISH (VHL gene), next-generation sequencing (VHL and c-MET genes), multiplex ligation-dependent probe amplification, and array-(comparative genomic hybridization) CGH analyses were realized. Metastases were nodal, hepatic (synchronous), adrenal, and pulmonary (metachronous). High-grade tumor cells were significantly more frequent in metastases (p = 0.019). Metastases and high-grade zones of primary tumors shared similar characteristics compared to low-grade zones: a lower microscopic vascular density (43.5 vs 382.5 vessels/mm²; p = 0.0027), a higher expression of VEGF (73 vs 10%, p = 0.045), Ki67 (37.6 vs 8.3%; p = 0.011), and p53 (54 vs 10.6%; p = 0.081), and a cytoplasmic and membranous PAR-3 staining. Metastases exhibited more chromosomal imbalances than primary tumors in total (18.75 ± 6.8; p = 0.044) with more genomic gains (13.5 ± 7; p = 0.013). The loss of chromosome 9 and gain of Xq were found in both primary tumors and metastases but gains of loci or chromosomes 2p, 3q, 5, 8q, 12, and 20 were only found in metastases. The VHL gene status was similar in each tumor couple. Although metastases and primary tumors share common histological features, this study highlights chromosomal differences specific to metastases which could be involved in ccRCC metastatic evolution.

Development and Validation of a Histological Method to Measure Microvessel Density in Whole-Slide Images of Cancer Tissue

Despite all efforts made to develop predictive biomarkers for antiangiogenic therapies, no unambiguous markers have been identified so far. This is due to among others the lack of standardized tests. This study presents an improved microvessel density quantification method in tumor tissue based on stereological principles and using whole-slide images. Vessels in tissue sections of different cancer types were stained for CD31 by an automated and validated immunohistochemical staining method. The stained slides were digitized with a digital slide scanner. Systematic, uniform, random sampling of the regions of interest on the whole-slide images was performed semi-automatically with the previously published applications AutoTag and AutoSnap. Subsequently, an unbiased counting grid was combined with the images generated with these scripts. Up to six independent observers counted microvessels in up to four cancer types: colorectal carcinoma, glioblastoma multiforme, ovarian carcinoma and renal cell carcinoma. At first, inter-observer variability was found to be unacceptable. However, after a series of consensus training sessions and interim statistical analysis, counting rules were modified and inter-observer concordance improved considerably. Every CD31-positive object was counted, with exclusion of suspected CD31-positive monocytes, macrophages and tumor cells. Furthermore, if interconnected, stained objects were considered a single vessel. Ten regions of interest were sufficient for accurate microvessel density measurements. Intra-observer and inter-observer variability were low (intraclass correlation coefficient > 0.7) if the observers were adequately trained.

Prognostic value of carbonic anhydrase IX immunohistochemical expression in renal cell carcinoma: a meta-analysis of the literature

Background

Carbonic anhydrase IX (CAIX) protein has been correlated with progression and survival in patients with renal cell carcinoma (RCC). The prognostic value of CAIX in RCC however, remains inconclusive according to published works. This study aimed to analyze CAIX as a biological marker to predict RCC patient prognosis.

Methods

A literature search of the PubMed and Web of Knowledge databases was performed to retrieve original studies from their inception to December of 2013. Fifteen studies, collectively including a total of 2611 patients with renal cell carcinoma, were carefully reviewed. Standard meta-analysis methods were applied to evaluate the prognostic impact of CAIX expression on patient prognosis. The hazard ratio (HR) and its 95% confidence interval (CI) were recorded for the relationship between CAIX expression and survival, and the data were analyzed using Review Manager 5.2 software and Stata software 11.0.

Results

In patients with RCC, low CAIX expression was associated with poor disease-specific survival (HR = 1.89, 95% CI: 1.20–2.98, P = 0.006), unfavorable progression-free survival (HR = 2.62, 95% CI: 1.14–6.05, P = 0.02) and worse overall survival (HR = 2.03, 95% CI: 1.28–3.21, P = 0.002). Furthermore, low CAIX expression was significantly associated with the presence of lymph node metastases (odds ratio (OR) = 0.31, 95% CI = 0.15–0.62, P = 0.0009) and distant metastases (OR = 0.66, 95% CI = 0.46–0.96, P = 0.03) and predicted a higher tumor grade (OR = 0.41, 95% CI = 0.31–0.54, P<0.00001).

Conclusions

Low CAIX expression most likely indicates poor prognosis in RCC patients. Moreover, low CAIX expression was significantly associated with unfavorable clinicopathological factors. To strengthen our findings, further well-designed prospective studies should be conducted to investigate the role of CAIX expression in RCC.

Overexpression of the polarity protein PAR-3 in clear cell renal cell carcinoma is associated with poor prognosis

The partition-defective 3 (PAR-3) protein is implicated in the development and maintenance of cell polarity and is associated with proteins that mediate the changes in cytoskeleton organization required for cell polarity establishment. In this work, we used two original primary cell lines (R-180 and R-305) derived from clear cell Renal Cell Carcinoma (ccRCC) surgical specimens of a patient with unfavorable clinical course (R-180 cells) and a patient with favorable prognosis (R-305 cells) to identify genetic and molecular features that may explain the survival difference of the two patients. The cytogenetic analysis of these cell lines revealed that the PARD3 gene was amplified only in the R-180 cell line that was derived from an aggressive ccRCC. PARD3 gene amplification was associated with overexpression of the encoded protein and altered cytoskeleton organization. Consistently, PARD3 knockdown in R-180 cells restored the cytoskeleton organization and reduced cell migration in comparison to non-transfected cells. Immunohistochemical analysis of ccRCC samples from a cohort of 96 patients with a follow-up of 6 years revealed that PAR-3 overexpression was correlated with poor survival. Our results suggest that PAR-3 has a role in the clinical aggressiveness of ccRCC, possibly by promoting cell migration.

Computed tomography perfusion imaging of renal cell carcinoma: systematic comparison with histopathological angiogenic and prognostic markers

PURPOSE

The aim of this study was to systematically analyze the correlation between computed tomography (CT) perfusion and histopathological angiogenic and prognostic markers in patients with renal cell carcinoma (RCC).

MATERIAL AND METHODS

Fifteen patients (12 men; mean age, 64.5 ± 9.4 years) with RCC underwent contrast-enhanced CT perfusion imaging (scan range, 10 cm; scan time, 40 seconds; dual-source 128-section CT) 1 day before surgery. The procedure for surgical specimen processing was modified to obtain an exact match with CT images. Microvessel density (MVD) was quantified by CD34 staining, and lymphatic vessel density (LVD) was stained with D2-40 antibodies. The CT perfusion values blood flow (BF), blood volume (BV), and flow extraction product (K(Trans)) were calculated using the maximum-slope and a delay-corrected modified Patlak approach and were correlated to MVD and LVD. The relationship between CT perfusion and the prognostic markers pT stage, Fuhrman grade, and tumor necrosis was evaluated.

RESULTS

Histopathology revealed varying high MVD but low or absent intratumoral LVD. The BF and BV of RCC, both including and excluding necrotic regions, showed significant correlations with MVD (r = 0.600-0.829, P < 0.05 each). Significant correlations between MVD and K(Trans) were found only in small tumor areas exhibiting no necrosis (r = 0.550, P < 0.05). No significant correlation was found between BF, BV, and K(Trans) with intratumoral LVD (P = 0.35-0.82). With higher pT stage and Fuhrman grade, BF, BV, and K(Trans) were lower, similar to the MVD, but without reaching statistical significance. Blood flow, BV, and K(Trans) were significantly higher in RCCs with less than 50% necrosis than in those with 50% or grater necrosis (P < 0.05 each).

CONCLUSION

Our study indicates that BF and BV from CT perfusion reflect blood vessels of RCC. Computed tompgraphic perfusion parameters differ significantly depending upon the degree of tumor necrosis.

Tumor-to-tumor metastasis from lung cancer: a clinicopathological postmortem study

This study examined 47 cases of lung cancer concomitant with other tumors and found eight cases (17 %) with nine foci of tumor-to-tumor metastasis, defined as metastasis of lung cancer into another tumor. Donor lung cancers were four adenocarcinomas, two squamous cell carcinomas, and two small cell carcinomas. Tumor-to-tumor metastasis was found in five of six renal cell carcinomas (83 %), one of eight thyroid papillary carcinomas (13 %), one of three adrenocortical adenomas (33 %), one of three pancreatic endocrine microadenomas (33 %), and another lung cancer (one of six cases of multiple lung cancers, 17 %). The higher recipient incidence in renal cell carcinoma was statistically significant compared with prostatic carcinoma (0/16, P < 0.001), colorectal carcinoma (0/7, P = 0.005), and gastric carcinoma (0/5, P = 0.015). Generalized metastases were found in 88 % of the tumor-to-tumor metastasis cases. The total clinical course of patients with tumor-to-tumor metastasis was shorter than that of the patients without tumor-to-tumor metastasis (mean, 5.4 versus 18.8 months; P = 0.046). Tumor-to-tumor metastasis sometimes mimicked undifferentiated recipient tumor cells. Immunostains for thyroid transcription factor 1 (TTF-1), Napsin A, cytokeratin 7 (CK7), and CK5/6 were useful to confirm tumor-to-tumor metastasis. However, TTF-1-, Napsin A-, and/or CK7-negative lung adenocarcinoma components metastasized to renal cell carcinoma in three cases, and recipient renal cell carcinomas were focally Napsin A+ (two cases) or CK7+ (two cases). Tumor-to-tumor metastasis can occur as a result of metastasis from lung cancer with more aggressive behavior. Tumor-to-tumor metastasis should be carefully distinguished from undifferentiated recipient tumor cells.