Comprehensive analysis of lower mitochondrial complex I expression is associated with cell metastasis of clear cell renal cell carcinoma

Renal Cell Carcinoma: Diagnosis Based on Metastatic Manifestations

Identification of Genomic Alterations Associated With Metastasis and Cancer Specific Survival in Clear Cell Renal Cell Carcinoma

Renal cell carcinoma (RCC) is the most common form of kidney cancer, caused by renal epithelial cells. RCC remains to be a challenging public health problem worldwide. Metastases that are resistant to radiotherapy and chemotherapy are the major cause of death from cancer. However, the underlying molecular mechanism regulating the metastasis of RCC is poorly known. Publicly available databases of RCC were obtained from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified using GEO2R analysis, whereas the Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed by Gene Set Enrichment Analysis (GSEA) and Metascape. Protein-protein interaction (PPI) network of DEGs was analyzed by STRING online database, and Cytoscape software was used for visualizing PPI network. Survival analysis of hub genes was conducted using GEPIA online database. The expression levels of hub genes were investigated from The Human Protein Atlas online database and GEPIA online database. Finally, the comparative toxicogenomics database (CTD; http://ctdbase.org) was used to identify hub genes associated with tumor or metastasis. We identified 229 DEGs comprising 135 downregulated genes and 94 upregulated genes. Functional analysis revealed that these DEGs were associates with cell recognition, regulation of immune, negative regulation of adaptive immune response, and other functions. And these DEGs mainly related to P53 signaling pathway, cytokine-cytokine receptor interaction, Natural killer cell mediated cytotoxicity, and other pathways are involved. Ten genes were identified as hub genes through module analyses in the PPI network. Finally, survival analysis of 10 hub genes was conducted, which showed that the MMP2 (matrix metallo peptidase 2), DCN, COL4A1, CASR (calcium sensing receptor), GPR4 (G protein-coupled receptor 4), UTS2 (urotensin 2), and LDLR (low density lipoprotein receptor) genes were significant for survival. In this study, the DEGs between RCC and metastatic RCC were analyzed, which assist us in systematically understanding the pathogeny underlying metastasis of RCC. The MMP2, DCN, COL4A1, CASR, GPR4, UTS2, and LDLR genes might be used as potential targets to improve diagnosis and immunotherapy biomarkers for RCC.

The aim of this study was to explore the key genes, microRNA (miRNA), and the pathogenesis of oral squamous cell carcinoma (OSCC) at the molecular level through the analysis of bioinformatics, which could provide a theoretical basis for the screening of drug targets. Data of OSCC were obtained from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified via GEO2R analysis. Next, protein-protein interaction (PPI) network of DEGs was constructed through Search Tool for the Retrieval of Interacting Gene and visualized via Cytoscape, whereas the hub genes were screened out with Cytoscape. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed by Database for Annotation, Visualization and Integrated Discovery. The miRNA, which might regulate hub genes, were screened out with TargetScan and GO and KEGG analysis of miRNA was performed by DNA Intelligent Analysis-miRPath. Survival analyses of DEGs were conducted via the Kaplan-Meier plotter. Finally, the relationships between gene products and tumors were analyzed by Comparative Toxicogenomics Database. A total of 121 differential genes were identified. One hundred thirty-five GO terms and 56 pathways were obtained, which were mainly related to PI3K-Akt signals pathway, FoxO signaling pathway, Wnt signaling pathway, cell cycle, p53 signaling pathway, cellular senescence, and other pathways; 10 genes were identified as hub genes through modules analyses in the PPI network. Finally, a survival analysis of 10 hub genes was conducted, which showed that the low expression of matrix metalloproteinase (MMP)1, MMP3, and C-X-C motif chemokine ligand (CXCL)1 and the high expression of CXCL9 and CXCL10 resulted in a significantly poor 5-year overall survival rate in patients with OSCC. In this study, the DEGs of OSCC was analyzed, which assists us in a systematic understanding of the pathogenicity underlying occurrence and development of OSCC. The MMP1, MMP3, CXCL1, CXCL9, and CXCL10 genes might be used as potential targets to improve diagnosis and as immunotherapy biomarkers for OSCC.

Impact of Recurrent Copy Number Alterations and Cancer Gene Mutations on the Predictive Accuracy of Prognostic Models in Clear Cell Renal Cell Carcinoma

Renal cell carcinoma (RCC) is a renal cortical tumor with high clinical incidence. The effect of glutathione peroxidases (GPXs) on RCC and the possible mechanism are still unclear. This study aims to explore the expression level of GPXs gene in RCC and its effect on the clinical prognosis of patients with RCC via bioinformatics analysis. The mRNA expressions of GPXs family genes were obtained from the public data of The Cancer Genome Atlas (TCGA) database. The Kruskal-Wails test was used to analyze the differences in mRNA expression of GPXs family genes between samples from patients with RCC and the normal population. UALAN databases were used to analyze the differences in protein expression of GPXs family genes between samples from patients with renal clear cell carcinoma and the normal population, and to evaluate the role of GPXs family genes in RCC. The Kaplan-Meier Plotter was used to analyze the correlation between different types of RCC and overall survival (OS), disease-free survival (DFS), disease-specific survival (DSS), and progression-free survival (PFS). Kaplan-Meier survival curve was drawn based on the GPX8 gene expression to study the relationship between GPX8 gene expression and prognosis of RCC patients. Based on the results of multivariate Cox regression analysis, a Nomogram scoring model for RCC prediction was established by introducing GPX8 gene. The mRNA expressions of GPX1 and GPX4 were higher in the sample of renal chromophobe cell carcinoma, renal clear cell carcinoma, and renal papillary cell carcinoma than those in the normal population (all P<0.01), and GPX7 and GPX8 were significantly over-expressed in patients with renal papillary cell carcinoma and renal clear cell carcinoma (all P<0.01). Compared with the normal group, the protein expressions of GPX1, GPX2, GPX7, and GPX8 were increased significantly in renal clear cell carcinoma (all P<0.01), while GPX3 and GPX4 expressions were decreased significantly (both P<0.01). The protein expressions of GPX1, GPX2, GPX7, and GPX8 were increased significantly in patients with renal clear cell carcinoma at different tumor grades (all P<0.01), while GPX3 and GPX4 expressions were decreased significantly (both P<0.01). Survival analysis showed that OS, DFS, DSS, and PFS were all decreased in patients with clear cell carcinoma compared with patients with papillary cell carcinoma and chromophobe cell carcinoma. According to the GPX8 level, patients were assigned into the low, medium, and high expression groups. Compared with the low GPX8 level group, the OS (P<0.01), DFS (P=0.03), DSS (P<0.01), and PFS (P=3.18×10-7) were significantly decreased in the high level group. Univariate Cox proportional regression analysis showed that the high level of GPX8 was associated with poor OS of 3 different types of renal cancer. Multifactorial analysis showed that GPX8 was an independent factor affecting the OS of patients with renal papillary cell carcinoma. Race and post tumor node metastasis (pTNM) typing were independent factors influencing the OS of patients with renal clear cell carcinoma. GPX8 and pTMN were independent factors influencing the OS of patients with renal chromophobe cell carcinoma. Based on these variables, the Nomogram risk models of 3 types of cell carcinoma were established, and the discrimination and calibration of the models were evaluated using the Consistency index (C-index) and calibration curves. The C-index of the risk model of renal papillary cell carcinoma was 0.62 (95% CI 0.51 to 1.00, P=0.03). The results of receiver operating characteristic (ROC) curve showed that the area under the curve (AUC) was 0.88. The C-index of the risk model of renal clear cell carcinoma was 0.72 (95% CI 0.52 to 1.00, P=0.03). The results of ROC curve showed that the AUC was 0.90. The C-index of the risk model of chromophobe cell carcinoma of kidney was 0.90 (95% CI 0.85 to 1.00, P<0.01). The results of ROC curve showed that the AUC was 0.59. GPXs family genes, especially GPX8, are potential markers for poor prognosis of RCC, and the occurrence and development of RCC can be predicted in clinical practice based on the expressions of GPXs family genes.

Diagnostic and Prognostic Molecular Markers in Renal Cell Carcinoma

miRNA Profiling for Clear Cell Renal Cell Carcinoma: Biomarker Discovery and Identification of Potential Controls and Consequences of miRNA Dysregulation

Possible prognostic utility of CD44 in renal cell carcinoma (RCC) prompted a comparison of its expression in primary and metastatic RCC. A total of 164 paraffin-embedded tissues of primary RCC and metastatic RCCs from 125 patients were immunostained with CD44 (standard form) antibody. It consisted of 86 primary RCCs (50 with subsequent metastasis [MET+] and 36 with no known metastasis [MET-]) during follow up and 78 metastatic RCCs (39 metastatic RCCs only and 39 with matched RCC primary from RCC MET + category). Immunoreactivity for CD44 was scored semiquantitatively as 0, 1, or 2 (0, <5%; 1, 5-50%; 2, > or =50%). Expression of CD44 was significantly higher in metastatic RCCs compared to primary RCCs (p = 0.036). CD44 immunoreactivity in the primary RCC (MET- and MET+) correlated with progression-free survival (p = 0.027). In metastatic RCCs, CD44 immunoreactivity also correlated with survival after detection of first metastasis (p = 0.011). In multivariate analysis, stage (p = 0.0001) and CD44 immunoreactivity (p = 0.03) in primary RCC were independent predictors of progression-free survival. Our study suggests that CD44 status in RCC provides useful prognostic information both in primary and metastatic RCCs and may have applicability in stratifying patients for therapeutic decisions.

Renal cell carcinoma: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up†.

Recent reports have shown altered expression of CD44 in renal cell carcinomas. However, to the authors' knowledge there are no data correlating CD44 expression in renal cell carcinomas with subsequent tumor progression or recurrence, nor is there information about the presence of particular splice variants of CD44 in these tumors. The authors examined the immunohistochemical expression of CD44S, the standard isoform of CD44, in renal cell carcinomas from 43 patients using 2 different monoclonal antibodies, Mab2137 and Hermes-3. In addition, they stained the renal cell carcinomas with antibodies to 2 splice variants of CD44, CD44v3 and CD44v6. Increased staining of renal clear cell carcinomas with Mab2137 was observed in high grade versus low grade tumors (45% vs. 0%, P = 0.013), whereas increased staining of clear cell carcinomas with Hermes-3 was noted in high stage versus low stage tumors (40% vs. 0%, P = 0.006). Few tumors stained with antibodies to CD44v3. Although increased expression of the splice variant CD44v6 was noted in papillary versus clear cell carcinomas, and increased staining of papillary carcinomas with Mab2137 and with antibodies to CD44v6 was noted for low stage versus high stage tumors, these differences did not achieve statistical significance. Clinical follow-up of at least 43 months was available for 26 patients. Six of these patients (five with clear cell carcinoma and one with papillary carcinoma) developed progressive or recurrent disease. The primary tumors from all 5 patients with progressive or recurrent clear cell carcinoma showed staining with Mab2137, whereas the primary tumors from only 2 of the 15 patients with at least 43 months follow-up and no evidence of progressive or recurrent clear cell carcinoma (13%) showed staining with Mab2137 (P = 0.001). Alternatively, 5 of 7 clear cell carcinomas (71%) that stained with Mab2137 were from patients who subsequently developed recurrence or progression, compared with 0 of 13 clear cell carcinomas that did not stain. Similar findings were not observed for papillary carcinomas, which appeared to be biologically distinct from clear cell carcinomas. CD44S staining with Mab2137 correlates with progression or recurrence of clear cell renal cell carcinoma. CD44S may, therefore, play a pathogenetic role in tumor progression.

Bone metastases is prevalent from renal cell carcinoma (RCC) with poor quality of life and prognosis. Our previous proteomics analysis identified dysregulated proteins in the bone-tropism RCC cells. In this study, we further examined the clinical implications of these proteins using multiple clinical cohorts. We identified 6 proteins with significant upregulation in RCC tumor tissue in comparing to tumor adjacent normal tissue (p<0.05). High expression of these 6 protein-encoding genes significantly correlates with a poor survival in the TCGA-KIRC (Kidney renal clear cell carcinoma) cohort (log-rank test p=2.7e-05), and they all individually had a reverse-correlation with the gene expression of VHL and PBRM1 (p<0.001), and positive-correlation with the expression of VEGFA (p<0.001). Further gene set variation analysis (GSVA) revealed positive correlation with Th17 cells enrichment and negative CD8 T cell infiltration in the RCC tumor microenvironment. High expression of these 6 genes in pretreatment tumors favors longer overall survival (OS)(p=0.027) in anti-PDL1 treated patients (n=428). We treated one humeral metastases RCC patient with the anti-PDL1 antibody drug atezolizumab after examined the elevated expression of the 6 proteins in his nephrectomy tumor tissue, the tumor at the fracture site shrunk remarkably after four courses of treatment. These results altogether suggest a clinical implication of the 6-protein signature in RCC bone metastasis prognosis and response to immune-checkpoint inhibitor treatment.

The distinction between central nervous system (CNS) metastases of clear cell renal cell carcinoma (RCC) and CNS haemangioblastoma still poses a challenge to the pathologist. Since both entities occur in von Hippel-Lindau disease, this aggravates the issue. The antibody renal cell carcinoma marker (RCC-ma) has been suggested to identify primary RCCs specifically, but its value for diagnosing metastases of RCC is controversial. The aim was to assess two distinct clones of the RCC-ma for their potential to: (i) identify primary RCCs and (ii) differentiate between CNS metastases of clear cell RCC and CNS haemangioblastomas. Using tissue microarrays, 77% (n = 363; PN-15) and 66% (n = 355; 66.4C2) of clear cell RCCs, and 93% (PN-15) and 74% (66.4C2) of papillary RCCs (n = 46) were immunopositive for RCC-ma, whereas none of the investigated chromophobe RCCs (n = 22) or any of the oncocytomas (n = 15) showed immunoreactivity. Importantly, 50.9% of CNS metastases of clear cell RCCs (n = 55) exhibited RCC-ma expression, whereas all CNS haemangioblastomas (71) were negative. Both RCC-ma clones, despite some variation in their sensitivity to detect clear cell and papillary RCCs, are of value in differentiating subtypes of primary RCC and are excellent markers for discriminating clear cell lesions in the brain.

Reporting Standards for Percutaneous Thermal Ablation of Renal Cell Carcinoma

14572 Background: RCC is often regarded as a radio-resistant tumor. However, brain metastases from RCC have been successful treated with SRS. Therefore, metastases to extra-cranial sites may be treated with similar success using stereotactic body radiation therapy (SBRT), where image-guidance allows for the delivery of precise high dose radiation in a few fractions. We report our experience with SRS/SBRT in the management of primary and metastatic RCC. Methods: The image-guided Novalis radiation therapy system was used. Thirty patients with brain metastases were treated with SRS (16–22 Gy in a single fraction). Five of these patients underwent resection of their metastatic lesions after SRS and their pathology were reviewed. Twenty patients with extra-cranial metastatic lesions (orbits, head and neck, lung, mediatinum, sternum, clavicle, scapula, humerus, rib, spine, abdomen) and 2 patients with biopsy proven primary RCC (not surgical candidates), were treated with SBRT (24–32 Gy in 3–4 fractions over 1–2 weeks). All patients were immobilized in body cast and image-guidance was used for all fractions. 4D-CT was utilized in the treatment planning to assess tumor motion. Results: Of the 30 patients who received SRS to brain metastases, 25 showed decreasing or stable lesion size. Five patients showed an increase in size and underwent resection. Their pathology revealed necrosis in &gt;99% of the specimen, with no viable RCC. Nineteen patients who received SBRT to extra-cranial metastases achieved symptom relief. One patient had local progression, yielding a local control rate of 95%. In the 2 patients with primary RCC, tumor size remained unchanged but their pain improved, and their renal function was unchanged post SBRT. There was no significant treatment related side-effect. Conclusions: Precise high dose radiation can cause significant tumor cell death in “radio-resistant” metastases from RCC. It also offers excellent local control and symptom palliation, without significant toxicity. Therefore, SBRT may represent a novel non-invasive, nephron-sparing option for the treatment of primary RCC as well as extra-cranial metastatic RCC. A prospective clinical trial using SBRT for primary and metastatic RCC is on-going. No significant financial relationships to disclose.