Renal cell carcinoma: Evolving and emerging subtypes

Gene mutation profiling and clinical significances in patients with renal cell carcinoma

OBJECTIVES

The pathological mechanisms of patients with Renal Cell Carcinoma (RCC) remain defined. This study aimed to evaluate relationships between the landscape of gene mutations and their clinical significance in RCC patients.

METHODS

Tissue and peripheral blood samples of 42 patients with RCC were collected and performed for the Next Generation Sequencing (NGS) with Geneseeq PrimeTM 425-gene panel probes. Their landscapes of gene mutation were analyzed. We also carried out an evaluation of Tumor-Node-Metastasis (TNM) staging, RENAL nephelometry score, surgery, and targeted drug treatment of patients. Then we compared the correlations of landscape in gene mutations and the prognosis.

RESULTS

The most common gene alternations, including BAP1, PBRM1, SETD2, CSF1R, NPM1, EGFR, POLE, RB1, and VHL genes, were identified in tissue and blood samples of 75% of patients. EGFR, POLE, and RB1 gene mutations frequently occurred in relapsed and metastatic patients. BAP1, CCND2, KRAS, PTPN11, ERBB2/3, JAK2, and POLE were presented in the patients with > 9 RENAL nephelometry score. Univariable analysis indicated that SETD2, BAP1, and PBRM1 genes were key factors for Disease-Free Survival (DFS). Multivariable analysis confirmed that mutated SETD1, NPM1, and CSF1R were critical factors for the Progression Free Survival (PFS) of RCC patients with target therapy.

CONCLUSIONS

Wild-type PBRM1 and mutated BAP1 in patients with RCC were strongly associated with the outcomes of the patient. The PFS of the patients with SETD2, NPM1, and CSF1R mutations were significantly shorter than those patients without variants.

Characteristics of Clear Cell Papillary Renal Cell Carcinoma (ccpRCC)

Renal cell carcinomas (RCCs) is a group of various malignant tumours of the renal cortex displaying distinct clinical, morphologic, and genetic features. Clear cell papillary renal cell carcinoma (ccpRCC), belonging to this group, shares morphologic features with both clear cell renal cell carcinoma (ccRCC) and papillary renal cell carcinoma (pRCC) and therefore, more strict diagnostic criteria should be developed to avoid misdiagnosis. Despite overlapping features, ccpRCC has also distinct clinical behaviour, histologic characteristics (morphologic and immunohistochemical), and genomic features. The concepts concerning this tumour are constantly developing since its biological potential and molecular basis remains to be fully unravelled. First reports indicated the presence of ccpRCC in end-stage renal disease, and they underlined the enriched development in this group of patients; however, currently, it is known that such tumours can also occur spontaneously in the normal kidney. Numerous studies have demonstrated that clinical outcomes and prognosis of ccpRCC patients is highly favourable. Till now, no convincing evidence of metastatic ccpRCC or death caused by the disease has been found. Therefore, it is of high importance to correctly differentiate ccpRCC from other subtypes of RCC with a much worse prognosis and to introduce appropriate management.

Differential sensitivity of renal carcinoma cells to doxorubicin and epigenetic therapeutics depends on the genetic background

Differential sensitivity to chemotherapeutics is a limitation in chemotherapy of kidney cancer patients. Role of genetic background in chemotherapy is not fully understood. Therefore, this study evaluated the influence of genetic/epigenetic background of renal cancer cells on the sensitivity to chemotherapeutics. Two renal cell carcinoma (RCC) cell lines, Caki-1 and 786-0, with different genetic makeup of p53 and VHL were treated with doxorubicin either alone or in combination with epigenetic therapeutics 5-aza-2-dc and TSA. Sensitivity of RCC cells to these drugs was evaluated by cell viability and cell cycle analysis and was further confirmed by analysis of selected genes expression. Cell viability data revealed that 786-0 cells were more sensitive than Caki-1 to doxorubicin. Combination of doxorubicin with 5-aza-2-dc or TSA was more effective to inhibit growth of Caki-1 cells but not the 786-0. Data of cell cycle analysis and expression of representative genes for tumor suppressor, cell cycle and survival, drug transporter and DNA repair further provided the molecular basis for differential sensitivity of Caki-1 and 786-0 cell lines to doxorubicin. Important findings of this study suggest that doxorubicin is more cytotoxic to primary renal cancer 786-0 cells with mutant VHL and p53 than the metastatic Caki-1 cells with wild-type VHL and p53, and this differential response was independent of p53 expression level. This study suggests that combination of doxorubicin with epigenetic therapeutics could potentially be beneficial in clinical treatment of renal cancer patients with wild-type VHL and p53 but not in patients with mutant VHL and p53.

DYSF expression in clear cell renal cell carcinoma: A retrospective study of 2 independent cohorts

OBJECTIVE

Renal cell carcinoma (RCC) is the most typical type of kidney cancer in adults. Hypercalcemia is a well known paraneoplastic syndrome associated with RCC and recent studies have reported that hypercalcemia is closely related to the poor prognosis of RCC patients. Clear cell RCC (ccRCC) is the most common and aggressive subtype of RCC. Although the histological classification of RCC is important for determination of appropriate treatment strategies, effective biomarkers for predicting prognosis of ccRCC have not yet been identified. Since calcium levels affect the prognosis of RCC patients, we evaluated whether the calcium-sensing genes on the plasma membrane, including those encoding calcium channels, CaSR, GPRC6a, and DYSF, could be used as biomarkers to predict the prognosis of ccRCC patients.

METHODS

Information from 537 patients from The Cancer Genome Atlas (TCGA; n = 446) and International Cancer Genome Consortium (ICGC; n = 91) was used in this study. Among these genes, DYSF was the only gene whose expression correlated with overall survival of both TGCA and ICGC patients.

RESULTS

Although DYSF gene expression was higher in ccRCC tissue than in normal kidney tissue, Kaplan-Meier curves showed that the survival rate of ccRCC patients with high DYSF expression was significantly higher than that of patients with low DYSF expression (TCGA, P < 0.0001; ICGC, P = 0.0011). We also validated the potential of DYSF as a prognostic biomarker for ccRCC by conducting a time-dependent area under the curve (AUC) analysis and 5-years receiver operating characteristic curve analysis. Finally, multivariate regression analysis revealed that the expression of DYSF is independent of other prognostic parameters (TCGA, P = 0.017; ICGC, P = 0.006).

CONCLUSIONS

These results suggested that DYSF may play a suppressive role in the progression of ccRCC and could act as a promising prognostic biomarker for predicting the survival of ccRCC patients.

Thyroid-Like Follicular Carcinoma of the Kidney With Extensive Sarcomatoid Differentiation: A Case Report and Review of the Literature

Thyroid-like follicular carcinoma of the kidney (TLFCK) is an extremely rare primary renal malignancy that typically has an indolent course and good prognosis. Histologically, this tumor mimics follicular carcinoma of the thyroid; however, typical thyroid markers are negative. There are fewer than 40 cases reported in the literature, and thus, the prognosis and course of disease is not well understood. Sarcomatoid differentiation has never been reported in a case of TLFCK. We present a case of a 48-year-old woman with an aggressive TLFCK with extensive sarcomatoid differentiation and metastatic disease at presentation. We performed targeted next-generation sequencing of both the thyroid-like component and the poorly differentiated sarcomatoid component using our solid tumor panel to evaluate for any disease-associated mutations and to better understand the molecular profile of these tumors.

The landscape of miRNA-related ceRNA networks for marking different renal cell carcinoma subtypes

We know that different types of cancers usually have different responses to the same treatment. Therefore, it is important to understand the similarities and differences across subtypes of cancers, so as to provide a basis for the individualized treatments. Until now, no comprehensive investigation on competing endogenous RNAs (ceRNAs) has been reported for the three main subtypes of renal cell carcinoma (RCC), so the regulation characteristics of ceRNAs in three subtypes are not well revealed. This paper firstly describes a comparative analysis of ceRNA-ceRNA interaction networks for all the three subtypes of RCC based on differential microRNAs (miRNAs). We comprehensively summarized all miRNA and messenger RNAdata of RCC from 126 matched tumor-normal tissues in The Cancer Genome Atlas, systematically analyzed a total of more than 80 000 ceRNA interactions and highlighted the common and specific properties among them, aiming to identify critical genes to classify them for providing supplementary help in the precise diagnosis of RCC. From three aspects, including common or specific ceRNAs, upregulated or downregulated and classifications across the three subtypes, we highlighted the common and specific properties for the three subtypes and also explored the classification of RCC by combining the specific ceRNAs with differential regulations. Moreover, for the most major subtype of clear cell renal cell carcinoma (KIRC), three critical genes were screened out from KIRC ceRNA network and further demonstrated to be the potential biomarkers of KIRC by performing biological experiments at the transcriptional level.

Choosing the right cell line for renal cell cancer research

Cell lines are still a tool of choice for many fields of biomedical research, including oncology. Although cancer is a very complex disease, many discoveries have been made using monocultures of established cell lines. Therefore, the proper use of in vitro models is crucial to enhance our understanding of cancer. Therapeutics against renal cell cancer (RCC) are also screened with the use of cell lines. Multiple RCC in vitro cultures are available, allowing in vivo heterogeneity in the laboratory, but at the same time, these can be a source of errors. In this review, we tried to sum up the data on the RCC cell lines used currently. An increasing amount of data on RCC shed new light on the molecular background of the disease; however, it revealed how much still needs to be done. As new types of RCC are being distinguished, novel cell lines and the re-exploration of old ones seems to be indispensable to create effective in vitro tools for drug screening and more.

Risk of Renal Cell Carcinoma Among Kidney Transplant Recipients in the United States

Renal cell carcinoma (RCC) is a common malignancy following kidney transplantation. We describe RCC risk and examine RCC risk factors among US kidney recipients (1987-2010). The Transplant Cancer Match Study links the US transplant registry with 15 cancer registries. Standardized incidence ratios (SIRs) were used to compare RCC risk (overall and for clear cell [ccRCC] and papillary subtypes) to the general population. Associations with risk factors were assessed using Cox models. We identified 683 RCCs among 116 208 kidney recipients. RCC risk was substantially elevated compared with the general population (SIR 5.68, 95% confidence interval 5.27-6.13), especially for papillary RCC (SIR 13.3 versus 3.98 for ccRCC). Among kidney recipients, RCC risk was significantly elevated for blacks compared to whites (hazard ratio [HR] 1.50) and lower in females than males (HR 0.56). RCC risk increased with prolonged dialysis preceding transplantation (p-trend < 0.0001). Risk was variably associated for RCC subtypes with some medical conditions that were indications for transplantation: ccRCC risk was reduced with polycystic kidney disease (HR 0.54), and papillary RCC was increased with hypertensive nephrosclerosis (HR 2.02) and vascular diseases (HR 1.86). In conclusion, kidney recipients experience substantially elevated risk of RCC, especially for papillary RCC, and multiple factors contribute to these cancers.

Adult Renal Cell Carcinoma: A Review of Established Entities from Morphology to Molecular Genetics

According to the current World Health Organization (WHO), renal cell carcinomas (RCCs) that primarily affect adults are classified into 8 major subtypes. Additional emerging entities in renal neoplasia have also been recently recognized and these are discussed in further detail by Mehra et al (Emerging Entities in Renal Neoplasia, Surgical Pathology Clinics, 2015, Volume 8, Issue 4). In most cases, the diagnosis of a RCC subtype can be based on morphologic criteria, but in some circumstances the use of ancillary studies can aid in the diagnosis. This review discusses the morphologic, genetic, and molecular findings in RCCs previously recognized by the WHO, and provides clues to distinction from each other and some of the newer subtypes of RCC. As prognosis and therapeutic options vary for the different subtypes of RCC, accurate pathologic distinction is critical for patient care.

Quantitative assessment of solid renal masses by contrast-enhanced ultrasound with time-intensity curves: how we do it

PURPOSE

To discuss the evaluation of the enhancement curve over time of the major renal cell carcinoma (RCC) subtypes, oncocytoma, and lipid-poor angiomyolipoma, to aid in the preoperative differentiation of these entities. Differentiation of these lesions is important, given the different prognoses of the subtypes, as well as the desire to avoid resecting benign lesions.

METHODS

We discuss findings from CT, MR, and US, but with a special emphasis on contrast-enhanced ultrasound (CEUS). CEUS technique is described, as well as time-intensity curve analysis.

RESULTS

Examples of each of the major RCC subtypes (clear cell, papillary, and chromophobe) are shown, as well as examples of oncocytoma and lipid-poor angiomyolipoma. For each lesion, the time-intensity curve of enhancement on CEUS is reviewed, and correlated with the enhancement curve over time reported for multiphase CT and MR.

CONCLUSIONS

Preoperative differentiation of the most common solid renal masses is important, and the time-intensity curves of these lesions show some distinguishing features that can aid in this differentiation. The use of CEUS is increasing, and as a modality it is especially well suited to the evaluation of the time-intensity curve.

RBP2 induces stem-like cancer cells by promoting EMT and is a prognostic marker for renal cell carcinoma

Renal cell carcinoma (RCC), one of the most common kidney cancers, has a poor prognosis. Epithelial to mesenchymal transition (EMT) is a hallmark of carcinoma invasion and metastasis. Several studies have examined the molecular regulation of EMT, but the relationship between histone demethylases and EMT is little understood. In this study, we investigated the role of retinoblastoma-binding protein-2 (RBP2), a histone demethylase that is highly expressed in RCC and is positively correlated with poor RCC prognosis in the regulation of EMT. We found that ectopic overexpression of RBP2 can induce cancer stem cell-like (CSC) phenotypes through EMT in RCC cells by converting them to a more mesenchymal phenotype. This results in increased resistance to apoptosis, which leads to enhanced tumor growth in xenograft models. Together, our data show that RBP2 is an epigenetic regulator that has an important role in the initiation of CSC phenotypes through EMT, leading to tumor progression. RBP2 is also a novel biomolecule for RCC diagnosis, and prognosis and may be a therapeutic target.

Multilevel Genomics-Based Taxonomy of Renal Cell Carcinoma

On the basis of multidimensional and comprehensive molecular characterization (including DNA methalylation and copy number, RNA, and protein expression), we classified 894 renal cell carcinomas (RCCs) of various histologic types into nine major genomic subtypes. Site of origin within the nephron was one major determinant in the classification, reflecting differences among clear cell, chromophobe, and papillary RCC. Widespread molecular changes associated with TFE3 gene fusion or chromatin modifier genes were present within a specific subtype and spanned multiple subtypes. Differences in patient survival and in alteration of specific pathways (including hypoxia, metabolism, MAP kinase, NRF2-ARE, Hippo, immune checkpoint, and PI3K/AKT/mTOR) could further distinguish the subtypes. Immune checkpoint markers and molecular signatures of T cell infiltrates were both highest in the subtype associated with aggressive clear cell RCC. Differences between the genomic subtypes suggest that therapeutic strategies could be tailored to each RCC disease subset.

In Vitro and In Vivo Evaluation of Targeted Sunitinib-Loaded Polymer Microbubbles Against Proliferation of Renal Cell Carcinoma

OBJECTIVES

The poor safety profile of sunitinib capsules has encouraged the identification of targeted drug delivery systems against renal cell carcinoma. This study aimed to explore the effect of sunitinib-loaded microbubbles along with ultrasound (US) treatment on proliferation and apoptosis of human GRC-1 granulocyte renal carcinoma cells in vitro and in vivo (xenograft tumor growth in nude mice).

METHODS

Liposomes containing sunitinib were prepared by using the transmembrane ammonium sulfate gradient method and then absorbed into polymer microbubbles to generate sunitinib-loaded microbubbles. Entrapment of sunitinib was verified by 25-25-[N-[(7-nitro-2-1,3-benzoxadiazol-4-yl)methyl]amino]-27-norcholesterol staining. GRC-1 cells were treated with microbubbles alone, liposomes alone, sunitinib alone, sunitinib-loaded microbubbles without and with US, and no treatment (control). Cell survival and apoptosis were assessed at 12, 24, and 48 hours after treatment. Xenograft tumors were induced by implantation of GRC-1 cells in nude mice. The animals with tumors were then randomly assigned to sunitinib alone, sunitinib-loaded microbubbles - US, sunitinib-loaded microbubbles + US, and no treatment (control; n = 10 per group). The tumor volumes were analyzed on the 7th, 15th, and 21st days.

RESULTS

The sunitinib entrapment efficiency in the liposomes was approximately 78%. The effective sunitinib concentration in each group was 0.1 μg/mL. The sunitinib-loaded microbubble + US group showed a lower in vitro cell survival rate (P < .001) compared with the other groups. Greater in vivo inhibition of xenograft tumor growth was also observed in the sunitinib-loaded microbubble + US group compared with the other groups.

CONCLUSIONS

Combined sunitinib-loaded microbubbles and US treatment significantly inhibits growth of renal carcinoma cells both in vitro and in vivo.

Clear cell papillary renal cell carcinoma: a review

The disease concept of clear cell (tubulo) papillary renal cell carcinoma (CCP-RCC) as a distinct subtype of renal cell carcinoma has been recently established. First described in the setting of end stage renal disease, this tumor type is more frequently recognized and encountered in a sporadic setting. In this article, we provide an overview of the recent understanding of this tumor. Macroscopically, tumors are well circumscribed with well-developed tumor capsule. Histologically, the tumor cells are cuboidal to low columnar cell with clear cytoplasm and papillary and tubulo-papillary configuration. Immunohistochemically, tumor cells generally show diffuse expression for cytokeratin 7, CA9 (cup-shaped pattern), HIF-1, GLUT-1 and high molecular weight cytokeratin, but negative for AMACR, RCC Ma and TFE3. CD10 is negative or focally positive in most tumors. Genetically, this tumor has no characteristics of clear cell RCC or papillary RCC. Prognostically, patients with CCP-RCC behave in an indolent fashion in all previously reported cases. In conclusion, although this tumor has been integrated into recent International Society of Urologic Pathology Classification of renal neoplasia, both aspects of disease concept and clinical behavior are yet to be fully elucidated. Further publications of large cohorts of patients will truly help understand the biologic potential and the molecular underpinnings of this tumor type.

How to get the most from microarray data: advice from reverse genomics

BACKGROUND

Whole-genome profiling of gene expression is a powerful tool for identifying cancer-associated genes. Genes differentially expressed between normal and tumorous tissues are usually considered to be cancer associated. We recently demonstrated that the analysis of interindividual variation in gene expression can be useful for identifying cancer associated genes. The goal of this study was to identify the best microarray data-derived predictor of known cancer associated genes.

RESULTS

We found that the traditional approach of identifying cancer genes--identifying differentially expressed genes--is not very efficient. The analysis of interindividual variation of gene expression in tumor samples identifies cancer-associated genes more effectively. The results were consistent across 4 major types of cancer: breast, colorectal, lung, and prostate. We used recently reported cancer-associated genes (2011-2012) for validation and found that novel cancer-associated genes can be best identified by elevated variance of the gene expression in tumor samples.

CONCLUSIONS

The observation that the high interindividual variation of gene expression in tumor tissues is the best predictor of cancer-associated genes is likely a result of tumor heterogeneity on gene level. Computer simulation demonstrates that in the case of heterogeneity, an assessment of variance in tumors provides a better identification of cancer genes than does the comparison of the expression in normal and tumor tissues. Our results thus challenge the current paradigm that comparing the mean expression between normal and tumorous tissues is the best approach to identifying cancer-associated genes; we found that the high interindividual variation in expression is a better approach, and that using variation would improve our chances of identifying cancer-associated genes.