Gene expression analysis in clear cell renal cell carcinoma using gene set enrichment analysis for biostatistical management

Dendritic Cells or Macrophages? The Microenvironment of Human Clear Cell Renal Cell Carcinoma Imprints a Mosaic Myeloid Subtype Associated with Patient Survival

Since their initial description by Elie Metchnikoff, phagocytes have sparked interest in a variety of biologic disciplines. These important cells perform central functions in tissue repair and immune activation as well as tolerance. Myeloid cells can be immunoinhibitory, particularly in the tumor microenvironment, where their presence is generally associated with poor patient prognosis. These cells are highly adaptable and plastic, and can be modulated to perform desired functions such as antitumor activity, if key programming molecules can be identified. Human clear cell renal cell carcinoma (ccRCC) is considered immunogenic; yet checkpoint blockades that target T cell dysfunction have shown limited clinical efficacy, suggesting additional layers of immunoinhibition. We previously described "enriched-in-renal cell carcinoma" (erc) DCs that were often found in tight contact with dysfunctional T cells. Using transcriptional profiling and flow cytometry, we describe here that ercDCs represent a mosaic cell type within the macrophage continuum co-expressing M1 and M2 markers. The polarization state reflects tissue-specific signals that are characteristic of RCC and renal tissue homeostasis. ErcDCs are tissue-resident with increasing prevalence related to tumor grade. Accordingly, a high ercDC score predicted poor patient survival. Within the profile, therapeutic targets (VSIG4, NRP1, GPNMB) were identified with promise to improve immunotherapy.

Ceruloplasmin expression in renal cell carcinoma correlates with higher-grade and shortened survival

Aim: We aimed to explore ceruloplasmin (CP) expression in clear cell renal cell carcinoma (ccRCC). Materials & methods: CP was analyzed in biofluid samples of 63 ccRCC patients, divided into three grading groups, and immunohistochemically, in 308 ccRCC. Results: Significant differences of mean plasma and urine CP levels in different grading groups were found. CP immunoreactivity was significantly linked to high-grade disease. Log rank tests showed a significant shorter overall survival rate in CP-positive cases (all p < 0.05). Conclusion: CP protein levels in biofluid samples confirmed differential CP expressions, depending on nuclear grade in ccRCC as previously seen in RNA expression analysis. CP expression was linked to high-grade disease and reduced survival rate in RCC.

Stratification of clear cell renal cell carcinoma (ccRCC) genomes by gene-directed copy number alteration (CNA) analysis

Tumorigenic processes are understood to be driven by epi-/genetic and genomic alterations from single point mutations to chromosomal alterations such as insertions and deletions of nucleotides up to gains and losses of large chromosomal fragments including products of chromosomal rearrangements e.g. fusion genes and proteins. Overall comparisons of copy number alterations (CNAs) presented in 48 clear cell renal cell carcinoma (ccRCC) genomes resulted in ratios of gene losses versus gene gains between 26 ccRCC Fuhrman malignancy grades G1 (ratio 1.25) and 20 G3 (ratio 0.58). Gene losses and gains of 15762 CNA genes were mapped to 795 chromosomal cytoband loci including 280 KEGG pathways. CNAs were classified according to their contribution to Fuhrman tumour gradings G1 and G3. Gene gains and losses turned out to be highly structured processes in ccRCC genomes enabling the subclassification and stratification of ccRCC tumours in a genome-wide manner. CNAs of ccRCC seem to start with common tumour related gene losses flanked by CNAs specifying Fuhrman grade G1 losses and CNA gains favouring grade G3 tumours. The appearance of recurrent CNA signatures implies the presence of causal mechanisms most likely implicated in the pathogenesis and disease-outcome of ccRCC tumours distinguishing lower from higher malignant tumours. The diagnostic quality of initial 201 genes (108 genes supporting G1 and 93 genes G3 phenotypes) has been successfully validated on published Swiss data (GSE19949) leading to a restricted CNA gene set of 171 CNA genes of which 85 genes favour Fuhrman grade G1 and 86 genes Fuhrman grade G3. Regarding these gene sets overall survival decreased with the number of G3 related gene losses plus G3 related gene gains. CNA gene sets presented define an entry to a gene-directed and pathway-related functional understanding of ongoing copy number alterations within and between individual ccRCC tumours leading to CNA genes of prognostic and predictive value.

DNA methylation status defines clinicopathological parameters including survival for patients with clear cell renal cell carcinoma (ccRCC)

Epigenetic alterations in the methylome have been associated with tumor development and progression in renal cell carcinoma (RCC). In this study, 45 tumor samples, 12 tumor-free kidney cortex tissues, and 24 peripheral blood samples from patients with clear cell RCC (ccRCC) were analyzed by genome-wide promoter-directed methylation arrays and related to clinicopathological parameters. Unsupervised hierarchical clustering separated the tumors into two distinct methylation groups (clusters A and B), where cluster B had higher average methylation and increased number of hypermethylated CpG sites (CpGs). Furthermore, tumors in cluster B had, compared with cluster A, a larger tumor diameter (p = 0.033), a higher morphologic grade (p < 0.001), a higher tumor-node-metastasis (TNM) stage (p < 0.001), and a worse prognosis (p = 0.005). Higher TNM stage was correlated to an increase in average methylation level (p = 0.003) and number of hypermethylated CpGs (p = 0.003), whereas a number of hypomethylated CpGs were mainly unchanged. However, the predicted age of the tumors based on methylation profile did not correlate with TNM stage, morphological grade, or methylation cluster. Differently methylated (DM) genes (n = 840) in ccRCC samples compared with tumor-free kidney cortex samples were predominantly hypermethylated and a high proportion were identified as polycomb target genes. The DM genes were overrepresented by transcription factors, ligands, and receptors, indicating functional alterations of significance for ccRCC progression. To conclude, increased number of hypermethylated genes was associated with increased TNM stage of the tumors. DNA methylation classification of ccRCC tumor samples at diagnosis can serve as a clinically applicable prognostic marker in ccRCC.

Metastasis-Initiating Cells in Renal Cancer

Metastasis is a complex process that propagates cells from the primary or initial site of the cancer occurrence to distant parts of the body. Cancer cells break from the cancer site and circulate through the bloodstream or lymph vessels, allowing them to reach nearly all parts of the body. These circulating tumour cells (CTCs) contain specialized metastasis-initiating cells (MICs) that reside in the biological heterogeneous primary tumour. Researchers have hypothesized that metastasis of renal cell carcinoma is initiated by circulation of MICs in patients’ blood and bone marrow. Based on the cancer stem/progenitor cell concept of carcinogenesis, understanding the molecular phenotypes of metastasis-initiating cells (MICs) in renal cancer could play a vital role in developing strategies for therapeutic interventions in renal cancer. Existence of MICs among CTCs in renal carcinoma has not been proven in large scale. However, some studies have reported that specialized markers are found on the surface of circulating cells from the primary tumour. In mice, MICs have been isolated from CTCs using such markers, which have then been transplanted into xenograft model to show whether they give rise to metastasis in different organs. Considering these findings, in this review we have attempted to summarize the studies connected with MICs and their gene expression profiles that are responsible for metastasis in renal cancer.

Altered metabolic pathways in clear cell renal cell carcinoma: A meta-analysis and validation study focused on the deregulated genes and their associated networks

Clear cell renal cell carcinoma (ccRCC) is the predominant subtype of renal cell carcinoma (RCC). It is one of the most therapy-resistant carcinomas, responding very poorly or not at all to radiotherapy, hormonal therapy and chemotherapy. A more comprehensive understanding of the deregulated pathways in ccRCC can lead to the development of new therapies and prognostic markers. We performed a meta- analysis of 5 publicly available gene expression datasets and identified a list of co- deregulated genes, for which we performed extensive bioinformatic analysis coupled with experimental validation on the mRNA level. Gene ontology enrichment showed that many proteins are involved in response to hypoxia/oxygen levels and positive regulation of the VEGFR signaling pathway. KEGG analysis revealed that metabolic pathways are mostly altered in ccRCC. Similarly, Ingenuity Pathway Analysis showed that the antigen presentation, inositol metabolism, pentose phosphate, glycolysis/gluconeogenesis and fructose/mannose metabolism pathways are altered in the disease. Cellular growth, proliferation and carbohydrate metabolism, were among the top molecular and cellular functions of the co-deregulated genes. qRT-PCR validated the deregulated expression of several genes in Caki-2 and ACHN cell lines and in a cohort of ccRCC tissues. NNMT and NR3C1 increased expression was evident in ccRCC biopsies from patients using immunohistochemistry. ROC curves evaluated the diagnostic performance of the top deregulated genes in each dataset. We show that metabolic pathways are mostly deregulated in ccRCC and we highlight those being most responsible in its formation. We suggest that these genes are candidate predictive markers of the disease.

A study exploring critical pathways in clear cell renal cell carcinoma

Renal cell carcinoma (RCC) is the most lethal type of cancer in the urinary system and often presents as a metastatic disease. Furthermore, there are no effective treatments for the disease. Several studies based on gene expression profiling have been performed with the aim of gaining insights into the pathogenesis of RCC; however, few studies have investigated RCC at the pathway level to search for the possible pathways involved in clear cell RCC (CCRCC). In this study, gene set enrichment analysis (GSEA) was conducted on microarray datasets from CCRCC tissue. DAVID functional enrichment analysis was performed based on the dysregulated genes that were identified in a meta-analysis performed on the microarray datasets from CCRCC tissue. In GSEA, 17 down- and 12 upregulated pathways coexisted in six datasets. The majority of the upregulated pathways were associated with the immune system. In addition, 32 dysregulated pathways were obtained from DAVID functional enrichment analysis, based on the abnormal genes identified by meta-analysis. This study demonstrated that cross-GSEA is a useful method for exploring the critical pathways involved CCRCC; however, an individual dataset with a small sample may introduce bias. A cross-GSEA based on certain well-designed datasets may be required to further the progress made in this study, following the analysis of its results.

Key pathways and genes controlling the development and progression of clear cell renal cell carcinoma (ccRCC) based on gene set enrichment analysis

Background

Clear-cell renal cell carcinoma (ccRCC) is one of the most common types of kidney cancer in adults; however, its causes are not completely understood. The study was designed to filter the key pathways and genes associated with the occurrence or development of ccRCC, acquaint its pathogenesis at gene and pathway level, to provide more theory evidence and targeted therapy for ccRCC.

Methods

Gene set enrichment analysis (GSEA) and meta-analysis (Meta) were used to screen the critical pathways and genes which may affect the occurrence and progression of ccRCC on the transcription level. Corresponding pathways of significant genes were obtained with the online website DAVID (http://david.abcc.ncifcrf.gov/).

Results

Thirty seven consistent pathways and key genes in these pathways related to ccRCC were obtained with combined GSEA and meta-analysis. These pathways were mainly involved in metabolism, organismal systems, cellular processes and environmental information processing.

Conclusion

The gene pathways that we identified could provide insight concerning the development of ccRCC. Further studies are needed to determine the biological function for the positive genes.

Genomics and epigenomics of clear cell renal cell carcinoma: recent developments and potential applications

Majority of clear cell renal cell carcinomas (ccRCCs) are diagnosed in the advanced metastatic stage resulting in dramatic decrease of patient survival. Thereby, early detection and monitoring of the disease may improve prognosis and treatment results. Recent technological advances enable the identification of genetic events associated with ccRCC and reveal significant molecular heterogeneity of ccRCC tumors. This review summarizes recent findings in ccRCC genomics and epigenomics derived from chromosomal aberrations, DNA sequencing and methylation, mRNA, miRNA expression profiling experiments. We provide a molecular insight into ccRCC pathology and recapitulate possible clinical applications of genomic alterations as predictive and prognostic biomarkers.

Expression profiling of metastatic renal cell carcinoma using gene set enrichment analysis

OBJECTIVE

To identify complex changes in cell biology occurring during metastatic progression of renal cell carcinoma using a novel gene expression analysis algorithm.

METHODS

Whole genome expression profiling was carried out on 32 snap-frozen samples of clear-cell renal cell carcinoma metastases, 29 primary tumors (14 low grade, 15 high grade) and 14 samples of normal kidney tissue using oligonucleotide microarrays. These data were analyzed with the gene set enrichment analysis method, which is able to detect even small, but significant, expression changes in functionally connected genes that cannot be shown by gene-by-gene comparisons.

RESULTS

There were 95 gene sets (pathways) with significant upregulation in metastases compared with normal kidney tissue (P < 0.01), and 77 gene sets with significant downregulation, respectively. Low-grade and high-grade tumors showed deregulation of various pathways that have previously not been described in renal cell carcinoma. There were significant changes of genes involved in cell cycle control, apoptosis, cell motility, metabolism, cell adhesion and cytoskeleton. Some promising new potential therapy targets were identified in renal cell carcinoma metastases; for example, aurora-kinase A and flap structure-specific endonuclease 1.

CONCLUSION

Expression profiling of metastatic renal cell carcinoma using the gene set enrichment analysis pathway analysis method provides new and detailed insights in alterations occurring in renal cell carcinoma during malignant transformation and progression. These data can help to develop new and specifically targeted renal cell carcinoma therapies.

Full-Length Enrich c-DNA Libraries-Clear Cell-Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC), the most common subtype of RCC, is characterized by high metastasis potential and strong resistance to traditional therapies, resulting in a poor five-year survival rate of patients. Several therapies targeted to VEGF pathway for advanced RCC have been developed, however, it still needs to discover new therapeutic targets for treating RCC. Genome-wide gene expression analyses have been broadly used to identify unknown molecular mechanisms of cancer progression. Recently, we applied the oligo-capping method to construct the full-length cDNA libraries of ccRCC and adjacent normal kidney, and analyzed the gene expression profiles by high-throughput sequencing. This paper presents a review for recent findings on therapeutic potential of MYC pathway and nicotinamide N-methyltransferase for the treatment of RCC.