Molecular Portrait of Clear Cell Renal Cell Carcinoma: An Integrative Analysis of Gene Expression and Genomic Copy Number Profiling

Renal cell carcinoma (RCC) incidence accounts for about 3 to 10 cases per 100,000 individuals with a predilection for adult males over 60 year old (1.6:1 male/female ratio) (Chow, 2010; Nese, 2009). In Europe, about 60,000 individuals are affected by RCC every year, with a mortality rate of about 18,000 subjects and an incidence rate for all stages steadily rising over the last three decades. Although inherited forms occur in a number of familial cancer syndromes, as the well-known von Hippel-Lindau (VHL) syndrome, RCC is commonly sporadic (Cohen & McGovern, 2005; Kaelin, 2007) and, as recently highlighted by the National Cancer Institute (NCI), influenced by the interplay between exposure to environmental risk factors and genetic susceptibility of exposed individuals (Chow et al., 2010). Being poorly symptomatic in early phases, many cases become clinically detectable only when already advanced and, as such, therapy-resistant (Motzer, 2011). Based on histology, RCC can be classified into several subtypes, i.e., clear cell (80% of cases), papillary (10%), chromophobe (5%) and oncocytoma (5%), each one characterized by specific histo- pathological features, malignant potential and clinical outcome (Cohen & McGovern, 2005). Patient stratification is normally achieved using prognostic algorithms and nomograms based on multiple clinico-pathological factors such as TNM stage, Fuhrman nuclear grade, tumor size, performance status, necrosis and other hematological indices (Flanigan et al., 2011), although the most efficient predictors of survival and recurrence are based on nuclear grade alone (Nese et al., 2009). As recently reviewed by Brannon et al. (Brannon & Rathmell, 2010), a finer RCC subtype classification could be obtained exploiting the vast amount of genomic and transcriptional data that have been presented in numerous studies. For instance, several authors proposed a molecular classification of RCC based on differential gene expression profiles, with any subtype characterized by the activation of distinct gene sets (Brannon, 2010; Furge, 2004; Skubitz, 2006; Su\u308ltmann, 2005; Zhang, 2008), while others identified RCC-specific biomarkers (e.g. CA9, ki67, VEGF proteins, phosphorylated AKT, PTEN, HIF-1). Lately, it has been reported that microRNAs, a small class of non coding RNA molecules, could contribute to RCC development at different levels and may represent a new group of potential tumor biomarkers (Redova et al., 2011). Despite the numerous efforts in dissecting the molecular features of RCC through functional genomics, not a single transcriptional signature or biomarker has gained approval for clinical application yet (Arsanious, 2009; Eichelberg, 2009; Lam, 2007; Yin-Goen, 2006), so that the identification of novel molecular markers to improve early diagnosis and prognostic prediction and of candidate targets to develop new therapeutic approaches remains of primary importance for this pathology

A computational procedure to identify significant overlap of differentially expressed and genomic imbalanced regions in cancer datasets†

The integration of high-throughput genomic data represents an opportunity for deciphering the interplay between structural and functional organization of genomes and for discovering novel biomarkers. However, the development of integrative approaches to complement gene expression (GE) data with other types of gene information, such as copy number (CN) and chromosomal localization, still represents a computational challenge in the genomic arena. This work presents a computational procedure that directly integrates CN and GE profiles at genome-wide level. When applied to DNA/RNA paired data, this approach leads to the identification of Significant Overlaps of Differentially Expressed and Genomic Imbalanced Regions (SODEGIR). This goal is accomplished in three steps. The first step extends to CN a method for detecting regional imbalances in GE. The second part provides the integration of CN and GE data and identifies chromosomal regions with concordantly altered genomic and transcriptional status in a tumor sample. The last step elevates the single-sample analysis to an entire dataset of tumor specimens. When applied to study chromosomal aberrations in a collection of astrocytoma and renal carcinoma samples, the procedure proved to be effective in identifying discrete chromosomal regions of coordinated CN alterations and changes in transcriptional levels

Characterization and identification of hidden rare variants in the human genome

BackgroundBy examining the genotype calls generated by the 1000 Genomes Project we discovered that the human reference genome GRCh37 contains almost 20,000 loci in which the reference allele has never been observed in healthy individuals and around 70,000 loci in which it has been observed only in the heterozygous state.ResultsWe show that a large fraction of this rare reference allele (RRA) loci belongs to coding, functional and regulatory elements of the genome and could be linked to rare Mendelian disorders as well as cancer. We also demonstrate that classical germline and somatic variant calling tools are not capable to recognize the rare allele when present in these loci. To overcome such limitations, we developed a novel tool, named RAREVATOR, that is able to identify and call the rare allele in these genomic positions. By using a small cancer dataset we compared our tool with two state-of-the-art callers and we found that RAREVATOR identified more than 1,500 germline and 22 somatic RRA variants missed by the two methods and which belong to significantly mutated pathways.ConclusionsThese results show that, to date, the investigation of around 100,000 loci of the human genome has been missed by re-sequencing experiments based on the GRCh37 assembly and that our tool can fill the gap left by other methods. Moreover, the investigation of the latest version of the human reference genome, GRCh38, showed that although the GRC corrected almost all insertions and a small part of SNVs and deletions, a large number of functionally relevant RRAs still remain unchanged. For this reason, also future resequencing experiments, based on GRCh38, will benefit from RAREVATOR analysis results. RAREVATOR is freely available at http://sourceforge.net/projects/rarevator

Genome-wide screening of copy number alterations and LOH events in renal cell carcinomas and integration with gene expression profile

<p>Abstract</p> <p>Background</p> <p>Clear cell renal carcinoma (RCC) is the most common and invasive adult renal cancer. For the purpose of identifying RCC biomarkers, we investigated chromosomal regions and individual genes modulated in RCC pathology. We applied the dual strategy of assessing and integrating genomic and transcriptomic data, today considered the most effective approach for understanding genetic mechanisms of cancer and the most sensitive for identifying cancer-related genes.</p> <p>Results</p> <p>We performed the first integrated analysis of DNA and RNA profiles of RCC samples using Affymetrix technology. Using 100K SNP mapping arrays, we assembled a genome-wide map of DNA copy number alterations and LOH areas. We thus confirmed the typical genetic signature of RCC but also identified other amplified regions (e.g. on chr. 4, 11, 12), deleted regions (chr. 1, 9, 22) and LOH areas (chr. 1, 2, 9, 13). Simultaneously, using HG-U133 Plus 2.0 arrays, we identified differentially expressed genes (DEGs) in tumor vs. normal samples. Combining genomic and transcriptomic data, we identified 71 DEGs in aberrant chromosomal regions and observed, in amplified regions, a predominance of up-regulated genes (27 of 37 DEGs) and a trend to clustering. Functional annotation of these genes revealed some already implicated in RCC pathology and other cancers, as well as others that may be novel tumor biomarkers.</p> <p>Conclusion</p> <p>By combining genomic and transcriptomic profiles from a collection of RCC samples, we identified specific genomic regions with concordant alterations in DNA and RNA profiles and focused on regions with increased DNA copy number. Since the transcriptional modulation of up-regulated genes in amplified regions may be attributed to the genomic alterations characteristic of RCC, these genes may encode novel RCC biomarkers actively involved in tumor initiation and progression and useful in clinical applications.</p

Severe Heterotopic Ossification in the Skeletal Muscle and Endothelial Cells Recruitment to Chondrogenesis Are Enhanced by Monocyte/Macrophage Depletion

Altered macrophage infiltration upon tissue damage results in inadequate healing due to inappropriate remodeling and stem cell recruitment and differentiation. We investigated in vivo whether cells of endothelial origin phenotypically change upon heterotopic ossification induction and whether infiltration of innate immunity cells influences their commitment and alters the ectopic bone formation. Liposome-encapsulated clodronate was used to assess macrophage impact on endothelial cells in the skeletal muscle upon acute damage in the ECs specific lineage-tracing Cdh5CreER(T2):R26REYFP/dtTomato transgenic mice. Macrophage depletion in the injured skeletal muscle partially shifts the fate of ECs toward endochondral differentiation. Upon ectopic stimulation of BMP signaling, monocyte depletion leads to an enhanced contribution of ECs chondrogenesis and to ectopic bone formation, with increased bone volume and density, that is reversed by ACVR1/SMAD pathway inhibitor dipyridamole. This suggests that macrophages contribute to preserve endothelial fate and to limit the bone lesion in a BMP/injury-induced mouse model of heterotopic ossification. Therefore, alterations of the macrophage-endothelial axis may represent a novel target for molecular intervention in heterotopic ossification

Glioma extracellular vesicles for precision medicine: prognostic and theragnostic application

EV produced by tumour cells carry a diverse population of proteins, lipids, DNA, and RNA molecules throughout the body and appear to play an important role in the overall development of the disease state, according to growing data. Gliomas account for a sizable fraction of all primary brain tumours and the vast majority of brain malignancies. Glioblastoma multiforme (GBM) is a kind of grade IV glioma that has a very dismal prognosis despite advancements in diagnostic methods and therapeutic options. The authors discuss advances in understanding the function of extracellular vesicles (EVs), in overall glioma growth, as well as how recent research is uncovering the utility of EVs in glioma diagnostics, prognostic and therapeutics approaches

Biological and prognostic impact of apobec-induced mutations in the spectrum of plasma cell dyscrasias

In multiple myeloma (MM), whole exome sequencing (WES) studies have revealed four mutational signatures: two associated with aberrant activities of APOBEC cytidine deaminases (Signatures #2 and #13) and two clock-like signatures associated with "cancer age" (Signatures #1 and #5). Mutational signatures have not been investigated systematically in larger series, nor in other primary plasma cell dyscrasias such as monoclonal gammopathy of unknown significance (MGUS) or primary plasma cell leukemia (pPCL). Finally, while APOBEC activity has been correlated to increased mutational burden and poor-prognosis MAF/MAFB translocations in MM at diagnosis, this has never been confirmed in multivariate analysis in an independent series. To answer these questions, we mined 1151 MM samples from public WES datasets, including samples from the IA9 public release of the CoMMpass trial. The CoMMpass data were generated as part of the Multiple Myeloma Research Foundation Personalized Medicine Initiatives. We also analyzed 6 MGUS/Smoldering MM as well as 5 previously published pPCLs. Extraction of mutational signatures was performed using the NNMF algorithm as previously described (Alexandrov et al. Nature 2013). NNMF in the whole cohort extracted the known 4 signatures pertaining to distinct mutational processes: the two clock-like processes (signatures #1 and #5) and aberrant APOBEC deaminase activity (signatures #2 and #13). While the clock-like processes were more prominent in the cohort as a whole (median 70%, range 0-100%), the APOBEC showed a heterogeneous contribution, more visible in samples with the highest mutation burden. In fact, the absolute and relative contribution of APOBEC activity to the mutational repertoire correlated with the overall number of mutations (r=0.71, p= < 0.0001). As previously described, APOBEC contribution was significantly enriched among MM patients with t(14;16) and with t(14;20) (p<0.001), but the association between relative APOBEC contribution and mutational load remained significant across all cytogenetic subgroups with the exception of t(11;14). In the MGUS/SMM series, APOBEC contribution was generally low. Conversely, APOBEC activity was preponderant in three out of five pPCL samples, all of them characterized by the t(14;16)( IGH / MAF); in the remaining two pPCL the absolute number of APOBEC mutations was similar to MM. Overall, the APOBEC contribution was characterized by a progressive increment from MGUS/SMM to MM and pPCL. We next went on to investigate the prognostic impact of APOBEC signatures at diagnosis. Patients with APOBEC contribution in the 4th quartile had shorter PFS (2-y PFS 47% vs 66%, p<0.0001) and OS (2-y OS 70% vs 85%, p=0.0033) than patients in quartiles 1-3 (Figure 1a-b). This was independent from the association of APOBEC activity with MAF translocations and higher mutational burden, as shown by multivariate analysis with Cox regression (Figure 1c-d). ISS stage III was the only other variable that retained its independent prognostic value for both PFS and OS. We therefore combined both variables and found that co-occurrence of ISS III and APOBEC 4th quartile identifies a fraction of high-risk patients with 2-y OS of 53.8% (95% CI 36.6%-79%), while their simultaneous absence identifies long term survivors with 2-y OS of 93.3% (95% CI 89.6-97.2%). In this study, we provided a global overview on the contribution of mutational processes in the largest whole exome series of plasma cell dyscrasias investigated to date by NNMF. We propose that cases with high APOBEC activity may represent a novel prognostic subgroup that is transversal to conventional cytogenetic subgroups, advocating for closer integration of next-generation sequencing studies and clinical annotation to confirm this finding in independent series

Renal cell carcinoma primary cultures maintain genomic and phenotypic profile of parental tumor tissues

<p>Abstract</p> <p>Background</p> <p>Clear cell renal cell carcinoma (ccRCC) is characterized by recurrent copy number alterations (CNAs) and loss of heterozygosity (LOH), which may have potential diagnostic and prognostic applications. Here, we explored whether ccRCC primary cultures, established from surgical tumor specimens, maintain the DNA profile of parental tumor tissues allowing a more confident CNAs and LOH discrimination with respect to the original tissues.</p> <p>Methods</p> <p>We established a collection of 9 phenotypically well-characterized ccRCC primary cell cultures. Using the Affymetrix SNP array technology, we performed the genome-wide copy number (CN) profiling of both cultures and corresponding tumor tissues. Global concordance for each culture/tissue pair was assayed evaluating the correlations between whole-genome CN profiles and SNP allelic calls. CN analysis was performed using the two CNAG v3.0 and Partek software, and comparing results returned by two different algorithms (Hidden Markov Model and Genomic Segmentation).</p> <p>Results</p> <p>A very good overlap between the CNAs of each culture and corresponding tissue was observed. The finding, reinforced by high whole-genome CN correlations and SNP call concordances, provided evidence that each culture was derived from its corresponding tissue and maintained the genomic alterations of parental tumor. In addition, primary culture DNA profile remained stable for at least 3 weeks, till to third passage. These cultures showed a greater cell homogeneity and enrichment in tumor component than original tissues, thus enabling a better discrimination of CNAs and LOH. Especially for hemizygous deletions, primary cultures presented more evident CN losses, typically accompanied by LOH; differently, in original tissues the intensity of these deletions was weaken by normal cell contamination and LOH calls were missed.</p> <p>Conclusions</p> <p>ccRCC primary cultures are a reliable <it>in vitro </it>model, well-reproducing original tumor genetics and phenotype, potentially useful for future functional approaches aimed to study genes or pathways involved in ccRCC etiopathogenesis and to identify novel clinical markers or therapeutic targets. Moreover, SNP array technology proved to be a powerful tool to better define the cell composition and homogeneity of RCC primary cultures.</p

miRNome and Proteome Profiling of Small Extracellular Vesicles Secreted by Human Glioblastoma Cell Lines and Primary Cancer Stem Cells

Glioblastoma (GBM) is the most common and aggressive brain tumor in adults. Despite available therapeutic interventions, it is very difficult to treat, and a cure is not yet available. The intra-tumoral GBM heterogeneity is a crucial factor contributing to poor clinical outcomes. GBM derives from a small heterogeneous population of cancer stem cells (CSCs). In cancer tissue, CSCs are concentrated within the so-called niches, where they progress from a slowly proliferating phase. CSCs, as most tumor cells, release extracellular vesicles (EVs) into the surrounding microenvironment. To explore the role of EVs in CSCs and GBM tumor cells, we investigated the miRNA and protein content of the small EVs (sEVs) secreted by two GBM-established cell lines and by GBM primary CSCs using omics analysis. Our data indicate that GBM-sEVs are selectively enriched for miRNAs that are known to display tumor suppressor activity, while their protein cargo is enriched for oncoproteins and tumor-associated proteins. Conversely, among the most up-regulated miRNAs in CSC-sEVs, we also found pro-tumor miRNAs and proteins related to stemness, cell proliferation, and apoptosis. Collectively, our findings support the hypothesis that sEVs selectively incorporate different miRNAs and proteins belonging both to fundamental processes (e.g., cell proliferation, cell death, stemness) as well as to more specialized ones (e.g., EMT, membrane docking, cell junction organization, ncRNA processing)