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

BACKGROUND: 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. METHODS: 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). RESULTS: 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. CONCLUSIONS: ccRCC primary cultures are a reliable in vitro 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.

Integrative Analysis of miRNA and inflammatory gene expression after acute particulate matter exposure.

MicroRNAs (miRNAs) are environmentally sensitive inhibitors of gene expression that may mediate the effects of metal-rich particulate matter (PM) and toxic metals on human individuals. Previous environmental miRNA studies have investigated a limited number of candidate miRNAs and have not yet evaluated the functional effects on gene expression. In this study, we wanted to identify PM-sensitive miRNAs using microarray profiling on matched baseline and postexposure RNA from foundry workers with well-characterized exposure to metal-rich PM and to characterize miRNA relations with expression of candidate inflammatory genes. We applied microarray analysis of 847 human miRNAs and real-time PCR analysis of 18 candidate inflammatory genes on matched blood samples collected from foundry workers at baseline and after 3 days of work (postexposure). We identified differentially expressed miRNAs (fold change [FC] > 2 and p < 0.05) and correlated their expression with the inflammatory associated genes. We performed in silico network analysis in MetaCore v6.9 to characterize the biological pathways connecting miRNA-mRNA pairs. Microarray analysis identified four miRNAs that were differentially expressed in postexposure compared with baseline samples, including miR-421 (FC = 2.81, p < 0.001), miR-146a (FC = 2.62, p = 0.007), miR-29a (FC = 2.91, p < 0.001), and let-7g (FC = 2.73, p = 0.019). Using false discovery date adjustment for multiple comparisons, we found 11 miRNA-mRNA correlated pairs involving the 4 differentially expressed miRNAs and candidate inflammatory genes. In silico network analysis with MetaCore database identified biological interactions for all the 11 miRNA-mRNA pairs, which ranged from direct mRNA targeting to complex interactions with multiple intermediates. Acute PM exposure may affect gene regulation through PM-responsive miRNAs that directly or indirectly control inflammatory gene expression.