Primary cell cultures obtained from clear cell Renal Cell Carcinoma specimens retain the transcriptomic profile and metabolic phenotype of corresponding tissues
Renal cell carcinoma (RCC) accounts for approximately 2-3% of all adult malignancies and clear cell RCC (ccRCC) is the most common subtype (1). In about 90% of its sporadic forms the bi-allelic inactivation of VHL prevents degradation of hypoxia-inducible factor-1α and 2α (HIF-1α, HIF-2α) with constitutive activation of their function (2). However, about 40% of ccRCC have deletions that include HIF-α locus and thus VHL-deficient ccRCC can be distinguished based on HIF-1α expression (3).HIF-1α and HIF-2α, through the regulation of different and specific hypoxia-inducible genes (4), have also an important role in the development of the various metabolic alterations that characterize ccRCC and are involved in its development (5). Recently, by combined proteomics and metabolomics analysis performed on ccRCC tissues we found that the Warburg effect (aerobic glycolysis) is more prominent at the expense of tricarboxylic acid cycle and oxidative metabolism pathway (6). Furthermore, the glutamine metabolism pathway acts to inhibit reactive oxygen species, as evidenced by an upregulated glutathione pathway, whereas the β-oxidation pathway is inhibited, leading to increased fatty acylcarnitines (6).
To overcome the difficulties and limitation due to tissue heterogeneity that characterizes ccRCC and to provide an in vitro model for functional studies, we established primary cell cultures (PCC) from normal cortex and ccRCC specimens with high efficiency and reproducibility. These cultures, composed of more than 90% of normal tubular or tumor cells respectively, were extensively characterized and showed to retain, at the early passages, the proteomic, phenotypic and genomic profile of the corresponding tissues (7-10). In order to extend the molecular characterization of our ccRCC PCC for their use in ccRCC metabolic alteration study with the final goal of favoring metabolic targeted therapies, we investigated here for the PCC transcriptomic profile and validated the molecular metabolic data obtained with phenotypic studies and metabolic assays.
Materials and Methods
PCC established from ccRCC and normal cortex tissue samples were characterized by FACS analysis (8). Total RNA samples were extracted from PCC and the transcriptome profiling of 8 ccRCC versus 8 cortex PCC cultures was performed by GeneChip Human Exon 1.0 ST array using Affymetrix technology. Functional enrichment analysis on Gene Ontoloy (GO) biological processes terms was performed on PCC differential expressed gene (DEG-PC) by ToppGene suite (https://toppgene.cchmc.org/). We compared our DEG-PC list to the list of differentially expressed genes related to ccRCC tissues (2493 DEG-tissues, derived from RNA-seq analysis) reported as supplementary data by Wozniak et al. (11). Comparison between GO biological processes enriched in ccRCC primary cultures and ccRCC tissues was performed using the ToppCluster tool.
Glycogen storage in PCC and corresponding tissues was evaluated by PAS staining and commercial kit; neutral lipid storage by Oil Red “O” staining or by lipid droplet marker PLIN2 expression evaluated by western blot. LDHA expression was evaluated by western blot and lactate content by commercial kit.
We globally found that the gene expression profiling well discriminated tumor from normal cortex PCC evidencing 1049 differential expressed genes (DEG) (552 up- and 497 down-regulated genes) in ccRCC as compared to normal kidney cultures. We found a significant functional enrichment for several biological processes, and among these also those related to metabolic processes, particularly lipid and carbohydrate metabolism. To verify whether ccRCC primary cultures can be considered a good in vitro model to represent and study ccRCC, we matched the transcriptomic analysis of our PCC in a metanalysis approach with ccRCC tissue transcriptomic profile. We found that 552 (52.6 %) out of 1049 DEG of our cultures were shared. In addition, we found that ccRCC PCC and tissues shared many GO biological processes, among which also several metabolic processes, indicating a good similarity between ccRCC cultures and tissues.
The molecular metabolic characterization evidenced from transcriptomic analysis of PCC was validated by the metabolic phenotype of our ccRCC PCC, also retained in corresponding tissues. In fact, PCCs at the first passages maintained the lipid and glycogen storage observed in corresponding tissues. Moreover, our ccRCC PCC maintain LDHA overexpression and L-lactate overproduction previously described in tissues.
The functional analysis of differentially modulated genes obtained comparing ccRCC versus normal cortex PCC showed significant enrichments of several biological processes known to be important for ccRCC development, among which those related to lipid and glucose metabolism. Moreover, by comparing the transcriptomic profile of the present study to the transcriptomic profile obtained in ccRCC tissues, we found that biological process categories such as lipid metabolic process and glucose/carbohydrate metabolic process were represented among the highest enriched terms shared by the two datasets. Thus, transcriptomic analysis of primary cell cultures indicated that our in vitro model well mimicked the molecular signature of ccRCC tissues also at metabolic level, suggesting that our cultures could be suitable tools to study the aspects related to ccRCC metabolism. The metabolic phenotype of our ccRCC PCCs, also observed in corresponding tissues, validated transcriptomic data, and confirmed the reliability of in vitro model of PCC to study ccRCC metabolism.
Here we described a further improvement in molecular characterization of our PCC, that will be instrumental for future metabolic studies that will aim to improve our understanding of ccRCC metabolic dysregulation. In the future, these PCC will be also used to evaluate the impact of the differential expression of HIF-a and of the clinical/pathological characteristics of the tumor on the metabolic behavior of ccRCC cells. The achievement of a complete molecular and metabolic characterization of ccRCC, based also on differential HIF-a expression, might pave the way to the discovery of innovative therapeutic approaches based on targeting specific differential metabolic pathways.
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