Oncogenic Role of miR-217 During Clear Cell Renal Carcinoma Progression

Abstract

Clear cell renal carcinoma (ccRC) comprises a set of heterogeneous, fast-progressing pathologies with poor prognosis. Analyzing ccRC progression in terms of modifications at the molecular level may provide us with a broader understanding of the disease, paving the way for improved diagnostics and therapeutics. The role of micro-RNAs (miRs) in cancer by targeting both oncogenes and tumor suppressor genes is widely known. Despite this knowledge, the role of specific miRs and their targets in the progression of ccRC is still unknown. To evaluate the action of miRs and their target genes during ccRC progression, here we implemented a three-step method for constructing miR–gene co-expression networks for each progression stage of ccRC as well as for adjacent-normal renal tissue (NT). In the first step, we inferred all miR–gene co-expression interactions for each progression stage of ccRC and for NT. Afterwards, we filtered the whole miR–gene networks by differential gene and miR expression between successive stages: stage I with non-tumor, stage II with stage I, and so on. Finally, all miR–gene interactions whose relationships were inversely proportional (overexpressed miR and underexpressed genes and vice versa) were kept and removed otherwise. We found that miR-217 is differentially expressed in all contrasts; however, its targets were different depending on the ccRC stage. Furthermore, the target genes of miR-217 have a known role in cancer progression—for instance, in stage II network, GALNTL6 is overexpressed, and it is related to cell signaling, survival, and proliferation. In the stage III network, WNK2, a widely known tumor suppressor, is underexpressed. For the stage IV network, IGF2BP2, a post-transcriptional regulator of MYC and PTEN, is overexpressed. This data-driven network approach has allowed us to discover miRs that have different targets through ccRC progression, thus providing a method for searching possible stage-dependent therapeutic targets in this and other types of cancer.

The network structure of hematopoietic cancers

“…As expected, several of these smaller components are made up of genes from the same chromosome. This result coincide with the previous GCNs analyzed from breast cancer (2–4), lung (5), and clear cell renal carcinoma (6, 7) suggesting a common regulatory mechanism affecting the entire system, which is manifested in the network topologies.…”

“…As expected, several of these smaller components are made up of genes from the same chromosome. This result coincide with the previous GCNs analyzed from breast cancer (2)(3)(4), lung (5), and clear cell renal carcinoma (6,7) suggesting a common regulatory mechanism affecting the entire system, which is manifested in the network topologies. Another aspect that we consider to be crucial in the topological analysis of the GCNs of cancer phenotypes is the regulation of inter-chromosomal interactions.…”

“…As mentioned before, the cancerous networks have several small components, many of them made up of genes from the same chromosome. This result coincide with the previous GCNs analyzed from breast cancer (13, 25), lung (26), and clear cell renal carcinoma (27, 28). In these studies, the cancer networks have a diminished amount of inter-chromosomal interactions.…”

“…In order to unveil the mechanisms behind the loss of interchromosome gene co-expression in cancer, other omic technologies have been evaluated. For instance, copy number variation data, transcription factor binding sites, or micro-RNA co-expression (28,(39)(40)(41). However, none of those omics have been determinant to explain the significant decrease of long-range gene co-expression.…”

Loss of long-range co-expression is a common trait in cancer

“…We have shown, for Luminal A and B breast cancer subtypes, that intra-chromosomal communities are not bound by CTCF binding sites and that copy number alterations do not influence co-expressed network communities with a similar differential expression trend (27) nor do they affect intra-cytoband co-expression patterns (63). Our group has also analyzed epigenetic mechanisms in the context of cancer gene co-expression, in particular the role of miRNA regulation, showing that specific miRNA families alter coexpression in genes related to the epithelial-mesenchymal transition (64, 65), they also promote subtype-specific pathways in breast cancer (66), and are associated with progression stage in clear cell renal carcinoma (67). However, these examples come from inter-chromosomal interactions.…”