Using the New Transcription Factor and Downstream Effects Prediction Capabilities in IPA to Understand the Tumor Suppressor Function of miR-16

See how new features in Ingenuity’s IPA help provide insights into the tumor suppression function of miR-16.   IPA helped Dr. Aimee Jackson rapidly and seamlessly integrate diverse  data (microRNA targets, functional annotation of downstream effects, pathway/network interactions, and transcription factor prediction) to generate testable hypotheses about the function of miR-16 in tumor suppression, and how its loss might contribute to cancer initiation or progression.

By Aimee Jackson, Ph.D., Molecular Genomics Consultant

Numerous studies have shown that the expression of microRNAs is dysregulated in human cancers, and the resulting aberrant function of microRNAs contributes to tumor development, tumor progression, and metastasis.  microRNAs regulate networks of genes whose coordinate regulation is important for controlling biological processes.  Given the large number of genes regulated by microRNAs, it can be challenging to elucidating molecular function in relation to a biological process or phenotype, such as tumor initiation and progression.  Integrated data analysis tools are critical to gain functional molecular insights from the large number of genes regulated by microRNAs.

One such microRNA is miR-16, a member of a family of microRNAs that is frequently lost or down-regulated in leukemias and solid tumors.  Down-regulation of miR-16 in cancer-associated fibroblasts promotes tumor growth and progression, suggesting that decreased expression of miR-16 plays an active, causal role in cancer progression.  We wondered how miR-16 normally functions to suppress tumor formation and progression.  In a study(1) published in 2007, we sought to elucidate miR-16 function by transfecting miR-16 into colon cancer cells in culture, and utilizing expression profiling to identify genes regulated in response to miR-16.  Through kinetic analysis of gene expression, we identified 2 distinct subsets of transcripts.  One set of genes was down-regulated at early times after transfection of miR-16 (6-10 hours), and was enriched for genes whose 3’ UTRs displayed sequence complementarity to the seed region of miR-16.  We considered these to be direct targets of miR-16.  A second set of transcripts was regulated at later times after transfection of miR-16 (24 hours) and was not enriched for 3’ UTR complementarity to the miR-16 seed region.  We defined these as downstream targets of miR-16.  We subsequently used Gene Ontology (GO) category enrichment to gain insight into functional annotation for these 2 sets of genes.  The direct targets did not show statistically significant enrichment for any single GO category, while the downstream targets were highly enriched for cell cycle.  This was the first suggestion of a role for miR-16 in cell cycle regulation.  We were subsequently able to validate this finding experimentally, by demonstrating that miR-16 negatively regulates cell cycle progression by coordinate down-regulation of multiple cell cycle genes, leading to arrest in the G1 phase of the cell cycle.

With the new Transcription Factor and Downstream Effects Analysis capabilities in IPA, I was curious to determine whether I could gain additional insights into the tumor suppressor function of miR-16 by re-analyzing this existing dataset in IPA.  Excitingly, with these new analysis capabilities, I was able to confirm and extend the previous conclusions, and reveal new insights that could be the basis for further experimental validation at the bench.  While previously we did not detect significant functional annotation for the direct targets of miR-16, IPA’s Downstream Effects predicts functions in cell proliferation and cell cycle for this subset of genes, a function that was confirmed by analysis of the downstream targets.  With IPA’s Pathway Explorer, I was able to visualize connections and interactions among the genes in my dataset, as well as additional genes in the cell cycle network that were not present in my geneset, to refine and expand biological interpretation of the role of miR-16 in cell cycle regulation.   The new Transcription Factor prediction capability of IPA predicted that TP53 is activated and MYC is inhibited in cells transfected with miR-16.  This novel finding could be interpreted in a number of ways:

1) miR-16 might exert its tumor suppressive effect in part through activation of the TP53 tumor suppressor and inactivation of the MYC oncogene.  Loss of miR-16 could therefore contribute to tumor initiation and progression through loss of TP53 activity and activation of MYC.  Due to the fact that much of the regulation of TP53 and MYC activity is due to mutation or post-translational modification (phosphorylation, methylation, etc.), rather than at the level of expression, we would not have detected these altered activation states in our microarray profiling data.  The new TF analysis tool from Ingenuity is able to infer activity of TFs at their protein level, making this type of discovery possible.

2) These findings could suggest the regulation of miR-16 by TP53 and MYC based on recent studies in which TP53 was found to enhance the processing of miR-16 and MYC was found to inhibit the expression of miR-16.  The decreased expression of miR-16 targets would reflect increased levels of miR-16, which in turn reflects active TP53 and inactive MYC.  In light of these recent findings, the potential regulation of miR-16 by TP53 and/or MYC is another testable hypothesis regarding miR-16 expression, activity, and connection to other tumor-modulating proteins.

3) TP53, MYC, and miR-16 all regulate genes to control cell cycle progression, such that the down-regulated signature of miR-16 overexpression could mimic the cell cycle effects of TP53 activation and/or MYC inactivation.  Thus, loss of miR-16 function could be a mechanism for tumor initiation and progression in settings of wild type TP53 and MYC.

With the new data analysis tools in IPA, I could rapidly and seamlessly integrate diverse aspects of the data (microRNA targets, functional annotation of downstream effects, pathway/network interactions, and transcription factor prediction) to generate testable hypotheses about the function of miR-16 in tumor suppression, and how its loss might contribute to cancer initiation or progression.

(1) Linsley, P.S., J. Schelter, J. Burchard, M. Kibukawa, M.M. Martin, S.R. Bartz, J.M. Johnson, J.M. Cummins, C.K. Raymond, H. Dai, N. Chau, M. Cleary, A.L. Jackson, M. Carleton, and L. Lim. 2007. Transcripts regulated by the microRNA-16 family cooperatively regulate cell cycle progression.  Mol. Cell. Biol. 27(6):2240-2252.

Learn more about these features in IPA.