Integrative Analysis Identifies Candidate Tumor Microenvironment and Intracellular Signaling Pathways that Define Tumor Heterogeneity in NF1

Neurofibromatosis type 1 (NF1) is a monogenic syndrome that gives rise to numerous symptoms including cognitive impairment, skeletal abnormalities, and growth of benign nerve sheath tumors. Nearly all NF1 patients develop cutaneous neurofibromas (cNFs), which occur on the skin surface, whereas 40-60% of patients develop plexiform neurofibromas (pNFs), which are deeply embedded in the peripheral nerves. Patients with pNFs have a ~10% lifetime chance of these tumors becoming malignant peripheral nerve sheath tumors (MPNSTs). These tumors have a severe prognosis and few treatment options other than surgery. Given the lack of therapeutic options available to patients with these tumors, identification of druggable pathways or other key molecular features could aid ongoing therapeutic discovery studies. In this work, we used statistical and machine learning methods to analyze 77 NF1 tumors with genomic data to characterize key signaling pathways that distinguish these tumors and identify candidates for drug development. We identified subsets of latent gene expression variables that may be important in the identification and etiology of cNFs, pNFs, other neurofibromas, and MPNSTs. Furthermore, we characterized the association between these latent variables and genetic variants, immune deconvolution predictions, and protein activity predictions.

Abstract 772: The molecular landscape of dermal neurofibromatosis

Background: Neurofibromatosis type I (NF1) is a genetic disorder that disrupts neurological tissue growth and can lead to a diverse set of symptoms including systematic growth of benign tumors, learning disorders and bone deformities. It is a rare disease occurring in only 1 in 3,000 people worldwide. While the disease has been linked to loss of function in the NF1 gene - a known tumor suppressor - there is a high degree of phenotypic diversity in the NF1 patient population, making it difficult to identify the underlying cause of the disease and treat it effectively. In this work we seek to improve overall knowledge of dermal NF1 through global molecular characterization of the disease.

Methods: We have collected four dermal neurofibromas and peripheral blood from each of 11 NF1 patients. We analyzed each sample using (1) Whole genome sequencing (WGS) on the Illumina HiSeq X platform, (2) Illumina OMNI2.5 Arrays (3) RNA-Sequencing on an Illumina HiSeq v4 machine and (4) iTRAQ-labeled proteomics. WGS data for both tumor and blood samples from each patient were used to identify patient-specific germ-line mutations as well as tumor-specific somatic mutations in each sample. Single nucleotide polymorphisms identified by the OMNI Arrays were used to identify copy number alterations in both blood and tumor samples. RNA-Seq data and proteomics data were mapped to transcripts and proteins respectively.

Results: Preliminary analysis of this data illustrates a diverse genomic landscape of NF1. Hierarchical clustering of copy number alterations largely show samples clustering by tissue, suggesting that most copy number alterations are somatic and not shared across the germline. However, there are two patients that show germline copy number alterations, including one patient with loss in the NF1 region. WGS analysis suggests similar diversity with each patient possessing a distinct combination of germline and somatic mutations of NF1 and other cancer-related genes. Cluster analysis of the RNA-Seq data shows no patient-specific clusters, suggesting that that each tumor executes a unique transcriptional program.

Conclusion: This work represents a first-ever attempt to profile the diversity of dermal neurofibromatosis at a molecular level. Preliminary analysis of the data underscores the complexity of this disease and explains, in part, previous difficulty in identifying effective treatments. Ongoing work includes expanding the analysis to include more patient samples and other types of NF1-derived tumors. As an orphan disease, NF1 has been poorly characterized compared to more common cancers. To rectify this, the Children's Tumor Foundation and Sage Bionetworks are collaborating to make NF1 data available to the public to accelerate research and the drug discovery pipeline. We expect that this data will be a resource for other NF1 researchers to assist in the study of this disease at the molecular level. All data and preliminary results are publicly available at http://www.synapse.org/dermalNF

Citation Format: Sara JC Gosline, Pamela Knight, Thomas Yu, Nripesh Prasad, Angela Jones, Shristi Shrestha, Braden Boone, Shawn E. Levy, Andrew J. Link, Allison C. Galassie, Hubert Weinberg, Stephen Friend, Salvatore La Rosa, Justin Guinney, Annette Bakker. The molecular landscape of dermal neurofibromatosis. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 772.

Abstract B2-45: Uncovering coordinated regulation of transcription factors by microRNAs using integrated network models

MicroRNAs (miRNAs) are small non-coding RNAs that play a significant role in development and cancer but induce only moderate repression of direct messenger RNA (mRNA) targets, suggesting that they coordinate with other modes of cellular regulation to affect cellular phenotype. In this work we exhaustively profile the transcriptional and post-transcriptional regulatory changes between an isogenic pair of murine fibroblast cell lines with and without Dicer, an enzyme required for miRNA processing. Through quantitative analysis of diverse high-throughput datasets collected from both cell lines, we were able to decouple transcriptional from post-transcriptional changes reflected in mRNA expression changes between cells with and without miRNAs.

We present three major findings. First, we find that direct miRNA-mRNA interactions have a limited impact on gene expression changes upon Dicer deletion when compared to changes at transcription. We then introduce an integrative graphical network approach to identify specific transcription factors that explain the observed changes in gene expression upon loss of Dicer. Validation of this computational model via transcription factor over-expression reveals a subset of the miRNA-mediated transcriptional program that is activated upon Dicer loss, confirming that transcriptional networks amplify the effects of miRNAs. Lastly, we use this network to examine coordination between transcriptional and post-transcriptional regulation. We identify numerous coherent and in-coherent feed-forward loops, network motifs that have been alluded to but only minimally studied in the context of microRNAs and transcription factors, and find that genes regulated within feed-forward loops by microRNAs and transcription factors exhibit distinct properties in development.

In summary, our work illustrates how transcriptional networks amplify the effects of microRNAs. We show coordinated regulation of transcription factors by microRNAs that suggests that most gene expression changes attributed to microRNAs in diseases such as cancer are due to changes in transcription rather than microRNA-mediated degradataion. As such, this work has the potential to reframe future studies of microRNAs in the context of cancer by shifting the focus to understanding the impact of microRNAs on transcription factors.

Citation Format: Sara JC Gosline, Allan M. Gurtan, Courtney K. JnBaptiste, Andrew Bosson, Pamela Milani, Simona Dalin, Bryan Matthews, Yoon Sing Yap, Phillip A. Sharp, Ernest Fraenkel. Uncovering coordinated regulation of transcription factors by microRNAs using integrated network models. [abstract]. In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr B2-45.