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

MEK inhibition synergizes with TYK2 inhibitors in NF1-associated malignant peripheral nerve sheath tumors

PURPOSE: Malignant peripheral nerve sheath tumors (MPNST) are aggressive sarcomas with limited treatment options and poor survival rates. About half of MPNST cases are associated with the neurofibromatosis type 1 (NF1) cancer predisposition syndrome. Overexpression of TYK2 occurs in the majority of MPNST, implicating TYK2 as a therapeutic target. EXPERIMENTAL DESIGN: The effects of pharmacologic TYK2 inhibition on MPNST cell proliferation and survival were examined using IncuCyte live cell assays in vitro, and downstream actions were analyzed using RNA-sequencing (RNA-seq), qPCR arrays, and validation of protein changes with the WES automated Western system. Inhibition of TYK2 alone and in combination with MEK inhibition was evaluated in vivo using both murine and human MPNST cell lines, as well as MPNST PDX. RESULTS: Pharmacologic inhibition of TYK2 dose-dependently decreased proliferation and induced apoptosis over time. RNA-seq pathway analysis on TYK2 inhibitor-treated MPNST demonstrated decreased expression of cell cycle, mitotic, and glycolysis pathways. TYK2 inhibition resulted in upregulation of the MEK/ERK pathway gene expression, by both RNA-seq and qPCR array, as well as increased pERK1/2 levels by the WES Western system. The compensatory response was tested with dual treatment with TYK2 and MEK inhibitors, which synergistically decreased proliferation and increased apoptosis in vitro. Finally, combination therapy was shown to inhibit growth of MPNST in multiple in vivo models. CONCLUSIONS: These data provide the preclinical rationale for the development of a phase I clinical trial of deucravacitinib and mirdametinib in NF1-assosciated MPNST

Perturbation biology: inferring signaling networks in cellular systems.

We present a powerful experimental-computational technology for inferring network models that predict the response of cells to perturbations, and that may be useful in the design of combinatorial therapy against cancer. The experiments are systematic series of perturbations of cancer cell lines by targeted drugs, singly or in combination. The response to perturbation is quantified in terms of relative changes in the measured levels of proteins, phospho-proteins and cellular phenotypes such as viability. Computational network models are derived de novo, i.e., without prior knowledge of signaling pathways, and are based on simple non-linear differential equations. The prohibitively large solution space of all possible network models is explored efficiently using a probabilistic algorithm, Belief Propagation (BP), which is three orders of magnitude faster than standard Monte Carlo methods. Explicit executable models are derived for a set of perturbation experiments in SKMEL-133 melanoma cell lines, which are resistant to the therapeutically important inhibitor of RAF kinase. The resulting network models reproduce and extend known pathway biology. They empower potential discoveries of new molecular interactions and predict efficacious novel drug perturbations, such as the inhibition of PLK1, which is verified experimentally. This technology is suitable for application to larger systems in diverse areas of molecular biology

Special Issue: “Genomics and Models of Nerve Sheath Tumors”

Nerve sheath tumors arising in the context of neurofibromatosis type 1 (NF1) include benign tumors such as cutaneous, diffuse and plexiform neurofibromas; atypical neurofibromas or atypical neurofibromatosis neoplasms of uncertain biological potential (ANNUBP); and the aggressive soft tissue sarcoma, the malignant peripheral nerve sheath tumor (MPNST) [...

Therapeutic Vulnerability to ATR Inhibition in Concurrent <i>NF1</i> and <i>ATRX</i>-Deficient/ALT-Positive High-Grade Solid Tumors

Subsets of Neurofibromatosis Type 1 (NF1)-associated solid tumors have been shown to display high frequencies of ATRX mutations and the presence of alternative lengthening of telomeres (ALT). We studied the phenotype of combined NF1 and ATRX deficiency in malignant solid tumors. Cell lines derived from NF1-deficient sporadic glioblastomas (U251, SF188), an NF1-associated ATRX mutant glioblastoma cell line (JHH-NF1-GBM1), an NF1-derived sarcoma cell line (JHH-CRC65), and two NF1-deficient MPNST cell lines (ST88-14, NF90.8) were utilized. Cancer cells were treated with ATR inhibitors, with or without a MEK inhibitor or temozolomide. In contrast to the glioma cell line SF188, combined ATRX knockout (KO) and TERC KO led to ALT-like properties and sensitized U251 glioma cells to ATR inhibition in vitro and in vivo. In addition, ATR inhibitors sensitized U251 cells to temozolomide, but not MEK inhibition, irrespective of ATRX level manipulation; whereas, the JHH-NF1-GBM1 cell line demonstrated sensitivity to ATR inhibition, but not temozolomide. Similar effects were noted using the MPNST cell line NF90.8 after combined ATRX knockdown and TERC KO; however, not in ST88-14. Taken together, our study supports the feasibility of targeting the ATR pathway in subsets of NF1-deficient and associated tumors