Lisa McFerrin

An Overview of MYC and Its Interactome

This review is intended to provide a broad outline of the biological and molecular functions of MYC as well as of the larger protein network within which MYC operates. We present a view of MYC as a sensor that integrates multiple cellular signals to mediate a broad transcriptional response controlling many aspects of cell behavior. We also describe the larger transcriptional network linked to MYC with emphasis on the MXD family of MYC antagonists. Last, we discuss evidence that the network has evolved for millions of years, dating back to the emergence of animals.

Deregulated Myc Requires MondoA/Mlx for Metabolic Reprogramming and Tumorigenesis

Deregulated Myc transcriptionally reprograms cell metabolism to promote neoplasia. Here we show that oncogenic Myc requires the Myc superfamily member MondoA, a nutrient-sensing transcription factor, for tumorigenesis. Knockdown of MondoA, or its dimerization partner Mlx, blocks Myc-induced reprogramming of multiple metabolic pathways, resulting in apoptosis. Identification and knockdown of genes coregulated by Myc and MondoA have allowed us to define metabolic functions required by deregulated Myc and demonstrate a critical role for lipid biosynthesis in survival of Myc-driven cancer. Furthermore, overexpression of a subset of Myc and MondoA coregulated genes correlates with poor outcome of patients with diverse cancers. Coregulation of cancer metabolism by Myc and MondoA provides the potential for therapeutics aimed at inhibiting MondoA and its target genes.

Molecular Portraits of Epithelial, Mesenchymal, and Hybrid States in Lung Adenocarcinoma and Their Relevance to Survival

Epithelial-to-mesenchymal transition (EMT) is a key process associated with tumor progression and metastasis. To define molecular features associated with EMT states, we undertook an integrative approach combining mRNA, miRNA, DNA methylation, and proteomic profiles of 38 cell populations representative of the genomic heterogeneity in lung adenocarcinoma. The resulting data were integrated with functional profiles consisting of cell invasiveness, adhesion, and motility. A subset of cell lines that were readily defined as epithelial or mesenchymal based on their morphology and E-cadherin and vimentin expression elicited distinctive molecular signatures. Other cell populations displayed intermediate/hybrid states of EMT, with mixed epithelial and mesenchymal characteristics. A dominant proteomic feature of aggressive hybrid cell lines was upregulation of cytoskeletal and actin-binding proteins, a signature shared with mesenchymal cell lines. Cytoskeletal reorganization preceded loss of E-cadherin in epithelial cells in which EMT was induced by TGFβ. A set of transcripts corresponding to the mesenchymal protein signature enriched in cytoskeletal proteins was found to be predictive of survival in independent datasets of lung adenocarcinomas. Our findings point to an association between cytoskeletal and actin-binding proteins, a mesenchymal or hybrid EMT phenotype and invasive properties of lung adenocarcinomas.

Functional Interactions Among Members of the MAX and MLX Transcriptional Network During Oncogenesis

The transcription factor MYC and its related family members MYCN and MYCL have been implicated in the etiology of a wide spectrum of human cancers. Compared to other oncoproteins, such as RAS or SRC, MYC is unique because its protein coding region is rarely mutated. Instead, MYCs oncogenic properties are unleashed by regulatory mutations leading to unconstrained high levels of expression. Under both normal and pathological conditions MYC regulates multiple aspects of cellular physiology including proliferation, differentiation, apoptosis, growth and metabolism by controlling the expression of thousands of genes. How a single transcription factor exerts such broad effects remains a fascinating puzzle. Notably, MYC is part of a network of bHLHLZ proteins centered on the MYC heterodimeric partner MAX and its counterpart, the MAX-like protein MLX. This network includes MXD1-4, MNT, MGA, MONDOA and MONDOB proteins. With some exceptions, MXD proteins have been functionally linked to cell cycle arrest and differentiation, while MONDO proteins control cellular metabolism. Although the temporal expression patterns of many of these proteins can differ markedly they are frequently expressed simultaneously in the same cellular context, and potentially bind to the same, or similar DNA consensus sequence. Here we review the activities and interactions among these proteins and propose that the broad spectrum of phenotypes elicited by MYC deregulation is intimately connected to the functions and regulation of the other network members. Furthermore, we provide a meta-analysis of TCGA data suggesting that the coordinate regulation of the network is important in MYC driven tumorigenesis. This article is part of a Special Issue entitled: Myc proteins in cell biology and pathology.

Multidimensional scaling of diffuse gliomas: application to the 2016 World Health Organization classification system with prognostically relevant molecular subtype discovery

Recent updating of the World Health Organization (WHO) classification of central nervous system (CNS) tumors in 2016 demonstrates the first organized effort to restructure brain tumor classification by incorporating histomorphologic features with recurrent molecular alterations. Revised CNS tumor diagnostic criteria also attempt to reduce interobserver variability of histological interpretation and provide more accurate stratification related to clinical outcome. As an example, diffuse gliomas (WHO grades II–IV) are now molecularly stratified based upon isocitrate dehydrogenase 1 or 2 (IDH) mutational status, with gliomas of WHO grades II and III being substratified according to 1p/19q codeletion status. For now, grading of diffuse gliomas is still dependent upon histological parameters. Independent of WHO classification criteria, multidimensional scaling analysis of molecular signatures for diffuse gliomas from The Cancer Genome Atlas (TCGA) has identified distinct molecular subgroups, and allows for their visualization in 2-dimensional (2D) space. Using the web-based platform Oncoscape as a tool, we applied multidimensional scaling-derived molecular groups to the 2D visualization of the 2016 WHO classification of diffuse gliomas. Here we show that molecular multidimensional scaling of TCGA data provides 2D clustering that represents the 2016 WHO classification of diffuse gliomas. Additionally, we used this platform to successfully identify and define novel copy-number alteration-based molecular subtypes, which are independent of WHO grading, as well as predictive of clinical outcome. The prognostic utility of these molecular subtypes was further validated using an independent data set of the German Glioma Network prospective glioblastoma patient cohort.

A Pilot Study of Clinical Targeted Next Generation Sequencing for Prostate Cancer: Consequences for Treatment and Genetic Counseling.

Targeted next generation sequencing (tNGS) is increasingly used in oncology for therapeutic decision‐making, but is not yet widely used for prostate cancer. The objective of this study was to determine current clinical utility of tNGS for prostate cancer management.

Copy number profiling across glioblastoma populations has implications for clinical trial design

Background Copy number alterations form prognostic molecular subtypes of glioblastoma with clear differences in median overall survival. In this study, we leverage molecular data from several glioblastoma cohorts to define the distribution of copy number subtypes across random cohorts as well as cohorts with selection biases for patients with inherently better outcome. Methods Copy number subtype frequency was established for 4 glioblastoma patient cohorts. Two randomly selected cohorts include The Cancer Genome Atlas (TCGA) and the German Glioma Network (GGN). Two more selective cohorts include the phase II trial ARTE in elderly patients with newly diagnosed glioblastoma and a multi-institutional cohort focused on paired resected initial/recurrent glioblastoma. The paired initial/recurrent cohort also had exome data available, which allowed for evaluation of multidimensional scaling analysis. Results Smaller selective glioblastoma cohorts are enriched for copy number subtypes that are associated with better survival, reflecting the selection of patients who do well enough to enter a clinical trial or who are deemed well enough to undergo resection at recurrence. Adding exome data to copy number data provides additional data reflective of outcome. Conclusions The overall outcome for diffuse glioma patients is predicted by DNA structure at initial tumor resection. Molecular signature shifts across glioblastoma populations reflect the inherent bias of patient selection toward longer survival in clinical trials. Therefore it may be important to include molecular profiling, including copy number, when enrolling patients for clinical trials in order to balance arms and extrapolate relevance to the general glioblastoma population.

Analysis and visualization of linked molecular and clinical cancer data by using Oncoscape

To the Editor — The rapid generation and expanding accessibility of clinical and molecular data is shifting the bottleneck in cancer research from data acquisition to data aggregation and interpretation. Many tools have been developed to address various aspects of this need1–5. To overcome the persistent challenges in cohort discovery and analysis for translational research and prospective clinical-decision support in precision medicine, we developed Oncoscape, an online open-access dataanalysis and visualization platform (see URLs) that empowers researchers and clinicians to discover novel patterns and relationships between linked clinical and molecular data. Through a suite of interoperable tools, Oncoscape offers a unique and intuitive approach to iterative hypothesis refinement and cohort discovery by establishing a platform that allows users to easily traverse data types and methods. With its a modern framework and modular design, Oncoscape is a scalable solution for easily implementing and building an extensible library of datasets and tools (Supplementary Note 1). The current release of Oncoscape (2.0) offers both common and new bioinformatic methods as mature online visualization applications (Fig. 1 and Supplementary Note 1). Through the cohort menu, users can easily toggle among and compare different patient/ sample groups within a specific tool or seamlessly apply the selected cohort within a new application for further analysis (Supplementary Fig. 1). The responsive spreadsheet (Supplementary Fig. 2) and graphical timeline (Supplementary Fig. 3) tools represent detailed clinical time-course data for patient cohorts, and the Kaplan– Meier6 survival plot (Supplementary Fig. 4) compares outcomes across user-defined groups. Principal component analysis (PCA)7 (Supplementary Fig. 5) based on either DNA or RNA data, such as copy number variation or expression, allows for comparison of tissue samples by using whole-genome or gene-set-specific calculations, with the added ability to color-code samples according to various clinical and genetic features. The newly developed markers + patients tool (Supplementary Fig. 6) connects a twodimensional landscape of patient molecular data on the basis of similarity measures (for example, PCA or multidimensional scaling) to the genes that are altered in those tumors. The representation of genes by chromosome location further indicates regional hotspots of copy number variations or mutations. The Cancer Genome Atlas (TCGA) was used as an exemplar dataset to construct the Oncoscape platform. Available through the Genomic Data Commons (GDC)8 and the UCSC Xena data hub, TCGA data provide an extensive resource of public, processed

A Pilot Study of Clinical Targeted Next Generation Sequencing for Prostate Cancer

Targeted next generation sequencing (tNGS) is increasingly used in oncology for therapeutic decision‐making, but is not yet widely used for prostate cancer. The objective of this study was to determine current clinical utility of tNGS for prostate cancer management.

A Pilot Study of Clinical Targeted Next Generation Sequencing for Prostate Cancer: Consequences for Treatment and Genetic Counseling: Clinical Targeted NGS for Prostate Cancer

Targeted next generation sequencing (tNGS) is increasingly used in oncology for therapeutic decision‐making, but is not yet widely used for prostate cancer. The objective of this study was to determine current clinical utility of tNGS for prostate cancer management.