Deconstructing intratumoral heterogeneity through multiomic and multiscale analysis of serial sections.

Tumors may contain billions of cells including distinct malignant clones and nonmalignant cell types. Clarifying the evolutionary histories, prevalence, and defining molecular features of these cells is essential for improving clinical outcomes, since intratumoral heterogeneity provides fuel for acquired resistance to targeted therapies. Here we present a statistically motivated strategy for deconstructing intratumoral heterogeneity through multiomic and multiscale analysis of serial tumor sections (MOMA). By combining deep sampling of IDH-mutant astrocytomas with integrative analysis of single-nucleotide variants, copy-number variants, and gene expression, we reconstruct and validate the phylogenies, spatial distributions, and transcriptional profiles of distinct malignant clones. By genotyping nuclei analyzed by single-nucleus RNA-seq for truncal mutations, we further show that commonly used algorithms for identifying cancer cells from single-cell transcriptomes may be inaccurate. We also demonstrate that correlating gene expression with tumor purity in bulk samples can reveal optimal markers of malignant cells and use this approach to identify a core set of genes that is consistently expressed by astrocytoma truncal clones, including AKR1C3, whose expression is associated with poor outcomes in several types of cancer. In summary, MOMA provides a robust and flexible strategy for precisely deconstructing intratumoral heterogeneity and clarifying the core molecular properties of distinct cellular populations in solid tumors.

MicroRNA Ratios Distinguish Melanomas from Nevi.

The use of microRNAs as biomarkers has been proposed for many diseases, including the diagnosis of melanoma. Although hundreds of microRNAs have been identified as differentially expressed in melanomas as compared to benign melanocytic lesions, a limited consensus has been achieved across studies, constraining the effective use of these potentially useful markers. In this study, we applied a machine learning-based pipeline to a dataset consisting of genetic features, clinical features, and next-generation microRNA sequencing from micro-dissected formalin-fixed paraffin embedded melanomas and their adjacent benign precursor nevi. We identified patient age and tumor cellularity as variables that frequently confound the measured expression of potentially diagnostic microRNAs. By employing the ratios of microRNAs that were either enriched or depleted in melanoma compared to the nevi as a normalization strategy, we developed a model that classified all the available published cohorts with an area under the receiver operating characteristic curve of 0.98. External validation on an independent cohort classified lesions with 81% sensitivity and 88% specificity and was uninfluenced by the tumor content of the sample or patient age.

A Glial Signature and Wnt7 Signaling Regulate Glioma-Vascular Interactions and Tumor Microenvironment.

Gliomas comprise heterogeneous malignant glial and stromal cells. While blood vessel co-option is a potential mechanism to escape anti-angiogenic therapy, the relevance of glial phenotype in this process is unclear. We show that Olig2+ oligodendrocyte precursor-like glioma cells invade by single-cell vessel co-option and preserve the blood-brain barrier (BBB). Conversely, Olig2-negative glioma cells form dense perivascular collections and promote angiogenesis and BBB breakdown, leading to innate immune cell activation. Experimentally, Olig2 promotes Wnt7b expression, a finding that correlates in human glioma profiling. Targeted Wnt7a/7b deletion or pharmacologic Wnt inhibition blocks Olig2+ glioma single-cell vessel co-option and enhances responses to temozolomide. Finally, Olig2 and Wnt7 become upregulated after anti-VEGF treatment in preclinical models and patients. Thus, glial-encoded pathways regulate distinct glioma-vascular microenvironmental interactions.

ERK phosphorylation of MED14 in promoter complexes during mitogen-induced gene activation by Elk-1.

The ETS domain transcription factor Elk-1 stimulates expression of immediate early genes (IEGs) in response to mitogens. These events require phosphorylation of Elk-1 by extracellular signal-regulated kinase (ERK) and phosphorylation-dependent interaction of Elk-1 with co-activators, including histone acetyltransferases and the Mediator complex. Elk-1 also recruits ERK to the promoters of its target genes, suggesting that ERK phosphorylates additional substrates in transcription complexes at mitogen-responsive promoters. Here we report that MED14, a core subunit of the Mediator, is a bona fide ERK substrate and identify serine 986 (S986) within a serine-proline rich region of MED14 as the major ERK phosphorylation site. Mitogens induced phosphorylation of MED14 on S986 at IEG promoters; RNAi knockdown of MED14 reduced CDK8 and RNA polymerase II (RNAPII) recruitment, RNAPII C-terminal domain phosphorylation and impaired activation of IEG transcription. A single alanine substitution at S986 reduced activation of an E26 (ETS)-responsive reporter by oncogenic Ras and mitogen-induced, Elk-1-dependent transcription, whereas activities of other transcriptional activators were unaffected. We also demonstrate that Elk-1 can associate with MED14 independently of MED23, which may facilitate phosphorylation of MED14 by ERK to impart a positive and selective impact on mitogen-responsive gene expression.

PU.1 is a major transcriptional activator of the tumour suppressor gene LIMD1.

LIMD1 is a tumour suppressor gene (TSG) down regulated in ∼80% of lung cancers with loss also demonstrated in breast and head and neck squamous cell carcinomas. LIMD1 is also a candidate TSG in childhood acute lymphoblastic leukaemia. Mechanistically, LIMD1 interacts with pRB, repressing E2F-driven transcription as well as being a critical component of microRNA-mediated gene silencing. In this study we show a CpG island within the LIMD1 promoter contains a conserved binding motif for the transcription factor PU.1. Mutation of the PU.1 consensus reduced promoter driven transcription by 90%. ChIP and EMSA analysis demonstrated that PU.1 specifically binds to the LIMD1 promoter. siRNA depletion of PU.1 significantly reduced endogenous LIMD1 expression, demonstrating that PU.1 is a major transcriptional activator of LIMD1.