Osteosarcoma PDX-Derived Cell Line Models for Preclinical Drug Evaluation Demonstrate Metastasis Inhibition by Dinaciclib through a Genome-Targeted Approach.

PURPOSE: Models to study metastatic disease in rare cancers are needed to advance preclinical therapeutics and to gain insight into disease biology. Osteosarcoma is a rare cancer with a complex genomic landscape in which outcomes for patients with metastatic disease are poor. As osteosarcoma genomes are highly heterogeneous, multiple models are needed to fully elucidate key aspects of disease biology and to recapitulate clinically relevant phenotypes. EXPERIMENTAL DESIGN: Matched patient samples, patient-derived xenografts (PDX), and PDX-derived cell lines were comprehensively evaluated using whole-genome sequencing and RNA sequencing. The in vivo metastatic phenotype of the PDX-derived cell lines was characterized in both an intravenous and an orthotopic murine model. As a proof-of-concept study, we tested the preclinical effectiveness of a cyclin-dependent kinase inhibitor on the growth of metastatic tumors in an orthotopic amputation model. RESULTS: PDXs and PDX-derived cell lines largely maintained the expression profiles of the patient from which they were derived despite the emergence of whole-genome duplication in a subset of cell lines. The cell lines were heterogeneous in their metastatic capacity, and heterogeneous tissue tropism was observed in both intravenous and orthotopic models. Single-agent dinaciclib was effective at dramatically reducing the metastatic burden. CONCLUSIONS: The variation in metastasis predilection sites between osteosarcoma PDX-derived cell lines demonstrates their ability to recapitulate the spectrum of the disease observed in patients. We describe here a panel of new osteosarcoma PDX-derived cell lines that we believe will be of wide use to the osteosarcoma research community.

UHRF1 is a mediator of KRAS driven oncogenesis in lung adenocarcinoma.

KRAS is a frequent driver in lung cancer. To identify KRAS-specific vulnerabilities in lung cancer, we performed RNAi screens in primary spheroids derived from a Kras mutant mouse lung cancer model and discovered an epigenetic regulator Ubiquitin-like containing PHD and RING finger domains 1 (UHRF1). In human lung cancer models UHRF1 knock-out selectively impaired growth and induced apoptosis only in KRAS mutant cells. Genome-wide methylation and gene expression analysis of UHRF1-depleted KRAS mutant cells revealed global DNA hypomethylation leading to upregulation of tumor suppressor genes (TSGs). A focused CRISPR/Cas9 screen validated several of these TSGs as mediators of UHRF1-driven tumorigenesis. In vivo, UHRF1 knock-out inhibited tumor growth of KRAS-driven mouse lung cancer models. Finally, in lung cancer patients high UHRF1 expression is anti-correlated with TSG expression and predicts worse outcomes for patients with KRAS mutant tumors. These results nominate UHRF1 as a KRAS-specific vulnerability and potential target for therapeutic intervention.

Development and characterization of new patient-derived xenograft (PDX) models of osteosarcoma with distinct metastatic capacities.

Models to study metastatic disease in rare cancers are needed to advance preclinical therapeutics and to gain insight into disease biology, especially for highly aggressive cancers with a propensity for metastatic spread. Osteosarcoma is a rare cancer with a complex genomic landscape in which outcomes for patients with metastatic disease are poor. As osteosarcoma genomes are highly heterogeneous, a large panel of models is needed to fully elucidate key aspects of disease biology and to recapitulate clinically-relevant phenotypes. We describe the development and characterization of osteosarcoma patient-derived xenografts (PDXs) and a panel of PDX-derived cell lines. Matched patient samples, PDXs, and PDX-derived cell lines were comprehensively evaluated using whole genome sequencing and RNA sequencing. PDXs and PDX-derived cell lines largely maintained the expression profiles of the patient from which they were derived despite the emergence of whole-genome duplication (WGD) in a subset of cell lines. These cell line models were heterogeneous in their metastatic capacity and their tissue tropism as observed in both intravenous and orthotopic models. As proof-of-concept study, we used one of these models to test the preclinical effectiveness of a CDK inhibitor on the growth of metastatic tumors in an orthotopic amputation model. Single-agent dinaciclib was effective at dramatically reducing the metastatic burden in this model.

Combined Proteomic and Genetic Interaction Mapping Reveals New RAS Effector Pathways and Susceptibilities.

Activating mutations in RAS GTPases drive many cancers, but limited understanding of less-studied RAS interactors, and of the specific roles of different RAS interactor paralogs, continues to limit target discovery. We developed a multistage discovery and screening process to systematically identify genes conferring RAS-related susceptibilities in lung adenocarcinoma. Using affinity purification mass spectrometry, we generated a protein-protein interaction map of RAS interactors and pathway components containing hundreds of interactions. From this network, we constructed a CRISPR dual knockout library targeting 119 RAS-related genes that we screened for KRAS-dependent genetic interactions (GI). This approach identified new RAS effectors, including the adhesion controller RADIL and the endocytosis regulator RIN1, and >250 synthetic lethal GIs, including a potent KRAS-dependent interaction between RAP1GDS1 and RHOA. Many GIs link specific paralogs within and between gene families. These findings illustrate the power of multiomic approaches to uncover synthetic lethal combinations specific for hitherto untreatable cancer genotypes. SIGNIFICANCE: We establish a deep network of protein-protein and genetic interactions in the RAS pathway. Many interactions validated here demonstrate important specificities and redundancies among paralogous RAS regulators and effectors. By comparing synthetic lethal interactions across KRAS-dependent and KRAS-independent cell lines, we identify several new combination therapy targets for RAS-driven cancers.This article is highlighted in the In This Issue feature, p. 1775.

Hydra: A mixture modeling framework for subtyping pediatric cancer cohorts using multimodal gene expression signatures.

Precision oncology has primarily relied on coding mutations as biomarkers of response to therapies. While transcriptome analysis can provide valuable information, incorporation into workflows has been difficult. For example, the relative rather than absolute gene expression level needs to be considered, requiring differential expression analysis across samples. However, expression programs related to the cell-of-origin and tumor microenvironment effects confound the search for cancer-specific expression changes. To address these challenges, we developed an unsupervised clustering approach for discovering differential pathway expression within cancer cohorts using gene expression measurements. The hydra approach uses a Dirichlet process mixture model to automatically detect multimodally distributed genes and expression signatures without the need for matched normal tissue. We demonstrate that the hydra approach is more sensitive than widely-used gene set enrichment approaches for detecting multimodal expression signatures. Application of the hydra analysis framework to small blue round cell tumors (including rhabdomyosarcoma, synovial sarcoma, neuroblastoma, Ewing sarcoma, and osteosarcoma) identified expression signatures associated with changes in the tumor microenvironment. The hydra approach also identified an association between ATRX deletions and elevated immune marker expression in high-risk neuroblastoma. Notably, hydra analysis of all small blue round cell tumors revealed similar subtypes, characterized by changes to infiltrating immune and stromal expression signatures.

Phosphate availability regulates ethylene biosynthesis gene expression and protein accumulation in white clover (Trifolium repens L.) roots.

The expression and accumulation of members of the 1-aminocyclopropane-1-carboxylate (ACC) synthase (ACS) and ACC oxidase (ACO) gene families was examined in white clover roots grown in either Pi (phosphate) sufficient or Pi-deprived defined media. The accumulation of one ACO isoform, TR-ACO1, was positively influenced after only 1 h of exposure to low Pi, and this was maintained over a 7-day time-course. Up-regulation of TR-ACS1, TR-ACS2 and TR-ACS3 transcript abundance was also observed within 1 h of exposure to low Pi in different tissue regions of the roots, followed by a second increase in abundance of TR-ACS2 after 5-7 days of exposure. An increase in transcript abundance of TR-ACO1 and TR-ACO3, but not TR-ACO2, was observed after 1 h of exposure to low Pi, with a second increase in TR-ACO1 transcripts occurring after 2-5 days. These initial increases of the TR-ACS and TR-ACO transcript abundance occurred before the induction of Trifolium repens PHOSPHATE TRANSPORTER 1 (TR-PT1), and the addition of sodium phosphite did not up-regulate TR-ACS1 expression over 24 h. In situ hybridization revealed some overlap of TR-ACO mRNA accumulation, with TR-ACO1 and TR-ACO2 in the root tip regions, and TR-ACO1 and TR-ACO3 mRNA predominantly in the lateral root primordia. TR-ACO1p-driven GFP expression showed that activation of the TR-ACO1 promoter was initiated within 24 h of exposure to low Pi (as determined by GFP protein accumulation). These results suggest that the regulation of ethylene biosynthesis in white clover roots is biphasic in response to low Pi supply.