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.

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.

Short-term effect of PM2.5 on stroke in susceptible populations: A case-crossover study.

BACKGROUND: Fine particulate matter (PM2.5) is a risk factor for stroke, and patients with pre-existing diseases appear to be particularly susceptible. We conducted a case-crossover study to examine the association between short-term exposure to fine particulate matter (PM2.5) and hospital admission for stroke in individuals with atrial fibrillation (AF), hypertension, diabetes, or hyperlipidemia. METHODS: Patients diagnosed with acute ischemic stroke (AIS) were recruited from 2015 to 2017 in Chinese Stroke Center Alliances. We estimated daily PM2.5 average exposures with a spatial resolution of 0.1° using a data assimilation approach combining satellite measurements, air model simulations, and monitoring values. Conditional logistic regression was used to assess PM2.5-related stroke risk in patients with pre-existing medical co-morbidities. RESULTS: A total of 155,616 patients diagnosed with AIS were admitted. Patients with a history of AF (n = 15,430), hypertension (n = 138,220), diabetes (n = 43,737), or hyperlipidemia (n = 16,855) were assessed separately. A 10 µg/m3 increase in daily PM2.5 was associated with a significant increase in AIS for individuals with AF at lag 4 (odds ratio (OR), 1.008; 95% confidence interval (CI), 1.002-1.014), and with hypertension (OR, 1.008; 95% CI, 1.006-1.010), diabetes (OR, 1.006; 95% CI, 1.003-1.010), and hyperlipidemia (OR, 1.007; 95% CI, 1.001-1.012) at lags 0-7. Elderly (⩾ 65 years old) and female patients with AF had significantly higher associations at lag 5 (OR, 1.009; 95% CI, 1.002-1.015) and lag 5 (OR, 1.010; 95% CI, 1.002-1.018), respectively. CONCLUSION: Short-term exposure to PM2.5 is significantly associated with hospital admission for stroke in individuals with pre-existing medical histories, especially in older or female patients with AF. Preventive measures to reduce PM2.5 concentrations are particularly important in individuals with other medical co-morbidities.

A Comprehensive Circulating Tumor DNA Assay for Detection of Translocation and Copy-Number Changes in Pediatric Sarcomas.

Most circulating tumor DNA (ctDNA) assays are designed to detect recurrent mutations. Pediatric sarcomas share few recurrent mutations but rather are characterized by translocations and copy-number changes. We applied Cancer Personalized Profiling by deep Sequencing (CAPP-Seq) for detection of translocations found in the most common pediatric sarcomas. We also applied ichorCNA to the combined off-target reads from our hybrid capture to simultaneously detect copy-number alterations (CNA). We analyzed 64 prospectively collected plasma samples from 17 patients with pediatric sarcoma. Translocations were detected in the pretreatment plasma of 13 patients and were confirmed by tumor sequencing in 12 patients. Two of these patients had evidence of complex chromosomal rearrangements in their ctDNA. We also detected copy-number changes in the pretreatment plasma of 7 patients. We found that ctDNA levels correlated with metastatic status and clinical response. Furthermore, we detected rising ctDNA levels before relapse was clinically apparent, demonstrating the high sensitivity of our assay. This assay can be utilized for simultaneous detection of translocations and CNAs in the plasma of patients with pediatric sarcoma. While we describe our experience in pediatric sarcomas, this approach can be applied to other tumors that are driven by structural variants.

[Gene polymorphism in oral lichen planus].

Oral lichen planus (OLP) is a common chronic inflammatory disease of the oral mucosa. The prevalence rate of OLP in adults is 0.5%-2%. The etiology and pathogenesis of OLP are still unclear. The pathogenesis of OLP may be related to the genetic polymorphism of some genes. Currently, the gene families, including tumor necrosis factor, interferon, interleukin, enzyme, and receptor, have been extensively studied. This work reviews related studies on gene polymorphism of OLP.

Comparative Tumor RNA Sequencing Analysis for Difficult-to-Treat Pediatric and Young Adult Patients With Cancer.

Importance: Pediatric cancers are epigenetic diseases; therefore, considering tumor gene expression information is necessary for a complete understanding of the tumorigenic processes. Objective: To evaluate the feasibility and utility of incorporating comparative gene expression information into the precision medicine framework for difficult-to-treat pediatric and young adult patients with cancer. Design, Setting, and Participants: This cohort study was conducted as a consortium between the University of California, Santa Cruz (UCSC) Treehouse Childhood Cancer Initiative and clinical genomic trials. RNA sequencing (RNA-Seq) data were obtained from the following 4 clinical sites and analyzed at UCSC: British Columbia Children's Hospital (n = 31), Lucile Packard Children's Hospital at Stanford University (n = 80), CHOC Children's Hospital and Hyundai Cancer Institute (n = 46), and the Pacific Pediatric Neuro-Oncology Consortium (n = 24). The study dates were January 1, 2016, to March 22, 2017. Exposures: Participants underwent tumor RNA-Seq profiling as part of 4 separate clinical trials at partner hospitals. The UCSC either downloaded RNA-Seq data from a partner institution for analysis in the cloud or provided a Docker pipeline that performed the same analysis at a partner institution. The UCSC then compared each participant's tumor RNA-Seq profile with more than 11 000 uniformly analyzed tumor profiles from pediatric and young adult patients with cancer, downloaded from public data repositories. These comparisons were used to identify genes and pathways that are significantly overexpressed in each patient's tumor. Results of the UCSC analysis were presented to clinical partners. Main Outcomes and Measures: Feasibility of a third-party institution (UCSC Treehouse Childhood Cancer Initiative) to obtain tumor RNA-Seq data from patients, conduct comparative analysis, and present analysis results to clinicians; and proportion of patients for whom comparative tumor gene expression analysis provided useful clinical and biological information. Results: Among 144 samples from children and young adults (median age at diagnosis, 9 years; range, 0-26 years; 72 of 118 [61.0%] male [26 patients sex unknown]) with a relapsed, refractory, or rare cancer treated on precision medicine protocols, RNA-Seq-derived gene expression was potentially useful for 99 of 144 samples (68.8%) compared with DNA mutation information that was potentially useful for only 34 of 74 samples (45.9%). Conclusions and Relevance: This study's findings suggest that tumor RNA-Seq comparisons may be feasible and highlight the potential clinical utility of incorporating such comparisons into the clinical genomic interpretation framework for difficult-to-treat pediatric and young adult patients with cancer. The study also highlights for the first time to date the potential clinical utility of harmonized publicly available genomic data sets.

Genome-Informed Targeted Therapy for Osteosarcoma.

Osteosarcoma is a highly aggressive cancer for which treatment has remained essentially unchanged for more than 30 years. Osteosarcoma is characterized by widespread and recurrent somatic copy-number alterations (SCNA) and structural rearrangements. In contrast, few recurrent point mutations in protein-coding genes have been identified, suggesting that genes within SCNAs are key oncogenic drivers in this disease. SCNAs and structural rearrangements are highly heterogeneous across osteosarcoma cases, suggesting the need for a genome-informed approach to targeted therapy. To identify patient-specific candidate drivers, we used a simple heuristic based on degree and rank order of copy-number amplification (identified by whole-genome sequencing) and changes in gene expression as identified by RNA sequencing. Using patient-derived tumor xenografts, we demonstrate that targeting of patient-specific SCNAs leads to significant decrease in tumor burden, providing a road map for genome-informed treatment of osteosarcoma. SIGNIFICANCE: Osteosarcoma is treated with a chemotherapy regimen established 30 years ago. Although osteosarcoma is genomically complex, we hypothesized that tumor-specific dependencies could be identified within SCNAs. Using patient-derived tumor xenografts, we found a high degree of response for "genome-matched" therapies, demonstrating the utility of a targeted genome-informed approach.This article is highlighted in the In This Issue feature, p. 1.