Ultrasonography of Osteosarcoma in Dogs
Sonography Atlas of Dogs

Keywords: Personalized medicine, Feasibility trial, Canine, Osteosarcoma, Gene expression, Drug prediction

Background

The treatment of cancer is constantly evolving towards the integration of ever advancing knowledge of disease processes and improvements in molecular and computational technologies. Until recently, approaches towards the treatment of cancer have been disease centric and predominantly determined on the basis of histological classification [1-3]. However, the disparate responses of patients to a given agent with “the same” disease defined through this method of nosology has been attributed to significant molecular heterogeneity within phenotypically defined tumors, and demands the inclusion of molecular biomarkers towards the improved classification of cancers [4,5].

The last 20 years has seen an explosion in both genomic and proteomic technologies, that have assisted in increasing our understanding of disease heterogeneity and have aggressively driven the focus of both drug discovery and development towards the fundamental molecular drivers of disease. Advances in molecular and computational technologies now permit the global analysis of the genome, epigenome, proteome and metabolome at unprecedented granularity, and provide opportunities to study disease heterogeneity within an individual and across populations. This revolution in technologies has made the promise of personalized medicine a reality, through which health care can be customized/tailored for an individual based on information derived from the patient and/or their disease [6]. In the sub-branch of personalized medicine often referred to as pharmacogenomics or precision therapeutics, molecular biomarkers are being used with increased frequency to identify agents with predicted efficacy (and/or reduced toxicity). Oncology is driving the adoption of PMed, where examples include the recommended administration of trastuzumab for tumors exhibiting HER-2 receptor gene amplification or protein over-expression, tamoxifen in breast cancers overexpressing the estrogen receptor, imatinib in the treatment of AML harboring the BCR-ABL translocation [7], and Vemurafinib in the treatment of melanomas carrying the BRAF V600E/K mutation [8]. In addition to these relatively simple drug-single biomarker rules, gene/protein panels are increasingly being use in the diagnostic/prognostic setting to identify patients that would best benefit from neoadjuvant or adjuvant therapy [9-12]. Germline determinants of drug response in key drug metabolism enzymes such as CYP450 have also been identified and are being assessed for their ability to optimize the therapeutic index of agents in the clinic [13]. Such examples are a clear indication that the field of oncology is moving towards rational selection of appropriate therapies for individual patients. However, these tests are limited in that they do not provide global coverage of the genome, and are restricted to a handful of select agents and cancer types. It is clear that a more comprehensive and systematic approach is required to maximize the utility of new genomic and computational technologies and expand drug coverage, and thereby more rapidly and broadly advance the implementation of precision therapy in oncology.

Optimization of PMed through human clinical trials is challenging as refinement of these methods is frequently muddied against a background of standard of care therapy and therapeutic refractoriness. Preclinical mouse models, although offering the advantages of low cost, accelerated endpoints, and ease of genetic manipulation are far from adequate [14]. Human cancers arise spontaneously and are polygenic involving coordinate networks of genes that evolve over time, whilst transgenic mouse models primarily involving the modulation of one or two genes to drive rapid onset malignancies. The classical human cell line-xenograft mouse model used predominantly in drug development typically requires an immune compromised background, thus eliminating the influence of a syngeneic environment in the development of the disease. The emergence of tumorgraft (patient-derived tumor xenografts) models has advanced the field of in vivo cancer models due to reduced genetic drift, persistence of human tumor heterogeneity, and maintenance of the tumor microenvironment [15,16]. However, these models also typically require immune compromised mice and are sub-optimal when compared to spontaneously arising cancers in non-laboratory subjects.

To address the void between preclinical models and clinical medicine, many researchers have increasingly turned to comparative oncology as an alternative clinical model of human disease. Comparative oncology describes the study of spontaneous cancers in non-human species, most frequently referring to those animals that are considered pets/companions [17,18]. Canines, in particular, have rapidly risen to become a favored model for the study of human disease with around 400 inherited diseases that have cognate human conditions [19]. Studies have shown that canines are far superior models of human cancers than rodents, being more similar histologically and molecularly at the levels of both DNA and protein sequence [20]. Stark similarities in the molecular drivers of disease, including oncogenes, tumor suppressors and mutations have all been shown to contribute to the development of cancer in both dogs and humans [21]. Additional factors in favor of the selection of canines as a translational model include a shared environment, the contribution of etiological factors including nutrition, age and sex, and analogous diagnostic and interventional procedures used in veterinary and human healthcare (reviewed in [17,18,22]). Genetically, canines are ideal candidates to study the fundamental genetic drivers of human disease, owing to the breed specific proclivity of particular cancer types. This phenomenon has arisen following approximately 200 years of inbreeding, restricting the genetic flow between breeds, consequently selecting for founder mutations that are associated with breed specific traits and disease [21,23]. Canines age 5-8-times more rapidly than humans, which provides an opportunity to study diseases that are age related [18]. Similarly, and in part due to less aggressive disease management, cancer progression is quicker in dogs, with the average disease-free interval being 18 months compared to 7 years in humans [17]. This has significant benefits as it enables shorter clinical trials, which, alongside similar response to conventional (human) therapeutic regimes, support the use of canine subjects in early clinical trials. The lack of established standard of care treatments for canines also provides an opportunity to evaluate novel therapies and protocols in subjects with less advanced, non-refractory (even naïve) disease, prospects that are difficult to impossible in human patients [17].

Osteosarcoma (OSA) is an ideal disease candidate for inter-species investigation of personalized medicine approaches. It has been shown that canine and human OSA are analogous at a number of levels, histologically, behaviorally, genetically and with regards to response to therapy (reviewed by [18,22,24]). The incidence of OSA in dogs is 20-fold greater than in humans [25], with around 10,000 canines diagnosed per year compared to approximately 2,650 primary bone tumors in humans (a statistic which includes OSA, chondrosarcoma, Ewings sarcoma and malignant fibrous histiocytoma) [18], therefore increasing the number of subjects that are available for recruitment into clinical trials. OSA occurs primarily at around 7–9 years of age [26], with large and giant breeds (e.g. Saint Bernards Greyhounds, Great Danes, German Shepherds, Golden Retrievers) having a 60-fold greater risk of developing OSA [27,28]. Following amputation alone, >90% of dogs die within a year, with cause of death being related to the development of metastasis, typically to the lung [26]. Adjuvant chemotherapy can further improve survival from 103–175 days following surgery alone, to 262–450 days (review – [24]). Even considering these dramatic changes in survival time, the long-term prognosis for OSA is morose and 2 year survival has been measured at between 10-26% [24]. It is the poor long term survival of canines with OSA, along with the translational value for the corresponding human disease, which makes this tumor an ideal candidate for the identification of novel therapeutic agents using PMed approaches.

In this report we outline the results of a 20 subject feasibility study in canine osteosarcoma, with the key goal of establishing the infrastructure and logistics for a subsequent prospective large scale PMed trial. The design of this study was not intended to validate the clinical utility of a PMed report in dogs with cancer. We describe the utility of global gene expression profiling of osteosarcomas from canine patients, which in parallel with advances in laboratory procedures, bioinformatics tools and a physician reporting interface permits the application of real-time genomic medicine in the context of veterinary medicine. Gene expression profiling is a tool that has been used by other groups to examine canine osteosarcoma to identify differentially expressed genes that can stratify patients as short or long-term survival [29] and identify biomarkers and pathways associated with patient prognosis [30].

The PMed system utilized here is an assembly of 5 predictive methodologies that rank the overall drugs predictions weighted by the number of methods which predict the drug, frequency of inclusion (multiple targets for a drug) and strength of prediction (high differential expression above the normal reference). The PMed system is drug centric and focused around 183 FDA approved medications (see Additional file 1: Table S1). Drug target expression [31] and drug sensitive/resistant Biomarker rules [32] are both linked directly to the expression levels of individual genes. Two of the methods namely Drug sensitivity signatures – PGSEA [33] and Drug Response Signatures-CMAP [34], use global gene expression patterns which have been associated with drug effectiveness. The fifth method uses a global gene-gene interaction database, to identify putative drug targets based on topological analysis of differentially expressed genes that are up or downstream of transcriptional events (Network Target activity [35]). Global gene expression analysis (microarray) has been used in both a clinical trial where it was shown to benefit progression free survival [32] and in vitro to better predict pharmacological response [36].

Within this investigational trial, we established a number of objectives including; a) to establish a timely process for the collection, shipping, processing and diagnosis of tumor samples from canine osteosarcoma patients, and; b) to determine the feasibility of generating a PMed report from predictive modeling of canine tumor-derived gene expression data within 5 business days of sample receipt. Although this study was not designed to include a treatment arm, we collected the opinions of the practicing veterinarians regarding the potential clinical utility of the PMed report. We identified that, while the presentation of the PMed report to the veterinarian in a timely fashion is critical to support the clinical management of the disease, the interpretation and implementation of the report by the clinician is essential for the success of PMed Trials and clinical adoption in the future.

 

Methods

Study overview

The study design and overall processes are summarized in Figure 1. In brief, the study involved the identification and recruitment of 20 mixed breed or purebred dogs with suspected appendicular OSA. The MiniMax approach was used to identify 20 patients as a suitable sample size for this study. Based on previous work the expected censor rate due to sample quality and diagnosis was conservatively estimated at 25% (5 patients). In this regard an initial patient population of 20 patients provided sufficient power for statistical significance if 70% of the samples (11 of 15) were completed in the 5-day targeted time limit. The presumptive diagnosis of OSA was based on review of limb radiographs or from histology performed pre-study. Study dogs were screened and samples collected at Animal Clinical Investigation (ACI) network clinics. Ethical approval for this study was granted by the respective Institutional Animal Care and Use Committees (IACUC) at the Van Andel Research Institute (VARI), Zoetis and Animal Clinical Investigations (ACI). All procedures and veterinary care provided to each patient was performed by trained veterinary specialists who followed standard clinical or protocol driven procedures as documented in the study documentation training files. For those patients that met the inclusion criteria, the amputation surgery was scheduled at which time the tumor collection was performed. The appropriate samples were sent to VARI, processed and submitted to Clinical Reference Laboratory (CRL) for genomic profiling. Following receipt of the Affymetrix gene expression data from CRL, it was imported into VARI’s database and input into the PMed analysis/reporting system. The PMed report was then distributed to ACI, who further distributed to the collection sites and obtained responses to a questionnaire regarding the clinical utility of the provided PMed report.

 

Figure 1: Process diagram defining the steps and timing of the osteosarcoma PMed feasibility study. The figure highlights the numerous steps, which are grouped by day (color), that were followed in order to produce a PMed report in 5 business days from the receipt of the sample.

Site training

Prior to the start of the study, training was provided to each of the participating veterinary practices with regards to the sampling of the tumor from the amputated limbs. Specific instructions were provided as to where best to harvest tumor tissue to minimize normal tissue contamination and bone involvement which could complicate downstream procedures, e.g. cryo-sectioning of snap frozen tissue for RNA extraction and H&E sectioning. The primary site of harvest was designated as grossly viable, unmixed tissue present at the advancing front of the tumor. This site was commonly identified outside of the marrow space, and was evident in the majority of cases. The medullary cavity was identified as the secondary site of harvest.

 

Normal tissue reference

The purpose of the reference set is to facilitate comparative analysis of the fundamental differences of the tumor versus a biologically appropriate denominator, i.e. normal tissue capturing the cell(s) of origin of the tumor. Due to the practical challenges in obtaining breed, age and sex matched disease-free normal bone in a study that was open to all breeds, combined with the need to have the reference set available prior to the start of enrollment, five total bone samples (cortical bone and marrow) were collected from 5 disease free Beagles. These five normal samples were processed identically to the tumor samples in order to provide a tissue specific reference for the tumor samples. Standard statistics consisting of mean and standard deviation were compiled for each probe set across the reference samples. The tumor sample probe sets intensities were transformed to Z-Score by utilizing the reference sample probe set mean and standard deviation. This score was subsequently utilized by the PMed methods to suggest possible therapies.

 

Tissue processing

Upon receipt at VARI, the samples were logged and processed immediately. For the purpose of this study, Day 1 was considered to be the time at which tissue processing (RNA isolation and pathology) commenced. In the case where samples were received on a Friday (or on the weekend), day 1 automatically defaulted to the next business day. When sample processing was delayed, formalin fixed samples were transferred to 70% ethanol (to avoid over fixation) and stored at room temperature (RT), while snap frozen samples were stored at −80°C.

 

Snap frozen

The snap frozen tissue was maintained on dry ice and immediately embedded in Optimal Cutting Temperature (Tissue-Tek® O.C.T.) media, which was used to hold the tissue in position during cryosectioning. When possible, two 5 μM sections above and below preparative RNA cuts were taken (mounted together on a single slide) and stained with hematoxylin and eosin (H&E). The H&E slides were scanned using an Aperio ScanScope XT (Aperio, Vista, CA.), and uploaded to a centralized location for evaluation by an off-site veterinary pathologist. In between the H&E sections, 8-10x 50 μM slices were collected for RNA extraction.

 

Formalin fixed

Due to the production of mineralized osteoid by osteosacrcomas which can hinder the sectioning of the tissue, the formalin fixed sample was decalcified for 3 hours in Formic-Decal solution (Rowley Biochemical, MA), followed by a 1 hr. wash in running tap water. The tissue was subsequently processed overnight into paraffin, embedded, sectioned and stained with H&E. These slides were also scanned using the Aperio ScanScope XT and the image uploaded to a centralized location for review by the veterinary pathologist.

 

RNA extraction

Total RNA was isolated directly from the OCT sections using Trizol, with an initial homogenization for 2 minutes at 40 oscillations/second using the TissueLyser LT (Qiagen), followed by a DNase digestion and RNA clean-up using Qiagen RNeasy Mini Kit. Following elution in H₂O, the RNA was analyzed spectrophotometrically (Nanodrop) to determine RNA yield and purity (A260/280). RNA integrity was subsequently determined using the Agilent RNA 6000 Nano Kit on the Agilent Bioanalyzer 2100 (Agilent Technologies, Inc. CA.). In order for samples to proceed to Affymetrix GeneChip profiling, three RNA QC parameters had to be met; RNA yield >20 ng, A260/280 ≥1.8, and an RNA Integrity Number (RIN) ≥ 6.0. The RNA integrity number is generated by an algorithm which uses the entire electrophoretic trace of the RNA sample, rather than just the ribosomal bands, to assess the presence or absence of degradation products. A RIN is calculated by the software that interprets a sample’s RNA electropherogram, independent of concentration, and assigns a number between 1 (highly degraded) and 10 (intact) [37]. Samples that passed these criteria were immediately shipped overnight on dry ice to a CLIA (Clinical Laboratory Improvement Amendments) certified external contract laboratory (CRL). Samples failing any of these QC parameters were not sent for pathological review and were censored from the study and classified as a fail.

 

Pathological assessment and diagnosis

The primary pathological assessment was made using the H&E sections from the OCT embedded snap frozen tissue, taken immediately adjacent (above and below) to the 50 μM sections used for the RNA extraction. In the event that the OCT H&E section were unavailable (e.g. the tissue couldn’t be cut at 5 μM sections) the H&E section from the FFPE tissue (derived from the same tumor mass) was used. In either case, the pathologist was provided with H&E images from both sample types, in the event that the snap frozen H&E section was not of sufficient quality to make a clear diagnosis and determination of tissue composition. The tissue sections were assessed for % viable tumor (by Nuclei), % viable normal tissue (by nuclei) and % Necrosis; to pass QC these values needed to be ≥50%, <50% and ≤20%, respectively. Failure of any of these QC parameters resulted in censoring from the study and classification as a fail.

 

Gene expression analysis

Upon receipt of the sample at the CLIA Certified Laboratory the following day (Day 2), the RNA samples were held and processing delayed until the results of the pathological assessment were available. Samples, that passed pathological QC, were then subject to a second RNA QC (as described above) as required by the CLIA laboratory Standard Operating Procedure (SOP) to ensure no loss in RNA integrity during shipment and thaw. Fifty nanograms of total RNA was used for cDNA synthesis and amplification using the NuGEN Ovation Pico WTA System (NuGEN Technologies, Inc. CA), following which additional cDNA QC checks were performed (total cDNA yield ≥5 μg, A260/280 ≥1.8). Following fragmentation and labeling (NuGEN Encore Biotin Module) the cDNA was hybridized overnight to the Affymetrix Canine 2.0 array. The arrays were then washed, labeled (GeneChip Hybridization, wash and stain kit, Affymetrix, Inc. CA.) and scanned using the Affymetrix gene chip scanner 3000 7G. The image file produced by the scanner was subsequently analyzed using the Affymetrix Expression Console producing .CEL and .DAT files, from which additional post-analysis QC pass/fail criteria were recorded, including, background (<100), percent present (>30%), scale factor (<100), spiked controls: 3’ signal (bioB < bioC < bioD < cre) and a visual inspection of the image file for surface anomalies. Post-analysis QC failures would result in the data not being submitted for PMed report generation. Upon passing all criteria, a MAS5.0 normalization process was performed producing a tab delimited pivot table with probe identifiers, quality scores, present calls, and intensities. All quality information and data files along with the original image files were uploaded to a secure FTP site hosted at VARI.