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Supplementary Figure 1 from Prognostic Significance of Growth Kinetics in Newly Diagnosed Glioblastomas Revealed by Combining Serial Imaging with a Novel Biomathematical Model

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Supplementary Methods, Figure and Table Legend from Prognostic Significance of Growth Kinetics in Newly Diagnosed Glioblastomas Revealed by Combining Serial Imaging with a Novel Biomathematical Model

Glioblastomas are the most aggressive primary brain tumors, characterized by their rapid proliferation and diffuse infiltration of the brain tissue. Survival patterns in patients with glioblastoma have been associated with a number of clinicopathologic factors including age and neurologic status, yet a significant quantitative link to in vivo growth kinetics of each glioma has remained elusive. Exploiting a recently developed tool for quantifying glioma net proliferation and invasion rates in individual patients using routinely available magnetic resonance images (MRI), we propose to link these patient-specific kinetic rates of biological aggressiveness to prognostic significance. Using our biologically based mathematical model for glioma growth and invasion, examination of serial pretreatment MRIs of 32 glioblastoma patients allowed quantification of these rates for each patient's tumor. Survival analyses revealed that even when controlling for standard clinical parameters (e.g., age and Karnofsky performance status), these model-defined parameters quantifying biological aggressiveness (net proliferation and invasion rates) were significantly associated with prognosis. One hypothesis generated was that the ratio of the actual survival time after whatever therapies were used to the duration of survival predicted (by the model) without any therapy would provide a therapeutic response index (TRI) of the overall effectiveness of the therapies. The TRI may provide important information, not otherwise available, about the effectiveness of the treatments in individual patients. To our knowledge, this is the first report indicating that dynamic insight from routinely obtained pretreatment imaging may be quantitatively useful in characterizing the survival of individual patients with glioblastoma. Such a hybrid tool bridging mathematical modeling and clinical imaging may allow for stratifying patients for clinical studies relative to their pretreatment biological aggressiveness. [Cancer Res 2009;69(23):9133–40]

Supplementary Table 1 from Prognostic Significance of Growth Kinetics in Newly Diagnosed Glioblastomas Revealed by Combining Serial Imaging with a Novel Biomathematical Model

Glioblastoma multiforme is the most aggressive type of primary brain tumor. Glioblastoma growth dynamics vary widely across patients, making it difficult to accurately gauge their response to treatment. We developed a model-based metric of therapy response called Days Gained that accounts for this heterogeneity. Here, we show in 63 newly diagnosed patients with glioblastoma that Days Gained scores from a simple glioblastoma growth model computed at the time of the first postradiotherapy MRI scan are prognostic for time to tumor recurrence and overall patient survival. After radiation treatment, Days Gained also distinguished patients with pseudoprogression from those with true progression. Because Days Gained scores can be easily computed with routinely available clinical imaging devices, this model offers immediate potential to be used in ongoing prospective studies. Cancer Res; 73(10); 2976–86. ©2013 AACR.

Purpose: Hypoxia is associated with resistance to radiotherapy and chemotherapy and activates transcription factors that support cell survival and migration. We measured the volume of hypoxic tumor and the maximum level of hypoxia in glioblastoma multiforme before radiotherapy with [18F]fluoromisonidazole positron emission tomography to assess their impact on time to progression (TTP) or survival. Experimental Design: Twenty-two patients were studied before biopsy or between resection and starting radiotherapy. Each had a 20-minute emission scan 2 hours after i.v. injection of 7 mCi of [18F]fluoromisonidazole. Venous blood samples taken during imaging were used to create tissue to blood concentration (T/B) ratios. The volume of tumor with T/B values above 1.2 defined the hypoxic volume (HV). Maximum T/B values (T/Bmax) were determined from the pixel with the highest uptake. Results: Kaplan-Meier plots showed shorter TTP and survival in patients whose tumors contained HVs or tumor T/Bmax ratios greater than the median (P ≤ 0.001). In univariate analyses, greater HV or tumor T/Bmax were associated with shorter TTP or survival (P < 0.002). Multivariate analyses for survival and TTP against the covariates HV (or T/Bmax), magnetic resonance imaging (MRI) T1Gd volume, age, and Karnovsky performance score reached significance only for HV (or T/Bmax; P < 0.03). Conclusions: The volume and intensity of hypoxia in glioblastoma multiforme before radiotherapy are strongly associated with poorer TTP and survival. This type of imaging could be integrated into new treatment strategies to target hypoxia more aggressively in glioblastoma multiforme and could be applied to assess the treatment outcomes.

Background: Current cancer treatments have different mechanisms and variable responses in most histologic groups. The ability to determine treatment response at the molecular level by measuring tumor thymidine kinase 1 activity is being evaluated with FLT PET in groups of patients with different tumor histology. Methods: Under FDA IND approved protocols, patients treated on standard clinical and clinical trial protocols for glioblastoma, carcinoma brain metastases, breast cancer, and AML underwent quantitative PET imaging with FLT at baseline, mid-therapy, and post therapy. Dynamic acquisitions of the sites of known tumor were acquired for 60 minutes, followed by a whole-body static image survey. All images were reconstructed with CT attenuation correction. Regions of interest for the tumor, liver, and surrounding tissues were analyzed for uptake at each data time. Regional tissue FLT uptake was described as the tissue standard uptake variable (SUV), and FLT transport (K1) and flux using a compartmental model analysis. The tumor K1 values were generated to quantify FLT delivery to tumor. Comparisons were made between FLT-PET obtained at sequential times in individual patients and with clinical response. Results: At this time, 19 patients with primary brain tumors, 3 patients with brain metastases, 9 breast cancer patients, and 7 AML patients have been enrolled; at least one post-therapy image has been completed in all but 2 patients. The results have been analyzed semi-quantitatively as SUV and quantitatively by compartmental modeling to determine K1 and flux values for tumor baseline and post therapy comparisons. In most tumors, uptake by either SUV or flux declined in response to treatment but trends in tumor SUV values were not consistent with FLT flux values. In several cases, the FLT K1 and flux values were divergent, emphasizing the requirement to account for FLT delivery changes in observed tumor activity in response to therapy. This effect was most prominent in brain tumors and AML patients. Tumor blood flow/delivery is likely an independent response parameter that can be estimated from analysis of dynamic FLT PET. The poster will show evaluation of the predictive ability of baseline FLT studies as well as the role of pre/post comparisons. Conclusions: FLT PET imaging shows increased tumor uptake across several histologic types. This uptake decreases significantly with therapy, however the flow/delivery parameters and flux values from imaging are important uptake parameters to consider individually to understand changes in response to therapy. Supported by NIH/NCI P01 CA042045-23 and S10 RR017229. Citation Information: Mol Cancer Ther 2013;12(11 Suppl):B147. Citation Format: Janet F. Eary, Jeanne M. Link, Mark Muzi, Finbarr O'Sullivan, Jason K. Rockhill, James R. Fink, Hannah M. Linden, Kenneth A. Krohn. Tumor response imaging with [F-18] fluorothymidine (FLT). [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2013 Oct 19-23; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2013;12(11 Suppl):Abstract nr B147.

Background: Gliomas are the most common primary brain tumors and their prognosis is related to WHO histopathological grade. Glioblastoma (grade IV astrocytoma or GBM) is characterized by microscopic invasion into surrounding brain and universally poor prognosis despite treatment with surgery, radiation and chemotherapy . Recently, the matricellular protein periostin (POSTN) has been shown to be associated with increased parenchymal invasion (measured by edema on MRI) and poor prognosis in GBM. The specific aim of the present analysis was to determine the mechanistic impact of POSTN on glioma outcome. Methods: We used the gene expression of POSTN from 559 GBM patients (pts) included in the Cancer Genome Atlas (TCGA) to build a gene expression model of the expression of 12184 genes to predict POSTN expression using elastic net. This model was used to predict the POSTN expression in a testing set of 419 pts with gliomas included in Repository for Brain Neoplasia Data (REMBRANDT) (99 grade II, 71 grade III and 125 grade IV and 124 with no grade). Receiver-operating characteristic (ROC) and survival analysis were performed to measure the performance of the model, and gene-set enrichment analysis (GSEA) was used to reveal network topology perturbations. Results: The gene expression model discovered 721 genes highly correlated to POSTN expression that predict POSTN in the testing set with an area under the curve (AUC) of 0.96 on ROC curve. GSEA reveals genes involved in “mesenchymal transition,” transition of invasive ductal carcinoma (IDC) from ductal carcinoma in situ (DCIS) in breast cancer and stem cell signatures. Survival analysis of the TCGA GBM pts showed that the cohort with “high POSTN” had worse survival (median 12 months versus 15 months, log-rank p=0.0002). When applied to all pts in REMBRANDT, the model predicted classes also had significantly different survival (median 13.4 versus 38 months, log-rank p Conclusions: We have developed a gene expression model related to POSTN, a gene linked to poor prognosis in GBM, to investigate the role correlated genes may play in the aggressive phenotype. Some of the genes found to be highly correlated to POSTN are related to mesenchymal transition, invasive behavior in breast cancer and stemness. We verify that high POSTN expression is a strong prognostic indicator for poor outcome in GBM, and reveal for the first time that pts with grade II and III glioma with a “high” POSTN signature have significantly worse survival. Given that low grade glioma pts often have less aggressive treatment at time of diagnosis, we propose studying the role of early chemoradiation in the subset of pts with poor POSTN signature to potentially improve their outcome. Citation Format: Andrew D. Trister, Andrei M. Mikheev, Jason K. Rockhill, Stephen H. Friend, Robert C. Rostomily. Periostin expression in glioma correlates with genes related to mesenchymal transition and survival. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 1210. doi:10.1158/1538-7445.AM2013-1210

Molecular imaging with PET is most commonly associated with tumor detection and staging, currently with [F-18]-fluorodeoxyglucose (FDG-PET) to measure energy metabolism. However other imaging agents can be used to measure important characteristics of tumors that have the potential to guide in therapy selection or provide an early indication of response to therapy. Even though there are enthusiastic predictions of the role that “omics” biomarkers will play in personalized medicine, imaging biomarkers have some practical advantages over tissue and serum biomarkers. Imaging characterizes the entire tumor burden in the context of its environment and it can be repeated frequently. Several new PET agents are becoming widely available to probe important aspects of the tumor phenotype. The UW NCI-sponsored program project is developing PET to image tumor cancer biology with new agents that examine the tumor phenotype and how it changes in response to therapy. There are many biological factors that can influence response of an individual patient to cancer therapy. Evaluation of these factors provides the questions and hypotheses posed in the UW PPG. The group focuses on investigations of reasons for poor tumor response to treatment. Hypoxia, cellular proliferation, low abundance of therapeutic targets (e.g. estrogen receptors) and acquired multidrug resistance (MDR/P-gp) are some of the imaging targets. These tumor variables can be quantified by PET imaging with [F-18]-fluoromisonidazole, [F-18]-3′-fluoro-3′-deoxythymidine, [F-18]-16α-fluoroestradiol and [C-11]-verapamil, respectively. Because hypoxia is a common characteristic of tumors but it is heterogeneous within a tumor mass and differs between tumor sites in a patient, imaging has an important role in assessing regional tumor tissue oxygenation. [F-18]-Fluoromisonidazole (FMISO) developed by our group is a PET hypoxia-imaging probe that accumulates at low PO2. Imaging results with this agent have demonstrated tumor hypoxic volume is an independent predictor of overall survival in patients with head and neck cancer, soft tissue sarcoma and primary brain tumors. PET can also be used to image the response mechanism of a tumor to therapy. Current therapies are cytotoxic or cytostatic, with some combinations that are overlapping or aimed at a particular phosphokinase pathway. Uncontrolled tumor growth results from dysregulation of cellular proliferation and/or deficiencies in programmed cell death. FDG has been advocated for monitoring this net process but there are many contributors to energy metabolism in tumors, thus reducing the specificity of FDG-PET for evaluating tumor response. Thymidine and its analogs can be used to image the salvage pathway of cellular proliferation (DNA synthesis) with better specificity because these nucleosides are accumulated and phosphorylated during cellular S-phase. The UW PET group developed [F-18]-3′-fluoro-3′-deoxythymidine (FLT) for this purpose. Our recent studies have focused on the challenge of distinguishing whether clinical symptoms and standard imaging appearance after therapy is predominantly a result of tumor progression or radionecrosis/pseudoprogression in patients with primary brain tumors. This application of FLT-PET emphasizes the value of dynamic imaging to separate the blood flow or delivery phase of the imaging agent from its tumor incorporation as a flux through the DNA salvage pathway. Segmentation algorithms and compartmental analyses are being used to generate parametric maps of regional tumor transport and synthetic flux. In several study results, the flux parametric image in recurrent brain tumors shows much higher FLT accumulation (salvage pathway activity) than in tumors with pseudo-progression whereas the transport images overlap between the two groups. Imaging the P-gp drug resistance mechanism is performed using [C-11]-verapamil, a substrate for the transporter similar to the anthracyclines, which are the mainstay of many chemotherapy regimens. Preliminary work in sarcoma patients has shown that levels of P-gp activity are variable in tumors at presentation and change in response to therapy, usually resulting in an increase in activity. This increase in P-gp activity may confirm clinical suspicion that drug resistance has been induced in an individual as an important contributor to treatment resistance. In summary, PET imaging provides an important tool for selecting patients with specific mechanisms of resistance to cancer therapy so that new drugs can be used with maximum effectiveness. PET imaging results can also provide useful biomarkers for tumor response to standard and experimental therapy, and will be important contributors towards the goal of personalized medicine for cancer patients. The UW PET group has worked with NCI-CIP to develop INDs for FMISO and FLT that are now used in multicenter trials. The group has also developed methods for analysis of FMISO and FLT images and provides a resource for image analysis in the trials. Both of these imaging agents, and approaches to acquiring and analyzing their images, are widely available to nuclear medicine clinical research groups to contribute toward progress in understanding cancer and its response to therapy. The research results to be presented were supported by P01 CA042045-22. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr SY42-02. doi:1538-7445.AM2012-SY42-02