Jason K. Rockhill

Regional Hypoxia in Glioblastoma Multiforme Quantified with [18F]Fluoromisonidazole Positron Emission Tomography before Radiotherapy: Correlation with Time to Progression and Survival

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.

Predicting the efficacy of radiotherapy in individual glioblastoma patients in vivo: a mathematical modeling approach

Glioblastoma multiforme (GBM) is the most malignant form of primary brain tumors known as gliomas. They proliferate and invade extensively and yield short life expectancies despite aggressive treatment. Response to treatment is usually measured in terms of the survival of groups of patients treated similarly, but this statistical approach misses the subgroups that may have responded to or may have been injured by treatment. Such statistics offer scant reassurance to individual patients who have suffered through these treatments. Furthermore, current imaging-based treatment response metrics in individual patients ignore patient-specific differences in tumor growth kinetics, which have been shown to vary widely across patients even within the same histological diagnosis and, unfortunately, these metrics have shown only minimal success in predicting patient outcome. We consider nine newly diagnosed GBM patients receiving diagnostic biopsy followed by standard-of-care external beam radiation therapy (XRT). We present and apply a patient-specific, biologically based mathematical model for glioma growth that quantifies response to XRT in individual patients in vivo. The mathematical model uses net rates of proliferation and migration of malignant tumor cells to characterize the tumors growth and invasion along with the linear-quadratic model for the response to radiation therapy. Using only routinely available pre-treatment MRIs to inform the patient-specific bio-mathematical model simulations, we find that radiation response in these patients, quantified by both clinical and model-generated measures, could have been predicted prior to treatment with high accuracy. Specifically, we find that the net proliferation rate is correlated with the radiation response parameter (r = 0.89, p = 0.0007), resulting in a predictive relationship that is tested with a leave-one-out cross-validation technique. This relationship predicts the tumor size post-therapy to within inter-observer tumor volume uncertainty. The results of this study suggest that a mathematical model can create a virtual in silico tumor with the same growth kinetics as a particular patient and can not only predict treatment response in individual patients in vivo but also provide a basis for evaluation of response in each patient to any given therapy.

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 patients 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.

A mathematical model for brain tumor response to radiation therapy

Gliomas are highly invasive primary brain tumors, accounting for nearly 50% of all brain tumors (Alvord and Shaw in The pathology of the aging human nervous system. Lea & Febiger, Philadelphia, pp 210–281, 1991). Their aggressive growth leads to short life expectancies, as well as a fairly algorithmic approach to treatment: diagnostic magnetic resonance image (MRI) followed by biopsy or surgical resection with accompanying second MRI, external beam radiation therapy concurrent with and followed by chemotherapy, with MRIs conducted at various times during treatment as prescribed by the physician. Swanson et al. (Harpold et al. in J Neuropathol Exp Neurol 66:1–9, 2007) have shown that the defining and essential characteristics of gliomas in terms of net rates of proliferation (ρ) and invasion (D) can be determined from serial MRIs of individual patients. We present an extension to Swanson’s reaction-diffusion model to include the effects of radiation therapy using the classic linear-quadratic radiobiological model (Hall in Radiobiology for the radiologist. Lippincott, Philadelphia, pp 478–480, 1994) for radiation efficacy, along with an investigation of response to various therapy schedules and dose distributions on a virtual tumor (Swanson et al. in AACR annual meeting, Los Angeles, 2007).

Intracranial meningiomas: an overview of diagnosis and treatment

Meningiomas are extraaxial central nervous system tumors most often discovered in middle to late adult life, and are more often seen in women. Ninety percent of meningiomas are benign, 6% are atypical, and 2% are malignant. Most patients in whom a meningioma is diagnosed undergo resection to relieve neurological symptoms. Complete resection is often curative. For the majority of incompletely resected or recurrent tumors not previously irradiated, radiotherapy is administered. Radiotherapy may be administered as either conventional external-beam radiation therapy or stereotactically by linear accelerator, Leksell Gamma Knife, or Cyberknife radiosurgery. Advocates of stereo-tactic radiotherapy have suggested this therapy in lieu of surgery particularly in high-risk patients, those with meningiomas in eloquent or surgically inaccessible locations, and elderly patients. When the meningioma is unresectable or all other treatments (surgery and radiotherapy) have failed, hormonal therapy or chemotherapy may be considered. Notwithstanding limited data, hydroxyurea has been modestly successful in patients with recurrent meningiomas.

Distinction between glioma progression and post-radiation change by combined physiologic MR imaging

IntroductionMagnetic resonance (MR) diffusion-weighted imaging (DWI), dynamic susceptibility contrast-enhanced perfusion imaging (DSC), and MR spectroscopy (MRS) techniques provide specific physiologic information that may distinguish malignant glioma progression from post-radiation change, yet no single technique is completely reliable. We propose a simple, multiparametric scoring system to improve diagnostic accuracy beyond that of each technique alone.MethodsFifteen subjects with lesions suspicious for glioma progression following radiation therapy who had also undergone 3-tesla DWI, DSC, and MRS studies of the lesion were retrospectively reviewed. Minimum apparent diffusion coefficient (ADC) ratio, maximum regional cerebral blood volume (rCBV) ratio, and maximum MRS choline/creatine (Cho/Cr) and choline/N-acetyl-aspartate (Cho/NAA) metabolic peak-height ratios were quantified within each lesion. Each parameter (ADC ratio, rCBV ratio, and combined Cho/Cr and Cho/NAA ratios) was scored as either glioma progression (one point) or radiation change (zero point) based upon thresholds derived from our own data. For each lesion, the combined parameters yielded a multiparametric score (0 to 3) for prediction of tumor progression or post-radiation change.ResultsOptimum thresholds for ADC ratio (1.30), rCBV ratio (2.10), and either combined Cho/Cr (1.29) and Cho/NAA (1.06) yielded diagnostic accuracies of 86.7%, 86.7%, and 84.6%, respectively (p < 0.05). A combined multiparametric score threshold of 2 improved diagnostic accuracy to 93.3% (p < 0.05).ConclusionIn this small series combining 3-T DWI, DSC, and MRS diagnostic results using a simple, multiparametric scoring system has potential to improve overall diagnostic accuracy in distinguishing glioma progression from post-radiation change beyond that of each technique alone.

Extended Survival of Glioblastoma Patients After Chemoprotective HSC Gene Therapy

Gene therapy using P140K-modified hematopoietic progenitor cells is chemoprotective, enabling glioblastoma patients to withstand myelotoxic doses of chemotherapy. Arming Blood Stem Cells to Fight Cancer The toxic effects of chemotherapy (chemotoxicity) on blood and bone marrow cells of cancer patients can be a significant barrier to treating tumors. Delivery of a gene that can protect bone marrow stem and progenitor cells from chemotoxicity could overcome this barrier. In a new study by Adair et al., patients with chemotherapy-resistant brain tumors with very poor chances of survival were given a transplant with their own bone marrow hematopoietic stem cells after the cells had been modified with a gene that protects these cells from chemotherapy. After the bone marrow transplant, patients were then given dose-intensified chemotherapy. Adair et al. report that the patients were able to tolerate these chemotherapy doses better after transplant of the gene-modified bone marrow stem cells than did patients in previous studies who had received the same type of chemotherapy but without the gene-modified bone marrow stem cell transplant. The authors found that chemotherapy increased the number of gene-modified blood and bone marrow cells in these patients. These patients survived longer than predicted without any negative side effects from the transplanted cells or the treatment given. This strategy could be used for treating other types of cancer, or diseases treated with the same type of chemotherapy, to increase the efficacy of the drug regimen. This strategy could also be further developed as a clinical application in other diseases where defective bone marrow stem cells can be corrected by gene therapy but need to be increased to higher levels to produce a therapeutic benefit. Chemotherapy with alkylating agents for treating malignant disease results in myelosuppression that can significantly limit dose escalation and potential clinical efficacy. Gene therapy using mutant methylguanine methyltransferase (P140K) gene–modified hematopoietic stem and progenitor cells may circumvent this problem by abrogating the toxic effects of chemotherapy on hematopoietic cells. However, this approach has not been evaluated clinically. Here, we show efficient polyclonal engraftment of autologous P140K-modified hematopoietic stem and progenitor cells in three patients with glioblastoma. Increases in P140K-modified cells after transplant indicate selection of gene-modified hematopoietic repopulating cells. Longitudinal retroviral integration site (RIS) analysis identified more than 12,000 unique RISs in the three glioblastoma patients, with multiple clones present in the peripheral blood of each patient throughout multiple chemotherapy cycles. To assess safety, we monitored RIS distribution over the course of chemotherapy treatments. Two patients exhibited emergence of prominent clones harboring RISs associated with the intronic coding region of PRDM16 (PR domain–containing 16) or the 3′ untranslated region of HMGA2 (high-mobility group A2) genes with no adverse clinical outcomes. All three patients surpassed the median survival for glioblastoma patients with poor prognosis, with one patient alive and progression-free more than 2 years after diagnosis. Thus, transplanted P140K-expressing hematopoietic stem and progenitor cells are chemoprotective, potentially maximizing the drug dose that can be administered.

Comparison of 3 Tesla proton MR spectroscopy, MR perfusion and MR diffusion for distinguishing glioma recurrence from posttreatment effects

To compare 3 Tesla (3T) multi‐voxel and single‐voxel proton MR spectroscopy (MRS), dynamic susceptibility contrast perfusion MRI (DSC), and diffusion‐weighted MRI (DWI) for distinguishing recurrent glioma from postradiation injury.

Toward Patient-Specific, Biologically Optimized Radiation Therapy Plans for the Treatment of Glioblastoma

Purpose To demonstrate a method of generating patient-specific, biologically-guided radiotherapy dose plans and compare them to the standard-of-care protocol. Methods and Materials We integrated a patient-specific biomathematical model of glioma proliferation, invasion and radiotherapy with a multiobjective evolutionary algorithm for intensity-modulated radiation therapy optimization to construct individualized, biologically-guided plans for 11 glioblastoma patients. Patient-individualized, spherically-symmetric simulations of the standard-of-care and optimized plans were compared in terms of several biological metrics. Results The integrated model generated spatially non-uniform doses that, when compared to the standard-of-care protocol, resulted in a 67% to 93% decrease in equivalent uniform dose to normal tissue, while the therapeutic ratio, the ratio of tumor equivalent uniform dose to that of normal tissue, increased between 50% to 265%. Applying a novel metric of treatment response (Days Gained) to the patient-individualized simulation results predicted that the optimized plans would have a significant impact on delaying tumor progression, with increases from 21% to 105% for 9 of 11 patients. Conclusions Patient-individualized simulations using the combination of a biomathematical model with an optimization algorithm for radiation therapy generated biologically-guided doses that decreased normal tissue EUD and increased therapeutic ratio with the potential to improve survival outcomes for treatment of glioblastoma.

Gene therapy enhances chemotherapy tolerance and efficacy in glioblastoma patients

BACKGROUND Temozolomide (TMZ) is one of the most potent chemotherapy agents for the treatment of glioblastoma. Unfortunately, almost half of glioblastoma tumors are TMZ resistant due to overexpression of methylguanine methyltransferase (MGMT(hi)). Coadministration of O6-benzylguanine (O6BG) can restore TMZ sensitivity, but causes off-target myelosuppression. Here, we conducted a prospective clinical trial to test whether gene therapy to confer O6BG resistance in hematopoietic stem cells (HSCs) improves chemotherapy tolerance and outcome. METHODS We enrolled 7 newly diagnosed glioblastoma patients with MGMT(hi) tumors. Patients received autologous gene-modified HSCs following single-agent carmustine administration. After hematopoietic recovery, patients underwent O6BG/TMZ chemotherapy in 28-day cycles. Serial blood samples and tumor images were collected throughout the study. Chemotherapy tolerance was determined by the observed myelosuppression and recovery following each cycle. Patient-specific biomathematical modeling of tumor growth was performed. Progression-free survival (PFS) and overall survival (OS) were also evaluated. RESULTS Gene therapy permitted a significant increase in the mean number of tolerated O6BG/TMZ cycles (4.4 cycles per patient, P < 0.05) compared with historical controls without gene therapy (n = 7 patients, 1.7 cycles per patient). One patient tolerated an unprecedented 9 cycles and demonstrated long-term PFS without additional therapy. Overall, we observed a median PFS of 9 (range 3.5-57+) months and OS of 20 (range 13-57+) months. Furthermore, biomathematical modeling revealed markedly delayed tumor growth at lower cumulative TMZ doses in study patients compared with patients that received standard TMZ regimens without O6BG. CONCLUSION These data support further development of chemoprotective gene therapy in combination with O6BG and TMZ for the treatment of glioblastoma and potentially other tumors with overexpression of MGMT. TRIAL REGISTRATION Clinicaltrials.gov NCT00669669. FUNDING R01CA114218, R01AI080326, R01HL098489, P30DK056465, K01DK076973, R01HL074162, R01CA164371, R01NS060752, U54CA143970.