Citations

Abstract With mean survival from glioblastoma multiforme (GBM) barely edging over 15 months, it become imperative to develop novel tools informing on both progression and treatment efficacy. As the aggressive growth of GBM outstrips available resources, regions of hypoxia develop. Hypoxia can be clinically assessed through [18F]-flouromisonidazole (FMISO) PET. However, PET imaging suffers from low resolution and reconstruction artifact. We present the comparative and predictive results of a multi-stage model utilizing the mathematical biology of cancer and the physics of PET imaging. Our mathematical model of GBM characterizes cancer cells into the interacting phenotypes of normoxic, hypoxic, and necrotic cells supported by vasculature. The pharmacokinetic activity of FMISO is induced in the simulated tissue then acquired and reconstructed by an analytic simulator of the PET process. This multi-stage process creates a patient-specific virtual PET images with characteristic of the clinical PET scan. Extending previous work, we model the full three-dimensional dynamics of tumor progression, pharmacokinetic activity, and FMISO PET for the tumor kinetics of six GBM patients. Virtual and clinical FMISO PET images are compared. Overall hypoxic burden and spatial distribution show strong correspondence between virtual and clinical FMISO PET images for all six patients. Simulated FMISO PET dynamics, with tumor kinetics derived from routine clinical MRI scans, provide a unique and evolving tool giving insight into the biological connections between magnetic resonance and molecular imaging. Citation Format: Joshua Jacobs, Andrea Hawkins-Darrud, Robert Harrison, Sandra Johnston, Paul Kinahan, Kristin Swanson. Correlating magnetic resonance and molecular imaging using three dimensional untreated virtual control. [abstract]. In: Proceedings of the AACR Special Conference on Engineering and Physical Sciences in Oncology; 2016 Jun 25-28; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2017;77(2 Suppl):Abstract nr A10.

Abstract Purpose: Investigate the utility of patient-specific spatial predictions of tumor cell density from a bio-mathematical model. Introduction: Glioblastomas (GBMs) are the most malignant of all primary brain tumors. While it is known there is always a non-detectable portion of the tumor, current techniques of monitoring GBM progression, imaging and initial histological assessment, are not able to reliably estimate the tumor invasion past the enhancing region on T2-Weighted (T2W) imaging. Over the last two decades, a large effort has been made to create a simple patient-specific mathematical model of gliomas. The resulting model, referred to as the Proliferation-Invasion (PI) model, is based on two key parameters, the net growth rate, ρ, and the dispersal coefficient, D. In this model, the ratio of D/ρ is related to degree of invasion and the product D*ρ, is related to the speed of growth. The intuitive understanding provided by this model has been able to provide patient-specific understanding of disease kinetics enabling prediction of outcomes following surgical resection, radiation and the development of a prognostic response metric. Previous literature utilizing this model has been based on the assumption that what is seen on the pretreatment T1-Weighted contrast-enhanced (T1Gd) and T2W, images correspond to an 80% and 16% tumor cell density threshold respectively. This assumption allows for an estimate of D/ρ from a single time point of imaging. While these values were based on extensive experience, for ethical and technical reasons, they have never been rigorously investigated histologically. Recent technological advances have made it possible for surgeons to use an MRI to guide the acquisition of tissue making it possible to know with a good degree of accuracy where on the MR image the histological specimen comes from. Methods: Model Calibration : To estimate D/ρ for each patient, we assume abnormalities on the T1Gd and T2W images correspond to an 80% and 16% tumor cell density threshold respectively. We then utilize a Bayesian calibration approach based on adaptive grid refinement while holding the velocity constant to find the most likely value of D/ρ to match the observed radial measurements. Three-Dimensional Density Maps : Given a gray/white segmentation and an estimate for D/ρ, we can build a tumor cell density prediction in the patient's anatomy using the Eikonal equations and the modified Fast Marching Method (FMM) algorithm presented by Konukoglu et al. Patient Cohort : Eighteen patients were recruited with clinically suspected GBM undergoing preoperative stereotactic MRI for surgical resection with IRB approval Barrow Neurological Institute and Mayo Clinic in Arizona. Surgical Biopsy : Pre-operative conventional MRI, including T1Gd and T2W, was utilized to guide stereotactic biopsies. An average of 5–6 tissue specimens were acquired from each tumor by using stereotactic surgical localization, following the smallest possible diameter craniotomies to minimize brain shift. Histological Analysis : 4 μm tissue sections were stained with hematoxylin and eosin (H&E) for neuropathology review. H&E slides were reviewed by a neuropathologist. The percent tumor nuclei in the field was estimated. Results and Conclusion: Our analysis showed that the intuitive ordering of diffuse to nodular tumor profiles from the PI model is consistent with the histologic data. Further, utilizing the histologic data, limitations to a universal threshold cutoff of the T2/FLAIR region are specified and a better threshold cutoff value is suggested. We hope that this paper will lead to more studies of this kind resulting in more accurate ways to predict the spatial distribution of GBM tumor cells from medical imaging. Such advances could revolutionize surgical procedures and radiation therapy and may enable additional insights into tumor kinetic differences meaningful for treatment. Citation Format: Andrea Hawkins-Daarud, Lauren DeGirolamo, Joshua Jacobs, Kamala Clark-Swanson, Jennifer M. Eschbacher, Kris A. Smith, Peter Nakaji, Leslie C. Baxter, John P. Karis, Teresa Wu, J. Ross Mitchell, Jing Li, Leland Hu, Kristin R. Swanson. Histologic evidence for a bio-mathematical model of glioblastoma invasion. [abstract]. In: Proceedings of the AACR Special Conference on Engineering and Physical Sciences in Oncology; 2016 Jun 25-28; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2017;77(2 Suppl):Abstract nr A08.

1 Background: To determine whether the efficacy of a hypofractionated (H) schedule is no worse than a conventional (C) schedule in men with low-risk prostate cancer. Methods: From April 2006 to December 2009, one thousand one hundred fifteen men with low-risk prostate cancer (clinical stage T1-2a, Gleason ≤ 6, PSA < 10) were randomly assigned 1:1 to a conventional (C) schedule (73.8 Gy in 41 fractions over 8.2 weeks) or to a hypofractionated (H) schedule (70 Gy in 28 fractions over 5.6 weeks). The trial was designed to establish with 90% power and alpha = 0.05 that (H) results in 5-year disease-free survival (DFS) that is not lower than (C) by more than 7% (hazard ratio (HR) < 1.52). Secondary endpoints include freedom from biochemical recurrence (FFBR) and overall survival. At the third planned interim analysis (July 2015), the NRG Oncology Data Monitoring Committee recommended that the results of the trial be reported. Results: One thousand one hundred and one protocol eligible men were randomized: 547 to C and 554 to H. Median follow-up is 5.9 years. Baseline characteristics are not different according to treatment arm. At the time of analysis 185 DFS events have been observed; 99 in the C arm and 86 in the H arm. The estimated 7-year disease-free survival is 75.6% (95% CI 70.3, 80.1) in the C arm and 81.8% (77.5, 85.3) in the H arm. The DFS HR (C/H) is 0.85 (0.64, 1.14). Comparison of biochemical recurrence (HR = 0.77, (0.51, 1.17)) and overall survival (HR = 0.95, (0.65, 1.41)) also met protocol non-inferiority criteria. Grade ≥ 3 GI toxicity is 3.0% (C) vs. 4.6% (H), Relative risk (RR) for H vs. C 1.53, (95% CI 0.86, 2.83); grade ≥ 3 GU toxicity is 4.5% (C) vs. 6.4% (H), RR = 1.43 (0.86,2.37). Conclusions: In men with low-risk prostate cancer, 70 Gy in 28 fractions over 5.6 weeks is non-inferior to 73.8 Gy in 41 fractions over 8.2 weeks. Clinical trial information: NCT00331773.

AimsMassive gastric polyposis is a rare entity that is often associated with juvenile polyposis syndrome (JPS). The aim of this study was to evaluate the clinicopathological features of 22 patients with abundant gastric juvenile‐type or hyperplastic‐like polyps.Methods and resultsThe study included 12 males and 10 females with a median age of 48 years (range: 13–79 years). Fourteen (64%) patients carried a diagnosis of JPS, and three had prior gastrointestinal adenocarcinomas. Patients without known JPS presented at an older median age (60 years versus 40 years; P = 0.0068). Clinical symptoms included nausea, vomiting, and abdominal pain; 23% of patients were asymptomatic. Eighteen cases showed complete or near‐complete carpeting of the gastric mucosa by innumerable polyps, ranging from a few millimetres to ~100 mm. Most polyps formed long, bulbous projections and had characteristic histological features, including a smooth outer contour, prominent stromal oedema, and widely spaced, often cystically dilated glands lined by foveolar epithelium; some polyps had less stroma and more hyperplastic foveolar epithelium. All had normal underlying or adjacent mucosa. Four (18%) cases harboured adenocarcinoma, and seven (32%) others showed dysplasia. SMAD4 immunohistochemical staining showed patchy loss in polyps from 19 of 20 cases tested. Five of six (84%) patients tested had a germline SMAD4 mutation.ConclusionsMassive gastric juvenile‐type polyposis can occur in patients with and without known JPS, and may mimic different conditions, such as other polyposis syndromes and Ménétrier disease. Pathologists play an important role in disease classification, as some patients lack a family or personal history of JPS, have few if any colonic polyps, and may not harbour diagnostic germline mutations.

Objective Limited efficacy of immune checkpoint inhibitors in pancreatic ductal adenocarcinoma (PDAC) has prompted investigation into combination therapy. We hypothesised that interleukin 6 (IL-6) blockade would modulate immunological features of PDAC and enhance the efficacy of anti-programmed death-1-ligand 1 (PD-L1) checkpoint inhibitor therapy. Design Transcription profiles and IL-6 secretion from primary patient-derived pancreatic stellate cells (PSCs) were analyzed via Nanostring and immunohistochemistry, respectively. In vivo efficacy and mechanistic studies were conducted with antibodies (Abs) targeting IL-6, PD-L1, CD4 or CD8 in subcutaneous or orthotopic models using Panc02, MT5 or KPC-luc cell lines; and the aggressive, genetically engineered PDAC model (Kras LSL−G12D , Trp53 LSL−R270H , Pdx1-cre, Brca2 F/F (KPC-Brca2 mice)). Systemic and local changes in immunophenotype were measured by flow cytometry or immunohistochemical analysis. Results PSCs (n=12) demonstrated prominent IL-6 expression, which was localised to stroma of tumours. Combined IL-6 and PD-L1 blockade elicited efficacy in mice bearing subcutaneous MT5 (p<0.02) and Panc02 tumours (p=0.046), which was accompanied by increased intratumoural effector T lymphocytes (CD62L − CD44 − ). CD8-depleting but not CD4-depleting Abs abrogated the efficacy of combined IL-6 and PD-L1 blockade in mice bearing Panc02 tumours (p=0.0016). This treatment combination also elicited significant antitumour activity in mice bearing orthotopic KPC-luc tumours and limited tumour progression in KPC-Brca2 mice (p<0.001). Histological analysis revealed increased T-cell infiltration and reduced α-smooth muscle actin cells in tumours from multiple models. Finally, IL-6 and PD-L1 blockade increased overall survival in KPC-Brca2 mice compared with isotype controls (p=0.0012). Conclusions These preclinical results indicate that targeted inhibition of IL-6 may enhance the efficacy of anti-PD-L1 in PDAC.