<div>AbstractPurpose:<p>Radiomics is the extraction of multidimensional imaging features, which when correlated with genomics, is termed radiogenomics. However, radiogenomic biological validation is not sufficiently described in the literature. We seek to establish causality between differential gene expression status and MRI-extracted radiomic-features in glioblastoma.</p>Experimental Design:<p>Radiogenomic predictions and validation were done using the Cancer Genome Atlas and Repository of Molecular Brain Neoplasia Data glioblastoma patients (<i>n</i> = 93) and orthotopic xenografts (OX; <i>n</i> = 40). Tumor phenotypes were segmented, and radiomic-features extracted using the developed radiome-sequencing pipeline. Patients and animals were dichotomized on the basis of Periostin (<i>POSTN)</i> expression levels. RNA and protein levels confirmed RNAi-mediated <i>POSTN</i> knockdown in OX. Total RNA of tumor cells isolated from mouse brains (knockdown and control) was used for microarray-based expression profiling. Radiomic-features were utilized to predict <i>POSTN</i> expression status in patient, mouse, and interspecies.</p>Results:<p>Our robust pipeline consists of segmentation, radiomic-feature extraction, feature normalization/selection, and predictive modeling. The combination of skull stripping, brain-tissue focused normalization, and patient-specific normalization are unique to this study, providing comparable cross-platform, cross-institution radiomic features. <i>POSTN</i> expression status was not associated with qualitative or volumetric MRI parameters. Radiomic features significantly predicted <i>POSTN</i> expression status in patients (AUC: 76.56%; sensitivity/specificity: 73.91/78.26%) and OX (AUC: 92.26%; sensitivity/specificity: 92.86%/91.67%). Furthermore, radiomic features in OX were significantly associated with patients with similar <i>POSTN</i> expression levels (AUC: 93.36%; sensitivity/specificity: 82.61%/95.74%; <i>P</i> = 02.021E−15).</p>Conclusions:<p>We determined causality between radiomic texture features and <i>POSTN</i> expression levels in a preclinical model with clinical validation. Our biologically validated radiomic pipeline also showed the potential application for human–mouse matched coclinical trials.</p></div>
Abstract Purpose: Radiomics is the extraction of multidimensional imaging features, which when correlated with genomics, is termed radiogenomics. However, radiogenomic biological validation is not sufficiently described in the literature. We seek to establish causality between differential gene expression status and MRI-extracted radiomic-features in glioblastoma. Experimental Design: Radiogenomic predictions and validation were done using the Cancer Genome Atlas and Repository of Molecular Brain Neoplasia Data glioblastoma patients (n = 93) and orthotopic xenografts (OX; n = 40). Tumor phenotypes were segmented, and radiomic-features extracted using the developed radiome-sequencing pipeline. Patients and animals were dichotomized on the basis of Periostin (POSTN) expression levels. RNA and protein levels confirmed RNAi-mediated POSTN knockdown in OX. Total RNA of tumor cells isolated from mouse brains (knockdown and control) was used for microarray-based expression profiling. Radiomic-features were utilized to predict POSTN expression status in patient, mouse, and interspecies. Results: Our robust pipeline consists of segmentation, radiomic-feature extraction, feature normalization/selection, and predictive modeling. The combination of skull stripping, brain-tissue focused normalization, and patient-specific normalization are unique to this study, providing comparable cross-platform, cross-institution radiomic features. POSTN expression status was not associated with qualitative or volumetric MRI parameters. Radiomic features significantly predicted POSTN expression status in patients (AUC: 76.56%; sensitivity/specificity: 73.91/78.26%) and OX (AUC: 92.26%; sensitivity/specificity: 92.86%/91.67%). Furthermore, radiomic features in OX were significantly associated with patients with similar POSTN expression levels (AUC: 93.36%; sensitivity/specificity: 82.61%/95.74%; P = 02.021E−15). Conclusions: We determined causality between radiomic texture features and POSTN expression levels in a preclinical model with clinical validation. Our biologically validated radiomic pipeline also showed the potential application for human–mouse matched coclinical trials.
Abstract Pseudoprogression (PsP) is a diagnostic clinical dilemma in cancer. In this study, we retrospectively analyse glioblastoma patients, and using their dynamic susceptibility contrast and dynamic contrast-enhanced perfusion MRI images we build a classifier using radiomic features obtained from both Ktrans and rCBV maps coupled with support vector machines. We achieve an accuracy of 90.82% (area under the curve (AUC) = 89.10%, sensitivity = 91.36%, 67 specificity = 88.24%, p = 0.017) in differentiating between pseudoprogression (PsP) and progressive disease (PD). The diagnostic performances of the models built using radiomic features from Ktrans and rCBV separately were equally high (Ktrans: AUC = 94%, 69 p = 0.012; rCBV: AUC = 89.8%, p = 0.004). Thus, this MR perfusion-based radiomic model demonstrates high accuracy, sensitivity and specificity in discriminating PsP from PD, thus provides a reliable alternative for noninvasive identification of PsP versus PD at the time of clinical/radiologic question. This study also illustrates the successful application of radiomic analysis as an advanced processing step on different MR perfusion maps.
Abstract Aromatic based chemistries have been used extensively as additives in the pre-flush systems of acid stimulation programs. The need for these solvents stems from the requirement to displace oil or break asphaltic or waxy materials ahead of the main stimulation treatment. These chemicals while effective, are highly flammable, difficult to handle and have negative impact on the enviroment. Aromatic additives are always mixed with diesel-based pre-flush systems in acid stimulation jobs. If water is added to this system, the resultant emulsion damages the productivity of the formation. Water wetting surfactants typically of aqueous nature pose the same problems when mixed with diesel systems. The main challenge, however, is to mix these hydrocarbon-based fluids with water and surfactant to clean the wellbore and water-wet the formation face in preparation for the acid stimulation treatment. The objective of this work was to evaluate new environment-friendly water-based pre-flush formulations for oil and injector wells. The new aqueous Pre-flush formulations was developed to avoid the aformentioned problems with using diesel. The new Pre-flush formulations include between 10-15% blend of specialty surfactants and solvents, successfully homogenized with low-cost field water. These formulations are able to alter the wettability of the formation face by breaking the oily phase and separating it from the surface of the formation. The new formulations have high flash points and are biodegradable which results in easier handling and an environment-friendly alternative to existing diesel pre-flush systems. Wettability, stability and interfacial tension tests at reservoir conditions helped optimized the new formulation. The results showed excellent dissolving power for oily sludges and surfaces in addition to excellent stability and wettability. The new pre-flush formulations can enhance the reactivity of the acid with the formation and improve treatment results. It will enhance the flowback and post-treatment cleaning of the well.
Abstract PURPOSE Clinical care and outcome in Glioblastoma (GBM) remains challenging due to the tumor's invasive grwoth. To establish personalized treatment options in GBM, discovery of genetic mechanisms essential for the tumor's invasion is needed. We have previously described radiogenomic approaches to diagnose gene networks non invasively by analyzing genomic data from TCGA. The purpose of the current reseach is to identify a genetic network that drives GBM invasion and can be targeted specifically. METHOD AND MATERIALS Using Kaplan-Meier statistics, the data of the two independent databases TCGA and REMBRANDT were used to validate the genetic netowork's impact on clinical outcome. The genes’ staus was assessed in a panel of human glioma stem cells (GSCs) and conventional proneural, classical and mesenchymal GBM cell lines using RT-PCR. Differentiation potential (Tuj1+ve, S100A+ve, and GFAP+ve), self-renewal (limiting dilution assays), invasion (Boyden chamber) and proliferation (BrdU) were assessed. Gain (lentiviral vectors) and loss (SMARTchoice Inducible shRNA) of function experiments were performed. Orthotopic xenograft models (nude mice) were used to characterize the genes impact in vivo. Potential FDA approved therapeutics were identified using connectivity map. RESULTS Texture analysis based on radiogenomics significantly predicted the genes responsible for invasion of GBM in a non-invasive manner. Invasion in both, in vitro and in vivo was significantly decreased upun downregulation of this gene network. Transcriptome micro-array analysis showed that an upregulation of the described genes results in class switching from proneural to mesenchymal sub-types. Cmap derived therapeutics could significantly inhibit the gene network's activitiy and hence invasion. CONCLUSION The describend genes could be essential drivers of molecular subtypes and invasion in GBM. The therapeutics defined with cmap offer a targetted therapy to adress these key features of GBM pathogenesis. Noninvasive radiogenomics-based identification of tumor subgroups and potential treatment approaches can significantly contribute to personalized therapy. CLINICAL RELEVANCE/APPLICATION The described gene network seems to be key for GBM pathogenesis. Noninvasive, radiogenomics-based subgroup identification and specific novel treatment approaches can significanty contribution to personalized GBM therapy. Citation Format: Rivka R. Colen, Markus Luedi, Sanjay K. Singh, Islam Hassan, Joy Gumin, Erik P. Sulman, Frederick F. Lang, Pascal O. Zinn. Radiogenomics defines key genomic network driving GBM invasion. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1505.
Abstract BACKGROUND Ivosidenib (AG-120, IVO) is a first-in-class oral inhibitor of mutant isocitrate dehydrogenase 1 (mIDH1), and vorasidenib (AG-881, VOR) is an oral, potent, brain-penetrant inhibitor of mIDH1/2. Both have been evaluated in glioma patients in ongoing phase 1 studies. In orthotopic glioma models, IVO and VOR reduced 2-hydroxyglutarate (2-HG) levels by 85% and 98%, respectively, despite different brain-to-plasma ratios (< 0.04 vs 1.33). METHODS Patients with recurrent, nonenhancing, WHO-2016 grade 2/3, mIDH1-R132H oligodendroglioma or astrocytoma undergoing craniotomy were randomized 2:2:1 to IVO 500mg QD, VOR 50mg QD, or no treatment (cohort 1), or 1:1 to IVO 250mg BID or VOR 10mg QD (cohort 2), for 4 weeks preoperatively. Postoperatively, patients continued receiving IVO or VOR (control patients were randomized 1:1 to IVO or VOR). Tumors were assessed for mIDH1 status, cellularity, and 2-HG and drug concentrations. Treated subjects were compared with controls and mIDH1/wild-type banked reference samples. Primary endpoint: tumor 2-HG concentration following IVO or VOR. RESULTS As of March 1, 2019, 27 patients (18 men; 25/2 grade 2/3) were randomized preoperatively in cohort 1 (IVO 10, VOR 12, untreated 5): 27 received drug (IVO 13, VOR 14); 1 discontinued VOR postoperatively due to disease progression. Of 26 tumors analyzed, 22 were evaluable. Mean brain-to-plasma ratios: 0.13 IVO, 1.59 VOR. Relative to untreated samples, IVO and VOR reduced tumor 2-HG by 92.0% (95% CI 73.2, 97.4) and 92.5% (95% CI 78.1, 97.7), respectively. Common (≥ 4 patients) TEAEs (all cohort 1 patients, all grades): diarrhea (37.0%), constipation, hypocalcemia, and nausea (each 18.5%), anemia, hyperglycemia, pruritus, headache, and fatigue (each 14.8%). Cohort 2 has completed accrual, with analyses ongoing. CONCLUSIONS In cohort 1 of this phase 1 perioperative study, IVO and VOR demonstrated brain penetrance and lowered 2-HG compared with controls. Updated data from both cohorts will be presented.
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