Gist Model Research Articles

Promising antitumor activity of olverembatinib (HQP1351) in patients (pts) with tyrosine kinase inhibitor- (TKI-) resistant succinate dehydrogenase- (SDH-) deficient gastrointestinal stromal tumor (GIST).

11513 Background: GIST is a rare mesenchymal tumor whose management has been transformed by approvals of TKIs. However, treatment resistance is a formidable challenge in managing locally advanced or metastatic GIST. Pts with SDH-deficient GIST are not sensitive to imatinib and other TKIs, are frequently multifocal, and typically have a multinodular architecture. Olverembatinib is a novel, potent, orally active third-generation TKI with promising activity against GIST in multiple preclinical GIST models. Methods: The aim of this phase Ib/II study was to evaluate the safety/tolerability, pharmacokinetics (PK), and efficacy (assessed per RECIST v1.1) of olverembatinib (NCT03594422) in pts with metastatic GIST whose disease was resistant or failed to respond to imatinib or other TKIs. Olverembatinib was administered orally once every other day (QOD) in 28-day repeated cycles. After 3 pts were treated at 20 mg, other pts were randomly allocated in a 1:1:1 ratio to 30, 40, and 50 mg regimens. Results: On the cutoff date of January 30, 2022, 39 pts (median age 52 [range 19-72] years) had received at least 1 dose of olverembatinib. The average (range) treatment period was 5.0 (0.2-35) months. PK analyses indicated an approximately dose-proportional increase in systemic exposure over the dose range of 20 to 50 mg. Thirty-one pts had KIT or PDGFRA mutations, 13 had stable disease for at least 2 cycles as the best response, 8 withdrew early, and 10 had progressive disease before Cycle 3. Very interestingly, 6 of 8 pts with KIT wild-type GIST were confirmed as SDH deficient: 2 pts had partial responses (PRs), 1 patient’s tumor had shrunk by 35.9% and lasted for 16 cycles, and another patient’s tumor had shrunk by 54.2% in the first evaluation. Four pts had stable disease as best response for 2, 6, 14, and 36 cycles. A total of 36 (92.3%) pts experienced treatment-emergent adverse events, most of which were mild or moderate. Ten (25.6%) pts experienced serious adverse events, of which intestinal obstruction attributed to GIST was the most reported. Common treatment-related adverse events (≥ 20%) included increased leukocyte (59.0%) and neutrophil (46.2%) counts, anemia (20.5%), constipation or asthenia (35.9% each), hyperuricemia (25.6%), hypoalbuminemia (23.1%), and elevated AST or ALT (20.5% each). Conclusions: Olverembatinib was well tolerated at doses of up to 50 mg QOD and showed antitumor activity in pts with TKI-resistant SDH-deficient GIST, with 2 PRs in 6 evaluable pts with SDH-deficient GIST and 1 with stable disease for 36 cycles. These promising findings warrant further investigation. Clinical trial information: NCT03594422.

Selected Articles from This Issue

Abemaciclib is an oral, potent and selective CDK4 & 6 inhibitor, dosed on a continuous schedule and approved as monotherapy and in combination with either fulvestrant or an aromatase inhibitor for HR+, HER2− advanced breast cancer (ABC). ESR1 mutation and PI3K pathway dysregulation are associated with resistance to endocrine therapy, and treatment with CDK4 & 6 inhibitors has been hypothesized as a therapeutic strategy to overcome endocrine resistance. In this exploratory analysis, Tolaney and colleagues show in HR+, HER2− ABC, abemaciclib plus fulvestrant improved both PFS and OS, regardless of PIK3CA or ESR1 mutation status. Additionally, abemaciclib plus fulvestrant improved other endpoints, including TTC, CFS and PFS2, regardless of PIK3CA or ESR1 mutation status. These findings support further evaluation in suitably powered trials.Combined targeting of the lineage-specific master transcription factor, ETV1, and signaling factor, KIT, by the combination of KIT and MEK inhibitors, is synergistic in preclinical GIST models. Chi and colleagues report the results of a phase Ib clinical trial designed to both evaluate the safety of the combination of imatinib and binimetinib and to determine the recommended phase II dose (RP2D) and early efficacy signal of this drug combination in patients with refractory advanced KIT/PDGFRA-mutant and KIT/PDGFRA wild-type GIST including SDH-deficient GIST. The study demonstrated that the combination of imatinib/binimetinib was safe with manageable side effects and determined the RP2D. They observed durable pathological responses in a small cohort of SDH-deficient GIST patients in the phase Ib expansion at RP2D. The promising clinical activity of the combination treatment in SDH-deficient GIST observed is worthy of further clinical investigation.Cyclin-dependent kinase 4/6 inhibition may have synergistic anticancer activity when combined with taxane chemotherapy. To explore this combination in metastatic castration-resistant prostate cancer (mCRPC), de Kouchkovsky and colleagues conducted a phase Ib/IIa study of ribociclib plus docetaxel in mCRPC patients who had progressed on an androgen receptor signaling inhibitor (ARSI). With intermittent ribociclib dosing and prophylactic growth factor, the combination demonstrated an acceptable safety profile, achieved a 6-month radiographic progression-free survival (rPFS) rate of 65.8%, and a median rPFS of 8.1 months. These results compare favorably to outcomes seen with docetaxel monotherapy after ARSI therapy. Further prospective study is warranted.KRAS is the most commonly mutated driver oncogene in solid tumors, including non-small cell lung cancer (NSCLC), with mutations spanning codons 12, 13 and 61. To explore the role of different mutant KRAS isoforms in pre-clinical models and samples from patients, Ricciuti and colleagues developed an isogenic cell-based platform to compare the oncogenic properties and specific therapeutic actionability across the 6 most common KRAS mutant variants. In addition, by surveying a large institutional dataset totaling >3000 NSCLC they identified clinicopathologic and genomic characteristics which correlated with unique KRAS mutant isoforms. Together, these findings revealed that KRAS mutations are highly heterogenous in terms of biological outcome and genomic profiling, and that this heterogeneity can be exploited to unveil novel potentially actionable vulnerabilities for KRAS mutant NSCLC.

When You Do Not Get the Whole Picture: Scene Perception After Occipital Cortex Lesions.

Background: Occipital cortex lesions (OCLs) typically result in visual field defects (VFDs) contralateral to the damage. VFDs are usually mapped with perimetry involving the detection of point targets. This, however, ignores the important role of integration of visual information across locations in many tasks of everyday life. Here, we ask whether standard perimetry can fully characterize the consequences of OCLs. We compare performance on a rapid scene discrimination task of OCL participants and healthy observers with simulated VFDs. While the healthy observers will only suffer the loss of part of the visual scene, the damage in the OCL participants may further compromise global visual processing.Methods: VFDs were mapped with Humphrey perimetry, and participants performed two rapid scene discrimination tasks. In healthy participants, the VFDs were simulated with hemi- and quadrant occlusions. Additionally, the GIST model, a computational model of scene recognition, was used to make individual predictions based on the VFDs.Results: The GIST model was able to predict the performance of controls regarding the effects of the local occlusion. Using the individual predictions of the GIST model, we can determine that the variability between the OCL participants is much larger than the extent of the VFD could account for. The OCL participants can further be categorized as performing worse, the same, or better as their VFD would predict.Conclusions: While in healthy observers the extent of the simulated occlusion accounts for their performance loss, the OCL participants’ performance is not fully determined by the extent or shape of their VFD as measured with Humphrey perimetry. While some OCL participants are indeed only limited by the local occlusion of the scene, for others, the lesions compromised the visual network in a more global and disruptive way. Yet one outperformed a healthy observer, suggesting a possible adaptation to the VFD. Preliminary analysis of neuroimaging data suggests that damage to the lateral geniculate nucleus and corpus callosum might be associated with the larger disruption of rapid scene discrimination. We believe our approach offers a useful behavioral tool for investigating why similar VFDs can produce widely differing limitations in everyday life.

GIST do it! How motivational mechanisms help wearable users develop healthy habits

Wearable devices and other smart technologies are becoming widely popular as more individuals adopt the goal of improving their health. Users of such devices are exploiting technology in their struggle to combat poor sedentary habits that have been shown to have severe consequences for physical and mental wellness. Using the U-Commerce perspective, this study goes beyond user adoption studies to examine how motivational technology characteristics help users sustain their motivation and acquire habitual behaviors. Specifically, we propose a model that shows how autonomous motivation leads to habitual intentions predicated upon user preferences for different motivational features, namely gaming, instructing, sharing, and tracking (or, as we have termed them, GIST). After developing user preference measures, we empirically test the GIST model in a large sample with diverse characteristics to identify motivational differences by gender and age. We find that autonomous motivation has a significant, fully mediated impact on habitual intentions through the app mechanisms of gamification, instruction, and tracking. Although the mechanism of sharing is still important for habitual purposes, this effect does not significantly change with differences in autonomous motivation. We close with future directions for motivational technology research and health management practice.

Impact of the GIST Model in Development of Thinking in Students

Impact of the GIST Model in Development of Thinking in Students

Wnt/β-catenin Signaling Contributes to Tumor Malignancy and Is Targetable in Gastrointestinal Stromal Tumor.

Gastrointestinal stromal tumor (GIST) is the most common type of sarcoma and usually harbors either a KIT or PDGFRA mutation. However, the molecular basis for tumor malignancy is not well defined. Although the Wnt/β-catenin signaling pathway is important in a variety of cancers, its role in GIST is uncertain. Through analysis of nearly 150 human GIST specimens, we found that some human GISTs expressed β-catenin and contained active, dephosphorylated nuclear β-catenin. Furthermore, advanced human GISTs expressed reduced levels of the Wnt antagonist DKK4. Accordingly, in human GIST T1 cells, Wnt stimulation increased β-catenin-mediated transcriptional activity in a reporter assay as well as transcription of the downstream target genes Axin2 and CCND1 In contrast, DKK4 overexpression in GIST T1 cells reduced Wnt/β-catenin signaling. In addition, we showed that nuclear β-catenin stability was partially regulated by the E3 ligase COP1, as demonstrated with coimmunoprecipitation and COP1 knockdown. Three molecular inhibitors of the Wnt/β-catenin pathway demonstrated antitumor efficacy in various GIST models, both in vitro and in vivo Notably, the tankyrase inhibitor G007-LK alone had substantial activity against tumors of genetically engineered KitV558Δ/+ mice, and the effect was increased by the addition of the Kit inhibitor imatinib mesylate. Collectively, our findings demonstrate that Wnt/β-catenin signaling is a novel therapeutic target for selected untreated or imatinib-resistant GISTs. Mol Cancer Ther; 16(9); 1954-66. ©2017 AACR.

ETV1-Positive Cells Give Rise to BRAFV600E -Mutant Gastrointestinal Stromal Tumors.

Gastrointestinal stromal tumor (GIST) is the most common subtype of sarcoma. Despite clinical advances in the treatment of KIT/PDGFRA-mutant GIST, similar progress against KIT/PDGFRA wild-type GIST, including mutant BRAF-driven tumors, has been limited by a lack of model systems. ETV1 is a master regulator in the intestinal cells of Cajal (ICC), thought to be the cells of origin of GIST. Here, we present a model in which the ETV1 promoter is used to specifically and inducibly drive Cre recombinase in ICC as a strategy to study GIST pathogenesis. Using a conditional allele for BrafV600E , a mutation observed in clinical cases of GIST, we observed that BrafV600E activation was sufficient to drive ICC hyperplasia but not GIST tumorigenesis. In contrast, combining BrafV600E activation with Trp53 loss was sufficient to drive both ICC hyperplasia and formation of multifocal GIST-like tumors in the mouse gastrointestinal tract with 100% penetrance. This mouse model of sporadic GIST model was amenable to therapeutic intervention, and it recapitulated clinical responses to RAF inhibition seen in human GIST. Our work offers a useful in vivo model of human sporadic forms of BRAF-mutant GIST to help unravel its pathogenesis and therapeutic response to novel experimental agents. Cancer Res; 77(14); 3758-65. ©2017 AACR.

Abstract 795: Dovitinib exerts potent antitumor effects in gastrointestinal stromal tumors

Abstract Gastrointestinal stromal tumors (GISTs) are the most common mesenchymal tumours of the gastrointestinal (GI) tract. Although Imatinib is the current first-line therapy for patients not suitable for surgical resection, 10 - 20% of GIST patients taking Imatinib do not respond to this therapy and 40-50% of the patients develop acquired resistance to Imatinib following partial response or stable disease. Thus, novel treatments are needed for GIST. In the present study, four different patient-derived xenograft (PDX) GIST models were used to demonstrate that Imatinib effectively caused tumor regression in GIST26-0208A and GIST09-0210 models with the common exon 11 KIT W557-K558 mutation (Imatinib-sensitive models), inhibited tumor growth of GIST27-0510 model with Y568-I571 and P573-L576 deletion and delayed tumor growth in GIST27-0612 with wild-type KIT. Unlike Imatinib, Dovitinib effectively caused tumor regression in all four PDX models tested regardless of their KIT mutational status. On GIST27-0510 model, tumor regression was observed as early as day 3 of Dovitinib treatment and continued to approximately 22% of the initial tumor volume. Dovitinib provided longer progression-free period than Imatinib after a 21-day treatment cycle. In the GIST26-0208A model, signs of tumor regrowth were observed on day 2 for Imatinib and day 59 for Dovitinib following a 21-day treatment. Dovitinib treatment took approximately 3.7 - 5 times longer to reach initial tumor volume than Imatinib following a 21-day treatment. Utilizing micro-Positron Emission Tomography (mPET), both Imatinib and Dovitinib treatment showed decreased SUV and TLG readings after 8-day treatment in GIST26-0208A. A trend of increasing activity was observed in Imatinib but not in Dovitinib-treated tumors at day 11 and day 21 following an 8-day treatment, suggesting mPET could potentially be used to access tumor response to Dovitinib. In Imatinib/Dovitinib-sensitive models, Imatinib and Dovitinib induced significant reduction in expression of p-ERK1/2, Bim, p-AKT (Ser473) and p-Cdc2 at 72 hours post treatment. Although inhibition of p-c-Kit (Tyr568/570) was observed, higher levels of p-Histone H2A-X (Ser139) and Cleaved PARP expression were observed in Dovitinib than Imatinib treatment, suggesting that Dovitinib was more effective than Imatinib in inducing cell death. Our data showed that Dovitinib treatment is able to provide greater advantages over Imatinib in all four PDX models regardless of their KIT mutational status, suggesting that Dovitinib may offer an alternative treatment for GIST that are insensitive to Imatinib. Citation Format: Huynh T. Hung, Richard Ong, Pierce Chow. Dovitinib exerts potent antitumor effects in gastrointestinal stromal tumors. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 795. doi:10.1158/1538-7445.AM2015-795

Pharmacological Inhibition of KIT Activates MET Signaling in Gastrointestinal Stromal Tumors.

Gastrointestinal stromal tumors (GIST) are the most common adult sarcomas and the oncogenic driver is usually a KIT or PDGFRA mutation. Although GISTs are often initially sensitive to imatinib or other tyrosine kinase inhibitors, resistance generally develops, necessitating backup strategies for therapy. In this study, we determined that a subset of human GIST specimens that acquired imatinib resistance acquired expression of activated forms of the MET oncogene. MET activation also developed after imatinib therapy in a mouse model of GIST (KitV558del/+ mice), where it was associated with increased tumor hypoxia. MET activation also occurred in imatinib-sensitive human GIST cell lines after imatinib treatment in vitro. MET inhibition by crizotinib or RNA interference was cytotoxic to an imatinib-resistant human GIST cell population. Moreover, combining crizotinib and imatinib was more effective than imatinib alone in imatinib-sensitive GIST models. Finally, cabozantinib, a dual MET and KIT small-molecule inhibitor, was markedly more effective than imatinib in multiple preclinical models of imatinib-sensitive and imatinib-resistant GIST. Collectively, our findings showed that activation of compensatory MET signaling by KIT inhibition may contribute to tumor resistance. Furthermore, our work offered a preclinical proof of concept for MET inhibition by cabozantinib as an effective strategy for GIST treatment.

Applying artificial vision models to human scene understanding.

How do we understand the complex patterns of neural responses that underlie scene understanding? Studies of the network of brain regions held to be scene-selective—the parahippocampal/lingual region (PPA), the retrosplenial complex (RSC), and the occipital place area (TOS)—have typically focused on single visual dimensions (e.g., size), rather than the high-dimensional feature space in which scenes are likely to be neurally represented. Here we leverage well-specified artificial vision systems to explicate a more complex understanding of how scenes are encoded in this functional network. We correlated similarity matrices within three different scene-spaces arising from: (1) BOLD activity in scene-selective brain regions; (2) behavioral measured judgments of visually-perceived scene similarity; and (3) several different computer vision models. These correlations revealed: (1) models that relied on mid- and high-level scene attributes showed the highest correlations with the patterns of neural activity within the scene-selective network; (2) NEIL and SUN—the models that best accounted for the patterns obtained from PPA and TOS—were different from the GIST model that best accounted for the pattern obtained from RSC; (3) The best performing models outperformed behaviorally-measured judgments of scene similarity in accounting for neural data. One computer vision method—NEIL (“Never-Ending-Image-Learner”), which incorporates visual features learned as statistical regularities across web-scale numbers of scenes—showed significant correlations with neural activity in all three scene-selective regions and was one of the two models best able to account for variance in the PPA and TOS. We suggest that these results are a promising first step in explicating more fine-grained models of neural scene understanding, including developing a clearer picture of the division of labor among the components of the functional scene-selective brain network.

Augmentation of multiple protein kinase activities associated with secondary imatinib resistance in gastrointestinal stromal tumors as revealed by quantitative phosphoproteome analysis.

In this study, we performed a quantitative phosphoproteome analysis using a cell culture-based GIST model system. The goal of the study was to investigate the mechanism of acquired resistance in GISTs against imatinib, a molecularly targeted drug that inhibits kinase activity of the KIT protein and that has been approved for the treatment of GISTs. In imatinib-resistant GIST cells, we observed elevated expression of KIT and restoration of its kinase activity, as well as activation of multiple proliferative signaling pathways. Our results indicate that the effects of even so-called 'molecularly targeted' drugs, are broad rather than convergent, and that the mechanisms of action of such drugs during continuous administration are extremely complex.

A Panel of Gastrointestinal Stromal Tumours (Gist) Xenograft Models for in Vivo Preclinical Drug Testing

ABSTRACT Aim: Most GIST are dependent on the KIT/PDGFRA signalling pathway and therefore can be treated with specific tyrosine kinase inhibitors (TKI). With time GIST develop resistance to the TKI. We need reliable models which can be used for preclinical drug testing. Methods: Patient-derived xenografts were established in nu/nu NMRI mice by subcutaneous implantation of fresh, surgically resected tumour specimens from consenting patients with GIST treated at the University Hospitals Leuven. Once tumour growth was observed, pieces of tumour were re-transplanted to next generations of mice. At each passage tumour fragments were collected for histological and molecular characterization. A model was considered to be established after observing stable histological and molecular features for at least two passages. Results: At present we have access to five successfully established GIST models, with different KIT mutations and different sensitivity to standard TKIs (Table). Established GIST xenograft models and their sensitivity to standard treatment. In vivo efficacy was assessed by % of relative tumour volume after 3 weeks under either imatinib (50mg/kg BID) or sunitinib (40mg/kg QD) Model* KIT mutation In vivo efficacy Imatinib Sunitinib UZLX-GIST1 p.V560D 20 20 UZLX-GIST2 p.A502_Y503dup 170 80 UZLX-GIST3 p.W557_V559delinsF 25 25 UZLX-GIST4 p.K558_G565delinsR 45 20 UZLX-GIST9 p.P577del; p.W557LfsX5; p.D820G 250 170 *models which showed tumor growth for at least two passages Untreated tumours from subsequent passages show morphological and immunohistochemical features resembling the original patient biopsy, verifying the stability GIST xenografts growth. KIT mutational status has also been confirmed in samples obtained from all models. These models are used for subsequent testing of new therapeutic approaches and current results have had an impact on at least four prospective clinical trials. If needed, we parallel our patient-derived models with in vitro or in vivo studies using one of the few established GIST cell lines. Conclusions: Our established GIST xenografts maintain the histological and molecular characteristics of the original patient sample and are a very useful and reliable preclinical platform for testing the new targeted approaches in GIST. Disclosure: All authors have declared no conflicts of interest.

Evaluation of a multi-site weather generator in simulating precipitation in the Qiantang River Basin, East China

Recent years have seen a surge in assessment of potential impacts of climate change. As one of the most important tools for generating synthetic hydrological model inputs, weather generators have played an important role in climate change impact analysis of water management. However, most weather generators like statistical downscaling model (SDSM) and long Ashton research station weather generator (LARS-WG) are designed for single site data generation. Considering the significance of spatial correlations of hydro-meteorological data, multi-site weather data generation becomes a necessity. In this study we aim to evaluate the performance of a new multi-site stochastic model, geo-spatial temporal weather generator (GiST), in simulating precipitation in the Qiantang River Basin, East China. The correlation matrix, precipitation amount and occurrence of observed and GiST-generated data are first compared for the evaluation process. Then we use the GiST model combined with the change factor method (CFM) to investigate future changes of precipitation (2071–2100) in the study area using one global climate model, Hadgem2_ES, and an extreme emission scenario RCP 8.5. The final results show that the simulated precipitation amount and occurrence by GiST matched their historical counterparts reasonably. The correlation coefficients between simulated and historical precipitations show good consistence as well. Compared with the baseline period (1961–1990), precipitation in the future time period (2071–2100) at high elevation stations will probably increase while at other stations decreases will occur. This study implies potential application of the GiST stochastic model in investigating the impact of climate change on hydrology and water resources.

Testing of geroprotectors in experiments on cell cultures: Choosing the correct model system

We believe that cytogerontological models, such as the Hayflick model, though very useful for experimental gerontology, are based only on certain correlations and do not directly apply to the gist of the aging process. Thus, the Hayflick limit concept cannot explain why we age, whereas our “stationary phase aging” model appears to be a “gist model,” since it is based on the hypothesis that the main cause of both various “age-related” changes in stationary cell cultures and similar changes in the cells of aging multicellular organism is the restriction of cell proliferation. The model is applicable to experiments on a wide variety of cultured cells, including normal and transformed animal and human cells, plant cells, bacteria, yeasts, mycoplasmas, etc. The results of relevant studies show that cells in this model die out in accordance with the Gompertz law, which describes exponential increase of the death probability with time. Therefore, the “stationary phase aging” model may prove effective in testing of various geroprotectors (anti-aging factors) and geropromoters (pro-aging factors) in cytogerontological experiments. It should be emphasized, however, that even the results of such experiments do not always agree with the data obtained in vivo and therefore cannot be regarded as final but should be verified in studies on laboratory animals and in clinical trials (provided this complies with ethical principles of human subject research).

Abstract 3927: Evaluating new therapies in Gastrointestinal Stromal Tumor using in vivo molecular optical imaging.

Abstract Gastrointestinal stromal tumors (GISTs) are the most common mesenchymal tumors with an estimated annual incidence of ∼6,000 new cases in the United States. The majority (∼75%) of GISTs possess gain-of-function mutations in KIT exons 9, 11, 13 or 17, causing constitutive activation of the kinase receptor, with smaller subsets possessing either gain-of-function mutations in PDGFRA (exons 12, 14 or 18) or BRAF (exon 15). Management of GIST has been transformed by the identification of these tumor driver mutations leading to unprecedented disease control of advanced GIST with the introduction of imatinib mesylate (IM). Despite the efficacy of IM, most patients experience primary and/or secondary resistance within 2 years of treatment. Therefore additional therapies are needed and methods to optimize screening of novel approaches are warranted. Efficacy of treatment is typically assessed using Response Evaluation Criteria In Solid Tumors (RECIST) guidelines. Using RECIST, patients with advanced disease have equivalent survival when they have stable disease as when they have complete or partial responses. The Choi criteria define treatment response as a >10% decrease in tumor size or a >15% decrease in tumor density of tumor lesions assessed on CT scans. Response by Choi criteria has been shown to correlate better with FDG-PET than RECIST response, but can only be used with contrast enhanced CT imaging. RECIST and Choi both require a period of time on therapy before changes indicative of response can be observed. None of these criteria however informs us directly about cell death. Here we evaluate the use of molecular imaging technology using near-infrared (NIR) imaging probes in combination with three-dimensional fluorescence molecular tomography (FMT) for assessing therapeutic response and ultimately optimizing our understanding of the biologic effects of these agents. We determine the potential of two NIR probes (PSVueTM794 and KcapQ647) for detecting apoptosis and compare this to tumor size measured by MRI in response to IM treatment in GIST-T1 xenografts. PSVueTM794, used as a marker of apoptosis, binds to phosphatidylserine residues exposed on the surface of apoptotic cells and, in addition, binds to negatively-charged necrotic regions found in various tumors. KcapQ647, a cell penetrating activatable probe was used to detect apoptosis-associated caspase acitivity. Our studies revealed statistically significant increases in apoptotic activity due to IM treatment (compared to control) using both the PSVue TM794 and KcapQ647 probes (p=1.41e-04, 0.002 respectively) as early as 24 hours post IM treatment. These findings were confirmed by IHC. We believe that this methodology will allow for faster and more effective screening of novel therapies in preclinical GIST models. Citation Format: Lori A. Rink, Harvey Hensley, Karthik Devarajan, James R. Johnson, David Piwinica-Worms, Andrew K. Godwin, Margaret von Mehren. Evaluating new therapies in Gastrointestinal Stromal Tumor using in vivo molecular optical imaging. [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 3927. doi:10.1158/1538-7445.AM2013-3927

Biologically inspired task oriented gist model for scene classification

Capturing the scene gist is account for rapid and accurate scene classification in human visual system. This paper presents a biologically inspired task oriented gist model (BT-Gist) that attempts to emulate two important attributes of biological gist: holistic scene centered spatial layout representation and task oriented resolution determination. For the first attribute, we enrich the model of Oliva and Torralba by refining the low-level features in several biological plausible ways, extending the spatial layout to multiple resolution and followed by perceptually meaningful manifold analysis for a set of multi-resolution biologically inspired intrinsic manifold spatial layouts (BMSLs). Since the optimal resolution that best represents the spatial layout varies from task to task, we embody the second attribute as learning the combination of BMSLs of multiple resolution with respect to their optimal discriminative invariance trade-off for the task at hand, and then cast it in the SVM based localized multiple kernel learning (LMKL) framework, by which the kernel of each scene gist is approximated as a local combination of kernels associated to multi-resolution BMSLs. By exploring the task specific category distribution pattern over BMSL, we define the local model as a category distribution sensitive (CDS) kernel, which can accommodate both the diverse individuality of specific BMSL and the universality shared within the whole category space. Via CDS-LMKL, both the optimal resolution for spatial layouts and the final classifier can be efficiently obtained in a joint manner. We evaluate BT-Gist on four natural scene databases and one cluttered indoor scene database with a range of comparison: From different MKL methods, to various biologically inspired models and BoF based computer vision models. CDS-LMKL leads to better results compared to several existing MKL algorithms. Given the two biological attributes that the framework has to follow, BT-Gist, despite its holistic nature, outperforms existing biologically inspired models and BoF based computer vision models in natural scene classification, and competes with the object segmentation based ROI-Gist in cluttered indoor scene classification.

Statistics of eye movements in scene categorization and scene memorization

Humans can grasp the gist of complex natural scenes in less than 100 milliseconds. To model this rapid scene perception, we developed ultra-sparse structural representations of natural scenes. In this model, a natural scene is represented by a probability distribution based on a set of natural scene structures and their spatial concatenations. In contrast to bottom-up, image-based processing and recent scene gist models based on global features, the structural representations in our model require no isolation of objects, nor computation of global scene features. We tested this model by comparing the patterns of eye movements of human subjects while they were performing two scene-viewing tasks, scene categorization and scene memorization[1,2]. Since human vision system always actively seeks visual information needed to support current cognitive requirements[3], we predicted that the subjects would scan more informative patches of the scenes in scene categorization than in scene memorization. We examined the statistics of the eye movements of the subjects in the two tasks. We found that: 1) the average number of fixations in scene categorization was significantly less than that in scene memorization (t = 7.02, p < 0.001); 2) the average fixation duration in scene categorization was significant longer than that in scene memorization (t = 2, p = 0.05); 3) the subjects executed more long fixations in scene categorization than in scene memorization; and 4) the total length of the scan paths in scene categorization was shorter than that in scene memorization (t = 5.48, p < 0.01). We also developed models of scene categorization and scene memorization using the scene patches sampled at the fixations and found that the subjects extracted more informative scene patches in scene categorization than in scene memorization. Therefore, the subjects tended to coarsely scan the whole scenes when performing scene memorization, but opted to scan smaller scene patches with more detailed information when performing scene categorization. This observation supports our model of visual scenes as spatial concatenations of natural scene structures, each of which conveys a variety of amount of information about scene identity and category.

Sorafenib (SOR) in patients (pts) with imatinib (IM) and sunitinib (SU)-resistant (RES) gastrointestinal stromal tumors (GIST): Final results of a University of Chicago Phase II Consortium trial.

10009 Background: Treatment (tx) options are limited after GIST pts develop resistance to IM and SU. SOR inhibits KIT, VEGFR, PDGFR-β, and BRAF kinases. In preclinical GIST models, SOR inhibits many secondary resistance mutations, including IM-RES ATP-binding pocket and IM/SU-RES activation loop mutations (Heinrich, Proc ASCO 2009). Methods: We performed a multi-center, phase II trial of SOR in KIT-expressing GIST pts who had disease progression (PD) on IM by RECIST. After FDA approval of SU for GIST, the amended study required PD after both IM and SU. Pts received SOR 400 mg orally twice daily. Primary endpoint: objective response rate. A Simon minimax 2-stage design required 1 response in 18 pts for a 2nd stage, and 4 responses in 32 IM/SU RES pts for further study. Results: 38 pts (6 IM-RES, 32 IM/SU-RES) enrolled 1/06-9/09 at 6 centers. Pt characteristics: male 55%; median age 57 (range 42-85); PS 0/1/2: 47%/47%/5%; liver metastases 74%; primary drug resistance (PD ≤ 6 mo): IM 3%, SU 59%. Baseline mut...

Comparison of gist models in rapid scene categorization tasks

Comparison of gist models in rapid scene categorization tasks

Multi-scale and multi-modal GIS-T data model

The role of urban transportation becomes increasingly important with the change of demographic and economic patterns. The trend to expect better urban living standards for inhabitants has significantly increased the demand for efficient and sustainable multi-modal transportation systems in large urban areas. This should favour emergence of balanced transportation system that uses each mode for what it does best. But still, the development of urban transportation policies partly relies on the availability of appropriate data and information. The research presented in this paper proposes a multi-modal and multi-scale GIS-T data model. The model introduced takes into account different transportation modes and integrates them within an integrated data model designed using an object-oriented approach. The model allows the development of specialised services designed after a survey and study of users’ and planners’ requirements. The approach is applied in a district of the city of Guangzhou and validated by a prototype development. This experimental system enables transportation planners and decision-makers to take better decisions effectively, and provides high-quality geospatial information-based services to final end-users.