Durvalumab and guadecitabine in advanced clear cell renal cell carcinoma: results from the phase Ib/II study BTCRC-GU16-043

Epigenetic modulation is well established in hematologic malignancies but to a lesser degree in solid tumors. Here we report the results of a phase Ib/II study of guadecitabine and durvalumab in advanced clear cell renal cell carcinoma (ccRCC; NCT03308396). Patients received guadecitabine (starting at 60 mg/m2 subcutaneously on days 1-5 with de-escalation to 45 mg/m2 in case of dose limiting toxicity) with durvalumab (1500 mg intravenously on day 8). The study enrolled 57 patients, 6 in phase Ib with safety being the primary objective and 51in phase II, comprising 2 cohorts: 36 patients in Cohort 1 were treatment naive to checkpoint inhibitors (CPI) with 0-1 prior therapies and 15 patients in Cohort 2 were treated with up to two prior systemic therapies including one CPI. The combination of guadecitabine 45 mg/m2 with durvalumab 1500 mg was deemed safe. The primary objective of overall response rate (ORR) in cohort 1 was 22%. Sixteen patients (44%) experienced stable disease (SD). Secondary objectives included overall survival (OS), duration of response, progression-free survival (PFS), clinical benefit rate, and safety as well as ORR for Cohort 2. Median PFS for cohort 1 and cohort 2 were 14.26 and 3.91 months respectively. Median OS was not reached. In cohort 2, one patient achieved a partial response and 60% achieved SD. Asymptomatic neutropenia was the most common adverse event. Even though the trial did not meet the primary objective in cohort 1, the tolerability and PFS signal in CPI naive patients are worth further investigation.

Final results of phase Ib/II study of durvalumab and guadecitabine in advanced clear cell renal cell carcinoma (ccRCC) and biomarker analysis

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Background: Hypomethylating agents (HMA) can augment the anti-tumor immune response. Guadecitabine (G) is a novel HMA shown to induce a dose-dependent decrease of global DNA and gene-specific methylation in pre-clinical models. Methods: This is phase Ib/II clinical trial of Guadecitabine (G) and Durvalumab (D) in advanced ccRCC. Phase Ib tested two doses of G, de-escalated from 60 mg/m2 to 45 mg/m2 in combination with standard dose of D. Followed by two cohorts in phase II. Cohort 1 (C1, CPI naïve) allowed up to one prior line of treatment and Cohort 2 (C2, CPI refractory) enrolled patients with up to two prior systemic therapies including at least one CPI. Primary endpoint in phase 1b was safety, primary endpoint in phase II was overall response rate (ORR) and secondary endpoint of progression free survival (PFS) and overall survival (OS) and biomarkers evaluation. Results: Fifty-seven patients were enrolled, 42 were in C1 and 15 in C2. One dose limiting toxicity (DLT) of grade 3 neutropenia was noted with G 60 mg/m2. The combination of G 45 mg/m2 on days 1-5 along with D at 1500 mg on day 8, was deemed safe and the recommended phase II dose. Asymptomatic neutropenia was the most common adverse event (AE). Other AEs included thyroid dysfunction, diarrhea, pneumonitis, myalgia, and hepatotoxicity. No treatment-related deaths were reported. The ORR for C1 and C2 were 26% and 7% respectively. The median PFS for C1 and C2 were 18.4 and 3.9 months respectively. Median OS was not reached. Flow cytometry on peripheral blood (PB) collected before treatment demonstrated myeloid-derived suppressor cells (MDSC) to be inversely associated with response, showing the highest levels in progressive disease (PD) and the lowest in partial response (PR). Responders to treatment had the highest expression of IFN γ, IL-17 and RORyt in CD8+ T cells and lower Foxp3 expression in CD4+ T cells compared to non-responders. We observed a significant increase in serum CXCL9/CXCL10 with the study combination (p 0.00003 and p 0.000005 respectively) and this increase correlated with better clinical outcome. Conclusions: The combination of D and G has an acceptable toxicity profile and promising efficacy mainly PFS in CPI naïve ccRCC patients, that is worth further investigation in larger randomized clinical trial. Clinical trial information: NCT03308396 .

SRGN-Triggered Aggressive and Immunosuppressive Phenotype in a Subset of TTF-1-Negative Lung Adenocarcinomas

BACKGROUND

About 20% of lung adenocarcinoma (LUAD) is negative for the lineage-specific oncogene Thyroid transcription factor 1 (TTF-1) and exhibits worse clinical outcome with a low frequency of actionable genomic alterations. To identify molecular features associated with TTF-1-negative LUAD, we compared the transcriptomic and proteomic profiles of LUAD cell lines. SRGN, a chondroitin sulfate proteoglycan Serglycin, was identified as a markedly overexpressed gene in TTF-1-negative LUAD. We therefore investigated the roles and regulation of SRGN in TTF-1-negative LUAD.

METHODS

Proteomic and metabolomic analyses of 41 LUAD cell lines were done using mass spectrometry. The function of SRGN was investigated in 3 TTF-1-negative and 4 TTF-1-positive LUAD cell lines and in a syngeneic mouse model (n = 5 to 8 mice per group). Expression of SRGN in was evaluated in 94 and 105 surgically resected LUAD tumor specimens using immunohistochemistry. All statistical tests were two-sided.

RESULTS

SRGN was markedly overexpressed at mRNA and protein levels in TTF-1-negative LUAD cell lines (P < .001 for both mRNA and protein levels). Expression of SRGN in LUAD tumor tissue was associated with poor outcome (hazard ratio = 4.22, 95% confidential interval = 1.12 to 15.86; likelihood ratio test, P = .03), and with higher expression of Programmed cell death 1 ligand 1 (PD-L1) in tumor cells and higher infiltration of Programmed cell death protein 1 (PD-1)-positive lymphocytes. SRGN regulated expression of PD-L1, as well as proinflammatory cytokines including Interleukin-6 (IL-6), Interleukin-8 (IL-8), and C-X-C motif chemokine 1 (CXCL1) in LUAD cell lines, and increased migratory and invasive properties of LUAD cells and fibroblasts, and enhanced angiogenesis. SRGN was induced by DNA de-methylation resulting from Nicotinamide N-methyltransferase (NNMT)-mediated impairment of methionine metabolism.

CONCLUSION

Our findings suggest that SRGN plays a pivotal role in tumor-stromal interaction and reprogramming into an aggressive and immunosuppressive tumor microenvironment in TTF-1-negative LUAD.

The Calcium Versus Hemorrhage Trial: Developing Diagnostic Criteria for Chronic Intracranial Susceptibility Lesions Using Single-Energy Computed Tomography, Dual-Energy Computed Tomography, and Quantitative Susceptibility Mapping

PURPOSE

Chronic susceptibility lesions in the brain can be either hemorrhagic (potentially dangerous) or calcific (usually not dangerous) but are difficult to discriminate on routine imaging. We proposed to develop quantitative diagnostic criteria for single-energy computed tomography (SECT), dual-energy computed tomography (DECT), and quantitative susceptibility mapping (QSM) to distinguish hemorrhage from calcium.

MATERIALS AND METHODS

Patients with positive susceptibility lesions on routine T2*-weighted magnetic resonance of the brain were recruited into this prospective imaging clinical trial, under institutional review board approval and with informed consent. The SECT, DECT, and QSM images were obtained, the lesions were identified, and the regions of interest were defined, with the mean values recorded. Criteria for quantitative interpretation were developed on the first 50 patients, and then applied to the next 45 patients. Contingency tables, scatter plots, and McNemar test were applied to compare classifiers.

RESULTS

There were 95 evaluable patients, divided into a training set of 50 patients (328 lesions) and a validation set of 45 patients (281 lesions). We found the following classifiers to best differentiate hemorrhagic from calcific lesions: less than 68 Hounsfield units for SECT, calcium level of less than 15 mg/mL (material decomposition value) for DECT, and greater than 38 ppb for QSM. There was general mutual agreement among the proposed criteria. The proposed criteria outperformed the current published criteria.

CONCLUSIONS

We provide the updated criteria for the classification of chronic positive susceptibility brain lesions as hemorrhagic versus calcific for each major clinically available imaging modality. These proposed criteria have greater internal consistency than the current criteria and should likely replace it as gold standard.

Estimating Local Cellular Density in Glioma Using MR Imaging Data

BACKGROUND AND PURPOSE

Increased cellular density is a hallmark of gliomas, both in the bulk of the tumor and in areas of tumor infiltration into surrounding brain. Altered cellular density causes altered imaging findings, but the degree to which cellular density can be quantitatively estimated from imaging is unknown. The purpose of this study was to discover the best MR imaging and processing techniques to make quantitative and spatially specific estimates of cellular density.

MATERIALS AND METHODS

We collected stereotactic biopsies in a prospective imaging clinical trial targeting untreated patients with gliomas at our institution undergoing their first resection. The data included preoperative MR imaging with conventional anatomic, diffusion, perfusion, and permeability sequences and quantitative histopathology on biopsy samples. We then used multiple machine learning methodologies to estimate cellular density using local intensity information from the MR images and quantitative cellular density measurements at the biopsy coordinates as the criterion standard.

RESULTS

The random forest methodology estimated cellular density with R 2 = 0.59 between predicted and observed values using 4 input imaging sequences chosen from our full set of imaging data (T2, fractional anisotropy, CBF, and area under the curve from permeability imaging). Limiting input to conventional MR images (T1 pre- and postcontrast, T2, and FLAIR) yielded slightly degraded performance (R2 = 0.52). Outputs were also reported as graphic maps.

CONCLUSIONS

Cellular density can be estimated with moderate-to-strong correlations using MR imaging inputs. The random forest machine learning model provided the best estimates. These spatially specific estimates of cellular density will likely be useful in guiding both diagnosis and treatment.

Guiding the first biopsy in glioma patients using estimated Ki-67 maps derived from MRI: conventional versus advanced imaging

BACKGROUND

Undersampling of gliomas at first biopsy is a major clinical problem, as accurate grading determines all subsequent treatment. We submit a technological solution to reduce the problem of undersampling by estimating a marker of tumor proliferation (Ki-67) using MR imaging data as inputs, against a stereotactic histopathology gold standard.

METHODS

MR imaging was performed with anatomic, diffusion, permeability, and perfusion sequences, in untreated glioma patients in a prospective clinical trial. Stereotactic biopsies were harvested from each patient immediately prior to surgical resection. For each biopsy, an imaging description (23 parameters) was developed, and the Ki-67 index was recorded. Machine learning models were built to estimate Ki-67 from imaging inputs, and cross validation was undertaken to determine the error in estimates. The best model was used to generate graphical maps of Ki-67 estimates across the whole brain.

RESULTS

Fifty-two image-guided biopsies were collected from 23 evaluable patients. The random forest algorithm best modeled Ki-67 with 4 imaging inputs (T2-weighted, fractional anisotropy, cerebral blood flow, Ktrans). It predicted the Ki-67 expression levels with a root mean square (RMS) error of 3.5% (R2 = 0.75). A less accurate predictive result (RMS error 5.4%, R2 = 0.50) was found using conventional imaging only.

CONCLUSION

Ki-67 can be predicted to clinically useful accuracies using clinical imaging data. Advanced imaging (diffusion, perfusion, and permeability) improves predictive accuracy over conventional imaging alone. Ki-67 predictions, displayed as graphical maps, could be used to guide biopsy, resection, and/or radiation in the care of glioma patients.

Imaging-Based Algorithm for the Local Grading of Glioma

BACKGROUND AND PURPOSE

Gliomas are highly heterogeneous tumors, and optimal treatment depends on identifying and locating the highest grade disease present. Imaging techniques for doing so are generally not validated against the histopathologic criterion standard. The purpose of this work was to estimate the local glioma grade using a machine learning model trained on preoperative image data and spatially specific tumor samples. The value of imaging in patients with brain tumor can be enhanced if pathologic data can be estimated from imaging input using predictive models.

MATERIALS AND METHODS

Patients with gliomas were enrolled in a prospective clinical imaging trial between 2013 and 2016. MR imaging was performed with anatomic, diffusion, permeability, and perfusion sequences, followed by image-guided stereotactic biopsy before resection. An imaging description was developed for each biopsy, and multiclass machine learning models were built to predict the World Health Organization grade. Models were assessed on classification accuracy, Cohen κ, precision, and recall.

RESULTS

Twenty-three patients (with 7/9/7 grade II/III/IV gliomas) had analyzable imaging-pathologic pairs, yielding 52 biopsy sites. The random forest method was the best algorithm tested. Tumor grade was predicted at 96% accuracy (κ = 0.93) using 4 inputs (T2, ADC, CBV, and transfer constant from dynamic contrast-enhanced imaging). By means of the conventional imaging only, the overall accuracy decreased (89% overall, κ = 0.79) and 43% of high-grade samples were misclassified as lower-grade disease.

CONCLUSIONS

We found that local pathologic grade can be predicted with a high accuracy using clinical imaging data. Advanced imaging data improved this accuracy, adding value to conventional imaging. Confirmatory imaging trials are justified.

Quantile Graphical Models: Bayesian Approaches

Graphical models are ubiquitous tools to describe the interdependence between variables measured simultaneously such as large-scale gene or protein expression data. Gaussian graphical models (GGMs) are well-established tools for probabilistic exploration of dependence structures using precision matrices and they are generated under a multivariate normal joint distribution. However, they suffer from several shortcomings since they are based on Gaussian distribution assumptions. In this article, we propose a Bayesian quantile based approach for sparse estimation of graphs. We demonstrate that the resulting graph estimation is robust to outliers and applicable under general distributional assumptions. Furthermore, we develop efficient variational Bayes approximations to scale the methods for large data sets. Our methods are applied to a novel cancer proteomics data dataset where-in multiple proteomic antibodies are simultaneously assessed on tumor samples using reverse-phase protein arrays (RPPA) technology.

Concomitant targeting of the mTOR/MAPK pathways: novel therapeutic strategy in subsets of RICTOR/KRAS-altered non-small cell lung cancer

Despite a therapeutic paradigm shift into targeted-driven medicinal approaches, resistance to therapy remains a hallmark of lung cancer, driven by biological and molecular diversity. Using genomic and expression data from advanced non-small cell lung cancer (NSCLC) patients enrolled in the BATTLE-2 clinical trial, we identified RICTOR alterations in a subset of lung adenocarcinomas and found RICTOR expression to carry worse overall survival. RICTOR-altered cohort was significantly enriched in KRAS/MAPK axis mutations, suggesting a co-oncogenic driver role in these molecular settings. Using NSCLC cell lines, we showed that, distinctly in KRAS mutant backgrounds, RICTOR blockade impairs malignant properties and generates a compensatory enhanced activation of the MAPK pathway, exposing a unique therapeutic vulnerability. In vitro and in vivo concomitant pharmacologic inhibition of mTORC1/2 and MEK1/2 resulted in synergistic responses of anti-tumor effects. Our study provides evidence of a distinctive therapeutic opportunity in a subset of NSCLC carrying concomitant RICTOR/KRAS alterations.

A Coclinical Radiogenomic Validation Study: Conserved Magnetic Resonance Radiomic Appearance of Periostin-Expressing Glioblastoma in Patients and Xenograft Models

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.

TUSC2 Immunogene Therapy Synergizes with Anti-PD-1 through Enhanced Proliferation and Infiltration of Natural Killer Cells in Syngeneic Kras-Mutant Mouse Lung Cancer Models

Expression of the multikinase inhibitor encoded by the tumor suppressor gene TUSC2 (also known as FUS1) is lost or decreased in non-small cell lung carcinoma (NSCLC). TUSC2 delivered systemically by nanovesicles has mediated tumor regression in clinical trials. Because of the role of TUSC2 in regulating immune cells, we assessed TUSC2 efficacy on antitumor immune responses alone and in combination with anti-PD-1 in two Kras-mutant syngeneic mouse lung cancer models. TUSC2 alone significantly reduced tumor growth and prolonged survival compared with anti-PD-1. When combined, this effect was significantly enhanced, and correlated with a pronounced increases in circulating and splenic natural killer (NK) cells and CD8⁺ T cells, and a decrease in regulatory T cells (Tregs), myeloid-derived suppressor cells (MDSCs), and T-cell checkpoint receptors PD-1, CTLA-4, and TIM-3. TUSC2 combined with anti-PD-1 induced tumor infiltrating more than NK and CD8⁺ T cells and fewer MDSCs and Tregs than each agent alone, both in subcutaneous tumor and in lung metastases. NK-cell depletion abrogated the antitumor effect and Th1-mediated immune response of this combination, indicating that NK cells mediate TUSC2/anti-PD-1 synergy. Release of IL15 and IL18 cytokines and expression of the IL15Rα chain and IL18R1 were associated with NK-cell activation by TUSC2. Immune response-related gene expression in the tumor microenvironment was altered by combination treatment. These data provide a rationale for immunogene therapy combined with immune checkpoint blockade in the treatment of NSCLC. Cancer Immunol Res; 6(2); 163-77. ©2018 AACR.

Integrating Clinical and Multiple Omics Data for Prognostic Assessment across Human Cancers

Multiple omic profiles have been generated for many cancer types; however, comprehensive assessment of their prognostic values across cancers is limited. We conducted a pan-cancer prognostic assessment and presented a multi-omic kernel machine learning method to systematically quantify the prognostic values of high-throughput genomic, epigenomic, and transcriptomic profiles individually, integratively, and in combination with clinical factors for 3,382 samples across 14 cancer types. We found that the prognostic performance varied substantially across cancer types. mRNA and miRNA expression profile frequently performed the best, followed by DNA methylation profile. Germline susceptibility variants displayed low prognostic performance consistently across cancer types. The integration of omic profiles with clinical variables can lead to substantially improved prognostic performance over the use of clinical variables alone in half of cancer types examined. Moreover, we showed that the kernel machine learning method consistently outperformed existing prognostic signatures, suggesting that including a large number of omic biomarkers may provide substantial improvement in prognostic assessment. Our study provides a comprehensive portrait of omic architecture for tumor prognosis across cancers, and highlights the prognostic value of genome-wide omic biomarker aggregation, which may facilitate refined prognostic assessment in the era of precision oncology.

Abstract 2674: Fusobacterium nucleatum subspecies animalis influences pro-inflammatory cytokine expression and monocyte activation in human colorectal tumors

Chronic infection and associated inflammation have long been suspected to promote human carcinogenesis. Recently, certain gut bacteria, including some in the Fusobacterium genus, have been implicated in playing a role in human colorectal cancer (CRC) development. However, the Fusobacterium species and subspecies involved and their oncogenic mechanisms remain to be determined. We sought to identify the specific Fusobacterium spp. and ssp. in clinical CRC specimens by targeted sequencing of Fusobacterium 16S ribosomal RNA gene. Five Fusobacterium spp. were identified in clinical CRC specimens. Additional analyses confirmed that Fusobacterium nucleatum ssp. animalis was the most prevalent F. nucleatum subspecies in human CRCs. We also assessed inflammatory cytokines in CRC specimens using immunoassays and found that expression of the cytokines interleukin-17A and tumor necrosis factor-alpha was markedly increased but interleukin-21 decreased in the colorectal tumors. Furthermore, the chemokine (C-C motif) ligand 20 was differentially expressed in colorectal tumors at all stages. In in vitro co-culture assays, F. nucleatum ssp. animalis induced CCL20 expression in CRC cells and monocytes. It also stimulated the monocyte/macrophage activation and migration. Our observations suggested that infection with F. nucleatum ssp. animalis in colorectal tissue could induce inflammatory response and promote CRC development. Further studies are warranted to determine if F. nucleatum ssp. animalis could be a novel target for CRC prevention and treatment.

Citation Format: Xiangcang Ye, Rui Wang, Rajat Bhattacharya, Delphine R. Boulbes, Fan Fan, Ling Xia, Adoni Harish, Nadim J. Ajami, Matthew C. Wong, Daniel P. Smith, Joseph F. Petrosino, Susan Venable, Wei Qiao, Veera Baladandayuthapani, Dipen Maru, Lee M. Ellis. Fusobacterium nucleatum subspecies animalis influences pro-inflammatory cytokine expression and monocyte activation in human colorectal tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2674. doi:10.1158/1538-7445.AM2017-2674

Fusobacterium Nucleatum Subspecies Animalis Influences Proinflammatory Cytokine Expression and Monocyte Activation in Human Colorectal Tumors

Chronic infection and associated inflammation have long been suspected to promote human carcinogenesis. Recently, certain gut bacteria, including some in the Fusobacterium genus, have been implicated in playing a role in human colorectal cancer development. However, the Fusobacterium species and subspecies involved and their oncogenic mechanisms remain to be determined. We sought to identify the specific Fusobacterium spp. and ssp. in clinical colorectal cancer specimens by targeted sequencing of Fusobacterium 16S ribosomal RNA gene. Five Fusobacterium spp. were identified in clinical colorectal cancer specimens. Additional analyses confirmed that Fusobacterium nucleatum ssp. animalis was the most prevalent F. nucleatum subspecies in human colorectal cancers. We also assessed inflammatory cytokines in colorectal cancer specimens using immunoassays and found that expression of the cytokines IL17A and TNFα was markedly increased but IL21 decreased in the colorectal tumors. Furthermore, the chemokine (C-C motif) ligand 20 was differentially expressed in colorectal tumors at all stages. In in vitro co-culture assays, F. nucleatum ssp. animalis induced CCL20 protein expression in colorectal cancer cells and monocytes. It also stimulated the monocyte/macrophage activation and migration. Our observations suggested that infection with F. nucleatum ssp. animalis in colorectal tissue could induce inflammatory response and promote colorectal cancer development. Further studies are warranted to determine if F. nucleatum ssp. animalis could be a novel target for colorectal cancer prevention and treatment. Cancer Prev Res; 10(7); 398-409. ©2017 AACR.

Performance Assessment for Brain MR Imaging Registration Methods

BACKGROUND AND PURPOSE

Clinical brain MR imaging registration algorithms are often made available by commercial vendors without figures of merit. The purpose of this study was to suggest a rational performance comparison methodology for these products.

MATERIALS AND METHODS

Twenty patients were imaged on clinical 3T scanners by using 4 sequences: T2-weighted, FLAIR, susceptibility-weighted angiography, and T1 postcontrast. Fiducial landmark sites (n = 1175) were specified throughout these image volumes to define identical anatomic locations across sequences. Multiple registration algorithms were applied by using the T2 sequence as a fixed reference. Euclidean error was calculated before and after each registration and compared with a criterion standard landmark registration. The Euclidean effectiveness ratio is the fraction of Euclidean error remaining after registration, and the statistical effectiveness ratio is similar, but accounts for dispersion and noise.

RESULTS

Before registration, error values for FLAIR, susceptibility-weighted angiography, and T1 postcontrast were 2.07 ± 0.55 mm, 2.63 ± 0.62 mm, and 3.65 ± 2.00 mm, respectively. Postregistration, the best error values for FLAIR, susceptibility-weighted angiography, and T1 postcontrast were 1.55 ± 0.46 mm, 1.34 ± 0.23 mm, and 1.06 ± 0.16 mm, with Euclidean effectiveness ratio values of 0.493, 0.181, and 0.096 and statistical effectiveness ratio values of 0.573, 0.352, and 0.929 for rigid mutual information, affine mutual information, and a commercial GE registration, respectively.

CONCLUSIONS

We demonstrate a method for comparing the performance of registration algorithms and suggest the Euclidean error, Euclidean effectiveness ratio, and statistical effectiveness ratio as performance metrics for clinical registration algorithms. These figures of merit allow registration algorithms to be rationally compared.

Novel algorithmic approach predicts tumor mutation load and correlates with immunotherapy clinical outcomes using a defined gene mutation set

BACKGROUND

While clinical outcomes following immunotherapy have shown an association with tumor mutation load using whole exome sequencing (WES), its clinical applicability is currently limited by cost and bioinformatics requirements.

METHODS

We developed a method to accurately derive the predicted total mutation load (PTML) within individual tumors from a small set of genes that can be used in clinical next generation sequencing (NGS) panels. PTML was derived from the actual total mutation load (ATML) of 575 distinct melanoma and lung cancer samples and validated using independent melanoma (n = 312) and lung cancer (n = 217) cohorts. The correlation of PTML status with clinical outcome, following distinct immunotherapies, was assessed using the Kaplan-Meier method.

RESULTS

PTML (derived from 170 genes) was highly correlated with ATML in cutaneous melanoma and lung adenocarcinoma validation cohorts (R2 = 0.73 and R2 = 0.82, respectively). PTML was strongly associated with clinical outcome to ipilimumab (anti-CTLA-4, three cohorts) and adoptive T-cell therapy (1 cohort) clinical outcome in melanoma. Clinical benefit from pembrolizumab (anti-PD-1) in lung cancer was also shown to significantly correlate with PTML status (log rank P value < 0.05 in all cohorts).

CONCLUSIONS

The approach of using small NGS gene panels, already applied to guide employment of targeted therapies, may have utility in the personalized use of immunotherapy in cancer.

Selective Internal Radiation Therapy With Yttrium-90 Glass Microspheres: Biases and Uncertainties in Absorbed Dose Calculations Between Clinical Dosimetry Models

PURPOSE

To quantify differences that exist between dosimetry models used for ⁹⁰Y selective internal radiation therapy (SIRT).

METHODS AND MATERIALS

Retrospectively, 37 tumors were delineated on 19 post-therapy quantitative ⁹⁰Y single photon emission computed tomography/computed tomography scans. Using matched volumes of interest (VOIs), absorbed doses were reported using 3 dosimetry models: glass microsphere package insert standard model (SM), partition model (PM), and Monte Carlo (MC). Univariate linear regressions were performed to predict mean MC from SM and PM. Analysis was performed for 2 subsets: cases with a single tumor delineated (best case for PM), and cases with multiple tumors delineated (typical clinical scenario). Variability in PM from the ad hoc placement of a single spherical VOI to estimate the entire normal liver activity concentration for tumor (T) to nontumoral liver (NL) ratios (TNR) was investigated. We interpreted the slope of the resulting regression as bias and the 95% prediction interval (95%PI) as uncertainty. MC_NL^single represents MC absorbed doses to the NL for the single tumor patient subset; other combinations of calculations follow a similar naming convention.

RESULTS

SM was unable to predict MC_T^single or MC_T^multiple (p>.12, 95%PI >±177 Gy). However, SM^single was able to predict (p<.012) MC_NL^single, albeit with large uncertainties; SM^single and SM^multiple yielded biases of 0.62 and 0.71, and 95%PI of ±40 and ± 32 Gy, respectively. PM_T^single and PM_T^multiple predicted (p<2E-6) MC_T^single and MC_T^multiple with biases of 0.52 and 0.54, and 95%PI of ±38 and ± 111 Gy, respectively. The TNR variability in PM_T^single increased the 95%PI for predicting MC_T^single (bias = 0.46 and 95%PI = ±103 Gy). The TNR variability in PM_T^multiple modified the bias when predicting MC_T^multiple (bias = 0.32 and 95%PI = ±110 Gy).

CONCLUSIONS

The SM is unable to predict mean MC tumor absorbed dose. The PM is statistically correlated with mean MC, but the resulting uncertainties in predicted MC are large. Large differences observed between dosimetry models for ⁹⁰Y SIRT warrant caution when interpreting published SIRT absorbed doses. To reduce uncertainty, we suggest the entire NL VOI be used for TNR estimates when using PM.

INTEGRATIVE BAYESIAN ANALYSIS OF NEUROIMAGING-GENETIC DATA THROUGH HIERARCHICAL DIMENSION REDUCTION

Advances in neuromedicine have emerged from endeavors to elucidate the distinct genetic factors that influence the changes in brain structure that underlie various neurological conditions. We present a framework for examining the extent to which genetic factors impact imaging phenotypes described by voxel-wise measurements organized into collections of functionally relevant regions of interest (ROIs) that span the entire brain. Statistically, the integration of neuroimaging and genetic data is challenging. Because genetic variants are expected to impact different regions of the brain, an appropriate method of inference must simultaneously account for spatial dependence and model uncertainty. Our proposed framework combines feature extraction using generalized principal component analysis to account for inherent short- and long-range structural dependencies with Bayesian model averaging to effectuate variable selection in the presence of multiple genetic variants. The methods are demonstrated on a cocaine dependence study to identify ROIs associated with genetic factors that impact diffusion parameters.

PCAN: Probabilistic correlation analysis of two non-normal data sets

Most cancer research now involves one or more assays profiling various biological molecules, e.g., messenger RNA and micro RNA, in samples collected on the same individuals. The main interest with these genomic data sets lies in the identification of a subset of features that are active in explaining the dependence between platforms. To quantify the strength of the dependency between two variables, correlation is often preferred. However, expression data obtained from next-generation sequencing platforms are integer with very low counts for some important features. In this case, the sample Pearson correlation is not a valid estimate of the true correlation matrix, because the sample correlation estimate between two features/variables with low counts will often be close to zero, even when the natural parameters of the Poisson distribution are, in actuality, highly correlated. We propose a model-based approach to correlation estimation between two non-normal data sets, via a method we call Probabilistic Correlations ANalysis, or PCAN. PCAN takes into consideration the distributional assumption about both data sets and suggests that correlations estimated at the model natural parameter level are more appropriate than correlations estimated directly on the observed data. We demonstrate through a simulation study that PCAN outperforms other standard approaches in estimating the true correlation between the natural parameters. We then apply PCAN to the joint analysis of a microRNA (miRNA) and a messenger RNA (mRNA) expression data set from a squamous cell lung cancer study, finding a large number of negative correlation pairs when compared to the standard approaches.

CDK5 Regulates Paclitaxel Sensitivity in Ovarian Cancer Cells by Modulating AKT Activation, p21Cip1- and p27Kip1-Mediated G1 Cell Cycle Arrest and Apoptosis

Cyclin-dependent kinase 5 (CDK5) is a cytoplasmic serine/ threonine kinase. Knockdown of CDK5 enhances paclitaxel sensitivity in human ovarian cancer cells. This study explores the mechanisms by which CDK5 regulates paclitaxel sensitivity in human ovarian cancers. Multiple ovarian cancer cell lines and xenografts were treated with CDK5 small interfering RNA (siRNA) with or without paclitaxel to examine the effect on cancer cell viability, cell cycle arrest and tumor growth. CDK5 protein was measured by immunohistochemical staining of an ovarian cancer tissue microarray to correlate CDK5 expression with overall patient survival. Knockdown of CDK5 with siRNAs inhibits activation of AKT which significantly correlates with decreased cell growth and enhanced paclitaxel sensitivity in ovarian cancer cell lines. In addition, CDK5 knockdown alone and in combination with paclitaxel induced G1 cell cycle arrest and caspase 3 dependent apoptotic cell death associated with post-translational upregulation and nuclear translocation of TP53 and p27^Kip1 as well as TP53-dependent transcriptional induction of p21^Cip1 in wild type TP53 cancer cells. Treatment of HEYA8 and A2780 wild type TP53 xenografts in nu/nu mice with CDK5 siRNA and paclitaxel produced significantly greater growth inhibition than either treatment alone. Increased expression of CDK5 in human ovarian cancers correlates inversely with overall survival. CDK5 modulates paclitaxel sensitivity by regulating AKT activation, the cell cycle and caspase-dependent apoptosis. CDK5 inhibition can potentiate paclitaxel activity in human ovarian cancer cells.

Characteristics and outcomes of patients with multiple myeloma who develop therapy-related myelodysplastic syndrome, chronic myelomonocytic leukemia, or acute myeloid leukemia

BACKGROUND

Patients with multiple myeloma (MM) have had significant improvements in outcomes. An increased risk of therapy-related myeloid neoplasms (t-MNs) has also developed. Little is known about the characteristics and outcomes of these patients.

PATIENTS AND METHODS

Patients with MM treated at our institution from 1993 to 2011 were reviewed. Forty-seven patients were diagnosed with t-MN. Our primary objective was to evaluate the interval to t-MN, response to treatment, and overall survival (OS).

RESULTS

The median patient age at the MM diagnosis was 65 years. Of the 47 patients, 32 (68.0%) initially received conventional chemotherapeutic agents, 7 (14.9%), novel agents (eg, lenalidomide, thalidomide, bortezomib), and 8 (17.0%), a combination. Twenty patients (42.6%) underwent high-dose chemotherapy and autologous hematopoietic stem cell transplantation. The median interval from the MM diagnosis to t-MN was 7 years (95% CI, 5.0-28.0). Of the 47 patients, 33 (70.2%) developed therapy-related myelodysplastic syndrome (t-MDS), 11 (23.4%) acute myeloid leukemia (t-AML), and 3 (6.4%) chronic myelomonocytic leukemia (t-CMML). The median age at the t-MN diagnosis was 65 years. Of the 47 patients, 26 (78.8%) with t-MDS, 9 (81.8%) with t-AML, and 1 (33.3%) with t-CMML had complex/high-risk cytogenetics. The median OS for all 47 patients after the t-MN diagnosis was 6.3 months (95% CI, 4.0-8.7).

CONCLUSION

The development of t-MN in patients with MM is associated with poor outcomes. These patients, in general, have complex cytogenetic abnormalities and short complete remission and OS times. A better understanding of the disease biology and novel therapeutic approaches are warranted.

The association of diabetes and anti-diabetic medications with clinical outcomes in multiple myeloma

Background:

Insulin/insulin-like growth factor-1 signalling may underlie the promoting effect of type 2 diabetes on cancer. This study examined the association of diabetes, including steroid-induced diabetes (SID), and the impact of anti-diabetic medication on clinical outcomes of multiple myeloma (MM).

Methods:

A retrospective review was conducted of 1240 MM patients. Overall survival (OS) and MM disease status prior to death were analysed.

Results:

Diabetic patients had a significantly shorter OS than non-diabetic patients (median: 65.4 vs 98.7 months). In multivariate analysis, SID was a significant predictor of decreased OS, along with age, comorbidity, MM stage, and cytogenetic abnormalities. Analyzing only the diabetic MM patients, Cox regression showed that metformin predicted an increased OS, whereas use of insulin/analogues predicted a decreased OS. Competing risk analysis showed that DM was associated with increased cumulative incidence of death with progressive MM. Among the diabetics, multivariate regression showed that insulin/analogues were associated with increased, but metformin with decreased death with progressive MM. Potential immortal time bias was evaluated by landmark analyses.

Conclusions:

DM, SID in particular, is associated with poor clinical outcomes in MM. Insulin/analogues are associated with poor outcomes, whereas metformin is associated with improved outcomes. No conclusion about causal relationships can be made at this time. Managing hyperglycaemia with non-insulin regimens should be investigated in randomised trials.

Correlation of pretreatment nuclear GLI-1 labeling indices (LIs) with initial SUV (iSUV) in esophageal cancer (EC) patients undergoing trimodality therapy (TMT): A potential pathway to esophageal preservation

18

Background: For the purpose of understanding clinical behavior of EC, imaging and biomarkers have not been correlated. We attempted to correlate iSUV with a variety of biomarkers (NF-kB, SHH, ALDH1, ABCB1, survivin, and BCRP) including pre-treatment nuclear Gli-1 LIs in patients with EC who had undergone TMT. Methods: 128 patients were analyzed. The iSUV and pre-treatment nuclear Gli-1 LIs were assessed among others. Post-treatment residual cancer status in the resected specimen was also correlated (P0=0% residual cells, P1=1-50% residual cells, and P2=>50% residual cells) with iSUV and nuclear Gli-1 LIs. The Kruskal-Wallis test was performed to find correlations between (1) iSUV and P status; and (2) between nuclear Gli-1 LIs and P status. Results: The Pearson’s correlation coefficient between iSUV and nuclear Gli-1 LIs was 0.21 (p = 0.02). Pre-treatment nuclear Gli-1 LIs were strongly associated with the P status (p<0.0001) but iSUV was not (as has been reported in the literature; PMID: 17532577, 23247658, and 23994746). iSUV, most likely, is not correlative with the P status because of its narrow range compared to that of nuclear Gli-1 LIs.Conclusions: Our data, for the first time, demonstrate that iSUV can be a surrogate for pre-treatment nuclear Gli-1 LIs in EC. This correlation can be exploited in the development of predictive strategies for esophageal preservation. Pre-treatment nuclear Gli-1 is a strong candidate for the biomarker-based predictive model(s). From U. T. M. D. Anderson Cancer Center (UTMDACC), Houston, Texas, USA. Supported by UTMDACC Multidisciplinary Research Grants, CA138671, CA172741, and CA129926 From the NCI (JAA), and Generous Donors. [Table: see text]

Targeting MET kinase with the small-molecule inhibitor amuvatinib induces cytotoxicity in primary myeloma cells and cell lines

BACKGROUND

MET is a receptor tyrosine kinase that is activated by the ligand HGF and this pathway promotes cell survival, migration, and motility. In accordance with its oncogenic role, MET is constitutively active, mutated, or over-expressed in many cancers. Corollary to its impact, inhibition of MET kinase activity causes reduction of the downstream signaling and demise of cells. In myeloma, a B-cell plasma malignancy, MET is neither mutated nor over-expressed, however, HGF is increased in plasma or serum obtained from myeloma patients and this was associated with poor prognosis. The small-molecule, amuvatinib, inhibits MET receptor tyrosine kinase. Based on this background, we hypothesized that targeting the HGF/MET signaling pathway is a rational approach to myeloma therapy and that myeloma cells would be sensitive to amuvatinib.

METHODS

Expression of MET and HGF mRNAs in normal versus malignant plasma cells was compared during disease progression. Cell death and growth as well as MET signaling pathway were assessed in amuvatinib treated primary myeloma cells and cell lines.

RESULTS

There was a progressive increase in the transcript levels of HGF (but not MET) from normal plasma cells to refractory malignant plasma cells. Amuvatinib readily inhibited MET phosphorylation in primary CD138+ cells from myeloma patients and in concordance, increased cell death. A 48-hr amuvatinib treatment in high HGF-expressing myeloma cell line, U266, resulted in growth inhibition. Levels of cytotoxicity were time-dependent; at 24, 48, and 72 h, amuvatinib (25 μM) resulted in 28%, 40%, and 55% cell death. Consistent with these data, there was an amuvatinib-mediated decrease in MET phosphorylation in the cell line. Amuvatinib at concentrations of 5, 10, or 25 μM readily inhibited HGF-dependent MET, AKT, ERK and GSK-3-beta phosphorylation. MET-mediated effects were not observed in myeloma cell line that has low MET and/or HGF expression.

CONCLUSIONS

These data suggest that at the cellular level MET/HGF pathway inclines with myeloma disease progression. Amuvatinib, a small molecule MET kinase inhibitor, is effective in inducing growth inhibition and cell death in myeloma cell lines as well as primary malignant plasma cells. These cytostatic and cytotoxic effects were associated with an impact on MET/HGF pathway.

ALDH-1 expression levels predict response or resistance to preoperative chemoradiation in resectable esophageal cancer patients

PURPOSE

Operable thoracic esophageal/gastroesophageal junction carcinoma (EC) is often treated with chemoradiation and surgery but tumor responses are unpredictable and heterogeneous. We hypothesized that aldehyde dehydrogenase-1 (ALDH-1) could be associated with response.

METHODS

The labeling indices (LIs) of ALDH-1 by immunohistochemistry in untreated tumor specimens were established in EC patients who had chemoradiation and surgery. Univariate logistic regression and 3-fold cross validation were carried out for the training (67% of patients) and validation (33%) sets. Non-clinical experiments in EC cells were performed to generate complimentary data.

RESULTS

Of 167 EC patients analyzed, 40 (24%) had a pathologic complete response (pathCR) and 27 (16%) had an extremely resistant (exCRTR) cancer. The median ALDH-1 LI was 0.2 (range, 0.01-0.85). There was a significant association between pathCR and low ALDH-1 LI (p ≤ 0.001; odds-ratio [OR] = 0.432). The 3-fold cross validation led to a concordance index (C-index) of 0.798 for the fitted model. There was a significant association between exCRTR and high ALDH-1 LI (p ≤ 0.001; OR = 3.782). The 3-fold cross validation led to the C-index of 0.960 for the fitted model. In several cell lines, higher ALDH-1 LIs correlated with resistant/aggressive phenotype. Cells with induced chemotherapy resistance upregulated ALDH-1 and resistance conferring genes (SOX9 and YAP1). Sorted ALDH-1+ cells were more resistant and had an aggressive phenotype in tumor spheres than ALDH-1- cells.

CONCLUSIONS

Our clinical and non-clinical data demonstrate that ALDH-1 LIs are predictive of response to therapy and further research could lead to individualized therapeutic strategies and novel therapeutic targets for EC patients.

Abstract 3561: Silencing of farnesoid X receptor in human colon cancer by epigenetic mechanisms is associated with cancer progression

Background: Colon cancer is the third leading cause of cancer related deaths in the United States. Epidemiological studies suggest an increase in the intestinal bile-acid load resulting from the consumption of a high-fat diet is a significant risk factor for colon cancer. Bile acids are the endogenous ligands for the farnesoid X receptor (FXR), a ligand-activated transcription factor and member of the nuclear receptor superfamily, and high levels of bile acids can promote colon cancer development. FXR is essential for maintaining bile-acid homeostasis by regulating bile-acid synthesis and transport, preventing the accumulation of intestinal bile acid levels to cancer promoting levels. Previous studies have demonstrated that FXR knockout mice are more susceptible to the development of colon adenocarcinomas, indicating that FXR plays a suppressive role in colon tumor formation. This study investigates the role of FXR in the development of human colon cancer. Methods: Immunohistochemistry was used to label for FXR in normal human colon, colon polyps, and colon adenocarcinomas staged I-IV. SYBR green quantitative PCR and western blot analysis were used to measure expression of FXR and FXR target genes in normal human colon and colon cancers staged I-IV as well as colon cancer cell lines. Reverse phase protein array on colon cancer cell line lysates was used to correlate FXR expression with oncogenic signaling cascades. To test if FXR expression was suppressed by DNA methylation, colon cancer cell lines were treated with a DNA methyltransferase (DNMT) inhibitor and DNMT siRNA and FXR mRNA measured by real-time PCR. Immunoprecipitation with an antibody against 5-methylcytosine (MeDIP) analysis was done in human colon cancer cell lines to determine methylation of NR1H4 (gene encoding FXR) promoter. Results: IHC and qPCR analysis reveals that the expression and function of FXR is markedly reduced early in colon cancer progression, with suppression seen within precancerous lesions. Furthermore, FXR expression in colon cancer cell lines were negatively correlated to oncogenic PI3 kinase signaling cascades and associated with epithelial to mesenchymal transition (EMT). Results suggest DNA methylation as a mechanism of FXR silencing in colon cancer and confirms methylation of the FXR promoter. Conclusion: FXR deficiency in animals indicates FXR serves a tumor suppressive role. Our studies show that FXR is silenced in early in human colon cancer progression possibly by DNA methylation, which could be a cancer promoting event. The overall mechanism of FXR's anti-tumorigenic activity is not fully established but may be due to FXR's role in regulating EMT and bile acid homeostasis. Restoration and enhancement of FXR activity, by blocking DNA methylation or increasing baseline activity of FXR, represents a potential therapeutic option for the treatment of colon cancer.

Citation Format: Ann M. Thomas, Le Zhan, Julie Izzo, Dipen Maru, Imad Shureiqi, Veera Baladandayuthapani, Han Liang, Grace L. Guo, Garth Powis. Silencing of farnesoid X receptor in human colon cancer by epigenetic mechanisms is associated with cancer progression. [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 3561. doi:10.1158/1538-7445.AM2013-3561

Abstract 375: Role of intracrine vascular endothelial growth factor (VEGF) signaling in colorectal cancer cell survival and metastasis

Vascular endothelial growth factor (VEGF) is a key regulator of angiogenesis and vascular function, and it's role in biology are thought to be well understood. Although the effects of VEGF on angiogenesis, i.e. on endothelial cells, have been extensively studied, its effects on tumor cell function remain to be clearly elucidated. Our laboratory has demonstrated the VEGF receptors are present and active on colorectal cancer (CRC) cells. Recently we have studied the phenotypic changes in human CRC cells to determine the role of autocrine/intracrine VEGF signaling on tumor cell function. Using cell lines with somatic knockout of the VEGF gene we have been able to show that loss of VEGF expression led to significantly decreased cell growth and increased spontaneous apoptosis in CRC cells. Depletion of VEGF also increased the in vitro sensitivity of cells to the cytotoxic effects of the chemotherapeutic agent 5-fluorouracil. Importantly, these effects are not mediated in an autocrine or paracrine fashion, as neutralization of extracellular VEGF with a monoclonal antibody, or inhibition of kinase activity with small molecule inhibitors had no effect on CRC cell survival. These studies support a novel role for VEGF in cell survival as an intracrine factor. In our attempt to characterize the molecular mechanisms responsible for the intracrine pro-survival role of VEGF, we have performed gene microarray analyses on a pair of CRC cells with and without expression of VEGF. These studies show a clear difference in expression patterns of genes between cells that produce or lack VEGF, but surprisingly find no significant changes in gene expression when VEGF function is inhibited by functional antibodies (Bevacizumab). Our preliminary analyses of the gene expression profiles indicate that CRC cells lacking VEGF have increased levels of multiple receptor tyrosine kinases. In other biochemical assays, we also find that cells lacking VEGF have increased activation of survival and proliferation pathways compared to normal cells. Based on our data, we hypothesize that loss of VEGF may induce activation of other survival pathways that compensate for depletion of VEGF. Our microarray studies also indicate significant increases in a factor that has been implicated in increased metastasis in breast and lung cancer. This factor may be responsible for the increased migration and invasion of CRC cells lacking VEGF observed in vitro. Future studies will elucidate the exact role of VEGF in tumor cell survival and metastasis.

Citation Format: Rajat Bhattacharya, Shaija Samuel, Fan Fan, Ganiraju Manyam, Veera Baladandayuthapani, Lee Ellis. Role of intracrine vascular endothelial growth factor (VEGF) signaling in colorectal cancer cell survival and metastasis. [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 375. doi:10.1158/1538-7445.AM2013-375

Abstract 4491: Transforming growth factor (TGF) ≤ pathway and clinical outcome of pancreatic cancer

Background: TGFβ acts both as a tumor suppressor or tumor promoter depending upon cellular context and stage of tumor progression. TGFβ exerts its effects through the TGFβR1/ R2 receptors and the SMAD transcription regulators. We investigated the prognostic value of TGFβ signaling biomarkers in pancreatic cancer. Methods: We measured plasma TGFβ1 level using Meso Scale Discovery Multi-array® Human TGFβ1 Assay in 643 pancreatic cancer patients. TGFβR2 (Novus) and SMAD4 (Proteintech) protein expression were measured in 86 biopsies using immunohistochemisty (IHC). IHC intensity was scored 0-3. Percentage IHC-positive cancer cells were 0-3 (0: 0%+, 1: 1-10%+, 2: 10-25%+, 3: &gt;25%+). Final IHC score was measured as intensity × percentage. We also genotyped 3 SNPs of TGFB1 gene using the Taqman assay. Kaplan-Meier and log-rank tests were used to analyze overall survival (OS) by TGFβ1 level. Multivariate Cox proportional hazards models with relevant clinical covariates were used to assess the relationship between IHC score and OS. Results: In patients with locally advanced and metastatic disease (n = 355), there was a significant association of plasma TGFβ1 with OS. OS of the top quartile of TGFβ1 levels (&gt;19.05 ng/mL) vs. those with low level was 27.7 weeks vs. 40 weeks, respectively [log-rank p = 0.0125, adjusted for baseline CA 19-9 and performance status (PS)]. No significant association between plasma TGFβ1 and OS was noted in surgical patients (n = 288). In the multivariate Cox model, after adjusting for baseline stage, CA 19-9, PS, age and TGFβR2 expression, complete loss of SMAD4 expression (IHC score 0) was significantly associated with lower OS [HR (95% CI): 1.85 (1.06-3.23), p = 0.03]. Progressive disease on gemcitabine-based therapy was more likely in SMAD4 IHC 0 group as compared with higher score (46.5% vs. 38.1% progressed; chi square p = 0.069). TGFB1 –1346T&gt;C CT/TT genotype correlated with shorter OS [HR (95% CI): 1.21 (1.02-1.45), p = 0.03] after adjusting for clinical variables. Conclusions: This large retrospective study suggests an important stage-dependant role of the TGFβ pathway in pancreatic cancer. Targeting this pathway in advanced pancreatic cancer may have therapeutic relevance.

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 4491. doi:1538-7445.AM2012-4491

Survival advantage observed with the use of metformin in patients with type II diabetes and colorectal cancer

BACKGROUND

Patients with type II diabetes mellitus (DM) have an increased risk of adenomatous colorectal (CRC) polyps and CRC cancer. The use of the anti-hyperglycemic agent metformin is associated with a reduced incidence of cancer-related deaths.

METHODS

We retrospectively evaluated the medical records of 4758 patients seen at a single institution and determined that 424 patients were identified by their physicians as having type II DM and CRC cancer. Data were subsequently acquired determining the subject's age, body mass index (BMI), and disease date of diagnosis, stage, site of cancer, treatment, and survival.

RESULTS

Patients with type II DM and CRC cancer treated with metformin as one of their diabetic medications had a survival of 76.9 months (95% CI=61.4-102.4) as compared with 56.9 months in those patients not treated with metformin (95% CI=44.8-68.8), P=0.048. By using a multivariable Cox regression model adjusted for age, sex, race, BMI, and initial stage of disease, we demonstrated that type II diabetic patients treated with metformin had a 30% improvement in overall survival (OS) when compared with diabetic patients treated with other diabetic agents.

CONCLUSION

Colorectal cancer patients with DM treated with metformin as part of their diabetic therapy appear to have a superior OS.

Transforming growth factor (TGF) beta pathway and clinical outcome of pancreatic cancer

201

Background: TGF-beta acts both as a tumor suppressor or tumor promoter depending upon cellular context and stage of tumor progression. TGF-β exerts its effects through the TGF-beta-R1/ R2 receptors and the SMAD transcription regulators. We investigated the prognostic value of TGFβ signaling biomarkers in pancreatic cancer.

Methods: We measured plasma TGF-beta-1 level using Meso Scale Discovery Multi-array Human TGF-beta-1 Assay in 643 pancreatic cancer patients. TGF-beta-R2 and SMAD4 protein expression were measured in 86 biopsies using immunohistochemisty (IHC). IHC intensity was scored 0-3. Percentage IHC-positive cancer cells were 0-3 (0: 0%+, 1: 1-10%+, 2: 10-25%+, 3: >25%+). Final IHC score was measured as intensity x percentage. We also genotyped 3 SNPs of TGFB1 gene using the Taqman assay. Kaplan-Meier and log-rank tests were used to analyze overall survival (OS) by TGFβ1 level. Multivariate Cox proportional hazards models with relevant clinical covariates were used to assess the relationship between IHC score and OS.

Results: In patients with locally advanced and metastatic disease (n = 355), there was a significant association of plasma TGF-beta-1 with overall survival (OS). OS of the top quartile of TGF-beta-1 levels (>19.05 ng/mL) vs. those with low level was 27.7 weeks vs. 40 weeks, respectively [log-rank p = 0.0125, adjusted for baseline CA 19-9 and performance status (PS)]. No significant association between plasma TGF-beta-1 and OS was noted in surgical patients (n=288). In the multivariate Cox model, after adjusting for baseline stage, CA 19-9, PS, age and TGF-beta-R2 expression, complete loss of SMAD4 expression (IHC score 0) was significantly associated with lower OS (HR: 1.85, 95% CI: 1.06-3.23; p = 0.03). Progressive disease on gemcitabine-based therapy was more likely in SMAD4 IHC 0 group as compared with higher score (46.5% vs. 38.1% progressed; chi square p = 0.069). TGFB1 -1346T>C CT/TT genotype correlated with shorter OS [HR (95% CI): 1.21 (1.02-1.45), p=0.03] after adjusting for clinical variables.

Conclusions: This large retrospective study suggests an important stage-dependant role of the TGF-beta pathway in pancreatic cancer. Targeting this pathway in advanced pancreatic cancer may have therapeutic relevance.

Novel phosphatidylinositol 3-kinase inhibitor NVP-BKM120 induces apoptosis in myeloma cells and shows synergistic anti-myeloma activity with dexamethasone

NVP-BKM120 is a novel phosphatidylinositol 3-kinase (PI3K) inhibitor and is currently being investigated in phase I clinical trials in solid tumors. This study aimed to evaluate the therapeutic efficacy of BKM120 in multiple myeloma (MM). BKM120 induces cell growth inhibition and apoptosis in both MM cell lines and freshly isolated primary MM cells. However, BKM120 only shows limited cytotoxicity toward normal lymphocytes. The presence of MM bone marrow stromal cells, insulin-like growth factor, or interleukin-6 does not affect BKM120-induced tumor cell apoptosis. More importantly, BKM120 treatment significantly inhibits tumor growth in vivo and prolongs the survival of myeloma-bearing mice. In addition, BKM120 shows synergistic cytotoxicity with dexamethasone in dexamethasone-sensitive MM cells. Low doses of BKM120 and dexamethasone, each of which alone has limited cytotoxicity, induce significant cell apoptosis in MM.1S and ARP-1. Mechanistic study shows that BKM120 exposure causes cell cycle arrest by upregulating p27 (Kip1) and downregulating cyclin D1 and induces caspase-dependent apoptosis by downregulating antiapoptotic XIAP and upregulating expression of cytotoxic small isoform of Bim, BimS. In summary, our findings demonstrate the in vitro and in vivo anti-MM activity of BKM120 and suggest that BKM120 alone or together with other MM chemotherapeutics, particularly dexamethasone, may be a promising treatment for MM.

Survival advantage associated with palliative oophorectomy in patients with metastatic colorectal cancer (CRC) to the ovaries (mCRC-O): A single institution retrospective analysis

539

Background: The ovaries are an uncommon site for secondary spread from metastatic CRC. We hypothesize that palliative oophorectomy improves survival among patients with mCRC-O.

Methods: We undertook a single institution IRB-approved (DR-09-623) retrospective evaluation of women with mCRC-O from 2001-2008; 110 pts with ovarian metastases and follow-up information for survival analysis were identified out of 3,776 female pts with CRC (2.9%). Survival data was calculated from the date of diagnosis of ovarian metastases (by pathology or radiology) to date of death.

Results: Median age of patients was 49 years (range 19-82); median duration of follow-up was 49 months. Twenty patients were identified from 1,758 female patients with CRC seen at our institution from 2001-2004 (1.1%) and ninety patients identified from 2,018 female CRC patients from 2005-2008 (4.5%). KRAS mutation was present in the primary tumor in 23 of 43 (54%). Sixteen evaluable patients who received systemic chemotherapy with mCRC-O and other sites of metastatic disease were identified; five (31%) had a mixed radiographic response (progression in the ovarian metastases with disease response in other sites of metastases). Seventy-one (64.5%) patients had metastatic disease at the time of initial presentation; 39 (35.5%) had completely resected stage II or III CRC with mCRC-O occurring at a later date. 86 (78.2%) underwent unilateral or bilateral oophorectomy for treatment of their disease. Patients who had metastatic disease at presentation and underwent oophorectomy had a median survival of 39.4 months versus 18.2 months for those with ovarian metastases left in situ (p < 0.0001); patients who developed ovarian relapse after prior colectomy and subsequently underwent oophorectomy had a median survival of 50 months versus 12 months for those patients who did not (p = 0.001). Patients with mCRC-O and peritoneal metastases had a significantly worse survival (p = 0.003).

Conclusions: This single institution retrospective data analysis suggests that women with colorectal cancer metastatic to the ovaries may derive a survival benefit from palliative oophorectomy.

No significant financial relationships to disclose.

Retrospective evaluation of patients with colorectal cancer (CRC) and type II non-insulin-dependent diabetes (NIDDM)

507

Background: Patients with NIDDM have an increased risk of colorectal adenomas and CRC possibly mediated through the insulin growth factor receptor pathway. Metformin is associated with anticancer efficacy in preclinical models and a lower risk of cancer mortality in patients with NIDDM. We undertook to evaluate the difference in outcome in NIDDM patients with CRC based upon their medications taken for glycemic control.

Methods: We conducted an IRB-approved (DR09-0719) retrospective analysis of 4,758 patients seen at a single institution (University of Texas M. D. Anderson) with CRC between the years of 2005-2008, to determine the prevalence of NIDDM in this patient population, in addition to determining whether patient survival differs based upon their diabetic therapy.

Results: 425 out of 4,758 CRC patients (8.9%) were identified as having NIDDM. Gender, male:female 283:142 (67%, 33%), age, mean 62 years (range 31-91), stage I/II/III/IV 37:55:175:158 (8.7%, 12.9%, 41.2%, 37.2%). Overall survival (OS) for the 397 patients with follow-up data available, by univariable Kaplan Meier analysis, was 63.7 months (95% confidence interval (CI), 52.3-75.5). Patients with NIDDM and CRC treated with metformin as one of their diabetic medications had a survival of 76.9 months (95% CI, 61.4-102.4) as compared to 56.9 months in those patients not treated with metformin (95% CI, 44.8- 68.8), p = 0.048. By using a Cox regression model adjusted for age, sex, race, body mass index, and initial stage of disease we demonstrated that NIDDM patients treated with metformin had a 30% improvement in OS when compared to NIDDM patients treated with other diabetic agents. There was a non-statistically significant trend toward higher complete and minor pathologic response rate (≤ 10% residual tumor) in NIDDM patients with rectal cancer receiving chemoradiation who were treated with metformin when compared to those who were not (14/19, 74% vs. 9/19, 47%, p = 0.09).

Conclusions: In this analysis the use of metformin in NIDDM patients with CRC was associated with an improved overall survival. While these results are consistent with the findings in other solid tumors they will need to be validated in other colorectal cancer data sets.

No significant financial relationships to disclose.

Estimating Shared Copy Number Aberrations for Array CGH Data: The Linear-Median Method

MOTIVATION

Existing methods for estimating copy number variations in array comparative genomic hybridization (aCGH) data are limited to estimations of the gain/loss of chromosome regions for single sample analysis. We propose the linear-median method for estimating shared copy numbers in DNA sequences across multiple samples, demonstrate its operating characteristics through simulations and applications to real cancer data, and compare it to two existing methods.

RESULTS

Our proposed linear-median method has the power to estimate common changes that appear at isolated single probe positions or very short regions. Such changes are hard to detect by current methods. This new method shows a higher rate of true positives and a lower rate of false positives. The linear-median method is non-parametric and hence is more robust in estimating copy number. Additionally the linear-median method is easily computable for practical aCGH data sets compared to other copy number estimation methods.

Abstract 2303: The redox-active protein thioredoxin: A modulator of epithelial-mesenchymal transition

Human thioredoxin is a ubiquitous redox-active protein that induces the activation of many redox-sensitive transcription factors, inhibits the activity of the apoptosis-signal regulating kinase, and activates the AKT signaling pathway. Thioredoxin is thus associated with many biological processes, including the induction of cellular proliferation leading to cancer progression and metastasis. The morphogenetic changes occurring during the initial stage of metastasis is referred to as epithelial-mesenchymal transition (EMT). EMT results in the transition of cancer cells from an epithelial to a fibroblastic or mesenchymal phenotype, accompanied by a large number of changes in gene expression, particularly down regulation in the expression of the epithelial marker E-cadherin and induction of expression and activation of the mesenchymal marker vimentin, N-cadherin, or fibronectin. Transforming growth factor (TGF)-β is regarded as the prototype cytokine for induction of EMT both in vitro and in vivo. Using a high throughput functional genomic screen, we previously showed that members of the TGF-β signaling pathway induce the expression of thioredoxin in both pancreatic and breast cancer cells. In addition, we showed that TGF-β1 stimulation in these cells resulted in a two-fold induction of thioredoxin expression. Therefore, we hypothesized that thioredoxin is a modulator of EMT. We based this hypothesis on the finding that increased expression of thioredoxin is associated with metastasis and that TGF-β1 induces thioredoxin expression. Herein we present evidence in both breast cancer cells and human biopsy samples of breast tumors that support our hypothesis. In vitro three-dimensional cell cultures of the MDA-MB-231 breast cancer cell line undergo phenotypic changes similar to the morphogenetic changes associated with EMT. Treating MDA-MB-231 cells with PX12, a potent inhibitor of thioredoxin, blocked the onset of these morphogenetic changes. We show a correlation between the expression of thioredoxin and the EMT markers utilizing Reverse-Phase Protein Array of 250 fine-needle aspirates from breast tumor patients and the Pearson correlation coefficients. There was a positive correlation between thioredoxin and N-cadherin (p&lt;0.0001), and a negative correlation between thioredoxin and E-cadherin (p&lt;0.0001) as well as between thioredoxin and β-catenin (p&lt;0.0001). High expression of thioredoxin correlate with decreased expression of E-cadherin and β-catenin and an increased expression of N-cadherin. Our data demonstrated that thioredoxin might be an important regulator of EMT in breast cancer. Based on our findings we propose a model indicating that thioredoxin modulates TGF-β-induced EMT by functioning to maintain EMT once it is initiated. Ongoing studies by our group will enable us to confirm this model.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2303.

Contrast sensitivity of digital imaging display systems: contrast threshold dependency on object type and implications for monitor quality assurance and quality control in PACS

The American Association of Physicists in Medicine Task Group 18 has published standards and quality control (QC) guidelines to ensure consistency and optimal quality for digital image display systems (DIDSs). In many of these recommended QC tests, static test patterns that contain low-contrast objects are often used to assess and validate the quality of a DIDS. These low-contrast objects often have the shape of circular disks or squares with sharp edges, neither of which resemble most of the diagnostic findings in medical images. On the other hand, circular objects with fuzzy boundaries bear a closer resemblance to lung nodules in chest radiography and masses in mammography; thus, they may be more clinically relevant in assessing display system quality. In this article human observers' contrast sensitivities of circular objects with sharp edges and those with fuzzy ones were investigated. The contrast thresholds of human viewers using a consumer-grade color LCD monitor and a medical-grade monochrome LCD monitor were measured for objects of various sizes displayed against uniform backgrounds with various luminance levels. Contrast-detail curves for circular objects with sharp edges and those with fuzzy boundaries were measured and compared. It was found that contrast thresholds for objects with fuzzy boundaries were higher (i.e., the objects were more difficult to detect) than those with sharp edges. Objects with fuzzy boundaries were potentially more sensitive in distinguishing quality differences among image display devices and thus may be a better QC measurement in detecting subtle deterioration in image display devices.

Targeting cell signaling pathways for drug discovery: an old lock needs a new key

In this age of targeted therapy, the failure of most current drug-discovery efforts to yield safe, effective, and inexpensive drugs has generated widespread concern. Successful drug development has been stymied by a general focus on target selection rather than clinical safety and efficacy. The very process of validating the targets themselves is inefficient and in many cases leads to drugs having poor efficacy and undesirable side effects. Indeed, some rationally designed drugs (e.g., inhibitors of receptor tyrosine kinases, tumor necrosis factor (TNF), cyclooxygenase-2 (COX-2), vascular endothelial growth factor (VEGF), bcr-abl, and proteasomes) are ineffective against cancers and other inflammatory conditions and produce serious side effects. Since any given cancer carries mutations in an estimated 300 genes, this raises an important question about how effective these targeted therapies can ever be against cancer. Thus, it has become necessary to rethink drug development strategies. This review analyzes the shortcomings of rationally designed target-specific drugs against cancer cell signaling pathways and evaluates the available options for future drug development.