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The signaling mechanisms between prostate cancer cells and infiltrating immune cells may illuminate novel therapeutic approaches. Here, utilizing a prostate adenocarcinoma model driven by loss of Pten and Smad4, we identify polymorphonuclear myeloid-derived suppressor cells (MDSC) as the major infiltrating immune cell type, and depletion of MDSCs blocks progression. Employing a novel dual reporter prostate cancer model, epithelial and stromal transcriptomic profiling identified CXCL5 as a cancer-secreted chemokine to attract CXCR2-expressing MDSCs, and, correspondingly, pharmacologic inhibition of CXCR2 impeded tumor progression. Integrated analyses identified hyperactivated Hippo–YAP signaling in driving CXCL5 upregulation in cancer cells through the YAP–TEAD complex and promoting MDSC recruitment. Clinicopathologic studies reveal upregulation and activation of YAP1 in a subset of human prostate tumors, and the YAP1 signature is enriched in primary prostate tumor samples with stronger expression of MDSC-relevant genes. Together, YAP-driven MDSC recruitment via heterotypic CXCL5–CXCR2 signaling reveals an effective therapeutic strategy for advanced prostate cancer. Significance: We demonstrate a critical role of MDSCs in prostate tumor progression and discover a cancer cell nonautonomous function of the Hippo–YAP pathway in regulation of CXCL5, a ligand for CXCR2-expressing MDSCs. Pharmacologic elimination of MDSCs or blocking the heterotypic CXCL5–CXCR2 signaling circuit elicits robust antitumor responses and prolongs survival. Cancer Discov; 6(1); 80–95. ©2015 AACR. This article is highlighted in the In This Issue feature, p. 1

Exosomes are extracellular vesicles produced by all cells with a remarkable ability to efficiently transfer genetic material, including exogenously loaded siRNA, to cancer cells. Here, we report on a bioreactor-based, large-scale production of clinical-grade exosomes employing good manufacturing practice (GMP) standards. A standard operating procedure was established to generate engineered exosomes with the ability to target oncogenic Kras (iExosomes). The clinical-grade GMP iExosomes were tested in multiple in vitro and in vivo studies to confirm suppression of oncogenic Kras and an increase in the survival of several mouse models with pancreatic cancer. We perform studies to determine the shelf life, biodistribution, toxicology profile, and efficacy in combination with chemotherapy to inform future clinical testing of GMP iExosomes. Collectively, this report illustrates the process and feasibility of generating clinical-grade exosomes for various therapies of human diseases.

SummaryPancreatic ductal adenocarcinoma (PDAC) is associated with marked fibrosis and stromal myofibroblasts, but their functional contribution remains unknown. Transgenic mice with the ability to delete αSMA+ myofibroblasts in pancreatic cancer were generated. Depletion starting at either noninvasive precursor (pancreatic intraepithelial neoplasia) or the PDAC stage led to invasive, undifferentiated tumors with enhanced hypoxia, epithelial-to-mesenchymal transition, and cancer stem cells, with diminished animal survival. In PDAC patients, fewer myofibroblasts in their tumors also correlated with reduced survival. Suppressed immune surveillance with increased CD4+Foxp3+ Tregs was observed in myofibroblast-depleted mouse tumors. Although myofibroblast-depleted tumors did not respond to gemcitabine, anti-CTLA4 immunotherapy reversed disease acceleration and prolonged animal survival. This study underscores the need for caution in targeting carcinoma-associated fibroblasts in PDAC.

There is substantial heterogeneity among primary prostate cancers, evident in the spectrum of molecular abnormalities and its variable clinical course. As part of The Cancer Genome Atlas (TCGA), we present a comprehensive molecular analysis of 333 primary prostate carcinomas. Our results revealed a molecular taxonomy in which 74% of these tumors fell into one of seven subtypes defined by specific gene fusions (ERG, ETV1/4, and FLI1) or mutations (SPOP, FOXA1, and IDH1). Epigenetic profiles showed substantial heterogeneity, including an IDH1 mutant subset with a methylator phenotype. Androgen receptor (AR) activity varied widely and in a subtype-specific manner, with SPOP and FOXA1 mutant tumors having the highest levels of AR-induced transcripts. 25% of the prostate cancers had a presumed actionable lesion in the PI3K or MAPK signaling pathways, and DNA repair genes were inactivated in 19%. Our analysis reveals molecular heterogeneity among primary prostate cancers, as well as potentially actionable molecular defects., National Institutes of Health (U.S.). (grant 5U24CA143799), National Institutes of Health (U.S.). (grant 5U24CA143835), National Institutes of Health (U.S.). (grant 5U24CA143840), National Institutes of Health (U.S.). (grant 5U24CA143843), National Institutes of Health (U.S.). (grant 5U24CA143845), National Institutes of Health (U.S.). (grant 5U24CA143848), National Institutes of Health (U.S.). (grant 5U24CA143858), National Institutes of Health (U.S.). (grant 5U24CA143866), National Institutes of Health (U.S.). (grant 5U24CA143867), National Institutes of Health (U.S.). (grant 5U24CA143882), National Institutes of Health (U.S.). (grant 5U24CA143883), National Institutes of Health (U.S.). (grant 5U24CA144025), National Institutes of Health (U.S.). (grant U54HG003067), National Institutes of Health (U.S.). (grant U54HG003079), National Institutes of Health (U.S.). (grant U54HG003273), National Institutes of Health (U.S.). (grant P30CA16672)

Meeting abstracts Myeloid-derived suppressor cells (MDSCs) represent a phenotypically heterogeneous population of immature myeloid cells that play a tumor-promoting role by maintaining a state of immunological anergy and tolerance. Similar to other solid tumor types, Prostate cancer (PCa) is

In the version of this article originally published, information regarding several funding sources was omitted from the Acknowledgements section. The following sentences should have been included: "This work was supported by the generous philanthropic contributions to The University of Texas MD Anderson Lung Cancer Moon Shots Program, the UT Lung SPORE 5 P50 CA07090, and the MD Anderson Cancer Center Support Grant P30CA01667. V.P is supported by R01CA155196-01A1 from the National Cancer Institute." Also, reference 18 was incorrect. The original reference was: Kim, E. S. et al. The BATTLE trial: personalizing therapy for lung cancer. Cancer Discov. 1, 44-53 (2011). It should have been: Papadimitrakopoulou, V. et al. The BATTLE-2 study: a biomarker-integrated targeted therapy study in previously treated patients with advanced non-small-cell lung cancer. J Clin. Oncol. 34, 3638-3647 (2016). The errors have been corrected in the HTML and PDF versions of this article.

10520Background: Despite the high levels of point mutations, rearrangements, and other genomic instability events such as kataegis and chromothripsis, immune checkpoint inhibitors have shown limite...

11522Background: Osteosarcoma (OS) is characterized by genomic complexity and significant genetic heterogeneity. However, it is unknown whether relapse and metastatic samples incur additional insul...

The ways for improving a cost-effective industrial production program described in an earlier paper primarily focused on the quality assurance/quality control (QA/QC) schemes within the manufacturing stage. However, industry with high demand of resources input must evolve the essential production strategies to meet the goals in an environmentally benign production program. This paper describes the method and procedure for optimizing a textile-dyeing manufacturing process with respect to the potential impact of pollution charges, resources conservation fees, production cost, inventory cost, and the limitations of production capacity simultaneously. The optimal production strategy concerning numerous screening processes of those production alternatives in terms of market demand, production technology, and resources allocation is treated as an integral part in the multi-objective decision analysis. Facing the growing impact of rising environmental costs and the awareness of implications of industria...

Design and implementation of an H∞ controller for a micropermanent- magnet synchronous motor position control system is proposed. The diameter of the micromotor is only 6 mm. In addition, the weighting functions of the H∞ controller are selected using the genetic algorithms. A state-space H∞ controller, obtained using a systematic design procedure, is incorporated in a closed-loop position control micromotor system. The system has good performance, including fast transient responses and good load disturbance rejection responses, although its encoder is only 100 pulses/revolution. A digital signal processor, TMS320F2407, is used to execute the position control algorithms. Experimental results validate the theoretical analysis and show the correctness and feasibility of the proposed method. An advanced controller design is proposed for a micromotor.

Incorporating environmental costs and considerations into corporate decision-making becomes a challenging task nowadays. Decision-making techniques, such as input–output models and multicriteria decision-making tools, have been developed over the past decades, which help to create a system-wide industrial ecology philosophy in many industrial communities. In response to emerging environmental regulations and policies, the impact of environmental costs on a production program should be realized with regard to the level and extent of compliance. This paper, which presents the first part of the study, illustrates the miniaturized level framework of greening accounting for an individual company. The case study applies an input–output analysis model to assess the environmental cost impacts due to the required pollution charges and resources conservation fees faced in a textile-dyeing firm in Taiwan. Based on a production process designed for generating two types of textile products in this factory, the case st...

Corporate environmental and resources management has become more strategically oriented when many pollution charges, environmental taxes, and resources conservation fees have been gradually imposing to the industry. The need for explicit consideration and incorporation of varying environmental costs within production-planning program is becoming critical to corporate management. This paper attempts to assess an optimal production-planning program in response to varying environmental costs in an uncertain environment. The optimal production strategy concerning numerous screening of possible production alternatives of dyeing cloth in a textile-dyeing firm in terms of market demand, resources availability, and impact of environmental costs is treated as an integral part of the multi-criteria decision-making framework based on the grey compromise programming approach. It covers not only the regular part of production costs and the direct income from product sales but also the emission/effluent charges and water resource fees reflecting part of the goals for internalization of external cost in a sustainable society. In particular, all the crucial variables in the model are addressed by interval expressions, the same as they are frequently applied in the grey systems theory, in support of a vital uncertainty assessment, which is much better suited for this particular study than other approaches. Research results demonstrate the applicability and significance of such an approach based on a case study. Industry looking for the competitive advantage of environmental management must be aware of the potential benefits from such an integrated production-planning program once the trend of increasing pollution charges, environmental taxes, and resources conservation fees remains.

This paper describes the method and procedure for optimizing a textile dyeing manufacturing process in response to the designated waste minimization alternatives, the new environmental regulations, and the limitations of production resources. The optimization steps concerning numerous screening and sequencing combinations of those waste minimization alternatives along the timeline are, therefore, treated as an integral part of the optimal production-planning program under uncertainty. It utilizes a nonlinear integer optimization framework formulated in terms of multiple products to account for the trade-offs between costs and benefits relevant to each alternative in decision-making. Such an analysis profile covers not only the production costs and the incomes from product sale but also the emission/effluent charge and water resources fees required by new environmental relations. The inclusion of an interval analysis skill in model formulation notably reflects the subjectivity, impreciseness, and variations in the measurement of parameter values. The embedded systematic uncertainties can then be grossly addressed by a series of interval expressions as the same as they have been using in the grey systems theory for a decade. Facing the challenge of dealing with the numerous nonlinear constraints and integer variables in the optimization steps, genetic algorithm is applied as a means in the solution procedure to aid in finding the optimal decision. The case study, illustrating the applicability and suitability of this methodology in a textile dyeing firm, finally demonstrates the application potential and presents the germane insight in the nexus of environmental management and production planning. Such long-term strategic planning issues internal to the organization and its stakeholders in the context of emerging regulatory impact on corporate management exactly reflect the complexity and uncertainty of application challenges in the optimal production planning program in industry.

8541 Background: Despite complete resection, many non-small cell lung cancer (NSCLC) patients still develop and succumb to distant metastases. Previous studies suggested distant metastasis may be due to genomic evolution and/or suppressed immune surveillance. However, the relationship between specific genomic alterations and immune surveillance has not been systemically studied. Methods: We performed whole exome sequencing, RNA-Seq, methylation microarray, immunohistochemistry using multiple immune markers, and T cell receptor sequencing on 7 pairs of NSCLC primary tumors and matched metastases including 6 metachronous brain and 1 synchronous liver metastases. Results: On average, 84% of all somatic mutations (54% to 97%) and all 28 canonical cancer gene mutations were shared between primary tumors and paired distant metastases. Metastases also resembled paired primary tumors closely in regard to somatic copy number aberration profiles, methylation profiles. Subclonal analysis showed almost identical clonal architectures in 4 of 7 pairs of primary tumor and metastasis comparable to the similarity observed between different regions within the same tumors. The other 3 pairs, however, displayed clear evidence of clonal evolution. We validated these findings in a published dataset consisting of 38 pairs of primary NSCLC tumors and matched distant metastases. The RNA-Seq data showed that 25 of the top 35 significantly down-regulated signaling pathways in metastases relative to primary tumors were related to immune activation, which was validated in an independent cohort of 41 primary NSCLC tumors and distant metastases using NanoString’s PanCancer Immune Profiling Panel. Conclusions: Our data suggest that molecular mechanisms underlying postsurgical distant metastasis may be variable among NSCLC patients. While genomic evolution may play a role in development of metastasis in some patients, distant metastasis may be early event during carcinogenesis without further genomic evolution in a substantial proportion of NSCLC patients. Furthermore, immune suppression may be a characteristic of cancer cells of metastatic capacity.

8538 Background: In many types of cancer, infiltration of tumor by immune cells, as a reflection of the immune response against the tumor, is thought to play a critical role in clinical outcome. Tumors, however, tend to evade the immune response as they progress. In this study, we characterize the interplay between immune infiltration and tumor progression and survival in non-small cell lung cancer (NSCLC). Methods: We performed histologic immune profiling and microarray expression analysis on primary tumor specimens from 275 NSCLC patients (PR: PROSPECT trial) as well as RNA-Seq expression analysis on biopsy specimens from 50 patients with advanced NSCLC (B2: BATTLE-2 trial). RNA-Seq data from the TCGA lung cancer project was also analyzed. Immune Infiltration Score (IIS) was computed from the expression data using the Estimate package in R. Immune Suppression Score (ISS) was defined as the difference between the mean of CD3, CD4, CD8, FOXP3, and PD1 counts in the periphery and core of the tumor. Results: Tumor IIS is correlated (all p < 0.0005) with tumor immune infiltration as measured by inflammatory cell count on frozen tumor or several immune marker counts in tumor core. IIS is positively associated with survival (p = 0.04) independently of age (p = 0.008) and stage (p = 8e-10). IIS in the top half is associated with higher median survival vs. bottom half (10.2 vs 2.2 months, p < 0.0001) in B2. In TCGA lung adenocarcinoma samples, IIS is higher in stage I/II disease vs stage III/IV (p = 0.003). For all immune markers in PR samples, periphery of the tumor on average has higher counts vs tumor core (p < 0.0011), and this difference (suppression score) is higher in stage III/IV samples vs stage I/II for CD3, CD4, and CD8 (all p < 0.04) and for FOXP3 and PD1 (p < 0.1). ISS is negatively associated with survival (p = 0.02) independently of age (p = 0.06) and stage (p < 0.0001). Conclusions: As NSCLC tumors progress, immune infiltration in the periphery of the tumor increases while infiltration in the core decreases, reflecting increasing immune suppression. Tumor immune infiltration and suppression, as measured by IIS and ISS, are significant predictors of survival, independently of age and stage.

Motivation: Three major problems confront the construction of a human genetic network from heterogeneous genomics data using kernel-based approaches: definition of a robust gold-standard negative set, large-scale learning and massive missing data values. Results: The proposed graph-based approach generates a robust GSN for the training process of genetic network construction. The RVM-based ensemble model that combines AdaBoost and reduced-feature yields improved performance on large-scale learning problems with massive missing values in comparison to Naïve Bayes. Contact: dargenio@bmsr.usc.edu Supplementary information: Supplementary material is available at Bioinformatics online.

This paper proposes a novel shaft position/speed estimating technique for a micro permanent magnet synchronous motor. By using the special characteristics of the micro motor, the back emf of the motor can be easily detected. In addition, the shaft position/speed can be derived according to the back emf. After obtaining the rotor position and speed, a closed-loop drive system can be achieved. A TMS-320-LF2407A DSP is used to estimate the shaft position/speed. In addition, a current controlled circuit, PWM circuit, and an inverter are implemented to control the stator current, and then control the motor. As a result, a closed-loop system is thus achieved. Experimental results validate the theoretical analysis.

Summary: Inferring genetic network architecture from time series data generated from high-throughput experimental technologies, such as cDNA microarray, can help us to understand the system behavior of living organisms. We have developed an interactive tool, GeneNetwork, which provides four reverse engineering models and three data interpolation approaches to infer relationships between genes. GeneNetwork enables a user to readily reconstruct genetic networks based on microarray data without having intimate knowledge of the mathematical models. A simple graphical user interface enables rapid, intuitive mapping and analysis of the reconstructed network allowing biologists to explore gene relationships at the system level. Availability: Download from http://genenetwork.sbl.bc.sinica.edu.tw/ Supplementary information: Supplement documentation of algorithms for the four approaches is downloadable at the above location.

Purpose: It is difficult to prioritize potential therapeutic targets from thousands of differentially expressed genes identified by genome-wide gene expression profiling in cancer. The vast array of in silico resources currently available in life sciences research offer the possibility of aiding drug discovery process. Here we propose to take advantage of these resources to develop a genetic network-based model to comprehensively and effectively identify potential therapeutic targets in several cancer types. Method: A whole-genome genetic network, which can reveal the tendency for genes to operate in the same or similar pathways, is first constructed from heterogeneous data using a developed machine learning approach, RVM-based ensemble. A tumor-specific network can then be generated by mapping the differentially expressed genes in a tumor to the whole-genome network. Finally, potential therapeutic targets can be identified as hub genes that are functionally associated to multiple existing cancer pathways in the tumor-specific network. Result: Here, the approach is applied to Breast, Colon, and Lung Cancer separately. In each case, differentially expressed genes are all ranked based on the extent of their functional association with multiple known cancer pathways in the tumor-specific network. The result in each case shows that higher ranked genes are cited by more literature respectively related to the three cancers (Spearman's Rank Correlations, R>0.2 with p0.75). Additionally, we also identified drugs and compounds that can target the highly ranked genes based on known drug-target information. Targets of many drugs, already in clinical trials and used for treatment of the three cancers, are all highly ranked in each case. Other drugs and compounds identified but not in clinical trials have also shown anti-cancer effect and could be considered as potential novel drug for these cancers. Moreover, we also find several novel targets in each case, which are not yet identified as cancer genes, are highly ranked and also increase cancer cell death in siRNA screens. One example is CSNK1G2 (casein kinase 1, gamma 2) in Colon cancer. Conclusion: Our approach has demonstrated the ability to identify potential therapeutic targets in cancer systematically and comprehensively using integrated functional genomic and proteomic data. It also implies that the proposed approach could be utilized to generate personal therapeutics. 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 109.

The paper proposes a shaft-position/speed-estimating technique for a micropermanent-magnet synchronous motor. Based on the characteristics of the micromotor, the back EMF of the motor can be detected. In addition, the shaft position/speed can be estimated according to the back EMF. Finally, a closed-loop sensorless adjustable speed-control system is implemented. The controlled speed range is from 600 to 36000 rev/min. A DSP is used to estimate the shaft position/speed and to execute the speed-loop control algorithm. In addition, some hardware circuits, including current-controlled circuits, PWM circuits, and an inverter are implemented to control the current of the micromotor. Satisfactory performance, including a wide adjustable speed range, good transient responses, and good load-disturbance responses can be achieved. Experimental results validate the theoretical analysis and show the correctness and feasibility of the proposed estimation technique.