Director's Challenge Research Articles

Challenges in sustaining technology enhanced learning: Recruitment, employment and retention of learning designers in Australian universities


 
 
 Universities require learning designers with creative digital experience and significant knowledge of educational theory and practice to meet institutional teaching and learning strategic priorities. Little is known about how best to attract and retain learning designers or alternatively, to assist learning designers navigate their career pathways in higher education. In response to these needs, this study aimed to provide a snapshot of current learning design practices across Australian universities; to document relevant skills, knowledge, education and professional background, role types and employment conditions, challenges for directors, and to identify areas for future attention. The researchers used two separate online surveys to target 1) directors of central teaching and learning units and 2) learning designers employed in universities. The results are useful as a means to sustain and improve practice through evidence-based decision-making in the conceptualisation of learning designer positions, the management and retention of learning design staff, and to assist learning designers in their career choices.
 
 

Remote Learning in School Bands During the COVID-19 Shutdown.

The global pandemic caused by the novel Coronavirus (COVID-19) in spring 2020 resulted in schools moving to remote learning (RL) models for the remainder of the academic year. The purpose of this study was to examine the practices, experiences, and perspectives of elementary and secondary school band directors in relation to RL during this period. Directors (N = 462) responded to survey questions related to several aspects of RL, including (a) technologies and materials, (b) activities and assessments, (c) student participation, (d) the challenges of teaching remotely, and (e) the extent to which experiences varied among participants in low-poverty versus high-poverty schools and at the elementary/middle school level versus high school level. I also examined (f) the conditions and practices of programs that experienced both high and consistent levels of student participation. Data indicated that the COVID-19 shutdown created many challenges for directors, particularly in schools with higher poverty levels and/or in rural locations. However, RL also created opportunities for instrumental teachers to incorporate into curricula (a) a wider range of technology; (b) more of a focus on individual musicianship; (c) lessons in music theory, history, and culture; and to a lesser extent, (d) student creativity through composition and arranging.

Selection of suitable bank based on quality of providing systems for internet banking services using AHP and ANP methods

Due to rising complexity of decision-making environments, the suitable multi-criteria methods have become important to support from decision in management and decision-making has been converted into a challenge for directors and organizations in today complicated world. Thus, more particularly during two recent decades, mathematical models and computer sciences have contributed them to solve decision-making problems and created multi-criteria decision- making techniques and decision- making supporting systems. With respect to extension and high volume of activities in national banking systems we are exposed to data production and many data that led decision- making subject to become especially important. The importance and position of internet banking and growing trend of services in this field in the country during recent years has put financial and credit institutions (especially banks) on the scene for serious competition in line with upgrading quality of service. The present study aims at ranking and order preference of banks based on effective parameters and factors on enhancement of quality of system providers for internet banking services. By conducting study to evaluate effectiveness of criteria in this paper and by means of both multi-criteria decision- making methods of AHP and ANP, we have described a model that could contribute to make suitable decision and select the best choice among options we designated for them. In order to indicate the given mechanisms by means of decision- making supporting system, it has been suggested that % banks to be classified using AHP and ANP models. Although the final result of both techniques is the same in selection of suitable bank based on quality of internet banking services, various values are observed among ranking criteria. Hence, it is suggested to employ ANP method in which dependency among criteria is considered.

Abstract 4155: ARID1A loss leads to chemotherapy resistance and is associated with a poor clinic outcome for patients with non-small cell lung cancer

Abstract Purpose: ARID1A (AT-rich interactive domain 1A) is a member of the switch/sucrose nonfermentable (SWI/SNF) chromatin remodeling complex, and plays important roles in the regulation of gene transcription and DNA damage responses. ARID1A mutations occur frequently in non-small cell lung cancer (NSCLC), but the functions of ARID1A loss in the initiation, progression and maintenance of NSCLC remains largely unknown. This study aimed to investigate the clinical, pathological, and functional significance of ARID1A in NSCLC. Experimental design: We first analyzed the prognostic value of ARID1A using a gene-expression microarray from the Director's Challenge Lung Study. Kaplan-Meier method and Log-rank tests were used to estimate the correlation between ARID1A expression and overall survival (OS). Univariate and multivariate Cox regression models were used to investigate the relationship between ARID1A and other clinical covariates. We further established stable ARID1A knockdown H1299 and H358 cell lines, and ARID1A exogenously expressing H460 and A549 cell lines. We performed functional assays to study the effects of ARID1A on proliferation, migration, invasion, cell cycle progression, sensitivity to chemotherapy, and in vivo tumor growth. Results: In the Director's Challenge Study, decreased expression of ARID1A was associated with lymph node dissemination, higher T-stage (T3/T4), and worse survival compared with high expression in patients in the whole group (n=440) and subgroup who received surgery alone and no adjuvant therapy (n=328). ARID1A ablation by shRNA suppressed cell proliferation, promoted cell mobility, increased G2/M phase cell cycle distribution, and protected NSCLC cells from chemotherapy; whereas overexpression of ARID1A showed the opposite biological effects. Consistent with in vitro findings, in vivo tumor xenografts demonstrated ARID1A depletion led to reductions in cell growth but resistance of NSCLC to chemotherapy. Conclusions: Our results suggest that loss of ARID1A suppresses NSCLC cell growth perhaps by inducing G2/M arrest, but promotes cell migration/invasion, and protect cells from chemotherapy. Further study of ARID1A is needed to better define its roles in the initiation and progression of NSCLC and response to chemotherapy. Citation Format: Linlin Yang, Changxian Shen, Xiaokui Mo, Terence M. Williams. ARID1A loss leads to chemotherapy resistance and is associated with a poor clinic outcome for patients with non-small cell lung cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4155.

Take the initiative to reduce surgical site infections

Take the initiative to reduce surgical site infections

Thyroid Transcription Factor‐1 modulation of secretome alters sensitivity to cisplatin in lung cancer

Thyroid Transcription Factor‐1 (TTF‐1, alternatively known as NKX2‐1) is essential for lung development. Mice homozygous null for TTF‐1 fail to develop lungs and will die in utero. Like many developmental genes, TTF‐1 has also been shown to play a role in cancer development. Its role was originally elucidated when our lab and others showed that TTF‐1 resides in the 14q13.3 region that undergoes focal amplification in roughly 15% of lung adenocarcinomas, and knockdown of TTF‐1 retarded cell growth, suggesting a role as an oncogene. Since this finding, many tumor suppressive roles have been discovered, and TTF‐1 positivity in lung cancer is correlated with a better patient outcome. Our lab is interested in how TTF‐1 can alter lung cancer sensitivity to cisplatin, a common chemotherapy drug used in lung cancer. Our findings reveal that TTF‐1 can sensitize A549 cells to cisplatin. Furthermore, this sensitivity can be found in the secretome of TTF‐1 expressing cells, as conditioned media collected from TTF‐1 transfected cells can sensitize recipient cells to cisplatin relative to controls. We dissected the secretome between vesicle and soluble fractions. Exosomes failed to alter sensitivity to cisplatin. By probing the soluble secreted factors altered by TTF‐1 we found that GM‐CSF was the most differentially regulated. By adding a GM‐CSF neutralizing antibody to A549 cells expressing TTF‐1, we found a conferral of resistance to cisplatin. Conversely, by adding a recombinant GM‐CSF to A549 control cells not expressing TTF‐1, we found that it had the ability to confer sensitivity to cisplatin. Patient data from The Cancer Genome Atlas and the Director's Challenge Lung Study have found a strong positive correlation with TTF‐1 and GM‐CSF in patients. Intriguingly other chemotherapy drugs including carboplatin and gemcitabine did not show a differential effect with TTF‐1, suggesting that TTF‐1 may confer a special sensitivity to cisplatin and could serve as a guide for deciding patient treatment strategies.This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

SMARCA4/BRG1 Is a Novel Prognostic Biomarker Predictive of Cisplatin-Based Chemotherapy Outcomes in Resected Non-Small Cell Lung Cancer.

Identification of predictive biomarkers is critically needed to improve selection of patients who derive the most benefit from platinum-based chemotherapy. We hypothesized that decreased expression of SMARCA4/BRG1, a known regulator of transcription and DNA repair, is a novel predictive biomarker of increased sensitivity to adjuvant platinum-based therapies in non-small cell lung cancer (NSCLC). The prognostic value was tested using a gene-expression microarray from the Director's Challenge Lung Study (n = 440). The predictive significance of SMARCA4 was determined using a gene-expression microarray (n = 133) from control and treatment arms of the JBR.10 trial of adjuvant cisplatin/vinorelbine. Kaplan-Meier method and log-rank tests were used to estimate and test the differences of probabilities in overall survival (OS) and disease-specific survival (DSS) between expression groups and treatment arms. Multivariate Cox regression models were used while adjusting for other clinical covariates. In the Director's Challenge Study, reduced expression of SMARCA4 was associated with poor OS compared with high and intermediate expression (P < 0.001 and P = 0.009, respectively). In multivariate analysis, compared with low, high SMARCA4 expression predicted a decrease in risk of death [HR, 0.6; 95% confidence interval (CI), 0.4-0.8; P = 0.002]. In the JBR.10 trial, improved 5-year DSS was noted only in patients with low SMARCA4 expression when treated with adjuvant cisplatin/vinorelbine [HR, 0.1; 95% CI, 0.0-0.5, P = 0.002 (low); HR, 1.0; 95% CI, 0.5-2.3, P = 0.92 (high)]. An interaction test was highly significant (P = 0.01). Low expression of SMARCA4/BRG1 is significantly associated with worse prognosis; however, it is a novel significant predictive biomarker for increased sensitivity to platinum-based chemotherapy in NSCLC. Clin Cancer Res; 22(10); 2396-404. ©2015 AACR.

MiR-342-3p regulates MYC transcriptional activity via direct repression of E2F1 in human lung cancer

Accumulating evidence indicates that altered miRNA expression is crucially involved in lung cancer development, though scant information is available regarding how MYC, an archetypical oncogene, is regulated by miRNAs, especially via a mechanism involving MYC cofactors. In this study, we attempted to identify miRNAs involved in regulation of MYC transcriptional activity in lung cancer. To this end, we utilized an integrative approach with combinatorial usage of miRNA and mRNA expression profile datasets of patient tumor tissues, as well as those of MYC-inducible cell lines in vitro. In addition to miRNAs previously reported to be directly regulated by MYC, including let-7 and miR-17-92, our strategy also helped to identify miR-342-3p as capable of indirectly regulating MYC activity via direct repression of E2F1, a MYC-cooperating molecule. Furthermore, miR-342-3p module activity, which we defined as a gene set reflecting the experimentally substantiated influence of miR-342-3p on mRNA expression, was found to be inversely correlated with MYC activity reflected by MYC module activity in three independent datasets of lung adenocarcinoma patients obtained from the Director's Challenge Consortium of the United States (P = 1.94 × 10(-73)), the National Cancer Center of Japan (P = 9.05 × 10(-34)) and the present study (P = 1.17 × 10(-19)). Our integrative approach appears to be useful to elucidate inter-regulatory relationships between miRNAs and protein coding genes of interest, even those present in patient tumor tissues, which remains a challenge to better understand the pathogenesis of this devastating disease.

MiR-342-3p regulates MYC transcriptional activity via direct repression of E2F1 in human lung cancer.

Accumulating evidence indicates that altered miRNA expression is crucially involved in lung cancer development, though scant information is available regarding how MYC, an archetypical oncogene, is regulated by miRNAs, especially via a mechanism involving MYC cofactors. In this study, we attempted to identify miRNAs involved in regulation of MYC transcriptional activity in lung cancer. To this end, we utilized an integrative approach with combinatorial usage of miRNA and mRNA expression profile datasets of patient tumor tissues, as well as those of MYC-inducible cell lines in vitro. In addition to miRNAs previously reported to be directly regulated by MYC, including let-7 and miR-17-92, our strategy also helped to identify miR-342-3p as capable of indirectly regulating MYC activity via direct repression of E2F1, a MYC-cooperating molecule. Furthermore, miR-342-3p module activity, which we defined as a gene set reflecting the experimentally substantiated influence of miR-342-3p on mRNA expression, was found to be inversely correlated with MYC activity reflected by MYC module activity in three independent datasets of lung adenocarcinoma patients obtained from the Director's Challenge Consortium of the United States (P = 1.94 × 10(-73)), the National Cancer Center of Japan (P = 9.05 × 10(-34)) and the present study (P = 1.17 × 10(-19)). Our integrative approach appears to be useful to elucidate inter-regulatory relationships between miRNAs and protein coding genes of interest, even those present in patient tumor tissues, which remains a challenge to better understand the pathogenesis of this devastating disease.

Sample size determination for training cancer classifiers from microarray and RNA-seq data

The objective of many high-dimensional microarray and RNA-seq studies is to develop a classifier of cancer patients based on characteristics of their disease. The germinal center B-cell (GCB) classifier study in lymphoma and the National Cancer Institute's Director's Challenge lung (DC-lung) study are two examples. In recent years, such classifiers are often developed using regularized regression, such as the lasso. A critical question is whether a better classifier can be developed from a larger training set size and, if so, how large the training set should be. This paper examines these two questions using an existing sample size method and a novel sample size method developed here specifically for lasso logistic regression. Both methods are based on pilot data. We reexamine the lymphoma and lung cancer data sets to evaluate the sample sizes, and use resampling to assess the estimation methods. We also study application to an RNA-seq data set. We find that it is feasible to estimate sample size for regularized logistic regression if an adequate pilot data set exists. The GCB and the DC-lung data sets appear adequate, under specific assumptions. Existing human RNA-seq data sets are by and large inadequate, and cannot be used as pilot data. Pilot RNA-seq data can be simulated, and the methods in this paper can be used for sample size estimation. A MATLAB program is made available.

Role of LKB1-CRTC1 on Glycosylated COX-2 and Response to COX-2 Inhibition in Lung Cancer

Cyclooxygenase-2 (COX-2) directs the synthesis of prostaglandins including PGE-2 linking inflammation with mitogenic signaling. COX-2 is also an anticancer target, however, treatment strategies have been limited by unreliable expression assays and by inconsistent tumor responses to COX-2 inhibition. We analyzed the TCGA and Director's Challenge lung cancer datasets (n = 188) and also generated an LKB1-null lung cancer gene signature (n = 53) to search the Broad Institute/Connectivity-MAP (C-MAP) dataset. We performed ChIP analyses, real-time polymerase chain reaction, immunoblotting, and drug testing of tumor cell lines (n = 8) and primary lung adenocarcinoma surgical resections (n = 13). We show that COX-2 is a target of the cAMP/CREB coactivator CRTC1 signaling pathway. In addition, we detected a correlation between LKB1 status, CRTC1 activation, and presence of glycosylated, but not inactive hypoglycosylated COX-2 in primary lung adenocarcinoma. A search of the C-MAP drug database discovered that all high-ranking drugs positively associated with the LKB1-null signature are known CRTC1 activators, including forskolin and six different PGE-2 analogues. Somatic LKB1 mutations are present in 20.0% of lung adenocarcinomas, and we observed growth inhibition with COX-2 inhibitors in LKB1-null lung cancer cells with activated CRTC1 as compared with LKB1-wildtype cells (NS-398, P = .002 and Niflumic acid, P = .006; two-tailed t test). CRTC1 activation is a key event that drives the LKB1-null mRNA signature in lung cancer. We also identified a positive feedback LKB1/CRTC1 signaling loop for COX-2/PGE2 regulation. These data suggest a role for LKB1 status and glycosylated COX-2 as specific biomarkers that provide a framework for selecting patients for COX-2 inhibition studies.

Abstract 2357: Gene expression profiling robustly predicts the outcome of patients diagnosed with early stage lung adenocarcinoma

Abstract Background: Although the management of metastatic lung adenocarcinoma has been profoundly modified by the identification of actionnable molecular traits, decision making for early-stage lung adenocarcinoma still relies on the tumor stage (TNM) only. Most of these patients recur within 5 years after tumor resection and are given platinum based adjuvant chemotherapy. The recent availability of multiple gene expression data and the concomitant developments of novel algorithms - such as the Hypercube algorithm - could dramatically improve such predictive challenges. Methods: Datasets were selected from public repositories (Director's challenge (DC) n=274, Rousseaux n=86, Hou n=35, JBR.21 n=31) upon the following criteria: lung adenocarcinoma, stage IA-3A, no adjuvant therapy, R0 tumor resection. To generate robust predictors of 3-year overall survival, an iterative feature selection framework (Hypercube algorithm) was applied successively on DC and Hou. Only highly predictive rules in both datasets (AUC &amp;gt;.7) were then included in a subsequent logistic regression model and finally assessed for external validation. The predictive performance of the models was evaluated by ROC-AUC and by Kaplan Meier curves. Results: Our best model combining gene expression (10 genes) and clinical data (TNM) was robust across three lung adenocarcinoma datasets (AUC= .85, .80 and .59). Particularly, it was able to better predict the 3 year of survival compared to the TNM-based clinical model only (100% vs. 77%). Kaplan Meier estimates of overall survival in the validation datasets were dramatically discriminated according to the high- and low-risk groups predicted by our model (all P values =.01). Interestingly, this predictive classifier was specific to lung adenocarcinoma and has no predictive value in lung squamous datasets. Conclusion: We developed a robust and highly performing gene expression predictive signature of 3-year overall survival, specific to the lung adenocarcinoma setting. These promising results have the potential to change the decision making at bedside for early stage lung adenocarcinoma patients. Citation Format: Yann Gaston-Mathé, CHARLES FERTE, benoit gauthier, mathilde bateson, david planchard, benjamin besse, Jean-Pierre Armand, jean-charles soria. Gene expression profiling robustly predicts the outcome of patients diagnosed with early stage lung adenocarcinoma. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2357. doi:10.1158/1538-7445.AM2014-2357

Abstract 914: Development of a prognostic and predictive E2F signature in formalin-fixed, paraffin-embedded early-stage non-small cell lung cancer samples

Abstract Lung cancer remains the leading cause of cancer-related death in the United States. The 5 year survival for stage I-IIIA lung cancer ranges from only 15-50%. For many in the early stages of the disease, especially stage II patients, adjuvant chemotherapy (ACT) following surgical resection is standard treatment. Still, it appears that the benefits for ACT have plateaued at 4%. With these marginal survival rates and the toxicities associated with chemotherapy, there is a need to develop a predictive tool to identify those patients with early-stage disease who would most benefit from receiving ACT. Previously, we developed an E2F-based gene expression signature derived from microarrays of two non-small cell lung cancer cell lines that were transfected with small interfering RNAs targeted against several members of the E2F pathway. This signature was then filtered for genes that were altered in cancer, but not in normal lung tissues, agreeing between two publicly-available lung tumor/adjacent normal datasets. Through principal component analysis (PCA), the E2F signature was shown to be prognostic in the Molecular Classification of Lung Adenocarcinoma (MCLA) from the Director's Challenge Consortium, as well as predictive of early-stage lung adenocarcinoma patients’ response to ACT in the JBR.10 clinical trial. In order to demonstrate efficacy of the signature in a typical clinical setting, we evaluated whether the NanoString platform (a method that involves the use of a novel “barcode” system to measure gene expression) would be as effective using RNA derived from formalin-fixed, paraffin-embedded (FFPE) tumor samples as compared to fresh frozen RNA. NanoString quantification of RNA from fresh frozen samples correlated very well to FFPE samples (average r=0.9070, median r=0.9290, SD=0.0859). Further, NanoString expression for 32 pairs of both the fresh frozen and FFPE RNA were compared to gene expression microarray readings of the genes in the signature. This analysis demonstrated that the NanoString readings corresponded well to microarray expression, regardless of the method of RNA extraction for NanoString (paired NanoString-frozen vs. microarray: average r=0.5585, median r=0.5608, SD=0.0718; paired NanoString-FFPE vs. microarray: average r=0.5384, median r=0.5401, SD=0.0891). Taken together, these results demonstrate that this E2F signature may be a useful tool for predicting which patients would best respond to adjuvant chemotherapy, and NanoString analysis may be a very effective means of applying this signature to patient samples. Citation Format: Courtney A. Kurtyka, Lu Chen, Matthew B. Schabath, Dung-Tsa Chen, William Brazelle, Eric A. Welsh, Anders E. Berglund, Steven A. Eschrich, Jhanelle E. Gray, Eric B. Haura, W. Douglas Cress. Development of a prognostic and predictive E2F signature in formalin-fixed, paraffin-embedded early-stage non-small cell lung cancer samples. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 914. doi:10.1158/1538-7445.AM2014-914

A Novel Gene Expression Signature that Robustly Predicts the Outcome of Patients Diagnosed with Stage 1 Nsclc

ABSTRACT Aim: Although the management of metastatic lung adenocarcinoma has been profoundly modified by the identification of actionable molecular aberrations, the decision making for early-stage NSCLC still relies on the tumor stage (TNM) only. Stage 1 patients are considered of good prognosis and do not receive adjuvant therapy. However a significant proportion of those patients recur within 5 years after tumor resection. The identification of those high-risk patients through high performing molecular signature would enable to treat them preventively in order to avoid or reduce the rate of recurrence and premature death. Methods: Datasets were selected from public repositories (Director's challenge (DC) n = 402, Rousseaux n = 200, Hou n = 90, Zhu n = 143; Raponi: n = 120; Bhattacharjee; n = 125) upon the following criteria: NSCLC, stage IA-IB, no adjuvant therapy, R0 tumor resection, min 3-year follow-up. Gene expression data from various data sets were normalized using RMA and rescaled. To generate robust predictors of 3-year overall survival, an iterative feature selection framework based on predictive multivariate rules was applied on DC and on a pool of data sets composed of Hou, Zhu and Raponi (Pool) (Development sets). Only highly predictive rules in both datasets were then included in a subsequent predictive model and finally assessed for external validation in Bhattacharjee and Rousseaux (Validation sets). The predictive performances of the models were evaluated by ROC-AUC and by Kaplan Meier curves. Results: Our best model was robust across three independent datasets (all AUC > 0.50, p Conclusions: We developed a robust and highly performing gene expression predictive signature of 3-year overall survival for stage I NSCLC regardless of histology. These promising results have the potential to change the decision making at bedside for early stage lung NSCLC patients by allowing high-risk patients to receive adjuvant therapy and prevent future recurrence and death. Disclosure: All authors have declared no conflicts of interest.

Abstract B221: Hmga2 furthers lung adenocarcinoma progression through function as a competing endogenous RNA.

Abstract Lung adenocarcinoma is the most widespread cancer type worldwide. As the majority of patients are diagnosed with metastatic disease, it is vital to understand that biological basis of adenocarcinoma progression. Hmga2 is among the most over-expressed genes in lung adenocarcinoma, and we have previously shown it is necessary for lung cancer progression in vivo. However, the mechanism of Hmga2-mediated cancer progression is unclear. Here we demonstrate Hmga2 promotes oncogenic transformation by functioning as a competing endogenous RNA (ceRNA) for the let-7 family of microRNAs (miRNAs). First, Hmga2 can promote lung cancer cell transformation independent of its protein-coding function but dependent upon let-7 sites in its 3’ untranslated region. These effects are observed both in vitro and in vivo, where Hmga2 ceRNA activity promotes lung cancer growth and dissemination, impairing survival. Combined analyses of miRNA target prediction and cell line gene expression data suggested the TGF-β co-receptor Tgfbr3 lies downstream of the Hmga2 ceRNA. Follow-up studies demonstrated Hmga2 specifically regulated Tgfbr3 expression through differential recruitment of the miRNA regulatory machinery. This regulation is functionally relevant, as both Tgfbr3 in particular and TGF-β in general are necessary for Hmga2 to promote transformation. To assess the clinical relevance of these experimental findings, we assessed gene expression data from two extensive lung cancer patient gene expression datasets: the Cancer Genome Atlas and the Director's Challenge. Analysis of this gene expression data revealed that HMGA2 and TGFBR3 are coordinately and reciprocally regulated in patients, a necessary prediction of HMGA2 ceRNA function. In total, these results indicate the Hmga2 oncogene functions as both a protein-coding gene and a ceRNA. Such multi-level regulation of gene expression constitutes a novel paradigm by which genes alter cancer development and progression through combined function as both coding proteins and non-coding RNAs. Citation Information: Mol Cancer Ther 2013;12(11 Suppl):B221. Citation Format: Madhu S. Kumar, Elena Armenteros-Monterroso, Philip East, Probir Chakravorty, Nik Matthews, Monte M. Winslow, Julian Downward. Hmga2 furthers lung adenocarcinoma progression through function as a competing endogenous RNA. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2013 Oct 19-23; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2013;12(11 Suppl):Abstract nr B221.

Ribonucleotide reductase subunit-2 (RRM2) and thymidylate synthase (TS) to predict shorter survival in patients (pts) with resected stage I-III non-small cell lung cancer (NSCLC).

11063 Background: Tumor biomarkers can help to identify pts with early-stage NSCLC with high risk of relapse and poor prognosis. The aim of this study was to investigate the prognostic value of 7 biomarkers involved in DNA synthesis and repair. Methods: Tumour tissues from 82 radically resected, stage I-III NSCLC pts were consecutively collected to investigate the following biomarkers: excision repair cross-complementation group 1 (ERCC1), breast cancer 1 (BRCA1), ribonucleotide reductase subunit 1 (RRM1), ribonucleotide reductase subunit 2 (RRM2), subunit p53R2, thymidylate synthase (TS) and class III beta-tubulin (TUBB3) using immunohistochemistry (IHC) and quantitative real time-polymerase chain reaction (qRT-PCR). Expression levels of these genes were also investigated in a large publicly available NSCLC microarray dataset (Director Challenge Consortium, DCC). Results: RRM2 expression (p=0.031), TS expression (p=0.023), and pathologic stage (p&lt;0.001) were found as independent prognostic factors for shorter survival. The expression of ERCC1, RRM1, p53R2, TUBB3, BRCA1, as well as other clinical characteristics, failed to show any statistically significant association with the survival. Despite the lack of statistical significance, patients with lower RRM2 expression (i.e., ≤ 140) survived longer than pts with higher RRM2 levels (p=0.069). There was a trend towards longer survival for BRCA1-, ERCC1-, RRM1- and TS-negative pts and for p53R2- and TUBB3-positive pts. For all of the biomarkers except TUBB3, the OS trends relative to the protein expression levels were in agreement with those relative to the respective gene expression levels, although the differences were not statistically significant. In the larger DCC dataset, TS (p=0.005), and BRCA1 (p=0.021) were identified as prognostic markers for OS, independent of tumour stage. Conclusions: This study has shown that high RRM2 and TS protein levels are negative prognostic factors for resected, stage I-III NSCLC pts. The data obtained by qRT-PCR confirmed these results. Analysis of the DCC microarray dataset detected TS and BRCA1 as independent prognostic markers of OS.

Abstract 5271: Nicotinic acetylcholine receptors and EGF induce c-Kit ligand/Stem Cell Factor (SCF) in a β-arrestin-1 and E2F1 dependent manner in NSCLC .

Abstract β-arrestin-1 (ARRB1), a scaffolding protein involved in the termination or desensitization of signals arising from activated G-protein-coupled receptors (GPCRs) has been shown to play a role in invasion and proliferation of many cancers, including nicotine-induced proliferation of human non-small cell lung cancers (NSCLCs). In this study, we carried out microarray analysis of cells lacking β-arrestin-1 which have been rendered quiescent and subsequently stimulated with nicotine or EGF. Nicotine induced and β-arrestin-1 dependent genes from the microarray data were analyzed. We identified 296 genes that were upregulated and 208 that were downregulated by nicotine in a β-arrestin-1 dependent fashion. The functional pathway analysis tool, MetaCoreTM (Genego, MI, USA) was used to obtain curated molecular interactions related to the above selected genes. We selected top 10 genes from both up and down regulated list for prognosis prediction. Prognostic prediction was carried out using a subset of NCI Director's Challenge Set. Kaplan-Meier analyses for 5 year as well as overall survival showed significance for 4 genes namely COL4A4, NFASC, SCF and ZNF137 by log-rank test. We also examined whether the expression of these gens correlated with smoking; it was found that SCF strongly differentiated smokers from non-smokers implying an important role of this gene in lung carcinogenesis induced by smoking. Stem cell factor (SCF) is the ligand of the c-Kit proto-oncogene product. It is a major human cytokine for the self-renewal, proliferation and differentiation of numerous embryonic, adult hematopoietic and primordial stem cells. Earlier reports show that uncontrolled activity of c-Kit contributes to formation of an array of human tumors. This unregulated activity of c-Kit may be due to overexpression or mutational activation suggesting that SCF-c-Kit signaling can be a potential target for cancer therapy. We elucidate the molecular mechanisms by which nicotine as well as EGF induces the expression of SCF in lung adenocarcinoma cell lines A549 and H1650. ChIP assays and transient transfection experiments showed that transcription factor E2F1 can positively regulate SCF expression at the transcriptional level; depletion of E2F1 or β-arrestin-1 prevented the nicotine-mediated induction of SCF. Given that the binding of SCF to c-Kit leads to activation of multiple downstream signaling pathways including Src, PI3-kinase and MAP/ERK pathways, our data suggest that the SCF/c-Kit pathway plays a central role in lung carcinogenesis, and may be a potential therapeutic target for combating NSCLC. Citation Format: Deepak Perumal, Smitha Pillai, Srikumar Chellappan. Nicotinic acetylcholine receptors and EGF induce c-Kit ligand/Stem Cell Factor (SCF) in a β-arrestin-1 and E2F1 dependent manner in NSCLC . [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 5271. doi:10.1158/1538-7445.AM2013-5271

Abstract 2878: Targeting the CXCL5-CXCR2-CREB signaling axis suppresses growth, survival, and invasion of lung adenocarcinoma.

Abstract The role of chemokines and chemokine receptors has been evolving in cancer. Besides their functions in the immune system, they also play a critical role in tumor initiation, promotion and progression. Since the tumor microenvironment play a critical role in cancer development and progression, the immune components of the tumor microenvironment have gained attention in the recent decades for its critical role in tumorigenesis and tumor control. Recent studies have clearly demonstrated the importance of CXCR2 in the development of lung cancer. Our recent studies showed that CXCR2 expression in tumor cells was associated with poor prognosis in non-small cell lung cancer (NSCLC) patients (n=262). Analysis of gene expression profiles from the National Cancer Institute (NCI) Director's Challenge Cohort of in lung adenocarcinoma patients (n=442) revealed that overexpression of CXCR2 ligands and CXCR2 genes was clustered together in approximately 25% of lung adenocarcinoma patients. Expression of CXCR2 and its associated ligand gene cluster in tumor cells was associated with poor prognosis, smoking status, and poor histologic differentiation. Furthermore, CXCL5 was involved as an potent angiogenic factor in NSCLC. The objective of the current study was to establish the role of the CXCL5/CXCR2 axis in tumor growth and invasion and to determine its related molecular mechanisms. In the study, CXCL5 activated the CREB transcription factor via the pERK1/2-p90Rsk-pCREB signaling pathway. In addition, inhibitors of CXCR2 and downstream signal transduction molecules blocked the activation of pERK1/2-pRsk-pCREB signaling molecules. Blockade of the CXCR2 receptor, CXCR2-dependent signal molecules, or CREB resulted in suppression of NSCLC cell growth, survival and invasion. These results suggest that the CXCL5-CXCR2-CREB signaling axis may be a source of potential therapeutic targets in lung adenocarcinoma. . Citation Format: Hee Sun Park, Jong Woo Lee, Pierre Saintigny, Jonathan M. Kurie, Roy S. Herbst, Jaseok Peter Koo. Targeting the CXCL5-CXCR2-CREB signaling axis suppresses growth, survival, and invasion of lung adenocarcinoma. [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 2878. doi:10.1158/1538-7445.AM2013-2878

Abstract 2354: An E2F signature predicts benefit of adjuvant chemotherapy in early-stage non-small cell lung cancer.

Abstract Early-stage non-small cell lung cancer (NSCLC) is primarily treated by surgical resection. Unfortunately, after resection, one-third to one-half of early-stage patients will die of metastatic recurrence. Adjuvant chemotherapy (ACT) improves the survival of patients with early-stage disease and has become the standard treatment for patients with resected stage II-III NSCLC. However, the five-year survival advantage of ACT is only 4%-15% suggesting that many patients do not benefit. Given the morbidity associated with ACT, it is imperative to develop new prognostic tools to identify those patients with a high probability of relapse. Toward this end, we have used small inhibitory RNAs targeting multiple E2F pathway components to derive an E2F gene expression signature in vitro. This signature was refined by filtering for its components that were altered in non-small cell lung cancers compared to normal tissue. Principle component analysis was then used to represent the signature which was tested for correlation to overall survival in two large cohorts. The first of the two cohorts was the Molecular Classification of Lung Adenocarcinoma (MCLA) from the Director's Challenge Consortium and the second was a novel database on 444 lung adenocarcinomas treated as a part of Moffitt's Total Cancer Care Network. The E2F signature is strongly prognostic in both cohorts with P values &amp;lt;0.0001. Additionally, using data in the JBR.10 trial (GSE14814) for patients who either did or did not receive ACT we were able to determine that patients having a high E2F signature benefit from ACT (have increased overall survival), whereas patients with a low E2F signature do not. Overall, these results suggest that this approach could be optimized in the clinical setting to distinguish patients likely to benefit from ACT from those who will not. Citation Format: Courtney A. Kurtyka, Dung-Tsa Chen, Lu Chen, William Brazelle, Eric A. Welsh, Anders E. Berglund, Steven A. Eschrich, Matthew B. Schabath, Eric B. Haura, W. Douglas Cress. An E2F signature predicts benefit of adjuvant chemotherapy in early-stage non-small cell lung cancer. [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 2354. doi:10.1158/1538-7445.AM2013-2354

A Novel Five Gene Signature Derived from Stem-Like Side Population Cells Predicts Overall and Recurrence-Free Survival in NSCLC

Gene expression profiling has been used to characterize prognosis in various cancers. Earlier studies had shown that side population cells isolated from Non-Small Cell Lung Cancer (NSCLC) cell lines exhibit cancer stem cell properties. In this study we apply a systems biology approach to gene expression profiling data from cancer stem like cells isolated from lung cancer cell lines to identify novel gene signatures that could predict prognosis. Microarray data from side population (SP) and main population (MP) cells isolated from 4 NSCLC lines (A549, H1650, H460, H1975) were used to examine gene expression profiles associated with stem like properties. Differentially expressed genes that were over or under-expressed at least two fold commonly in all 4 cell lines were identified. We found 354 were upregulated and 126 were downregulated in SP cells compared to MP cells; of these, 89 up and 62 downregulated genes (average 2 fold changes) were used for Principle Component Analysis (PCA) and MetaCore™ pathway analysis. The pathway analysis demonstrated representation of 4 up regulated genes (TOP2A, AURKB, BRRN1, CDK1) in chromosome condensation pathway and 1 down regulated gene FUS in chromosomal translocation. Microarray data was validated using qRT-PCR on the 5 selected genes and all showed robust correlation between microarray and qRT-PCR. Further, we analyzed two independent gene expression datasets that included 360 lung adenocarcinoma patients from NCI Director's Challenge Set for overall survival and 63 samples from Sungkyunkwan University (SKKU) for recurrence free survival. Kaplan-Meier and log-rank test analysis predicted poor survival of patients in both data sets. Our results suggest that genes involved in chromosome condensation are likely related with stem-like properties and might predict survival in lung adenocarcinoma. Our findings highlight a gene signature for effective identification of lung adenocarcinoma patients with poor prognosis and designing more aggressive therapies for such patients.