Supplementary Data from Characterizing the Clinical Relevance of an Embryonic Stem Cell Phenotype in Lung Adenocarcinoma

Supplementary Tables 6-9 from Utilization of Pathway Signatures to Reveal Distinct Types of B Lymphoma in the Eμ-myc Model and Human Diffuse Large B-Cell Lymphoma

Supplementary Figures 1-5 from Utilization of Pathway Signatures to Reveal Distinct Types of B Lymphoma in the Eμ-myc Model and Human Diffuse Large B-Cell Lymphoma

This chapter highlights both opportunities presented by recent advances in the development of genomic-based approaches within the field of breast cancer and corresponding strategies for implementation of these techniques into clinical practice. Additionally, the development of predictive signatures specific for response to individual cytotoxic agents would provide an invaluable clinical tool to enable the better use of available standard-of-care agents. Chang et al. performed gene expression profiling on locally advanced breast cancers treated with docetaxel to identify genes predictive of response to this therapeutic modality. Similar work has been done with preoperative doxorubicin therapy and sequential taxane/anthracycline therapy. Pathway signatures have the potential to identify patients most sensitive to standard-of-care cytotoxic drugs, as well as those resistant to standard regimens. Commonly, patients are treated with one or more therapeutic regimens that, on a population basis, have individually demonstrated equal efficacy.

To the Editor: We would like to retract the article entitled “Gene Expression Signatures, Clinicopathological Features, and Individualized Therapy in Breast Cancer,” which was published in the April 2, 2008, issue of JAMA. A component of this article reported the use of chemotherapy sensitivity predictions based on an approach described by Potti et al in Nature Medicine in 2006. The Nature Medicine article was recently retracted due to an inability to reproduce the results with the chemotherapy signatures. Because a significant component of this JAMA article was based on the use of chemotherapy signatures reported in the Nature Medicine paper, we have decided to retract the JAMA article. We apologize for any negative impact on scientific research or clinical care caused by the publication of our article in JAMA.

Many examples highlight the power of gene expression profiles, or signatures, to provide an understanding of biological phenotypes. This is best seen in the context of cancer, where expression signatures have tremendous power to identify new cancer subtypes and to predict clinical outcomes. Gene expression profiles have been developed to personalize medicine, accurately predicting disease recurrence and tumor response to therapy. The use of these signatures as surrogate phenotypes allows us to link diverse experimental systems, which dissect the complexity of biological systems, with the in vivo setting in a way that was not previously feasible. Taken together, these new genomic tools provide the opportunity to develop rational strategies for treating the individual cancer patient.

Introduction Perhaps the major challenge in developing more effective therapeutic strategies for the treatment of breast cancer patients is confronting the heterogeneity of the disease, recognizing that breast cancer is not one disease but multiple disorders with distinct underlying mechanisms. Gene-expression profiling studies have been used to dissect this complexity, and our previous studies identified a series of intrinsic subtypes of breast cancer that define distinct populations of patients with respect to survival. Additional work has also used signatures of oncogenic pathway deregulation to dissect breast cancer heterogeneity as well as to suggest therapeutic opportunities linked to pathway activation.Methods We used genomic analyses to identify relations between breast cancer subtypes, pathway deregulation, and drug sensitivity. For these studies, we use three independent breast cancer gene-expression data sets to measure an individual tumor phenotype. Correlation between pathway status and subtype are examined and linked to predictions for response to conventional chemotherapies.Results We reveal patterns of pathway activation characteristic of each molecular breast cancer subtype, including within the more aggressive subtypes in which novel therapeutic opportunities are critically needed. Whereas some oncogenic pathways have high correlations to breast cancer subtype (RAS, CTNNB1, p53, HER1), others have high variability of activity within a specific subtype (MYC, E2F3, SRC), reflecting biology independent of common clinical factors. Additionally, we combined these analyses with predictions of sensitivity to commonly used cytotoxic chemotherapies to provide additional opportunities for therapeutics specific to the intrinsic subtype that might be better aligned with the characteristics of the individual patient.Conclusions Genomic analyses can be used to dissect the heterogeneity of breast cancer. We use an integrated analysis of breast cancer that combines independent methods of genomic analyses to highlight the complexity of signaling pathways underlying different breast cancer phenotypes and to identify optimal therapeutic opportunities.

To the Editor: We would like to retract our article, "A Genomic Strategy to Refine Prognosis in Early-Stage Non-Small-Cell Lung Cancer,"(1) which was published in the Journal on August 10, 2006. Using a sample set from a study by the American College of Surgeons Oncology Group (ACOSOG) and a collection of samples from a study by the Cancer and Leukemia Group B (CALGB), we have tried and failed to reproduce results supporting the validation of the lung metagene model described in the article. We deeply regret the effect of this action on the work of other investigators.

BACKGROUND:The Lung Cancer Exercise Training Study (LUNGEVITY) is a randomized trial to investigate the efficacy of different types of exercise training on cardiorespiratory fitness (VO2peak), patient-reported outcomes, and the organ components that govern VO2peak in post-operative non-small cell lung cancer (NSCLC) patients.METHODS/DESIGN:Using a single-center, randomized design, 160 subjects (40 patients/study arm) with histologically confirmed stage I-IIIA NSCLC following curative-intent complete surgical resection at Duke University Medical Center (DUMC) will be potentially eligible for this trial. Following baseline assessments, eligible participants will be randomly assigned to one of four conditions: (1) aerobic training alone, (2) resistance training alone, (3) the combination of aerobic and resistance training, or (4) attention-control (progressive stretching). The ultimate goal for all exercise training groups will be 3 supervised exercise sessions per week an intensity above 70% of the individually determined VO2peak for aerobic training and an intensity between 60 and 80% of one-repetition maximum for resistance training, for 30-45 minutes/session. Progressive stretching will be matched to the exercise groups in terms of program length (i.e., 16 weeks), social interaction (participants will receive one-on-one instruction), and duration (30-45 mins/session). The primary study endpoint is VO2peak. Secondary endpoints include: patient-reported outcomes (PROs) (e.g., quality of life, fatigue, depression, etc.) and organ components of the oxygen cascade (i.e., pulmonary function, cardiac function, skeletal muscle function). All endpoints will be assessed at baseline and postintervention (16 weeks). Substudies will include genetic studies regarding individual responses to an exercise stimulus, theoretical determinants of exercise adherence, examination of the psychological mediators of the exercise - PRO relationship, and exercise-induced changes in gene expression.DISCUSSION:VO2peak is becoming increasingly recognized as an outcome of major importance in NSCLC. LUNGEVITY will identify the optimal form of exercise training for NSCLC survivors as well as provide insight into the physiological mechanisms underlying this effect. Overall, this study will contribute to the establishment of clinical exercise therapy rehabilitation guidelines for patients across the entire NSCLC continuum.TRIAL REGISTRATION:NCT00018255.

7611 Background: Tobacco exposure has a profound influence on the molecular biology of NSCLC. In this study, gene expression arrays were used: 1) to define distinct molecular sub-phenotypes that drive the biology of NSCLC in smokers versus never smokers; and 2) to combine an epidermal growth factor receptor (EGFR) pathway signature with EGFR mutation status to predict response to an EGFR tyrosine kinase inhibitor (gefitinib). Methods: Clinically annotated genomic data from 680 patients with stage I-IIIA adenocarcinoma and squamous cell carcinoma were analyzed. Signatures representing oncogenic pathway deregulation (β-CAT, E2F1, Myc, Ras, Src, EGFR, and STAT3) and tumor biology (chromosomal instability [CIN], epigenetic stem cell [EPI], invasiveness [IGS], tumor necrosis factor-α [TNF-α], and wound healing [WH]) were applied to these samples to define sub-phenotypes. Multivariate analyses were then performed to evaluate the clinical relevance of pathway-based prognostic clusters. Finally, in vitro gefitinib inhibitory concentration (IC50) data was obtained for 26 NSCLC cell lines for which corresponding gene expression data was available. The ability of an EGFR pathway signature to predict response to gefitinib was evaluated. Results: WH (p < 0.01), TNF-α (p < 0.01), STAT3 (p < 0.001), and CIN (p < 0.01) pathways were significantly up-regulated in smokers, as compared to the activation of EPI (p < 0.01) and E2F1 (p < 0.05) pathways in never-smokers. Furthermore, using 60-month overall survival as a clinical endpoint, multivariate analyses confirmed the relevance of pathway-based sub-phenotypes (p < 0.001), HR: 1.59 (95% CI: 1.2-2.1). Finally, by combining EGFR mutation status with predicted EGFR pathway activation, sensitivity for predicting response to gefitinib was increased from 38% to 67% without compromising specificity (90% vs. 88%). Conclusions: Gene expression data demonstrates unique patterns of oncogenic pathway activation in never smokers versus smokers, and can further stratify patients into high and low risk cohorts. The combination of established molecular markers with gene expression data may enhance the therapeutic index of targeted therapies. No significant financial relationships to disclose.

This chapter contains sections titled: Introduction Methods Results Discussion References

e17519 Background: Tumor response to radiotherapy in NSCLC remains markedly heterogeneous. Few successful radiosensitivity predictive assays exist that can be applied to individualize radiotherapeutic options. Methods: Using Bayesian regression analysis, a 52-gene expression signature that predicts sensitivity to external beam radiotherapy was developed and independently validated. On the basis of the signature, using Connectivity Map, novel candidate radiosensitizers were identified and tested in vitro by cell proliferation assays on predicted radioresistant NSCLC cell lines at three different radiation doses (3, 5 and 7 Gy). Cisplatin was used as a clinically relevant control. Furthermore, a systemic computational approach was developed to identify potential radiation-specific miRNAs, which were later transiently expressed and validated in vitro using the aforementioned NSCLC cell lines. Results: The 52-gene expression signature accurately predicted radiosensitivity in vitro and in individuals treated with radiation or chemoradiation independent of tissue. Tumor cell-specific novel agents, such as ethacrynic acid and docosahexaenoic acid have shown to radiosensitize NSCLC cell lines in a drug and radiation dose-indepependent manner. Finally, radiation-specific miRNAs (hsa-let-7b, hsa- let-7i and hsa-miR30a), which were shown to regulate RAS signaling pathway as evidenced from Western analyses, significantly radiosensitize (p<0.001 for all three miRNAs with respect to mock transfected controls) NSCLC cell lines. Conclusions: Comprehensive genomic analysis using gene expression signatures and miRNA data provides opportunities to better understand the mechanisms underlying radiation response and provides novel therapeutic opportunities in NSCLC. No significant financial relationships to disclose.

7012 Background: Insulin and insulin-like growth factors are key regulators of normal metabolism and growth. Independently, and via interactions with the epidermal growth factor receptor (EGFR), the insulin receptor (IR) and insulin-like growth factor 1 receptor (IGF-1R) are implicated in the development and progression of NSCLC. Though novel agents targeting the IR/IGF-1R pathway are under investigation, no molecular markers exist to guide therapy. Methods: After confirming IR and IGF-1R pathway activation, RNA from control, insulin and IGF treated cells was submitted for gene expression profiling. Using binary regression, an in vitro gene signature for IR and IGF-1R pathway activation was generated and validated in two independent early stage (I-IIIA) NSCLC data sets (cohort 1, n= 442, cohort 2, n=170) and in 63 NSCLC cell lines. Matrigel invasion, EGFR tyrosine-kinase inhibition (TKI) resistance, and miRNA expression were assayed and correlated to predicted pathway activation. Results: Hierarchical clustering of predicted IR/IGF-1R pathway activation ranging from high to low revealed four prognostic clusters. NSCLC tumors with concomitant high activation of IR and IGF-1R pathway had a significantly worse survival compared to those with low-intermediate activation (cohort 1, p=0.008; cohort 2, p=0.02). Invasiveness was increased in NSCLC cell lines predicted to have high pathway activation (p=0.003), as were miRNAs associated with invasiveness and metastasis (miR-155, miR-373). Conversely, miRNAs associated with tumor suppression (let-7 family) were enriched in the low- intermediate cluster. Moreover, cell lines resistant to EGFR-TKIs were more likely to have high IR/IGF-1R pathway activation (p=0.04). Work is ongoing to evaluate the differential susceptibility to EGFR-TKIs, and identify IR/IGF-1R related miRNA targets mediating EGFR-TKI resistance. Conclusions: A transcriptomic-based strategy delineates patterns of the IR/IGF-1R pathways that are prognostic in NSCLC, and identifies cohorts of patients who may be candidates for adjuvant therapy with IGF-1R inhibitors. Such a directed approach could improve therapeutic efficacy and subvert EGFR resistance mechanisms in NSCLC. No significant financial relationships to disclose.

10507 Background: We propose that the sonic hedge hog pathway (SHH) induces EMT in vitro, resulting in gene expression changes that are clinically relevant. Methods: EMT was induced in lung, breast, and prostate cancer cells in vitro through co-culture with myofibroblasts, a rich source of the SHH ligand. Real-time PCR (QRT-PCR) and immunoflorescence were used to confirm EMT, and invasiveness of the phenotype was assessed with matrigel assays. Microarray analysis was performed on RNA extracted from EMT induced cells and controls and bayesian regression methods were used to generate an EMT signature. Clinically annotated gene expression data from patients with lung (n = 128), breast (n = 286) and prostate (n = 79) cancer was used to ascertain the clinical importance of EMT, using survival as a relevant outcome. Results: QRT-PCR confirmed upregulation of EMT related genes, demonstrating a several fold increase in the expression of Snail, N- cadherin, Gli 2 and SHH genes, respectively (p < 0.0001). Immunoflorescence confirmed the necessary Cadherin switch and the EMT induced cells demonstrated increased invasion (p = 0.001). Cyclopamine inhibited increased expression of Snail, N-cadherin, SHH, and Gli2 (p <0.0001) confirming that SHH was a principal mediator of EMT in human tumors. Using EMT induced cells and control cells, a genomic signature for EMT in adenocarcinoma was characterized, comprised of 200 genes. Upregulated pathways include keratan sulfate biosynthesis and extracellular matrix interaction. Importantly, the EMT signature predicts for 5-yr metastasis-free survival in a large dataset of node negative breast cancer patients (p = 0.004). Similar statistically significant survival differences exist in prostate (p = 0.03) and lung cancer (p = 0.04). In addition, chemosensitivity for over 40 lung cancer cell lines was assessed, with median EC50 values significantly higher in cell lines with a high probability of EMT. Conclusions: Activation of the SHH pathway induces EMT in human cancers and genome-wide changes occurring during EMT can be used to predict clinical outcomes. The SHH pathway represents a unique therapeutic target for suppression of distant metastasis and modulating chemotherapeutic resistance. No significant financial relationships to disclose.

The hallmark of human cancer is heterogeneity, reflecting the complexity and variability of the vast array of somatic mutations acquired during oncogenesis. An ability to dissect this heterogeneity, to identify subgroups that represent common mechanisms of disease, will be critical to understanding the complexities of genetic alterations and to provide a framework to develop rational therapeutic strategies. Here, we describe a classification scheme for human breast cancer making use of patterns of pathway activity to build on previous subtype characterizations using intrinsic gene expression signatures, to provide a functional interpretation of the gene expression data that can be linked to therapeutic options. We show that the identified subgroups provide a robust mechanism for classifying independent samples, identifying tumors that share patterns of pathway activity and exhibit similar clinical and biological properties, including distinct patterns of chromosomal alterations that were not evident in the heterogeneous total population of tumors. We propose that this classification scheme provides a basis for understanding the complex mechanisms of oncogenesis that give rise to these tumors and to identify rational opportunities for combination therapies.