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J.D. Minna



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    MO05 - Prognostic and Predictive Biomarkers II (ID 95)

    • Event: WCLC 2013
    • Type: Mini Oral Abstract Session
    • Track: Medical Oncology
    • Presentations: 1
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      MO05.05 - Lung Cancer Explorer (LCE): an open web portal to explore gene expression and clinical associations in lung cancer (ID 2512)

      16:35 - 16:40  |  Author(s): J.D. Minna

      • Abstract
      • Presentation
      • Slides

      Background
      Lung cancer is the leading cause of death from cancer for both men and women in the United States with a 5-year survival rate of approximately 15%. Many gene expression microarray datasets have been collected through different studies, while a single genomics study usually contains no more than 500 microarrays due to the high cost. We collected and manually curated mRNA expression microarrays together with clinical information for 5,218 lung cancer patients from 40 studies. The wealth of these large-scale datasets provides us great opportunities to generate significant scientific findings, while also posing great challenges for data integration.

      Methods
      To facilitate clinicians and researchers to access and use the resource, we developed an open web portal, The Lung Cancer Explorer, to explore gene expression and clinical associations in lung cancer. This database aggregates over 40 public clinically-annotated lung cancer gene expression studies, along with some private data from the University of Texas Southwestern Medical Center, and presents a user-friendly, web-based interface to explore and analyze this data. The database stores various information about patients including demographics, histology, stage classifications, clinical outcomes, and also stores the probe-level genome-wide mRNA expression information, allowing users to perform very rich analysis on the data.

      Results
      From the user’s perspective, usage is as easy as logging in and clicking a button to perform any of our current analysis functions: · Survival Analysis: Test the association between the gene expression level and patients’ overall survival time in one study. · Meta-Survival Analysis: Summarize the association between the gene expression level and patients’ overall survival time across multiple studies. · Comparative Analysis: Test the association between the gene expression level and patients’ characteristics, such as gender, age, histology types, disease stages, etc. · Tumor vs. Normal: Test whether the gene expression levels different significantly between tumor samples and normal samples. · Co-expression analysis: Calculate the correlations among a list of user-specified genes based on the gene expression levels. The web application is now online and available for usage: http://qbrc.swmed.edu/lce/ . I will talk about the data curation, quality control, database development and the usage of this resource.

      Conclusion
      The Lung Cancer Explorer is a highly interactive open resource for lung cancer research and it can greatly facilitate the translational lung cancer research.

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    MO15 - Novel Genes and Pathways (ID 89)

    • Event: WCLC 2013
    • Type: Mini Oral Abstract Session
    • Track: Biology
    • Presentations: 1
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      MO15.02 - Impact of co-occurring genetic events on the signaling landscape of KRAS-mutant lung adenocarcinoma. (ID 2936)

      16:20 - 16:25  |  Author(s): J.D. Minna

      • Abstract
      • Presentation
      • Slides

      Background
      Personalized medicine frameworks centered on identification and therapeutic targeting of dominant oncogenic driver mutations are rapidly becoming a standard of care in the clinical management of patients with lung adenocarcinoma. However, little is currently known about the nature and impact of co-occurring genetic events on signaling output downstream of initiating oncogenes. This lacuna in our understanding is particularly pertinent for the subgroup of KRAS-driven tumors, where mounting data point towards considerable heterogeneity in pathway activation and clinical response to targeted therapies. Here, we report a comprehensive analysis of genetic events that co-occur with or are mutually exclusive of mutant KRAS in a cohort of 230 lung adenocarcinomas and assess the impact of individual co-mutations on signaling streams using data derived from state of the art transcriptomic and (phospho)proteomic profiling of primary tumors.

      Methods
      An integrated analysis of 230 lung adenocarcinomas from The Cancer Genome Atlas (TCGA) consortium was performed using mutation (whole exome sequencing), transcriptomic (RNASeq), and proteomic (reverse phase protein array) datasets. Fischer’s exact test was applied to identify secondary mutations that occurred more frequently in either KRAS-mutant (n=68) or KRAS-wild-type (n=162) tumors and (phospho)protein markers that associated with each co-mutation. Genes with a mutation rate of ≥3% in the overall cohort were included in the analysis.

      Results
      Mutations in 18 genes were associated with KRAS mutational status in patient tumors (p≤0.01). Mutations in EGFR (p=0.0001), NF1 (p=0.001), and TP53 (p=0.001) were negatively correlated with the KRAS mutation. On the other hand, mutations in STK11 were significantly more frequent in the KRAS-mutant cohort (p=0.004), as were mutations in ATM (p=0.023) and MTOR (p=0.045). The most significant positive association involved mutations in ARHGEF11, a gene that encodes a Rho guanine nucleotide exchange factor (p=0.0004). Mutations in STK11 (29.4%) and TP53 (29.4%), the two most highly prevalent genetic events within the KRAS-mutant cohort were mutually exclusive. Unsupervised hierarchical clustering of transcriptomic and quantitative (phospho)proteomic profiles revealed separation of STK11-mutant tumors at the first branch of the cluster dendrogram, indicating activation of distinct signaling pathways downstream of this key tumor suppressor gene. Several less frequent genetic events had prominent and consistent effects on signaling output. We focused our attention on signaling via the MAPK pathway which may impact clinical sensitivity to MEK inhibitors, one of the most promising classes of targeted agents currently in clinical development for KRAS-mutant tumors. Preliminary analysis suggests that mutations in 3 individual genes can identify a subgroup of tumors (19% of the cohort) with profoundly suppressed MAPK signaling flux.

      Conclusion
      Analysis of recurrent secondary genetic events may define distinct and clinically relevant subsets of KRAS-mutant lung adenocarcinoma. Efforts to refine the sub-classification further and assess the impact of co-mutations on sensitivity to molecularly targeted agents are underway and updated results will be presented at the meeting.

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    P1.01 - Poster Session 1 - Cancer Biology (ID 143)

    • Event: WCLC 2013
    • Type: Poster Session
    • Track: Biology
    • Presentations: 1
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      P1.01-003 - Targeting EMT in lung cancer: An integrated analysis of Axl and other mesenchymal targets in The Cancer Genome Atlas (TCGA) (ID 1991)

      09:58 - 10:12  |  Author(s): J.D. Minna

      • Abstract

      Background
      We previously developed a 76-gene signature of epithelial-to-mesenchymal transition (EMT) that predicted resistance to EGFR and PI3K inhibition in non-small cell lung cancer (NSCLC). This analysis also identified Axl, a receptor tyrosine kinase, as a novel target for mesenchymal lung cancers. Here, we conducted an integrated molecular analysis of EMT in resected, treatment-naïve tumors from three clinical cohorts, including the Cancer Genome Atlas (TCGA) lung adenocarcinomas (LUAD) and squamous cell carcinomas (LUSC), with particular focus on Axl as a potential target in mesenchymal NSCLC.

      Methods
      Using our 76-gene EMT signature, TCGA patient tumors (230 LUAD, 178 LUSC) and a large MDACC cohort of resected tumors (n=279) were assigned an “EMT score.” Expression of >160 total and phosphoproteins were measured in the tumors by reverse phase protein array (RPPA). Proteomic profiles and other molecular markers (including mutation status, miRNA expression, and copy number) were correlated with EMT scores and Axl expression levels.

      Results
      The EMT score, derived from our EMT signature, identified NSCLC tumors with mesenchymal gene expression signatures (average 23% of tumors across all cohorts, range 14-34%). In both LUAD and LUSC, EMT scores were highly correlated with (1) expression levels of the miR200 family, a group of miRNAs previously known to regulate EMT (p-values <0.001 by Pearson correlation) and (2) levels of proteins central to EMT (e.g., E-cadherin, alpha-catenin, beta-catenin, claudin-7, fibronectin; p<0.001 for all). Mesenchymal tumors also had lower expression of TTF1 in LUAD (p=0.0002) and lower p63 in LUSC (p=0.003). Although pEGFR levels were higher in epithelial LUAD tumors (p=0.01), the frequency of EGFR mutations was not significantly higher in this group. EMT score was not associated with smoking status. Consistent with our previous findings in cell lines and patients with advanced NSCLC (BATTLE trial), protein expression of the receptor tyrosine kinase Axl was significantly higher in tumors with mesenchymal signatures (high EMT scores) and with low E-cadherin protein expression (p<0.005 for both). The inverse correlation between tumor E-cadherin and Axl expression was confirmed in an independent group of NSCLC cases by immunohistochemistry. Although a small number of Axl mutations were observed (<3% of tumors), few occurred in the kinase domain and their biological significance is unknown. Other potential therapeutic targets expressed at higher levels in mesenchymal lung cancers included PKC-alpha, NFKB, and FGFR1.

      Conclusion
      The EMT gene expression signature performed well in the TCGA LUAD, TCGA LUSC, and MDACC cohorts, correlating strongly with established markers of EMT on other data platforms (miRNA and protein). We observed strong protein expression of the receptor tyrosine kinase Axl (as well as other targets) among mesenchymal tumors, supporting further investigation of AXL as a potential EMT target and into the mechanism of its overexpression in NSCLC.