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I. Kim



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    MA17 - Genetic Drivers (ID 409)

    • Event: WCLC 2016
    • Type: Mini Oral Session
    • Track: Biology/Pathology
    • Presentations: 1
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      MA17.01 - Microarray Identification of Genetic Drivers of Brain Metastasis in Lung Adenocarcinoma (ID 3962)

      14:20 - 15:50  |  Author(s): I. Kim

      • Abstract
      • Presentation
      • Slides

      Background:
      Brain metastasis in non-small cell lung cancer (NSCLC) develop in 20-40% of all patients and represent a major cause of NSCLC morbidity and mortality. The mechanisms driving metastatic potential across the blood-brain-barrier remain poorly understood.

      Methods:
      Affymetrix microarray was performed on RNA extracted from 75 pairs of snap-frozen primary lung adenocarcinoma and matched normal lung tissue. Changes in gene expression from the primary lung adenocarcinomas that did not ever metastasize to brain over up to 15 years of follow up were compared to the lung adenocarcinomas that ultimately seeded a brain metastasis. From these 75 patients, tissue from 5 paired snap-frozen brain metastases was also available and gene expression changes between the primary lung adenocarcinomas and matched brain metastases were investigated to identify genes and pathways of interest in the development of brain metastasis. Affymetrix Transcriptome Analysis Console software was used for data analysis and interpretation with fold changes >2.0 and p-value of <0.05 for significance.

      Results:
      From the 75 patients 20 (27%) ultimately developed a brain metastasis from their primary lung adenocarcinoma and 55 (73%) were followed long term without development of brain metastasis. Microarray identified 71 genes that were differentially expressed in lung adenocarcinomas that later produced brain metastasis. S100 calcium binding protein, RAP1GAP, GPR160, and immunoglobins were among the upregulated genes in primary lung adenocarcinomas that developed brain metastasis. Within the matched sets of brain metastasis, hierarchical clustering showed clear distinction in expression patterns comparing brain metastasis verses normal lung, as well as primary adenocarcinomas verses normal lung. 267 genes were identified to be significantly differentially expressed between paired brain metastasis and primary lung adenocarcinomas. Significant changes in focal adhesion, angiogenesis, matrix metalloproteinase pathways, and immunoglobulins were found in the brain metastasis compared with the paired primary lung tumor.

      Conclusion:
      This study represents the largest microarray analysis of snap frozen pairs of primary lung adenocarcinoma and brain metastasis to date. S100 calcium binding protein, RAP1GAP, GPR160 genes, immunoglobulins, and focal adhesion, angiogenesis, and matrix metalloproteinase pathways were among the upregulated genes in primary lung adenocarcinomas that developed brain metastasis.

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    P1.03 - Poster Session with Presenters Present (ID 455)

    • Event: WCLC 2016
    • Type: Poster Presenters Present
    • Track: Radiology/Staging/Screening
    • Presentations: 1
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      P1.03-066 - Incorporation of a Molecular Prognostic Classifier Improves Conventional Non-Small Cell Lung Cancer TNM Staging (ID 5831)

      14:30 - 15:45  |  Author(s): I. Kim

      • Abstract

      Background:
      Tumor size, nodal spread, and distant metastases form the basis of current non-small cell lung cancer staging. Despite undergoing a major revision in 2009, the poor outcomes of early-stage lung cancer patients relative to other solid tumors such as breast and colorectal cancer suggests that further improvement to our ability to stage non-small cell lung cancers is needed. In this study, we demonstrate the benefit of integrating a clinically validated molecular prognostic signature into conventional TNM staging.

      Methods:
      A new staging system integrating a 14-gene molecular prognostic classifier with TNM descriptors was developed using 332 patients with stage I-IIIB non-squamous, non-small cell lung cancer resected at the University of California, San Francisco. This staging system was subsequently validated on a separate multi-institutional international cohort of 1379 patients with stage I-IIIB disease. Reclassification measures were used to assess for improvements in calibration and discrimination beyond conventional TNM staging.

      Results:
      In the validation cohort, 78.2% of patients were reclassified using the new staging system. 73% of these patients were reclassified more accurately. The new staging system demonstrated improved measures of model fit including the modified Nagelkerke’s R[2] statistic as well as the c-index. In addition, incorporation of the molecular classifier resulted in a Net Reclassification Improvement of 16.6% (95%CI 7.9-25.2%) and a relative Integrated Discrimination Improvement of 27.9% (95%CI 6.4-49.4%). Kaplan-Meier analysis of overall survival after surgical resection demonstrated superior survival curve separation with the addition of the molecular classifier. Figure 1. Kaplan-Meier analysis of overall survival from time of surgical resection (A: TNM staging, B: TNMB staging). Figure 1



      Conclusion:
      Incorporation of a molecular classifier of tumor biology offers substantial improvements to conventional TNM staging and encourages application of molecular prognostic classifiers into the refinement of TNM staging systems for other solid tumors.