Ni Zhao1, Matthew D Wilkerson2, Usman Shah3, Xiaoying Yin4, Anyou Wang4, Michele C Hayward4, Patrick Roberts4, Carrie B Lee5, Alden M Parsons6, Leigh B Thorne7, Benjamin E Haithcock6, Juneko E Grilley-Olson5, Thomas E Stinchcombe5, William K Funkhouser7, Kwok-Kin Wong8, Norman E Sharpless9, D Neil Hayes10. 1. The Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, United States; Department of Biostatistics, The Gilling School of Global Public Health, University of North Carolina at Chapel Hill, United States. 2. The Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, United States; Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States. 3. Department of medicine, Division of hematology/oncology, Lehigh Valley Health Network, Allentown, PA. 4. The Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, United States. 5. The Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, United States; Department of Internal Medicine, Division of Hematology/Oncology, Multidisciplinary Thoracic Oncology Program, University of North Carolina at Chapel Hill, United States. 6. Department of Surgery, Division of Cardiothoracic Surgery, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States. 7. The Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, United States; Department of Pathology and Lab Medicine, UNC School of Medicine, University of North Carolina at Chapel Hill, United States. 8. Department of Medicine, Harvard Medical School, Adult Oncology, Dana-Farber Cancer Institute, United States. 9. The Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, United States; Department of Internal Medicine, Division of Hematology/Oncology, Multidisciplinary Thoracic Oncology Program, University of North Carolina at Chapel Hill, United States; Department of Genetics, School of Medicine, University of North Carolina at Chapel Hill, United States. 10. The Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, United States; Department of Internal Medicine, Division of Hematology/Oncology, Multidisciplinary Thoracic Oncology Program, University of North Carolina at Chapel Hill, United States. Electronic address: hayes@med.unc.edu.
Abstract
BACKGROUND: Brain metastases are one of the most malignant complications of lung cancer and constitute a significant cause of cancer related morbidity and mortality worldwide. Recent years of investigation suggested a role of LKB1 in NSCLC development and progression, in synergy with KRAS alteration. In this study, we systematically analyzed how LKB1 and KRAS alteration, measured by mutation, gene expression (GE) and copy number (CN), are associated with brain metastasis in NSCLC. MATERIALS AND METHODS: Patients treated at University of North Carolina Hospital from 1990 to 2009 with NSCLC provided frozen, surgically extracted tumors for analysis. GE was measured using Agilent 44,000 custom-designed arrays, CN was assessed by Affymetrix GeneChip Human Mapping 250K Sty Array or the Genome-Wide Human SNP Array 6.0 and gene mutation was detected using ABI sequencing. Integrated analysis was conducted to assess the relationship between these genetic markers and brain metastasis. A model was proposed for brain metastasis prediction using these genetic measurements. RESULTS: 17 of the 174 patients developed brain metastasis. LKB1 wild type tumors had significantly higher LKB1 CN (p<0.001) and GE (p=0.002) than the LKB1 mutant group. KRAS wild type tumors had significantly lower KRAS GE (p<0.001) and lower CN, although the latter failed to be significant (p=0.295). Lower LKB1 CN (p=0.039) and KRAS mutation (p=0.007) were significantly associated with more brain metastasis. The predictive model based on nodal (N) stage, patient age, LKB1 CN and KRAS mutation had a good prediction accuracy, with area under the ROC curve of 0.832 (p<0.001). CONCLUSION: LKB1 CN in combination with KRAS mutation predicted brain metastasis in NSCLC.
BACKGROUND:Brain metastases are one of the most malignant complications of lung cancer and constitute a significant cause of cancer related morbidity and mortality worldwide. Recent years of investigation suggested a role of LKB1 in NSCLC development and progression, in synergy with KRAS alteration. In this study, we systematically analyzed how LKB1 and KRAS alteration, measured by mutation, gene expression (GE) and copy number (CN), are associated with brain metastasis in NSCLC. MATERIALS AND METHODS:Patients treated at University of North Carolina Hospital from 1990 to 2009 with NSCLC provided frozen, surgically extracted tumors for analysis. GE was measured using Agilent 44,000 custom-designed arrays, CN was assessed by Affymetrix GeneChip Human Mapping 250K Sty Array or the Genome-Wide Human SNP Array 6.0 and gene mutation was detected using ABI sequencing. Integrated analysis was conducted to assess the relationship between these genetic markers and brain metastasis. A model was proposed for brain metastasis prediction using these genetic measurements. RESULTS: 17 of the 174 patients developed brain metastasis. LKB1 wild type tumors had significantly higher LKB1 CN (p<0.001) and GE (p=0.002) than the LKB1 mutant group. KRAS wild type tumors had significantly lower KRAS GE (p<0.001) and lower CN, although the latter failed to be significant (p=0.295). Lower LKB1 CN (p=0.039) and KRAS mutation (p=0.007) were significantly associated with more brain metastasis. The predictive model based on nodal (N) stage, patient age, LKB1 CN and KRAS mutation had a good prediction accuracy, with area under the ROC curve of 0.832 (p<0.001). CONCLUSION:LKB1 CN in combination with KRAS mutation predicted brain metastasis in NSCLC.
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