OTHR-11 - Marina Kazarian.mp4
Comprehensive Analysis of Driver Mutation Profile in a Cohort of Lung Cancer Patients Using Targeted Gene Panel Analysis with Focus on Brain Metastatic Disease
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Marina Kazarian, Jin Cui, Irena Tocino, Amit Mahajan, Mariam Aboian
Yale University, New Haven, CT, USA
Purpose: Approximately 228,820 people are diagnosed annually with lung cancer diagnosis and 135,720 die from their disease1. EGFR and KRAS targeted therapies have been shown to significantly improve treatment of non-small cell lung cancer (NSCLC), but they don’t apply to the majority of patients. There’s a critical need to characterize the molecular signature of patients with lung cancer and to define the proportion of patients eligible for novel targeted therapies.
Methods: IRB approval was obtained to retrospectively extract data from tertiary hospital tumor registry from 2011 to 2017. Data collected included patient demographics, targeted next generation sequencing results (50 and 150 gene panel), histology, and biopsy location in the final 2,203 patients, 715 of which were manually checked.
Findings: 83.8% of patients in the lung cancer cohort that had targeted next-generation gene panel analysis demonstrated presence of at least one mutation. 50.9% of the patients in our cohort had a targetable mutation. There were 9.5% with hypermutated phenotype characterized as at least 5 mutations per sample. 1.3% of patients had at least 10 mutations per sample. We also characterize the distribution of mutations within brain metastatic lesions and demonstrate that brain metastases with hypermutated phenotype demonstrate larger volumes of edema and greater involvement of deep white matter than non-hypermutated brain metastases.
Conclusion: We present a comprehensive analysis of the molecular signature of lung cancer from a tertiary referral institution with focused analysis of brain metastases. Lung cancer brain metastases with greater than 5 mutations correspond to greater volume of edema and involvement of deep white matter.
Contact Presenter
Marina Kazarian, Jin Cui, Irena Tocino, Amit Mahajan, Mariam Aboian
Yale University, New Haven, CT, USA
Purpose: Approximately 228,820 people are diagnosed annually with lung cancer diagnosis and 135,720 die from their disease1. EGFR and KRAS targeted therapies have been shown to significantly improve treatment of non-small cell lung cancer (NSCLC), but they don’t apply to the majority of patients. There’s a critical need to characterize the molecular signature of patients with lung cancer and to define the proportion of patients eligible for novel targeted therapies.
Methods: IRB approval was obtained to retrospectively extract data from tertiary hospital tumor registry from 2011 to 2017. Data collected included patient demographics, targeted next generation sequencing results (50 and 150 gene panel), histology, and biopsy location in the final 2,203 patients, 715 of which were manually checked.
Findings: 83.8% of patients in the lung cancer cohort that had targeted next-generation gene panel analysis demonstrated presence of at least one mutation. 50.9% of the patients in our cohort had a targetable mutation. There were 9.5% with hypermutated phenotype characterized as at least 5 mutations per sample. 1.3% of patients had at least 10 mutations per sample. We also characterize the distribution of mutations within brain metastatic lesions and demonstrate that brain metastases with hypermutated phenotype demonstrate larger volumes of edema and greater involvement of deep white matter than non-hypermutated brain metastases.
Conclusion: We present a comprehensive analysis of the molecular signature of lung cancer from a tertiary referral institution with focused analysis of brain metastases. Lung cancer brain metastases with greater than 5 mutations correspond to greater volume of edema and involvement of deep white matter.