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Somatic mutation variant analysis in rural, resectable non‐small cell lung carcinoma patients

  • Jonathan B. Mitchem
    Correspondence
    Corresponding authors at: Department of Surgery, University of Missouri, 1 Hospital Dr., Columbia, MO 65212, USA.
    Affiliations
    Department of Surgery, School of Medicine, University of Missouri, Columbia, MO, USA

    Harry S. Truman Memorial Veterans’ Hospital, Columbia, MO, USA

    Institute for Data Science and Informatics, University of Missouri, Columbia, MO, USA

    Center for Biomedical Informatics, University of Missouri School of Medicine, Columbia, MO, USA

    Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO, USA
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  • Amanda Miller
    Affiliations
    Center for Biomedical Informatics, University of Missouri School of Medicine, Columbia, MO, USA
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  • Yariswamy Manjunath
    Affiliations
    Department of Surgery, School of Medicine, University of Missouri, Columbia, MO, USA

    Harry S. Truman Memorial Veterans’ Hospital, Columbia, MO, USA
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  • Mouadh Barbirou
    Affiliations
    Center for Biomedical Informatics, University of Missouri School of Medicine, Columbia, MO, USA
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  • Murugesan Raju
    Affiliations
    Institute for Data Science and Informatics, University of Missouri, Columbia, MO, USA
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  • Yuanyuan Shen
    Affiliations
    Institute for Data Science and Informatics, University of Missouri, Columbia, MO, USA
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  • Guangfu Li
    Affiliations
    Department of Surgery, School of Medicine, University of Missouri, Columbia, MO, USA

    Harry S. Truman Memorial Veterans’ Hospital, Columbia, MO, USA
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  • Diego M. Avella
    Affiliations
    Department of Surgery, School of Medicine, University of Missouri, Columbia, MO, USA
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  • Aadel A. Chaudhuri
    Affiliations
    Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO, USA

    Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO, USA
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  • Chi-Ren Shyu
    Affiliations
    Institute for Data Science and Informatics, University of Missouri, Columbia, MO, USA
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  • Wesley C. Warren
    Affiliations
    Department of Surgery, School of Medicine, University of Missouri, Columbia, MO, USA

    Institute for Data Science and Informatics, University of Missouri, Columbia, MO, USA

    Center for Biomedical Informatics, University of Missouri School of Medicine, Columbia, MO, USA
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  • Peter J. Tonellato
    Affiliations
    Center for Biomedical Informatics, University of Missouri School of Medicine, Columbia, MO, USA
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  • Jussuf T. Kaifi
    Correspondence
    Corresponding authors at: Department of Surgery, University of Missouri, 1 Hospital Dr., Columbia, MO 65212, USA.
    Affiliations
    Department of Surgery, School of Medicine, University of Missouri, Columbia, MO, USA

    Harry S. Truman Memorial Veterans’ Hospital, Columbia, MO, USA

    Institute for Data Science and Informatics, University of Missouri, Columbia, MO, USA

    Center for Biomedical Informatics, University of Missouri School of Medicine, Columbia, MO, USA

    Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO, USA
    Search for articles by this author
Published:September 23, 2022DOI:https://doi.org/10.1016/j.cancergen.2022.09.008

      Highlights

      • Rural non-small cell lung cancer (NSCLC) patients have worse survival.
      • Whole exome sequencing reveals similar somatic mutation profile as urban patients.
      • Most common mutations and actionable genes are also observed in rural NSCLC.
      • 24% of patients had variants in actionable genes based on OncoKB annotation.
      • Findings establish foundation for targeted clinical trials in rural NSCLC patients.

      Abstract

      Rural non-small cell lung cancer (NSCLC) patients do worse, largely related to lack of access to care. In this study, the mutational characteristics and potential for targeted therapy in rural, resectable NSCLC patients using whole exome sequencing (WES) were analyzed. WES was performed on tumor-adjacent normal pairs from rural patients undergoing resection for NSCLC. Sequencing alignment, variant-calling, annotation, and tumor mutational burden (TMB) calculations were performed using standard methods. cBioportal and OncoKB were used for comparisons of mutational frequencies and actionable targets. Thirty-four NSCLC patients underwent WES after surgical resection. The gene most frequently containing somatic variants was TP53. The median number of somatic variants was 188 (Range 11–1056), and median TMB was 3.30 (0.33–18.56) nonsynonymous mutations per Mb. Tumor stage and survival were not associated with number of variants, TMB or TP53 mutational status. Significant concordance among the most common mutations when cross-referenced to cBioportal (R = 0.78, p < 0.0001) was observed. 24% of patients had variants in actionable genes based on OncoKB annotation. In summary, we demonstrate baseline mutational frequency and establish foundations for targeted adjuvant trials in rural NSCLC patients with specific differences. Future studies must ensure to include rural patients to improve NSCLC patient outcomes.

      Keywords

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