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Simon D Spivack



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    MA04 - Models and Biomarkers (ID 122)

    • Event: WCLC 2019
    • Type: Mini Oral Session
    • Track: Biology
    • Presentations: 1
    • Now Available
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      MA04.06 - Lung Epithelium Whole Transcriptome Signatures That Reflect Incident Lung Cancer Case-Control Status (Now Available) (ID 2526)

      13:30 - 15:00  |  Presenting Author(s): Simon D Spivack

      • Abstract
      • Presentation
      • Slides

      Background

      BACKGROUND: Focusing early detection and prevention efforts on those at high risk for lung cancer is central to leveraging such strategies. Notably, that risk persists even after removal of a lung cancer, as reflected in lung recurrences, which are common, and usually occur remote from the surgical removal site. This implies risk for future incident lung cancer is represented in the biology of broad areas of lung epithelium, before, during, and after diagnosis. Given that somatic mutations in the bronchial tree are known to persist for decades, there is a suggestion that smoking transforms the entire epithelium at several somatic and gene regulatory levels. We hypothesize that the normal lung epithelium contains expression and epigenetic epithelial signatures that are representative of donor case-control status, that is poised for carcinogenesis.

      Method

      METHODS: As a first step, in order to identify differentially expressed genes (DEGs) associated with aging, smoking and cancer case-control status, we analyzed RNA-seq transcriptome data of laser capture microdissected (LCM) bronchial and alveolar epithelium separately, in paired tissue sets of 40- and 74 respective individuals, summarized here. Read count was the main normalization variable. We also measured differentially methylated sites (DME) by whole genome bisulfite genome sequencing (WGBSeq), covering >60% of the genome/methylome [as of this deadline, these methylome data are not yet fully analyzed].

      Result

      RESULTS: Mean subject age for 77 total subjects was 65 (+/-9.9), 19% current-, 76% former, 5% never smokers. For each cell type, we modeled gene expression level as a result of aging, gender, smoking and case-control status. We put all four clinical variables age, gender, smoking status, case-control status) along with cell type (alveolar/bronchial) into the model, to avoid potential confounding effects. We discovered 175 DEGs discriminating case-control status (FDR p<0.05) in alveolar and bronchial cells combined, and 420 case-control DEGs with bronchial cells alone. Bronchial cells displayed 31 DEGs discriminating current versus former smokers (FDR-adjusted P<0.05). Gene ontology (David) clusters for case-control discrimination in these “normal” bronchial epithelia included energetics pathways (GO 0042776/0006754; ATP biosynthesis) as well as transcriptional and translational regulation pathways; KEGG clusters also included oxidative phosphorylation pathways (hsa00190), among others.

      Conclusion

      CONCLUSION: There is a donor case-control discriminant expression signature for human lung bronchial captured cells, emphasizing bioenergetically-deranged metabolic pathways, among others. If confirmed in larger studies that measure deranged metabolites directly, metabolomics biomarkers representing bioenergetics and other pathways may serve to define those individuals whose epithelia is tilted toward carcinogenesis, and therefore are at increased risk for lung cancer.

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    P1.11 - Screening and Early Detection (ID 177)

    • Event: WCLC 2019
    • Type: Poster Viewing in the Exhibit Hall
    • Track: Screening and Early Detection
    • Presentations: 1
    • Moderators:
    • Coordinates: 9/08/2019, 09:45 - 18:00, Exhibit Hall
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      P1.11-11 - Initial Discovery of Exhaled Small Polar Energetics-Related Metabolites by GC-MS for Lung Cancer Risk Assessment (ID 2418)

      09:45 - 18:00  |  Presenting Author(s): Simon D Spivack

      • Abstract
      • Slides

      Background

      Background: There is a need for non-invasive airway-based biomarkers in lung carcinogenesis for both risk assessment, and earlier diagnosis. Exhaled breath condensate (EBC) contains airway lining fluid molecules, including small molecules of polar and non-polar lipid origin, presumably in part from epithelial cellular origins. Here we pilot a GC-MS strategy for measurement of small, polar molecules in exhaled breath condensate in EBC from lung cancer patients and controls.

      Method

      Methods: Exhaled breath condensate (EBC) was collected non-invasively, using a handheld device (RTube) in ambulatory subjects engaged/recruited/consented through our pulmonary and thoracic surgery practices, under IRB protocol. A volume of 50 ul of EBC samples were combined with 200uL of methanol, containing 2 internal standards, 1nmol U13_succinate, 5nmol U13_citrate. Then, the samples were vortexed and 240 µl of supernatant was transferred to a sampling vial. The samples were dried under gentle nitrogen flow and derivatized with a two-step derivatization procedure, including a methoxyamine step for 90 minutes, and a silylation step for 60 minutes. QC sample was run multiple times during the analysis. The samples were analyzed by gas chromatography time-of-flight mass spectrometry (GC-TOFMS premier, Waters, USA).

      Result

      Results: A number of 282 variables were detected after alignment and excluding any known artificial peaks, 49 of them were annotated. The data was normalized to the intensity of the sum of all the metabolites. The data set was then imported into SIMCA-p software (Umeå, Sweden) for multivariate analysis. A multivariate case-control ROC discriminant analysis compared the clinical model (AUC 0.72) to clinical plus exhaled small polar discriminant metabolites combined (AUC 0.92), showed incremental discrimination attributable to these metabolites (p=2.22e-62).

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      ROC comparing clinical model (AUC 0.72) to clinical model plus metabolites (AUC 0.92); the difference attributable to metabolites was significant (p=2.22e-62).

      Conclusion

      Conclusion: This exhaled biomarker platform can yield case-control discriminant small polar molecule sets related to known metabolic pathways, some of which are known to be deranged in cancers. Once further distilled and validated, our goal is to apply this non-invasive biomarker approach to prospective cohorts for non-invasive lung cancer risk assessment of the at-risk epithelium, in order to better select higher risk individuals to undergo effective CT screening.

      Supported by NIH-R21 CA192168-01; DoD-CDMRP- LC150738, NIH-NCI P60DK020541.

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