Author of

• 17398

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  P2.01 - Poster Session with Presenters Present (ID 461)

  • Event: WCLC 2016
  • Type: Poster Presenters Present
  • Track: Biology/Pathology
  • Presentations: 1
  • Moderators:
  • Coordinates: 12/06/2016, 14:30 - 15:45, Hall B (Poster Area)

  • 17424

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    P2.01-026 - A Mass Spectrometry Based Stem Cell-Oriented Phylogeny of Intra-Tumoral NSCLC Subclones (ID 4385)

    14:30 - 14:30  |  Author(s): E. Seeley
    • Abstract

    Background:
    Sub-clones within a cancer diverge due to ongoing accumulation of mutations. We sought to characterize the intratumor heterogeneity and phylogenetic relationships among different histological patterns present in lung adenocarcinomas based on mass spectrometric analysis of tumor subclones.
    
    Methods:
    MALDI-TOF mass spectrometry was used to generate proteomics data from different histological regions of 35 resected lung tumors, as well as from 3 basal cell and 3 mesenchymal cell samples. A total of 1985 different histological regions were analyzed from the 35 resected tumors along with the 3 samples each of airway basal cells and mesenchymal stem cells. For each of the 1991 samples, a spectral profile was generated with expression data from 217 peptide mass peaks to allow comparison of the proteomics profiles from the different histological regions from each cancer to the basal and mesenchymal stem cell profiles. Weighted protein co-expression networks were analyzed by using WGCNA package in R. Global and histologic specific networks were generated through using a power adjacency function which defines the similarity between any pairs of proteins The network modules were decided by using average linkage hierarchical clustering and a dynamic tree-cut algorithm. Networks of the different histologies and normal were compared and visualized by heat map methods.
    
    Results:
    The clinically more aggressive histologies ( micropapillary/solid) clustered with stem cells and away from normal alveolar tissue (Fig 1) and had severe loss in peptide connectivities (Fig 3). Applying t-SNE dimensionality reduction method showed that subclones from one specimen cluster differently from each other suggesting underlying heterogeneity, with more heterogenous tumors being associated with worse prognosis (Fig 2). Figure 1
    
    
    
    Conclusion:
    Construction of a phylogenetic tree of lung ACA subclones oriented to stem cells demonstrated that the degree of disruption of a subclone correlated with the degree of similarity of the subclone to stem cells, and with prognosis.