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Aurélie Gabriel



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    OA08 - Advanced Models and "Omics" for Therapeutic Development (ID 133)

    • Event: WCLC 2019
    • Type: Oral Session
    • Track: Biology
    • Presentations: 1
    • Now Available
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      OA08.02 - A Multidisciplinary Multi-Omics Study of Spatial and Temporal Tumor Evolution in Thoracic Cancers with Clinical Implications (Now Available) (ID 2365)

      11:00 - 12:30  |  Author(s): Aurélie Gabriel

      • Abstract
      • Presentation
      • Slides

      Background

      In the context of the MESOMICS and lungNENomics projects1, we generated comprehensive molecular profiles of Malignant Pleural Mesothelioma (MPM)2 and pulmonary carcinoids (PCa)3. We showed that a continuous molecular model can better explain the prognosis of MPM than the three histologies, with strong differences in the expression of immune checkpoints and pro-angiogenic genes across samples. We also identified a new entity of PCa (supra-carcinoids) with carcinoid-like morphology yet the molecular and clinical features of LCNEC, which challenges the general believe that PCa have no relationship or genetic, epidemiologic, and clinical traits in common with LCNEC and SCLC. These two studies suggest an important role of heterogeneity in the biology of these tumors.

      Method

      Much progress has been made in revealing the evolutionary history of individual cancers, in particular using multi-region sequencing. However, most studies focused on a single ‘omic technique, and lacked temporal samples. Here we present the results of an innovative approach to study spatial and temporal tumor evolution based on (i) integration of whole-genome and transcriptome sequencing and EPIC 850K methylation arrays on multiple regions from 12 MPM, and (ii) a novel tumor-derived organoid-based strategy for studying the evolution of PCa.

      mesomics_example.png

      Figure 1. Multi-omic multi-regional profiling of a MPM patient. A) Somatic Copy Number Variants (CNV), somatic Structural Variants (SV), kernel density plots of (top) somatic single nucleotide variants (SNVs) allelic fractions, (middle) expression normalized read counts, and (bottom) methylation array M-values. B) Projection of the transcriptomic profile of two tumoral regions into the Principal Component Analysis (PCA) space computed from 284 malignant pleural mesotheliomas2C) Expression (z-score of normalized read counts) for two clinically relevant genes with substantial inter-regional differences.

      Biorepositories: French MESOBANK; LungNEN Network

      Result

      In the data analyses of the 12 MPM we detected significant intra-tumor heterogeneity (ITH) in the expression of immune checkpoints and pro-angiogenic genes (see example in Fig. 1). This might explain the modest and variable response to treatment in clinical trials assessing immunotherapies and antiangiogenic drugs. In the case of PCa, we are currently analysing the organoids genomic data and we will present the preliminary data for the temporal evolution of these diseases.

      Conclusion

      We found that our approach can detect clinically and biologically meaningful ITH. All the computational methods we developed for these evolutionary studies are available to the scientific community4.

      1RareCancersGenomics.com
      2Alcala et al., under review in Cancer Res
      3Alcala et al., under review in Nat Commun
      4https://github.com/IARCbioinfo

      LFC and MF co-supervised this work

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