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Lise Mangiante



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    MA12 - New Frontiers from Pathology to Genomics (ID 138)

    • Event: WCLC 2019
    • Type: Mini Oral Session
    • Track: Mesothelioma
    • Presentations: 1
    • Now Available
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      MA12.01 - Redefining Malignant Pleural Mesothelioma Types as a Continuum Uncovers Immune-Vascular Interactions (Now Available) (ID 1773)

      14:00 - 15:30  |  Author(s): Lise Mangiante

      • Abstract
      • Presentation
      • Slides

      Background

      Malignant Pleural Mesothelioma (MPM) is a deadly disease. The current histopathologycal classification recognises three major types (epithelioid, biphasic, and sarcomatoid) with different prognosis, but showes high interobserver variability. This classification also has a role in the clinical decision-making although, ultimately, MPM becomes refractory to all conventional treatment modalities, and alternative therapeutic options have been evaluated with limited success.

      Method

      We have performed unsupervised analyses of publicly available RNA-seq data of 284 MPM tumours1,2 with no assumption of discreteness. We have performed an orthogonal validation in a subset of 187 samples, and we have replicated the findings in an independent series of 77 MPM from the French MESOBANK.

      Result

      A continuum of molecular profiles appeared to explain the prognosis of this disease better than discrete models based on the histopathological classification or on expression data. We identified the immune and vascular pathways as major sources of molecular variation, with strong differences in the expression of immune checkpoints and pro-angiogenic genes across samples; the extrema of this continuum had very specific molecular profiles: a "hot" bad-prognosis profile (median survival of 7 months), with high lymphocyte infiltration, and high expression of immune checkpoints and pro-angiogenic genes; a "cold" bad-prognosis profile (median survival of 10 months), with low lymphocyte infiltration and high expression of pro-angiogenic genes; and a better-prognosis profile (VEGFR2+/VISTA+, median survival of 36 months), with high expression of the immune checkpoint VISTA and the pro-angiogenic VEGFR2 gene. We selected five genes belonging to the immune and vascular pathways (CD8A, PDL1, VEGFR3, VEGFR2, and VISTA), which expression was enough to capture the three molecular profiles, to validate the expression of these genes at the protein level by immunohistochemistry on a subset of 187 samples from the discovery cohort, and to replicate the molecular profiles as well as their prognostic value in an independent series of 77 MPMs.

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      Conclusion

      In this study we found that the prognosis of MPM is best explained by a continuous model, which extremes show characteristic molecular profiles with specific expression patterns of genes involved in the angiogenesis and immune response3. These data may inform future classifications of MPM and provides insights that may assist the clinical management of this disease.

      1Bueno et al., Nat Genet 2016; 2Hmeljak et al., Cancer Discov 2018; 3Alcala et al., under review in Cancer Res; NA and LM equally contributed to this work; MF, FGS, and LFC jointly supervised this work

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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): Lise Mangiante

      • 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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