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Lise Mangiante
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OA09 - Mesothelioma from Pathogenesis to Therapy (ID 132)
- Event: WCLC 2020
- Type: Oral
- Track: Mesothelioma, Thymoma and Other Thoracic Malignancies
- Presentations: 1
- Moderators:
- Coordinates: 1/30/2021, 15:30 - 16:30, Scientific Program Auditorium
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OA09.03 - MESOMICS Project: Molecular Characterization of Malignant Pleural Mesothelioma Using a Multi-Omic Approach (ID 2235)
15:30 - 16:30 | Presenting Author(s): Lise Mangiante
- Abstract
- Presentation
Introduction
The MESOMICS project for the multi-omic characterization of Malignant Pleural Mesothelioma (MPM) belongs to the Rare Cancers Genomics initiative (www.rarecancersgenomics.com) aiming at providing a better understanding of the molecular characteristics of rare cancers, such as MPM. Taking advantage of the expertise provided by a multidisciplinary team, and by means of state-of-the-art computational analyses as well as exceptional bio-repositories, our research is focused on: (1) identifying the molecular characteristics that may inform the carcinogenesis and aetiology of MPM; (2) providing the necessary data to generate a more clinically relevant classification of tumours; and (3) improving clinical management by identifying and validating novel candidate diagnostic, prognostic, and predictive biomarkers.
Methods
We have generated whole-genome sequencing, RNA sequencing data, and EPIC 850k methylation arrays data for 124 MPM of the three main histological types (epithelioid, sarcomatoid, and biphasic) and subtypes (epithelioid morphological subtypes). In addition, we have generated multi-regional multi-omic data for 12 of the MPM epithelioid samples. We have performed in-depth characterization of genomes (single nucleotide variants, indels, copy number variants, and structural variants), transcriptomes (genes, transcripts, and fusion genes), and methylomes (methylation levels), as well as integrative analyses of the three 'omic layers, including unsupervised molecular classifications and supervised analyses of molecular subtypes.
Results
Analyses of whole-genome sequencing data for our series of 124 MPM samples uncovered frequent genomic rearrangements affecting, among others, BAP1 (Mangiante et al. In preparation). This suggests that BAP1 inactivation might be more frequent than initially estimated based on published whole-exome sequencing data (Bueno et al. Nat Genet 2016; TCGA Cancer Discov 2019). We also provide the first continuous integrative multi-omic classification of MPM, extending the continuous classifications recently proposed using expression data (Alcala et al. Ebiomedicine 2019; Blum et al. Nat Commun 2019); this classification reveals novel, specific copy number and methylation profiles associated with expression profiles and histological types. In addition, leveraging the information from whole-genome sequencing data, we provide the first large scale assessment of mutational signatures in MPM. We also perform the first fine-scale reconstruction of tumor evolution in MPM, shedding light into the events occurring during the long latency period of the disease by revealing the timing of alterations in MPM, and showing that histological type, survival, and molecular profiles are associated with the strength of natural selection acting on hallmarks of cancer genes. Finally, multi-omic integrative analyses of multi-region samples from 12 MPMs detected significant intra-tumour heterogeneity in the expression of immune checkpoints and pro-angiogenic genes, providing some biological insight on the modest and variable response to immunotherapy and anti-angiogenic drugs, respectively, observed in recent clinical trials.
Conclusion
Considerable progress has been made in recent years in the molecular characterization of MPM. However, the assumptions made in the analyses of the data and the limited whole-genome sequencing data generated have hampered the discovery of important findings for the clinical management of MPM. The MESOMICS project aims to fill these gaps to provide the missing pieces needed to tackle this aggressive disease.
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P47 - Small Cell Lung Cancer/NET - Biology / Translational (ID 234)
- Event: WCLC 2020
- Type: Posters
- Track: Small Cell Lung Cancer/NET
- Presentations: 1
- Moderators:
- Coordinates: 1/28/2021, 00:00 - 00:00, ePoster Hall
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P47.03 - Understanding Lung Neuroendocrine Tumor Progression Combining Organoid Models and Multi-Omic Analyses (ID 2449)
00:00 - 00:00 | Author(s): Lise Mangiante
- Abstract
Introduction
We have recently identified a novel subtype of lung neuroendocrine tumors (LNET)--supra-carcinoids--that has the histopathological features of low-grade pulmonary carcinoids but the molecular profile and prognosis of the deadly large-cell neuroendocrine carcinoma (LCNEC; Alcala et al. Nat Commun 2019). However, how such entities acquire high-grade molecular features starting from low-grade cell features remains a mystery. Patient-derived organoids (PDOs)--in vitro models that represent the three-dimensional organization of tissues--provide a unique opportunity to model mechanistically the progression of tumors (Drost and Clevers Nat Rev Cancer 2018). Nevertheless, PDOs have currently been developed only for a handful of neoplasms, and such models for rare tumors such as LNET are lacking.
Methods
The Clevers’ lab is currently generating a living biobank of PDOs, including neuroendocrine neoplasms (NEN) and the very first NET PDOs. We are collaborating with them in testing whether these PDOs faithfully represent their associated primary tumors at the molecular level. For this, whole-genome and RNA sequencing are being performed on the original tumors plus on the organoids at multiple passages of the experiment (2 or 3 time-points), for 9 LNEN (5 grade 1, 1 grade 2, and 3 grade 3 neoplasms), 1 pancreatic NEN, and 4 small intestine NET, resulting in 34 whole-genomes and 28 RNA-seq.
Results
Genomic analyses of PDOs along with their matched primary tumors show that PDOs maintain the genomic makeup of the primary tumor. The intratumor heterogeneity of the primary tumor is maintained, with remarkably stable levels of genetic diversity through time, although analyses of mutational signatures show that PDOs can experience different mutational processes than the primary tumor. In addition, analyses of the evolutionary trajectory of PDOs show that most of the clonal structure of PDOs is conserved in late passage PDOs. Using PDO transcriptomes and leveraging the molecular profiles of lung NEN that we have recently identified as reference (Alcala et al. Nat Commun 2019; Fernandez-Cuesta and Foll Transl Lung Cancer Res 2019; recently summarized in Gabriel et al. GigaScience In Press), we further show that PDOs express neuroendocrine markers within the range of what is observed in primary tumors of lung NEN, and that they have temporally stable expression profiles.
Conclusion
Integrative multi-omic analyses show that PDOs provide faithful novel preclinical in vitro models for the study of NE biology and disease, and will provide the necessary tools to study tumor progression from low- to high-grade.
