GLORIA

GEOMAR Library Ocean Research Information Access

X

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
Filter
  • American Society of Clinical Oncology (ASCO)  (2)
  • 1
    Online Resource
    Online Resource
    Non-small cell lung cancer: Analysis using mass cytometry and next generation sequencing reveals new opportunities for the development of personalized therapies.
    American Society of Clinical Oncology (ASCO) ; 2020
    In:  Journal of Clinical Oncology Vol. 38, No. 15_suppl ( 2020-05-20), p. e21026-e21026
    Details
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 38, No. 15_suppl ( 2020-05-20), p. e21026-e21026
    Abstract: e21026 Background: Comprehensive molecular profiling and the use of biomarkers as companion diagnostics have transformed precision medicine for cancer patients. To identify patient-specific tumor microenvironment and biomarker profiles, we assessed the accuracy of our deconvolution algorithm in identifying cellular compositions from whole exome (WES) and whole transcriptome (RNA-seq) sequencing of solid tumors compared with cell populations identified by Mass Cytometry by Time of Flight (CyTOF) in surgically resected tissue from non-small cell lung cancer (NSCLC) patients. Methods: Resected NSCLC tissue was divided for RNA-seq and WES of whole tissue (n = 9) and for generating tissue single cell suspensions through mechanical dissociation and enzymatic digestion (n = 11). Bulk RNA-seq and CyTOF were performed on all cell suspensions. Cellular phenotypes were identified using clustering algorithms in CyTOF and predicted from bulk RNA-seq using our proprietary computational method. Results: Cellular composition reconstructed from RNA-seq correlated with the composition detected by CyTOF (R 2 = 0.922, n = 7) from cell suspensions. To recover the cell percentage from bulk RNA-seq, a machine learning framework was trained on the cell compendia comprising 7,117 unique cell type RNA-seq profiles. A two-stage hierarchical learning procedure generated a gradient boosting Light GBM model that included training on artificial RNA-seq mixtures of different cell types. With this method, we found that stromal and malignant cells were depleted during single cell suspension preparation, resulting in statistically significant differences in the tumor cell composition reconstructed from solid tissue and single cell suspensions. Immune cell types namely T cells and macrophages were similarly represented in both the bulk tumor tissue and matched single cell suspensions. Transcriptomics revealed a subgroup of patients whose tumors were B-cell-enriched, which was validated in other NSCLC cohorts and was associated with greater CD4+ and CD8+ T cell infiltration and improved clinical outcomes. Conclusions: Since preparation of single cell suspensions leads to the loss of several cellular components, RNA-seq of tumor bulk tissue better describes the molecular and cellular properties of the tumor microenvironment. The combination of RNA-seq and WES of tumor tissue provides a comprehensive profile of cellular composition, suggesting that this combination is ideal for precision medicine applications.
    Type of Medium: Online Resource
    ISSN: 0732-183X , 1527-7755
    URL: Article
    DOI: 10.1200/JCO.2020.38.15_suppl.e21026
    RVK:
    XA 52760
    RVK:
    XA 10000
    Language: English
    Publisher: American Society of Clinical Oncology (ASCO)
    Publication Date: 2020
    detail.hit.zdb_id: 2005181-5
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 2
    Online Resource
    Online Resource
    Immune functional portraits of head and neck cancer using next generation sequencing.
    American Society of Clinical Oncology (ASCO) ; 2020
    In:  Journal of Clinical Oncology Vol. 38, No. 15_suppl ( 2020-05-20), p. 6561-6561
    Details
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 38, No. 15_suppl ( 2020-05-20), p. 6561-6561
    Abstract: 6561 Background: The addition of biomarkers as companion diagnostics and Next Generation Sequencing (NGS) have dramatically increased therapeutic efficacy and have aided precision medicine development. The unique genomic profile and tumor microenvironment (TME) composition of each patient can be ascertained through NGS. Using TCGA and Geo datasets, we characterized head and neck cancers (HNC) according to the cellular and functional state of their TME and conducted a pilot validation study using prospectively collected HNC tumors. Methods: To stratify the TME of HNC tumors into molecular functional portraits, we analyzed the sequencing data of 1,486 HNC tumor samples and 143 controls (normal, oral leukoplakia) from TCGA and GEO data sets. For the prospective pilot study, resected tissue from oropharyngeal carcinomas independent of HPV status were processed for whole exome (WES) and RNA-seq (n = 6; HPV-positive = 1). Results: To characterize the cellular composition and functional state of HNC tumors and their TMEs, we created 26 separate molecular signatures related to functional processes such as immune checkpoint inhibition, immune infiltration, immunosuppression, and stromal activities represented by angiogenesis and mesenchymal stromal cells. Unsupervised clustering of these signatures delineated tumors into 4 types: immune infiltration with increased stromal signatures (type A), immune infiltration with decreased stromal signatures (type B), no immune infiltration with increased stromal signature (type C), and no immune infiltration and decreased stromal signatures (type D). Most HPV-positive tumors were type B (p = 1e-27) and associated with increased survival compared to the HPV-negative tumors (types C and D; p = 3e-05). Type B HPV-positive tumors had reduced FAT1 and TP53 mutations, whereas type B HPV-negative tumors had increased caspase 8 mutations/loss. In the validation cohort, actionable mutations were found in PI3KCA and TSC2 in types A and B HPV-negative tumors. Moreover, while the HPV-positive tumor was classified as type C, we identified a caspase 8 homozygous deletion and absence of FAT1 and TP53 mutations, supporting the TCGA and GEO analysis. Conclusions: Exome and transcriptome analyses with cellular deconvolution from bulk RNA-seq enrich tumor characterization by including major TME components, providing a comprehensive biomarker profile for precision therapy and clinical decision making. Our prospective analysis identified TME parameters comparable with the large datasets and revealed targetable genomic alterations.
    Type of Medium: Online Resource
    ISSN: 0732-183X , 1527-7755
    URL: Article
    DOI: 10.1200/JCO.2020.38.15_suppl.6561
    RVK:
    XA 52760
    RVK:
    XA 10000
    Language: English
    Publisher: American Society of Clinical Oncology (ASCO)
    Publication Date: 2020
    detail.hit.zdb_id: 2005181-5
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...