dc.contributor.advisor | Huang P | |
dc.contributor.author | Pankova, V | |
dc.contributor.editor | Huang, P | |
dc.date.accessioned | 2023-12-08T11:01:07Z | |
dc.date.available | 2023-12-08T11:01:07Z | |
dc.date.issued | 2023-12-08 | |
dc.identifier.citation | 2023 | en_US |
dc.identifier.uri | https://repository.icr.ac.uk/handle/internal/6086 | |
dc.description.abstract | Soft tissue sarcomas (STS) are a rare and diverse group of mesenchymal malignancies that present significant challenges in clinical management due to their extensive clinical and biological heterogeneity. STS have a dismal prognosis, and an incomplete understanding of the underlying biology of these tumours impedes progress in clinical management. Previous research efforts have primarily focused on the molecular characteristics of STS tumour cells, leaving a critical gap in our knowledge regarding the role of the tumour microenvironment (TME), specifically the extracellular matrix (ECM), in STS pathobiology. This thesis aimed to address this knowledge gap by leveraging a recent large-scale proteomic study of STS to comprehensively analyse the composition of the ECM and its associated integrin adhesion signalling across multiple STS subtypes. The findings revealed substantial intra-subtype heterogeneity in matrix signalling among different STS subtypes, such as leiomyosarcoma (LMS), dedifferentiated liposarcoma (DDLPS), and undifferentiated pleomorphic sarcoma (UPS). This matrix signalling heterogeneity was associated with some of the clinical diversity observed within these STS subtypes. Throughout the analysis, the study identified both subtype-agnostic and subtype-specific prognostic biomarkers, shedding light on potential targets for improving clinical outcomes. To address the lack of STS-specific preclinical models of the ECM, the thesis introduced a workflow for generating and characterising patient-derived ECM. Additionally, the analysis uncovered zyxin as a previously unrecognised protein implicated in LMS pathogenesis. In summary, this thesis contributes to our understanding of STS pathobiology by identifying several ECM-related prognostic biomarkers with potential for future development and suggesting putative anti-stroma therapy targets tailored to specific STS subtypes. These insights can potentially guide the development of more effective treatment strategies for STS patients and advance our overall understanding of these complex and heterogeneous malignancies. | |
dc.language.iso | eng | en_US |
dc.publisher | Institute of Cancer Research (University Of London) | en_US |
dc.rights.uri | https://www.rioxx.net/licenses/all-rights-reserved | en_US |
dc.title | Deconstructing the soft tissue sarcoma matrisome and adhesome for drug target and biomarker discovery | en_US |
dc.type | Thesis or Dissertation | |
dcterms.accessRights | Public | |
dc.date.updated | 2023-12-08T11:00:21Z | |
rioxxterms.version | AO | en_US |
rioxxterms.licenseref.uri | https://www.rioxx.net/licenses/all-rights-reserved | en_US |
rioxxterms.licenseref.startdate | 2023-12-08 | |
rioxxterms.type | Thesis | en_US |
pubs.organisational-group | ICR | |
pubs.organisational-group | ICR/Primary Group | |
pubs.organisational-group | ICR/Primary Group/ICR Divisions | |
pubs.organisational-group | ICR/Primary Group/ICR Divisions/Molecular Pathology | |
pubs.organisational-group | ICR/Primary Group/ICR Divisions/Molecular Pathology/Molecular and Systems Oncology | |
pubs.organisational-group | ICR/Students | |
pubs.organisational-group | ICR/Students/PhD and MPhil | |
pubs.organisational-group | ICR/Students/PhD and MPhil/19/20 Starting Cohort | |
icr.researchteam | Mol and Systems Oncology | en_US |
dc.contributor.icrauthor | Pankova, Valeriya | |
uketdterms.institution | Institute of Cancer Research | |
uketdterms.qualificationlevel | Doctoral | |
uketdterms.qualificationname | Ph.D | |
icr.provenance | Deposited by Mr Barry Jenkins (impersonating Dr Valeriya Pankova) on 2023-12-08. Deposit type is initial. No. of files: 1. Files: Valeriya_Pankova_thesis_postcorrections.pdf | |
dc.type.qualificationlevel | Doctoral | |
dc.type.qualificationname | Ph.D | |