Data · dataset · 2026
From pathogenesis to therapy: understanding molecular drivers and novel treatments in mastocytosis and myeloproliferative neoplasms
Listed in ZivaHub and Deakin Research Online and DMU Figshare — shown once because both records carry DOI 10.17034/32805854.v1
Myeloproliferative neoplasms (MPNs) and systemic mastocytosis (SM) are clonal haematological disorders that originate from dysregulated haematopoietic stem cells within the bone marrow (BM).
Description
Both disorders are characterised by activating kinase mutations, <i>JAK2 V617F</i> in MPNs and <i>KIT D816V</i> in SM, and aberrant activation of these tyrosine kinases drives constitutive proliferative signalling. Persistence and suboptimal response to targeted therapies remain major clinical challenges in Philadelphia-negative MPNs.
Although Janus kinase (JAK) inhibitors such as ruxolitinib (RUX) represent standard-of-care treatment for advanced MPNs, they do not fully eradicate mutant clones, prevent disease progression or reliably overcome acquired persistence. Similarly, therapeutic strategies in SM predominantly target KIT mutations, yet alternative signalling pathways may drive disease maintenance and progression. This study aimed to identify treatment-responsive signalling pathways and alternative therapeutic vulnerabilities in MPN and SM using integrated proteomic approaches.
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In MPN models, a proteasome inhibitor showed strong anti-proliferative activity. Proteosome inhibition combined with RUX showed synergistic activity and reduced the effective IC50 of RUX, supporting dual targeting as a means to enhance efficacy. A RUX-persistent essential thrombocythaemia (ET) model was generated to reflect reduced responsiveness after prolonged exposure, and persistent cells retained proteosome sensitivity similar to RUX-naïve cells.
To capture early adaptation to JAK2 inhibition, bioorthogonal non-canonical amino acid tagging (BONCAT) was implemented for the first time in an MPN cell model, enabling selective enrichment of newly synthesised proteins. Functional enrichment analysis showed time-dependent protein remodelling, with early suppression of immune-associated proteins followed by later enrichment of apoptotic and immune processes at 24 hours, providing a temporal framework for early adaptation to JAK inhibition.
In SM, global plasma proteomics identified CXCL7, LBP, TGFβ1 and PDGFRβ as candidate biomarkers. Proteomic profiling was extended to SM BM, generating a high-resolution digital proteomic map and highlighting dysregulated immune signalling. In human mast cell models, proteosome inhibition induced proteomic signatures of stress responses and apoptosis.
Overall, this work defines early proteomic responses to JAK2 inhibition and supports proteasome inhibition as a shared therapeutic vulnerability across MPN and SM models, providing a rationale for combination and pathway-diversified strategies beyond current kinase-directed therapy.<br><br><i>Thesis is embargoed until 31 July 2031</i>.<br>
Links
Where it is published
- DOI doi.org/10.17034/32805854.v1 ↗
DOI / persistent id · from zivahub uct ac za
Catalogue records · 1
- OAI-PMH record api.figshare.com/v2/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Af… ↗
metadata API · from zivahub uct ac za
Topics
- From keywords
- Earth & Environmental Science · Earth & Environmental Science · Earth & Environmental Science · Mass spectrometry · Mass spectrometry · Mass spectrometry
- Inferred from text
- Disease 75%
Provenance · 3 source records, 12 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ZivaHub | oai:figshare.com:article/32805854 | 11 d ago | JSON v1 |
| Deakin Research Online | oai:figshare.com:article/32805854 | 11 d ago | JSON v1 |
| DMU Figshare | oai:figshare.com:article/32805854 | 11 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| concepts[disease].local:disease:disease | enrichment · zivahub uct ac za | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[field].local:field:earth-environmental | mapping · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · figshare dmu ac uk | connector:figshare_dmu_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · dro deakin edu au | connector:dro_deakin_edu_au@1.0.0 | |
| concepts[modality].local:modality:mass-spectrometry | mapping · zivahub uct ac za | vocabulary-mapper@1.0.0 | keywords['proteomics'] |
| concepts[modality].local:modality:mass-spectrometry | mapping · dro deakin edu au | vocabulary-mapper@1.0.0 | keywords['proteomics'] |
| concepts[modality].local:modality:mass-spectrometry | mapping · figshare dmu ac uk | vocabulary-mapper@1.0.0 | keywords['proteomics'] |
| description | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | /metadata/dc/description |
| license_text | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| publication_date | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| title | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | /metadata/dc/title |