23rd Human Proteome Organization World Congress

Elucidation of tumor cellular interactions using high-throughput proteomics

Professor

Keynote speaker

Keynote lecture

Proteomic characterisation of rare quiescent therapy-resistant cancer cells

Cell Biology Insights

Many cancers are characterised by the presence of a rare subpopulation of quiescent stem-like cells which are a source of heterogeneity, phenotypic therapy resistance, relapse and further disease evolution. These cells are able to evade cytotoxic chemotherapy, which selectively targets proliferating cells, thus representing a major therapeutic challenge. The mechanisms controlling quiescence remain largely unknown, and transcriptomic analysis of quiescent cells has yielded only limited insights. Proteomic analysis of rare cancer stem cells requires the development of a low-input methodology in order to capture global protein changes and differentially expressed post-translational modifications. To identify and isolate rare quiescent cells, we generated and validated a fluorescent label-retaining in vitro model using patient-derived glioblastoma cell lines and used somatic mouse models with the same inducible reporter. Using these model systems, we have demonstrated the presence of a pre-existing quiescent population and shown that these cells exhibit self-renewal capacity and increased therapy resistance. We have developed a robust proteomic workflow for analysing rare FACS-sorted cells, using multiplexed isobaric labelling and phosphopeptide enrichment. This method enables the processing of protein loads down to the low-microgram/sub-microgram level to identify signalling networks that govern quiescence. Our findings indicate that the quiescent proteome is conserved across models of glioblastoma, regardless of driver mutations. Network modelling with causal integration of multi-omic data has led to the identification of potential mechanisms of resistance and targetable vulnerabilities. Functional assays indicate PML as a potential therapeutic target for overcoming quiescence mediated therapy resistance in glioblastoma. We propose extracellular interferon signalling initiates upregulation of PML leading to suppression of mTORC1-mediated translation and ultimately entry to cellular quiescence. By bridging the gap in knowledge between transcriptomic regulation and protein-driven phenotypes, we aim to contribute to the understanding of phenotypic therapy resistance and provide new strategies for modulating quiescence.

Oral presentation

Prof

A proteomic atlas of the human monocytic compartment

Monocytes (Mo) and macrophages (MAC) are key players in tissue-cleaning processes during body homeostasis and response to stressors (e.g. infection, cancer). Mo derive from precursor cells in the bone marrow (BM) and differentiate into MAC after leaving the bloodstream and entering tissues. Despite the existing knowledge about these cells, their plasticity, functional heterogeneity, and the discovery of new subsets, currently hamper the definition of their exact maturational relationship.To address this, we combined single cell-based mass cytometry (CyTOF) and bulk mass spectrometry (MS)-based proteomics approaches to define the proteome and maturational relationship of monocytic cells across tissues (BM, peripheral blood (PB), skin, peritoneal dialysate (PD) and colon). Firstly, &gt;100 proteins were screened to design a 35-marker CyTOF panel to evaluate &gt;15 Mo/MAC populations. Based on this data, we purified 5 (pro)monocyte subsets from BM (n=4-5, from 9 donors), 8 monocytic subsets from PB (n=2-5, from 7 donors), and MAC from skin (n=4, from 7 donors), PD (n=3, from 6 donors) and colon (n=5, from 7 donors) samples, for TMT-based MS.Based on population relationships, as defined using single-cell trajectory analysis, 11 distinct protein expression patterns were observed during maturation in BM, reflecting diverse functions (e.g. metabolism, signalling, lysosome assembly, antigen presentation) at different stages of differentiation. Analysis of PB subsets suggested a close relationship between CD62L- FcεRI- classical Mo (cMo), intermediate Mo (iMo) and CD36+ Slan- non-classical Mo (ncMo) subsets, with iMo acting as a bridge between cMo and ncMo. Within ncMo subpopulations, a distinct functional profile distinguished Slan- cells, primarily involved in metabolic and protein production processes, from CD36- subsets, showing a stronger commitment to protein production and vesicle transport. Regarding MAC, a common core functional identity signature encompassing 425 functions (79.6% of all MAC functions) was identified across all tissues. A microenvironment effect was also observed, as colon MAC exhibited distinctive TOR and TLR signalling pathways, skin MAC expressed proteins involved in cellular responses to gamma radiation, and PD MAC reflected processes like immunological synapse formation. Notably, when compared to Mo, CD62L+ FcεRI- cMo from PB displayed the closest resemblance to the general MAC signature, despite differences in their immune profiles. While MAC were prominently involved in antiviral responses, the cMo subset played a main role in T-cell activation, receptor signalling, cytokine production and antigen processing and presentation processes.In conclusion, by integrating CyTOF and MS-based proteomics approaches, we provide a detailed proteome atlas of monocytes and MAC across tissues, shedding light on the complex maturational relationships and functional heterogeneity of these cells.

Developing a miniturboid mass spectrometry-based method for characterizing aggregate proteomics in metabolically distressed cells

Protein aggresomes are a hallmark of impaired proteostasis, but the assembly and detailed cellular function of this biomolecular condensate remain largely unknown. Until recently, systematic methods for identifying aggresome proteins were either unavailable or incomplete. Past efforts including centrifugation or gel filtration could fractionate aggregate proteins in vitro, but they fail to capture proteins in situ or in vivo. To address this limitation, we introduce AggresomeID as a novel approach for screening aggresome proteins in live cells. Autophagy adaptor protein sequestome1 (SQSTM1) is visibly enriched in aggresomes in response to various pathophysiological stresses. Here, we genetically fused human SQSTM1 with the biotin ligase miniTurboID to create a recombinant protein (an aggresome sensor). With this fusion construct, we engineered a stable HEK293 cell line. Fluorescent microscopy showed that aggresome sensors were cytosolic in DMSO-treated cells but coalesced with the aggresome markers ubiquitin and HDAC6 following 2 µM MG132 (a proteasome inhibitor) treatment for 18 hours. Proximity-based biotinylation of aggresome proteins was enriched using immobilized streptavidin followed by SAINT bioinformatics. SAINT analyses identified over 250 proteins that were significantly enriched in aggresomes (Log2 enrichment &gt; 2 between the groups, MG-132/DMSO; Bayesian false discovery rate cut-off &lt; 1%). Interestingly, several clusters of these enriched proteins appear to be functionally relevant for protein degradation, including autophagy receptors (NDP52, TAX1BP1, TOLLIP, and NBR1), autophagosome biogenesis and assembly (ATG7, ATG101), proteasome 20s subunits (PSMA1, PSMA5, PSMB1, PSMB2), and valosin-containing protein complex subunits (VCP/p97, UFD1, UBXD1). We also confirmed the enrichment of these proteins in aggresomes by flag-tagged fusion constructs expressed in cells, with MG132 treatment followed by confocal microscopy and immunoblots. Ongoing work include building a AggresomeID toolkit in this model system, as well as explore additional cell types. In conclusion, our study is the first report to address the technical limitation in studying aggresome proteomics and our approach enables the continuous monitoring of aggresome proteomics in live cells. Ongoing studies will focus on the characterization of aggresome subtypes in different lines of cells following pathological stresses (e.g., heat shock, oxidative stress, and proteasome inhibition) and establish a timeline (and possibly mechanisms) through which candidate proteins participate in aggresome biogenesis.

Plenary hall

Session

Proteomics in cell biology

Session
Proteomics in cell biology

Termin

Vorsitzende

Programm

SessionProteomics in cell biology

Termin

Vorsitzende

Programm

Session
Proteomics in cell biology