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  Regulation of glioblastoma stem cell quiescence


   MRC Centre for Neurodevelopmental Disorders

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  Dr R Sousa-Nunes, Dr Edward Manser  No more applications being accepted  Competition Funded PhD Project (Students Worldwide)

About the Project

Significance

Innovative approaches to tackle glioblastoma multiforme (GBM) are greatly needed. GBM is high-grade (IV) glioma, the most common and aggressive of malignant primary brain tumours. GBM patients have an average of 12-15 months post-diagnosis survival given universal recurrence after standard treatment (surgery followed by concurrent radio-and chemotherapy)1.

GBM is driven by neural stem cell (NSC)-like cells2-4 so a cure requires eradicating them. This is particularly difficult because, unlike NSCs, glioblastoma stem cells (GSCs) exhibit unlimited proliferation and are inflitrative1,5-8; they are also frequently quiescent2-4,9

Quiescence (also known as G0) consists in reversible cell-cycle arrest accompanied by diminished biosynthesis10, which protects cells from replicative exhaustion, proliferation-induced mutations and environmental insults10-12. A consequence of these properties is that quiescent cancer stem cells evade cytostatic therapies and are immunologically quiet10,11,13-18. Quiescent glioblastoma stem cells (qGSCs) in particular have been shown to be therapy-resistant and able to reinitiate GBM2,7.

Novel tactics to wipe out GBM could include: i) driving all GSCs into quiescence; ii) activating GSCs to make them amenable to existing therapies; iii) specifically kill qGSCs (safest). In all cases, we need to understand regulation of GSC quiescence to find ways to perturb it. Challenges include quiescence reversibility, heterogeneity and absence of positive markers. Indeed, quiescence is a continuum of states between near-active (“shallow”) and profound quiescence (dormancy), with depth defined by reactivation speed19-21.

In addition to novel insight into a fundamental biological problem, this work will explore the first positive marker of (GSC) quiescence, refining it to a convenient and robust biomarker. This will then be tested in clinical samples and assessed for prognostic value (beyond the scope of the proposal).

 

Background and preliminary data

Mechanisms governing quiescence are of great clinical relevance but only partially understood18,22,23. We and others have established that inhibition of the Target of Rapamycin pathway is a common denominator of quiescence10,24-26. Recently, we found another evolutionarily conserved mechanism governing this state: altered nucleocytoplasmic partitioning and nuclear retention of polyadenylated (poly(A)) RNA (which mostly comprises mRNA). Although there is less poly(A) RNA in quiescent NSCs (qNSCs) than in active NSCs (aNSCs), we found that levels decrease more in the cytoplasm than in the nucleus. This results in elevated nucleocytoplasmic poly(A) ratio, observed across species and cell types27, including human GSCs. Increased nucleocytoplasmic poly(A) ratio is the first generalisable positive marker of quiescence to be reported and it is therefore very likely that the underlying mechanism we discovered also applies generally.

Subcellular bias of mRNAs has a major impact on directionality of change in protein levels as NSCs shift into quiescence so we anticipate this will be the case also for GSCs. We also hypothesize that differential nucleocytoplasmic partitioning in quiescence will extend to proteins.

The objective of this project is to identify in an unbiased manner what proteins are differentially expressed in quiescent versus active GSCs, including in nuclear versus cytoplasmic compartments. We will join complementary expertise to identify qGSC biomarkers and molecules / pathways controlling GSC quiescence.

Aims   

1. To identify proteins that are differentially expressed in quiescent versus active GSCs

2. To select from the above, proteins that are specifically differentially expressed in quiescent GSCs

3. To establish mechanistic links between selected protein(s) and quiescent versus active GSC states.

Methodology

Aim 1. During their first year, the student will familiarize themselves with the human GSC model to be used, which can be driven into quiescence by addition of Bone Morphogenetic Protein 4 (BMP4)5. The Sousa-Nunes laboratory have established that longer cultures in BMP4 correspond to deeper NSC quiescence27 and the student will determine whether this is the case also for GSCs. They will fractionate these cells into nuclear and cytoplasmic compartments followed by generating protein extracts using standard biochemical methods already setup. They will perform a time-course experiment, with nuclear and cytoplasmic RNA and protein extractions at different days after BMP4 addition (where 0 d is the active condition). Extract quality will be assessed by reverse-transcriptase polymerase chain reaction and Western Blot analyses of markers expected to be nuclear or cytoplasmic. Polyadenylated RNA with be extracted from total RNA and RNA-seq outsourced.

The student will spend their second year in the laboratory of Dr Manser, who will guide them to perform advanced mass spectrometry (MS)-based proteomics analysis of their samples, particularly using Tandem Mass Tag (TMT), a robust MS approach for system-wide comparison of proteome profiles. Differentially expressed protein clusters with respect to each condition in each subcellular compartment can be obtained from the generated TMT datasets using statistical analyses. The student will also be guided in analysing their protein expression data via advanced network biology to extract potential molecular factors/hubs/pathways specific to each condition/compartment. The Manser Lab has already established all the workflows for similar kinds of analyses28.

Aim 2. The student will remain in the Manser laboratory in their third year for the time required to carry out further bioinformatics analyses to compare transcriptomic and proteomic results on GSCs and these with those previously obtained in the Sousa-Nunes laboratory for quiescent versus active NSCs (also via TMT). We expect to find commonalities and differences between GSCs and NSCs. Back in the Sousa-Nunes laboratory, they will validate analyses by ICC where good antibodies are available. Where appropriate, quantitative imaging (confocal microscopy) can determine nuclear-to-cytoplasmic ratios for candidates (~10) in each condition. From these experiments, the student will select markers and molecules to study functionally.

Aim 3. Functional studies of selected molecules will be carried out via genetic perturbations in GSCs followed by assessment of their effect on quiescence/activation. Specifically, gain- and loss-of-function perturbations will be followed by proliferation assays, using incorporation of the thymidine analog 5-ethynyl-2'-deoxyuridine (EdU), an S-phase marker, and anti-phospho-histone H3 (PH3), a mitotic marker.

IMPORTANT NOTE: Please follow the web link provided and contacts therein for details on eligibility and application process. This is one of a few projects proposed within the KCL-A*STAR PhD Programme. If competitively selected for the scheme you will then have the opportunity to rank projects of interest.

Biological Sciences (4)

Funding Notes

Open to citizens from the UK, the EU, the USA, Canada, Latin America, and Australia.

References

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13. Liau, B. B., Sievers, C., Donohue, L. K., Gillespie, S. M., Flavahan, W. A., Miller, T. E., Venteicher, A. S., Herbert, C. H., Carey, C. D., Rodig, S. J., Shareef, S. J., Najm, F. J., van Galen, P., Wakimoto, H., Cahill, D. P., Rich, J. N., Aster, J. C., Suvà, M. L., Patel, A. P. & Bernstein, B. E. Adaptive Chromatin Remodeling Drives Glioblastoma Stem Cell Plasticity and Drug Tolerance. Cell Stem Cell 20, 233–246 (2017).
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16. Ahmed, A. U., Auffinger, B. & Lesniak, M. S. Understanding glioma stem cells: rationale, clinical relevance and therapeutic strategies. Expert Rev. Neurother. 13, 545–555 (2014).
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18. Prager, B. C., Xie, Q., Bao, S. & Rich, J. N. Cancer Stem Cells: The Architects of the Tumor Ecosystem. Cell Stem Cell 24, 41–53 (2019).
19. Rodgers, J. T., King, K. Y., Brett, J. O., Cromie, M. J., Charville, G. W., Maguire, K. K., Brunson, C., Mastey, N., Liu, L., Tsai, C.-R., Goodell, M. A. & Rando, T. A. mTORC1 controls the adaptive transition of quiescent stem cells from G0 to G(Alert). Nature 510, 393–396 (2014).
20. Llorens-Bobadilla, E., Zhao, S., Baser, A., Saiz-Castro, G., Zwadlo, K., Martin-Villalba, A. Single-Cell Transcriptomics Reveals a Population of Dormant Neural Stem Cells that Become Activated upon Brain Injury. Cell Stem Cell 17, 329–340 (2015).
21. Kwon, J. S., Everetts, N. J., Wang, X., Wang, W., Croce, K. D., Xing, J. & Yao, G. Controlling Depth of Cellular Quiescence by an Rb-E2F Network Switch. Cell Rep. 20, 3223–3235 (2017).
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23. Ferrer, A. I., Trinidad, J. R., Sandiford, O., Etchegaray, J.-P. & Rameshwar, P. Epigenetic dynamics in cancer stem cell dormancy. Cancer Metastasis Rev. 29, 1203–18 (2020).
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25. Sousa-Nunes, R., Yee, L. L. & Gould, A. P. Fat cells reactivate quiescent neuroblasts via TOR and glial insulin relays in Drosophila. Nature 471, 508–512 (2011).
26. Paliouras, G. N., Hamilton, L. K., Aumont, A., Joppé, S. E., Barnabé-Heider, F. & Fernandes, K. J. L. Mammalian target of rapamycin signaling is a key regulator of the transit-amplifying progenitor pool in the adult and aging forebrain. J. Neurosci. 32, 15012–15026 (2012).
27. Rossi, A., Coum, A., Madelenat, M., Harris, L., Miedzik A., Strohbuecker, S., Chai, A., Fiaz, H., Chaouni, R., Faull, P., Grey, W., Bonnet, D., Makeyev, E. V., Snijders, A. P., Kelly, G., Guillemot, F. & Sousa-Nunes, R. Neural stem cells alter nucleocytoplasmic partitioning and accumulate nuclear polyadenylated transcripts during quiescence. bioRxiv doi.org/10.1101/2021.01.06.425462 (2021).
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