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Peptide PROTACs: an experimental framework to evaluate genetically encoded targeted degradation in human cells
No full textSmall molecule PROTACs are emerging as a promising therapeutic strategy for the targeted degradation of disease-related proteins. However, their development remains laborious and unpredictable. To accelerate target selection and provide substantive evidence for prioritising targets in small molecule PROTAC development, this project focuses on the development of genetically encoded peptide PROTACs. The main advantage of using peptide PROTACs is that this approach allows medium-throughput testing of the spatiotemporal compatibility between E3 ligases and their targets, as well as the phenotype of dose-dependent target degradation.
The aim of this work is to design and express genetically encoded peptide PROTACs in human cells to (i) expand the range of E3 ligases that can be recruited by PROTACs and (ii) explore their potential to mediate targeted protein degradation. These peptide PROTACs consist of a degron-derived peptide for E3 ligase recruitment and a SLiM-binding peptide to target specific proteins. To achieve these goals, I have developed a framework that allows fast and cost-effective testing of peptide PROTACs in human cells. This system includes a CRISPR-Cas9 engineered cell line optimised for inducible and dose-responsive protein expression, a functional peptide PROTAC design, and a triple fluorophore reporter to assess their function.
Using this framework, a set of degron-derived peptides were validated for efficient recruitment of endogenous E3 ligases. Expanding the toolkit of E3 ligases opens new possibilities for designing PROTACs that harness E3-specific attributes such as subcellular localisation and cell state-specific activity. Additionally, a proof-of-concept design demonstrated that peptide PROTACs can mediate target protein degradation, offering valuable insights into the spatiotemporal compatibility of E3 ligases and their targets
Elucidating resistance to AKT inhibition in metastatic breast cancer
No full textTargeted therapies have generated promising results both pre-clinically and clinically, but resistance remains an inevitable issue especially in the treatment of advanced cancer. The PI3K-AKT pathway is frequently altered in cancer, including breast, and capivasertib (AKT inhibitor) has shown promising clinical trial results with FDA approval (2023). However, acquired resistance mechanisms remain undocumented, especially AKT1 activating mutations due to the lack of AKT1 E17K mutant breast cancer models. By understanding mechanisms of acquired resistance, the hope is to identify novel therapeutic strategies.
To investigate this new AKT1 E17K models were developed, both patient derived organoids (PDOs) from AKT1 E17K breast cancer patients’ tumours, as well as CRISPR-Cas9 edited cancer cell lines. Mutant models were characterised and resistance to capivasertib generated. To assess in vivo effects of capivasertib in the PDO model, a xenograft experiment was conducted.
Derived resistant cell lines maintained AKT inhibition under capivasertib exposure, shown by inhibited phosphorylation of downstream markers and Foxo3a nuclear localisation. Resistant cells showed upregulated oestrogen and mTOR signalling, plus reengagement of translation. An siRNA screen was used to investigate potential sensitisers, and drug combinations targeting the resistance phenotype identified. Proteomics showed increased FOXP1 in the resistant cells, which has been shown to be an oestrogen signalling output and able to suppress Foxo3a induced apoptosis, this will be explored in future work.
To extend the pre-clinical work, a cohort of AKT1 mutant breast cancers was collated from three trials/ studies, and sequencing (RNA and WES) was used to identify de novo determinants of response to capivasertib. Patients with allelic imbalance (LOH of the WT allele or mutant amplification) had significantly greater PFS benefit on capivasertib and was prognostic/predictive
Tailored sampling approaches to capture cancer evolution in human tumour tissue
No full textIntratumour heterogeneity (ITH) is a pervasive feature of solid cancers. This thesis examines how existing and novel sampling methodologies capture cancer evolution emphasising two forms of sampling; a modified form of random sampling termed representative sampling (RepSamp), and machine-learning augmented multi-regional profiling called TILAgg. There are four main results sections.Section 1 explores RepSamp as a tool to capture genomic ITH in breast cancer in the clinic. VAULT trial endpoints are reported. The landscape of RepSeq in breast cancer is described. The benefit of RepSamp in identifying evolving mechanisms of therapy resistance is highlighted. RepSamp for phenotypic biomarkers is introduced. Section 2 utilises RepSamp to decipher tumour evolution. A bespoke in silico sampling model is generated. Simulated and real-world tumour data are contrasted. Pheno-phylogenies are reconstructed using RepSamp of dividing cells. Evidence of selection in certain genes highlights the ability to identify existing and novel driver genes. The role of RepSamp in the identification of metastasis-seeding subclones is explored.Section 3 focuses on iTME, particularly in quantifying lymphocytic infiltration and a novel classifier is generated (TILAgg). This is validated using bulk sequencing approaches and is strongly predictive of patient outcomes. Section 4 presents an iteration of TILAgg using spatial transcriptomic profiling of 1000 genes applied to multi-regional melanoma TRACERx samples which are used to train a deep learning classifier. In parallel, a deep learning model (TILAgg2.0) is trained on data from TILAgg1.0 annotations and lymphocyte annotations in addition to spatial transcriptomics, to classify H&E slides with high throughput and automation. I conclude that sampling is an essential component of cancer molecular profiling but must be tailored correctly by context. RepSamp can better select a sample of cancer cells for molecular profiling. Deep learning can extend the inferences of molecular assays to larger sample areas by classifying H&E image features.
Uptake, utility and resource requirements of a genetic counselling telephone helpline within the BRCA-DIRECT digital pathway for mainstreamed BRCA testing in patients with breast cancer.
Full text linkBACKGROUND: We trialled the first digital pathway (BRCA-DIRECT) aiming to improve capacity for mainstreamed BRCA testing within UK breast oncology services. Patients received standardised digital pretest information, with saliva sampling and consent to testing completed at home. For individualised support, we offered access to a clinical genetics professional via a telephone helpline (TH). METHODS: To evaluate the utilisation, uptake and resource requirements for provision of the TH, we analysed data from structured call logs recorded in the BRCA-DIRECT Study. Mixed-methods analysis included combining quantitative data from call logs and patient demographics with thematic analysis of free-text notes establishing reasons for calls. Additional data were analysed from structured telephone interviews. RESULTS: Calls were received from 201/1140 (17.6%) patients. We identified that 84.6% of calls (274 calls, 1097 min) pertained to 'administrative' support needs only. The remaining 15.4% required a clinical genetics professional (50 calls, 344 min). Of the clinical calls received: 26.0% were placed prior to test consent, 36.0% while awaiting results and 38.0% post results, with median (interquartile) call lengths of 8 (4-10) min; 5.5 (4-10) min; and 5 (3-7) min, respectively. Across all 1140 patients, a mean of 0.3 min of clinical time was required per patient. CONCLUSIONS: Our findings demonstrate that the 'BRCA-DIRECT' model of standardised information provision served most patients, with a minority using the helpline for supplementary clinical information or support. The modest per-patient requirement for clinical time supports the scalability of this model for expanding mainstream genetic testing within UK oncology services
Mesothelin-Targeting Armoured CAR-T Cells for Malignant Pleural Mesothelioma
No full textSecond and third generation chimeric antigen receptor (CAR)-T cells have shown significant clinical benefit in haematological malignancies, which has not yet been observed in solid tumours. Malignant pleural mesothelioma (MPM) is a highly aggressive tumour with limited treatment options and poor patient prognosis, largely attributed to the tumour-specific tumour microenvironment (TME). In these highly immunosuppressive tumours, mesothelin-targeting CAR-T cells (M11-CAR-T cells) have shown limited clinical benefit so far.
Previously, combining M11-CAR-T cells with an anti-transforming growth factor-β (TGF-β) antibody has augmented their effect preclinically, owing to inhibition of immunosuppressive functions of TGF-β in the TME. This project aims to develop a CAR-T cell therapy for MPM, using the M11-CAR with downstream secretion of TGF-β inhibitory peptides (M11-β-CAR), ultimately aiming to augment M11-CAR-T cell efficacy in the context of MPM.
To test this, M11-β-CAR constructs were cloned and assessed in vitro and in vivo for their function in MPM tumours and reduction of immunosuppression in the TME. The M11-β-CAR-T cells were significantly more functional than conventional M11-CAR-T cells both in vitro and in vivo. In immunocompetent MPM mouse models, the M11-β-CAR was shown to significantly inhibit tumour growth, increase proliferation and function of endogenous tumour-infiltrating lymphocytes (TILs), and significantly increased the levels of neutrophils in the tumour. The increase in neutrophils was also determined to be required for the function of the M11-β-CAR-T cells and were found to be capable of spontaneous tumour killing in responding tumours.
This research is important as it will highlight the potential of M11-β-CAR-T cells in increasing CAR-T cell efficacy through limiting immunosuppression in the TME of MPM and enabling TME remodelling. The findings of this research will have an impact on treating other immunosuppressive solid tumours with armoured CAR-T cell therapy
The pulsing brain: state of the art and an interdisciplinary perspective.
No full textUnderstanding the pulsing dynamics of tissue and fluids in the intracranial environment is an evolving research theme aimed at gaining new insights into brain physiology and disease progression. This article provides an overview of related research in magnetic resonance imaging, ultrasound medical diagnostics and mathematical modelling of biological tissues and fluids. It highlights recent developments, illustrates current research goals and emphasizes the importance of collaboration between these fields
Standardising management of consent withdrawal and other clinical trial participation changes: the UKCRC Registered Clinical Trials Unit Network’s PeRSEVERE project
No full textInterpreting results from biomarker-guided clinical trials: avoiding "negative" or "failed" terminology.
No full textComputational pathology applied to clinical colorectal cancer cohorts identifies immune and endothelial cell spatial patterns predictive of outcome.
No full textColorectal cancer (CRC) is a histologically heterogeneous disease with variable clinical outcome. The role the tumour microenvironment (TME) plays in determining tumour progression is complex and not fully understood. To improve our understanding, it is critical that the TME is studied systematically within clinically annotated patient cohorts with long-term follow-up. Here we studied the TME in three clinical cohorts of metastatic CRC with diverse molecular subtype and treatment history. The MISSONI cohort included cases with microsatellite instability that received immunotherapy (n = 59, 24 months median follow-up). The BRAF cohort included BRAF V600E mutant microsatellite stable (MSS) cancers (n = 141, 24 months median follow-up). The VALENTINO cohort included RAS/RAF WT MSS cases who received chemotherapy and anti-EGFR therapy (n = 175, 32 months median follow-up). Using a Deep learning cell classifier, trained upon >38,000 pathologist annotations, to detect eight cell types within H&E-stained sections of CRC, we quantified the spatial tissue organisation and colocalisation of cell types across these cohorts. We found that the ratio of infiltrating endothelial cells to cancer cells, a possible marker of vascular invasion, was an independent predictor of progression-free survival (PFS) in the BRAF+MISSONI cohort (p = 0.033, HR = 1.44, CI = 1.029-2.01). In the VALENTINO cohort, this pattern was also an independent PFS predictor in TP53 mutant patients (p = 0.009, HR = 0.59, CI = 0.40-0.88). Tumour-infiltrating lymphocytes were an independent predictor of PFS in BRAF+MISSONI (p = 0.016, HR = 0.36, CI = 0.153-0.83). Elevated tumour-infiltrating macrophages were predictive of improved PFS in the MISSONI cohort (p = 0.031). We validated our cell classification using highly multiplexed immunofluorescence for 17 markers applied to the same sections that were analysed by the classifier (n = 26 cases). These findings uncovered important microenvironmental factors that underpin treatment response across and within CRC molecular subtypes, while providing an atlas of the distribution of 180 million cells in 375 clinically annotated CRC patients. © 2025 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland
Impact of NICE Guideline NG241 'Ovarian Cancer: identifying and managing familial and genetic risk' on a regional NHS family history and clinical genetics service
No full text
Background
NICE Guideline NG241: identifying and managing familial and genetic risk of ovarian cancer (OC) was published by the National Institute for Health and Care Excellence (NICE) in March 2024. NG241 advises germline genetic testing of genes predisposing to OC in unaffected individuals with an OC family history at different mutation likelihood thresholds depending on age and sex, ranging from 2% to 10% likelihood of finding a germline pathogenic variant (GPV). Prior to implementation of NG241, updates to the NHS England National Genomic Test Directory would be required. Clinical genetics services have to consider equity of access to assessment and testing across all familial cancer types, best use of their limited resources and other factors such as complexity of delivery of clinical pathways.
Methods
We analysed data from 8011 patients who provided digital family histories to the South West Thames Centre for Genomics between October 2019 and June 2024.
Results
We estimate 527/782 (68%) females and 28/77 (36%) males would meet test criteria for NICE NG241. We estimate we would reject 2919/5485 (53%) females and 135/1208 (11%) males with the same likelihood of carrying a GPV, but with a breast cancer rather than OC family history. Testing the familial OC cohort at a universal 5% threshold in OC families would detect ~11 carriers for 229 tests compared with ~8 carriers for 278 tests following NG241 criteria.
Conclusion
Our data highlight additional factors needing to be considered before the NICE Guideline NG241 can be implemented by regional genetics services.
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