5728 research outputs found
Sort by
Herding clonal evolution to overcome drug resistance in high-grade serous ovarian cancer
No full textOvarian cancer (OC) is one of the most common malignancies responsible for cancer-related deaths in women, and finding new treatment strategies is an area of unmet clinical need. To investigate how the concepts of cancer evolution could be applied to OC care, we hypothesised that the understanding of the clonal dynamics of high-grade serous OC barcoded models under the selection pressure of anticancer drug therapy would allow the development of new sequences of drug treatment, changing current paradigms.
The core of this thesis centred on exploring cancer evolution in OC, emphasising how commonly used drugs to treat this disease (carboplatin, paclitaxel and olaparib) influence its course, employing an advanced state-of-the-art DNA barcode methodology. My experiments showed a tangible correlation between barcoded cell populations pre- and post-drug exposure and barcodes detectable in culture medium. This pivotal observation suggests that liquid biopsies hold promise for real-time tracking evolution in OC.
Further, my experiments revealed consistent cell population profiles post-drug exposure across triplicate experiments, suggesting the presence of pre-existing persistent clones prior to drug exposure. Notably, my experiments also revealed significant differences between paclitaxel and DNA damaging/DNA repair-targeting drugs (carboplatin and olaparib) in barcoded populations. Specifically, carboplatin and paclitaxel caused less heterogeneous cell populations, while olaparib-exposed cells exhibited more pronounced heterogeneity. Furthermore, cells that emerged or persisted post carboplatin and olaparib exposure shared more similar evolutionary phenotypic patterns compared to OC cells exposed to paclitaxel.
Additional findings revealed intricate patterns of cancer evolution trade-offs in terms of proliferation and development of collateral sensitivity. Through single-cell RNA sequencing, gene expression patterns were elucidated, demonstrating distinct differences between paclitaxel-persistent and carboplatin/olaparib-persistent populations. In conclusion, this thesis provides an in-depth exploration of drug resistance/tolerance in OC. Such insights could impact treatment strategies and lead to further research, refining therapeutic approaches for OC
Rapid autopsies to enhance metastatic research: the UPTIDER post-mortem tissue donation program.
No full textResearch on metastatic cancer has been hampered by limited sample availability. Here we present the breast cancer post-mortem tissue donation program UPTIDER and show how it enabled sampling of a median of 31 (range: 5-90) metastases and 5-8 liquids per patient from its first 20 patients. In a dedicated experiment, we show the mild impact of increasing time after death on RNA quality, transcriptional profiles and immunohistochemical staining in tumor tissue samples. We show that this impact can be counteracted by organ cooling. We successfully generated ex vivo models from tissue and liquid biopsies from distinct histological subtypes of breast cancer. We anticipate these and future findings of UPTIDER to elucidate mechanisms of disease progression and treatment resistance and to provide tools for the exploration of precision medicine strategies in the metastatic setting
The use of pembrolizumab monotherapy for the management of head and neck squamous cell carcinoma (HNSCC) in the UK.
No full textPembrolizumab has received approval in the UK as first-line monotherapy for recurrent and/or metastatic HNSCC (R/M HNSCC) following the results of the KEYNOTE-048 trial, which demonstrated a longer overall survival (OS) in comparison to the EXTREME chemotherapy regimen in patients with a combined positive score (CPS) ≥1. In this article, we provide retrospective real-world data on the role of pembrolizumab monotherapy as first-line systemic therapy for HNSCC across 18 centers in the UK from March 20, 2020 to May 31, 2021. 211 patients were included, and in the efficacy analysis, the objective response rate (ORR) was 24.7%, the median progression-free survival (PFS) was 4.8 months (95% confidence interval [CI]: 3.6-6.1), and the median OS was 10.8 months (95% CI 9.0-12.5). Pembrolizumab monotherapy was well tolerated, with 18 patients having to stop treatment owing to immune-related adverse events (irAEs). 53 patients proceeded to second-line treatment with a median PFS2 of 10.2 months (95% CI: 8.8-11.5). Moreover, patients with documented irAEs had a statistically significant longer median PFS (11.3 vs. 3.3 months; log-rank p value = <.001) and median OS (18.8 vs. 8.9 months; log-rank p value <.001). The efficacy and safety of pembrolizumab first-line monotherapy for HNSCC has been validated using real-world data
Phosphatase specificity principles uncovered by MRBLE:Dephos and global substrate identification.
No full textPhosphoprotein phosphatases (PPPs) regulate major signaling pathways, but the determinants of phosphatase specificity are poorly understood. This is because methods to investigate this at scale are lacking. Here, we develop a novel in vitro assay, MRBLE:Dephos, that allows multiplexing of dephosphorylation reactions to determine phosphatase preferences. Using MRBLE:Dephos, we establish amino acid preferences of the residues surrounding the dephosphorylation site for PP1 and PP2A-B55, which reveals common and unique preferences. To compare the MRBLE:Dephos results to cellular substrates, we focused on mitotic exit that requires extensive dephosphorylation by PP1 and PP2A-B55. We use specific inhibition of PP1 and PP2A-B55 in mitotic exit lysates coupled with phosphoproteomics to identify more than 2,000 regulated sites. Importantly, the sites dephosphorylated during mitotic exit reveal key signatures that are consistent with MRBLE:Dephos. Furthermore, integration of our phosphoproteomic data with mitotic interactomes of PP1 and PP2A-B55 provides insight into how binding of phosphatases to substrates shapes dephosphorylation. Collectively, we develop novel approaches to investigate protein phosphatases that provide insight into mitotic exit regulation
Early breast cancer: ESMO Clinical Practice Guideline for diagnosis, treatment and follow-up.
No full textMultiparametric bone MRI targeting aides lesion selection for CT-guided sclerotic bone biopsies in metastatic castrate resistant prostate cancer.
No full textBACKGROUND: Bone biopsies in metastatic castrate-resistant prostate cancer (mCRPC) patients can be challenging. This study's objective was to prospectively validate a multiparametric bone MRI (mpBMRI) algorithm to facilitate target lesion selection in mCRPC patients with sclerotic bone disease for subsequent CT-guided bone biopsies. METHODS: 20 CT-guided bone biopsies were prospectively performed between 02/2021 and 11/2021 in 17 mCRPC patients with only sclerotic bone disease. Biopsy targets were selected based on MRI, including diffusion-weighted (DWI) and T1-weighted VIBE Dixon MR images, allowing for calculation of the apparent diffusion coefficient (ADC) and the relative fat-fraction (rFF), respectively. Bone marrow with high DWI signal, ADC 0.137). Lesion mean HU was 387 ± 187 HU in NGS feasible and 493 ± 218 HU in non-feasible biopsies (p = 0.521). For targets fulfilling all MRI selection algorithm criteria, 13/14 (93%) biopsies were tumor-positive and 10/12 (83%) provided NGS adequate tissue. CONCLUSIONS: Multiparametric bone MRI can facilitate target lesion selection for subsequent CT-guided bone biopsy in mCPRC patients with sclerotic metastases. TRIAL REGISTRATION: Committee for Clinical Research of the Royal Marsden Hospital registration number SE1220
Developing and validating a simple urethra surrogate model to facilitate dosimetric analysis to predict genitourinary toxicity.
No full textPURPOSE: The urethra is a critical structure in prostate radiotherapy planning; however, it is impossible to visualise on CT. We developed a surrogate urethra model (SUM) for CT-only planning workflow and tested its geometric and dosimetric performance against the MRI-delineated urethra (MDU). METHODS: The SUM was compared against 34 different MDUs (within the treatment PTV) in patients treated with 36.25Gy (PTV)/40Gy (CTV) in 5 fractions as part of the PACE-B trial. To assess the surrogate's geometric performance, the Dice similarity coefficient (DSC), Hausdorff distance (HD), mean distance to agreement (MDTA) and the percentage of MDU outside the surrogate (UOS) were calculated. To evaluate the dosimetric performance, a paired t-test was used to calculate the mean of differences between the MDU and SUM for the D99, D98, D50, D2 and D1. The D(n) is the dose (Gy) to n% of the urethra. RESULTS: The median results showed low agreement on DSC (0.32; IQR 0.21-0.41), but low distance to agreement, as would be expected for a small structure (HD 8.4mm (IQR 7.1-10.1mm), MDTA 2.4mm (IQR, 2.2mm-3.2mm)). The UOS was 30% (IQR, 18-54%), indicating nearly a third of the urethra lay outside of the surrogate. However, when comparing urethral dose between the MDU and SUM, the mean of differences for D99, D98 and D95 were 0.12Gy (p=0.57), 0.09Gy (p=0.61), and 0.11Gy (p=0.46) respectively. The mean of differences between the D50, D2 and D1 were 0.08Gy (p=0.04), 0.09Gy (p=0.02) and 0.1Gy (p=0.01) respectively, indicating good dosimetric agreement between MDU and SUM. CONCLUSION: While there were geometric differences between the MDU and SUM, there was no clinically significant difference between urethral dose-volume parameters. This surrogate model could be validated in a larger cohort and then used to estimate the urethral dose on CT planning scans in those without an MRI planning scan or urinary catheter
Spatial Phenotyping of Tumour Immune Microenvironment in the Non-small Cell Lung Cancer Using Artificial Intelligence
No full textLung cancer is the second most common cancer type worldwide, with a five-year survival rate of about 20%. The aggressiveness of the disease and the inefficiency of treatment are partially attributed to the intra-tumour heterogeneity (ITH), which is reflected by the diverse cell interactions in the tumour microenvironment (TME), complicated arrangement of extracellular matrix, and the presence of heterogeneous tumour cell subpopulations. Deconvolving ITH from histo-pathological evaluations plays a critical role in risk stratification and guiding treatment strategies.
In this PhD thesis, I aim to use spatial statistics powered by artificial intelligence (AI) to decipher the ITH, specifically the heterogeneous tumour immune microenvironment in non-small cell lung cancer and to identify the prognostic value of image-derived features.
I first investigate the heterogeneous composition and interactions of immune cell types at different tissue compartments. Specifically, I identified differences in B and T cell interplays between intratumoral and peritumoral immune cell hotspots beyond tertiary lymphoid structures in lung squamous cell carcinoma, which might be associated with an immunosuppressive TME at the tumour-immune interface. I further developed spatial analysis methods to systematically characterise local TME surrounding individual tumour islands in lung squamous cell carcinoma, which revealed distinct phenotypes of tumour islands associated with patient outcomes, metastasis, and immune evasion. Lastly, I developed a self-supervised deep learning pipeline SANDI to enable cost-efficient yet accurate identification of diverse immune cell phenotypes on multiplex images. The SANDI pipeline facilitates the analysis of ITH and the identification of biomarkers in noisy patient samples.
To conclude, by developing AI and spatial statistical analysis pipeline tailored for digital pathology, I identified the composition and interplay of immune cells underpinning their spatial organisation pattern, which signifies the role of the tumour immune microenvironment in tumour progression and therapeutic response
ALK-positive pulmonary inflammatory myofibroblastic tumour: A case report of long term remission achieved with bronchoscopic debulking, radical external beam radiotherapy and pulse steroids, and NSAIDs.
No full textElucidating Prostate Cancer Immunopathology and Immunogenomics Utilizing Computational Analyses of Digital Imaging
No full textProstate Cancer (PCa) is a prominent non-cutaneous malignancy in men in developed countries, necessitating effective treatments. Chronic inflammation is a key factor in PCa pathogenesis and progression, involving a multifaceted interplay between inflammation, genetic aberrations, and the tumour microenvironment. Heightened cellular regeneration due to inflammation-induced DNA damage raises mutation risk, while inflammation fosters angiogenesis and epithelial-mesenchymal transition (EMT), contributing to tumour growth and possible immune evasion.
This study investigated the intricate landscape in castration-resistant prostate cancer (CRPC) using single-stain CD3 Immunohistochemistry (IHC), Hyperplex Immunofluorescence (IF), and AI-assisted image analysis. Screening of 360 hormone-sensitive prostate cancer (HSPC) and 465 CRPC samples revealed considerable inflammation, challenging the perception of PCa as a 'cold' tumour. Notably, distinctive spatial patterns of CD3+ cell distribution across the tumour-stroma interface in CRPC positively correlated with patient survival.
I identified diffuse and nodular patterns of CD3+ inflammation, with nodular inflammation implying worse survival outcomes and potentially indicating immature tertiary lymphoid structures (TLSs) fostering an immunosuppressive environment. Hyperplex IF data from a smaller CRPC cohort highlighted different immune responses in inflamed tumours. Analysis across the tumour-stroma interface identified two immune reaction types: one characterised by high, diffuse inflammation and a variety of immune cells, and the other by B cells, MDSCs, and naïve CD8 cells forming nodules, suggestive of nascent immature TLSs. Mature TLSs correlated with increased inflammation and proliferation of immune cells.
These observations suggest that diffuse inflammation and mature TLSs may indicate NLRP3 inflammasome activation, while immature TLSs might reflect the Senescence Associated Secretory Phenotype (SASP). This enhanced understanding of the CRPC immune microenvironment is pivotal for optimising immunotherapy.
In summary, this study elucidates the complex immune microenvironment in CRPC, proposing an innovative understanding of its role in disease progression and identifying potential biomarkers to enhance treatment efficacy. These insights have implications for patient selection and monitoring in immune checkpoint inhibition therapy, ultimately enhancing patient outcomes in prostate cancer treatment