379 results found
Boubnovski MM, Chen M, Linton-Reid K, et al., 2022, Development of a multi-task learning V-Net for pulmonary lobar segmentation on CT and application to diseased lungs, Clinical Radiology, Vol: 77, Pages: e620-e627, ISSN: 0009-9260
AIMTo develop a multi-task learning (MTL) V-Net for pulmonary lobar segmentation on computed tomography (CT) and application to diseased lungs.MATERIALS AND METHODSThe described methodology utilises tracheobronchial tree information to enhance segmentation accuracy through the algorithm's spatial familiarity to define lobar extent more accurately. The method undertakes parallel segmentation of lobes and auxiliary tissues simultaneously by employing MTL in conjunction with V-Net-attention, a popular convolutional neural network in the imaging realm. Its performance was validated by an external dataset of patients with four distinct lung conditions: severe lung cancer, COVID-19 pneumonitis, collapsed lungs, and chronic obstructive pulmonary disease (COPD), even though the training data included none of these cases.RESULTSThe following Dice scores were achieved on a per-segment basis: normal lungs 0.97, COPD 0.94, lung cancer 0.94, COVID-19 pneumonitis 0.94, and collapsed lung 0.92, all at p<0.05.CONCLUSIONDespite severe abnormalities, the model provided good performance at segmenting lobes, demonstrating the benefit of tissue learning. The proposed model is poised for adoption in the clinical setting as a robust tool for radiologists and researchers to define the lobar distribution of lung diseases and aid in disease treatment planning.
Komodromos M, Aboagye EO, Evangelou M, et al., 2022, Variational Bayes for high-dimensional proportional hazards models with applications within gene expression, BIOINFORMATICS, ISSN: 1367-4803
Komodromos M, Aboagye EO, Evangelou M, et al., 2022, Variational Bayes for high-dimensional proportional hazards models with applications within gene expression, Bioinformatics, ISSN: 1367-4803
Motivation:Few Bayesian methods for analyzing high-dimensional sparse survival data provide scalable variable selection, effect estimation and uncertainty quantification. Such methods often either sacrifice uncertainty quantification by computing maximum a posteriori estimates, or quantify the uncertainty at high (unscalable) computational expense.Results:We bridge this gap and develop an interpretable and scalable Bayesian proportional hazards model for prediction and variable selection, referred to as SVB. Our method, based on a mean-field variational approximation, overcomes the high computational cost of MCMC whilst retaining useful features, providing a posterior distribution for the parameters and offering a natural mechanism for variable selection via posterior inclusion probabilities. The performance of our proposed method is assessed via extensive simulations and compared against other state-of-the-art Bayesian variable selection methods, demonstrating comparable or better performance. Finally, we demonstrate how the proposed method can be used for variable selection on two transcriptomic datasets with censored survival outcomes, and how the uncertainty quantification offered by our method can be used to provide an interpretable assessment of patient risk.Availability and implementation:our method has been implemented as a freely available R package survival.svb (https://github.com/mkomod/survival.svb).
Inglese M, Patel N, Linton-Reid K, et al., 2022, A predictive model using the mesoscopic architecture of the living brain to detect Alzheimer’s disease, Communications Medicine, Vol: 2, ISSN: 2730-664X
Background:Alzheimer’s disease, the most common cause of dementia, causes a progressive and irreversible deterioration of cognition that can sometimes be difficult to diagnose, leading to suboptimal patient care.Methods:We developed a predictive model that computes multi-regional statistical morpho-functional mesoscopic traits from T1-weighted MRI scans, with or without cognitive scores. For each patient, a biomarker called “Alzheimer’s Predictive Vector” (ApV) was derived using a two-stage least absolute shrinkage and selection operator (LASSO).Results:The ApV reliably discriminates between people with (ADrp) and without (nADrp) Alzheimer’s related pathologies (98% and 81% accuracy between ADrp - including the early form, mild cognitive impairment - and nADrp in internal and external hold-out test sets, respectively), without any a priori assumptions or need for neuroradiology reads. The new test is superior to standard hippocampal atrophy (26% accuracy) and cerebrospinal fluid beta amyloid measure (62% accuracy). A multiparametric analysis compared DTI-MRI derived fractional anisotropy, whose readout of neuronal loss agrees with ADrp phenotype, and SNPrs2075650 is significantly altered in patients with ADrp-like phenotype.Conclusions:This new data analytic method demonstrates potential for increasing accuracy of Alzheimer diagnosis.
Piletsky S, Garcia Cruz A, Piletska E, et al., 2022, Iodo silanes as superior substrates for the solid phase synthesis of molecularly imprinted polymer nanoparticles, Polymers, Vol: 14, Pages: 1-8, ISSN: 2073-4360
Current state-of-the-art techniques for the solid phase synthesis of molecularly imprinted polymer (MIP) nanoparticles typically rely on amino silanes for the immobilisation of template molecules prior to polymerisation. An investigation into commonly used amino silanes identified a number of problematic side reactions which negatively affect the purity and affinity of these polymers. Iodo silanes are presented as a superior alternative in a case study describing the synthesis of MIPs against epitopes of a common cancer biomarker, epidermal growth factor receptor (EGFR). The proposed iodo silane outperformed the amino silane by all metrics tested, showing high purity and specificity, and nanomolar affinity for the target peptide.
Hindocha S, Charlton TG, Linton-Reid K, et al., 2022, A comparison of machine learning methods for predicting recurrence and death after curative-intent radiotherapy for non-small cell lung cancer: Development and validation of multivariable clinical prediction models., EBioMedicine, Vol: 77, ISSN: 2352-3964
BackgroundSurveillance is universally recommended for non-small cell lung cancer (NSCLC) patients treated with curative-intent radiotherapy. High-quality evidence to inform optimal surveillance strategies is lacking. Machine learning demonstrates promise in accurate outcome prediction for a variety of health conditions. The purpose of this study was to utilise readily available patient, tumour, and treatment data to develop, validate and externally test machine learning models for predicting recurrence, recurrence-free survival (RFS) and overall survival (OS) at 2 years from treatment.MethodsA retrospective, multicentre study of patients receiving curative-intent radiotherapy for NSCLC was undertaken. A total of 657 patients from 5 hospitals were eligible for inclusion. Data pre-processing derived 34 features for predictive modelling. Combinations of 8 feature reduction methods and 10 machine learning classification algorithms were compared, producing risk-stratification models for predicting recurrence, RFS and OS. Models were compared with 10-fold cross validation and an external test set and benchmarked against TNM-stage and performance status. Youden Index was derived from validation set ROC curves to distinguish high and low risk groups and Kaplan-Meier analyses performed.FindingsMedian follow-up time was 852 days. Parameters were well matched across training-validation and external test sets: Mean age was 73 and 71 respectively, and recurrence, RFS and OS rates at 2 years were 43% vs 34%, 54% vs 47% and 54% vs 47% respectively. The respective validation and test set AUCs were as follows: 1) RFS: 0·682 (0·575–0·788) and 0·681 (0·597–0·766), 2) Recurrence: 0·687 (0·582–0·793) and 0·722 (0·635–0·81), and 3) OS: 0·759 (0·663–0·855) and 0·717 (0·634–0·8). Our models were superior to TNM stage and performan
Doran SJ, Al Sad M, Petts JA, et al., 2022, Integrating the OHIF viewer into XNAT: achievements, challenges and prospects for quantitative imaging studies, Tomography, Vol: 8, Pages: 497-512, ISSN: 2379-139X
Purpose: XNAT is an informatics software platform to support imaging research, particularly in the context of large, multicentre studies of the type that are essential to validate quantitative imaging biomarkers. XNAT provides import, archiving, processing and secure distribution facilities for image and related study data. Until recently, however, modern data visualisation and annotation tools were lacking on the XNAT platform. We describe the background to, and implementation of, an integration of the Open Health Imaging Foundation (OHIF) Viewer into the XNAT environment. We explain the challenges overcome and discuss future prospects for quantitative imaging studies. Materials and methods: The OHIF Viewer adopts an approach based on the DICOM web protocol. To allow operation in an XNAT environment, a data-routing methodology was developed to overcome the mismatch between the DICOM and XNAT information models and a custom viewer panel created to allow navigation within the viewer between different XNAT projects, subjects and imaging sessions. Modifications to the development environment were made to allow developers to test new code more easily against a live XNAT instance. Major new developments focused on the creation and storage of regions-of-interest (ROIs) and included: ROI creation and editing tools for both contour- and mask-based regions; a “smart CT” paintbrush tool; the integration of NVIDIA’s Artificial Intelligence Assisted Annotation (AIAA); the ability to view surface meshes, fractional segmentation maps and image overlays; and a rapid image reader tool aimed at radiologists. We have incorporated the OHIF microscopy extension and, in parallel, introduced support for microscopy session types within XNAT for the first time. Results: Integration of the OHIF Viewer within XNAT has been highly successful and numerous additional and enhanced tools have been created in a programme started in 2017 that is still ongoing. The software has bee
Fotopoulou C, Rockall A, Lu H, et al., 2021, Validation analysis of the novel imaging-based prognostic radiomic signature in patients undergoing primary surgery for advanced high-grade serous ovarian cancer (HGSOC), British Journal of Cancer, Vol: 126, Pages: 1047-1054, ISSN: 0007-0920
BackgroundPredictive models based on radiomics features are novel, highly promising approaches for gynaecological oncology. Here, we wish to assess the prognostic value of the newly discovered Radiomic Prognostic Vector (RPV) in an independent cohort of high-grade serous ovarian cancer (HGSOC) patients, treated within a Centre of Excellence, thus avoiding any bias in treatment quality.MethodsRPV was calculated using standardised algorithms following segmentation of routine preoperative imaging of patients (n = 323) who underwent upfront debulking surgery (01/2011-07/2018). RPV was correlated with operability, survival and adjusted for well-established prognostic factors (age, postoperative residual disease, stage), and compared to previous validation models.ResultsThe distribution of low, medium and high RPV scores was 54.2% (n = 175), 33.4% (n = 108) and 12.4% (n = 40) across the cohort, respectively. High RPV scores independently associated with significantly worse progression-free survival (PFS) (HR = 1.69; 95% CI:1.06–2.71; P = 0.038), even after adjusting for stage, age, performance status and residual disease. Moreover, lower RPV was significantly associated with total macroscopic tumour clearance (OR = 2.02; 95% CI:1.56–2.62; P = 0.00647).ConclusionsRPV was validated to independently identify those HGSOC patients who will not be operated tumour-free in an optimal setting, and those who will relapse early despite complete tumour clearance upfront. Further prospective, multicentre trials with a translational aspect are warranted for the incorporation of this radiomics approach into clinical routine.
Piletsky S, Piletska E, Poblocka M, et al., 2021, Snapshot imprinting: Rapid identification of cancer cell surface proteins and epitopes using molecularly imprinted polymers, Nano Today: an international rapid reviews journal, Vol: 41, Pages: 1-8, ISSN: 1748-0132
Proteomic mapping of cell surfaces is an invaluable tool for drug development and clinical diagnostics. This work describes a new ‘snapshot imprinting’ method designed to obtain proteomic maps of cell surfaces, with the aim of identifying cell surface markers and epitopes for diagnostic and therapeutic applications. The analysis of two cancer cell lines, HN5 and MDA-MB-468, is described herein as a proof of concept, along with the selective targeting of three identified epitopes of epidermal growth factor receptor using molecularly imprinted polymer nanoparticles. 438 proteins were identified using this technique, with 283 considered to be transmembrane or extracellular proteins. The major advantage of the molecular imprinting approach developed here is the ability to analyse cell surface proteins without tedious fractionation, affinity separation or labelling. We believe that this system of protein analysis may provide a basic molecular diagnostics toolbox for precise, personalised treatment of cancer and other diseases.
Braga M, Leow CH, Gil JH, et al., 2021, Investigating CXCR4 expression of tumor cells and the vascular compartment: A multimodal approach, PLOS ONE, Vol: 16, ISSN: 1932-6203
Teh JH, Braga M, Allott L, et al., 2021, A kit-based aluminium-[F-18]fluoride approach to radiolabelled microbubbles, CHEMICAL COMMUNICATIONS, Vol: 57, Pages: 11677-11680, ISSN: 1359-7345
Aboagye E, Li Y, Inglese M, et al., 2021, Consideration of metabolite efflux in radiolabelled choline kinetics, Pharmaceutics, Vol: 13, Pages: 1-18, ISSN: 1999-4923
Hypoxia is a complex microenvironmental condition known to regulate choline kinase α (CHKA) activity and choline transport through transcription factor hypoxia-inducible factor-1α (HIF-1α) and, therefore may confound uptake of choline radiotracer[18F]fluoromethyl-[1,2-2H4]-choline ([18 F]-D4-FCH). The aim of this study was to investigate how hypoxia affects choline radiotracer dynamics. Three underlying mechanisms by which hypoxiacould potentially alter the uptake of the choline radiotracer, [18 F]-D4-FCH, were investigated: 18F-D4-FCH import, CHKA phosphorylation activity, and efflux of [18 F]-D4-FCH and its phosphorylated product [18F]-D4-FCHP. Effects of hypoxia on [18 F]-D4-FCH uptake were studied in CHKA-overexpressing cell lines of prostate cancer, PC-3, and breast cancer, MDA-MB-231 cells. Mechanisms of radiotracer efflux were assessed by cell uptake and immunofluorescence in vitro, and examined in vivo (N=24). Mathematical modelling methodology was further developed to verify efflux hypothesis using [18 F]-D4-FCH dynamic PET scans from non-small cell lung cancer (NSCLC) patients (N=17). We report a novel finding involving export of phosphorylated[18F]-D4-FCH, [18 F]-D4-FCHP, via HIF-1α-responsive efflux transporters including ABCB4 when HIF-1α level is augmented. This is supported by graphical analysis of human data with a compartmental model (M2T6k+k5) that accounts for efflux. Hypoxia/HIF-1α increases the efflux of phosphorylated radiolabelled choline species, thus supporting consideration of efflux in modelling of radiotracer dynamics.
McAteer MA, O'Connor JPB, Koh DM, et al., 2021, Introduction to the National Cancer Imaging Translational Accelerator (NCITA): a UK-wide infrastructure for multicentre clinical translation of cancer imaging biomarkers, British Journal of Cancer, Vol: 125, Pages: 1462-1465, ISSN: 0007-0920
The National Cancer Imaging Translational Accelerator (NCITA) is creating a UK national coordinated infrastructure for accelerated translation of imaging biomarkers for clinical use. Through the development of standardised protocols, data integration tools and ongoing training programmes, NCITA provides a unique scalable infrastructure for imaging biomarker qualification using multicentre clinical studies.
Aboagye E, Young JD, Jauregui-Osoro M, et al., 2021, An overview of nuclear medicine research in the UK and the landscape for clinical adoption, Nuclear Medicine Communications, Vol: 42, Pages: 1301-1312, ISSN: 0143-3636
Background and objectives Nuclear medicine contributes greatly to the clinical management of patients and experimental medicine. This report aims to (1) outline the current landscape of nuclear medicine research in the UK, including current facilities and recent or ongoing clinical studies and (2) provide information about the available pathways for clinical adoption and NHS funding (commissioning) of radiopharmaceuticals.Methods Evidence was obtained through database searches for UK-based nuclear medicine clinical studies and by conducting a questionnaire-based survey of UK radiopharmaceutical production facilities. A recent history of clinical commissioning, either through recommendations from the National Institute for Health and Care Excellence (NICE) or through NHS specialised services commissioning, was compiled from publicly available documents and policies.Results The collected data highlighted the UK’s active nuclear medicine research community and recent investment in new facilities and upgrades. All commissioning routes favour radiopharmaceuticals that have marketing authorisation and since 2017 there has been a requirement to demonstrate both clinical and cost-effectiveness. Whilst radiopharmaceuticals for molecular radiotherapy are well suited to these commissioning pathways, diagnostic radiotracers have not historically been assessed in this manner.Conclusions We hope that by collating this information we will provide stimulus for future discussion and consensus statements around this topic.
Aboagye E, Wang N, Brickute D, et al., 2021, Novel non-congeneric derivatives of the choline kinase alpha inhibitor ICL-CCIC-0019, Pharmaceutics, Vol: 13, Pages: 1-17, ISSN: 1999-4923
Choline kinase alpha (CHKA) is a promising target for the development of cancer therapeutics. We have previously reported ICL-CCIC-0019, a potent CHKA inhibitor with high cellular activity but with some unfavorable pharmacological properties. In this work, we present an active analogue of ICL-CCIC-0019 bearing a piperazine handle (CK146) to facilitate further structural elaboration of the pharmacophore and thus improve the biological profile. Two different strategies were evaluated in this study: (1) a prodrug approach whereby selective CHKA inhibition could be achieved through modulating the activity of CK146, via the incorporation of an ε-(Ac) Lys motif, cleavable by elevated levels of histone deacetylase (HDAC) and cathepsin L (CTSL) in tumour cells; (2) a prostate-specific membrane antigen (PSMA) receptor targeted delivery strategy. Prodrug (CK145) and PSMA-targeted (CK147) derivatives were successfully synthesized and evaluated in vitro. While the exploitation of CK146 in those two strategies did not deliver the expected results, important and informative structure-activity relationships were observed and have been reported.
Vassileva V, Braga M, Barnes C, et al., 2021, Effective detection and monitoring of glioma using [18F]FPIA PET imaging, Biomedicines, Vol: 9, Pages: 1-14, ISSN: 2227-9059
Background: Reprogrammed cellular metabolism is a cancer hallmark. In addition to increased glycolysis, the oxidation of acetate in the citric acid cycle is another common metabolic phenotype. We have recently developed a novel fluorine-18-labelled trimethylacetate-based radiotracer, [18F]fluoro-pivalic acid ([18F]FPIA), for imaging the transcellular flux of short-chain fatty acids, and investigated whether this radiotracer can be used for the detection of glioma growth. Methods: We evaluated the potential of [18F]FPIA PET to monitor tumor growth in orthotopic patient-derived (HSJD-GBM-001) and cell line-derived (U87, LN229) glioma xenografts, and also included [18F]FDG PET for comparison. We assessed proliferation (Ki-67) and the expression of lipid metabolism and transport proteins (CPT1, SLC22A2, SLC22A5, SLC25A20) by immunohistochemistry, along with etomoxir treatment to provide insights into [18F]FPIA uptake. Results: Longitudinal PET imaging showed gradual increase in [18F]FPIA uptake in orthotopic glioma models with disease progression (p < 0.0001), and high tumor-to-brain contrast compared to [18F]FDG (p < 0.0001). [18F]FPIA uptake correlated positively with Ki-67 (p < 0.01), SLC22A5 (p < 0.001) and SLC25A20 (p = 0.001), and negatively with CPT1 (p < 0.01) and SLC22A2 (p < 0.01). Etomoxir reduced [18F]FPIA uptake, which correlated with decreased Ki-67 (p < 0.05). Conclusions: Our findings support the use of [18F]FPIA PET for the detection and longitudinal monitoring of glioma, showing a positive correlation with tumor proliferation, and suggest transcellular flux-mediated radiotracer uptake.
Allott L, Chen C, Braga M, et al., 2021, Detecting hypoxia in vitro using 18F-pretargeted IEDDA “click” chemistry in live cells, RSC Advances: an international journal to further the chemical sciences, Vol: 11, Pages: 20335-20341, ISSN: 2046-2069
We have exemplified a pretargeted approach to interrogate hypoxia in live cells using radioactive bioorthogonal inverse electron demand Diels–Alder (IEDDA) “click” chemistry. Our novel 18F-tetrazine probe ([18F]FB-Tz) and 2-nitroimidazole-based TCO targeting molecule (8) showed statistically significant (P < 0.0001) uptake in hypoxic cells (ca. 90 %ID per mg) vs. normoxic cells (<10 %ID per mg) in a 60 min incubation of [18F]FB-Tz. This is the first time that an intracellularly targeted small-molecule for IEDDA “click” has been used in conjunction with a radioactive reporter molecule in live cells and may be a useful tool with far-reaching applicability for a variety of applications.
Boubnovski Martell M, Chen M, Linton-Reid K, et al., 2021, [pre-print] Development of a Multi-Task Learning V-Net for Pulmonary Lobar Segmentation on Computed Tomography and Application to Diseased Lungs, Publisher: arXiv
Automated lobar segmentation allows regional evaluation of lung disease and is important for diagnosis and therapy planning. Advanced statistical workflows permitting such evaluation is a needed area within respiratory medicine; their adoption remains slow, with poor workflow accuracy. Diseased lung regions often produce high-density zones on CT images, limiting an algorithm's execution to specify damaged lobes due to oblique or lacking fissures. This impact motivated developing an improved machine learning method to segment lung lobes that utilises tracheobronchial tree information to enhance segmentation accuracy through the algorithm's spatial familiarity to define lobar extent more accurately. The method undertakes parallel segmentation of lobes and auxiliary tissues simultaneously by employing multi-task learning (MTL) in conjunction with V-Net-attention, a popular convolutional neural network in the imaging realm. In keeping with the model's adeptness for better generalisation, high performance was retained in an external dataset of patients with four distinct diseases: severe lung cancer, COVID-19 pneumonitis, collapsed lungs and Chronic Obstructive Pulmonary Disease (COPD), even though the training data included none of these cases. The benefit of our external validation test is specifically relevant since our choice includes those patients who have diagnosed lung disease with associated radiological abnormalities. To ensure equal rank is given to all segmentations in the main task we report the following performance (Dice score) on a per-segment basis: normal lungs 0.97, COPD 0.94, lung cancer 0.94, COVID-19 pneumonitis 0.94 and collapsed lung 0.92, all at p<0.05. Even segmenting lobes with large deformations on CT images, the model maintained high accuracy. The approach can be readily adopted in the clinical setting as a robust tool for radiologists.
Allott L, Amgheib A, Barnes C, et al., 2021, Radiolabelling an F-18 biologic via facile IEDDA "click" chemistry on the GE FASTLab (TM) platform, Reaction Chemistry and Engineering, Vol: 6, Pages: 1070-1078, ISSN: 2058-9883
The use of biologics in positron emission tomography (PET) imaging is an important area of radiopharmaceutical development and new automated methods are required to facilitate their production. We report an automated radiosynthesis method to produce a radiolabelled biologic via facile inverse electron demand Diels–Alder (IEDDA) “click” chemistry on a single GE FASTLab™ cassette. We exemplified the method by producing a fluorine-18 radiolabelled interleukin-2 (IL2) radioconjugate from a trans-cyclooctene (TCO) modified IL2 precursor. The radioconjugate was produced using a fully automated radiosynthesis on a single FASTLab™ cassette in a decay-corrected radiochemical yield (RCY, d.c.) of 19.8 ± 2.6% in 110 min (from start of synthesis); the molar activity was 132.3 ± 14.6 GBq μmol−1. The in vitro uptake of [18F]TTCO-IL2 correlated with the differential receptor expression (CD25, CD122, CD132) in PC3, NK-92 and activated human PBMCs. The automated method may be adapted for the radiosynthesis of any TCO-modified protein via IEDDA chemistry.
Lu H, Cunnea P, Nixon K, et al., 2021, Discovery of a biomarker candidate for surgical stratification in high-grade serous ovarian cancer, British Journal of Cancer, Vol: 124, Pages: 1286-1293, ISSN: 0007-0920
Background: Maximal effort cytoreductive surgery is associated with improved outcomes in advanced high-grade serous ovarian cancer (HGSOC). However, despite complete gross resection (CGR), there is a percentage of patients who will relapse and die early. The aim of this study is to identify potential candidate biomarkers to help personalise surgical radicality.Methods: 136 advanced HGSOC cases who underwent CGR were identified from three public transcriptomic datasets. Candidate prognostic biomarkers were discovered in this cohort by Cox regression analysis, and further validated by targeted RNA-sequencing in HGSOC cases from Imperial College Healthcare NHS Trust (n = 59), and a public dataset. Gene set enrichment analysis was performed to understand the biological significance of the candidate biomarker.Results: We identified ALG5 as a prognostic biomarker for early tumour progression in advanced HGSOC despite CGR (HR = 2.42, 95% CI (1.57–3.75), p < 0.0001). The prognostic value of this new candidate biomarker was additionally confirmed in two independent datasets (HR = 1.60, 95% CI (1.03–2.49), p = 0.0368; HR = 3.08, 95% CI (1.07–8.81), p = 0.0365). Mechanistically, the oxidative phosphorylation was demonstrated as a potential biological pathway of ALG5-high expression in patients with early relapse (p < 0.001).Conclusion: ALG5 has been identified as an independent prognostic biomarker for poor prognosis in advanced HGSOC patients despite CGR. This sets a promising platform for biomarker combinations and further validations towards future personalised surgical care.
Brickute D, Beckley A, Allott L, et al., 2021, Synthesis and evaluation of 3’-[18F]fluorothymidine-5’-squaryl as a bioisostere of 3’-[18F]fluorothymidine-5’-monophosphate, RSC Advances: an international journal to further the chemical sciences, Vol: 11, Pages: 12423-12433, ISSN: 2046-2069
The squaryl moiety has emerged as an important phosphate bioisostere with reportedly greater cell permeability. It has been used in the synthesis of several therapeutic drug molecules including nucleoside and nucleotide analogues but is yet to be evaluated in the context of positron emission tomography (PET) imaging. We have designed, synthesised and evaluated 3′-[18F]fluorothymidine-5′-squaryl ([18F]SqFLT) as a bioisostere to 3′-[18F]fluorothymidine-5′-monophosphate ([18F]FLTMP) for imaging thymidylate kinase (TMPK) activity. The overall radiochemical yield (RCY) was 6.7 ± 2.5% and radiochemical purity (RCP) was >90%. Biological evaluation in vitro showed low tracer uptake (<0.3% ID mg−1) but significantly discriminated between wildtype HCT116 and CRISPR/Cas9 generated TMPK knockdown HCT116shTMPK−. Evaluation of [18F]SqFLT in HCT116 and HCT116shTMPK− xenograft mouse models showed statistically significant differences in tumour uptake, but lacked an effective tissue retention mechanism, making the radiotracer in its current form unsuitable for PET imaging of proliferation.
Hu Z, Cunnea P, Zhong Z, et al., 2021, The Oxford Classic links epithelial-to-mesenchymal transition to immunosuppression in poor prognosis ovarian cancers, Clinical Cancer Research, Vol: 27, Pages: 1570-1579, ISSN: 1078-0432
Purpose: Using RNA sequencing, we recently developed the 52-gene–based Oxford classifier of carcinoma of the ovary (Oxford Classic, OxC) for molecular stratification of serous ovarian cancers (SOCs) based on the molecular profiles of their cell of origin in the fallopian tube epithelium. Here, we developed a 52-gene NanoString panel for the OxC to test the robustness of the classifier.Experimental Design: We measured the expression of the 52 genes in an independent cohort of prospectively collected SOC samples (n = 150) from a homogenous cohort who were treated with maximal debulking surgery and chemotherapy. We performed data mining of published expression profiles of SOCs and validated the classifier results on tissue arrays comprising 137 SOCs.Results: We found evidence of profound nongenetic heterogeneity in SOCs. Approximately 20% of SOCs were classified as epithelial-to-mesenchymal transition–high (EMT-high) tumors, which were associated with poor survival. This was independent of established prognostic factors, such as tumor stage, tumor grade, and residual disease after surgery (HR, 3.3; P = 0.02). Mining expression data of 593 patients revealed a significant association between the EMT scores of tumors and the estimated fraction of alternatively activated macrophages (M2; P < 0.0001), suggesting a mechanistic link between immunosuppression and poor prognosis in EMT-high tumors.Conclusions: The OxC-defined EMT-high SOCs carry particularly poor prognosis independent of established clinical parameters. These tumors are associated with high frequency of immunosuppressive macrophages, suggesting a potential therapeutic target to improve clinical outcome.
Kenny LM, Gopalakrishnan GS, Barwick TD, et al., 2021, Herpet study- PET imaging of HER2 expression in breast cancer using the novel Affibody tracer [18F]GE-226, a first in patient study, Publisher: AMER ASSOC CANCER RESEARCH, ISSN: 0008-5472
Natoli M, Gallon J, Lu H, et al., 2021, Transcriptional analysis of multiple ovarian cancer cohorts reveals prognostic and immunomodulatory consequences of ERV expression, Journal for ImmunoTherapy of Cancer, Vol: 9, ISSN: 2051-1426
Background Endogenous retroviruses (ERVs) play a role in a variety of biological processes, including embryogenesis and cancer. DNA methyltransferase inhibitors (DNMTi)-induced ERV expression triggers interferon responses in ovarian cancer cells via the viral sensing machinery. Baseline expression of ERVs also occurs in cancer cells, though this process is poorly understood and previously unexplored in epithelial ovarian cancer (EOC). Here, the prognostic and immunomodulatory consequences of baseline ERV expression was assessed in EOC.Methods ERV expression was assessed using EOC transcriptional data from The Cancer Genome Atlas (TCGA) and from an independent cohort (Hammersmith Hospital, HH), as well as from untreated or DNMTi-treated EOC cell lines. Least absolute shrinkage and selection operator (LASSO) logistic regression defined an ERV expression score to predict patient prognosis. Immunohistochemistry (IHC) was conducted on the HH cohort. Combination of DNMTi treatment with γδ T cells was tested in vitro, using EOC cell lines and patient-derived tumor cells.Results ERV expression was found to define clinically relevant subsets of EOC patients. An ERV prognostic score was successfully generated in TCGA and validated in the independent cohort. In EOC patients from this cohort, a high ERV score was associated with better survival (log-rank p=0.0009) and correlated with infiltration of CD8+PD1+T cells (r=0.46, p=0.0001). In the TCGA dataset, a higher ERV score was found in BRCA1/2 mutant tumors, compared to wild type (p=0.015), while a lower ERV score was found in CCNE1 amplified tumors, compared to wild type (p=0.019). In vitro, baseline ERV expression dictates the level of ERV induction in response to DNMTi. Manipulation of an ERV expression threshold by DNMTi resulted in improved EOC cell killing by cytotoxic immune cells.Conclusions These findings uncover the potential for baseline ERV expression to robustly inform EOC patient prognosis, influence
Santhirasekaram A, Pinto K, Winkler M, et al., 2021, Multi-scale Hybrid Transformer Networks: Application to Prostate Disease Classification, Pages: 12-21, ISSN: 0302-9743
Automated disease classification could significantly improve the accuracy of prostate cancer diagnosis on MRI, which is a difficult task even for trained experts. Convolutional neural networks (CNNs) have shown some promising results for disease classification on multi-parametric MRI. However, CNNs struggle to extract robust global features about the anatomy which may provide important contextual information for further improving classification accuracy. Here, we propose a novel multi-scale hybrid CNN/transformer architecture with the ability of better contextualising local features at different scales. In our application, we found this to significantly improve performance compared to using CNNs. Classification accuracy is even further improved with a stacked ensemble yielding promising results for binary classification of prostate lesions into clinically significant or non-significant.
Arshad MA, Gitau S, Tam H, et al., 2020, Optimal method for metabolic tumour volume assessment of cervical cancers with inter-observer agreement on [18F]-fluoro-deoxy-glucose positron emission tomography with computed tomography, European Journal of Nuclear Medicine and Molecular Imaging, Pages: 1-15, ISSN: 0340-6997
PurposeCervical cancer metabolic tumour volume (MTV) derived from [18F]-FDG PET/CT has a role in prognostication and therapy planning. There is no standard method of outlining MTV on [18F]-FDG PET/CT. The aim of this study was to assess the optimal method to outline primary cervical tumours on [18F]-FDG PET/CT using MRI-derived tumour volumes as the reference standard.Methods81 consecutive cervical cancer patients with pre-treatment staging MRI and [18F]-FDG PET/CT imaging were included. MRI volumes were compared with different PET segmentation methods. Method 1 measured MTVs at different SUVmax thresholds ranging from 20 to 60% (MTV20-MTV60) with bladder masking and manual adjustment when required. Method 2 created an isocontour around the tumour prior to different SUVmax thresholds being applied. Method 3 used an automated gradient method. Inter-observer agreement of MTV, following manual adjustment when required, was recorded.ResultsFor method 1, the MTV25 and MTV30 were closest to the MRI volumes for both readers (mean percentage change from MRI volume of 2.9% and 13.4% for MTV25 and − 13.1% and − 2.0% for MTV30 for readers 1 and 2). 70% of lesions required manual adjustment at MTV25 compared with 45% at MTV30. There was excellent inter-observer agreement between MTV30 to MTV60 (ICC ranged from 0.898–0.976 with narrow 95% confidence intervals (CIs)) and moderate agreement at lower thresholds (ICC estimates of 0.534 and 0.617, respectively for the MTV20 and MTV25 with wide 95% CIs). Bladder masking was performed in 86% of cases overall. For method 2, excellent correlation was demonstrated at MTV25 and MTV30 (mean % change from MRI volume of −3.9% and − 8.6% for MTV25 and − 16.9% and 19% for MTV30 for readers 1 and 2, respectively). This method also demonstrated excellent ICC across all thresholds with no manual adjustment. Method 3 demonstrated excellent ICC of 0.96 (95% CI 0.94–0.97) but had a
Ordonez AA, Abhishek S, Singh AK, et al., 2020, Caspase-based PET for evaluating pro-apoptotic treatments in a tuberculosis mouse model, Molecular Imaging and Biology, Vol: 22, Pages: 1489-1494, ISSN: 1095-0397
PurposeDespite recent advances in antimicrobial treatments, tuberculosis (TB) remains a major global health threat. Mycobacterium tuberculosis proliferates in macrophages, preventing apoptosis by inducing anti-apoptotic proteins leading to necrosis of the infected cells. Necrosis then leads to increased tissue destruction, reducing the penetration of antimicrobials and immune cells to the areas where they are needed most. Pro-apoptotic drugs could be used as host-directed therapies in TB to improve antimicrobial treatments and patient outcomes.ProcedureWe evaluated [18F]-ICMT-11, a caspase-3/7-specific positron emission tomography (PET) radiotracer, in macrophage cell cultures and in an animal model of pulmonary TB that closely resembles human disease.ResultsCells infected with M. tuberculosis and treated with cisplatin accumulated [18F]-ICMT-11 at significantly higher levels compared with that of controls, which correlated with levels of caspase-3/7 activity. Infected mice treated with cisplatin with increased caspase-3/7 activity also had a higher [18F]-ICMT-11 PET signal compared with that of untreated infected animals.Conclusions[18F]-ICMT-11 PET could be used as a noninvasive approach to measure intralesional pro-apoptotic responses in situ in pulmonary TB models and support the development of pro-apoptotic host-directed therapies for TB.
Aboagye E, Sharma R, Inglese M, et al., 2020, Monitoring response to transarterial chemoembolization in hepatocellular carcinoma using 18F-Fluorothymidine Positron Emission Tomography, The Journal of Nuclear Medicine, Vol: 61, Pages: 1743-1748, ISSN: 0161-5505
Accurate disease monitoring is essential following transarterial chemoembolization (TACE) in hepatocellular carcinoma (HCC) due to potential for profound adverse event and large variation in survival outcome. Post-treatment changes on conventional imaging can confound determination of residual/recurrent disease, magnifying the clinical challenge. Based on increased expression of thymidylate synthase (TYMS), thymidine kinase-1 (TK-1) and SLC29A1 (Equilibrative nucleoside transporter 1, ENT1) in HCC compared with liver tissue, we conducted a proof of concept study evaluating the efficacy of 18F-fluorothymidine (18F-FLT)-PET to assess response to TACE. As previous PET studies in HCC have been hampered by high background liver signal, we investigated if a temporal-intensity voxel-clustering (“Kinetic Spatial Filtering”) (KSF) improved lesion detection. Methods: A tissue microarray (TMA) was built from 36 HCC samples and matched surrounding cirrhotic tissue and was stained for thymidine kinase-1 (TK-1). A prospective study was conducted; eighteen patients with a diagnosis of HCC by American Association for the Study of Liver Diseases criteria (AALSD) who were eligible to treatment with TACE were enrolled. Patients underwent baseline conventional imaging and dynamic 18F-FLT-PET/KSF followed by TACE. Repeat imaging was performed 6-8 weeks post TACE. PET parameters were compared with modified-Response Evaluation in Solid Tumours (mRECIST) enhancement-based criteria. Results: Cancer Genome Atlas analysis revealed increased RNA expression of TYMS, TK-1 and SLC29A1 in HCC. TK-1 protein expression was significantly higher in HCC (p<0.05). The sensitivity of 18F-FLT-PET for baseline HCC detection was 73% (SUVmax of 9.7 ± 3.0; tumour to liver ratio of 1.2 ± 0.3). Application of KSF did not improve lesion detection. Lesion response following TACE by mRECIST criteria was 58% (14 patients with 24 lesions). A 30% reduction in mean 18F-FLT-PET uptake was o
Ferris T, Carroll L, Jenner S, et al., 2020, Use of radioiodine in nuclear medicine-A brief overview, JOURNAL OF LABELLED COMPOUNDS & RADIOPHARMACEUTICALS, Vol: 64, Pages: 92-108, ISSN: 0362-4803
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