Radiotheranostics in oncology: Making precision medicine possible.

A quintessential setting for precision medicine, theranostics refers to a rapidly evolving field of medicine in which disease is diagnosed followed by treatment of disease-positive patients using tools for the therapy identical or similar to those used for the diagnosis. Against the backdrop of only-treat-when-visualized, the goal is a high therapeutic index with efficacy markedly surpassing toxicity. Oncology leads the way in theranostics innovation, where the approach has become possible with the identification of unique proteins and other factors selectively expressed in cancer versus healthy tissue, advances in imaging technology able to report these tissue factors, and major understanding of targeting chemicals and nanodevices together with methods to attach labels or warheads for imaging and therapy. Radiotheranostics-using radiopharmaceuticals-is becoming routine in patients with prostate cancer and neuroendocrine tumors who express the proteins PSMA (prostate-specific membrane antigen) and SSTR2 (somatostatin receptor 2), respectively, on their cancer. The palpable excitement in the field stems from the finding that a proportion of patients with large metastatic burden show complete and partial responses, and this outcome is catalyzing the search for more radiotheranostics approaches. Not every patient will benefit from radiotheranostics; but, for those who cross the target-detected line, the likelihood of response is very high.

Radiomics and artificial intelligence for precision medicine in lung cancer treatment.

Lung cancer is the leading cause of cancer-related deaths worldwide. It exhibits, at the mesoscopic scale, phenotypic characteristics that are generally indiscernible to the human eye but can be captured non-invasively on medical imaging as radiomic features, which can form a high dimensional data space amenable to machine learning. Radiomic features can be harnessed and used in an artificial intelligence paradigm to risk stratify patients, and predict for histological and molecular findings, and clinical outcome measures, thereby facilitating precision medicine for improving patient care. Compared to tissue sampling-driven approaches, radiomics-based methods are superior for being non-invasive, reproducible, cheaper, and less susceptible to intra-tumoral heterogeneity. This review focuses on the application of radiomics, combined with artificial intelligence, for delivering precision medicine in lung cancer treatment, with discussion centered on pioneering and groundbreaking works, and future research directions in the area.

Weibull parametric model for survival analysis in women with endometrial cancer using clinical and T2-weighted MRI radiomic features.

BACKGROUND: Semiparametric survival analysis such as the Cox proportional hazards (CPH) regression model is commonly employed in endometrial cancer (EC) study. Although this method does not need to know the baseline hazard function, it cannot estimate event time ratio (ETR) which measures relative increase or decrease in survival time. To estimate ETR, the Weibull parametric model needs to be applied. The objective of this study is to develop and evaluate the Weibull parametric model for EC patients' survival analysis. METHODS: Training (n = 411) and testing (n = 80) datasets from EC patients were retrospectively collected to investigate this problem. To determine the optimal CPH model from the training dataset, a bi-level model selection with minimax concave penalty was applied to select clinical and radiomic features which were obtained from T2-weighted MRI images. After the CPH model was built, model diagnostic was carried out to evaluate the proportional hazard assumption with Schoenfeld test. Survival data were fitted into a Weibull model and hazard ratio (HR) and ETR were calculated from the model. Brier score and time-dependent area under the receiver operating characteristic curve (AUC) were compared between CPH and Weibull models. Goodness of the fit was measured with Kolmogorov-Smirnov (KS) statistic. RESULTS: Although the proportional hazard assumption holds for fitting EC survival data, the linearity of the model assumption is suspicious as there are trends in the age and cancer grade predictors. The result also showed that there was a significant relation between the EC survival data and the Weibull distribution. Finally, it showed that Weibull model has a larger AUC value than CPH model in general, and it also has smaller Brier score value for EC survival prediction using both training and testing datasets, suggesting that it is more accurate to use the Weibull model for EC survival analysis. CONCLUSIONS: The Weibull parametric model for EC survival analysis allows simultaneous characterization of the treatment effect in terms of the hazard ratio and the event time ratio (ETR), which is likely to be better understood. This method can be extended to study progression free survival and disease specific survival. TRIAL REGISTRATION: ClinicalTrials.gov NCT03543215, https://clinicaltrials.gov/ , date of registration: 30th June 2017.

Modulation of EGFR Activity by Molecularly Imprinted Polymer Nanoparticles Targeting Intracellular Epitopes.

In recent years, molecularly imprinted polymer nanoparticles (nanoMIPs) have proven to be an attractive alternative to antibodies in diagnostic and therapeutic applications. However, several key questions remain: how suitable are intracellular epitopes as targets for nanoMIP binding? And to what extent can protein function be modulated via targeting specific epitopes? To investigate this, three extracellular and three intracellular epitopes of epidermal growth factor receptor (EGFR) were used as templates for the synthesis of nanoMIPs which were then used to treat cancer cells with different expression levels of EGFR. It was observed that nanoMIPs imprinted with epitopes from the intracellular kinase domain and the extracellular ligand binding domain of EGFR caused cells to form large foci of EGFR sequestered away from the cell surface, caused a reduction in autophosphorylation, and demonstrated effects on cell viability. Collectively, this suggests that intracellular domain-targeting nanoMIPs can be a potential new tool for cancer therapy.

Radiomics-based decision support tool assists radiologists in small lung nodule classification and improves lung cancer early diagnosis.

BACKGROUND: Methods to improve stratification of small (≤15 mm) lung nodules are needed. We aimed to develop a radiomics model to assist lung cancer diagnosis. METHODS: Patients were retrospectively identified using health records from January 2007 to December 2018. The external test set was obtained from the national LIBRA study and a prospective Lung Cancer Screening programme. Radiomics features were extracted from multi-region CT segmentations using TexLab2.0. LASSO regression generated the 5-feature small nodule radiomics-predictive-vector (SN-RPV). K-means clustering was used to split patients into risk groups according to SN-RPV. Model performance was compared to 6 thoracic radiologists. SN-RPV and radiologist risk groups were combined to generate "Safety-Net" and "Early Diagnosis" decision-support tools. RESULTS: In total, 810 patients with 990 nodules were included. The AUC for malignancy prediction was 0.85 (95% CI: 0.82-0.87), 0.78 (95% CI: 0.70-0.85) and 0.78 (95% CI: 0.59-0.92) for the training, test and external test datasets, respectively. The test set accuracy was 73% (95% CI: 65-81%) and resulted in 66.67% improvements in potentially missed [8/12] or delayed [6/9] cancers, compared to the radiologist with performance closest to the mean of six readers. CONCLUSIONS: SN-RPV may provide net-benefit in terms of earlier cancer diagnosis.

Variational Bayes for high-dimensional proportional hazards models with applications within gene expression.

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 sparse variational Bayes. Our method, based on a mean-field variational approximation, overcomes the high computational cost of Markov chain Monte Carlo, 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). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Feasibility of [18F]fluoropivalate hybrid PET/MRI for imaging lower and higher grade glioma: a prospective first-in-patient pilot study.

PURPOSE: MRI and PET are used in neuro-oncology for the detection and characterisation of lesions for malignancy to target surgical biopsy and to plan surgical resections or stereotactic radiosurgery. The critical role of short-chain fatty acids (SCFAs) in brain tumour biology has come to the forefront. The non-metabolised SCFA radiotracer, [18F]fluoropivalate (FPIA), shows low background signal in most tissues except eliminating organs and has appropriate human dosimetry. Tumour uptake of the radiotracer is, however, unknown. We investigated the uptake characteristics of FPIA in this pilot PET/MRI study. METHODS: Ten adult glioma subjects were identified based on radiological features using standard-of-care MRI prior to any surgical intervention, with subsequent histopathological confirmation of glioma subtype and grade (lower-grade - LGG - and higher-grade - HGG - patients). FPIA was injected as an intravenous bolus injection (range 342-368 MBq), and dynamic PET and MRI data were acquired simultaneously over 66 min. RESULTS: All patients tolerated the PET/MRI protocol. Three patients were reclassified following resection and histology. Tumour maximum standardised uptake value (SUVmax,60) increased in the order LGG (WHO grade 2) < HGG (WHO grade 3) < HGG (WHO grade 4). The net irreversible solute transfer, Ki, and influx rate constant, K1, were significantly higher in HGG (p < 0.05). Of the MRI variables studied, DCE-MRI-derived extravascular-and-extracellular volume fraction (ve) was high in tumours of WHO grade 4 compared with other grades (p < 0.05). SLC25A20 protein expression was higher in HGG compared with LGG. CONCLUSION: Tumoural FPIA PET uptake is higher in HGG compared to LGG. This study supports further investigation of FPIA PET/MRI for brain tumour imaging in a larger patient population. CLINICAL TRIAL REGISTRATION: Clinicaltrials.gov, NCT04097535.

An Integrated Clinical-MR Radiomics Model to Estimate Survival Time in Patients With Endometrial Cancer.

BACKGROUND: Determination of survival time in women with endometrial cancer using clinical features remains imprecise. Features from MRI may improve the survival estimation allowing improved treatment planning. PURPOSE: To identify clinical features and imaging signatures on T2-weighted MRI that can be used in an integrated model to estimate survival time for endometrial cancer subjects. STUDY TYPE: Retrospective. POPULATION: Four hundred thirteen patients with endometrial cancer as training (N = 330, 66.41 ± 11.42 years) and validation (N = 83, 67.60 ± 11.89 years) data and an independent set of 82 subjects as testing data (63.26 ± 12.38 years). FIELD STRENGTH/SEQUENCE: 1.5-T and 3-T scanners with sagittal T2-weighted spin echo sequence. ASSESSMENT: Tumor regions were manually segmented on T2-weighted images. Features were extracted from segmented masks, and clinical variables including age, cancer histologic grade and risk score were included in a Cox proportional hazards (CPH) model. A group least absolute shrinkage and selection operator method was implemented to determine the model from the training and validation datasets. STATISTICAL TESTS: A likelihood-ratio test and decision curve analysis were applied to compare the models. Concordance index (CI) and area under the receiver operating characteristic curves (AUCs) were calculated to assess the model. RESULTS: Three radiomic features (two image intensity and volume features) and two clinical variables (age and cancer grade) were selected as predictors in the integrated model. The CI was 0.797 for the clinical model (includes clinical variables only) and 0.818 for the integrated model using training and validation datasets, the associated mean AUC value was 0.805 and 0.853. Using the testing dataset, the CI was 0.792 and 0.882, significantly different and the mean AUC was 0.624 and 0.727 for the clinical model and integrated model, respectively. DATA CONCLUSION: The proposed CPH model with radiomic signatures may serve as a tool to improve estimated survival time in women with endometrial cancer. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 2.

Bench to Bedside Development of [18F]Fluoromethyl-(1,2-2H4)choline ([18F]D4-FCH).

Malignant transformation is characterised by aberrant phospholipid metabolism of cancers, associated with the upregulation of choline kinase alpha (CHKα). Due to the metabolic instability of choline radiotracers and the increasing use of late-imaging protocols, we developed a more stable choline radiotracer, [18F]fluoromethyl-[1,2-2H4]choline ([18F]D4-FCH). [18F]D4-FCH has improved protection against choline oxidase, the key choline catabolic enzyme, via a 1H/2D isotope effect, together with fluorine substitution. Due to the promising mechanistic and safety profiles of [18F]D4-FCH in vitro and preclinically, the radiotracer has transitioned to clinical development. [18F]D4-FCH is a safe positron emission tomography (PET) tracer, with a favourable radiation dosimetry profile for clinical imaging. [18F]D4-FCH PET/CT in lung and prostate cancers has shown highly heterogeneous intratumoral distribution and large lesion variability. Treatment with abiraterone or enzalutamide in metastatic castrate-resistant prostate cancer patients elicited mixed responses on PET at 12-16 weeks despite predominantly stable radiological appearances. The sum of the weighted tumour-to-background ratios (TBRs-wsum) was associated with the duration of survival.

Validation analysis of the novel imaging-based prognostic radiomic signature in patients undergoing primary surgery for advanced high-grade serous ovarian cancer (HGSOC).

BACKGROUND: Predictive 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. METHODS: RPV 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. RESULTS: The 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). CONCLUSIONS: RPV 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.

Highly effective liquid and solid phase extraction methods to concentrate radioiodine isotopes for radioiodination chemistry.

Radioactive iodine isotopes play a pivotal role in radiopharmaceuticals. Large-scale production of multi-patient dose of radioiodinated nuclear medicines requires high concentration of radioiodine. We demonstrate that tetrabutylammonium chloride and methyltrioctylamonium chloride are effective phase transfer reagents to concentrate iodide-124, iodide-125 and iodide-131 from the corresponding commercial water solutions. The resulting concentrated radioiodide, in the presence of either phase transfer reagent, does not hamper the chemical reactivity of aqueous radioiodide in the copper (II)-mediated one-pot three-component click chemistry to produce radioiodinated iodotriazoles.

Discovery of a biomarker candidate for surgical stratification in high-grade serous ovarian cancer.

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.

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.

PURPOSE: Cervical 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. METHODS: 81 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. RESULTS: For 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 mean percentage difference from the MRI volume of - 19.1 and - 18.2% for readers 1 and 2, respectively. 21% required manual adjustment for both readers. CONCLUSION: MTV30 provides the optimal correlation with MRI volume taking into consideration the excellent inter-reader agreement and less requirement for manual adjustment.

Use of radioiodine in nuclear medicine-A brief overview.

Radioiodines have a long history in nuclear medicine. Herein, we discuss the production, properties and applications of these versatile iodine-based imaging and theragnostic agents. There are 38 isotopes of iodine (I) including one stable form (127 I). The most common radionuclides used in medical imaging and treatment, including Iodine-123 (123 I), Iodine-124 (124 I), Iodine-125 (125 I) and Iodine-131 (131 I), are discussed in this review.

Lactic acidosis induces resistance to the pan-Akt inhibitor uprosertib in colon cancer cells.

BACKGROUND: Akt signalling regulates glycolysis and drives the Warburg effect in cancer, thus decreased glucose utilisation is a pharmacodynamic marker of Akt inhibition. However, cancer cells can utilise alternative nutrients to glucose for energy such as lactate, which is often elevated in tumours together with increased acidity. We therefore hypothesised that lactic acidosis may confer resistance to Akt inhibition. METHODS: The effect of the pan-Akt inhibitor uprosertib (GSK2141795), on HCT116 and LS174T colon cancer cells was evaluated in the presence and absence of lactic acid in vitro. Expression of downstream Akt signalling proteins was determined using a phosphokinase array and immunoblotting. Metabolism was assessed using 1H nuclear magnetic resonance spectroscopy, stable isotope labelling and gas chromatography-mass spectrometry. RESULTS: Lactic acid-induced resistance to uprosertib was characterised by increased cell survival and reduced apoptosis. Uprosertib treatment reduced Akt signalling and glucose uptake irrespective of lactic acid supplementation. However, incorporation of lactate carbon and enhanced respiration was maintained in the presence of uprosertib and lactic acid. Inhibiting lactate transport or oxidative phosphorylation was sufficient to potentiate apoptosis in the presence of uprosertib. CONCLUSIONS: Lactic acidosis confers resistance to uprosertib, which can be reversed by inhibiting lactate transport or oxidative metabolism.

Clinical translation of 18F-fluoropivalate - a PET tracer for imaging short-chain fatty acid metabolism: safety, biodistribution, and dosimetry in fed and fasted healthy volunteers.

BACKGROUND: Fatty acids derived de novo or taken up from the extracellular space are an essential source of nutrient for cell growth and proliferation. Radiopharmaceuticals including 11C-acetate, and 18F-FAC (2-18F-fluoroacetate), have previously been used to study short-chain fatty acid (SCFA) metabolism. We developed 18F-fluoropivalate (18F-FPIA; 3-18F-fluoro-2,2-dimethylpropionic acid) bearing a gem-dimethyl substituent to assert metabolic stability for studying SCFA metabolism. We report the safety, biodistribution, and internal radiation dosimetry profile of 18F-FPIA in 24 healthy volunteers and the effect of dietary conditions. MATERIALS AND METHODS: Healthy volunteer male and female subjects were enrolled (n = 24), and grouped into 12 fed and 12 fasted. Non-esterified fatty acids (NEFA) and carnitine blood measurements were assessed. Subjects received 159.48 MBq (range, 47.31-164.66 MBq) of 18F-FPIA. Radiochemical purity was > 99%. Safety data were obtained during and 24 h after radiotracer administration. Subjects underwent detailed multiple whole-body PET/CT scanning with sampling of venous bloods for radioactivity and radioactive metabolite quantification. Regions of interest were defined to derive individual and mean organ residence times; effective dose was calculated using OLINDA 1.1. RESULTS: All subjects tolerated 18F-FPIA with no adverse events. Over 90% of radiotracer was present in plasma at 60 min post-injection. The organs receiving highest absorbed dose (in mGy/MBq) were the liver (0.070 ± 0.023), kidneys (0.043 ± 0.013), gallbladder wall (0.026 ± 0.003), and urinary bladder (0.021 ± 0.004); otherwise there was low tissue uptake. The calculated effective dose using mean organ residence times over all 24 subjects was 0.0154 mSv/MBq (SD ± 0.0010). No differences in biodistribution or dosimetry were seen in fed and fasted subjects, though systemic NEFA and carnitine levels reflected fasted and fed states. CONCLUSION: The favourable safety, imaging, and dosimetric profile makes 18F-FPIA a promising candidate radiotracer for tracing SCFA metabolism.

[18F]Fluciclatide PET as a biomarker of response to combination therapy of pazopanib and paclitaxel in platinum-resistant/refractory ovarian cancer.

BACKGROUND: Angiogenesis is a driver of platinum resistance in ovarian cancer. We assessed the effect of combination pazopanib and paclitaxel followed by maintenance pazopanib in patients with platinum-resistant/refractory ovarian cancer. Integrins αvß3 and αvß5 are both upregulated in tumor-associated vasculature. [18F]Fluciclatide is a novel PET tracer that has high affinity for integrins αvß3/5, and was used to assess the anti-angiogenic effect of pazopanib. PATIENTS AND METHODS: We conducted an open-label, phase Ib study in patients with platinum-resistant/refractory ovarian cancer. Patients received 1 week of single-agent pazopanib (800 mg daily) followed by combination therapy with weekly paclitaxel (80 mg/m2). Following completion of 18 weeks of combination therapy, patients continued with single-agent pazopanib until disease progression. Dynamic [18F]fluciclatide-PET imaging was conducted at baseline and after 1 week of pazopanib. Response (RECIST 1.1), toxicities, and survival outcomes were recorded. Circulating markers of angiogenesis were assessed with therapy. RESULTS: Fourteen patients were included in the intention-to-treat analysis. Complete and partial responses were seen in seven patients (54%). Median progression-free survival (PFS) was 10.63 months, and overall survival (OS) was 18.5 months. Baseline [18F]fluciclatide uptake was predictive of long PFS. Elevated baseline circulating angiopoietin and fibroblast growth factor (FGF) were predictive of greater reduction in SUV60,mean following pazopanib. Kinetic modeling of PET data indicated a reduction in K1 and Ki following pazopanib indicating reduced radioligand delivery and retention. CONCLUSIONS: Combination therapy followed by maintenance pazopanib is effective and tolerable in platinum-resistant/refractory ovarian cancer. [18F]Fluciclatide-PET uptake parameters predict clinical outcome with pazopanib therapy indicating an anti-angiogenic response.

Chemistry Considerations for the Clinical Translation of Oncology PET Radiopharmaceuticals.

Positron emission tomography (PET) has proven to be an invaluable tool in the staging and management of disease in oncology; however, [18F]fluorodeoxyglucose ([18F]FDG) remains the most widely used PET radiopharmaceutical despite the large financial investment in novel radiotracer development. We report our perspective and experience of translating radiopharmaceuticals into clinical studies, discussing the PET development pipeline from a chemistry perspective. We hope that, by identifying potential points of attrition along the pipeline and suggesting solutions to these problems, we may help others take their preclinical radiotracers into human studies. This review focuses primarily on the development of fluorine-18 radiopharmaceuticals, although the broader field of radiometal chemistry is considered where the translation journey is similar.

Radiological assessment of Peritoneal Cancer Index on preoperative CT in ovarian cancer is related to surgical outcome and survival.

PURPOSE: To evaluate whether Peritoneal Cancer Index (PCI) assessed on preoperative CT (CT-PCI) can be used as non-invasive preoperative tool to predict surgical outcome, disease-free survival (DFS) and overall survival (OS). MATERIALS AND METHODS: This is a retrospective, observational cohort study performed in a single institution. We considered all patients with diagnosis of ovarian cancer and preoperative CT, who had undergone upfront cytoreductive surgery between 2008 and 2010 and had post-operative clinical follow-up to December 2015. Two radiologists reviewed CT scans and assessed CT-PCI using Sugarbaker's diagram. We assessed the discriminatory capacity of the CT-PCI score on the surgical outcome by ROC curve analysis. DFS and OS were assessed by Kaplan-Meier nonparametric curves and by multivariable Cox-regression analysis. RESULTS: A total of 297 patients were included in the present analysis. CT-PCI was positively correlated with post-operative residual disease [odds ratio (OR) 1.04, 95% CI 1.01-1.07, p = 0.003]. ROC curve analysis returned AUC = 0.64 for the prediction of total macroscopic tumour clearance. In multivariable analysis, patients with no peritoneal disease seen on CT had a significantly longer DFS [Hazard ratio (HR) 2.28, p = 0.007]. Radiological serosal small bowel involvement was an independent predictor for shorter OS (HR 3.01, p = 0.002). CONCLUSION: Radiological PCI assessed on preoperative CT is associated with the probability of residual disease after cytoreductive surgery; however, it has low performance as a triage test to reliably identify patients who are likely to have complete cytoreductive surgery. CT-PCI is positively correlated with both DFS and OS and may be used as an independent prognostic factor, for example in patients with high FIGO stages.

Integrated analysis of multiple receptor tyrosine kinases identifies Axl as a therapeutic target and mediator of resistance to sorafenib in hepatocellular carcinoma.

BACKGROUND: Aberrant activation of Axl is implicated in the progression of hepatocellular carcinoma (HCC). We explored the biologic significance and preclinical efficacy of Axl inhibition as a therapeutic strategy in sorafenib-naive and resistant HCC. METHODS: We evaluated Axl expression in sorafenib-naive and resistant (SR) clones of epithelial (HuH7) and mesenchymal origin (SKHep-1) using antibody arrays and confirmed tissue expression. We tested the effect of Axl inhibition with RNA-interference and pharmacologically with R428 on a number of phenotypic assays. RESULTS: Axl mRNA overexpression in cell lines (n = 28) and RNA-seq tissue datasets (n = 373) correlated with epithelial-to-mesenchymal transition (EMT). Axl was overexpressed in HCC compared to cirrhosis and normal liver. We confirmed sorafenib resistance to be associated with EMT and enhanced motility in both HuH7-SR and SKHep-1-SR cells documenting a 4-fold increase in Axl phosphorylation as an adaptive feature of chronic sorafenib treatment in SKHep-1-SR cells. Axl inhibition reduced motility and enhanced sensitivity to sorafenib in SKHep-1SR cells. In patients treated with sorafenib (n = 40), circulating Axl levels correlated with shorter survival. CONCLUSIONS: Suppression of Axl-dependent signalling influences the transformed phenotype in HCC cells and contributes to adaptive resistance to sorafenib, providing a pre-clinical rationale for the development of Axl inhibitors as a measure to overcome sorafenib resistance.