Prospective study evaluating the relative sensitivity of 18F-NaF PET/CT for detecting skeletal metastases from renal cell carcinoma in comparison to multidetector CT and 99mTc-MDP bone scintigraphy, using an adaptive trial design.

BACKGROUND: The detection of occult bone metastases is a key factor in determining the management of patients with renal cell carcinoma (RCC), especially when curative surgery is considered. This prospective study assessed the sensitivity of (18)F-labelled sodium fluoride in conjunction with positron emission tomography/computed tomography ((18)F-NaF PET/CT) for detecting RCC bone metastases, compared with conventional imaging by bone scintigraphy or CT. PATIENTS AND METHODS: An adaptive two-stage trial design was utilized, which was stopped after the first stage due to statistical efficacy. Ten patients with stage IV RCC and bone metastases were imaged with (18)F-NaF PET/CT and (99m)Tc-labelled methylene diphosphonate ((99m)Tc-MDP) bone scintigraphy including pelvic single photon emission computed tomography (SPECT). Images were reported independently by experienced radiologists and nuclear medicine physicians using a 5-point scoring system. RESULTS: Seventy-seven lesions were diagnosed as malignant: 100% were identified by (18)F-NaF PET/CT, 46% by CT and 29% by bone scintigraphy/SPECT. Standard-of-care imaging with CT and bone scintigraphy identified 65% of the metastases reported by (18)F-NaF PET/CT. On an individual patient basis, (18)F-NaF PET/CT detected more RCC metastases than (99m)Tc-MDP bone scintigraphy/SPECT or CT alone (P = 0.007). The metabolic volumes, mean and maximum standardized uptake values (SUV mean and SUV max) of the malignant lesions were significantly greater than those of the benign lesions (P < 0.001). CONCLUSIONS: (18)F-NaF PET/CT is significantly more sensitive at detecting RCC skeletal metastases than conventional bone scintigraphy or CT. The detection of occult bone metastases could greatly alter patient management, particularly in the context when standard-of-care imaging is negative for skeletal metastases.This work was supported by Cancer Research UK [grant number C19212/A16628]. The authors also received research support from the National Institute of Health Research Cambridge Biomedical Research Centre, Engineering and Physical Sciences Research Council Imaging Centre in Cambridge and Manchester, and the Cambridge Experimental Cancer Medicine Centre. The research has also been partly funded by a generous donation from the family and friends of a patient.This is the final version of the article. It first appeared from Oxford University Press via http://dx.doi.org/10.1093/annonc/mdv28

Localisation of an occult thyrotropinoma with 11^{11}C-methionine PET-CT before and after somatostatin analogue therapy

A 75-year-old woman presented to her local endocrine service with tiredness, palpitations, and enlargement of a longstanding goitre. Unexpectedly, her thyrotropin (thyroid-stimulating hormone [TSH]) concentration was not suppressed (6·3 mU/L; reference range 0·35–5·5) despite raised concentrations of thyroid hormones (free thyroxine [T$_{4}$] 89·1 pmol/L [reference range 10–19·8]; free triiodothyronine [T$_{3}$] 11·7 pmol/L [3·0–6·5]). After exclusion of laboratory assay interference, a thyrotropin-releasing hormone test showed an attenuated response (TSH at 0 min was 6·1 mU/L, at 20 min was 6·8 mU/L, and at 60 min was 8·5 mU/L), raising suspicion of a thyrotropinoma (also known as TSHoma). However, pituitary MRI was normal. The patient was referred to our centre for further assessment. On repeat MRI, the pituitary gland showed mild asymmetry (right larger than left; figure A). Functional imaging with 11C-methionine ($^{11}$C-Met) PET-CT revealed intense tracer uptake (denoting active peptide synthesis) on the right side of the sella (red hot spot in figure A). Treatment with a depot somatostatin analogue (SSA) led to resolution of symptoms and normalisation of thyroid function (TSH 0·6 mU/L, free T$_{4}$ 12·5 pmol/L, and free T$_{3}$ 3·8 pmol/L). Repeat $^{11}$C-Met PET-CT showed absence of the right-sided focal hot spot (figure B). 14 months into treatment, the patient had several hypoglycaemic episodes, which resolved after discontinuation of SSA. However, thyrotoxicosis recurred (TSH 4·3 mU/L, free T$_{4}$ 38·1 pmol/L, free T$_{3}$ 11·6 pmol/L), and repeat $^{11}$C-Met PET-CT revealed the reappearance of the right-sided hot spot (figure C). During pituitary surgery, a microthyrotropinoma was resected from the right side of the gland (figure D). The patient remains in clinical and biochemical remission more than 12 months after surgery and has normal pituitary function

Dynamic phenotypic heterogeneity and the evolution of multiple RNA subtypes in Hepatocellular Carcinoma: the PLANET study

Intra-tumor heterogeneity (ITH) is a key challenge in cancer treatment, but previous studies have focused mainly on the genomic alterations without exploring phenotypic (transcriptomic and immune) heterogeneity. Using one of the largest prospective surgical cohorts for Hepatocellular Carcinoma (HCC) with multi-region sampling, we sequenced whole genomes and paired transcriptomes from 67 HCC patients (331 samples). We found that while genomic ITH was rather constant across TNM stages, phenotypic ITH had a very different trajectory and quickly diversified in stage II patients. Most strikingly, 30% patients were found to contain more than one transcriptomic subtype within a single tumor. Such phenotypic ITH was found to be much more informative in predicting patient survival than genomic ITH and explains the poor efficacy of single-target systemic therapies in HCC. Taken together, we not only revealed an unprecedentedly dynamic landscape of phenotypic heterogeneity in HCC, but also highlighted the importance of studying phenotypic evolution across cancer types

Impact of solitary pulmonary nodule size on qualitative and quantitative assessment using 18F-fluorodeoxyglucose PET/CT: the SPUTNIK trial

Purpose: To compare qualitative and semi-quantitative PET/CT criteria, and the impact of nodule size on the diagnosis of solitary pulmonary nodules in a prospective multicentre trial. / Methods: Patients with an SPN on CT ≥ 8 and ≤ 30 mm were recruited to the SPUTNIK trial at 16 sites accredited by the UK PET Core Lab. Qualitative assessment used a five-point ordinal PET-grade compared to the mediastinal blood pool, and a combined PET/CT grade using the CT features. Semi-quantitative measures included SUVmax of the nodule, and as an uptake ratio to the mediastinal blood pool (SURBLOOD) or liver (SURLIVER). The endpoints were diagnosis of lung cancer via biopsy/histology or completion of 2-year follow-up. Impact of nodule size was analysed by comparison between nodule size tertiles. / Results: Three hundred fifty-five participants completed PET/CT and 2-year follow-up, with 59% (209/355) malignant nodules. The AUCs of the three techniques were SUVmax 0.87 (95% CI 0.83;0.91); SURBLOOD 0.87 (95% CI 0.83; 0.91, p = 0.30 versus SUVmax); and SURLIVER 0.87 (95% CI 0.83; 0.91, p = 0.09 vs. SUVmax). The AUCs for all techniques remained stable across size tertiles (p > 0.1 for difference), although the optimal diagnostic threshold varied by size. For nodules  16 mm, an SUVmax ≥ 3.6 or visual PET uptake greater than the mediastinum was the most accurate. / Conclusion: In this multicentre trial, SUVmax was the most accurate technique for the diagnosis of solitary pulmonary nodules. Diagnostic thresholds should be altered according to nodule size. / Trial registration: ISRCTN - ISRCTN30784948. ClinicalTrials.gov - NCT0201306

Statistical and integrative system-level analysis of DNA methylation data

Epigenetics plays a key role in cellular development and function. Alterations to the epigenome are thought to capture and mediate the effects of genetic and environmental risk factors on complex disease. Currently, DNA methylation is the only epigenetic mark that can be measured reliably and genome-wide in large numbers of samples. This Review discusses some of the key statistical challenges and algorithms associated with drawing inferences from DNA methylation data, including cell-type heterogeneity, feature selection, reverse causation and system-level analyses that require integration with other data types such as gene expression, genotype, transcription factor binding and other epigenetic information