Purpose-Tumor hypoxia fuels an aggressive tumor phenotype and confers resistance to anticancer treatments. We conducted a clinical trial to determine whether the antimalarial drug atovaquone, a known mitochondrial inhibitor, reduces hypoxia in non-small cell lung cancer (NSCLC).Patients and methods-Patients with NSCLC scheduled for surgery were recruited sequentially into two cohorts: Cohort 1 received oral atovaquone at the standard clinical dose 750 mg twice-daily, whilst Cohort 2 did not. Primary imaging endpoint was change in tumor hypoxic volume (HV) measured by hypoxia PET-CT. Inter-cohort comparison of hypoxia gene expression signatures using RNA sequencing from resected tumors was performed.Results-Thirty patients were evaluable for hypoxia PET-CT analysis, 15 per cohort. Median treatment duration was 12 days. Eleven (73.3%) atovaquone-treated patients had meaningful HV reduction with median change −28.0% [95% confidence interval (CI), −58.2 to −4.4]. In contrast, median change in untreated patients was +15.5% (95% CI, −6.5 to 35.5). Linear regression estimated the expected mean HV was 55% (95% CI, 24% to 74%) lower in Cohort 1 compared to Cohort 2 (p=0.004), adjusting for cohort, tumor volume and baseline HV. A key pharmacodynamic endpoint was reduction in hypoxia regulated genes, which were significantly downregulated in atovaquone-treated tumors. Data from multiple additional measures of tumor hypoxia and perfusion are presented. No atovaquone-related adverse events were reported.Conclusions-This is the first clinical evidence that targeting tumor mitochondrial metabolism can reduce hypoxia and produce relevant anti-tumor effects at the mRNA level. Repurposing atovaquone for this purpose may improve treatment outcomes for NSCLC.

Background Pre-clinically, phosphoinositide 3-kinase (PI3K) inhibition radiosensitises tumours by increasing intrinsic radiosensitivity and by reducing tumour hypoxia. We assessed whether buparlisib, a class 1 PI3K inhibitor, can be safely combined with radiotherapy in patients with non-small cell lung carcinoma (NSCLC) and investigated its effect on tumour hypoxia. Methods This was a 3 + 3 dose escalation and dose expansion phase I trial in patients with advanced NSCLC. Buparlisib dose levels were 50 mg, 80 mg and 100 mg once daily orally for 2 weeks, with palliative thoracic radiotherapy (20 Gy in 5 fractions) delivered during week 2. Tumour hypoxic volume (HV) was measured using 18 F-fluoromisonidazole positron-emission tomography–computed tomography at baseline and following 1 week of buparlisib. Results Twenty-one patients were recruited with 9 patients evaluable for maximum tolerated dose (MTD) analysis. No dose-limiting toxicity was reported; therefore, 100 mg was declared the MTD, and 10 patients received this dose in the expansion phase. Ninety-four percent of treatment-related adverse events were ≤grade 2 with fatigue (67%), nausea (24%) and decreased appetite (19%) most common per patient. One serious adverse event (grade 3 hypoalbuminaemia) was possibly related to buparlisib. No unexpected radiotherapy toxicity was reported. Ten (67%) of 15 patients evaluable for imaging analysis were responders with 20% median reduction in HV at the MTD. Conclusion This is the first clinical trial to combine a PI3K inhibitor with radiotherapy in NSCLC and investigate the effects of PI3K inhibition on tumour hypoxia. This combination was well tolerated and PI3K inhibition reduced hypoxia, warranting investigation into whether this novel class of radiosensitisers can improve radiotherapy outcomes.

Tumour hypoxia is a well-recognised barrier to anti-cancer therapy and represents one of the best validated targets in oncology. Previous attempts to tackle hypoxia have focussed primarily on increasing tumour oxygen supply; however, clinical studies using this approach have yielded only modest clinical benefit, with often significant toxicity and practical limitations. Therefore, there are currently no anti-hypoxia treatments in widespread clinical use. As an emerging alternative strategy, we discuss the relevance of inhibiting tumour oxygen metabolism to alleviate hypoxia and highlight recently initiated clinical trials using this approach.

BackgroundTo determine the relative abilities of compartment models to describe time-courses of 18F-fluoromisonidazole (FMISO) tumor uptake in patients with advanced stage non-small cell lung cancer (NSCLC) imaged using dynamic positron emission tomography (dPET), and study correlations between values of the blood flow-related parameter K1 obtained from fits of the models and an independent blood flow measure obtained from perfusion CT (pCT).NSCLC patients had a 45-min dynamic FMISO PET/CT scan followed by two static PET/CT acquisitions at 2 and 4-h post-injection. Perfusion CT scanning was then performed consisting of a 45-s cine CT.Reversible and irreversible two-, three- and four-tissue compartment models were fitted to 30 time-activity-curves (TACs) obtained for 15 whole tumor structures in 9 patients, each imaged twice. Descriptions of the TACs provided by the models were compared using the Akaike and Bayesian information criteria (AIC and BIC) and leave-one-out cross-validation. The precision with which fitted model parameters estimated ground-truth uptake kinetics was determined using statistical simulation techniques. Blood flow from pCT was correlated with K1 from PET kinetic models in addition to FMISO uptake levels.ResultsAn irreversible three-tissue compartment model provided the best description of whole tumor FMISO uptake time-courses according to AIC, BIC, and cross-validation scores totaled across the TACs. The simulation study indicated that this model also provided more precise estimates of FMISO uptake kinetics than other two- and three-tissue models.The K1 values obtained from fits of the irreversible three-tissue model correlated strongly with independent blood flow measurements obtained from pCT (Pearson r coefficient = 0.81). The correlation from the irreversible three-tissue model (r = 0.81) was stronger than that from than K1 values obtained from fits of a two-tissue compartment model (r = 0.68), or FMISO uptake levels in static images taken at time-points from tracer injection through to 4 h later (maximum at 2 min, r = 0.70).ConclusionsTime-courses of whole tumor FMISO uptake by advanced stage NSCLC are described best by an irreversible three-tissue compartment model. The K1 values obtained from fits of the irreversible three-tissue model correlated strongly with independent blood flow measurements obtained from perfusion CT (r = 0.81).Electronic supplementary materialThe online version of this article (10.1186/s13550-018-0430-4) contains supplementary material, which is available to authorized users.

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Background Tumour hypoxia promotes an aggressive tumour phenotype and enhances resistance to anticancer treatments. Following the recent observation that the mitochondrial inhibitor atovaquone increases tumour oxygenation in NSCLC, we sought to assess whether atovaquone affects tumour subregions differently depending on their level of hypoxia. Methods Patients with resectable NSCLC participated in the ATOM trial (NCT02628080). Cohort 1 (n = 15) received atovaquone treatment, whilst cohort 2 (n = 15) did not. Hypoxia-related metrics, including change in mean tumour-to-blood ratio, tumour hypoxic volume, and fraction of hypoxic voxels, were assessed using hypoxia PET imaging. Tumours were divided into four subregions or distance categories: edge, outer, inner, and centre, using MATLAB. Results Atovaquone-induced reduction in tumour hypoxia mostly occurred in the inner and outer tumour subregions, and to a lesser extent in the centre subregion. Atovaquone did not seem to act in the edge subregion, which was the only tumour subregion that was non-hypoxic at baseline. Notably, the most intensely hypoxic tumour voxels, and therefore the most radiobiologically resistant areas, were subject to the most pronounced decrease in hypoxia in the different subregions. Conclusions This study provides insights into the action of atovaquone in tumour subregions that help to better understand its role as a novel tumour radiosensitiser. Trial registration: ClinicalTrials.gov, NCT0262808. Registered 11th December 2015, https://clinicaltrials.gov/ct2/show/NCT02628080

Tumor heterogeneity can be assessed quantitatively by analyzing dynamic contrast-enhanced imaging modalities potentially leading to improvement in the diagnosis and treatment of cancer, for example of the lung. However, the acquisition of standard lung sequences is often compromised by irregular breathing motion artefacts, resulting in unsystematic errors when estimating tissue perfusion parameters. In this work, we illustrate implicit deformable image registration that integrates the Demons algorithm using the local correlation coefficient as a similarity measure, and locally adaptive regularization that enables incorporation of both spatial sliding motions and irregular temporal motion patterns. We also propose a practical numerical approximation of the regularization model to improve both computational time and registration accuracy, which are important when analyzing long clinical sequences. Our quantitative analysis of 4D lung Computed Tomography and Computed Tomography Perfusion scans from clinical lung trial shows significant improvement over state-of-the-art pairwise registration approaches.

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