The Cancer Hub Approach for Upper Gastrointestinal Surgery During COVID-19 Pandemic: Outcomes from a UK Cancer Centre.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic caused unprecedented disruption to global healthcare delivery. In England, the majority of elective surgery was postponed or cancelled to increase intensive care capacity. Our unit instituted the 'RM Partners Cancer Hub' at the Royal Marsden Hospital in London, to deliver ongoing cancer surgery in a 'COVID-lite' setting. This article describes the operational set-up and outcomes for upper gastrointestinal (UGI) cancer resections performed during this period. METHODS: From April 2020 to April 2021, the Royal Marsden Hospital formed the RM Partners Cancer Hub. This approach was designed to coordinate resources and provide as much oncological treatment as feasible for patients across the RM Partners West London Cancer Alliance. A UGI surgical case prioritisation strategy, along with strict infection control pathways and pre-operative screening protocols, was adopted. RESULTS: A total of 231 patients underwent surgery for confirmed or suspected UGI cancer during the RM Partners Cancer Hub, with 213 completed resections and combined 90-day mortality rate of 3.5%. Good short-term survival outcomes were demonstrated with 2-year disease free survival (DFS) and overall survival (OS) for oesophageal (70.8% and 72.9%), gastric (66.7% and 83.3%) and pancreatic cancer resections (68.0% and 88.0%). One patient who developed perioperative COVID-19 during the RM Partners Cancer Hub operation made a full recovery with no lasting clinical sequelae. CONCLUSION: Our experience demonstrates that the RM Partners Cancer Hub approach is a safe strategy for continuing upper gastrointestinal (GI) resectional surgery during future periods of healthcare service disruption.

The Diagnostic Accuracy of 18 F-FGD-PET/CT for Cancer of the Gallbladder: A Retrospective Study.

Background Gallbladder cancer has a poor prognosis and imaging can have variable diagnostic accuracy. We assessed the ability of preoperative 18 F-fluorodeoxyglucose positron emission tomography computed tomography ( 18 F-FDG-PET/CT) imaging to predict a postoperative histological diagnosis of gallbladder cancer. Method A retrospective analysis was undertaken in a cohort of patients, who had suspected gallbladder cancer on cross-sectional imaging and that underwent preoperative FDG-PET/CT scan. The discriminatory power of FDG-PET/CT was determined in receiver operator characteristic (ROC) analysis and diagnostic accuracy parameters were estimated at different thresholds of maximum standard unit value (SUV max ) . Results Twenty-two patients were included in the study; 7 had malignant and 15 benign diagnoses. There was no statistically significant difference between the measured SUV max between the two groups ( p = 0.71). With an area under the curve of 0.486, the ROC curve did not indicate any discriminatory power of FDG-PET/CT at any potential threshold of SUV max. Conclusion This study indicates that the diagnosis of primary gallbladder cancer cannot be accurately confirmed with FDG PET/CT scanning.

Auto-deconvolution and molecular networking of gas chromatography-mass spectrometry data.

We engineered a machine learning approach, MSHub, to enable auto-deconvolution of gas chromatography-mass spectrometry (GC-MS) data. We then designed workflows to enable the community to store, process, share, annotate, compare and perform molecular networking of GC-MS data within the Global Natural Product Social (GNPS) Molecular Networking analysis platform. MSHub/GNPS performs auto-deconvolution of compound fragmentation patterns via unsupervised non-negative matrix factorization and quantifies the reproducibility of fragmentation patterns across samples.

Cross-platform mass spectrometry annotation in breathomics of oesophageal-gastric cancer.

Disease breathomics is gaining importance nowadays due to its usefulness as non-invasive early cancer detection. Mass spectrometry (MS) technique is often used for analysis of volatile organic compounds (VOCs) associated with cancer in the exhaled breath but a long-standing challenge is the uncertainty in mass peak annotation for potential volatile biomarkers. This work describes a cross-platform MS strategy employing selected-ion flow tube mass spectrometry (SIFT-MS), high resolution gas chromatography-mass spectrometry (GC-MS) retrofitted with electron ionisation (EI) and GC-MS retrofitted with positive chemical ionisation (PCI) as orthogonal analytical approaches in order to provide facile identification of the oxygenated VOCs from breath of cancer patients. In addition, water infusion was applied as novel efficient PCI reagent in breathomics analysis, depicting unique diagnostic ions M+ or [M-17]+ for VOC identification. Identity confirmation of breath VOCs was deduced using the proposed multi-platform workflow, which reveals variation in breath oxygenated VOC composition of oesophageal-gastric (OG) cancer patients with dominantly ketones, followed by aldehydes, alcohols, acids and phenols in decreasing order of relative abundance. Accurate VOC identification provided by cross-platform approach would be valuable for the refinement of diagnostic VOC models and the understanding of molecular drivers of VOC production.

Optimisation of sampling parameters for standardised exhaled breath sampling.

The lack of standardisation of breath sampling is a major contributing factor to the poor repeatability of results and hence represents a barrier to the adoption of breath tests in clinical practice. On-line and bag breath sampling have advantages but do not suit multicentre clinical studies whereas storage and robust transport are essential for the conduct of wide-scale studies. Several devices have been developed to control sampling parameters and to concentrate volatile organic compounds (VOCs) onto thermal desorption (TD) tubes and subsequently transport those tubes for laboratory analysis. We conducted three experiments to investigate (i) the fraction of breath sampled (whole versus lower expiratory exhaled breath); (ii) breath sample volume (125, 250, 500 and 1000 ml); and (iii) breath sample flow rate (400, 200, 100 and 50 ml min-1). The target VOCs were acetone and potential volatile biomarkers for oesophago-gastric cancer belonging to the aldehyde, fatty acids and phenol chemical classes. We also examined the collection execution time and the impact of environmental contamination. The experiments showed that the use of exhaled breath-sampling devices requires the selection of optimum sampling parameters. The increase in sample volume has improved the levels of VOCs detected. However, the influence of the fraction of exhaled breath and the flow rate depends on the target VOCs measured. The concentration of potential volatile biomarkers for oesophago-gastric cancer was not significantly different between the whole and lower airway exhaled breath. While the recovery of phenols and acetone from TD tubes was lower when breath sampling was performed at a higher flow rate, other VOCs were not affected. A dedicated 'clean air supply' reduces the contamination from ambient air, but the breath collection device itself can be a source of contaminants. In clinical studies using VOCs to elicit potential biomarkers of gastro-oesophageal cancer, the optimum parameters are 500 mls sample volume of whole breath with a flow rate of 200 ml min-1.

Enhanced recovery protocols after oesophagectomy.

The feasibility and safety of enhanced recovery protocols (ERP) have been demonstrated in a large number of surgical specialties. Several studies have shown improved post-operative outcomes and economic benefit from the use of ERPs in oesophageal cancer surgery. However, these improvements are not always translated more widely into clinical practice due to variation in protocols, poor compliance and failure to implement a robust implementation strategy. ERP implementation strategies should reflect the fact that these are complex interventions that are influenced by a wide range of social, organizational and cultural factors.