ESTRO 2020 Abstract Book

S119 ESTRO 2020

program. CPMG: Carr-Purcell-Meiboom-Gill pulse program (to specifically supress macromolecule signals).

These results underline the importance of radiotherapy quality on outcome in terms of overall survival and locoregional tumor control. Especially OAR delination and non-adherence to OAR contraints were significantly related to outcome.

Poster Highlights: Poster highlights 7 RB: Novel radiobiological targets

PH-0232 Metabolic profiles do not recover to normal after pelvic IMRT for high-risk prostate cancer. M. Reis Ferreira 1 , C.J. Sands 2 , J.V. Li 3 , H.J.N. Andreyev 4 , J. Marchesi 5 , M.R. Lewis 2 , D. Dearnaley 6 1 Guys and St Thomas NHS Foundation Trust, Clinical Oncology, London, United Kingdom ; 2 Imperial College, National Phenome Centre, London, United Kingdom ; 3 Imperial College, Department of Surgery and Cancer, London, United Kingdom ; 4 United Lincolnshire Hospitals NHS Trust, Gastroenterology, Lincoln, United Kingdom ; 5 Imperial College, Department of Metabolism- Digestion and Reproduction, London, United Kingdom ; 6 Institute of Cancer Research, Department of Radiotherapy and Imaging, London, United Kingdom Purpose or Objective EBRT to the prostate and pelvic lymph nodes (PLNRT) is part of the curative treatment of high-risk prostate cancer (PCa). However, we do not know how radiotherapy influences the overall metabolism of patients. This question has become increasingly topical with improvements in radiotherapy accuracy, which have led to rising interest in PLNRT. To better understand the impact of radiotherapy on metabolic profiles, we conducted deep metabonomic analysis in patients undergoing EBRT to the prostate and pelvis for high-risk PCa. Material and Methods We sampled urine, serum and stools in 32 patients at 6 timepoints: baseline, 2/3 and 4/5 weeks of PLNRT; and 3, 6, and 12 months after PLNRT. We characterised the whole metabolome in urine/serum with nuclear-magnetic resonance (NMR) and mass spectrometry (MS), and in stools (faecal water; FW) with NMR. We used linear mixed- effects modelling to remove subject-specific variance from data. Partial least squares (PLS) discriminant analysis was used to model changes between timepoints for each biofluid and assay. Significant metabolites were determined by cross-validation for valid models (α=0.05). Results After removal of individual variation, we found that metabolites in urine, serum and FW changed significantly after PLNRT initiation (figure 1). In urine and serum, some recovery was observed after treatment completion however not to baseline levels, as significant metabolic differences were observed between baseline and 12 weeks post-PLNRT, which subsequently remained stable. In FW, no recovery was observed. When analysing specific metabolites over time we observed that at 12 weeks the metabolic state had not returned to baseline, which was sustained until one year post-treatment completion. Figure 1: Changes in overall metabolic profiles over time in patients undergoing PLNRT after removal of individual variance. Only assays where robust significant changes were found are shown (Positive Q2, Permutation test value < 0.01). Green cells show significant changes in metabolic profiles. Red cells show no or non-significant changes. MS: mass spectrometry. LPOS and LNEG: lipid (tailored to detect complex-lipid species) positive and negative ionisation modes. HPOS: hilic (tailored to detect small and polar-molecules) positive ionisation mode. RPOS and RNEG: reverse-phase (tailored to detect small molecules of moderate hydrophobicity) positive and negative ionisation modes. NMR: Nuclear Magnetic Resonance. standard 1D: standard one dimension pulse

Conclusion We show for the first time that, when individual variation is removed, a lasting overall metabolic impact is observed in patients undergoing EBRT for high-risk prostate cancer. This observation has potential in terms of treatment response biomarker discovery. We are also exploring relationships with our recently published microbiota/toxicity observations in this group of patients. PH-0233 Microbiome Structures and Function Changes in RE of Cervical Cancer Based on 16S-rDNA Sequencing C. Ma 1 , X. Xiaoting 1 , Q. Songbing 1 , H. Xiaolan 1 , Z. Juying 1 1 The First Affiliated Hospital of Soochow University, Dept. of Radiotherapy & Oncology, Suzhou, China Purpose or Objective To investigate the changes in contents and function of intestinal microbial colonies of the radiation enteritis model, which included time variable. Material and Methods A total of 50 cervical cancer patients who received radiotherapy (RT) in our hospital from September 2017 to June 2018 and 15 healthy female controls were enrolled. Fecal samples were collected from patients at five time points during radiotherapy, i.e. baseline, 2 weeks post-RT starting, 4 weeks post-RT starting, ending of RT and 3 months post-RT ending, and the control group on the baseline, respectively. The fecal supernatent samples were detected by 16S-rDNA amplicon sequencing to investigate the changes in colonial contents and diversities using bioinformatic analysis. The samples were analyzed by liquid chromatography-mass spectrometry (LC-MS) to investigate the changes in colonical functions. Results The top three enrichments were as follows: on phylum level, Firmicutes, Bacteroidetes, Proteobacteria; on genus level, Bacteroidaceae , brauteria , E. coli-shigella . As to the microbial alpha-diversity, the samples of the control group were homogeneous while radiotherapy groups were more diversed. The diversities of radiotherapy groups were much lower than that of the control group, and negatively related to the time-dose relationship. However, there were not significant differences in the recheck time, compared with the control group. Further analyses of correlation between microbial diversity and clinical characteristics showed that specific microorganism changes were strongly positively or negatively related to normal tissue constraints, such as rectum V 40 , colon V 40 , left-semicolon V 40 , right-semicolon V 40 , small intestine V 20 . In terms of microbial community structure, the internal diversities of radiotherapy groups were more than that of the contol group. Compared with the control group, the abundance of Barnesiella was much lower, while abundances of Ruminococcus gnavus and Erysipelatoclostridiu were higher during radiotherapy, according to the Metastats analysis. At the time point of the highest radiation enteritis occurency, i.e. four weeks after RT starting, E. coli-shigella and Tyzzerella abundances increased. PICRUSt functional predictive analysis revealed the vital participation of intestinal microorganisms in animino acid and carbohydrate transportation and metabolism in the radiation enteritis