Tumour response to hypoxia: understanding the hypoxic tumour microenvironment to improve treatment outcome in solid tumours.

Hypoxia is a common feature of solid tumours affecting their biology and response to therapy. One of the main transcription factors activated by hypoxia is hypoxia-inducible factor (HIF), which regulates the expression of genes involved in various aspects of tumourigenesis including proliferative capacity, angiogenesis, immune evasion, metabolic reprogramming, extracellular matrix (ECM) remodelling, and cell migration. This can negatively impact patient outcomes by inducing therapeutic resistance. The importance of hypoxia is clearly demonstrated by continued research into finding clinically relevant hypoxia biomarkers, and hypoxia-targeting therapies. One of the problems is the lack of clinically applicable methods of hypoxia detection, and lack of standardisation. Additionally, a lot of the methods of detecting hypoxia do not take into consideration the complexity of the hypoxic tumour microenvironment (TME). Therefore, this needs further elucidation as approximately 50% of solid tumours are hypoxic. The ECM is important component of the hypoxic TME, and is developed by both cancer associated fibroblasts (CAFs) and tumour cells. However, it is important to distinguish the different roles to develop both biomarkers and novel compounds. Fibronectin (FN), collagen (COL) and hyaluronic acid (HA) are important components of the ECM that create ECM fibres. These fibres are crosslinked by specific enzymes including lysyl oxidase (LOX) which regulates the stiffness of tumours and induces fibrosis. This is partially regulated by HIFs. The review highlights the importance of understanding the role of matrix stiffness in different solid tumours as current data shows contradictory results on the impact on therapeutic resistance. The review also indicates that further research is needed into identifying different CAF subtypes and their exact roles; with some showing pro-tumorigenic capacity and others having anti-tumorigenic roles. This has made it difficult to fully elucidate the role of CAFs within the TME. However, it is clear that this is an important area of research that requires unravelling as current strategies to target CAFs have resulted in worsened prognosis. The role of immune cells within the tumour microenvironment is also discussed as hypoxia has been associated with modulating immune cells to create an anti-tumorigenic environment. Which has led to the development of immunotherapies including PD-L1. These hypoxia-induced changes can confer resistance to conventional therapies, such as chemotherapy, radiotherapy, and immunotherapy. This review summarizes the current knowledge on the impact of hypoxia on the TME and its implications for therapy resistance. It also discusses the potential of hypoxia biomarkers as prognostic and predictive indictors of treatment response, as well as the challenges and opportunities of targeting hypoxia in clinical trials.

A hypoxia biomarker does not predict benefit from giving chemotherapy with radiotherapy in the BC2001 randomised controlled trial.

BACKGROUND: BC2001 showed combining chemotherapy (5-FU + mitomycin-C) with radiotherapy improves loco-regional disease-free survival in patients with muscle-invasive bladder cancer (MIBC). We previously showed a 24-gene hypoxia-associated signature predicted benefit from hypoxia-modifying radiosensitisation in BCON and hypothesised that only patients with low hypoxia scores (HSs) would benefit from chemotherapy in BC2001. BC2001 allowed conventional (64Gy/32 fractions) or hypofractionated (55Gy/20 fractions) radiotherapy. An exploratory analysis tested an additional hypothesis that hypofractionation reduces reoxygenation and would be detrimental for patients with hypoxic tumours. METHODS: RNA was extracted from pre-treatment biopsies (298 BC2001 patients), transcriptomic data generated (Affymetrix Clariom-S arrays), HSs calculated (median expression of 24-signature genes) and patients stratified as hypoxia-high or -low (cut-off: cohort median). PRIMARY ENDPOINT: invasive loco-regional control (ILRC); secondary overall survival. FINDINGS: Hypoxia affected overall survival (HR = 1.30; 95% CI 0.99-1.70; p = 0.062): more uncertainty for ILRC (HR = 1.29; 95% CI 0.82-2.03; p = 0.264). Benefit from chemotherapy was similar for patients with high or low HSs, with no interaction between HS and treatment arm. High HS associated with poor ILRC following hypofractionated (n = 90, HR 1.69; 95% CI 0.99-2.89 p = 0.057) but not conventional (n = 207, HR 0.70; 95% CI 0.28-1.80, p = 0.461) radiotherapy. The finding was confirmed in an independent cohort (BCON) where hypoxia associated with a poor prognosis for patients receiving hypofractionated (n = 51; HR 14.2; 95% CI 1.7-119; p = 0.015) but not conventional (n = 24, HR 1.04; 95% CI 0.07-15.5, p = 0.978) radiotherapy. INTERPRETATION: Tumour hypoxia status does not affect benefit from BC2001 chemotherapy. Hypoxia appears to affect fractionation sensitivity. Use of HSs to personalise treatment needs testing in a biomarker-stratified trial. FUNDING: Cancer Research UK, NIHR, MRC.

Developing and Validating a Multivariable Prognostic-Predictive Classifier for Treatment Escalation of Oropharyngeal Squamous Cell Carcinoma: The PREDICTR-OPC Study.

PURPOSE: While there are several prognostic classifiers, to date, there are no validated predictive models that inform treatment selection for oropharyngeal squamous cell carcinoma (OPSCC).Our aim was to develop clinical and/or biomarker predictive models for patient outcome and treatment escalation for OPSCC. EXPERIMENTAL DESIGN: We retrospectively collated clinical data and samples from a consecutive cohort of OPSCC cases treated with curative intent at ten secondary care centers in United Kingdom and Poland between 1999 and 2012. We constructed tissue microarrays, which were stained and scored for 10 biomarkers. We then undertook multivariable regression of eight clinical parameters and 10 biomarkers on a development cohort of 600 patients. Models were validated on an independent, retrospectively collected, 385-patient cohort. RESULTS: A total of 985 subjects (median follow-up 5.03 years, range: 4.73-5.21 years) were included. The final biomarker classifier, comprising p16 and survivin immunohistochemistry, high-risk human papillomavirus (HPV) DNA in situ hybridization, and tumor-infiltrating lymphocytes, predicted benefit from combined surgery + adjuvant chemo/radiotherapy over primary chemoradiotherapy in the high-risk group [3-year overall survival (OS) 63.1% vs. 41.1%, respectively, HR = 0.32; 95% confidence interval (CI), 0.16-0.65; P = 0.002], but not in the low-risk group (HR = 0.4; 95% CI, 0.14-1.24; P = 0.114). On further adjustment by propensity scores, the adjusted HR in the high-risk group was 0.34, 95% CI = 0.17-0.67, P = 0.002, and in the low-risk group HR was 0.5, 95% CI = 0.1-2.38, P = 0.384. The concordance index was 0.73. CONCLUSIONS: We have developed a prognostic classifier, which also appears to demonstrate moderate predictive ability. External validation in a prospective setting is now underway to confirm this and prepare for clinical adoption.

Randomized Phase 3 Trial of the Hypoxia Modifier Nimorazole Added to Radiation Therapy With Benefit Assessed in Hypoxic Head and Neck Cancers Determined Using a Gene Signature (NIMRAD).

PURPOSE: Tumor hypoxia is an adverse prognostic factor in head and neck squamous cell carcinoma (HNSCC). We assessed whether patients with hypoxic HNSCC benefited from the addition of nimorazole to definitive intensity modulated radiation therapy (IMRT). METHODS AND MATERIALS: NIMRAD was a phase 3, multicenter, placebo-controlled, double-anonymized trial of patients with HNSCC unsuitable for concurrent platinum chemotherapy or cetuximab with definitive IMRT (NCT01950689). Patients were randomized 1:1 to receive IMRT (65 Gy in 30 fractions over 6 weeks) plus nimorazole (1.2 g/m2 daily, before IMRT) or placebo. The primary endpoint was freedom from locoregional progression (FFLRP) in patients with hypoxic tumors, defined as greater than or equal to the median tumor hypoxia score of the first 50 patients analyzed (≥0.079), using a validated 26-gene signature. The planned sample size was 340 patients, allowing for signature generation in 85% and an assumed hazard ratio (HR) of 0.50 for nimorazole effectiveness in the hypoxic group and requiring 66 locoregional failures to have 80% power in a 2-tail log-rank test at the 5% significance level. RESULTS: Three hundred thirty-eight patients were randomized by 19 centers in the United Kingdom from May 2014 to May 2019, with a median follow-up of 3.1 years (95% CI, 2.9-3.4). Hypoxia scores were available for 286 (85%). The median patient age was 73 years (range, 44-88; IQR, 70-76). There were 36 (25.9%) locoregional failures in the hypoxic group, in which nimorazole + IMRT did not improve FFLRP (adjusted HR, 0.72; 95% CI, 0.36-1.44; P = .35) or overall survival (adjusted HR, 0.96; 95% CI, 0.53-1.72; P = .88) compared with placebo + IMRT. Similarly, nimorazole + IMRT did not improve FFLRP or overall survival in the whole population. In total (N = 338), 73% of patients allocated nimorazole adhered to the drug for ≥50% of IMRT fractions. Nimorazole + IMRT caused more acute nausea compared with placebo + IMRT (Common Terminology Criteria for Adverse Events version 4.0 G1+2: 56.6% vs 42.4%, G3: 10.1% vs 5.3%, respectively; P < .05). CONCLUSIONS: Addition of the hypoxia modifier nimorazole to IMRT for locally advanced HNSCC in older and less fit patients did not improve locoregional control or survival.

Contouring variation affects estimates of normal tissue complication probability for breast fibrosis after radiotherapy.

BACKGROUND: Normal tissue complication probability (NTCP) models can be useful to estimate the risk of fibrosis after breast-conserving surgery (BCS) and radiotherapy (RT) to the breast. However, they are subject to uncertainties. We present the impact of contouring variation on the prediction of fibrosis. MATERIALS AND METHODS: 280 breast cancer patients treated BCS-RT were included. Nine Clinical Target Volume (CTV) contours were created for each patient: i) CTV_crop (reference), cropped 5 mm from the skin and ii) CTV_skin, uncropped and including the skin, iii) segmenting the 95% isodose (Iso95%) and iv) 3 different auto-contouring atlases generating uncropped and cropped contours (Atlas_skin/Atlas_crop). To illustrate the impact of contour variation on NTCP estimates, we applied two equations predicting fibrosis grade ≥ 2 at 5 years, based on Lyman-Kutcher-Burman (LKB) and Relative Seriality (RS) models, respectively, to each contour. Differences were evaluated using repeated-measures ANOVA. For completeness, the association between observed fibrosis events and NTCP estimates was also evaluated using logistic regression. RESULTS: There were minimal differences between contours when the same contouring approach was followed (cropped and uncropped). CTV_skin and Atlas_skin contours had lower NTCP estimates (-3.92%, IQR 4.00, p < 0.05) compared to CTV_crop. No significant difference was observed for Atlas_crop and Iso95% contours compared to CTV_crop. For the whole cohort, NTCP estimates varied between 5.3% and 49.5% (LKB) or 2.2% and 49.6% (RS) depending on the choice of contours. NTCP estimates for individual patients varied by up to a factor of 4. Estimates from "skin" contours showed higher agreement with observed events. CONCLUSION: Contour variations can lead to significantly different NTCP estimates for breast fibrosis, highlighting the importance of standardising breast contours before developing and/or applying NTCP models.

Comparison of prone and supine positioning for breast cancer radiotherapy using REQUITE data: dosimetry, acute and two years physician and patient-reported outcomes.

OBJECTIVE: Most patients receive whole breast radiotherapy in a supine position. However, two randomised trials showed lower acute toxicity in prone position. Furthermore, in most patients, prone positioning reduced doses to the organs at risk. To confirm these findings, we compared toxicity outcomes, photographic assessment, and dosimetry between both positions using REQUITE data. METHODS: REQUITE is an international multi-centre prospective observational study that recruited 2069 breast cancer patients receiving radiotherapy. Data on toxicity, health-related quality of life (HRQoL), and dosimetry were collected, as well as a photographic assessment. A matched case control analysis compared patients treated prone (n = 268) versus supine (n = 493). Exact matching was performed for the use of intensity-modulated radiotherapy, boost, lymph node irradiation, chemotherapy and fractionation, and the nearest neighbour for breast volume. Primary endpoints were dermatitis at the end of radiotherapy, and atrophy and cosmetic outcome by photographic assessment at two years. RESULTS: At the last treatment fraction, there was no significant difference in dermatitis (p = .28) or any HRQoL domain, but prone positioning increased the risk of breast oedema (p < .001). At 2 years, patients treated in prone position had less atrophy (p = .01), and higher body image (p < .001), and social functioning (p < .001) scores. The photographic assessment showed no difference in cosmesis at 2 years (p = .22). In prone position, mean heart dose (MHD) was significantly lower for left-sided patients (1.29 Gy vs 2.10 Gy, p < .001) and ipsilateral mean lung dose (MLD) was significantly lower for all patients (2.77 Gy vs 5.89 Gy, p < .001). CONCLUSIONS: Prone radiotherapy showed lower MLD and MHD compared to supine position, although the risk of developing breast oedema during radiotherapy was higher. At 2 years the photographic assessment showed no difference in the cosmetic outcome, but less atrophy was seen in prone-treated patients and this seems to have a positive influence on the HRQoL domain of body image.

(Pre)treatment risk factors for late fatigue and fatigue trajectories following radiotherapy for breast cancer.

Fatigue is common in breast-cancer survivors. Our study assessed fatigue longitudinally in breast cancer patients receiving adjuvant radiotherapy (RT) and aimed to identify risk factors associated with long-term fatigue and underlying fatigue trajectories. Fatigue was measured in a prospective multicenter cohort (REQUITE) using the Multidimensional Fatigue Inventory (MFI-20) and analyzed using mixed models. Multivariable logistic models identified factors associated with fatigue dimensions at 2 years post-RT and latent class growth analysis identified individual fatigue trajectories. A total of 1443, 1302, 1203 and 1098 patients completed the MFI-20 at baseline, end of RT, after 1 and 2 years. Overall, levels of fatigue significantly increased from baseline to end of RT for all fatigue dimensions (P < .05) and returned to baseline levels after 2 years. A quarter of patients were assigned to latent trajectory high (23.7%) and moderate (24.8%) fatigue classes, while 46.3% and 5.2% to the low and decreasing fatigue classes, respectively. Factors associated with multiple fatigue dimensions at 2 years include age, BMI, global health status, insomnia, pain, dyspnea and depression. Fatigue present at baseline was consistently associated with all five MFI-20 fatigue dimensions (ORGeneralFatigue = 3.81, P < .001). From latent trajectory analysis, patients with a combination of factors such as pain, insomnia, depression, younger age and endocrine therapy had a particularly high risk of developing early and persistent high fatigue years after treatment. Our results confirmed the multidimensional nature of fatigue and will help clinicians identify breast cancer patients at higher risk of having persistent/late fatigue so that tailored interventions can be delivered.

Genome-wide association study of treatment-related toxicity two years following radiotherapy for breast cancer.

BACKGROUND AND PURPOSE: Up to a quarter of breast cancer patients treated by surgery and radiotherapy experience clinically significant toxicity. If patients at high risk of adverse effects could be identified at diagnosis, their treatment could be tailored accordingly. This study was designed to identify common single nucleotide polymorphisms (SNPs) associated with toxicity two years following whole breast radiotherapy. MATERIALS AND METHODS: A genome-wide association study (GWAS) was performed in 1,640 breast cancer patients with complete SNP, clinical, treatment and toxicity data, recruited across 18 European and US centres into the prospective REQUITE cohort study. Toxicity data (CTCAE v4.0) were collected at baseline, end of radiotherapy, and annual follow-up. A total of 7,097,340 SNPs were tested for association with the residuals of toxicity endpoints, adjusted for clinical, treatment co-variates and population substructure. RESULTS: Quantile-quantile plots showed more associations with toxicity above the p < 5 × 10-5 level than expected by chance. Eight SNPs reached genome-wide significance. Nipple retraction grade ≥ 2 was associated with the rs188287402 variant (p = 2.80 × 10-8), breast oedema grade ≥ 2 with rs12657177 (p = 1.12 × 10-10), rs75912034 (p = 1.12 × 10-10), rs145328458 (p = 1.06 × 10-9) and rs61966612 (p = 1.23 × 10-9), induration grade ≥ 2 with rs77311050 (p = 2.54 × 10-8) and rs34063419 (p = 1.21 × 10-8), and arm lymphoedema grade ≥ 1 with rs643644 (p = 3.54 × 10-8). Heritability estimates across significant endpoints ranged from 25% to 39%. Our study did not replicate previously reported SNPs associated with breast radiation toxicity at the pre-specified significance level. CONCLUSIONS: This GWAS for long-term breast radiation toxicity provides further evidence for significant association of common SNPs with distinct toxicity endpoints.

Evaluating Approaches for Constructing Polygenic Risk Scores for Prostate Cancer in Men of African and European Ancestry.

Genome-wide polygenic risk scores (GW-PRS) have been reported to have better predictive ability than PRS based on genome-wide significance thresholds across numerous traits. We compared the predictive ability of several GW-PRS approaches to a recently developed PRS of 269 established prostate cancer risk variants from multi-ancestry GWAS and fine-mapping studies (PRS 269 ). GW-PRS models were trained using a large and diverse prostate cancer GWAS of 107,247 cases and 127,006 controls used to develop the multi-ancestry PRS 269 . Resulting models were independently tested in 1,586 cases and 1,047 controls of African ancestry from the California/Uganda Study and 8,046 cases and 191,825 controls of European ancestry from the UK Biobank and further validated in 13,643 cases and 210,214 controls of European ancestry and 6,353 cases and 53,362 controls of African ancestry from the Million Veteran Program. In the testing data, the best performing GW-PRS approach had AUCs of 0.656 (95% CI=0.635-0.677) in African and 0.844 (95% CI=0.840-0.848) in European ancestry men and corresponding prostate cancer OR of 1.83 (95% CI=1.67-2.00) and 2.19 (95% CI=2.14-2.25), respectively, for each SD unit increase in the GW-PRS. However, compared to the GW-PRS, in African and European ancestry men, the PRS 269 had larger or similar AUCs (AUC=0.679, 95% CI=0.659-0.700 and AUC=0.845, 95% CI=0.841-0.849, respectively) and comparable prostate cancer OR (OR=2.05, 95% CI=1.87-2.26 and OR=2.21, 95% CI=2.16-2.26, respectively). Findings were similar in the validation data. This investigation suggests that current GW-PRS approaches may not improve the ability to predict prostate cancer risk compared to the multi-ancestry PRS 269 constructed with fine-mapping.

Normal Tissue Toxicity Prediction: Clinical Translation on the Horizon.

Improvements in radiotherapy delivery have enabled higher therapeutic doses and improved efficacy, contributing to the growing number of long-term cancer survivors. These survivors are at risk of developing late toxicity from radiotherapy, and the inability to predict who is most susceptible results in substantial impact on quality of life and limits further curative dose escalation. A predictive assay or algorithm for normal tissue radiosensitivity would allow more personalized treatment planning, reducing the burden of late toxicity, and improving the therapeutic index. Progress over the last 10 years has shown that the etiology of late clinical radiotoxicity is multifactorial and informs development of predictive models that combine information on treatment (eg, dose, adjuvant treatment), demographic and health behaviors (eg, smoking, age), co-morbidities (eg, diabetes, collagen vascular disease), and biology (eg, genetics, ex vivo functional assays). AI has emerged as a useful tool and is facilitating extraction of signal from large datasets and development of high-level multivariable models. Some models are progressing to evaluation in clinical trials, and we anticipate adoption of these into the clinical workflow in the coming years. Information on predicted risk of toxicity could prompt modification of radiotherapy delivery (eg, use of protons, altered dose and/or fractionation, reduced volume) or, in rare instances of very high predicted risk, avoidance of radiotherapy. Risk information can also be used to assist treatment decision-making for cancers where efficacy of radiotherapy is equivalent to other treatments (eg, low-risk prostate cancer) and can be used to guide follow-up screening in instances where radiotherapy is still the best choice to maximize tumor control probability. Here, we review promising predictive assays for clinical radiotoxicity and highlight studies that are progressing to develop an evidence base for clinical utility.

Evaluating approaches for constructing polygenic risk scores for prostate cancer in men of African and European ancestry.

Genome-wide polygenic risk scores (GW-PRSs) have been reported to have better predictive ability than PRSs based on genome-wide significance thresholds across numerous traits. We compared the predictive ability of several GW-PRS approaches to a recently developed PRS of 269 established prostate cancer-risk variants from multi-ancestry GWASs and fine-mapping studies (PRS269). GW-PRS models were trained with a large and diverse prostate cancer GWAS of 107,247 cases and 127,006 controls that we previously used to develop the multi-ancestry PRS269. Resulting models were independently tested in 1,586 cases and 1,047 controls of African ancestry from the California Uganda Study and 8,046 cases and 191,825 controls of European ancestry from the UK Biobank and further validated in 13,643 cases and 210,214 controls of European ancestry and 6,353 cases and 53,362 controls of African ancestry from the Million Veteran Program. In the testing data, the best performing GW-PRS approach had AUCs of 0.656 (95% CI = 0.635-0.677) in African and 0.844 (95% CI = 0.840-0.848) in European ancestry men and corresponding prostate cancer ORs of 1.83 (95% CI = 1.67-2.00) and 2.19 (95% CI = 2.14-2.25), respectively, for each SD unit increase in the GW-PRS. Compared to the GW-PRS, in African and European ancestry men, the PRS269 had larger or similar AUCs (AUC = 0.679, 95% CI = 0.659-0.700 and AUC = 0.845, 95% CI = 0.841-0.849, respectively) and comparable prostate cancer ORs (OR = 2.05, 95% CI = 1.87-2.26 and OR = 2.21, 95% CI = 2.16-2.26, respectively). Findings were similar in the validation studies. This investigation suggests that current GW-PRS approaches may not improve the ability to predict prostate cancer risk compared to the PRS269 developed from multi-ancestry GWASs and fine-mapping.

Prediction of prostate tumour hypoxia using pre-treatment MRI-derived radiomics: preliminary findings.

PURPOSE: To develop a machine learning (ML) model based on radiomic features (RF) extracted from whole prostate gland magnetic resonance imaging (MRI) for prediction of tumour hypoxia pre-radiotherapy. MATERIAL AND METHODS: Consecutive patients with high-grade prostate cancer and pre-treatment MRI treated with radiotherapy between 01/12/2007 and 1/08/2013 at two cancer centres were included. Cancers were dichotomised as normoxic or hypoxic using a biopsy-based 32-gene hypoxia signature (Ragnum signature). Prostate segmentation was performed on axial T2-weighted (T2w) sequences using RayStation (v9.1). Histogram standardisation was applied prior to RF extraction. PyRadiomics (v3.0.1) was used to extract RFs for analysis. The cohort was split 80:20 into training and test sets. Six different ML classifiers for distinguishing hypoxia were trained and tuned using five different feature selection models and fivefold cross-validation with 20 repeats. The model with the highest mean validation area under the curve (AUC) receiver operating characteristic (ROC) curve was tested on the unseen set, and AUCs were compared via DeLong test with 95% confidence interval (CI). RESULTS: 195 patients were included with 97 (49.7%) having hypoxic tumours. The hypoxia prediction model with best performance was derived using ridge regression and had a test AUC of 0.69 (95% CI: 0.14). The test AUC for the clinical-only model was lower (0.57), but this was not statistically significant (p = 0.35). The five selected RFs included textural and wavelet-transformed features. CONCLUSION: Whole prostate MRI-radiomics has the potential to non-invasively predict tumour hypoxia prior to radiotherapy which may be helpful for individualised treatment optimisation.

Hypoxia Is Associated with Increased Immune Infiltrates and Both Anti-Tumour and Immune Suppressive Signalling in Muscle-Invasive Bladder Cancer.

Hypoxia and a suppressive tumour microenvironment (TME) are both independent negative prognostic factors for muscle-invasive bladder cancer (MIBC) that contribute to treatment resistance. Hypoxia has been shown to induce an immune suppressive TME by recruiting myeloid cells that inhibit anti-tumour T cell responses. Recent transcriptomic analyses show hypoxia increases suppressive and anti-tumour immune signalling and infiltrates in bladder cancer. This study sought to investigate the relationship between hypoxia-inducible factor (HIF)-1 and -2, hypoxia, and immune signalling and infiltrates in MIBC. ChIP-seq was performed to identify HIF1α, HIF2α, and HIF1ß binding in the genome of the MIBC cell line T24 cultured in 1% and 0.1% oxygen for 24 h. Microarray data from four MIBC cell lines (T24, J82, UMUC3, and HT1376) cultured under 1%, 0.2%, and 0.1% oxygen for 24 h were used. Differences in the immune contexture between high- and low-hypoxia tumours were investigated using in silico analyses of two bladder cancer cohorts (BCON and TCGA) filtered to only include MIBC cases. GO and GSEA were used with the R packages "limma" and "fgsea". Immune deconvolution was performed using ImSig and TIMER algorithms. RStudio was used for all analyses. Under hypoxia, HIF1α and HIF2α bound to ~11.5-13.5% and ~4.5-7.5% of immune-related genes, respectively (1-0.1% O2). HIF1α and HIF2α both bound to genes associated with T cell activation and differentiation signalling pathways. HIF1α and HIF2α had distinct roles in immune-related signalling. HIF1 was associated with interferon production specifically, whilst HIF2 was associated with generic cytokine signalling as well as humoral and toll-like receptor immune responses. Neutrophil and myeloid cell signalling was enriched under hypoxia, alongside hallmark pathways associated with Tregs and macrophages. High-hypoxia MIBC tumours had increased expression of both suppressive and anti-tumour immune gene signatures and were associated with increased immune infiltrates. Overall, hypoxia is associated with increased inflammation for both suppressive and anti-tumour-related immune signalling and immune infiltrates, as seen in vitro and in situ using MIBC patient tumours.

Technical development and validation of a clinically applicable microenvironment classifier as a biomarker of tumour hypoxia for soft tissue sarcoma.

BACKGROUND: Soft tissue sarcomas (STS) are rare, heterogeneous tumours and biomarkers are needed to inform management. We previously derived a prognostic tumour microenvironment classifier (24-gene hypoxia signature). Here, we developed/validated an assay for clinical application. METHODS: Technical performance of targeted assays (Taqman low-density array, nanoString) was compared in 28 prospectively collected formalin-fixed, paraffin-embedded (FFPE) biopsies. The nanoString assay was biologically validated by comparing to HIF-1α/CAIX immunohistochemistry (IHC) in clinical samples. The Manchester (n = 165) and VORTEX Phase III trial (n = 203) cohorts were used for clinical validation. The primary outcome was overall survival (OS). RESULTS: Both assays demonstrated excellent reproducibility. The nanoString assay detected upregulation of the 24-gene signature under hypoxia in vitro, and 16/24 hypoxia genes were upregulated in tumours with high CAIX expression in vivo. Patients with hypoxia-high tumours had worse OS in the Manchester (HR 3.05, 95% CI 1.54-5.19, P = 0.0005) and VORTEX (HR 2.13, 95% CI 1.19-3.77, P = 0.009) cohorts. In the combined cohort, it was independently prognostic for OS (HR 2.24, 95% CI 1.42-3.53, P = 0.00096) and associated with worse local recurrence-free survival (HR 2.17, 95% CI 1.01-4.68, P = 0.04). CONCLUSIONS: This study comprehensively validates a microenvironment classifier befitting FFPE STS biopsies. Future uses include: (1) selecting high-risk patients for perioperative chemotherapy; and (2) biomarker-driven trials of hypoxia-targeted therapies.

Comparing symptom reporting by prostate cancer patients and healthcare professionals in the international multicentre REQUITE study.

INTRODUCTION: Previous studies showed that healthcare professionals and patients had only moderate to low agreement on their assessment of treatment-related symptoms. We aimed to determine the levels of agreement in a large cohort of prostate cancer patients. METHODS: Analyses were made of data from 1,756 prostate cancer patients treated with external beam radiotherapy (RT) and/or brachytherapy in Europe and the USA and recruited into the prospective multicentre observational REQUITE study. Eleven pelvic symptoms at the end of RT were compared after translating patient-reported outcomes (PROs) into CTCAE-based healthcare professional ratings. Gwet's AC2 agreement coefficient and 95% confidence intervals were calculated for each symptom. To compare severity of grading between patients and healthcare professionals, percent agreement and deviations for each symptom were graphically depicted. Stratified and sensitivity analyses were conducted to identify potential influencing factors and to assess heterogeneity and robustness of results. RESULTS: The agreement for the 11 pelvic symptoms varied from very good (AC2 > 0.8: haematuria, rectal bleeding, management of sphincter control) to poor agreement (AC2 ≤ 0.2: proctitis and urinary urgency). Fatigue had a negative impact on the agreement. Patients tended to grade symptoms more severely than healthcare professionals. Information on sexual dysfunction was missing more frequently in healthcare professional assessment than PROs. CONCLUSION: Agreement was better for observable than subjective symptoms, with patients usually grading symptoms more severely than healthcare professionals. Our findings emphasize that PROs should complement symptom assessment by healthcare professionals and be taken into consideration for clinical decision-making to incorporate the patient perspective.

Predicting tumour radiosensitivity to deliver precision radiotherapy.

Owing to advances in radiotherapy, the physical properties of radiation can be optimized to enable individualized treatment; however, optimization is rarely based on biological properties and, therefore, treatments are generally planned with the assumption that all tumours respond similarly to radiation. Radiation affects multiple cellular pathways, including DNA damage, hypoxia, proliferation, stem cell phenotype and immune response. In this Review, we summarize the effect of these pathways on tumour responses to radiotherapy and the current state of research on genomic classifiers designed to exploit these variations to inform treatment decisions. We also discuss whether advances in genomics have generated evidence that could be practice changing and whether advances in genomics are now ready to be used to guide the delivery of radiotherapy alone or in combination.

TORPEdO: A phase III trial of intensity-modulated proton beam therapy versus intensity-modulated radiotherapy for multi-toxicity reduction in oropharyngeal cancer.

•There is a lack of prospective level I evidence for the use of PBT for most adult cancers including oropharyngeal squamous cell carcinoma (OPSCC).•TORPEdO is the UK's first PBT clinical trial and aims to determine the benefits of PBT for OPSCC.•Training and support has been provided before and during the trial to reduce variations of contouring and radiotherapy planning.•There is a strong translational component within TORPEdO. Imaging and physics data along with blood, tissue collection will inform future studies in refining patient selection for IMPT.

Reirradiation Options for Previously Irradiated Prostate cancer (RO-PIP): Feasibility study investigating toxicity outcomes following reirradiation with stereotactic body radiotherapy (SBRT) versus high-dose-rate brachytherapy (HDR-BT).

INTRODUCTION: Radiotherapy is the most common curative treatment for non-metastatic prostate cancer; however, up to 13% of patients will develop local recurrence within 10 years. Patients can undergo further and potentially curative treatment including salvage surgery, brachytherapy (BT), external beam radiotherapy, high-intensity focused ultrasound and cryotherapy. Systematic review shows that high-dose-rate (HDR) BT and stereotactic body radiotherapy (SBRT) have the best outcomes in terms of biochemical control and lowest side effects. The reirradiation options for previously irradiated prostate cancer (RO-PIP) trial aims to determine the feasibility of recruitment to a trial randomising patients to salvage HDR-BT or SBRT and provide prospective data on patient recorded toxicity outcomes that will inform a future phase III trial. METHODS AND ANALYSIS: The primary endpoint of the RO-PIP feasibility study is to evaluate the patient recruitment potential over 2 years to a trial randomising to either SBRT or HDR-BT for patients who develop local recurrence of prostate cancer following previous radiation therapy. The aim is to recruit 60 patients across 3 sites over 2 years and randomise 1:1 to SBRT or HDR-BT. Secondary objectives include recording clinician and patient-reported outcome measures to evaluate treatment-related toxicity. In addition, the study aims to identify potential imaging, genomic and proteomic biomarkers that are predictive of toxicity and outcome based on hypoxia status, a prognostic marker of prostate cancer. ETHICS AND DISSEMINATION: This study has been approved by the Yorkshire and The Humber-Bradford Leeds Research Ethics Committee (Reference: 21/YH/0305, IRAS: 297060, January 2022). The results will be presented in national and international conferences, published in peer-reviewed journals and will be communicated to relevant stakeholders. A plain English report will be shared with the study participants, patients' organisations and media. TRIAL REGISTRATION NUMBER: ISRCTN 12238218 (Amy Ackroyd NIHR CPMS Team).