NIHRDataInsights/HRCSData huggingface dataset:
Title: Enriched eXosomal signatures for PANcreatic cancer early Detection (EXPAND)
Funder: Cancer Research UK

Abstract: Pancreatic ductal adenocarcinoma (PDAC) is the 5th leading cause of cancer deaths worldwide. Late diagnosis is a common feature of PDAC and is associated with poor survival, with less than one in twenty patients living longer than 5yrs. Fewer than one in five patients with PDAC are suitable for potentially curative treatment. Patients with early PDAC often have non-specific symptoms typical of common benign (non-cancer) conditions. In comparison, ‘Red flag’ symptoms (jaundice, weight loss, pain) linked to PDAC frequently indicate advanced incurable disease. Currently only patients with ‘red flag’ symptoms are urgently referred for diagnostic testing. Opening existing diagnostic pathways to patients with non-specific symptoms would lead to potentially harmful over-investigation that would consume NHS resources and cause unnecessary anxiety for the majority of patients who do not have PDAC. There remains therefore an important need to improve earlier detection of PDAC to increase patient survival. Previous studies have shown that volatile organic compounds (VOCs), small molecules produced within the body, can be used to detect PDAC. This proposal seeks to study how VOCs are produced by PDAC and associated gut bacteria. Specifically we will investigated whether VOCs are found in higher concentrations in small particles released by cancer cells calls extracellular vesicles (EVs). To study whether VOCs produced in PDAC patients are increased in EVs we will first conduct experiments in PDAC cells, healthy human pancreatic cells and associated bacteria grown in out laboratory. We will develop new method for selecting specific EVs that are release from PDAC cells. We will conduct preliminary studies in patients to examine whether EVs in blood and urine contained higher levels of cancer specific VOCs that may be linked to either the tumour or its associated bacteria. Intended outcomes of this research are: (i) a better understanding of how VOC concentrations mat be increases within cancer specific EVs, and; (ii) new methods for detecting cancer specific EVs and measuring the VOCs contained within them. This work is intended to precede a larger multicentre clinical study that aims to provide validation of an enriched biomarker test.


Research activity codes: 4.1 DISCOVERY AND PRECLINICAL TESTING OF MARKERS AND TECHNOLOGIES
Health categories: CANCER AND NEOPLASMS
Title: EARLY DIAPAC: EARLY DIAgnosis of PAncreatic Cancer by combined proteomics and genomics testing of pancreatic cyst fluid.
Funder: Cancer Research UK

Abstract: Background Pancreatic cancer (PC) is the 10th most common cancer and it currently stands as the sixth leading cause of death from cancer in the UK. The 5-year survival rate for PC has increased from 4% to only 7% in recent years, which is much behind the progress for other cancer types, such as melanoma. The timely diagnosis of PC is challenging, due to a lack of disease-specific symptoms, resulting in the majority of patients presenting with advanced disease and poor prognosis. Around 30% of pancreatic surgery is done for cysts that are suspected to be cancerous. Some of these cysts are proven to be malignant, whilst others can have genetic and protein pre-malignant changes, or be benign. The ideal diagnostic test would be capable of accurately determining the potential for these cysts to progress into PC at these early stages. Detection of malignant potential of cysts accurately would make surgery more patient-tailored and greatly increase survival rates. Aims The main aim of this study is to characterise proteomic and genomic data gained from the analysis of fluid from pancreatic cysts to identify protein and genetic changes associated with early stages of PC development. Methods We will use state-of-the-art platform technologies - label-free quantitative proteomic analysis and whole genome sequencing - and bioinformatics to examine fluid from pancreatic cysts (n=32). These samples have already been collected from patients and stored, in Hull, from an ethically-approved research study [NCT03536793]. The entire proteome and genome will be analysed using anonymised cystic fluid samples. We will compare findings from the whole data set to those samples which are from confirmed PC cases, as proven by histopathological analysis and from access to clinical data. We have assembled a collaborative multidisciplinary team/consortium from across the UK to ensure we have the expertise, tack record and credibility required to deliver this promising and novel study. How the results of this research will be used. This pioneering study will characterise and quantify for the first time and at a global scale the proteomic and genomic changes and identify molecular signatures associated with early stages of PC development. The study will gather preliminary data to inform the design of a larger trial at a national scale. Detecting malignant potential of cysts early and accurately would lead to better patient management and improved survival, therefore addressing a significant area of unmet need.


Research activity codes: 4.1 DISCOVERY AND PRECLINICAL TESTING OF MARKERS AND TECHNOLOGIES
Health categories: CANCER AND NEOPLASMS
Title: A new platform for discovering biomarkers of early lung cancer
Funder: Cancer Research UK

Abstract: BACKGROUND Lung cancer is the largest cause of cancer-related death in the world. This is principally due to late diagnosis – 75% cases are diagnosed at an advanced stage where treatment is limited. If diagnosed early, curative treatment is available. Developing tests to detect cancer early, before spreading, could therefore save lives. This funding will be used to develop a novel platform to discover biomarkers for the earliest stages of lung cancer. We will test the hypothesis that there is a detectable change in immune cells when they interact with cancer cells for the first time. Given that multiple immune cells can interact with each cancer cell, a signal associated with cancer will be amplified allowing detection when cancer burden is low. This contrasts with other approaches that have looked for direct products of cancer. These suffer from the fundamental problem of being in lower abundance than the cancer, making detection at the earliest stages difficult. AIMS 1. Develop, for the first time, a high-throughput platform using multiple types of primary human immune cells cultured with early cancer tissue, in an environment mimicking human body conditions. 2. Demonstrate the platform’s capability to mimic the immune response present in ‘normal’ and ‘early cancer’ tissue, comparing our results to available in vivo and clinical data. METHODS A dual-chamber bioreactor will be developed using a 96 well format, which fits into standard laboratory settings. The tailored design of culture substrates and porous membranes will enable a flexible platform capable of modelling many different pathological states. Primary bronchial epithelial cells from cancer naïve patients will be transformed with lentiviral vectors expressing relevant oncogenes to model early lung cancer. Co-culture and subsequent analysis of matched peripheral blood will be used to discover changes that could be exploited as biomarkers. HOW THE RESULTS OF THIS RESEARCH WILL BE USED 1. Candidate biomarkers emerging from this study will be evaluated prospectively in a population of patients ‘at-risk’ of lung cancer. 2. The platform itself will be shared widely to enable other researchers to use their particular expertise to detect biomarkers in new modalities 3. Further mechanistic work will be essential to characterise the cause and effect of any associated changes. This has the potential to look for new immunomodulatory therapies that can be used to reduce cancer risk


Research activity codes: 4.1 DISCOVERY AND PRECLINICAL TESTING OF MARKERS AND TECHNOLOGIES;4.5 RESOURCES AND INFRASTRUCTURE (DETECTION)
Health categories: CANCER AND NEOPLASMS
Title: Single cell genomics for early diagnosis in myelodysplastic syndromes
Funder: Cancer Research UK

Abstract: Background There has been major investment to support the introduction of genomics into clinical laboratory services. This has considerable potential to improve patient care enabling earlier diagnosis. Sequencing has developed to allow genomic analysis of individual cells at an unprecedented scale and resolution. The aim of my research is to use single cell genomics to improve precision diagnostics in myelodysplastic syndromes (MDS). MDS is a malignant haematopoietic stem cell disease, where a significant number of patients progress to leukaemia. Key cellular heterogeneity is largely masked with our current laboratory tests. Single cell genomic testing has the potential to uncover this cellular heterogeneity. As a doctor seeing patients with MDS, I have seen how difficult it is to diagnose MDS. We received 257 referrals in the past 6 years, of which 103 have been given a clear diagnosis. We need to improve diagnostics in order to identify and stratify patients with MDS, enabling access to an increasing array of therapies. Aim To establish the feasibility of introducing single cell genomics into a clinical laboratory, in order to improve precision diagnostics in MDS. Methods 1.We will recruit a pilot cohort of 5 patients with MDS and 5 normal controls, in order to validate the technology in this group. I will have access to fresh bone marrow samples via HaemBio biobank (Oxford-HRA-REC: 17/SC/0572). Key Output: Demonstration that bone marrow samples can be run through a single cell genomics pipeline in a robust and timely manner. 2. Routine testing will be performed, as per the current clinical diagnostic pipeline. In parallel, we will use CITE-seq as our novel single cell genomics platform. This technology uniquely enables high-throughput immunophenotyping and unbiased RNA sequencing. These data will determine whether CITE-seq correlates with and might ultimately replace current diagnostic modalities. We will work to develop and refine these pipelines so they can be transferred to a clinical setting. Key Output: To determine whether CITE-seq can improve on our current diagnostic modalities for MDS. Potential Impact My goal is to address the unmet need of inadequate diagnosis and classification of MDS. Addressing this issue is essential for improved clinical decision making and personalised medicine. I aim to take world leading scientific discoveries here in Oxford, and provide proof of concept for application into routine clinical cancer diagnostics. Our pipeline will have broad applicability for cancer, beyond MDS.


Research activity codes: 4.2 EVALUATION OF MARKERS AND TECHNOLOGIES
Health categories: CANCER AND NEOPLASMS
Title: Magnetic, Fluorescent Nanoparticles for the Isolation of Blood Biomarkers in the Early Detection of Pancreatic Cancer
Funder: Cancer Research UK

Abstract: Background Pancreatic ductal adenocarcinoma (PDAC) is associated with no or minor non-specific symptoms in the early stages. Therefore, the cancer is often detected at an advanced stage, where surgical intervention is too late. There is an urgent need for a non-invasive, low-cost test for PDAC which can streamline imaging techniques to locate and resect tumours before metastasis. A sensitive and specific blood test for early PDAC would dramatically improve patient outcomes. An issue with current blood biomarker panels for PDAC is achieving a sufficiently high specificity and sensitivity for an accurate diagnosis. Poor sensitivities are a general issue for early diagnosis, as biomarker levels typically correlate with progression of the disease. Aims We aim to address the sensitivity issue of early diagnosis with a novel magnetic isolation technique. Dual magnetic and fluorescent nanoparticles, coated with antibodies, will be mixed with the sample to allow for the nanoparticles to bind to the target antigens. A magnetic column will isolate the nanoparticles from the sample. The magnet will then be removed, and the nanoparticles will be extracted in a much smaller volume. A lateral flow immunoassay (LFIA) will then be run and the test lines recorded by a fluorescent reader (to give a quantitative result). Our fundamental aim is to show that biomarkers can be efficiently extracted and concentrated to improve the sensitivity and reliability of LFIAs towards a test for PDAC. Methods Dual magnetic and fluorescent nanoparticles will be fabricated. Antibodies will be anchored to the nanoparticle surface using click-chemistry. LFIAs will be built in-house by printing antibody test and control lines onto paper test strips. Fluorescent test lines will be read using an existing fluorescent-reader. The assay will be validated using serum samples from patients with stage I-III PDAC (and healthy patients as a control). How the results will be used This study will validate this concept as a model for the early detection of PDAC which will also be translatable to other cancers. The results of this study will be used to secure further funding to validate this on a larger sample size from a wide range of patients with early PDAC and disease controls. Moreover, as this one-year study will use standard lab equipment, further funding will be required to be build a fully-automated prototype.


Research activity codes: 4.2 EVALUATION OF MARKERS AND TECHNOLOGIES
Health categories: CANCER AND NEOPLASMS
Title: Reducing neurotoxicity from brain irradiation with FLASH radiation and PARP inhibitors
Funder: Cancer Research UK

Abstract: Background: The combination of PARPi and FLASH is of particular interest as both are shown to be modulated by the available oxygen in the irradiated tissue, which increases the possibility of a synergistic and beneficial effect when combining the two. Radiation delivered at ultra-high dose rates has already been shown to result in similar treatment efficacy as radiation delivered at conventional radiotherapy dose rates, when evaluating tumour growth delay in a human glioblastoma model, subcutaneously implanted on the flank of nude mice or when using a murine orthotopic glioblastoma model similarly established in nude mice. Whilst these studies emphasise the great clinical potential FLASH radiotherapy holds for the treatment of GBM as well as other brain tumours, enhanced normal tissue sparing via application of a PARPi will potentially lead to a further widening of the therapeutic window. Aims: Using the state-of-art linear accelerator (Linac) we have available for pre-clinical studies at the University of Oxford, which is capable of delivering dose rates from conventional (few Gy/minute) to FLASH (thousands of Gy/s), we aim to investigate: 1) if hemi-brain FLASH radiation to 20 Gy induces a neuroinflammatory response and whether this is constrained to the radiation field 2) if acute PARP activation differs between conventional and FLASH RT 3) if FLASH- radiation in combination with PARPi can further spare normal brain tissue following hemibrain irradiation of mice These studies will be run in parallel to work to investigate whether PARPi can enhance the therapeutic impact of FLASH GBM models [funded outside of this application]. Methods: We will use IHC approaches to investigate temporal changes in oxidative stress [8-oxoguanine], DNA-damage response (γH2AX, 53BP1) and PARP activity (PARP-1, PAR) as a consequence of FLASH or conventional dose rate hemibrain irradiation. We will complement IHC studies of brain pathology with non-invasive MRI and PET-CT studies monitoring neuroinflammatory responses, BBB function and neurodegeneration, following FLASH or conventional dose rate hemibrain irradiation of mice and the impact of PARPi thereupon. How the results of this research will be used: These will be the first studies combining FLASH and PARPi. We will share technologies and expertise across the participating sites to support the progression of these studies. The results will be used for further and larger grant applications, e.g. MRC or CRUK programme grants, further expanding the research collaboration between the universities in Oxford, Manchester and Glasgow.


Research activity codes: 6.1 PHARMACEUTICALS;6.5 RADIOTHERAPY AND OTHER NON-INVASIVE THERAPIES
Health categories: CANCER AND NEOPLASMS
Title: Overcoming hypoxia mediated resistance to radiotherapy-PARP inhibitor combinations in glioblastoma.
Funder: Cancer Research UK

Abstract: Background: Glioblastoma (GBM) is a cancer of unmet need; average survival is approximately 12 months. The only efficacious treatments are DNA damaging agents: radiotherapy and temozolomide. Overexpression of DNA damage response proteins in GBM correlates with radioresistance and poor prognosis. GBM are also hypoxic, which exacerbates radioresistance and worsens outcomes. The Vens and Chalmers laboratories have led preclinical and early clinical development of poly(ADP-ribose) polymerase (PARP) inhibitors (PARPi) as radiosensitizers. PARPi increase radiosensitivity in GBM models and clinical studies have shown both olaparib and veliparib to be well-tolerated in combination with radical radiotherapy in GBM patients. To date, however, there is no evidence that PARPi improve efficacy. Addition of veliparib to radiotherapy and adjuvant temozolomide did not improve survival in MGMT unmethylated GBM, and randomised data for olaparib are awaited. One potential barrier is hypoxia, which is highly prevalent in GBM and associates with radioresistance and poor outcomes. Giaccia recently showed that moderate hypoxia (2% oxygen) promotes resistance to PARPi, with tirapazamine restoring sensitivity. Hypoxia mediated PARPi resistance was attributed to reduced induction of reactive oxygen species (ROS) and diminished DNA damage. Since the radiosensitising effects of PARPi involve elevated ROS and DNA damage we hypothesised that moderate hypoxia would similarly reduce the radiosensitising activity of PARPi in GBM. Higgins has shown that mitochondrial targeting agents like atovaquone can combat hypoxia and increase radiosensitivity by inhibiting oxygen consumption. Atovaquone is clinically approved and exhibits excellent brain penetration. Aim: We will evaluate the ability of atovaquone to reduce hypoxia and overcome resistance to the radiosensitizing effects of PARPi in hypoxic, clinically relevant models of GBM. Methods: In vitro studies will utilise 2- and 3-dimensional cultures of patient-derived GBM cell lines (G7, E2, R10, Ox5); in vivo work will use our clinically relevant orthotopic G7 xenograft model. Mechanistic studies will measure effects of atovaquone and olaparib on oxygen consumption rate (Seahorse), hypoxia, ROS and DNA damage (immunofluorescence); radiosensitizing effects will be measured by clonogenic survival and spheroid growth delay. In vivo, hypoxia will be measured by in vivo imaging (oxygen-enhanced and glucose CESL-MRI) and validated by immunohistochemistry. Efficacy studies will evalute all combinations of atovaquone, olaparib and radiotherapy in the G7 model, using established SARRP protocols for micro-irradiation and symptom-free survival as endpoint. How results will be used: Mechanistic and efficacy data will inform development of an early phase clinical trial in patients with newly diagnosed, hypoxic GBM.


Research activity codes: 5.5 RADIOTHERAPY AND OTHER NON-INVASIVE THERAPIES
Health categories: CANCER AND NEOPLASMS
Title: Early detection of cancer in germline BRCA1/2 mutation carriers
Funder: Cancer Research UK

Abstract: Background Women carrying germline BRCA1/2 have a 65-70% lifetime risk of developing breast cancer. Current management options are either risk reducing mastectomy (RRM) or intensive screening, both of which can have a significant impact on those women who remain cancer free. Germline BRCA1/2 carriers would, therefore, benefit from additional tools to predict their risk of developing cancer. This is especially true in those patients carrying Variants of Uncertain Significance (VUS). We hypothesise that by implementing novel artificial intelligence(AI)-based computational approaches for digital pathology, subvisual morphometric phenotypes in the normal breast tissue can be identified and might be indicative of early signs of breast cancer. Aims Our aim is to (i) deliver the first repository of digitised whole slide images (WSI) of breast tissue, derived from prophylactic RRM of germline BRCA1/2 carriers with and without in situ or invasive breast cancer; (ii) advance our understanding of physiological processes underlying tumour initiation in the normal breast tissue; and (iii) to identify phenotypic characteristics of premalignant changes in breast tissues to aid in tool development for early cancer detection in germline BRCA1/2 carriers. Methods We will collect breast tissue from: A) healthy patients with known germline pathogenic or VUS BRCA1/2 status derived from RRM; (B) the contralateral normal breast of breast cancer patients with known germline pathogenic or VUS BRCA1/2 alterations; (C) ipsilateral normal tissue; and (D) peri-tumoural regions from breast cancer patients with known germline pathogenic or VUS BRCA1/2 alterations. Digitised WSI of H&E and multiplex immunofluorescence-stained tissue will be explored by single cell resolution and spatial cellular configuration models. To handle the multi-dimensional data, a combination of signal processing (Grassmannian Vector of Locally Aggregated Descriptors, gVLAD) and deep neural network methods is proposed, which is capable of correlating complex morphological features whilst requiring less data. How the results of this research will be used. Identifying premalignant features in the normal breast of germline BRCA1/2 carriers will provide new avenues for early cancer detection. Healthy BRCA1/2 carriers could opt for periodical breast biopsies, avoiding unnecessary RRM. If validated prospectively, our tool provides a management option and could be included in the NHS clinical screening programme for germline BRCA1/2 carriers, with the intent to intervene if premalignant features are observed. Moreover, by identifying biomarkers for patient selection to ongoing therapeutic strategies, our tool could increase the efficacy of current breast cancer prevention agents, and could be translatable to several early cancer detection approaches.


Research activity codes: 2.1 BIOLOGICAL AND ENDOGENOUS FACTORS;4.1 DISCOVERY AND PRECLINICAL TESTING OF MARKERS AND TECHNOLOGIES;4.2 EVALUATION OF MARKERS AND TECHNOLOGIES
Health categories: CANCER AND NEOPLASMS
Title: RADIANT: The application of machine learning to imaging and biological features from a clinical trial to predict outcomes to chemoradiation in locally advanced rectal cancer
Funder: Cancer Research UK

Abstract: Artificial intelligence approaches have the potential to affect several facets of cancer therapy and represent a gateway to the next frontier of precision cancer therapy, reconciling extraordinary amounts and different types of data into actionable decision aids. Anonymized patient-level data from clinical research are increasingly recognised as a fundamental and valuable resource. Post-hoc analysis of trials can take a long time, but treatment concepts might have changed. The proposal is a demonstrator pathway making use of data collected as part of a CRUK funded trial, fulfilling CRUK’s objective to learn as much as possible from every patient on a clinical trial. In this exemplar study we will demonstrate the feasibility of combining a clinical trial dataset, including clinical covariates, treatment toxicity and efficacy outcomes (ARISTOTLE ASCO 2020) with the associated histopathological, imaging and biological data (from the S:CORT consortium) that will provide the basis for future hypothesis driven and hypothesis free analyses.


Research activity codes: 4.2 EVALUATION OF MARKERS AND TECHNOLOGIES
Health categories: CANCER AND NEOPLASMS