NIHRDataInsights/HRCSData huggingface dataset:
Title: Towards a ‘toothbrush’ sensor for passive biomarker monitoring - "Sens Or Pass"
Funder: Cancer Research UK

Abstract: Background Early diagnosis of cancer is a priority for the NHS, with a target of 75% of new cancer diagnoses detected at early stage by 2028. Early stage cancer diagnosis is key to allow a wider range of treatment options which translate in increase survival. Cancer affecting the upper respiratory and gastrointestinal tracts have some of the lowest level of early stage diagnosis amongst all cancer types in the UK. These cancers very often have non-specific symptoms and high prevalence in population at high risk factors such as smokers and heavy drinkers, making them very difficult to identify at early stage development. It is well known that certain molecular biomarkers are correlated and specific to cancers. As such, the development and use of analytical techniques for the identification and quantification of such biomarkers is key to achieve effective early diagnosis. Aims This proposal aims at finding a new way to assist early detection of cancer in primary care and identify high cancer risk individuals for urgent referral for diagnostic testing. This will be achieved by developing "toothbrush" electrochemical-based tests that passively, e.g. during teeth brushing, can accurately, rapidly and cost effectively identify and detect molecular biomarkers related to upper respiratory and gastrointestinal cancers lung, such as head and neck, oral and oesophageal cancers. Methods The proposal will utilise the following: - Literature review and analysis of existing cancer proteomic database to identify the molecular biomarkers; - In vivo saliva sample collection and analysis; - Machine learning to develop clinical algorithms; - Synthesis of molecularly imprinted polymers having high affinity for the molecular biomarkers previously identified by means of the analysis of cancer proteomic databases and in-vivo saliva samples; - Fabrication of the sensor using aerosol jet imprinting; - Electrochemical characterisation of the device and detection of molecular cancer biomarkers. How the results of this research will be used The proof-of-principle sensor device developed in this grant would be of great benefit to GPs for the rapid identification of those patients that need urgent referral for suspected cancer even though apparent symptoms are not present. This test would operate passively as part of an individual daily routine such as toothbrush. This device could initially be used in the clinical assessment of patients presenting to primary care to identify undiagnosed lung, oesophagogastric, or oropharyngeal cancers.


Research activity codes: 4.1 DISCOVERY AND PRECLINICAL TESTING OF MARKERS AND TECHNOLOGIES;4.2 EVALUATION OF MARKERS AND TECHNOLOGIES
Health categories: CANCER AND NEOPLASMS
Title: MAARS Multimodal Active Adaptive Risk Stratification for Gastrointestinal Cancer
Funder: Cancer Research UK

Abstract: Background Compared to similar economically developed countries, the UK has an appalling record for diagnosing cancers at a late stage, when curative treatment is not possible. For example, the UK has one of the poorest survival rates for colorectal cancer in Europe1 which is thought to be partly related to late presentation, delays in diagnosis and delays in treatment. The five-year survival for early-stage colorectal cancer is greater than 90% compared with 10% for widespread cancer at diagnosis. Evidence suggests that increased awareness of symptoms and earlier diagnosis could help improve treatment options and improve 5 year survival. It has been estimated that such an approach might save 5,000 lives even without any new medical advances. Whilst there have been some advances over the last decade, there is currently no adaptive interpretable decision tool to enable earlier cancer diagnosis available for use at the point of care. There is no risk scoring system which updates and refines cancer risk over time as further clinical information becomes available along the patient pathway. Existing systems implemented into the NHS, such as the First-of-Type QCancer risk stratification system, only provide static risk estimates and do not include results of blood tests or scans. Aims Our aim is to determine whether adaptive interpretable decision-making tools enable early diagnosis of gastrointestinal cancer and improve patient outcomes. Methods We will analyse of routinely collected anonymised NHS linked multimodal data to assemble cohorts of patients over past 5 years presenting to GP. The primary data source is GP electronic health records linked to secondary care outcomes. We will use novel engineering methods to to derive cluster-based patient characteristics to understand which tests/diagnoses are considered in each clinical phenotype to assist the decision-making process. Furthermore, we will implement cluster-based patient-specific interpretability maps to understand when and which biomarker(s)/test(s) contribute to phenotypes of outcomes. We will compare this to established statistical techniques. How research will be used? We will develop and validate an active adaptive interpretation risk/tool to generate personalised clinical phenotypes linked to appropriate clinical pathway to help target resources to those at highest risk of having a cancer, as yet undiagnosed, and also most likely to benefit. It would also identify low-risk patients who can be reassured. As the patient progresses along the clinical pathway, their risks will be updated to incorporate the results of investigations to further refine the class assignment and improve decision making.


Research activity codes: 8.1 ORGANISATION AND DELIVERY OF SERVICES
Health categories: CANCER AND NEOPLASMS
Title: Target validation of apoptotic caspase activity in colorectal cancer
Funder: Cancer Research UK

Abstract: Background While screening has improved early detection of colorectal cancer (CRC), unfortunately 50% of patients are still diagnosed at an advanced stage. Treatment for advanced CRC has not improved significantly in over two decades. Secondly, sub-types of CRC have been defined for which no targeted therapies exist. More effective therapies for CRC are therefore urgently required. CRC therapies typically work by killing cancer cells through mitochondrial apoptosis. Nevertheless, incomplete tumour kill remains a big hurdle. Addressing this key problem, we have found that how a cancer cell dies profoundly effects therapeutic efficacy. During mitochondrial apoptosis, mitochondria release proteins that activate caspase proteases leading to rapid cell death. Crucially, mitochondrial outer membrane permeabilisation (MOMP) represents a point-of-no-return, since cells die irrespective of caspase activity. We have found that killing cancer cells in the absence of caspase activity, so called caspase-independent cell death (CICD) makes them immunogenic. By engaging anti-tumour immunity, CICD leads to a much more potent effect on tumour clearance than cytotoxic agents alone. This provides strong rationale for targeting apoptotic caspases to better treat colorectal cancer. This research will comprehensively validate apoptotic caspase inhibition as a therapy to treat advanced and treatment refractory CRC. Aims Comprehensive functional target validation of mitochondrial apoptotic caspase inhibition in colorectal cancer Methods To validate caspase inhibition, state-of-the-art mouse models that faithfully mirror advanced and treatment-refractory CRC. We will investigate inhibition of caspase activity alone (genetically/pharmacologically), with standard of care CRC therapies and in combination with immunotherapy (checkpoint blockade). Using patient derived cell lines that span all CRC subtypes we will investigate the ability to induce caspase independent cell death (by imaging) and the inflammatory/immunogenic output of CICD (by qRT-PCR, multiplex ELISA). How the results of this research will be used This research will comprehensively target validate inhibition of mitochondrial caspase activity as a way to treat CRC. This will provide crucial supportive rationale, as well as target guidance, for ongoing efforts (by Beatson DDU) to develop effective caspase inhibitors.


Research activity codes: 5.1 PHARMACEUTICALS
Health categories: CANCER AND NEOPLASMS
Title: A multimodal electronic capsule for identification of visual and biological markers of early stage colorectal cancer - Samplecam
Funder: Cancer Research UK

Abstract: Background : Up to 5% of the world’s population will be affected by colorectal cancer during their lifetime, and unfortunately, most of these cancers are discovered late when treatment is no longer effective. During the Covid-19 pandemic, access to endoscopy units has been severely compromised, affecting patients presenting with non-specific abdominal symptoms and patients at high risk of developing colorectal cancer who should receive regular colonoscopic surveillance. Faecal immunohistochemistry test (FIT) has been proposed as an alternative for patients with non-specific abdominal symptoms to stratify those who need an urgent colonoscopy; however, colonoscopy remains the standard of care. An alternative method of screening for colorectal cancer accessible to primary care is proposed in this project, with the development of a small ingestible device called samplecam, which could detect early malignant or pre-malignant lesions. Aims: This project aims to develop the underpinning technology that will enable samplecam to be used in a primary care setting to facilitate the early detection of colorectal cancer. Methods: This aim will be achieved by completing several tasks using varying methods. This includes using sociological techniques to determine patient and GP acceptance of the technology. A clinical trial will begin to build a dataset of colonoscopy and capsule endoscopy images from high-risk populations. This data-set will be used to validate machine learning models trained to detect subtle changes in the appearance of the gastrointestinal tract which could signify early stages of CRC and form the basis of future studies for enhancing low-resolution capsule endoscopy footage. Finally, a proof of concept sampling capsule will be created using additive manufacturing and off-the-shelf electronic components, which will be tested in phantom models. How the results of this research will be used: The technology developed as part of this research will eventually be tested in further clinical trials to demonstrate its effectiveness in the early detection of colorectal cancer. Ultimately, it is expected that this technology will potentially improve the early detection of colorectal cancer in primary and secondary care, which will beneficially impact survival outcomes.


Research activity codes: 4.1 DISCOVERY AND PRECLINICAL TESTING OF MARKERS AND TECHNOLOGIES;4.2 EVALUATION OF MARKERS AND TECHNOLOGIES
Health categories: CANCER AND NEOPLASMS
Title: Cell Plasticity & Epigenetics
Funder: Cancer Research UK

Abstract: A striking example that brings forward the plasticity of cancer cells is their resilience when confronted with therapeutic paradigms. Indeed it is acknowledged that, in response to sustained treatment, cancer cells may acquire genetic mutations that permanently block the tumouricidal action of the administered drug. However, in other settings, the emergence of fully drug-resistant clones cannot be explained by genetic mechanisms and results from cells that escape the initial death challenge by “adapting” to the pernicious agent. In the latter scenario, the traits granting adaptation to treatment are reversible in nature and are readily inherited through several cell divisions. This particularity strongly suggests the existence of a non-genetically encoded “temporal memory” underlying the acquisition of “drug-tolerant” phenotypes and represents an exquisite example of the transfer of non-genetic information through cell division. Along those lines, the ultimate goal of our lab is to unravel the network of molecular systems supporting cell plasticity and to shed light onto the core mechanisms underlying the inheritance of epigenetically encoded traits. We are currently setting up a multidisciplinary team that takes advantage of high-throughput sequencing and imaging technologies as well as more traditional molecular and cellular biology techniques to analyse the role of non-coding RNA molecules in the generation and propagation of epigenetic memories through subsequent cell divisions with particular interest in the acquisition of drug-tolerance in cancer relevant settings.


Research activity codes: 2.1 BIOLOGICAL AND ENDOGENOUS FACTORS;5.1 PHARMACEUTICALS
Health categories: CANCER AND NEOPLASMS
Title: CRUK/OHSU JOINT FUNDING AWARD - Longitudinal tracking of genetic and epigenetic signals for blood-cancer risk prediction - CRUK and OHSU Lead Applicants contribute equally, and this project will be jointly funded if successful
Funder: Cancer Research UK

Abstract: Background The first genetic steps towards cancer occur in healthy tissue decades before cancer onset. This raises the possibility that these early events could be used as a bellwether for predicting who is most at risk of developing cancer. Serial blood samples collected annually from hundreds of thousands of initially healthy people afford a unique opportunity to do this. By “zooming in” on the people who subsequently develop cancer, we can “rewind” time by performing genetic and epigenetic analyses on blood samples collected years before the cancer was diagnosed. An attractive initial target for this ambitious vision is the aggressive blood cancer Acute Myeloid Leukaemia (AML). Because AML is characterised by a relatively small number of genetic and epigenetic alterations, which are readily detectable in peripheral blood, it provides a unique opportunity to address one of the most fundamental questions in early detection: “How many years before diagnosis can cancer be reliably predicted?” Aims We will generate a unique dynamic data set that paints a highly quantitative genetic and epigenetic portrait of how AML evolves from healthy tissue. To do this we will: 1: Define the genetic evolution preceding AML by exploiting 10 years of serial bloods. 2: Define the epigenetic evolution preceding AML by exploiting 10 years of serial bloods. 3: Develop statistical techniques using machine learning to forecast blood-cancer risk. Methods The UK based team will focus on using a novel sequencing strategy to interrogate the genetic alterations and clonal evolution leading to AML. We have developed an error-correctable sequencing strategy that can detect variants down to 1 part in 10,000, which will be used to determine how early the cancer-driving genetic alterations emerge. The OHSU based team will focus on profiling DNA methylation changes in these longitudinal samples and how these changes differ between the AML cases and controls. Bringing these data together, Dr. Bacallado and Dr. Sonmez (machine learning and AI experts) will use this rich data resource to train a set of statistical and machine learning models that are capable of making probabilistic forecasts of leukaemia risk. How the results will be used Early detection of cancer is a major strategic focus for CRUK and OHSU. Our proposal will outline fundamental limits of early detection (how early can one reliably predict?) and identify the most informative signals for future biomarker development (how often should we sample, what should we measure?).


Research activity codes: 2.1 BIOLOGICAL AND ENDOGENOUS FACTORS;4.1 DISCOVERY AND PRECLINICAL TESTING OF MARKERS AND TECHNOLOGIES
Health categories: CANCER AND NEOPLASMS
Title: CRUK-OHSU JOINT AWARD - The role of extracellular vesicles in senescence surveillance - CRUK and OHSU Lead Applicants contribute equally, and this project will be jointly funded if successful
Funder: Cancer Research UK

Abstract: Background Cellular senescence is a stress-responsive tumour suppressor mechanism. Senescent cells accumulate in chronic inflammatory cancer-prone tissues. Senescent cells have profound non-autonomous effects upon immunocytes, driving their own destruction. Failure of this immune reaction with persistent senescence leads to tumorigenesis. Understanding how senescent cells communicate with their microenvironment represents a promising strategy to detect incipient tumorigenesis. Extracellular vesicles (EVs) are nanometer-scale membrane-bound vesicles, emitted from most cells types and are detectable in the circulation. Emerging evidence suggests they play a significant role in non-autonomous signalling. Tumor-derived EVs can be engulfed by and modulate the function of macrophages in distant lymph nodes. Previous in vitro studies have shown that senescent cells secrete EVs and that these carry specific nucleic acid and protein cargos, driving non-autonomous signaling. Nothing is known about senescent cell-derived extracellular vesicles (sEVs) in vivo. Hypotheses We hypothesise that: 1) senescent cells regulate immunocytes in vivo through sEVs and their cargo; 2) sEVs and regulated immune responses will be circulating diagnostic biomarkers for early detection in individuals at high-risk of cancer. Methods We aim to define a signature of sEVs, define their fate and precise effect upon the immune system before validating our findings in patients. To define the form and fate of sEVs we will use multiplexed proteomics to define a common phenotype of sEVs in multiple models of senescence in vitro. We will use genetic labelling of sEVs to conduct fate-tracing in mouse models of senescence, in particular identifying the immune cells that engulf sEVs. To identify the immunomodulatory role of sEVs we will analyse immune-mediated clearance of senescent cells, when sEVs production is blocked. We will then use single cell RNA-Sequencing to identify the expression changes in immunocytes that are dependent upon sEVs, before functional validation. We will then recruit patients with chronic inflammatory cancer-prone conditions, such as cirrhosis and oral leukoplakia to study whether sEVs are detectable circulating biomarkers of tissue senescence burden and their applicability for early detection. How the results of this research will be used If successful in this proposal we will have: 1) Defined a signature of sEVs, their ultimate fate and the immune cells that they regulate. 2) Identified sEVs in the circulation of patients with cancer-prone conditions To develop sEVs as clinically applicable biomarkers we will then seek to correlate form or function of sEVs with the tissue burden of senescence and the risk of subsequent cancer development.


Research activity codes: 4.1 DISCOVERY AND PRECLINICAL TESTING OF MARKERS AND TECHNOLOGIES
Health categories: CANCER AND NEOPLASMS
Title: Unbiased in vivo CRISPR screen to identify novel T-cell immune checkpoints for cancer immunotherapy
Funder: Wellcome Trust

Abstract: Harnessing the anti-tumour potential of T-cells for cancer treatment has been successful for a number of malignancies. The blockade of immune checkpoints, such as the T-cell receptor PD-1, reduces tumour burden in patients and can lead to durable cures for some. Treatment efficiency is further improved when PD-1 is targeted simultaneously with other checkpoints such as CTLA4 or LAG3. Despite the potential of co-targeting multiple checkpoints, the combinatorial co-inhibition of all known as well as yet undiscovered immune checkpoints has not been systematically assessed. Furthermore, genome-wide screening to identify novel checkpoints as well as modifiers of such checkpoints has been technically challenging. The objective of this proposal is to map the combinatorial landscape of known checkpoints coupled with PD-1 blockade as well as discover potentially new targets for immune activation against cancer. We propose to use of transplanted hematopoietic stem cells with different combinations of disabled T-cell surface proteins to screen for combinations which enable T-cell infiltration and tumour reduction in a PD-1 suppressed mouse melanoma model. Initially combinations of known checkpoints will be assessed, subsequently the screen will be expanded to all T-cell membrane proteins to identify novel immune checkpoints.

Lay abstract: T-cells are an important component of the immune system that can attack and kill tumour cells. However, some tumour cells are able to inactivate T-cells by hijacking natural immune checkpoints that prevent the immune system from targeting normal healthy tissue. Blockade of PD-1, an immune checkpoint receptor on the surface of T-cells, prevents the tumour from inactivating T-cells, resulting in immune-regulated reduction of tumour burden. However, the effect is incomplete. Inhibitors of other checkpoints have also been developed with similar outcomes. When other checkpoints are targeted simultaneously with PD-1, the treatment efficacy is improved considerably. We propose a systematic combinatorial testing of all checkpoint inhibitors for reduction of tumour burden in a melanoma mouse model. We will also take advantage of recent genome editing technologies to identify novel immune checkpoints on T-cells. This work will help identify novel therapeutic targets for cancer treatment.

Research activity codes: 2.1 BIOLOGICAL AND ENDOGENOUS FACTORS
Health categories: CANCER AND NEOPLASMS
Title: Epigenetic mapping of immune cells in colorectal cancer
Funder: Wellcome Trust

Abstract: A recent large-scale study of 39 different types of cancers has shown that the expression of the gene KLRB1, encoding the protein CD161, was the top predictor of favourable prognosis and overall survival. CD161 is expressed on various immune cells, including newly discovered populations such as MAIT cells and innate lymphoid cells. To identify the intratumoural cells contributing to improved prognosis, I will develop a tool for the bioinformatic enumeration of pure cell types from complex populations. As chromatin accessibility and enhancer landscape reflects cell identify better than mRNA levels, differentially accessible loci will be a unique signature for each cell type. Using state-of-the-art technologies, my key goals are to: 1. Generate a comprehensive epigenetic signature matrix encompassing novel immune cell types 2. Use this to deconvolute the epigenome of colorectal carcinoma tumours 3. Directly identify the infiltrating CD161-expressing population correlated with improved survival in colorectal cancer By improving our understanding of how multiple immune populations collectively infiltrate tumours, including novel CD161-expressing cells, this work will enable future cancer immunotherapies to target protective immune subsets. Furthermore, the proposed work will provide a resource that can be easily applied to epigenetic data from other malignancies.

Lay abstract: Recently the success of cancer treatments targeting the immune system has highlighted the importance of understanding the role of immune cells in cancer. Identifying which cells are infiltrating the tumour can be critical in selecting the correct type of immune therapy patients should receive. My plan is to generate a tool for accurately identifying the frequency of different immune cells within a tumour. First, I will generate a large map of the DNA state of immune cells, which controls how genes in the immune cells are turned on or off, and is specific to each immune cell. I will compare this to the DNA map of colorectal cancer tissues and use a computer-based algorithm to estimate the frequency of each immune cell within the colorectal tumours. This will provide a resource that can be used to aid the choice of immunotherapy and development of novel therapies for cancer.

Research activity codes: 2.1 BIOLOGICAL AND ENDOGENOUS FACTORS
Health categories: CANCER AND NEOPLASMS