<?xml version="1.0" encoding="UTF-8"?><ns2:project xmlns:ns1="http://gtr.rcuk.ac.uk/gtr/api" xmlns:ns2="http://gtr.rcuk.ac.uk/gtr/api/project" xmlns:ns3="http://gtr.rcuk.ac.uk/gtr/api/fund" xmlns:ns4="http://gtr.rcuk.ac.uk/gtr/api/person" xmlns:ns5="http://gtr.rcuk.ac.uk/gtr/api/project/outcome" xmlns:ns6="http://gtr.rcuk.ac.uk/gtr/api/organisation" ns1:created="2026-07-08T08:44:08Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/E9C9C1DA-E708-43B5-8BF4-66829C905943" ns1:id="E9C9C1DA-E708-43B5-8BF4-66829C905943"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/ABF6CB4E-A671-4FCA-A925-37543E7AC859" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/800BBA7A-5118-4B70-A602-160FB617C9E6" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/800BBA7A-5118-4B70-A602-160FB617C9E6" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2023-04-29T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/5E18D9C6-F353-45E9-96FE-B8C8729B8168" ns1:rel="FUND" ns1:start="2022-11-01T00:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10044369</ns2:identifier></ns2:identifiers><ns2:title>Developing profiles for early pancreatic cancer through bioinformatics analysis</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Grant for R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>Pancreatic cancer is the 5th leading cause of cancer-related death in the UK. Statistics have shown that the five-year survival rate will be markedly increased from 3% to 39% if tumours can be detected at early stages (Cancer Facts &amp;amp; Figures, 2021). However, due to the lack of validated and specific screening tests for early-stage pancreatic cancer patients who are usually asymptomatic, more than 80% of the pancreatic cancer cases are diagnosed at advanced stage, highlighting the needs to identify sensitive and specific markers for detection of the cancer at early stages. Studies have shown that circulating tumour cells remain detectable across all stages of pancreatic cancer, but with an uncertain detection rate of 11%-92% depending on the markers used for enrichment (Martini et al., 2019); in contrast, immune cells that respond to early pancreatic cancer progression exhibit distinct characteristics in peripheral blood and can be exploited for early diagnosis of pancreatic cancer in a non-invasive manner (Pereira et al., 2020).

This project focuses on bioinformatics analysis of the peripheral blood RNA-seq data generated from early pancreatic cancer cases. We differentiate our technology from others with the unique selling points listed as follows. (1) High sensitivity and specificity compared to detecting tumour DNA (49.5% accuracy; Klein et al., 2021); (2) Using large training data sets to avoid demographic differences regarding age, sex, disease status (e.g., diabetes, pancreatitis); (3) Ability of extracting novel biomarkers from different types of samples (e.g., blood, biopsy) and data (e.g., RNA, DNA, protein, etc.) to meet unique diagnostic needs.

We have the following objectives. (1) Upgrading our bioinformatics software package that can be used to automatically classify and predict early cancer cases (2) Validating the resulting biomarkers in samples from our early adopters who agree to beta test our product. (3) Filing patents to protect the new biomarkers with diagnostic potential.

Upon completion of the project, we are able to license the validated biomarkers to our biotech and clinical partners for commercialisation of diagnostic products. This will result in a clear clinical pathway from the blood sample, through data analysis, to diagnostic outcome and personalised therapy that meets the needs of pancreatic cancer patients on an individual basis.</ns2:abstractText></ns2:project>