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Understanding the molecular subtype of a cancer is becoming an importance part of the diagnostic process as it helps a doctor better understand a patient’s prognosis, determine the best course of action for treatment and helps researchers devise new, more-efficient, precision therapies.

Image information can be used to predict the molecular classification of patient tumour samples in colour, using state-of-the-art deep learning models in pathology © S:CORT

EMERALD Pancreas: Evaluation of hypofractionated adaptive radiotherapy using the MR Linac in localised pancreatic cancer

Designing Novel Vectors for Targeted In Vivo Transduction of Monocytes to Deliver Cancer Therapeutics into the Tumour Microenvironment

Student Interviews

The paradox of AMER1 driver mutations in colorectal cancer

Developing a neoantigen-like, ROP-based vaccine targeting SVN (ROP-SVN) to boost host immune responses

Tumour avatars of patients for assessment of therapeutic efficacy

Hippo signalling in Natural Killer Cells maturation and function

Hippo signalling in Natural Killer Cells maturation and function

60 seconds with...

Welcome

The Department of Oncology's mission is to improve cancer care through research and teaching. There is strong emphasis on translation, with established infrastructure to develop scientific insights toward clinical appreciation.

Identifying unique vulnerabilities of polyploid tumour cells to enhance radiation sensitivity

Course Overview

The MSc in Radiobiology is scheduled to run over one academic year as a full-time course consisting of eight compulsory taught modules and a research-based dissertation.

UKHSA project - Identifying biomarkers to prevent medical radiation toxicity: Role of Adipose tissue in skin toxicity during radiotherapy

Characterisation of the cross-talk between the hypoxia-induced DNA damage and unfolded protein responses

Developing a novel type of cancer vaccine for genetically-defined tumours

ARCADIAN: Atovaquone with Radical ChemorADIotherapy in locally Advanced NSCLC

Accelerator technology advancements enabling MV photon FLASH radiotherapy

Developing novel therapeutic strategies to improve radiotherapy

Elucidating the role of tumour microenvironment in breast cancer metastasis

The Fanconi anaemia pathway and cancer: a molecular dissection

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Oxford and GSK launch £50million immuno-prevention programme to advance novel cancer research

Global biopharma company GSK invests up to £50 million in a collaboration with Oxford to advance the understanding of how cancer develops, which could inform future development of vaccines to prevent cancer.

Machine Learning Enhances Detection of Multiple Cancer Types from Blood

Researchers from the University of Oxford have developed TriOx, a highly sensitive blood test that detects six cancers at their earliest stages. Published today in Nature Communications, the findings highlight the test’s potential to transform early cancer detection and improve patient outcomes.

Study Publishes New Insights on Goblet Cell Differentiation in Colorectal Cancer

The Oncology Department at the University of Oxford is excited to announce the forthcoming publication in the Proceedings of the National Academy of Sciences (PNAS) of the research paper “Goblet Cell Differentiation Subgroups in Colorectal Cancer.” This groundbreaking study sheds light on the role of goblet cell differentiation in colorectal cancer (CRC) and its impact on cancer progression and prognosis.

Ground-breaking Study reveals previously unknown genetic causes of Colorectal Cancer

A pioneering study, led by UK universities, including the University of Oxford, The Institute of Cancer Research, London, the University of Manchester and the University of Leeds, has provided the most comprehensive analysis to date of the genetic makeup of colorectal cancer (CRC).

Subashan Vadibeler wins 2024 Lasker Essay Contest

Subashan Vadibeler, a recent Oxford Rhodes scholar and Department of Oncology student, is one of five co-winners of the international 2024 Lasker Essay Contest, sponsored by the Lasker Foundation.