(a) This project aims to unlock how bacteria living within head and neck squamous cell carcinoma (HN-SCC) influence patient survival, with a special focus on a group of bacteria called Fusobacterium.
Our recent published research suggests that patients whose tumours contain more Fusobacterium may actually have better outcomes. However, only a small subset of patients has been studied so far, and we do not fully understand why this effect occurs in humans or whether other bacteria play a role.
The student will analyse large genetic datasets from hundreds of cancer patients in The Cancer Genome Atlas (TCGA) and Cancer Genomics England (CGE) HN-SCC cohorts, which will be filtered using advanced computational methods to derive bacterial communities living within cancers. They also provide data about the cancers themselves and their associated immunity. Using imputed metagenomics, we can also predict which molecules the microbiome produces.
Using the full TCGA cohort (500+ patients), the student will map intra-tumoural bacterial communities, explore how they interact with each other, the tumour, and immune cells living within it. They will also explore whether certain bacterial products, especially those known to kill HN-SCC in laboratory experiments conducted at the Reis Ferreira lab, are linked to better patient survival. Findings will be validated in the unique UK CGE dataset.
In tandem with our ongoing wet lab research, this project will provide critical information to develop novel prognostics and treatments for HN-SCC.
(b) Skills and Techniques Developed:
The student will gain experience in bioinformatics, data analysis, and cancer/microbiome research. They will learn to handle large-scale genetic data, interpret complex biological patterns, and work with clinical information. The project will also involve scientific communication and multidisciplinary collaboration.
(c) Aims:
The overarching aim is to understand how bacteria living within HN-SCC affect survival to improve patient care.
(d) Yearly Objectives:
Year 1: Learn core bioinformatics skills, process genetic data from cancer patients, and identify key bacteria linked to survival.
Year 2: Explore how groups of bacteria and their metabolic activities influence cancer outcomes, and investigate how bacteria interact with cancer-associated immunity.
Year 3: Validate findings, prepare results for publication.
Year 4: Complete analysis, write thesis, and present/publish findings.
(e) 3-Month Rotation Project:
To develop a robust foundation for the main project, the student will analyse a subset of already available cancer data (HN-SCC/colorectal/oesophageal cancers) to identify the most common bacteria in tumours and explore their links to patient outcomes while controlling for established confounding factors.