Summary
Understanding the molecular and cellular mechanisms of how epithelial tissues maintain a homeostatic state throughout the lifespan of mammals is a major challenge for developmental and stem cell biologists. From a developmental perspective, the epithelium of the mammary gland is unique as it undergoes most of its development during adulthood.
Despite recent efforts of characterising the tissue homeostasis at a cellular level, little is known about how this is affected by various developmental processes such as pregnancy or aging and how this might ultimately disrupt epithelial homeostasis resulting in malignant outgrowth. In this study we wish to further our understanding of the changing nature of the differentiation dynamics of the mammary gland.
To fully understand how tissue homeostasis is affected by parity and other events it is mandatory to characterise the differentiation dynamics in an age-dependent manner. This becomes evident when looking at epidemiological data. Age is the greatest risk factor for breast carcinomas, and it has been suggested that this is not only due to accumulation of mutations but also due to decreased clonality and selection of clones with proliferative advantage.
More importantly, the age-dependent risk of tumorigenesis is modulated by for example parity, which attenuates the risk or predisposing germline mutations which increase the age-associated risk. However, the exact mechanisms and effects of the interaction of these risk factors on tissue homeostasis of the mammary gland still remain to be elucidated.
Our lab uses scRNAseq to address these questions by studying the effects of parity, aging and germline mutation (BRCA1/2) on the homeostasis of the mammary gland in mouse and human (PMID:25574598, 29225342, 30127402, 32612221, 33686070, 35091553, 38548988).
Project aims
For this project the student will be analysing a large dataset of mouse and human scRNAseq which has been collected over several years to identify mechanisms that promote the transition of precancerous cells to cancer.
This project will suit someone with some experience in using R and/or Python. In addition, the student will have the opportunity to validate some of the findings using orthogonal techniques such as IHC and other spatial technologies.
Contact details
Professor Walid Khaled - wtk22@cam.ac.uk
Opportunities
This project is open to applicants who want to do a:
- PhD