Black Leaders in Cancer PhD Programme (Ram DasGupta & Tom Bird)

Job title

Black Leaders in Cancer PhD Programme (Ram DasGupta & Tom Bird)

Job reference

REQ00372

Date posted

21/10/2024

Application closing date

25/11/2024

Location

Glasgow

Salary

Stipend - £21,000 per annum

Package

All tuition fees will be covered

Contractual hours

Blank

Basis

Blank

Job category/type

PhD Students

Attachments

Blank

Job description

stages of fatty liver disease

Intra-tumour heterogeneity (both genetic and transcriptomic) poses one of the biggest challenges in the treatment of cancer treatment. The presence of clonal heterogeneity gives rise to multiple populations of competing tumour cells with distinct selective fitness. This in turn allows clonal evolution (selection of pre-existing clones or acquired mutations or plasticity driven by epigenetic modifications) under different selection pressures, such as drug treatment, and metastatic dissemination. More recently, we are beginning to identify the importance of a heterogeneous and dynamic tumour microenvironment (TME), including immune cells, endothelial cells and fibroblasts, that may serve important functions via signalling interactions with the transformed, malignant tumour cells. The function of the TME was specifically highlighted in our recent single cell study on the “onco-fetal reprogramming” of the TME in human liver cancer (HCC). By generating a single cell atlas of human hepatocellular carcinoma (HCC) we identified a remarkable fetal-like reprogramming of the HCC-tumour microenvironment (TME) into an immuno-tolerant ecosystem, which promotes growth and survival of cancer cells. Moreover, this onco-fetal reprogramming was not restricted to HCC-TME. We identified the emergence of similar onco- fetal signatures in cirrhotic liver samples as well as in a mouse model physiological regeneration. Additionally, we also find the activation of these fetal-like regenerative programs in mouse models of obesity, suggesting distinct aetiologies of liver damage can reprogram the intra-hepatic microenvironment into a niche that is favourable to the development of tumours. Based on these observations, we hypothesize that a growth-promoting, immune-tolerant microenvironment is established earlier during chronic liver disease/damage, which drives the creation of a pro-tumorigenic niche that supports growth and survival of malignant cells. However little is known about the mechanisms, signalling pathways, and dynamic cell-cell interactions, both in time and space, that underlie the generation of disease associated microenvironment during the progression of fatty liver disease to HCC. Obesity related HCC represents one of the major global health challenges currently. Better understanding of prognostic cell-state-based biomarkers, location of disease-prognostic cells in the TME, plus downstream mechanisms would not only help in early detection and clinical management, but also lead to the identification of novel, TME-associated therapeutic targets that could be utilized in the areas of both preventative medicine, as well as treatment of advanced cancer to block tumor progression into resistant, metastatic states. While single cell transcriptomics approaches are excellent in identifying novel, context-dependent cell types/cell states and can be used to infer cell- cell interactions, they do not directly reveal the spatial coordinates or arrangement of the tumour cells with respect to their microenvironment; how they change during tumour evolution and the biological significance of the interactions between tumour cells and cells of the microenvironment in time and space. Therefore, it is of paramount importance to spatially resolve individual cells types/states in the context of their microenvironment to truly understand the mechanisms that drive tumour evolution or disease progression. Better understanding of the spatial architecture of relevant gene expression will not only aid the development of better, spatially resolved prognostic biomarkers for clinical diagnostics, but also lays the foundation for the discovery of novel therapeutic targets aimed at the disease microenvironment.

In this project, we propose to query “how the spatial organization of damage- associated hepatocytes and their association with the tissue microenvironment is altered during the progression of metabolic-dysfunction associated steatotic/fatty liver disease (MASLD) to HCC”. We will spatial transcriptomics platforms including the Nanostring GeoMX DSP (to explore gene expression signatures in regions of interest or “spatial neighbourhoods” within the fatty liver or the associated tissue/tumour microenvironment), and the Nanostring CosMx, Spatial Molecular Imaging (SMI) platform (to identify unique, single-cell-based gene expression, pairwise cell-interactions that can aid in the discovery of mechanistic hypotheses around how specific interactions between tumour cells and their microenvironment (immune, fibroblast, endothelial cells) determine chronic liver disease progression to HCC development. We will focus on a carefully curated set of cross-sectional patient samples representing early to late stages of fatty liver disease/steato-hepatitis (MASH) as well as HCC that are associated with fatty liver disease (with non-NASH-HCC as control). Additionally, we will be testing our hypothesis in longitudinal samples isolated from preclinical models of mice fed on modified Western diet/high fat diet , that display markedly enhanced tumorigenesis upon induction with chemical carcinogens (such as DEN).

Students are expected to gain significant experience in spatial transcriptomics workflow/platforms, tissue processing, data analysis/bioinformatics, chronic disease modelling in mouse models in vivo, immunohistochemistry and in vivo functional validation studies aimed at testing mechanistic hypotheses derived from the discovery cohort studies.