Adipocytes and breast cancer: a dangerous liaison

Primary supervisor: Katiuscia Bianchi, Queen Mary University of London

Secondary supervisor: Umber Cheema, UCL

Project

The problem: The breast is composed of adipose tissue up to 90%. Considered for many years only as fat deposit, it is now recognized that the adipose tissue is our biggest endocrine organ. However, very little is known about the mechanism by which adipocytes and the adipose tissue promote and support breast cancer development, both in obese and lean patients.

Hypothesis: Our preliminary data indicate that adipocytes alter tumour cell metabolism, promoting key pathways in tumour growth and chemoresistance. Thus, our main hypothesis is that adipocytes are a missing piece of the tumour microenvironment jigsaw puzzle, capable of remodelling breast cancer cell metabolism, supporting tumour growth, progression and therapy resistance.

Approaches and expected outcome: (i) We will characterise the impact of adipocytes on metabolic fluxes of breast cancer cells in a physiologically relevant 3D model using metabolomics and computational approaches. (ii) We expect to restrict breast cancer growth and improve response to therapy by interrupting the communication between adipocytes and breast cancer cells.

Aim1:  Adipocyte characterization

We recently developed two cellular systems utilizing a newly developed medium mimicking the physiological metabolite composition of human plasma (Plasmax^R with dyalised serum) [1] 

(1) adipocytes differentiated from a preadipocyte cell line (SGBS) [2] and (2) primary adipocytes, isolated from patient-derived tissues (in collaboration with Prof Louise Jones and Fran Balkwill, BCI). Moreover, since the adipose tissue is profoundly remodelled during obesity [4], we also expanded the model to study “obese” adipocytes. In this aim, we will characterize the adipocyte secretome, including both adipokines/cytokines and metabolites via a combination of mass spectrometry- and protein array-based approaches. This represents the characterisation of the adipocyte secretome in a medium representing physiological conditions for the first time.

Aim2:  Adipocyte – breast cancer cell crosstalk

We will evaluate how adipocytes affect (i) proliferation, (ii) migratory/invasive potential, (iii) sensitivity to chemotherapy and (iv) metabolism of breast cancer cells, using 3D biomimetic models.

Merging the expertise of four collaborating laboratories, we will tackle the challenge of building a breast cancer tissue model that will include adipocytes. We will engineer 3D biomimetic models to recapitulate breast tissue stiffness and composition that will allow to study the separate compartments as well as their interactions (in collaboration with Umber Cheema and Gyorgy Szabadkai, UCL). Initially, cell lines will be used to limit variability, while in the second step, patient derived material will be utilised in the experimental models. Metabolites will be obtained by perfusion and quantified using MS. Quantified results will be fed into computational modelling. Genome-scale metabolic modelling (GEM) can simulate the fluxes of all intracellular reactions in the metabolic network (13,000 metabolic reactions and >8,000 metabolites) starting from a limited amount of quantitative flux data (i.e. 22 metabolites in the cell medium) (Rosemary Yu, Radboud University, Nijmegen, NL) [5].

Aim3: Stop talking! Interrupt the communication between adipocyte and breast cancer cells.

Based on the adipokine/metabolic signals identified in Aim 2 we will design approaches (i) to inhibit adipocytes to “send” a signal, (ii) to neutralise the secreted signal and (iii) to prevent the recipient of the signal (breast cancer cells) to “respond”. Ultimately we will assess the effect of blocking the crosstalk between adipocytes and breast cancer cells on tumour growth, progression and chemosensitivity.

Candidate background

The ideal candidate has a background in cancer biology and cellular metabolism. Experience with 3d culture will be an advantage.

Potential Research Placements

1. Fran Balkwill, Barts Cancer Institute, Queen Mary University of London
2. Umber Cheema, Surgery and Interventional Sciences, UCL
3. Gyorgy Szabadkai, Cell and Developmental Biology, UCL

References

1. Improving the metabolic fidelity of cancer models with a physiological cell culture medium. Vande Voorde J, Ackermann T, Pfetzer N, Sumpton D, Mackay G, Kalna G, Nixon C, Blyth K, Gottlieb E, Tardito S. Sci Adv. 2019 Jan 2;5(1):eaau7314. PMID: 30613774
2. Human SGBS cells – a unique tool for studies of human fat cell biology. Pamela Fischer-Posovszky, Felicity S Newell, Martin Wabitsch, Hans E Tornqvist Obes Facts 2008;1(4):184-9. PMID: 20054179
3. Building invitro 3D human multicellular models of high-grade serous ovarian cancer. Malacrida B, Pearce OMT, Balkwill FR. STAR Protoc. 2022 Jan 11;3(1):101086. PMID: 35072115
4. Obesity-associated changes in molecular biology of primary breast cancer. Nguyen HL et al. Nat Commun. 2023 Jul 21;14(1):4418. PMID: 37479706
5. Improved flux profiling in genome-scale modeling of human cell metabolism Cyriel Huijer, Xiang Jiao, Yun Chen, Rosemary Yu bioRxiv 2025.05.13.653488; doi: https://doi.org/10.1101/2025.05.13.653488