Targeting cancer using stromal and matrix signatures

Please note this PhD is for clinicians only

There is an urgent need for a first line ‘cancer screen test’ that is applicable to many cancer types, accurate, and relatively inexpensive. Currently there is no general cancer diagnostic test. This is partly because most research has concentrated on biomarkers produced by malignant cells, which can vary greatly between different malignancies. We hypothesise that signatures of tumour stroma and matrix, that are conserved features across many malignancies tested, may provide a pan-cancer test for early diagnosis and inform targeting of tumour-promoting stroma.

This project will address the hypothesis across 2 complementary approaches
1) A target specific approach – Investigating Podoplanin (PDPN) signatures in tumours.
2) A global approach – narrowing down the cancer matrix signature, to which components have potential for early diagnostic testing.

PDPN is expressed on cancer-associated fibroblasts in many tumour types, and podoplanin expression have been correlated with poor prognosis. We have shown that PDPN drives actomyosin contractility and may promote a myofibroblastic and matrix remodelling phenotype. We have determined transcriptional PDPN-dependent signatures including signalling downstream of the endogenous binding partner CLEC-2 in RNASeq datasets derived from lymphoid fibroblasts, which we will now apply to solid tumours. In a complementary approach, we deconstructed a tumour microenvironment across multiple levels from gene to biomechanics and identified 22 extracellular matrix (ECM) molecules which either change in expression or are uniquely expressed during disease, and describe a composition of tumour tissue that is prognostic in many cancer types demonstrating for the first time that the host response to cancer is remarkably conserved. Importantly, our ECM signature appears to be detectable at early time points in disease.

To build on these findings the fellow will:

•Determine whether PDPN-dependent transcriptional signatures are consistent between lymphoid fibroblasts and cancer-associated fibroblasts.
•Determine markers for stromal/matrix diagnostic testing. We have identified a panel of blood samples through the BCI Breast Cancer Now tissue bank. These samples are from patients diagnosed with triple negative breast cancer (where our matrix signature is a feature) or patients who have undergone cosmetic or prophylactic procedures (for control samples). The protocols for these samples will allow us to run both transcriptomic and proteomic analysis.
•Investigate a potential link between PDPN+ fibroblast phenotype and our prognostic ECM signature, to determine if and to what degree this CAF marker is responsible to the matrix signature.
•Observations from the analysis will be investigated within an established 3D in vitro tumour model made from primary human tissue.

The ideal candidate will have a background in oncology with a keen interest in learning mass spectrometry analysis and associated informatics for exploring potential biomarkers in the tumour microenvironment.

Potential placement opportunities

1. Pearce lab, Barts Cancer Institute, QMUL. Training will include how we analyse human tumour matrisomes and construction of 3D tumour models.

2. Acton lab, MRC LMCB, UCL. Training in lymphoid tissue fibroblast function and phenotype. Cell culture, histology and microscopy training provided. Production and characterisation cell derived matrices from lymphoid vs cancer fibroblasts.

3. Wang lab, Barts Cancer Institute, QMUL. Training will include informatics analysis of RNAseq and protein datasets from primary and metastatic human cancer tissues (analysis training will be on datasets we have already collected).

4. Mass Spectrometry Core, Barts Cancer Institute. Training will include fundamental principles of mass spectrometry including the chemical basis of detection. Hands on training of sample preparation and analysis.

For further details on how to apply please visit the CRUK CoL Clinical Research Training Fellowship programme web page: https://www.colcc.ac.uk/clinical-research-training-fellowships-crtf/