Characterising cancer-associated fibroblast heterogeneity in lung cancer: relating molecular phenotype to function

Lung cancer causes more deaths every year than any other cancer. Although there have recently been developments in the types of treatment available, fewer than 15% of patients with this disease survive longer than five years. In order to develop new treatments, it is critical to have an understanding of how lung tumour cancers develop and spread.

The environment surrounding a developing tumour (known as the tumour microenvironment) is key to its growth and spread (metastasis). One cell type that plays an important role in these processes is the fibroblast. Fibroblasts are found in both normal and cancerous tissues (where they are referred to as cancer-associated fibroblasts, or CAFs). In many cancers, the presence of these cells is related to shorter survival. CAFs have a number of effects, which promote the invasion of tumour cells into surrounding tissues and their subsequent spread. However, there is a large degree of variation within the fibroblast population, and some types of fibroblast are able to impair tumour growth and metastasis. How these different types of fibroblasts arise is currently unknown.

Targeting the fibroblast types that encourage cancer development, in combination with chemotherapy, is a potential future strategy for treating tumours. This project, led by world-renowned researchers and using cutting-edge techniques, aims to identify the different types of fibroblasts present in one of the types of lung cancer; non-small cell lung cancer (NSCLC). We also aim to determine whether the different fibroblast types have different effects on the behaviour of tumour and immune cells.

Our initial goal is to group CAFs according to the genes they express, using non-small cell lung cancer samples from patients. We shall achieve this using a new technique called droplet barcoded sequencing ('Drop-Seq'): the University of Southampton is currently one of the few centres in the world with this technology. Drop-Seq captures individual cells in separate droplets. Each droplet is labelled with its own unique barcode, allowing identification of the genes expressed by each individual cell.

We will then identify specific markers for each CAF subtype, and examine whether these can be used to predict patient survival or guide treatment. I shall carry out experiments examining the effects of different CAF types on both tumour cell invasion and the ability of immune cells to infiltrate tumours. Through our work exploring these subtypes, we hope to to identify new targets for the diagnosis and treatment of non-small cell lung cancer.

This research is being performed at the University of Southampton, a UK centre of academic excellence, involving new laboratory techniques (Drop-Seq) that have been implemented locally. During this project, I shall acquire knowledge of molecular pathology and bioinformatic skills, for the handling and analysis of large amounts of data. These attributes will be invaluable in my future academic career and in my clinical training as a cellular pathologist. In the long term, I hope that this research will identify new targets for the diagnosis and treatment of non-small lung cancer, This would enable the development of new therapies, improving the survival of patients with non-small cell lung cancer, with the potential to apply these findings to other types of cancer in the future.

Lung cancer is the leading cause of cancer-related death worldwide. Non-small cell lung cancer (NSCLC) represents around 80% of cases. Cancer-associated fibroblasts (CAFs) are the principal stromal cell type in many solid tumours, including NSCLC. These cells are known to drive tumour progression and correlate with poor prognosis.

CAFs are conventionally defined by a myofibroblast phenotype; however, the role and impact of CAFs in NSCLC is yet to be adequately characterised. Recent research (including our own preliminary data) has highlighted that CAFs are a heterogeneous population, with functionally distinct subtypes. This project will define the different CAF subtypes found in NSCLC, identify those correlating with poor survival, and investigate their functional role in tumour progression.

This will be achieved by single cell RNA-Sequencing (scRNA-Seq) of patient-matched samples from NSCLC and non-involved lung. Transcriptionally distinct fibroblast clusters will be identified through bioinformatic analysis. These groups will be correlated with clinical parameters (e.g. survival) using the publicly available cancer genome atlas dataset. Significant correlations will be validated using digital pathology analysis of an existing NSCLC patient cohort (n=600). Finally, the function of CAF subtypes correlating with disease progression will be analysed in silico using pathway analysis and in vitro using 3D model systems.

This project will elucidate the basic biological mechanisms underpinning the role of fibroblasts in lung tissue homeostasis, and how these mechanisms become dysregulated during malignant progression. Identifying pro-malignant CAF subtypes may lead to new diagnostic and therapeutic targets. Furthermore, this work will generate single-cell gene expression profiles from multiple cell types within the NSCLC tumour microenvironment, which will be of significant value to the scientific community.

Lung cancer is the leading cause of cancer-related death worldwide, with nearly 50,000 new cases annually in the UK (accounting for 13% of all cancers), and a 5-year survival of less than 10%. It is clear that new therapies are required. In recent years, there has been a paradigm shift in the rationale behind treatment of solid cancers. There has been a move away from targeting specific oncogenic signalling pathways in isolation, towards a combinatorial approach where non-cancerous cells within the multi-cellular tumour microenvironment are also targeted. The recent success of immune-checkpoint inhibitors aptly demonstrates the efficacy of this approach. However, the potential of targeting other cells within the tumour microenvironment is yet to be explored clinically.

The accumulation of cancer-associated fibroblasts (CAF) has been shown to correlate with poor prognosis in multiple solid cancers. Despite their association with poor prognosis, CAF remain a poorly-defined, heterogeneous cell population. This may be reflective of their cell(s) of origin, the tissue in which they develop, and their activation state.

The proposed project will identify specific CAF subgroups within non-small cell lung cancer, establish their tumour-promoting functional effects, and examine the correlation of subgroups with clinical outcome. This will inform our understanding of the tumour microenvironment: in particular, how 'normal' cells within tumours act to promote cancer progression. It is anticipated that CAF-specific biomarkers will have prognostic and predictive utility, thus also representing potential therapeutic targets.

Who will benefit from this research?

1. Patients with lung cancer
2. Basic scientists: tumour microenvironment researchers
3. Clinical academics
4. Health and pharmaceutical industry
5. University of Southampton

How might they benefit from this research?

1. Functional classification of CAFs in NSCLC may facilitate identification of new biomarkers. In the long term, this may to development of new diagnostic and therapeutic targets to inhibit tumour invasion and metastasis. Thus, this project has the potential to improve directly patient care and outcomes.

2. Most of the benefits to the wider academic community have been detailed in the relevant section. However, a few specific aspects are of particular relevance. The last decade has seen a sharp decline in the number of histopathology trainees pursuing a career in academia. I recognise that this project is an opportunity foster interest in basic science research in pathology, and shall capitalise on this by presenting at relevant conferences, including the Pathological Society Ghent 2018 meeting.

3. As stated above, this research has potential, in the long-term, to identify new tools for the diagnosis, stratification and management of NSCLC. With over three hundred lung resections for NSCLC per year, and a large existing cohort of NSCLC tissue microarrays, we are perfectly placed to identify and develop further biomarkers for clinical use.

4. Functional identification of pro-invasive CAF subtypes could generate new candidates for targeted therapies. This would be likely to generate significant interest from the pharmaceutical industry.

5. This project uses a cutting edge droplet barcoding technique to enable single cell transcriptomic analysis. The University of Southampton is one of the few centres worldwide with this technology, and expanding our capabilities in this area would cement the Cancer Sciences Unit's position as a leader in the implementation of this method.