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Centre for Squamous Cancer
  1. Centre for Squamous Cancer
  2. Research themes
  3. Molecular diagnostics and prognostics

Theme 2: Molecular diagnostics and prognostics

Squamous cancer is a heterogeneous disease with unique genomic and phenotypic features that differ markedly between individual patients and result in major differences in disease course and response to treatment. This tumour heterogeneity is one of the biggest challenges for cancer therapy and is one of the main causes of therapeutic failure. For example, around 30% of oral squamous cell carcinomas are metastatic, which is the single most important predictor of outcome and it is an important factor in treatment decisions. However, at presentation it is currently very difficult to predict which tumours are metastatic and this results in sub-optimal tailoring of treatment modalities to the individual patient. A molecular biomarker test that could predict the likelihood of a tumour to metastasise would therefore have a great impact on clinical management of the disease and enable more tailored treatment decisions to reduce both mortality and treatment-related morbidity.

Squamous cell carcinomas are often preceded by a premalignant condition characterised by dysplastic lesions. However, dysplasias are highly heterogeneous and their malignant conversion potential remains elusive; their histopathological phenotypes are often discordant with disease outcome. It is therefore difficult to make clinical decisions on management of premalignant lesions. A molecular biomarker test could have great utility in enabling more accurate identification of those lesions that are at risk of progressing to invasive cancer, and enabling appropriate clinical management.

All cellular processes are tightly regulated by a complex network of interacting biomolecules involving the genome, transcriptome, proteome and secretome, which in turn govern cellular and tissue function. We aim to decipher these biomolecular networks and mechanisms to identify key diagnostic and prognostic biomarkers which will enable clinicians to identify and treat patients with targeted therapeutics tailored to their individual tumour for better patient outcome.

Key research objectives:

  1. Genome mutational profile and tumour heterogeneity (Sequeira)

    Understanding the dynamics of cancer evolution can provide a quantitative measurement of tumour heterogeneity, identifying differences between patients as tumours progress from early stage-lesions to invasive carcinoma. We have recently identified how the genomic landscape of mouse oral squamous cell carcinoma predicts differences in behaviour as dysplasias progress to invasive cancer (Sequeira et al., 2020). We now aim to:

    1. Identify changes in the genomic and transcriptional landscape as dysplasias progress to invasive cancer in human tumour specimens. What molecular factors underlie the difference between those dysplasias that progress and those that do not? Can these form the basis of a more accurate prognostic test?

    2. As the tumour evolves, distinct tumour subpopulations with different sets of mutations evolve, and genetically distinct clonal subpopulations can co-exist within a single tumour for long periods of time. This can have a major effect on clinical outcome, as resistant clonal subpopulations evolve to evade therapeutic interventions. We will identify the role of these distinct subpopulations within a single tumour in driving tumour progression and therapeutic resistance, within the context of differences between tumours in the overall genomic landscape.

  2. Transcriptome pattern recognition using artificial intelligence (Teh, Biddle)

    Transcriptome instability in the form of gene expression alterations serves as a key signal for subsequent disease initiation and manifestation. Changes in gene expression levels often precede visible pathological manifestation of disease and are more predictable and reproducible. They can therefore provide a more sensitive, more specific, and less invasive prognostic indicator than traditional pathological techniques. We have developed techniques that can recognise and measure cancer-associated transcriptome instability, enabling better understanding of cancer initiation and prediction of cancer risk in otherwise asymptomatic patients (Ma et al., 2016, Teh et al., 2013). With the help of Artificial Intelligence (AI), we now aim to translate this study into a clinically useful AI tool for streamlined risk assessment before disease manifestation.

    Transcriptome Pattern Recognition

    Multidrug resistance results in chemotherapeutic treatment failure in a large proportion of squamous cell carcinoma patients, requiring multimodal therapy involving chemotherapy in conjunction with surgery and/or radiotherapy. Molecular events conferring chemoresistance remain unclear. We aim to identify transcriptional patterns associated with therapeutic resistance, and incorporate these into our transcriptome pattern recognition protocol, so that therapeutic resistance can be predicted in advance and treatment tailored accordingly.

  3. The role of the tumour microenvironment (Sequeira, Rognoni, Biddle)

    Tumours are infiltrated by an array of different cell types that interact with the tumour and greatly influence tumour behaviour and disease course. It has become clear that the tumour microenvironment, comprising all non-transformed tissue components associated with a tumour, can have both tumour-promoting and -inhibitory effects. The tumour microenvironment plays a more consistent and predictable role than tumour intrinsic factors in influencing progression, and therefore presents a promising target for diagnostic and prognostic developments, as well as new therapeutics. However, the underlying molecular and cellular mechanisms are still largely unknown.

    In squamous cancers, an important category of tumour infiltrating cells is the immune cell infiltrate, which contains an abundance of macrophages and T-cells that can exhibit either tumour-antagonizing or tumour-promoting functions. The makeup of the immune cell infiltrate has a marked impact on tumour progression, clinical outcome, and the response to immunotherapy techniques that seek to enhance the T-cell response to the tumour. The makeup of the immune cell infiltrate is controlled by factors released by the tumour, and in this way each tumour determines its own immune cell infiltrate. This raises the prospect that genetic profiling of the tumour may enable prediction of the immune cell infiltrate and thus selection of the best immunotherapeutic approach for the patient. One of our main goals is to understand how tumour genetic heterogeneity influences the tumour microenvironment. We use an interdisciplinary approach that combines integrative genome analysis, high-throughput multiplex imaging and digital pathology to identify the tumour mutations, define tumour architecture and microenvironment heterogeneity, and use this to predict the course of the disease.

    Cancer-associated fibroblasts (CAFs) play an important role in the evolution of squamous cancers and, alongside immune cells, are a major component of the tumour microenvironment. CAFs either reside within the tumour margin or infiltrate the tumour mass, and show increased proliferation, migration, connective tissue deposition and secretion of growth factors and other tissue remodelling factors. Recent advances in single cell sequencing technologies have revealed an astonishing functional heterogeneity within this cell population which may be responsible for their opposing effects observed in different tumours (Rognoni and Watt, 2018). We aim to understand the CAF heterogeneity and its organisation within a tumour, dissecting the molecular and cellular cross talk between CAFs and tumour cells at single cell resolution to predict the course of disease and foster the development of CAF targeted therapies in squamous cancers.

  4. Tumour invasion via the nervous system (Caetano)

    The nervous system has been increasingly recognised to regulate the development, plasticity, homeostasis, and regeneration of non-neural tissues. Notably, evidence over recent years has revealed an important role for the nervous system in cancer initiation and progression. Tumours consist of both cancer cells and host cells that regulate the tumour’s microenvironment. Interactions among the different types of cells in the tumour constantly shape cancer cellular behaviour and affect how the tumour progresses. Immune cells and fibroblasts control some of these communications; however, the neuroscience aspect of squamous cancer biology remains largely elusive.

    We aim to understand how the most common cells in the peripheral nervous system, neurons and glial cells, form during oral mucosa development, how they contribute to tissue homeostasis and how they control tumour initiation and progression. In our research we apply highly diverse experimental approaches, including molecular and genetic manipulations, computational biology, high resolution microscopy and in vitro model systems (Caetano et al., 2021). This research will help us to learn more about the relationship between the peripheral nervous system and squamous cancer to develop potential new treatments for oral and other squamous cancers.

 

CAETANO AJ, YIANNI V, VOLPONI A, BOOTH V, D'AGOSTINO EM, SHARPE P. 2021. Defining human mesenchymal and epithelial heterogeneity in response to oral inflammatory disease. Elife. 2021 Jan 4;10:e62810. doi: 10.7554/eLife.62810. 

MA, H., DAI, H., DUAN, X., TANG, Z., LIU, R., SUN, K., ZHOU, K., CHEN, H., XIANG, H., WANG, J., GAO, Q., ZOU, Y., WAN, H. & TEH, M. T. 2016. Independent evaluation of a FOXM1-based quantitative malignancy diagnostic system (qMIDS) on head and neck squamous cell carcinomas. Oncotarget, 7, 54555-54563.

ROGNONI, E. & WATT, F. M. 2018. Skin Cell Heterogeneity in Development, Wound Healing, and Cancer. Trends Cell Biol, 28, 709-722.

SEQUEIRA, I., RASHID, M., TOMÁS, I. M., WILLIAMS, M. J., GRAHAM, T. A., ADAMS, D. J., VIGILANTE, A. & WATT, F. M. 2020. Genomic landscape and clonal architecture of mouse oral squamous cell carcinomas dictate tumour ecology. Nat Commun, 11, 5671.

TEH, M. T., HUTCHISON, I. L., COSTEA, D. E., NEPPELBERG, E., LIAVAAG, P. G., PURDIE, K., HARWOOD, C., WAN, H., ODELL, E. W., HACKSHAW, A. & WASEEM, A. 2013. Exploiting FOXM1-orchestrated molecular network for early squamous cell carcinoma diagnosis and prognosis. Int J Cancer, 132, 2095-106.

 

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