Prof Payam Gammage - Mitochondrial Oncogenetics

Introduction

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Mitochondria are a cellular nexus, performing numerous signalling, biosynthetic and bioenergetic functions. In humans, mitochondria are composed of ~1200 proteins, the vast majority encoded in nuclear DNA, with a minor subset encoded in the spatially and heritably separate mitochondrial DNA (mtDNA).

The human mitochondrial genome is a genetically compact, circular, double-stranded DNA molecule of 16.5 kb, typically present at between 100 and 10,000 copies per cell on a cell type-specific basis. Encoded exclusively in mtDNA are subunits of the mitochondrial respiratory chain and ATP synthase, required for functional oxidative phosphorylation, and all RNA components necessary for their translation by mitochondrial ribosomes.

Mutations, deletions and rearrangements of mtDNA are a known source of hereditary metabolic disease in humans, causing a broad spectrum of pathology underpinned by mitochondrial dysfunction. Mutations of mtDNA are also found in approximately 60% of all solid tumours, often at levels that would result in profound mitochondrial dysfunction.

Mitochondrial dysregulation and dysfunction, particularly a switch from oxidative to glycolytic metabolism, is often observed in cancer. Our research focuses on determining the role of mitochondrial genetics and gene expression in human cancer.

Payam Figure

 Other funding:

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Prof Martin Bushell - RNA and Translational Control in Cancer

Introduction

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The dysregulation of protein synthesis in the tumour clone and the supporting stroma is essential for the delivery of oncogenic gene programmes that allow the establishment of both the intracellular and extracellular environments. This is driven by two fundamental post-transcriptional processes. First, hyperactivation of the eIF4F translation initiation complex results in the specific upregulation of oncogenic mRNAs. Secondly, a fundamental shift within tRNA pools promotes oncogenic gene expression programmes by altering the protein synthesis landscape. Recent data from our group and others show that these two processes are coordinated by a number of distinct regulatory RNA-binding complexes and suggest that there is cross-talk between these key steps of the translation process. Our current hypothesis is that these complexes control and connect all post-transcriptional stages of the mRNA lifecycle, from selection, through decoding, to turnover.

The balance of expressed tRNA and codon usage of oncogenic mRNAs that are sensed by these complexes represent a targetable axis of the malignant phenotype, which could be explored therapeutically if mechanistic understanding was available.

The research in our laboratory focuses on understanding how RNA-binding protein complexes, tRNA abundance and codon optimality dictate oncogenic protein production in a coordinated manner. We employ biochemical, biophysical and computational methods to address these questions. We are interested in how the changing tumour environment results in the redeployment of mRNA-binding complexes that control the balance between upregulation of protein translation and mRNA turnover and translational silencing. These mechanistic insights drive our endeavours in designing assays and drug discovery pipelines to target the heart of tumour cell biology.

Other funding:
 
 
   

 

Prof Imran Ahmad - Models of Advanced Prostate Cancer

Introduction

Prostate cancer is a leading cause of cancer mortality in men in the western world. Identifying and understanding the pathways that drive advanced and treatment-resistant prostate cancer will provide important information that will allow prognostication and individualised patient treatments.

Androgens have been found to be important for prostate cancer progression and androgen deprivation therapy is usually effective at initially controlling the disease. In many cases, however, there is a recurrent castration-resistant phase, for which there is no effective treatment.

Our current research interest is in understanding the mechanisms of treatment-resistance in advanced prostate cancer. Work in my laboratory uses state-of-the-art in vivo models in conjunction with patient samples to interrogate the disease processes in advanced and treatment-resistant prostate cancer. This work will help to provide information on drivers of prostate cancer progression and to identify novel biomarkers of disease and/or drug targets to treat the disease.

Starter Grant for Clinical Lecturers awardee

Prof Imran Ahmad explains how a Starter Grant from the Academy of Medical Sciences allowed him to continue his research following his PhD. Click here to read the interview.

Dr David Lewis - Molecular Imaging

Introduction

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Cancer cells are metabolically reprogrammed to provide the energy and biomass required to proliferate. The resulting metabolic phenotype is driven by genetic mutations and a nutrient-deprived microenvironment. Differing mutations and substrate availability create a dynamic and metabolically heterogeneous tumour. This heterogeneity drives tumour recurrence, metastasis and drug resistance leading to a poor clinical outcome for cancer patients.

Molecular imaging can non-invasively measure the spatial and temporal dynamics of cancer metabolism. Research in our group uses state-of-the art PET/MR imaging, metabolomics and genomics to understand the drivers and consequences of metabolic heterogeneity in living tumours. The goal of this research is to develop methods to non-invasively classify tumours and to direct cancer treatment.

Radionuclide imaging of lung tumour development (place cursor over image to play video):

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Young Investigator of the Year Award Finalist (World Molecular Imaging Congress, New York), 2016

See the following interviews about Dr Lewis' work:

Other funding:

              

       CRUK Glasgow Centre

 

Prof Crispin Miller - Computational Biology

Introduction

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The Computational Biology group is focused on using data-driven approaches from machine learning to develop a better understanding of the processes that underpin tumour growth and development. We are a highly interdisciplinary group that integrates computer science, mathematics, bench- and clinical science.

A major aspect of our work is the use of cancer ‘omics data generated by large-scale tumour sequencing projects. These datasets are large enough to use machine learning algorithms that seek to correlate patterns with phenotype. This is allowing us to explore aspects of tumour evolution, and to ask how the regulatory systems that control gene expression are perturbed in tumour cells.

Our group is particularly interested in the regulatory pathways that act downstream of transcription, including the processes that govern how alternative splicing is coordinated across different pathways. Other projects in the group focus on uncovering novel regulatory sequences within the genome, and in making use of comparative genomics to help interpret the genome rearrangements that occur in tumour cells.

Other funding:

 

  1. Dr Ed Roberts - Immune Priming and the Tumour Microenvironment
  2. Prof Stephen Tait - Mitochondria and Cell Death
  3. Prof Daniel J Murphy - Oncogene-Induced Vulnerabilities
  4. Prof Danny Huang - Ubiquitin Signalling

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