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The role of the microenvironment in driving tumour progression is increasingly recognized. Hypoxia is one of the key microenvironmental changes between tumour and normal tissue, and adaptation of cancer cells to this hostile environment contributes to their malignancy and aggressive phenotype. Such adaptation is governed by many factors, including metabolic reprogramming of tumour cells (1).

We have developed integrated approaches to identify transcriptional programs activated in response to hypoxia (2-4). We will use next generation sequencing (NGS) and CRISPR high-throughput methodologies to produce a comprehensive map of such response. We will interrogate not only protein-coding transcripts and micro-RNAs, which we have previously characterized (3-4), but also uncharacterized non-coding regions of the human genome (see e.g. 5).

This will elucidate for the first time the genome-wide networks underlying transcriptional response to hypoxia in different cancer types. Gene regulatory networks (GRNs) are complex and still uncharacterized sets of regulators and interactions that govern cellular processes. We have used co-expression networks to derive a hypoxia signature (3, 4), which is now being translated to the clinic as biomarker (5). Merging powerful computational techniques and GRNs, we have recently developed a computational framework to predict single- and multi-cellular behaviour in a heterogeneous microenvironment (6). Here we will combine this methodology with RNAseq and CRISPR technology to develop a comprehensive GRN model of HIF1 signaling. This will enable the discovery of new HIF1 targets and generation of testable biological hypotheses on their biology, which we will validate in the lab. It will also highlight candidate therapeutic targets, and inform the design of future biomarker studies.

Importantly, we expect the results produced in this project will have broader methodological impact on the development of integrative genomic approaches.

Training opportunities:

All the techniques mentioned are established in the Buffa and Harris labs. As this project builds on, and extend Prof Buffa research programme, supported by senior scientists Dr Sheldon and O’Reilly, there is some flexibility within the project to suit the candidate background and preferences with respect to the specific objectives and methodologies to be applied and developed. In any case, the candidate will benefit from a highly multidisciplinary environment so their work will benefit from, and be supervised daily by, experienced laboratory and computational scientists. The candidate will work closely with members of Prof Buffa’s CRUK Functional Genomics and ERC Tumour Microenvironment Modelling labs. They will benefit from supervision from Prof Buffa and Prof Harris, on computational biology, bioinformatics, RNAseq, CRISPR and tumour biology; and collaboration with Prof Saez-Rodriguez (EBI) on computational methods to reconstruct gene networks. 


1 Hayder et al (2016) Genome Biology 17:140

2 Masiero et al (2013) Cancer Cell, 24:229-41

3 Buffa et al (2011) Cancer Research, 71:5635-45

4 Korpal et al (2011) Nature Med, 17:1101-8

5 Choudhry et al (2014) EMBO Rep, 15:70-6

6 Voukantsis et al (2019) Gigascience 8(3)