Metabolic symbiosis between oxygenated and hypoxic tumour cells: An agent-based modelling study.

Deregulated metabolism is one of the hallmarks of cancer. It is well-known that tumour cells tend to metabolize glucose via glycolysis even when oxygen is available and mitochondrial respiration is functional. However, the lower energy efficiency of aerobic glycolysis with respect to mitochondrial respiration makes this behaviour, namely the Warburg effect, counter-intuitive, although it has now been recognized as source of anabolic precursors. On the other hand, there is evidence that oxygenated tumour cells could be fuelled by exogenous lactate produced from glycolysis. We employed a multi-scale approach that integrates multi-agent modelling, diffusion-reaction, stoichiometric equations, and Boolean networks to study metabolic cooperation between hypoxic and oxygenated cells exposed to varying oxygen, nutrient, and inhibitor concentrations. The results show that the cooperation reduces the depletion of environmental glucose, resulting in an overall advantage of using aerobic glycolysis. In addition, the oxygen level was found to be decreased by symbiosis, promoting a further shift towards anaerobic glycolysis. However, the oxygenated and hypoxic populations may gradually reach quasi-equilibrium. A sensitivity analysis using Latin hypercube sampling and partial rank correlation shows that the symbiotic dynamics depends on properties of the specific cell such as the minimum glucose level needed for glycolysis. Our results suggest that strategies that block glucose transporters may be more effective to reduce tumour growth than those blocking lactate intake transporters.

Translation reprogramming is an evolutionarily conserved driver of phenotypic plasticity and therapeutic resistance in melanoma.

The intratumor microenvironment generates phenotypically distinct but interconvertible malignant cell subpopulations that fuel metastatic spread and therapeutic resistance. Whether different microenvironmental cues impose invasive or therapy-resistant phenotypes via a common mechanism is unknown. In melanoma, low expression of the lineage survival oncogene microphthalmia-associated transcription factor (MITF) correlates with invasion, senescence, and drug resistance. However, how MITF is suppressed in vivo and how MITF-low cells in tumors escape senescence are poorly understood. Here we show that microenvironmental cues, including inflammation-mediated resistance to adoptive T-cell immunotherapy, transcriptionally repress MITF via ATF4 in response to inhibition of translation initiation factor eIF2B. ATF4, a key transcription mediator of the integrated stress response, also activates AXL and suppresses senescence to impose the MITF-low/AXL-high drug-resistant phenotype observed in human tumors. However, unexpectedly, without translation reprogramming an ATF4-high/MITF-low state is insufficient to drive invasion. Importantly, translation reprogramming dramatically enhances tumorigenesis and is linked to a previously unexplained gene expression program associated with anti-PD-1 immunotherapy resistance. Since we show that inhibition of eIF2B also drives neural crest migration and yeast invasiveness, our results suggest that translation reprogramming, an evolutionarily conserved starvation response, has been hijacked by microenvironmental stress signals in melanoma to drive phenotypic plasticity and invasion and determine therapeutic outcome.

Single cell RNA-sequencing: A powerful yet still challenging technology to study cellular heterogeneity.

Almost all biomedical research to date has relied upon mean measurements from cell populations, however it is well established that what it is observed at this macroscopic level can be the result of many interactions of several different single cells. Thus, the observable macroscopic 'average' cannot outright be used as representative of the 'average cell'. Rather, it is the resulting emerging behaviour of the actions and interactions of many different cells. Single-cell RNA sequencing (scRNA-Seq) enables the comparison of the transcriptomes of individual cells. This provides high-resolution maps of the dynamic cellular programmes allowing us to answer fundamental biological questions on their function and evolution. It also allows to address medical questions such as the role of rare cell populations contributing to disease progression and therapeutic resistance. Furthermore, it provides an understanding of context-specific dependencies, namely the behaviour and function that a cell has in a specific context, which can be crucial to understand some complex diseases, such as diabetes, cardiovascular disease and cancer. Here, we provide an overview of scRNA-Seq, including a comparative review of emerging technologies and computational pipelines. We discuss the current and emerging applications and focus on tumour heterogeneity a clear example of how scRNA-Seq can provide new understanding of a complex disease. Additionally, we review the limitations and highlight the need of powerful computational pipelines and reproducible protocols for the broader acceptance of this technique in basic and clinical research.

Obesity: a perfect storm for carcinogenesis.

Obesity-related cancers account for 40% of the cancer cases observed in the USA and obesity is overtaking smoking as the most widespread modifiable risk factor for carcinogenesis. Here, we use the hallmarks of cancer framework to delineate how obesity might influence the carcinogenic hallmarks in somatic cells. We discuss the effects of obesity on (a) sustaining proliferative signaling; (b) evading growth suppressors; (c) resisting cell death; (d) enabling replicative immortality; (e) inducing angiogenesis; (f) activating invasion and metastasis; (g) reprogramming energy metabolism; and (h) avoiding immune destruction, together with its effects on genome instability and tumour-promoting inflammation. We present the current understanding and controversies in this evolving field, and highlight some areas in need of further cross-disciplinary focus. For instance, the relative importance of the many potentially causative obesity-related factors is unclear for each type of malignancy. Even within a single tumour type, it is currently unknown whether one obesity-related factor consistently plays a predominant role, or if this varies between patients or, even in a single patient with time. Clarifying how the hallmarks are affected by obesity may lead to novel prevention and treatment strategies for the increasingly obese population.

E2F1 proteolysis via SCF-cyclin F underlies synthetic lethality between cyclin F loss and Chk1 inhibition.

Cyclins are central engines of cell cycle progression in conjunction with cyclin-dependent kinases (CDKs). Among the different cyclins controlling cell cycle progression, cyclin F does not partner with a CDK, but instead forms via its F-box domain an SCF (Skp1-Cul1-F-box)-type E3 ubiquitin ligase module. Although various substrates of cyclin F have been identified, the vulnerabilities of cells lacking cyclin F are not known. Thus, we assessed viability of cells lacking cyclin F upon challenging them with more than 180 different kinase inhibitors. The screen revealed a striking synthetic lethality between Chk1 inhibition and cyclin F loss. Chk1 inhibition in cells lacking cyclin F leads to DNA replication catastrophe. Replication catastrophe depends on accumulation of the transcription factor E2F1 in cyclin F-depleted cells. We find that SCF-cyclin F controls E2F1 ubiquitylation and degradation during the G2/M phase of the cell cycle and upon challenging cells with Chk1 inhibitors. Thus, Cyclin F restricts E2F1 activity during the cell cycle and upon checkpoint inhibition to prevent DNA replication stress. Our findings pave the way for patient selection in the clinical use of checkpoint inhibitors.

MAGNETO: Cell type marker panel generator from single-cell transcriptomic data.

Single-cell RNA sequencing experiments produce data useful to identify different cell types, including uncharacterized and rare ones. This enables us to study the specific functional roles of these cells in different microenvironments and contexts. After identifying a (novel) cell type of interest, it is essential to build succinct marker panels, composed of a few genes referring to cell surface proteins and clusters of differentiation molecules, able to discriminate the desired cells from the other cell populations. In this work, we propose a fully-automatic framework called MAGNETO, which can help construct optimal marker panels starting from a single-cell gene expression matrix and a cell type identity for each cell. MAGNETO builds effective marker panels solving a tailored bi-objective optimization problem, where the first objective regards the identification of the genes able to isolate a specific cell type, while the second conflicting objective concerns the minimization of the total number of genes included in the panel. Our results on three public datasets show that MAGNETO can identify marker panels that identify the cell populations of interest better than state-of-the-art approaches. Finally, by fine-tuning MAGNETO, our results demonstrate that it is possible to obtain marker panels with different specificity levels.

Replication catastrophe induced by cyclic hypoxia leads to increased APOBEC3B activity.

Tumor heterogeneity includes variable and fluctuating oxygen concentrations, which result in the accumulation of hypoxic regions in most solid tumors. Tumor hypoxia leads to increased therapy resistance and has been linked to genomic instability. Here, we tested the hypothesis that exposure to levels of hypoxia that cause replication stress could increase APOBEC activity and the accumulation of APOBEC-mediated mutations. APOBEC-dependent mutational signatures have been well-characterized, although the physiological conditions which underpin them have not been described. We demonstrate that fluctuating/cyclic hypoxic conditions which lead to replication catastrophe induce the expression and activity of APOBEC3B. In contrast, stable/chronic hypoxic conditions which induce replication stress in the absence of DNA damage are not sufficient to induce APOBEC3B. Most importantly, the number of APOBEC-mediated mutations in patient tumors correlated with a hypoxia signature. Together, our data support the conclusion that hypoxia-induced replication catastrophe drives genomic instability in tumors, specifically through increasing the activity of APOBEC3B.

New perspectives in liquid biopsy for glioma patients.

PURPOSE OF REVIEW: Gliomas are the most common primary tumors of the central nervous system. They are characterized by a disappointing prognosis and ineffective therapy that has shown no substantial improvements in the past 20 years. The lack of progress in treating gliomas is linked with the inadequacy of suitable tumor samples to plan translational studies and support laboratory developments. To overcome the use of tumor tissue, this commentary review aims to highlight the potential for the clinical application of liquid biopsy (intended as the study of circulating biomarkers in the blood), focusing on circulating tumor cells, circulating DNA and circulating noncoding RNA. RECENT FINDINGS: Thanks to the increasing sensitivity of sequencing techniques, it is now possible to analyze circulating nucleic acids and tumor cells (liquid biopsy). SUMMARY: Although studies on the use of liquid biopsy are still at an early stage, the potential clinical applications of liquid biopsy in the study of primary brain cancer are many and have the potential to revolutionize the approach to neuro-oncology, and importantly, they offer the possibility of gathering information on the disease at any time during its history.

Heritable genetic variants in key cancer genes link cancer risk with anthropometric traits.

BACKGROUND: Height and other anthropometric measures are consistently found to associate with differential cancer risk. However, both genetic and mechanistic insights into these epidemiological associations are notably lacking. Conversely, inherited genetic variants in tumour suppressors and oncogenes increase cancer risk, but little is known about their influence on anthropometric traits. METHODS: By integrating inherited and somatic cancer genetic data from the Genome-Wide Association Study Catalog, expression Quantitative Trait Loci databases and the Cancer Gene Census, we identify SNPs that associate with different cancer types and differential gene expression in at least one tissue type, and explore the potential pleiotropic associations of these SNPs with anthropometric traits through SNP-wise association in a cohort of 500,000 individuals. RESULTS: We identify three regulatory SNPs for three important cancer genes, FANCA, MAP3K1 and TP53 that associate with both anthropometric traits and cancer risk. Of particular interest, we identify a previously unrecognised strong association between the rs78378222[C] SNP in the 3' untranslated region (3'-UTR) of TP53 and both increased risk for developing non-melanomatous skin cancer (OR=1.36 (95% 1.31 to 1.41), adjusted p=7.62E-63), brain malignancy (OR=3.12 (2.22 to 4.37), adjusted p=1.43E-12) and increased standing height (adjusted p=2.18E-24, beta=0.073±0.007), lean body mass (adjusted p=8.34E-37, beta=0.073±0.005) and basal metabolic rate (adjusted p=1.13E-31, beta=0.076±0.006), thus offering a novel genetic link between these anthropometric traits and cancer risk. CONCLUSION: Our results clearly demonstrate that heritable variants in key cancer genes can associate with both differential cancer risk and anthropometric traits in the general population, thereby lending support for a genetic basis for linking these human phenotypes.

Machine Learning Using Gene-Sets to Infer miRNA Function.

miRNA are regulators of cell phenotype, and there is clear evidence that these small posttranscriptional modifiers of gene expression are involved in defining a cellular response across states of development and disease. Classical methods for elucidating the repressive effect of a miRNA on its targets involve controlling for the many factors influencing miRNA action, and this can be achieved in cell lines, but misses tissue and organism level context which are key to a miRNA function. Also, current technology to carry out this validation is limited in both generalizability and throughput. Methodologies with greater scalability and rapidity are required to better understand the function of these important species of RNA. To this end, there is an increasing store of RNA expression level data incorporating both miRNA and mRNA, and in this chapter, we describe how to use machine learning and gene-sets to translate the knowledge of phenotype defined by mRNA to putative roles for miRNA. We outline our approach to this process and highlight how it was done for our miRNA annotation of the hallmarks of cancer using the Cancer Genome Atlas (TCGA) dataset. The concepts we present are applicable across datasets and phenotypes, and we highlight potential pitfalls and challenges that may be faced as they are used.

Transcriptomic analysis of human primary breast cancer identifies fatty acid oxidation as a target for metformin.

BACKGROUND: Epidemiological studies suggest that metformin may reduce the incidence of cancer in patients with diabetes and multiple late phase clinical trials assessing the potential of repurposing this drug are underway. Transcriptomic profiling of tumour samples is an excellent tool to understand drug bioactivity, identify candidate biomarkers and assess for mechanisms of resistance to therapy. METHODS: Thirty-six patients with untreated primary breast cancer were recruited to a window study and transcriptomic profiling of tumour samples carried out before and after metformin treatment. RESULTS: Multiple genes that regulate fatty acid oxidation were upregulated at the transcriptomic level and there was a differential change in expression between two previously identified cohorts of patients with distinct metabolic responses. Increase in expression of a mitochondrial fatty oxidation gene composite signature correlated with change in a proliferation gene signature. In vitro assays showed that, in contrast to previous studies in models of normal cells, metformin reduces fatty acid oxidation with a subsequent accumulation of intracellular triglyceride, independent of AMPK activation. CONCLUSIONS: We propose that metformin at clinical doses targets fatty acid oxidation in cancer cells with implications for patient selection and drug combinations. CLINICAL TRIAL REGISTRATION: NCT01266486.

SCF (Fbxl17) ubiquitylation of Sufu regulates Hedgehog signaling and medulloblastoma development.

Skp1-Cul1-F-box protein (SCF) ubiquitin ligases direct cell survival decisions by controlling protein ubiquitylation and degradation. Sufu (Suppressor of fused) is a central regulator of Hh (Hedgehog) signaling and acts as a tumor suppressor by maintaining the Gli (Glioma-associated oncogene homolog) transcription factors inactive. Although Sufu has a pivotal role in Hh signaling, the players involved in controlling Sufu levels and their role in tumor growth are unknown. Here, we show that Fbxl17 (F-box and leucine-rich repeat protein 17) targets Sufu for proteolysis in the nucleus. The ubiquitylation of Sufu, mediated by Fbxl17, allows the release of Gli1 from Sufu for proper Hh signal transduction. Depletion of Fbxl17 leads to defective Hh signaling associated with an impaired cancer cell proliferation and medulloblastoma tumor growth. Furthermore, we identify a mutation in Sufu, occurring in medulloblastoma of patients with Gorlin syndrome, which increases Sufu turnover through Fbxl17-mediated polyubiquitylation and leads to a sustained Hh signaling activation. In summary, our findings reveal Fbxl17 as a novel regulator of Hh pathway and highlight the perturbation of the Fbxl17-Sufu axis in the pathogenesis of medulloblastoma.

Endogenous miRNA sponges mediate the generation of oscillatory dynamics for a non-coding RNA network.

Oscillations are crucial to the normal function of living organisms, across a wide variety of biological processes. In eukaryotes, oscillatory dynamics are thought to arise from interactions at the protein and RNA levels; however, the role of non-coding RNA in regulating these dynamics remains understudied. In this work, we show how non-coding RNA acting as microRNA (miRNA) sponges in a conserved miRNA - transcription factor feedback motif, can give rise to oscillatory behaviour, and how to test for this experimentally. Control of these non-coding RNA can dynamically create oscillations or stability, and we show how this behaviour predisposes to oscillations in the stochastic limit. These results, supported by emerging evidence for the role of miRNA sponges in development, point towards key roles of different species of miRNA sponges, such as circular RNA, potentially in the maintenance of yet unexplained oscillatory behaviour. These results help to provide a paradigm for understanding functional differences between the many redundant, but distinct RNA species thought to act as miRNA sponges in nature, such as long non-coding RNA, pseudogenes, competing mRNA, circular RNA, and3' UTRs.

miR-182-mediated downregulation of BRCA1 impacts DNA repair and sensitivity to PARP inhibitors.

Expression of BRCA1 is commonly decreased in sporadic breast tumors, and this correlates with poor prognosis of breast cancer patients. Here we show that BRCA1 transcripts are selectively enriched in the Argonaute/miR-182 complex and miR-182 downregulates BRCA1 expression. Antagonizing miR-182 enhances BRCA1 protein levels and protects them from IR-induced cell death, while overexpressing miR-182 reduces BRCA1 protein, impairs homologous recombination-mediated repair, and render cells hypersensitive to IR. The impaired DNA repair phenotype induced by miR-182 overexpression can be fully rescued by overexpressing miR-182-insensitive BRCA1. Consistent with a BRCA1-deficiency phenotype, miR-182-overexpressing breast tumor cells are hypersensitive to inhibitors of poly (ADP-ribose) polymerase 1 (PARP1). Conversely, antagonizing miR-182 enhances BRCA1 levels and induces resistance to PARP1 inhibitor. Finally, a clinical-grade PARP1 inhibitor impacts outgrowth of miR-182-expressing tumors in animal models. Together these results suggest that miR-182-mediated downregulation of BRCA1 impedes DNA repair and may impact breast cancer therapy.

Functional evolution of IGF2:IGF2R domain 11 binding generates novel structural interactions and a specific IGF2 antagonist.

Among the 15 extracellular domains of the mannose 6-phosphate/insulin-like growth factor-2 receptor (M6P/IGF2R), domain 11 has evolved a binding site for IGF2 to negatively regulate ligand bioavailability and mammalian growth. Despite the highly evolved structural loops of the IGF2:domain 11 binding site, affinity-enhancing AB loop mutations suggest that binding is modifiable. Here we examine the extent to which IGF2:domain 11 affinity, and its specificity over IGF1, can be enhanced, and we examine the structural basis of the mechanistic and functional consequences. Domain 11 binding loop mutants were selected by yeast surface display combined with high-resolution structure-based predictions, and validated by surface plasmon resonance. We discovered previously unidentified mutations in the ligand-interacting surface binding loops (AB, CD, FG, and HI). Five combined mutations increased rigidity of the AB loop, as confirmed by NMR. When added to three independently identified CD and FG loop mutations that reduced the koff value by twofold, these mutations resulted in an overall selective 100-fold improvement in affinity. The structural basis of the evolved affinity was improved shape complementarity established by interloop (AB-CD) and intraloop (FG-FG) side chain interactions. The high affinity of the combinatorial domain 11 Fc fusion proteins functioned as ligand-soluble antagonists or traps that depleted pathological IGF2 isoforms from serum and abrogated IGF2-dependent signaling in vivo. An evolved and reengineered high-specificity M6P/IGF2R domain 11 binding site for IGF2 may improve therapeutic targeting of the frequent IGF2 gain of function observed in human cancer.

Clinical whole-genome sequencing from routine formalin-fixed, paraffin-embedded specimens: pilot study for the 100,000 Genomes Project.

PURPOSE: Fresh-frozen (FF) tissue is the optimal source of DNA for whole-genome sequencing (WGS) of cancer patients. However, it is not always available, limiting the widespread application of WGS in clinical practice. We explored the viability of using formalin-fixed, paraffin-embedded (FFPE) tissues, available routinely for cancer patients, as a source of DNA for clinical WGS. METHODS: We conducted a prospective study using DNAs from matched FF, FFPE, and peripheral blood germ-line specimens collected from 52 cancer patients (156 samples) following routine diagnostic protocols. We compared somatic variants detected in FFPE and matching FF samples. RESULTS: We found the single-nucleotide variant agreement reached 71% across the genome and somatic copy-number alterations (CNAs) detection from FFPE samples was suboptimal (0.44 median correlation with FF) due to nonuniform coverage. CNA detection was improved significantly with lower reverse crosslinking temperature in FFPE DNA extraction (80 °C or 65 °C depending on the methods). Our final data showed somatic variant detection from FFPE for clinical decision making is possible. We detected 98% of clinically actionable variants (including 30/31 CNAs). CONCLUSION: We present the first prospective WGS study of cancer patients using FFPE specimens collected in a routine clinical environment proving WGS can be applied in the clinic.

Estrogen receptor-α directly regulates the hypoxia-inducible factor 1 pathway associated with antiestrogen response in breast cancer.

A majority of breast cancers are driven by estrogen via estrogen receptor-α (ERα). Our previous studies indicate that hypoxia-inducible factor 1α (HIF-1α) cooperates with ERα in breast cancer cells. However, whether ERα is implicated in the direct regulation of HIF-1α and the role of HIF-1α in endocrine therapy response are unknown. In this study we found that a subpopulation of HIF-1α targets, many of them bearing both hypoxia response elements and estrogen response elements, are regulated by ERα in normoxia and hypoxia. Interestingly, the HIF-1α gene itself also bears an estrogen response element, and its expression is directly regulated by ERα. Clinical data revealed that expression of the HIF-1α gene or a hypoxia metagene signature is associated with a poor outcome to endocrine treatment in ERα(+) breast cancer. HIF-1α was able to confer endocrine therapy resistance to ERα(+) breast cancer cells. Our findings define, for the first time to our knowledge, a direct regulatory pathway between ERα and HIF-1α, which might modulate hormone response in treatment.

In vitro downregulated hypoxia transcriptome is associated with poor prognosis in breast cancer.

BACKGROUND: Hypoxia is a characteristic of breast tumours indicating poor prognosis. Based on the assumption that those genes which are up-regulated under hypoxia in cell-lines are expected to be predictors of poor prognosis in clinical data, many signatures of poor prognosis were identified. However, it was observed that cell line data do not always concur with clinical data, and therefore conclusions from cell line analysis should be considered with caution. As many transcriptomic cell-line datasets from hypoxia related contexts are available, integrative approaches which investigate these datasets collectively, while not ignoring clinical data, are required. RESULTS: We analyse sixteen heterogeneous breast cancer cell-line transcriptomic datasets in hypoxia-related conditions collectively by employing the unique capabilities of the method, UNCLES, which integrates clustering results from multiple datasets and can address questions that cannot be answered by existing methods. This has been demonstrated by comparison with the state-of-the-art iCluster method. From this collection of genome-wide datasets include 15,588 genes, UNCLES identified a relatively high number of genes (>1000 overall) which are consistently co-regulated over all of the datasets, and some of which are still poorly understood and represent new potential HIF targets, such as RSBN1 and KIAA0195. Two main, anti-correlated, clusters were identified; the first is enriched with MYC targets participating in growth and proliferation, while the other is enriched with HIF targets directly participating in the hypoxia response. Surprisingly, in six clinical datasets, some sub-clusters of growth genes are found consistently positively correlated with hypoxia response genes, unlike the observation in cell lines. Moreover, the ability to predict bad prognosis by a combined signature of one sub-cluster of growth genes and one sub-cluster of hypoxia-induced genes appears to be comparable and perhaps greater than that of known hypoxia signatures. CONCLUSIONS: We present a clustering approach suitable to integrate data from diverse experimental set-ups. Its application to breast cancer cell line datasets reveals new hypoxia-regulated signatures of genes which behave differently when in vitro (cell-line) data is compared with in vivo (clinical) data, and are of a prognostic value comparable or exceeding the state-of-the-art hypoxia signatures.

TOPK modulates tumour-specific radiosensitivity and correlates with recurrence after prostate radiotherapy.

BACKGROUND: Tumour-specific radiosensitising treatments may enhance the efficacy of radiotherapy without exacerbating side effects. In this study we determined the radiation response following depletion or inhibition of TOPK, a mitogen-activated protein kinase kinase family Ser/Thr protein kinase that is upregulated in many cancers. METHODS: Radiation response was studied in a wide range of cancer cell lines and normal cells using colony formation assays. The effect on cell cycle progression was assessed and the relationship between TOPK expression and therapeutic efficacy was studied in a cohort of 128 prostate cancer patients treated with radical radiotherapy. RESULTS: TOPK knockdown did not alter radiation response in normal tissues, but significantly enhanced radiosensitivity in cancer cells. This result was recapitulated in TOPK knockout cells and with the TOPK inhibitor, OTS964. TOPK depletion altered the G1/S transition and G2/M arrest in response to radiation. Furthermore, TOPK depletion increased chromosomal aberrations, multinucleation and apoptotic cell death after irradiation. These results suggest a possible role for TOPK in the radiation-induced DNA damage checkpoints. These findings have clinical relevance, as elevated TOPK protein expression was associated with poorer clinical outcomes in prostate cancer patients treated with radical radiotherapy. CONCLUSIONS: This study demonstrates that TOPK disruption may cause tumour-specific radiosensitisation in multiple different tumour types.

IGF-1R associates with adverse outcomes after radical radiotherapy for prostate cancer.

BACKGROUND: Activated type 1 insulin-like growth factor receptors (IGF-1Rs) undergo internalisation and nuclear translocation, promoting cell survival. We previously reported that IGF-1R inhibition delays DNA damage repair, sensitising prostate cancer cells to ionising radiation. Here we tested the clinical relevance of these findings. METHODS: We assessed associations between IGF-1R and clinical outcomes by immunohistochemistry in diagnostic biopsies of 136 men treated with 55-70 Gy external beam radiotherapy for prostate cancer, comparing results with publicly available transcriptional data in surgically treated patients. RESULTS: Following radiotherapy, overall recurrence-free survival was shorter in patients whose tumours contained high total, cytoplasmic and internalised (nuclear/cytoplasmic) IGF-1R. High total IGF-1R associated with high primary Gleason grade and risk of metastasis, and cytoplasmic and internalised IGF-1R with biochemical recurrence, which includes patients experiencing local recurrence within the radiation field indicating radioresistance. In multivariate analysis, cytoplasmic, internalised and total IGF-1R were independently associated with risk of overall recurrence, and cytoplasmic IGF-1R was an independent predictor of biochemical recurrence post radiotherapy. Insulin-like growth factor receptors expression did not associate with biochemical recurrence after radical prostatectomy. CONCLUSIONS: These data reveal increased risk of post-radiotherapy recurrence in men whose prostate cancers contain high levels of total or cytoplasmic IGF-1R.