Radiogenomic analysis of primary breast cancer reveals [18F]-fluorodeoxglucose dynamic flux-constants are positively associated with immune pathways and outperform static uptake measures in associating with glucose metabolism.

BACKGROUND: PET imaging of 18F-fluorodeoxygucose (FDG) is used widely for tumour staging and assessment of treatment response, but the biology associated with FDG uptake is still not fully elucidated. We therefore carried out gene set enrichment analyses (GSEA) of RNA sequencing data to find KEGG pathways associated with FDG uptake in primary breast cancers. METHODS: Pre-treatment data were analysed from a window-of-opportunity study in which 30 patients underwent static and dynamic FDG-PET and tumour biopsy. Kinetic models were fitted to dynamic images, and GSEA was performed for enrichment scores reflecting Pearson and Spearman coefficients of correlations between gene expression and imaging. RESULTS: A total of 38 pathways were associated with kinetic model flux-constants or static measures of FDG uptake, all positively. The associated pathways included glycolysis/gluconeogenesis ('GLYC-GLUC') which mediates FDG uptake and was associated with model flux-constants but not with static uptake measures, and 28 pathways related to immune-response or inflammation. More pathways, 32, were associated with the flux-constant K of the simple Patlak model than with any other imaging index. Numbers of pathways categorised as being associated with individual micro-parameters of the kinetic models were substantially fewer than numbers associated with flux-constants, and lay around levels expected by chance. CONCLUSIONS: In pre-treatment images GLYC-GLUC was associated with FDG kinetic flux-constants including Patlak K, but not with static uptake measures. Immune-related pathways were associated with flux-constants and static uptake. Patlak K was associated with more pathways than were the flux-constants of more complex kinetic models. On the basis of these results Patlak analysis of dynamic FDG-PET scans is advantageous, compared to other kinetic analyses or static imaging, in studies seeking to infer tumour-to-tumour differences in biology from differences in imaging. Trial registration NCT01266486, December 24th 2010.

Role of carbohydrate response element-binding protein (ChREBP) in generating an aerobic metabolic phenotype and in breast cancer progression.

BACKGROUND: The lipogenic transcription factor carbohydrate response element-binding protein (ChREBP) may play a key role in malignant progression of breast cancer by allowing metabolic adaptations to take place in response to changes in oxygenation. METHODS: Immunohistochemical analysis of ChREBP was carried out in human breast tumour tissue microarrays representative of malignant progression from normal breast through to metastatic cancer. The ChREBP protein and mRNA expressions were then analysed in a series of breast cancers for correlative analysis with common and breast-specific hypoxia signatures, and survival. RESULTS: In invasive ductal carcinoma, ChREBP correlated significantly with mean 'downregulated' hypoxia scores (r=0.3, P<0.015, n=67) and in two distinct breast progression arrays, ChREBP protein also increased with malignant progression (P<0.001). However, bioinformatic analysis of a large data set (2136 cases) revealed an apparent reversal in the relationship between ChREBP mRNA level and clinical outcome - not only being significantly correlated with increased survival (log rank P<0.001), but also downregulated in malignant tissue compared with adjacent normal tissue. CONCLUSION: The ChREBP expression may be reflective of an aerobic metabolic phenotype that may conflict with hypoxia-induced signalling but provide a mechanism for growth at the oxygenated edge of the tumours.

COX-2 expression is predictive for early relapse and aromatase inhibitor resistance in patients with ductal carcinoma in situ of the breast, and is a target for treatment.

BACKGROUND: Stratification of patients for treatment of ductal carcinoma in situ (DCIS) is suboptimal, with high systemic overtreatment rates. METHODS: A training set of 95 tumours from women with pure DCIS were immunostained for proteins involved in cell survival, hypoxia, growth factor and hormone signalling. A generalised linear regression with regularisation and variable selection was applied to a multiple covariate Cox survival analysis with recurrence-free survival 10-fold cross-validation and leave-one-out iterative approach were used to build and test the model that was validated using an independent cohort of 58 patients with pure DCIS. The clinical role of a COX-2-targeting agent was then tested in a proof-of-concept neoadjuvant randomised trial in ER-positive DCIS treated with exemestane 25 mg day(-1)± celecoxib 800 mg day(-1). RESULTS: The COX-2 expression was an independent prognostic factor for early relapse in the training (HR 37.47 (95% CI: 5.56-252.74) P=0.0001) and independent validation cohort (HR 3.9 (95% CI: 1.8-8.3) P=0.002). There was no significant interaction with other clinicopathological variables. A statistically significant reduction of Ki-67 expression after treatment with exemestane ± celecoxib was observed (P<0.02) with greater reduction in the combination arm (P<0.004). Concomitant reduction in COX-2 expression was statistically significant in the exemestane and celecoxib arm (P<0.03) only. CONCLUSIONS: In patients with DCIS, COX-2 may predict recurrence, aiding clinical decision making. A combination of an aromatase inhibitor and celecoxib has significant biological effect and may be integrated into treatment of COX2-positive DCIS at high risk of recurrence.

Hypoxia regulates FGFR3 expression via HIF-1α and miR-100 and contributes to cell survival in non-muscle invasive bladder cancer.

BACKGROUND: Non-muscle invasive (NMI) bladder cancer is characterised by increased expression and activating mutations of FGFR3. We have previously investigated the role of microRNAs in bladder cancer and have shown that FGFR3 is a target of miR-100. In this study, we investigated the effects of hypoxia on miR-100 and FGFR3 expression, and the link between miR-100 and FGFR3 in hypoxia. METHODS: Bladder cancer cell lines were exposed to normoxic or hypoxic conditions and examined for the expression of FGFR3 by quantitative PCR (qPCR) and western blotting, and miR-100 by qPCR. The effect of FGFR3 and miR-100 on cell viability in two-dimensional (2-D) and three-dimensional (3-D) was examined by transfecting siRNA or mimic-100, respectively. RESULTS: In NMI bladder cancer cell lines, FGFR3 expression was induced by hypoxia in a transcriptional and HIF-1α-dependent manner. Increased FGFR3 was also in part dependent on miR-100 levels, which decreased in hypoxia. Knockdown of FGFR3 led to a decrease in phosphorylation of the downstream kinases mitogen-activated protein kinase (MAPK) and protein kinase B (PKB), which was more pronounced under hypoxic conditions. Furthermore, transfection of mimic-100 also decreased phosphorylation of MAPK and PKB. Finally, knocking down FGFR3 profoundly decreased 2-D and 3-D cell growth, whereas introduction of mimic-100 decreased 3-D growth of cells. CONCLUSION: Hypoxia, in part via suppression of miR-100, induces FGFR3 expression in bladder cancer, both of which have an important role in maintaining cell viability under conditions of stress.

The small-nucleolar RNAs commonly used for microRNA normalisation correlate with tumour pathology and prognosis.

BACKGROUND: To investigate small-nucleolar RNAs (snoRNAs) as reference genes when measuring miRNA expression in tumour samples, given emerging evidence for their role in cancer. METHODS: Four snoRNAs, commonly used for normalisation, RNU44, RNU48, RNU43 and RNU6B, and miRNA known to be associated with pathological factors, were measured by real-time polymerase chain reaction in two patient series: 219 breast cancer and 46 head and neck squamous cell carcinoma (HNSCC). SnoRNA and miRNA were then correlated with clinicopathological features and prognosis. RESULTS: Small-nucleolar RNA expression was as variable as miRNA expression (miR-21, miR-210, miR-10b). Normalising miRNA PCR expression data to these recommended snoRNAs introduced bias in associations between miRNA and pathology or outcome. Low snoRNA expression correlated with markers of aggressive pathology. Low levels of RNU44 were associated with a poor prognosis. RNU44 is an intronic gene in a cluster of highly conserved snoRNAs in the growth arrest specific 5 (GAS5) transcript, which is normally upregulated to arrest cell growth under stress. Low-tumour GAS5 expression was associated with a poor prognosis. RNU48 and RNU43 were also identified as intronic snoRNAs within genes that are dysregulated in cancer. CONCLUSION: Small-nucleolar RNAs are important in cancer prognosis, and their use as reference genes can introduce bias when determining miRNA expression.

Large meta-analysis of multiple cancers reveals a common, compact and highly prognostic hypoxia metagene.

BACKGROUND: There is a need to develop robust and clinically applicable gene expression signatures. Hypoxia is a key factor promoting solid tumour progression and resistance to therapy; a hypoxia signature has the potential to be not only prognostic but also to predict benefit from particular interventions. METHODS: An approach for deriving signatures that combine knowledge of gene function and analysis of in vivo co-expression patterns was used to define a common hypoxia signature from three head and neck and five breast cancer studies. Previously validated hypoxia-regulated genes (seeds) were used to generate hypoxia co-expression cancer networks. RESULTS: A common hypoxia signature, or metagene, was derived by selecting genes that were consistently co-expressed with the hypoxia seeds in multiple cancers. This was highly enriched for hypoxia-regulated pathways, and prognostic in multivariate analyses. Genes with the highest connectivity were also the most prognostic, and a reduced metagene consisting of a small number of top-ranked genes, including VEGFA, SLC2A1 and PGAM1, outperformed both a larger signature and reported signatures in independent data sets of head and neck, breast and lung cancers. CONCLUSION: Combined knowledge of multiple genes' function from in vitro experiments together with meta-analysis of multiple cancers can deliver compact and robust signatures suitable for clinical application.

Robust prognostic value of a knowledge-based proliferation signature across large patient microarray studies spanning different cancer types.

Tumour proliferation is one of the main biological phenotypes limiting cure in oncology. Extensive research is being performed to unravel the key players in this process. To exploit the potential of published gene expression data, creation of a signature for proliferation can provide valuable information on tumour status, prognosis and prediction. This will help individualizing treatment and should result in better tumour control, and more rapid and cost-effective research and development. From in vitro published microarray studies, two proliferation signatures were compiled. The prognostic value of these signatures was tested in five large clinical microarray data sets. More than 1000 patients with breast, renal or lung cancer were included. One of the signatures (110 genes) had significant prognostic value in all data sets. Stratifying patients in groups resulted in a clear difference in survival (P-values <0.05). Multivariate Cox-regression analyses showed that this signature added substantial value to the clinical factors used for prognosis. Further patient stratification was compared to patient stratification with several well-known published signatures. Contingency tables and Cramer's V statistics indicated that these primarily identify the same patients as the proliferation signature does. The proliferation signature is a strong prognostic factor, with the potential to be converted into a predictive test. Furthermore, evidence is provided that supports the idea that many published signatures track the same biological processes and that proliferation is one of them.

Dose- and time-dependent changes in gene expression in human glioma cells after low radiation doses.

We have used DNA microarrays to identify changes in gene expression in cells of the radioresistant human glioma cell lines T98G and U373 after low radiation doses (0.2-2 Gy). Using Bayesian linear models, we have identified a set of genes that respond to low doses of radiation; furthermore, a hypothesis-driven approach to data analysis has allowed us to identify groups of genes with defined non-linear dose responses. Specifically, one of the cell lines we have examined (T98G) shows increased radiosensitivity at low doses (low-dose hyper-radiosensitivity, HRS); thus we have also assessed sets of genes whose dose response mirrors this survival pattern. We have also investigated a time course for induction of genes over the period when the DNA damage response is expected to occur. We have validated these data using quantitative PCR and also compared genes up-regulated in array data to genes present in the polysomal RNA fraction after irradiation. Several of the radioresponsive genes that we describe code for proteins that may have an impact on the outcome of irradiation in these cells, including RAS homologues and kinases involved in checkpoint signaling, so understanding their differential regulation may suggest new ways of altering radioresistance. From a clinical perspective these data may also suggest novel targets that are specifically up-regulated in gliomas during radiotherapy treatments.

Gene Expression Signatures as Biomarkers of Tumour Hypoxia.

Hypoxia is a feature of most solid tumours and is associated with a poor prognosis. The hypoxic environment can reduce the efficacy of radiotherapy and some chemotherapeutics, and has been investigated extensively as a therapeutic target. The clinical use of hypoxia-targeting treatment will benefit from the development of a biomarker to assess tumour hypoxia. There are several possible techniques that measure either the level of oxygen or the tumour molecular response to hypoxia. The latter includes gene expression profiling, which measures the transcriptional response of a tumour to its hypoxic microenvironment. A systematic review identified 32 published hypoxia gene expression signatures. The methods used for their derivation varied, but are broadly classified as: (i) identifying genes with significantly higher or lower expression in cancer cells cultured under hypoxic versus normoxic conditions; (ii) using either previously characterised hypoxia-regulated genes/biomarkers to define hypoxic tumours and then identifying other genes that are over- or under-expressed in the hypoxic tumours. Both generated gene signatures useful in furthering our understanding of hypoxia biology. However, signatures derived using the second method seem to be superior in terms of providing prognostic information. Here we summarise all 32 published hypoxia signatures, discuss their commonalities and differences, and highlight their strengths and limitations. This review also highlights the importance of reproducibility and gene annotation, which must be accounted for to transfer signatures robustly for clinical application as biomarkers.

Radiation response and cure rate of human colon adenocarcinoma spheroids of different size: the significance of hypoxia on tumor control modelling.

PURPOSE: To evaluate the adequacy of a Poisson tumor control probability (tcp) model and the impact of hypoxia on tumor cure. METHODS AND MATERIALS: A human colon adenocarcinoma cell line, WiDr, was grown as multicellular spheroids of different diameters. Measurements were made of cell survival and spheroid cure following 300-kV X-ray external beam irradiation in air and nitrogen. Cell survival data were fitted using a two-compartment and an oxygen diffusion model. Spheroid cure data were fitted using the tcp model. RESULTS: Hypoxia was seen only for spheroids greater than 500 microm in diameter. For small spheroids tcp estimates of radiosensitivity and clonogenic number showed excellent agreement with experimentally derived values. For large spheroids, although tcp estimates of radiosensitivity were comparable with measurements, estimates of the clonogenic number were considerably lower than the experimental count. Reoxygenation of large spheroids before irradiation resulted in the tcp estimates of the number of clonogenic cells agreeing with measured values. CONCLUSIONS: When hypoxia was absent, the tcp model accurately predicted cure from measured radiosensitivity and clonogen number. When hypoxia was present, the number of cells capable of regrowth in situ was considerably lower than the number of clonogenic cells that initially survived irradiation. As this counteracted the decreased radiosensitivity, hypoxia was less important for cure than predicted from cell survival assays. This finding suggests that chronic hypoxia may not limit directly the success of radiation therapy.

Incorporating biologic measurements (SF(2), CFE) into a tumor control probability model increases their prognostic significance: a study in cervical carcinoma treated with radiation therapy.

PURPOSE: To assess whether incorporation of measurements of surviving fraction at 2 Gy (SF(2)) and colony-forming efficiency (CFE) into a tumor control probability (tcp) model increases their prognostic significance. METHODS AND MATERIALS: Measurements of SF(2) and CFE were available from a study on carcinoma of the cervix treated with radiation alone. These measurements, as well as tumor volume, dose, and treatment time, were incorporated into a Poisson tcp model (tcp(alpha,rho)). Regression analysis was performed to assess the prognostic power of tcp(alpha,rho) vs. the use of either tcp models with biologic parameters fixed to best-fit estimates (but incorporating individual dose, volume, and treatment time) or the use of SF(2) and CFE measurements alone. RESULTS: In a univariate regression analysis of 44 patients, tcp(alpha,rho) was a better prognostic factor for both local control and survival (p < 0.001 and p = 0.049, respectively) than SF(2) alone (p = 0.009 for local control, p = 0.29 for survival) or CFE alone (p = 0.015 for local control, p = 0.38 for survival). In multivariate analysis, tcp(alpha,rho) emerged as the most important prognostic factor for local control (p < 0.001, relative risk of 2.81). After allowing for tcp(alpha,rho), CFE was still a significant independent prognostic factor for local control, whereas SF(2) was not. The sensitivities of tcp(alpha,rho) and SF(2) as predictive tests for local control were 87% and 65%, respectively. Specificities were 70% and 77%, respectively. CONCLUSIONS: A Poisson tcp model incorporating individual SF(2), CFE, dose, tumor volume, and treatment time was found to be the best independent prognostic factor for local control and survival in cervical carcinoma patients.

Dosimetric features of linac head and phantom scattered radiation outside the clinical photon beam: experimental measurements and comparison with treatment planning system calculations.

BACKGROUND AND PURPOSE: Dosimetric measurements and treatment planning system (TPS) calculations in the region outside the clinical photon beams have been investigated. The aim was to estimate the calculation accuracy of a specific TPS in areas that are becoming increasingly relevant with the advent of new technologies, such as, for example, intensity modulation radiation therapy. MATERIALS AND METHODS: Measurements were performed on two different linacs to obtain, separately, the head scatter (electrons and photons), the transmission below the jaws and the phantom scatter outside the primary beam for different photon energies, distances from the field edge and field sizes. Calculations with a commercial TPS (Helax TMS) were then obtained and compared with these measurements. RESULTS: In general, reasonable agreement between calculations and measurements was obtained (1-2%), especially for photon scattering (head and phantom). Nevertheless, some discrepancies were found in the electron contamination computation, due probably to the approximations and assumptions made in the TPS calculation algorithm. CONCLUSIONS: The analyzed TPS presented good results, but for some particular clinical cases and moreover for advanced techniques such as intensity modulated radiation therapy, the calculation behaviour with respect to measurements and patient dose delivery should be carefully evaluated.

An analysis of the relationship between radiosensitivity and volume effects in tumor control probability modeling.

The dependence of local tumor control probability (tcp) on tumor volume is analyzed and discussed with the help of radiobiological modeling; in particular the impact of possible correlations between mean tumor radiosensitivity and tumor dimensions on the tcp volume dependence is explored. The linear-quadratic Poissonian tumor control probability (tcp) model was modified to account for the possible dependence of clonogenic cell density and radiosensitivity parameters on tumor volume; then the original and modified versions of the model were fitted to published clinical and laboratory tumor control data. These different versions of the tcp model often fitted tumor control data equally well, because of the high degree of correlation between the parameters. Nevertheless the results were very different from a physical point of view and we suggest that sometimes it is possible to choose between equally good fits on the basis of physical considerations. Possible links between the volume dependence of the mean radiosensitivity and the degree of tumor hypoxia were also analyzed through a comparison of the results of the tcp fit to published measurements of oxygen tension in tumors.

Monte Carlo dose calculations and radiobiological modelling: analysis of the effect of the statistical noise of the dose distribution on the probability of tumour control.

The aim of this work is to investigate the influence of the statistical fluctuations of Monte Carlo (MC) dose distributions on the dose volume histograms (DVHs) and radiobiological models, in particular the Poisson model for tumour control probability (tcp). The MC matrix is characterized by a mean dose in each scoring voxel, d, and a statistical error on the mean dose, sigma(d); whilst the quantities d and sigma(d) depend on many statistical and physical parameters, here we consider only their dependence on the phantom voxel size and the number of histories from the radiation source. Dose distributions from high-energy photon beams have been analysed. It has been found that the DVH broadens when increasing the statistical noise of the dose distribution, and the tcp calculation systematically underestimates the real tumour control value, defined here as the value of tumour control when the statistical error of the dose distribution tends to zero. When increasing the number of energy deposition events, either by increasing the voxel dimensions or increasing the number of histories from the source, the DVH broadening decreases and tcp converges to the 'correct' value. It is shown that the underestimation of the tcp due to the noise in the dose distribution depends on the degree of heterogeneity of the radiobiological parameters over the population; in particular this error decreases with increasing the biological heterogeneity, whereas it becomes significant in the hypothesis of a radiosensitivity assay for single patients, or for subgroups of patients. It has been found, for example, that when the voxel dimension is changed from a cube with sides of 0.5 cm to a cube with sides of 0.25 cm (with a fixed number of histories of 10(8) from the source), the systematic error in the tcp calculation is about 75% in the homogeneous hypothesis, and it decreases to a minimum value of about 15% in a case of high radiobiological heterogeneity. The possibility of using the error on the tcp to decide how many histories to run for a given voxel size is also discussed.

Quantifying effects of lead shielding in electron beams: a Monte Carlo study.

Lead shielding in contact with the patient's skin is often encountered in radiotherapy with electron beams. The influence of the lead shielding on dose distributions in the patient cannot fully be assessed using modern treatment planning systems. In this work the problem of quantifying the effect of lead shielding on dose distributions is addressed. Monte Carlo dose calculations were performed in a half-blocked water phantom shielded by lead, using a realistic model for the fluence of an electron linear accelerator. Electron beam energies of 6-20 MeV and lead thicknesses of 1-7 mm are used for 10 x 10 cm2 and 5 x 5 cm2 fields. The perturbation of the particle fluence and dose distributions in water introduced by the lead shielding is quantified. The effect of oblique electron beams on the dose perturbation is shown. A fictitious clinical example, the shielding of an eye in electron beam treatment, is used to demonstrate the usefulness of Monte Carlo based treatment planning algorithms that can incorporate the effects of lead shielding.

Multicellular dosimetry in voxel geometry for targeted radionuclide therapy.

A software package to investigate absorbed doses and dose-rates at the cellular and multicellular scale has been developed that considers two- and three-dimensional activity distributions and makes use of analytical representations of the point-dose kernels for (131)I, (32)P, and (90)Y. This software allows cell assemblies to be simulated by definition of the number, size, and geometry of cells and their nuclei, and radionuclide uptake can be specified to occur within the nucleus, the cytoplasm, at the membrane, or within the extracellular space. The software has been validated at a cellular scale by comparison with results obtained using spherical geometry, as found in the literature. At a multicellular scale, comparisons were made with a Monte Carlo simulation in voxel geometry. The software has been designed to work within a user-defined voxel geometry. This geometry is useful not only to simulate complex cell assemblies and realistic heterogeneous radionuclide distributions, but will also allow the use of histological and autoradiographic data. Absorbed dose distributions for a single cell calculated using this code varied significantly with activity localization within the cell, and to a lesser extent, with the cellular geometry. At a multicellular level, a two-dimensional heterogeneous activity distribution inferred from a two-dimensional image of a slice throughout a spheroid was used to calculate a dose-rate distribution. This resulted in a heterogeneous dose-rate delivery even for longer-range radionuclides such as (90)Y and (32)P.

Igf2 ligand dependency of Pten(+/-) developmental and tumour phenotypes in the mouse.

The tumour suppressor PTEN is a key negative regulator of the PI3K-Akt pathway, and is frequently either reduced or lost in human tumours. Murine genetic studies have confirmed that reduction of Pten promotes tumourigenesis in multiple organs, and demonstrated dependency of tumour development on the activation of downstream components such as Akt. Insulin-like growth factors (IGFs) act via IGF1R to activate the PI3K-Akt pathway, and are commonly upregulated in cancer. A context-dependent interplay between IGFs and PTEN exists in normal tissue and tumours; increased IGF2 ligand supply induces Pten expression creating an autoregulatory negative feedback loop, whereas complete loss of PTEN may either cooperate with IGF overexpression in tumour promotion, or result in desensitisation to IGF ligand. However, it remains unknown whether neoplasia associated with Pten loss is dependent on upstream IGF ligand supply in vivo. We evaluated this by generation of Pten(+/-) mice with differing allelic dosage of Igf2, an imprinted gene encoding the potent embryonic and tumour growth factor Igf2. We show that biallelic Igf2 supply potentiates a previously unreported Pten(+/-) placental phenotype and results in strain-dependent cardiac hyperplasia and neonatal lethality. Importantly, we also show that the effects of Pten loss in vivo are modified by Igf2 supply, as lack of Igf2 results in extended survival and delayed tumour development while biallelic supply is associated with reduced lifespan and accelerated neoplasia in females. Furthermore, we demonstrate that reduction of PTEN protein to heterozygote levels in human MCF7 cells is associated with increased proliferation in response to IGF2, and does not result in desensitisation to IGF2 signalling. These data indicate that the effects of Pten loss at heterozygote levels commonly observed in human tumours are modified by Igf2 ligand, and emphasise the importance of the evaluation of upstream pathways in tumours with Pten loss.

Hypoxia-driven cell motility reflects the interplay between JMY and HIF-1α.

Junction-mediating and regulatory protein (JMY) is a novel p53 cofactor that regulates p53 activity during stress. JMY interacts with p300/CBP, which are ubiquitous transcriptional co-activators that interact with a variety of sequence-specific transcription factors, including hypoxia-inducible factor-1α (HIF-1α). In addition, JMY is an actin-nucleating protein, which, through its WH2 domains, stimulates cell motility. In this study, we show that JMY is upregulated during hypoxia in a HIF-1α-dependent manner. The JMY gene contains HIF-responsive elements in its promoter region and HIF-1α is recruited to its promoter during hypoxia. HIF-1α drives transcription of JMY, which accounts for its induction under hypoxia. Moreover, the enhanced cell motility and invasion that occurs during hypoxia requires JMY, as depleting JMY under hypoxic conditions causes decreased cell motility. Our results establish the interplay between JMY and HIF-1α as a new mechanism that controls cell motility under hypoxic stress.