Impact of supervised gene signatures of early hypoxia on patient survival

Defining hypoxia in cancer: A landmark evaluation of hypoxia gene expression signatures

Tumor hypoxia drives metabolic shifts, cancer progression, and therapeutic resistance. Challenges in quantifying hypoxia have hindered the exploitation of this potential "Achilles' heel." While gene expression signatures have shown promise as surrogate measures of hypoxia, signature usage is heterogeneous and debated. Here, we present a systematic pan-cancer evaluation of 70 hypoxia signatures and 14 summary scores in 104 cell lines and 5,407 tumor samples using 472 million length-matched random gene signatures. Signature and score choice strongly influenced the prediction of hypoxia in vitro and in vivo. In cell lines, the Tardon signature was highly accurate in both bulk and single-cell data (94% accuracy, interquartile mean). In tumors, the Buffa and Ragnum signatures demonstrated superior performance, with Buffa/mean and Ragnum/interquartile mean emerging as the most promising for prospective clinical trials. This work delivers recommendations for experimental hypoxia detection and patient stratification for hypoxia-targeting therapies, alongside a generalizable framework for signature evaluation.

Elucidation of Dysregulated Pathways Associated With Hypoxia in Oestrogen Receptor-Negative Breast Cancer

PURPOSE

Carbonic anhydrase IX (CAIX) is a well-established prognostic marker in breast cancer (BC). Nevertheless, this prognostic value is yet to be confirmed in BC subtypes. This study aims to investigate the prognostic effects of CAIX in oestrogen receptor (ER)-negative (ER-) BCs and to establish pathways related to cytoplasmic CAIX expression in ER- and lymph node-negative BCs.

METHODS

Immunohistochemistry was performed to identify the prognostic role of CAIX protein expression in ER- tissue microarrays (TMAs) (n = 191). CAIX-positive samples (n = 37) were transcriptionally profiled by TempO-Seq and analysed by STRING. Real-time quantitative PCR (RT-qPCR) analysis was used to validate differentially expressed genes.

RESULTS

Overexpression of cytoplasmic CAIX was an independent predictor of recurrence free survival, disease-free survival and overall survival in ER- cohort. RNA transcriptomic analysis identified 10 significant genes in ER- cohort and 3 genes in the node-negative group. The STRING database demonstrated a significant interaction between MUCL1 and GALNT6, which were linked with extracellular matrix organisation, degradation of the extracellular matrix and disease of glycosylation pathways. In the node-negative group, SPNS2 is mainly involved in the sphingolipid de novo biosynthesis pathway. A significant correlation between cytoplasmic SphK1 and cytoplasmic hypoxia-inducible factor-1α was observed. Among the 10 genes, 7 genes (SERHL2, GALNT6, MUCL1, MMP7, PITX2, CEACAM6 and SPNS2) were selected, and their expression was quantitatively assessed by RT-qPCR. The PCR data of these genes showed that SERHL2, GALNT6, MUCL1, PITX2, and SPNS2 mRNA levels were expressed in MDA-MB-231 BC cell lines at variable levels of hypoxic exposure.

CONCLUSION

Cytoplasmic CAIX was independently associated with poor prognosis in ER- BC. Gene expression profiles shed light on the pathways and genes associated with hypoxia in ER- BC. In node-negative patients, SPNS2 was of particular interest.

Transcriptomic and epigenetic landscape of nimorazole-enhanced radiochemotherapy in head and neck cancer

BACKGROUND

Hypoxia remains a challenge for the therapeutic management of head and neck squamous cell carcinoma (HNSCC). The combination of radiotherapy with nimorazole has shown treatment benefit in HNSCC, but the precise underlying molecular mechanisms remain unclear.

PURPOSE

To assess and to characterize the transcriptomic/epigenetic landscape of HNSCC tumor models showing differential therapeutic response to fractionated radiochemotherapy (RCTx) combined with nimorazole.

MATERIALS/METHODS

Bulk RNA-sequencing and DNA methylation experiments were conducted using untreated and treated HNSCC xenografts after 10 fractions of RCTx with and without nimorazole. These tumor models (FaDu, SAS, Cal33, SAT and UT-SCC-45) previously showed a heterogeneous response to RCTx with nimorazole. The prognostic impact of candidate genes was assessed using clinical and gene expression data from HNSCC patients treated with primary RCTx within the DKTK-ROG.

RESULTS

Nimorazole responder and non-responder tumor models showed no differences in hypoxia gene signatures However, non-responder models showed upregulation of metabolic pathways. From that, a subset of 15 differentially expressed genes stratified HNSCC patients into low and high-risk groups with distinct outcome.

CONCLUSION

In the present study, we found that nimorazole non-responder models were characterized by upregulation of genes involved in Retinol metabolism and xenobiotic metabolic process pathways, which might contribute to identify mechanisms of resistance to nitroimidazole compounds and potentially expand the repertoire of therapeutic options to treat HNSCC.

Pan-cancer analysis of tissue and single-cell HIF-pathway activation using a conserved gene signature

Activation of cellular hypoxia pathways, orchestrated by HIF (hypoxia-inducible factor) transcription factors, is a common feature of multiple tumor types, resulting from microenvironment factors and oncogenic mutation. Although they help drive many of the "hallmarks" of cancer and are associated with poor outcome and resistance to therapy, the transcriptional targets of HIF vary considerably depending on the cell type. By integrating 72 genome-wide assays of HIF binding and transcriptional regulation from multiple cancer types, we define a consensus set of 48 HIF target genes that is highly conserved across cancer types and cell lineages. These genes provide an effective marker of HIF activation in bulk and single-cell transcriptomic analyses across a wide range of cancer types and in malignant and stromal cell types. This allows the tissue-orchestrated responses to the hypoxic tumor microenvironment and to oncogenic HIF activation to be deconvoluted at the tumor and single-cell level.

Hypoxia-driven immunosuppression by Treg and type-2 conventional dendritic cells in HCC

BACKGROUND AND AIMS

Hypoxia is one of the central players in shaping the immune context of the tumor microenvironment (TME). However, the complex interplay between immune cell infiltrates within the hypoxic TME of HCC remains to be elucidated.

APPROACH AND RESULTS

We analyzed the immune landscapes of hypoxia-low and hypoxia-high tumor regions using cytometry by time of light, immunohistochemistry, and transcriptomic analyses. The mechanisms of immunosuppression in immune subsets of interest were further explored using in vitro hypoxia assays. Regulatory T cells (Tregs) and a number of immunosuppressive myeloid subsets, including M2 macrophages and human leukocyte antigen-DR isotype (HLA-DR^lo ) type 2 conventional dendritic cell (cDC2), were found to be significantly enriched in hypoxia-high tumor regions. On the other hand, the abundance of active granzyme B^hi PD-1^lo CD8⁺ T cells in hypoxia-low tumor regions implied a relatively active immune landscape compared with hypoxia-high regions. The up-regulation of cancer-associated genes in the tumor tissues and immunosuppressive genes in the tumor-infiltrating leukocytes supported a highly pro-tumorigenic network in hypoxic HCC. Chemokine genes such as CCL20 (C-C motif chemokine ligand 20) and CXCL5 (C-X-C motif chemokine ligand 5) were associated with recruitment of both Tregs and HLA-DR^lo cDC2 to hypoxia-high microenvironments. The interaction between Tregs and cDC2 under a hypoxic TME resulted in a loss of antigen-presenting HLA-DR on cDC2.

CONCLUSIONS

We uncovered the unique immunosuppressive landscapes and identified key immune subsets enriched in hypoxic HCC. In particular, we identified a potential Treg-mediated immunosuppression through interaction with a cDC2 subset in HCC that could be exploited for immunotherapies.

SOCS5 knockdown suppresses metastasis of hepatocellular carcinoma by ameliorating HIF-1α-dependent mitochondrial damage

The Pringle maneuver (PM) is widely used during hepatocellular carcinoma (HCC) resection. However, it inevitably leads to ischemia and hypoxia, which promotes tumor metastasis. In this study, immunohistochemical staining of specimens from 130 HCC patients revealed that long-time PM significantly affected the prognosis of patients with high expression of suppressor of cytokine signaling 5 (SOCS5), but did not affect the prognosis of patients with low expression of SOCS5. The TCGA database showed that patients with high expression of SOCS5 had higher hypoxia scores, and it was proved that SOCS5 could promote the expression of hypoxia-inducible factor 1 subunit alpha (HIF-1α) protein by clinical tissue samples, cell experiments, lung metastases, and subcutaneous tumorigenesis experiments. Then, we used CoCl2 to construct a hypoxia model, and confirmed that SOCS5 knockdown resisted hypoxia-induced mitochondrial damage by inhibiting the expression of HIF-1α, thereby inhibiting the invasion and migration of HCC cells by immunofluorescence, electron microscopy, migration, invasion, and other experiments. We performed rescue experiments using LY294002 and rapamycin and confirmed that the knockdown of SOCS5-inhibited HCC cell invasion and migration by inhibiting the PI3K/Akt/mTOR/HIF-1α signaling axis. More importantly, we obtained consistent conclusions from clinical, cellular, and animal studies that the hypoxia-induced invasion and migration ability of SOCS5-inhibited HCC were weaker than that of normal HCC. In conclusion, we identified a novel role for SOCS5 in regulating HIF-1α-dependent mitochondrial damage and metastasis through the PI3K/Akt/mTOR pathway. The development of a SOCS5-specific inhibitor, an indirect inhibitor of HIF-1α, might be effective at controlling PM-induced tumor micrometastases during HCC resection.

Hypoxia classifier for transcriptome datasets

Molecular gene signatures are useful tools to characterize the physiological state of cell populations, but most have developed under a narrow range of conditions and cell types and are often restricted to a set of gene identities. Focusing on the transcriptional response to hypoxia, we aimed to generate widely applicable classifiers sourced from the results of a meta-analysis of 69 differential expression datasets which included 425 individual RNA-seq experiments from 33 different human cell types exposed to different degrees of hypoxia (0.1-5%[Formula: see text]) for 2-48 h. The resulting decision trees include both gene identities and quantitative boundaries, allowing for easy classification of individual samples without control or normoxic reference. Each tree is composed of 3-5 genes mostly drawn from a small set of just 8 genes (EGLN1, MIR210HG, NDRG1, ANKRD37, TCAF2, PFKFB3, BHLHE40, and MAFF). In spite of their simplicity, these classifiers achieve over 95% accuracy in cross validation and over 80% accuracy when applied to additional challenging datasets. Our results indicate that the classifiers are able to identify hypoxic tumor samples from bulk RNAseq and hypoxic regions within tumor from spatially resolved transcriptomics datasets. Moreover, application of the classifiers to histological sections from normal tissues suggest the presence of a hypoxic gene expression pattern in the kidney cortex not observed in other normoxic organs. Finally, tree classifiers described herein outperform traditional hypoxic gene signatures when compared against a wide range of datasets. This work describes a set of hypoxic gene signatures, structured as simple decision tress, that identify hypoxic samples and regions with high accuracy and can be applied to a broad variety of gene expression datasets and formats.

SPINK1 as a plasma marker for tumor hypoxia and a therapeutic target for radiosensitization

Hypoxia is associated with tumor radioresistance; therefore, a predictive marker for tumor hypoxia and a rational target to overcome it have been sought to realize personalized radiotherapy. Here, we show that serine protease inhibitor Kazal type I (SPINK1) meets these 2 criteria. SPINK1 expression was induced upon hypoxia (O2 < 0.1%) at the transcription initiation level in a HIF-dependent manner, causing an increase in secreted SPINK1 levels. SPINK1 proteins were detected both within and around hypoxic regions of xenografted and clinical tumor tissues, and their plasma levels increased in response to decreased oxygen supply to xenografts. Secreted SPINK1 proteins enhanced radioresistance of cancer cells even under normoxic conditions in EGFR-dependent and nuclear factor erythroid 2-related factor 2-dependent (Nrf2-dependent) manners and accelerated tumor growth after radiotherapy. An anti-SPINK1 neutralizing antibody exhibited a radiosensitizing effect. These results suggest that SPINK1 secreted from hypoxic cells protects the surrounding and relatively oxygenated cancer cells from radiation in a paracrine manner, justifying the use of SPINK1 as a target for radiosensitization and a plasma marker for predicting tumor hypoxia.

Nanoprobe-Based Magnetic Resonance Imaging of Hypoxia Predicts Responses to Radiotherapy, Immunotherapy, and Sensitizing Treatments in Pancreatic Tumors

Accurate diagnosis of tumors and predicting the therapeutic responses are highly demanded in the clinic to improve the treatment efficacy and survival rates. Since hypoxia develops in the progression of tumors and inversely correlates with prognosis and promotes resistance to radiotherapies and immunotherapies, it is a potential marker for therapeutic prediction. Therefore, effective discrimination of tumor hypoxia for predicting therapeutic outcomes is critical. Here, a magnetic resonance imaging (MRI)-based diagnosis strategy using contrast-amplifying nanoprobes that sense tumor acidosis and real-time observation of hypoxic conditions in tumors has been developed, aiming at accurate detection of pancreatic tumors and prediction of therapeutic effects. Our approach selectively probed xenograft, allograft, and transgenic spontaneous models of intractable pancreatic cancer, which lacks standardized predictive markers to identify patients who benefit most from treatments, and effectively discriminated the intratumoral hypoxia levels. By stratification of pancreatic tumors based on quantitative MR imaging of hypoxia, it enabled prediction of the responses to radiotherapy and immune checkpoint inhibitors. Moreover, the nanoprobe-based MRI could monitor hypoxia reduction by tumor normalization treatments, which permits visualizing pancreatic tumors that will respond to immune checkpoint blockade therapy, enhancing the response rate. The results demonstrate the potential of our strategy for accurate tumor diagnosis, patient stratification, and effective therapy.

Targeting BRF2 in Cancer Using Repurposed Drugs

Simple Summary

BRF2, a subunit of the RNA polymerase III transcription complex, is upregulated in a wide variety of cancers and is a potential therapeutic target; however, no effective drugs are available to target BRF2. The upregulation of BRF2 in cancer cells confers survival via the prevention of oxidative stress-induced apoptosis. In this manuscript, we report the identification of potential BRF2 inhibitors through in silico drug repurposing screening. We further characterized bexarotene as a hit compound for the development of selective BRF2 inhibitors and provide experimental validation to support the repurposing of this FDA-approved drug as an agent to reduce the cellular levels of ROS and consequent BRF2 expression in cancers with elevated levels of oxidative stress.

Abstract

The overexpression of BRF2, a selective subunit of RNA polymerase III, has been shown to be crucial in the development of several types of cancers, including breast cancer and lung squamous cell carcinoma. Predominantly, BRF2 acts as a central redox-sensing transcription factor (TF) and is involved in rescuing oxidative stress (OS)-induced apoptosis. Here, we showed a novel link between BRF2 and the DNA damage response. Due to the lack of BRF2-specific inhibitors, through virtual screening and molecular dynamics simulation, we identified potential drug candidates that interfere with BRF2-TATA-binding Protein (TBP)-DNA complex interactions based on binding energy, intermolecular, and torsional energy parameters. We experimentally tested bexarotene as a potential BRF2 inhibitor. We found that bexarotene (Bex) treatment resulted in a dramatic decline in oxidative stress and Tert-butylhydroquinone (tBHQ)-induced levels of BRF2 and consequently led to a decrease in the cellular proliferation of cancer cells which may in part be due to the drug pretreatment-induced reduction of ROS generated by the oxidizing agent. Our data thus provide the first experimental evidence that BRF2 is a novel player in the DNA damage response pathway and that bexarotene can be used as a potential inhibitor to treat cancers with the specific elevation of oxidative stress.

Hypoxia in Breast Cancer-Scientific Translation to Therapeutic and Diagnostic Clinical Applications

Breast cancer has been the leading cause of female cancer deaths for decades. Intratumoral hypoxia, mainly caused by structural and functional abnormalities in microvasculature, is often associated with a more aggressive phenotype, increased risk of metastasis and resistance to anti-malignancy treatments. The response of cancer cells to hypoxia is ascribed to hypoxia-inducible factors (HIFs) that activate the transcription of a large battery of genes encoding proteins promoting primary tumor vascularization and growth, stromal cell recruitment, extracellular matrix remodeling, cell motility, local tissue invasion, metastasis, and maintenance of the cancer stem cell properties. In this review, we summarized the role of hypoxia specifically in breast cancer, discuss the prognostic and predictive value of hypoxia factors, potential links of hypoxia and endocrine resistance, cancer hypoxia measurements, further involved mechanisms, clinical application of hypoxia-related treatments and open questions.

Arsenic Dispensing Powder Promotes Erythropoiesis in Myelodysplastic Syndromes via Downregulation of HIF1A and Upregulation of GATA Factors

Traditional Chinese Medicine (TCM) is a practical medicine based on thousands of years of medical practice in China. Arsenic dispensing powder (ADP) has been used as a treatment for MDS patients with a superior efficacy on anemia at Xiyuan Hospital of China Academy of Chinese Medical Sciences. In this study, we retrospectively analyzed MDS patients that received ADP treatment in the past 9 years and confirmed that ADP improves patients' anemia and prolongs overall survival in intermediate-risk MDS patients. Then, we used the MDS transgenic mice model and cell line to explore the drug mechanism. In normal and MDS cells, ADP does not show cellular toxicity but promotes differentiation. In mouse MDS models, we observed that ADP showed significant efficacy on promoting erythropoiesis. In the BFU-E and CFU-E assays, ADP could promote erythropoiesis not only in normal clones but also in MDS clones. Mechanistically, we found that ADP could downregulate HIF1A in MDS clones through upregulation of VHL, P53 and MDM2, which is involved in two parallel pathways to downregulate HIF1A. We also confirmed that ADP upregulates GATA factors in normal clones. Thus, our clinical and experimental studies indicate that ADP is a promising drug to promote erythropoiesis in both MDS and normal clones with a superior outcome than current regular therapies. ADP promotes erythropoiesis in myelodysplastic syndromes via downregulation of HIF1A and upregulation of GATA factors.

The Importance of the Tumor Microenvironment and Hypoxia in Delivering a Precision Medicine Approach to Veterinary Oncology

Treating individual patients on the basis of specific factors, such as biomarkers, molecular signatures, phenotypes, environment, and lifestyle is what differentiates the precision medicine initiative from standard treatment regimens. Although precision medicine can be applied to almost any branch of medicine, it is perhaps most easily applied to the field of oncology. Cancer is a heterogeneous disease, meaning that even though patients may be histologically diagnosed with the same cancer type, their tumors may have different molecular characteristics, genetic mutations or tumor microenvironments that can influence prognosis or treatment response. In this review, we describe what methods are currently available to clinicians that allow them to monitor key tumor microenvironmental parameters in a way that could be used to achieve precision medicine for cancer patients. We further describe exciting novel research involving the use of implantable medical devices for precision medicine, including those developed for mapping tumor microenvironment parameters (e.g., O2, pH, and cancer biomarkers), delivering local drug treatments, assessing treatment responses, and monitoring for recurrence and metastasis. Although these research studies have predominantly focused on and were tailored to humans, the results and concepts are equally applicable to veterinary patients. While veterinary clinical studies that have adopted a precision medicine approach are still in their infancy, there have been some exciting success stories. These have included the development of a receptor tyrosine kinase inhibitor for canine mast cell tumors and the production of a PCR assay to monitor the chemotherapeutic response of canine high-grade B-cell lymphomas. Although precision medicine is an exciting area of research, it currently has failed to gain significant translation into human and veterinary healthcare practices. In order to begin to address this issue, there is increasing awareness that cross-disciplinary approaches involving human and veterinary clinicians, engineers and chemists may be needed to help advance precision medicine toward its full integration into human and veterinary clinical practices.

Tumor Hypoxia: Impact on Radiation Therapy and Molecular Pathways

Tumor hypoxia is a common feature of the microenvironment in solid tumors, primarily due to an inadequate, and heterogeneous vascular network. It is associated with resistance to radiotherapy and results in a poorer clinical outcome. The presence of hypoxia in tumors can be identified by various invasive and non-invasive techniques, and there are a number of approaches by which hypoxia can be modified to improve outcome. However, despite these factors and the ongoing extensive pre-clinical studies, the clinical focus on hypoxia is still to a large extent lacking. Hypoxia is a major cellular stress factor and affects a wide range of molecular pathways, and further understanding of the molecular processes involved may lead to greater clinical applicability of hypoxic modifiers. This review is a discussion of the characteristics of tumor hypoxia, hypoxia-related molecular pathways, and the role of hypoxia in treatment resistance. Understanding the molecular aspects of hypoxia will improve our ability to clinically monitor hypoxia and to predict and modify the therapeutic response.

Modelling of hypoxia gene expression for three different cancer cell lines

Gene dynamic analysis is essential in identifying target genes involved pathogenesis of various diseases, including cancer. Cancer prognosis is often influenced by hypoxia. We apply a multi-step pipeline to study dynamic gene expressions in response to hypoxia in three cancer cell lines: prostate (DU145), colon (HT29), and breast (MCF7) cancers. We identified 26 distinct temporal expression patterns for prostate cell line, and 29 patterns for colon and breast cell lines. The module-based dynamic networks have been developed for all three cell lines. Our analyses improve the existing results in multiple ways. It exploits the time-dependence nature of gene expression values in identifying the dynamically significant genes; hence, more key significant genes and transcription factors have been identified. Our gene network returns significant information regarding biologically important modules of genes. Furthermore, the network has potential in learning the regulatory path between transcription factors and the downstream genes. In addition, our findings suggest that changes in genes BMP6 and ARSJ expression might have a key role in the time-dependent response to hypoxia in breast cancer.

Biological Determinants of Chemo-Radiotherapy Response in HPV-Negative Head and Neck Cancer: A Multicentric External Validation

Purpose: Tumor markers that are related to hypoxia, proliferation, DNA damage repair and stem cell-ness, have a prognostic value in advanced stage HNSCC patients when assessed individually. Here we aimed to evaluate and validate this in a multifactorial context and assess interrelation and the combined role of these biological factors in determining chemo-radiotherapy response in HPV-negative advanced HNSCC. Methods: RNA sequencing data of pre-treatment biopsy material from 197 HPV-negative advanced stage HNSCC patients treated with definitive chemoradiotherapy was analyzed. Biological parameter scores were assigned to patient samples using previously generated and described gene expression signatures. Locoregional control rates were used to assess the role of these biological parameters in radiation response and compared to distant metastasis data. Biological factors were ranked according to their clinical impact using bootstrapping methods and multivariate Cox regression analyses that included clinical variables. Multivariate Cox regression analyses comprising all biological variables were used to define their relative role among all factors when combined. Results: Only few biomarker scores correlate with each other, underscoring their independence. The different biological factors do not correlate or cluster, except for the two stem cell markers CD44 and SLC3A2 (r = 0.4, p < 0.001) and acute hypoxia prediction scores which correlated with T-cell infiltration score, CD8⁺ T cell abundance and proliferation scores (r = 0.52, 0.56, and 0.6, respectively with p < 0.001). Locoregional control association analyses revealed that chronic (Hazard Ratio (HR) = 3.9) and acute hypoxia (HR = 1.9), followed by stem cell-ness (CD44/SLC3A2; HR = 2.2/2.3), were the strongest and most robust determinants of radiation response. Furthermore, multivariable analysis, considering other biological and clinical factors, reveal a significant role for EGFR expression (HR = 2.9, p < 0.05) and T-cell infiltration (CD8⁺T-cells: HR = 2.2, p < 0.05; CD8⁺T-cells/Treg: HR = 2.6, p < 0.01) signatures in locoregional control of chemoradiotherapy-treated HNSCC. Conclusion: Tumor acute and chronic hypoxia, stem cell-ness, and CD8⁺ T-cell parameters are relevant and largely independent biological factors that together contribute to locoregional control. The combined analyses illustrate the additive value of multifactorial analyses and support a role for EGFR expression analysis and immune cell markers in addition to previously validated biomarkers. This external validation underscores the relevance of biological factors in determining chemoradiotherapy outcome in HNSCC.

Integrating tumor hypoxic stress in novel and more adaptable strategies for cancer immunotherapy

Immunotherapy is poised to become an increasingly utilized therapy in the treatment of cancer. However, several abnormalities in the tumor microenvironment (TME) that can thwart the efficacy of immunotherapies have been established. Microenvironmental hypoxia is a determining factor in shaping aggressiveness, metastatic potential and treatment resistance of solid tumors. The characterization of this phenomenon could prove beneficial for determining a patient's treatment path and for the introduction of novel targetable factors that can enhance therapeutic outcome. Indeed, the ablation of hypoxia has the potential to sensitize tumors to immunotherapy by metabolically remodeling their microenvironment. In this review, we discuss the intrinsic contributions of hypoxia to cellular plasticity, heterogeneity, stemness and genetic instability in the context of immune escape. In addition, we will shed light on how managing hypoxia can ameliorate response to immunotherapy and how integrating hypoxia gene signatures could play a role in this pursuit.

A transcriptome-based signature of pathological angiogenesis predicts breast cancer patient survival

The specific genes and molecules that drive physiological angiogenesis differ from those involved in pathological angiogenesis, suggesting distinct mechanisms for these seemingly related processes. Unveiling genes and pathways preferentially associated with pathologic angiogenesis is key to understanding its mechanisms, thereby facilitating development of novel approaches to managing angiogenesis-dependent diseases. To better understand these different processes, we elucidated the transcriptome of the mouse retina in the well-accepted oxygen-induced retinopathy (OIR) model of pathological angiogenesis. We identified 153 genes changed between normal and OIR retinas, which represent a molecular signature relevant to other angiogenesis-dependent processes such as cancer. These genes robustly predict the survival of breast cancer patients, which was validated in an independent 1,000-patient test cohort (40% difference in 15-year survival; p = 2.56 x 10-21). These results suggest that the OIR model reveals key genes involved in pathological angiogenesis, and these may find important applications in stratifying tumors for treatment intensification or for angiogenesis-targeted therapies.

Acute Hypoxia Profile is a Stronger Prognostic Factor than Chronic Hypoxia in Advanced Stage Head and Neck Cancer Patients

Hypoxic head and neck tumors respond poorly to radiotherapy and can be identified using gene expression profiles. However, it is unknown whether treatment outcome is driven by acute or chronic hypoxia. Gene expression data of 398 head and neck cancers was collected. Four clinical hypoxia profiles were compared to in vitro acute and chronic hypoxia profiles. Chronic and acute hypoxia profiles were tested for their association to outcome using Cox proportional hazard analyses. In an initial set of 224 patients, scores of the four clinical hypoxia profiles correlated with each other and with chronic hypoxia. However, the acute hypoxia profile showed a stronger association with local recurrence after chemoradiotherapy (p = 0.02; HR = 3.1) than the four clinical (chronic hypoxia) profiles (p = 0.2; HR = 0.9). An independent set of 174 patients confirmed that acute hypoxia is a stronger prognostic factor than chronic hypoxia for overall survival, progression-free survival, local and locoregional control. Multivariable analyses accounting for known prognostic factors substantiate this finding (p = 0.045; p = 0.042; p = 0.018 and p = 0.003, respectively). In conclusion, the four clinical hypoxia profiles are related to chronic hypoxia and not acute hypoxia. The acute hypoxia profile shows a stronger association with patient outcome and should be incorporated into existing prediction models.

Molecular landmarks of tumor hypoxia across cancer types

Many primary-tumor subregions have low levels of molecular oxygen, termed hypoxia. Hypoxic tumors are at elevated risk for local failure and distant metastasis, but the molecular hallmarks of tumor hypoxia remain poorly defined. To fill this gap, we quantified hypoxia in 8,006 tumors across 19 tumor types. In ten tumor types, hypoxia was associated with elevated genomic instability. In all 19 tumor types, hypoxic tumors exhibited characteristic driver-mutation signatures. We observed widespread hypoxia-associated dysregulation of microRNAs (miRNAs) across cancers and functionally validated miR-133a-3p as a hypoxia-modulated miRNA. In localized prostate cancer, hypoxia was associated with elevated rates of chromothripsis, allelic loss of PTEN and shorter telomeres. These associations are particularly enriched in polyclonal tumors, representing a constellation of features resembling tumor nimbosus, an aggressive cellular phenotype. Overall, this work establishes that tumor hypoxia may drive aggressive molecular features across cancers and shape the clinical trajectory of individual tumors.

Quantification of hypoxia-related gene expression as a potential approach for clinical outcome prediction in breast cancer

Breast cancers are solid tumors frequently characterized by regions with low oxygen concentrations. Cellular adaptations to hypoxia are mainly determined by “hypoxia inducible factors” that mediate transcriptional modifications involved in drug resistance and tumor progression leading to metastasis and relapse occurrence. In this study, we investigated the prognostic value of hypoxia-related gene expression in breast cancer. A systematic review was conducted to select a set of 45 genes involved in hypoxia signaling pathways and breast tumor progression. Gene expression was quantified by RT-qPCR in a retrospective series of 32 patients with invasive ductal carcinoma. Data were analyzed in relation to classical clinicopathological criteria and relapse occurrence. Coordinated overexpression of selected genes was observed in high-grade and HER2+ tumors. Hierarchical cluster analysis of gene expression significantly segregated relapsed patients (p = 0.008, Chi² test). All genes (except one) were up-regulated and six markers were significantly expressed in tumors from recurrent patients. The expression of this 6-gene set was used to develop a basic algorithm for identifying recurrent patients according to a risk score of relapse. Analysis of Kaplan-Meier relapse-free survival curves allowed the definition of a threshold score of 2 (p = 0.021, Mantel-Haenszel test). The risk of recurrence was increased by 40% in patients with a high score. In addition to classical prognostic factors, we showed that hypoxic markers have potential prognostic value for outcome and late recurrence prediction, leading to improved treatment decision-making for patients with early-stage invasive breast cancer. It will be necessary to validate the clinical relevance of this prognostic approach through independent studies including larger prospective patient cohorts.

Modern clinical research: How rapid learning health care and cohort multiple randomised clinical trials complement traditional evidence based medicine

BACKGROUND

Trials are vital in informing routine clinical care; however, current designs have major deficiencies. An overview of the various challenges that face modern clinical research and the methods that can be exploited to solve these challenges, in the context of personalised cancer treatment in the 21st century is provided.

AIM

The purpose of this manuscript, without intending to be comprehensive, is to spark thought whilst presenting and discussing two important and complementary alternatives to traditional evidence-based medicine, specifically rapid learning health care and cohort multiple randomised controlled trial design. Rapid learning health care is an approach that proposes to extract and apply knowledge from routine clinical care data rather than exclusively depending on clinical trial evidence, (please watch the animation: http://youtu.be/ZDJFOxpwqEA). The cohort multiple randomised controlled trial design is a pragmatic method which has been proposed to help overcome the weaknesses of conventional randomised trials, taking advantage of the standardised follow-up approaches more and more used in routine patient care. This approach is particularly useful when the new intervention is a priori attractive for the patient (i.e. proton therapy, patient decision aids or expensive medications), when the outcomes are easily collected, and when there is no need of a placebo arm.

DISCUSSION

Truly personalised cancer treatment is the goal in modern radiotherapy. However, personalised cancer treatment is also an immense challenge. The vast variety of both cancer patients and treatment options makes it extremely difficult to determine which decisions are optimal for the individual patient. Nevertheless, rapid learning health care and cohort multiple randomised controlled trial design are two approaches (among others) that can help meet this challenge.

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.

A generic cycling hypoxia-derived prognostic gene signature: application to breast cancer profiling

Background

Temporal and local fluctuations in O₂ in tumors require adaptive mechanisms to support cancer cell survival and proliferation. The transcriptome associated with cycling hypoxia (CycHyp) could thus represent a prognostic biomarker of cancer progression.

Methods

We exposed 20 tumor cell lines to repeated periods of hypoxia/reoxygenation to determine a transcriptomic CycHyp signature and used clinical data sets from 2,150 breast cancer patients to estimate a prognostic Cox proportional hazard model to assess its prognostic performance.

Results

The CycHyp prognostic potential was validated in patients independently of the receptor status of the tumors. The discriminating capacity of the CycHyp signature was further increased in the ER+ HER2- patient populations including those with a node negative status under treatment (HR=3.16) or not (HR=5.54). The CycHyp prognostic signature outperformed a signature derived from continuous hypoxia and major prognostic metagenes (P<0.001). The CycHyp signature could also identify ER+HER2 node-negative breast cancer patients at high risk based on clinicopathologic criteria but who could have been spared from chemotherapy and inversely those patients classified at low risk based but who presented a negative outcome.

Conclusions

The CycHyp signature is prognostic of breast cancer and offers a unique decision making tool to complement anatomopathologic evaluation.

Dual-action combination therapy enhances angiogenesis while reducing tumor growth and spread

Increasing chemotherapy delivery to tumors, while enhancing drug uptake and reducing side effects, is a primary goal of cancer research. In mouse and human cancer models in vivo, we show that coadministration of low-dose Cilengitide and Verapamil increases tumor angiogenesis, leakiness, blood flow, and Gemcitabine delivery. This approach reduces tumor growth, metastasis, and minimizes side effects while extending survival. At a molecular level, this strategy alters Gemcitabine transporter and metabolizing enzyme expression levels, enhancing the potency of Gemcitabine within tumor cells in vivo and in vitro. Thus, the dual action of low-dose Cilengitide, in vessels and tumor cells, improves chemotherapy efficacy. Overall, our data demonstrate that vascular promotion therapy is a means to improve cancer treatment.

Ensemble analyses improve signatures of tumour hypoxia and reveal inter-platform differences

Background

The reproducibility of transcriptomic biomarkers across datasets remains poor, limiting clinical application. We and others have suggested that this is in-part caused by differential error-structure between datasets, and their incomplete removal by pre-processing algorithms.

Methods

To test this hypothesis, we systematically assessed the effects of pre-processing on biomarker classification using 24 different pre-processing methods and 15 distinct signatures of tumour hypoxia in 10 datasets (2,143 patients).

Results

We confirm strong pre-processing effects for all datasets and signatures, and find that these differ between microarray versions. Importantly, exploiting different pre-processing techniques in an ensemble technique improved classification for a majority of signatures.

Conclusions

Assessing biomarkers using an ensemble of pre-processing techniques shows clear value across multiple diseases, datasets and biomarkers. Importantly, ensemble classification improves biomarkers with initially good results but does not result in spuriously improved performance for poor biomarkers. While further research is required, this approach has the potential to become a standard for transcriptomic biomarkers.

'Rapid Learning health care in oncology' - an approach towards decision support systems enabling customised radiotherapy'

PURPOSE

An overview of the Rapid Learning methodology, its results, and the potential impact on radiotherapy.

MATERIAL AND RESULTS

Rapid Learning methodology is divided into four phases. In the data phase, diverse data are collected about past patients, treatments used, and outcomes. Innovative information technologies that support semantic interoperability enable distributed learning and data sharing without additional burden on health care professionals and without the need for data to leave the hospital. In the knowledge phase, prediction models are developed for new data and treatment outcomes by applying machine learning methods to data. In the application phase, this knowledge is applied in clinical practice via novel decision support systems or via extensions of existing models such as Tumour Control Probability models. In the evaluation phase, the predictability of treatment outcomes allows the new knowledge to be evaluated by comparing predicted and actual outcomes.

CONCLUSION

Personalised or tailored cancer therapy ensures not only that patients receive an optimal treatment, but also that the right resources are being used for the right patients. Rapid Learning approaches combined with evidence based medicine are expected to improve the predictability of outcome and radiotherapy is the ideal field to study the value of Rapid Learning. The next step will be to include patient preferences in the decision making.

Differentially regulated functional gene clusters identified in early hypoxic cardiomyocytes

Pathological stress including myocardial infarction and hypertension causes a negative effect on calcium regulation and homeostasis. Nevertheless, few studies reveal that Ca(2+) regulatory genes are related to pathological status in cardiomyocytes under early hypoxia. To determine the alteration of Ca(2+)-related gene in hypoxic myocytes, primary neonatal rat ventricular cardiomyocytes (NRVCMs) was isolated. Survival of hypoxic NRVCMs was significantly decreased in 6 h. We confirmed an increase of reactive oxygen species (ROS) generation and Ca(2+) overload in hypoxic NRVCMs by using 2',7'-dichlorodihydro-fluorescein diacetate (H2DCFDA) and FACS analysis. Furthermore, survival/apoptotic signals were also regulated in same condition. The expression profiles of more than 30,000 genes from NRVCMs that were subjected to early hypoxia revealed 630 genes that were differentially regulated. The intracellular Na(+) overload and Ca(2+) handling genes with at least two-fold changes were confirmed. The levels of Ca(2+)-handling proteins (calsequestrin, calmodulin, and calreticulin), ion channels (NCX, Na(+)-K(+)-ATPase, SERCA2a, and PLB), and stress markers (RyR2, ANP, and BNP) were significantly altered in early hypoxia. These results demonstrate that early hypoxia alters Ca(2+)-related gene expression in NRVCMs, leading to pathological status.

Clinically relevant biomarkers in targeted radiotherapy

Three classic parameters have been recognized as predictors or biomarkers of radiation response: intrinsic radiosensitivity, degree of hypoxia and repopulation capacity of clonogenic cells during a course of fractionated radiation therapy. Although good functional assays exist to measure these tumor parameters, and their use has led to the understanding of factors affecting outcome after radiotherapy, their application in clinical practice is hampered by technical difficulties, the length of time needed to obtain results and the lack of prospective randomized clinical trials. Recently, with the progress in molecular biology, genome-wide screening methods have been used to look for genetic signatures that can distinguish between good and bad outcome after radiotherapy. One of the most promising candidates is the epidermal growth factor receptor which is overexpressed or mutated in a variety of malignancies, such lung and head and neck cancer. Inhibition of this receptor has led to radio-sensitization with the prolongation of median survival in several cancers. Since there is significant variability in the response of patients with the same disease to radiotherapy, it would be very valuable to be able to predict which patients would benefit from a molecularly targeted therapy administered with concomitant radiation in order to increase the response rate (and cure rate) of those patients with radioresistant tumors. Optimally, this assay should be able to provide results in an efficient and reproducible manner and detect tumor genetic mutations that would provide specificity to the intervention. One approach currently in clinical practice to overcome intrinsic radioresistance and repopulation is stereotactic body radiotherapy coupled with image-guided radiation, a highly precise and powerful form of radiation, allowing radiation oncologist to treat tumors with more aggressive biological doses of radiation without causing serious normal tissues injury.

A simple but highly effective approach to evaluate the prognostic performance of gene expression signatures

BACKGROUND

Highly parallel analysis of gene expression has recently been used to identify gene sets or 'signatures' to improve patient diagnosis and risk stratification. Once a signature is generated, traditional statistical testing is used to evaluate its prognostic performance. However, due to the dimensionality of microarrays, this can lead to false interpretation of these signatures.

PRINCIPAL FINDINGS

A method was developed to test batches of a user-specified number of randomly chosen signatures in patient microarray datasets. The percentage of random generated signatures yielding prognostic value was assessed using ROC analysis by calculating the area under the curve (AUC) in six public available cancer patient microarray datasets. We found that a signature consisting of randomly selected genes has an average 10% chance of reaching significance when assessed in a single dataset, but can range from 1% to ∼40% depending on the dataset in question. Increasing the number of validation datasets markedly reduces this number.

CONCLUSIONS

We have shown that the use of an arbitrary cut-off value for evaluation of signature significance is not suitable for this type of research, but should be defined for each dataset separately. Our method can be used to establish and evaluate signature performance of any derived gene signature in a dataset by comparing its performance to thousands of randomly generated signatures. It will be of most interest for cases where few data are available and testing in multiple datasets is limited.

Gene expression and hypoxia in breast cancer

Hypoxia is a feature of most solid tumors and is associated with poor prognosis in several cancer types, including breast cancer. The master regulator of the hypoxic response is the Hypoxia-inducible factor 1α (HIF-1α). It is becoming clear that HIF-1α expression alone is not a reliable marker of tumor response to hypoxia, and recent studies have focused on determining gene and microRNA (miRNA) signatures for this complex process. The results of these studies are likely to pave the way towards the development of a robust hypoxia signature for breast and other cancers that will be useful for diagnosis and therapy. In this review, we outline the existing markers of hypoxia and recently identified gene and miRNA expression signatures, and discuss their potential as prognostic and predictive biomarkers. We also highlight how the hypoxia response is being targeted in the development of cancer therapies.

Strategies to improve radiotherapy with targeted drugs

Radiotherapy is used to treat approximately 50% of all cancer patients, with varying success. The dose of ionizing radiation that can be given to the tumour is determined by the sensitivity of the surrounding normal tissues. Strategies to improve radiotherapy therefore aim to increase the effect on the tumour or to decrease the effects on normal tissues. These aims must be achieved without sensitizing the normal tissues in the first approach and without protecting the tumour in the second approach. Two factors have made such approaches feasible: namely, an improved understanding of the molecular response of cells and tissues to ionizing radiation and a new appreciation of the exploitable genetic alterations in tumours. These have led to the development of treatments combining pharmacological interventions with ionizing radiation that more specifically target either tumour or normal tissue, leading to improvements in efficacy.

Study on differences in the pathology, T cell subsets and gene expression in susceptible and non-susceptible hosts infected with Schistosoma japonicum

More than 40 kinds of mammals in China are known to be naturally infected with Schistosoma japonicum (S. japonicum); Microtus fortis (M. fortis), a species of vole, is the only mammal in which the schistosomes cannot mature or cause significant pathogenic changes. In the current study, we compared the differences in pathology by Hematoxylin-eosin staining and in changes in the T cell subsets with flow cytometry as well as gene expression using genome oligonucleotide microarrays in the lung and liver, before challenge and 10 days post-infection with schistosomes in a S. japonicum-susceptible mouse model of infection, a non-susceptible rat model and the non-permissive host, M. fortis. The results demonstrated that S. japonicum promoted a more intensive immune response and more pathological lesions in M. fortis and rats than in mice. Hematoxylin-eosin staining revealed that the immune effector cells involved were mainly eosinophilic granulocytes supplemented with heterophilic granulocytes and macrophages. The analysis of splenic T cell subsets showed that CD4(+) T cell subsets and the CD4(+)/CD8(+) ratio were increased, while the CD8(+) T cell subsets decreased remarkably in rats; whereas the CD8(+) T cell subsets were increased, but the CD4(+)/CD8(+) ratio was decreased significantly in mice. The analysis of the pattern of gene expression suggested that some immune-associated genes and apoptosis-inducing genes up-regulated, while some development-associated genes were down-regulated in the infected M. fortis compared to the uninfected controls; the three different hosts have different response mechanisms to schistosome infection. The results of this study will be helpful for identifying the key molecules in the immune response to S. japonicum in M. fortis and for understanding more about the underlying mechanism of the response, as well as for elucidating the interaction between S. japonicum and its hosts.

Identifying pH independent hypoxia induced genes in human squamous cell carcinomas in vitro

BACKGROUND

Genes upregulated by low oxygen have been suggested as endogenous markers for tumor hypoxia. Yet, most of the genes investigated have shown inconsistent results, which have led to concerns about their ability to be true hypoxia makers. Previous studies have demonstrated that expression of hypoxia induced genes can be affected by extracellular pH (pH(e)).

METHODS

Five different human cell lines (SiHa, FaDu(DD), UTSCC5, UTSCC14 and UTSCC15) were exposed to different oxygen concentrations and pH (7.5 or 6.3), and gene expression analyzed with microarray (Affymetrix - Human Genome U133 Plus 2.0 Array).

RESULTS

An analysis of two of the cell lines using SAM identified 461 probesets that were able to separate the four groups "Normal oxygen, normal pH", "Low oxygen, normal pH", "Normal oxygen, low pH" and "Low oxygen, low pH". From here it was possible to identify a fraction of probesets induced at low oxygen independent of pH in these two cell lines, this fraction included HIG2, NDRG1, PAI1 and RORA. Further verification by qPCR highlighted the necessity of using more cell lines to obtain a robust gene expression profiles. To specifically select pH independent hypoxia regulated genes across more cell lines, data for FaDu(DD), UTSCC5, UTSCC14 and UTSCC15 were analyzed to identify genes that were induced by hypoxia in each cell line, where the induction was not affected by low pH, and where the gene was not significantly induced by low pH alone. Each cell line had 65-122 probesets meeting these criteria. For genes to be considered as target genes (hypoxia inducible pH independent), genes had to be present in three of four cell lines.

CONCLUSION

The result is a robust hypoxia profile unaffected by pH across cell lines consisting of 27 genes. This study demonstrates a way to identify hypoxia markers by microarray, where other factors in the tumor microenvironment are taken into account.

A biology-driven approach identifies the hypoxia gene signature as a predictor of the outcome of neuroblastoma patients

BACKGROUND

Hypoxia is a condition of low oxygen tension occurring in the tumor microenvironment and it is related to poor prognosis in human cancer. To examine the relationship between hypoxia and neuroblastoma, we generated and tested an in vitro derived hypoxia gene signature for its ability to predict patients' outcome.

RESULTS

We obtained the gene expression profile of 11 hypoxic neuroblastoma cell lines and we derived a robust 62 probesets signature (NB-hypo) taking advantage of the strong discriminating power of the l1-l2 feature selection technique combined with the analysis of differential gene expression. We profiled gene expression of the tumors of 88 neuroblastoma patients and divided them according to the NB-hypo expression values by K-means clustering. The NB-hypo successfully stratifies the neuroblastoma patients into good and poor prognosis groups. Multivariate Cox analysis revealed that the NB-hypo is a significant independent predictor after controlling for commonly used risk factors including the amplification of MYCN oncogene. NB-hypo increases the resolution of the MYCN stratification by dividing patients with MYCN not amplified tumors in good and poor outcome suggesting that hypoxia is associated with the aggressiveness of neuroblastoma tumor independently from MYCN amplification.

CONCLUSIONS

Our results demonstrate that the NB-hypo is a novel and independent prognostic factor for neuroblastoma and support the view that hypoxia is negatively correlated with tumors' outcome. We show the power of the biology-driven approach in defining hypoxia as a critical molecular program in neuroblastoma and the potential for improvement in the current criteria for risk stratification.

Assessment of tumour hypoxia for prediction of response to therapy and cancer prognosis

Tumour cells exploit both genetic and adaptive means to survive and proliferate in hypoxic microenvironments, resulting in the outgrowth of more aggressive tumour cell clones. Direct measurements of tumour oxygenation, and surrogate markers of the hypoxic response in tumours (for instance, hypoxia inducible factor-1α, carbonic anhydrase 9 and glucose transporter-1) are well-established prognostic markers in solid cancers. However, individual markers do not fully capture the complex, dynamic and heterogeneous hypoxic response in cancer. To overcome this, expression profiling has been employed to identify hypoxia signatures in cohorts or models of human cancer. Several of these hypoxia signatures have demonstrated prognostic significance in independent cancer datasets. Nevertheless, individual hypoxia markers have been shown to predict the benefit from hypoxia-modifying or anti-angiogenic therapies. This review aims to discuss the clinical impact of translational work on hypoxia markers and to explore future directions for research in this area.

The use of a comprehensive tumour xenograft dataset to validate gene signatures relevant for radiation response

PURPOSE

To investigate the use of xenograft models in a novel gene signature validation method using gene expression microarrays.

MATERIALS AND METHODS

Gene expression profiles of ten human Head and Neck squamous cell carcinomas (HNSCCs) were obtained. Several published prognostic gene expression signatures were evaluated within this set. These consisted of different radiotherapy relevant signatures (i.e. for hypoxia, proliferation and 'stemness'). Signatures were correlated with various endpoints that have been determined in the ten different xenograft models. These include immunohistochemical measures for hypoxia and proliferation, volume doubling time (VDT) and local tumour control after fractionated irradiation or after single dose irradiation under clamp hypoxia.

RESULTS

We found several significant correlations between the published gene expression signatures and tumour parameters. Several signatures, like the proliferation and wound signature correlated with BrdU labelling index. Further a 'stemness'-related gene signature showed a strong negative correlation with hypoxic fraction.

CONCLUSIONS

Simultaneous assessment of immunohistochemistry, in vivo tumour properties and gene expression profiling in a comprehensive set of xenograft models can be used to validate and potentially infer biological information about prognostic gene signatures.

Taking advantage of tumor cell adaptations to hypoxia for developing new tumor markers and treatment strategies

Cancer cells in hypoxic areas of solid tumors are to a large extent protected against the action of radiation as well as many chemotherapeutic drugs. There are, however, two different aspects of the problem caused by tumor hypoxia when cancer therapy is concerned: One is due to the chemical reactions that molecular oxygen enters into therapeutically targeted cells. This results in a direct chemical protection against therapy by the hypoxic microenvironment, which has little to do with cellular biological regulatory processes. This part of the protective effect of hypoxia has been known for more than half a century and has been studied extensively. However, in recent years there has been more focus on the other aspect of hypoxia, namely the effect of this microenvironmental condition on selecting cells with certain genetic prerequisites that are negative with respect to patient prognosis. There are adaptive mechanisms, where hypoxia induces regulatory cascades in cells resulting in a changed metabolism or changes in extracellular signaling. These processes may lead to changes in cellular intrinsic sensitivity to treatment irrespective of oxygenation and, furthermore, may also have consequences for tissue organization. Thus, the adaptive mechanisms induced by hypoxia itself may have a selective effect on cells, with a fine-tuned protection against damage and stress of many kinds. It therefore could be that the adaptive mechanisms may take advantage of for new tumor labeling/imaging and treatment strategies. One of the Achilles' heels of hypoxia research has always been the exact measurements of tissue oxygenation as well as the control of oxygenation in biological tumor models. Thus, development of technology that can ease this control is vital in order to study mechanisms and perform drug development under relevant conditions. An integrated EU Framework project 2004-2009, termed EUROXY, demonstrates several pathways involved in transcription and translation control of the hypoxic cell phenotype and evidence of cross-talk with responses to pH and redox changes. The carbonic anhydrase isoenzyme CA IX was selected for further studies due to its expression on the surface of many types of hypoxic tumors. The effort has led to marketable culture flasks with sensors and incubation equipment, and the synthesis of new drug candidates against new molecular targets. New labeling/imaging methods for cancer diagnosing and imaging of hypoxic cancer tissue are now being tested in xenograft models and are also in early clinical testing, while new potential anti-cancer drugs are undergoing tests using xenografted tumor cancers. The present article describes the above results in individual consortium partner presentations.

Intra-voxel heterogeneity influences the dose prescription for dose-painting with radiotherapy: a modelling study

The purpose of this study was to increase the potential of dose redistribution by incorporating estimates of oxygen heterogeneity within imaging voxels for optimal dose determination. Cellular oxygen tension (pO(2)) distributions were estimated for imaging-size-based voxels by solving oxygen diffusion-consumption equations around capillaries placed at random locations. The linear-quadratic model was used to determine cell survival in the voxels as a function of pO(2) and dose. The dose distribution across the tumour was optimized to yield minimal survival after 30 x 2 Gy fractions by redistributing the dose based on differences in oxygen levels. Eppendorf data of a series of 69 tumours were used as a surrogate of what might be expected from oxygen imaging datasets. Dose optimizations were performed both taking into account cellular heterogeneity in oxygenation within voxels and assuming a homogeneous cellular distribution of oxygen. Our simulations show that dose redistribution based on derived cellular oxygen distributions within voxels result in dose distributions that require less total dose to obtain the same degree of cell kill as dose distributions that were optimized with a model that considered voxels as homogeneous with respect to oxygen. Moderately hypoxic tumours are expected to gain most from dose redistribution. Incorporating cellular-based distributions of radiosensitivity into dose-planning algorithms theoretically improves the potential gains from dose redistribution algorithms.

The histone demethylases JMJD1A and JMJD2B are transcriptional targets of hypoxia-inducible factor HIF

Posttranslational histone modifications serve to store epigenetic information and control both nucleosome assembly and recruitment of non-histone proteins. Histone methylation occurs on arginine and lysine residues and is involved in the regulation of gene transcription. A dynamic control of these modifications is exerted by histone methyltransferases and the recently discovered histone demethylases. Here we show that the hypoxia-inducible factor HIF-1alpha binds to specific recognition sites in the genes encoding the jumonji family histone demethylases JMJD1A and JMJD2B and induces their expression. Accordingly, hypoxic cells express elevated levels of JMJD1A and JMJD2B mRNA and protein. Furthermore, we find increased expression of JMJD1A and JMJD2B in renal cancer cells that have lost the von Hippel Lindau tumor suppressor protein VHL and therefore display a deregulated expression of hypoxia-inducible factor. Studies on ectopically expressed JMJD1A and JMJD2B indicate that both proteins retain their histone lysine demethylase activity in hypoxia and thereby might impact the hypoxic gene expression program.

Molecular imaging of metastatic potential

If molecular imaging is to prove clinically useful it will have to surpass current, primarily anatomic techniques in terms of sensitivity and the ability to detect minimal changes in tissue. One of the most important tests for molecular imaging is to determine whether it can image the metastatic potential of tumors. Like all predictive endeavors, the imaging of such "potential" is a daunting task, but one that only molecular imaging--rather than standard, anatomic techniques--is likely to solve. Although difficult, imaging of metastatic potential is also arguably the most important task for molecular imaging of cancer because it is generally the dissemination of malignant tissue, not its prolonged residence in an inopportune site, which kills the patient. Below are examples of uses of molecular imaging of metastases as well as of metastatic potential, the former being a far more developed area of clinical inquiry.