A prognostic hypoxia gene signature with low heterogeneity within the dominant tumour lesion in prostate cancer patients.

BACKGROUND: Gene signatures measured in a biopsy have been proposed as hypoxia biomarkers in prostate cancer. We assessed a previously developed signature, and aimed to determine its relationship to hypoxia and its heterogeneity within the dominant (index) lesion of prostate cancer. METHODS: The 32-gene signature was assessed from gene expression data of 141 biopsies from the index lesion of 94 patients treated with prostatectomy. A gene score calculated from the expression levels was applied in the analyses. Hypoxic fraction from pimonidazole immunostained whole-mount and biopsy sections was used as reference standard for hypoxia. RESULTS: The gene score was correlated with pimonidazole-defined hypoxic fraction in whole-mount sections, and the two parameters showed almost equal association with clinical markers of tumour aggressiveness. Based on the gene score, incorrect classification according to hypoxic fraction in whole-mount sections was seen in one third of the patients. The incorrect classifications were apparently not due to intra-tumour heterogeneity, since the score had low heterogeneity compared to pimonidazole-defined hypoxic fraction in biopsies. The score showed prognostic significance in uni-and multivariate analysis in independent cohorts. CONCLUSIONS: Our signature from the index lesion reflects tumour hypoxia and predicts prognosis in prostate cancer, independent of intra-tumour heterogeneity in pimonidazole-defined hypoxia.

Influx rate of 18F-fluoroaminosuberic acid reflects cystine/glutamate antiporter expression in tumour xenografts.

PURPOSE: 18F-fluoroaminosuberic acid (18F-FASu) is a recently developed amino acid tracer for positron emission tomography (PET) of oxidative stress that may offer improved tumour assessment over the conventional tracer 18F-fluorodeoxyglucose (18F-FDG). Our aim was to evaluate and relate dynamic 18F-FASu and 18F-FDG uptake with pharmacokinetic modelling to transporter protein expression levels in a panel of diverse tumour xenograft lines. METHODS: Four different tumour xenograft lines were implanted in female athymic nude mice: MAS98.12 and HBCx3 (breast), TPMX (osteosarcoma) and A549 (lung). Dynamic PET over 60 min was performed on a small animal unit. The time-activity curves (TACs) for 18F-FASu and 18F-FDG in individual tumours were used to extract early (SUVE; 2 min p.i.) and late (SUVL; 55 min p.i.) standardised uptake values. Pharmacokinetic two-tissue compartment models were applied to the TACs to estimate rate constants K1-k4 and blood volume fraction vB. Relative levels of cystine/glutamate antiporter subunit xCT were assessed by western blotting, and expression of GLUT1 and CD31 by immunohistochemistry. RESULTS: 18F-FASu showed higher SUVE, whilst 18F-FDG exhibited higher SUVL. Influx rate K1 for 18F-FASu was significantly correlated with xCT levels (p = 0.001) and was significantly higher than K1 for 18F-FDG (p < 0.001). K1 for 18F-FDG was significantly correlated with GLUT1 levels (p = 0.002). vB estimated from 18F-FASu and 18F-FDG TACs was highly consistent and significantly correlated (r = 0.85, p < 0.001). Two qualitatively different 18F-FASu uptake profiles were identified: type α with low xCT expression and low K1 (A549 and HBCx3), and type ß with high xCT expression and high K1 (MAS98.12 and TPMX). CONCLUSION: The influx rate of 18F-FASu reflects xCT activity in tumour xenografts. Dynamic PET with pharmacokinetic modelling is needed to fully appraise 18F-FASu distribution routes.

PTEN Expression in Prostate Cancer: Relationship With Clinicopathologic Features and Multiparametric MRI Findings.

OBJECTIVE. The objective of our study was to investigate whether phosphatase and tensin homolog (PTEN) expression is associated with clinicopathologic features and multiparametric MRI findings in prostate cancer. MATERIALS AND METHODS. Forty-three patients with prostate cancer who underwent radical prostatectomy were included. Index tumor was identified on pretreatment MRI and delineated in the area that correlated best with histopathology results. The apparent diffusion coefficient (ADC) from DWI and pharmacokinetic parameters derived from dynamic contrast-enhanced MRI (DCE-MRI) using the extended Tofts model (Ktrans, kep, ve, and vp) within the tumor were estimated. The following clinicopathologic parameters were assessed: pretreatment serum levels of prostate-specific antigen, disseminated tumor cell status, age, Gleason score, tumor size, extraprostatic extension (EPE), tumor location, and lymph node metastases. Gene expression profiles were acquired in biopsies from the tumor using bead arrays, and validated using reverse transcription quantitative polymerase chain reaction (RT-qPCR) on a different part of the biopsy. RESULTS. Based on bead arrays (p = 0.006) and RT-qPCR (p = 0.03) data, a significantly lower ADC was found in tumors with low PTEN expression. Moreover, PTEN expression was negatively associated with lymph node metastases (bead arrays, p = 0.008; RT-qPCR, p < 0.001). A weak but significant association between PTEN expression, EPE (p = 0.048), and Gleason score (p = 0.028) was revealed on bead arrays. ADC was negatively correlated with Gleason score (p = 0.001) and tumor size (p = 0.023). No association among DCE parameters, PTEN expression, and clinicopathologic features was found. CONCLUSION. ADC derived from DWI may be useful in selecting patients with potentially aggressive tumor caused by PTEN deficiency.

Low dose-rate irradiation with [3H]-labelled valine to selectively target hypoxic cells in a human colorectal cancer xenograft model.

BACKGROUND: Earlier in vitro studies show that irradiation with an ultra-low dose-rate of 15 mGy/h delivered with [3H]-valine leads to loss of clonogenicity in hypoxic T-47D cells. Here, the aim was to determine if [3H]-valine could be used to deliver low dose-rate irradiation in a colorectal cancer model. METHODS: Clonogenicity was measured in cultured cancer cell line HT29 irradiated with 15 mGy/h combined with intermittent hypoxia. Mice with HT29 xenografts were irradiated by repeated injections of [3H]-valine intravenously. The activity in the tumor tissue was measured by scintillation counting and tumor growth, hypoxic fraction and tritium distribution within tumors were assessed by pimonidazole staining and autoradiography. RESULTS: Ultra-low dose-rate irradiation decreased clonogenicity in hypoxic colorectal cancer cells. In vivo, the tumor growth, hypoxic fraction and weight of the mice were similar between the treated and untreated group. Autoradiography showed no [3H]-valine uptake in hypoxic tumor regions in contrast to aerobic tissue. CONCLUSION: Continuous low-dose-rate irradiation was well tolerated by aerobic tissue. This indicates a potential use of low dose-rate irradiation to target hypoxic tumor cells in combination with high dose-rate irradiation to eradicate the well oxygenated tumor regions. However, [3H]-valine is not the appropriate method to deliver ultra-low dose-rate irradiation in vivo.

Autodelineation of cervical cancers using multiparametric magnetic resonance imaging and machine learning.

BACKGROUND: Tumour delineation is a challenging, time-consuming and complex part of radiotherapy planning. In this study, an automatic method for delineating locally advanced cervical cancers was developed using a machine learning approach. MATERIALS AND METHODS: A method for tumour segmentation based on image voxel classification using Fisher?s Linear Discriminant Analysis (LDA) was developed. This was applied to magnetic resonance (MR) images of 78 patients with locally advanced cervical cancer. The segmentation was based on multiparametric MRI consisting of T2- weighted (T2w), T1-weighted (T1w) and dynamic contrast-enhanced (DCE) sequences, and included intensity and spatial information from the images. The model was trained and assessed using delineations made by two radiologists. RESULTS: Segmentation based on T2w or T1w images resulted in mean sensitivity and specificity of 94% and 52%, respectively. Including DCE-MR images improved the segmentation model?s performance significantly, giving mean sensitivity and specificity of 85?93%. Comparisons with radiologists? tumour delineations gave Dice similarity coefficients of up to 0.44. CONCLUSION: Voxel classification using a machine learning approach is a flexible and fully automatic method for tumour delineation. Combining all relevant MR image series resulted in high sensitivity and specificity. Moreover, the presented method can be extended to include additional imaging modalities.

Hypoxia-independent gene expression signature associated with radiosensitisation of prostate cancer cell lines by histone deacetylase inhibition.

BACKGROUND: Histone deacetylase inhibitors (HDACis) like vorinostat are promising radiosensitisers in prostate cancer, but their effect under hypoxia is not known. We investigated gene expression associated with radiosensitisation of normoxic and hypoxic prostate cancer cells by vorinostat. METHODS: Cells were exposed to vorinostat under normoxia or hypoxia and subjected to gene expression profiling before irradiation and clonogenic survival analysis. RESULTS: Pretreatment with vorinostat led to radiosensitisation of the intrinsically radioresistant DU 145 cells, but not the radiosensitive PC-3 and 22Rv1 cells, and was independent of hypoxia status. Knockdown experiments showed that the sensitisation was not caused by repression of hypoxia-inducible factor HIF1 or tumour protein TP53. Global deregulation of DNA repair and chromatin organisation genes was associated with radiosensitisation under both normoxia and hypoxia. A radiosensitisation signature with expression changes of 56 genes was generated and valid for both conditions. For eight signature genes, baseline expression also correlated with sensitisation, showing potential as pretreatment biomarker. The hypoxia independence of the signature was confirmed in a clinical data set. CONCLUSIONS: Pretreatment with HDACi may overcome radioresistance of hypoxic prostate tumours by similar mechanisms as under normoxia. We propose a gene signature to predict radiosensitising effects independent of hypoxia status.

Cluster analysis of dynamic contrast enhanced MRI reveals tumor subregions related to locoregional relapse for cervical cancer patients.

BACKGROUND: Solid tumors are known to be spatially heterogeneous. Detection of treatment-resistant tumor regions can improve clinical outcome, by enabling implementation of strategies targeting such regions. In this study, K-means clustering was used to group voxels in dynamic contrast enhanced magnetic resonance images (DCE-MRI) of cervical cancers. The aim was to identify clusters reflecting treatment resistance that could be used for targeted radiotherapy with a dose-painting approach. MATERIAL AND METHODS: Eighty-one patients with locally advanced cervical cancer underwent DCE-MRI prior to chemoradiotherapy. The resulting image time series were fitted to two pharmacokinetic models, the Tofts model (yielding parameters Ktrans and νe) and the Brix model (ABrix, kep and kel). K-means clustering was used to group similar voxels based on either the pharmacokinetic parameter maps or the relative signal increase (RSI) time series. The associations between voxel clusters and treatment outcome (measured as locoregional control) were evaluated using the volume fraction or the spatial distribution of each cluster. RESULTS: One voxel cluster based on the RSI time series was significantly related to locoregional control (adjusted p-value 0.048). This cluster consisted of low-enhancing voxels. We found that tumors with poor prognosis had this RSI-based cluster gathered into few patches, making this cluster a potential candidate for targeted radiotherapy. None of the voxels clusters based on Tofts or Brix parameter maps were significantly related to treatment outcome. CONCLUSION: We identified one group of tumor voxels significantly associated with locoregional relapse that could potentially be used for dose painting. This tumor voxel cluster was identified using the raw MRI time series rather than the pharmacokinetic maps.

Targeting tumour hypoxia to prevent cancer metastasis. From biology, biosensing and technology to drug development: the METOXIA consortium.

The hypoxic areas of solid cancers represent a negative prognostic factor irrespective of which treatment modality is chosen for the patient. Still, after almost 80 years of focus on the problems created by hypoxia in solid tumours, we still largely lack methods to deal efficiently with these treatment-resistant cells. The consequences of this lack may be serious for many patients: Not only is there a negative correlation between the hypoxic fraction in tumours and the outcome of radiotherapy as well as many types of chemotherapy, a correlation has been shown between the hypoxic fraction in tumours and cancer metastasis. Thus, on a fundamental basis the great variety of problems related to hypoxia in cancer treatment has to do with the broad range of functions oxygen (and lack of oxygen) have in cells and tissues. Therefore, activation-deactivation of oxygen-regulated cascades related to metabolism or external signalling are important areas for the identification of mechanisms as potential targets for hypoxia-specific treatment. Also the chemistry related to reactive oxygen radicals (ROS) and the biological handling of ROS are part of the problem complex. The problem is further complicated by the great variety in oxygen concentrations found in tissues. For tumour hypoxia to be used as a marker for individualisation of treatment there is a need for non-invasive methods to measure oxygen routinely in patient tumours. A large-scale collaborative EU-financed project 2009-2014 denoted METOXIA has studied all the mentioned aspects of hypoxia with the aim of selecting potential targets for new hypoxia-specific therapy and develop the first stage of tests for this therapy. A new non-invasive PET-imaging method based on the 2-nitroimidazole [(18)F]-HX4 was found to be promising in a clinical trial on NSCLC patients. New preclinical models for testing of the metastatic potential of cells were developed, both in vitro (2D as well as 3D models) and in mice (orthotopic grafting). Low density quantitative real-time polymerase chain reaction (qPCR)-based assays were developed measuring multiple hypoxia-responsive markers in parallel to identify tumour hypoxia-related patterns of gene expression. As possible targets for new therapy two main regulatory cascades were prioritised: The hypoxia-inducible-factor (HIF)-regulated cascades operating at moderate to weak hypoxia (<1% O(2)), and the unfolded protein response (UPR) activated by endoplasmatic reticulum (ER) stress and operating at more severe hypoxia (<0.2%). The prioritised targets were the HIF-regulated proteins carbonic anhydrase IX (CAIX), the lactate transporter MCT4 and the PERK/eIF2α/ATF4-arm of the UPR. The METOXIA project has developed patented compounds targeting CAIX with a preclinical documented effect. Since hypoxia-specific treatments alone are not curative they will have to be combined with traditional anti-cancer therapy to eradicate the aerobic cancer cell population as well.

Identification of eight candidate target genes of the recurrent 3p12-p14 loss in cervical cancer by integrative genomic profiling.

The pathogenetic role, including its target genes, of the recurrent 3p12-p14 loss in cervical cancer has remained unclear. To determine the onset of the event during carcinogenesis, we used microarray techniques and found that the loss was the most frequent 3p event, occurring in 61% of 92 invasive carcinomas, in only 2% of 43 high-grade intraepithelial lesions (CIN2/3), and in 33% of 6 CIN3 lesions adjacent to invasive carcinomas, suggesting a role in acquisition of invasiveness or early during the invasive phase. We performed an integrative DNA copy number and expression analysis of 77 invasive carcinomas, where all genes within the recurrent region were included. We selected eight genes, THOC7, PSMD6, SLC25A26, TMF1, RYBP, SHQ1, EBLN2, and GBE1, which were highly down-regulated in cases with loss, as confirmed at the protein level for RYBP and TMF1 by immunohistochemistry. The eight genes were subjected to network analysis based on the expression profiles, revealing interaction partners of proteins encoded by the genes that were coordinately regulated in tumours with loss. Several partners were shared among the eight genes, indicating crosstalk in their signalling. Gene ontology analysis showed enrichment of biological processes such as apoptosis, proliferation, and stress response in the network and suggested a relationship between down-regulation of the eight genes and activation of tumourigenic pathways. Survival analysis showed prognostic impact of the eight-gene signature that was confirmed in a validation cohort of 74 patients and was independent of clinical parameters. These results support the role of the eight candidate genes as targets of the 3p12-p14 loss in cervical cancer and suggest that the strong selection advantage of the loss during carcinogenesis might be caused by a synergetic effect of several tumourigenic processes controlled by these targets.

MRI-guided dynamic risk assessment in cervical cancer based on tumor hypoxia at diagnosis and volume response at brachytherapy.

BACKGROUND AND PURPOSE: Improvements in treatment outcome for patients with locally advanced cervical cancer (LACC) require a better classification of patients according to their risk of recurrence. We investigated whether an imaging-based approach, combining pretreatment hypoxia and tumor response during therapy, could improve risk classification. MATERIAL AND METHODS: Ninety-three LACC patients with T2-weigthed (T2W)-, dynamic contrast enhanced (DCE)- and diffusion weighted (DW)-magnetic resonance (MR) images acquired before treatment, and T2W- and, for 64 patients, DW-MR images, acquired at brachytherapy, were collected. Pretreatment hypoxic fraction (HFpre) was determined from DCE- and DW-MR images using the consumption and supply-based hypoxia (CSH)-imaging method. Volume regression at brachytherapy was assessed from T2W-MR images and combined with HFpre. In 17 patients with adequate DW-MR images at brachytherapy, the apparent diffusion coefficient (ADC), reflecting tumor cell density, was calculated. Change in ADC during therapy was combined with volume regression yielding functional regression as explorative response measure. Endpoint was disease free survival (DFS). RESULTS: HFpre was the strongest predictor of DFS, but a significant correlation with outcome was found also for volume regression. The combination of HFpre and volume regression showed a stronger association with DFS than HFpre alone. Patients with disease recurrence were selected to either the intermediate- or high-risk group with a 100 % accuracy. Functional regression showed a stronger correlation to HFpre than volume regression. CONCLUSION: The combination of pretreatment hypoxia and volume regression at brachytherapy improved patient risk classification. Integration of ADC with volume regression showed promise as a new tumor response parameter.

An Immune Gene Expression Risk Score for Distant Metastases after Radiotherapy for Cervical Cancer.

PURPOSE: To develop an immune-based gene expression risk score to identify patients with cervical cancer at increased risk of distant metastases (DM). EXPERIMENTAL DESIGN: Tumor biopsies were obtained from 81 patients prior to chemoradiotherapy. Whole-transcriptome RNA sequencing was performed (Illumina NextSeq500). Beginning with 4,723 immune-related genes, a 55-gene risk score for DM was derived using Cox modeling and principal component analysis. It was validated in independent cohorts of 274 patients treated at the Norwegian Radium Hospital (NRH) and 206 patients from The Cancer Genome Atlas (TCGA). RESULTS: The risk score was predictive of DM (HR, 2.7; P < 0.0001) and lower cause-specific survival (CSS) by univariate analysis (HR, 2.0; P = 0.0003) and multivariate analysis adjusted for clinical factors (DM HR, 3.0; P < 0.0001; CSS HR, 2.2; P = 0.0004). The risk score predicted DM (HR, 1.4; P = 0.05) and CSS (HR, 1.48; P = 0.013) in the NRH cohort and CSS (HR, 1.4; P = 0.03) in TCGA cohort. Higher risk scores were associated with lower CIBERSORT estimates of tumor-infiltrating immune cells, including CD8 T cells and M1 and M2 macrophages (all P < 0.001). Higher risk scores were associated with lower expression (all P < 0.001) of important chemokines (CXCL12, CXCR4), IFN-regulated genes (IRF1, STAT1, IDO1), and immune checkpoint regulators (PD-1, PD-L1, CTLA-4). CONCLUSIONS: The immune metastatic risk score addresses important challenges in the treatment of cervical cancer-identifying patients at high risk of DM after radiotherapy. The findings of this study indicate that high tumor mutational burden and a "cold," immune-excluded tumor microenvironment influence distant metastatic recurrence. Further validation of the risk score is needed.

Discovery and technical validation of high-performance methylated DNA markers for the detection of cervical lesions at risk of malignant progression in low- and middle-income countries.

BACKGROUND: Cervical cancer remains a leading cause of death, particularly in developing countries. WHO screening guidelines recommend human papilloma virus (HPV) detection as a means to identify women at risk of developing cervical cancer. While HPV testing identifies those at risk, it does not specifically distinguish individuals with neoplasia. We investigated whether a quantitative molecular test that measures methylated DNA markers could identify high-risk lesions in the cervix with accuracy. RESULTS: Marker discovery was performed in TCGA-CESC Infinium Methylation 450 K Array database and verified in three other public datasets. The panel was technically validated using Quantitative Multiplex-Methylation-Specific PCR in tissue sections (N = 252) and cervical smears (N = 244) from the USA, South Africa, and Vietnam. The gene panel consisted of FMN2, EDNRB, ZNF671, TBXT, and MOS. Cervical tissue samples from all three countries showed highly significant differential methylation in squamous cell carcinoma (SCC) with a sensitivity of 100% [95% CI 74.12-100.00], and specificity of 91% [95% CI 62.26-99.53] to 96% [95% CI 79.01-99.78], and receiver operating characteristic area under the curve (ROC AUC) = 1.000 [95% CI 1.00-1.00] compared to benign cervical tissue, and cervical intraepithelial neoplasia 2/3 with sensitivity of 55% [95% CI 37.77-70.84] to 89% [95% CI 67.20-98.03], specificity of 93% [95% CI 84.07-97.38] to 96% [95% CI 79.01-99.78], and a ROC AUC ranging from 0.793 [95% CI 0.68-0.89] to 0.99 [95% CI 0.97-1.00] compared to CIN1. In cervical smears, the marker panel detected SCC with a sensitivity of 87% [95% CI 77.45-92.69], specificity 95% [95% CI 88.64-98.18], and ROC AUC = 0.925 [95% CI 0.878-0.974] compared to normal, and high-grade squamous intraepithelial lesion (HSIL) at a sensitivity of 70% (95% CI 58.11-80.44), specificity of 94% (95% CI 88.30-97.40), and ROC AUC = 0.884 (95% CI 0.822-0.945) compared to low-grade intraepithelial lesion (LSIL)/normal in an analysis of pooled data from the three countries. Similar to HPV-positive, HPV-negative cervical carcinomas were frequently hypermethylated for these markers. CONCLUSIONS: This 5-marker panel detected SCC and HSIL in cervical smears with a high level of sensitivity and specificity. Molecular tests with the ability to rapidly detect high-risk HSIL will lead to timely treatment for those in need and prevent unnecessary procedures in women with low-risk lesions throughout the world. Validation of these markers in prospectively collected cervical smear cells followed by the development of a hypermethylated marker-based cervical cancer detection test is warranted.

ALDH1A1 drives prostate cancer metastases and radioresistance by interplay with AR- and RAR-dependent transcription.

Rationale: Current therapies for metastatic osseous disease frequently fail to provide a durable treatment response. To date, there are only limited therapeutic options for metastatic prostate cancer, the mechanisms that drive the survival of metastasis-initiating cells are poorly characterized, and reliable prognostic markers are missing. A high aldehyde dehydrogenase (ALDH) activity has been long considered a marker of cancer stem cells (CSC). Our study characterized a differential role of ALDH1A1 and ALDH1A3 genes as regulators of prostate cancer progression and metastatic growth. Methods: By genetic silencing of ALDH1A1 and ALDH1A3 in vitro, in xenografted zebrafish and murine models, and by comparative immunohistochemical analyses of benign, primary tumor, and metastatic specimens from patients with prostate cancer, we demonstrated that ALDH1A1 and ALDH1A3 maintain the CSC phenotype and radioresistance and regulate bone metastasis-initiating cells. We have validated ALDH1A1 and ALDH1A3 as potential biomarkers of clinical outcomes in the independent cohorts of patients with PCa. Furthermore, by RNAseq, chromatin immunoprecipitation (ChIP), and biostatistics analyses, we suggested the molecular mechanisms explaining the role of ALDH1A1 in PCa progression. Results: We found that aldehyde dehydrogenase protein ALDH1A1 positively regulates tumor cell survival in circulation, extravasation, and metastatic dissemination, whereas ALDH1A3 plays the opposite role. ALDH1A1 and ALDH1A3 are differentially expressed in metastatic tumors of patients with prostate cancer, and their expression levels oppositely correlate with clinical outcomes. Prostate cancer progression is associated with the increasing interplay of ALDH1A1 with androgen receptor (AR) and retinoid receptor (RAR) transcriptional programs. Polo-like kinase 3 (PLK3) was identified as a transcriptional target oppositely regulated by ALDH1A1 and ALDH1A3 genes in RAR and AR-dependent manner. PLK3 contributes to the control of prostate cancer cell proliferation, migration, DNA repair, and radioresistance. ALDH1A1 gain in prostate cancer bone metastases is associated with high PLK3 expression. Conclusion: This report provides the first evidence that ALDH1A1 and PLK3 could serve as biomarkers to predict metastatic dissemination and radiotherapy resistance in patients with prostate cancer and could be potential therapeutic targets to eliminate metastasis-initiating and radioresistant tumor cell populations.

Exploring Hypoxia in Prostate Cancer With T2-weighted Magnetic Resonance Imaging Radiomics and Pimonidazole Scoring.

BACKGROUND/AIM: Radiomics involves high throughput extraction of mineable precise quantitative imaging features that serve as non-invasive prognostic or predictive biomarkers. High levels of hypoxia are associated with a poorer prognosis in prostate cancer and limit radiation therapy efficacy. Most patients with prostate cancer undergo magnetic resonance imaging (MRI) as a part of their diagnostics, and T2 imaging is the most utilised imaging method. The aim of this study was to determine whether hypoxia in prostate tumors could be identified using a radiomics model extracted from T2-weighted MR images. MATERIALS AND METHODS: Eighty eight intermediate or high-risk prostate cancer patients were evaluated. Prior to radical prostatectomy, all patients received pimonidazole (PIMO). PIMO hypoxic scores were assigned in whole-mount sections from prostatectomy specimens by an experienced pathologist who was blinded to MRI. The region of interest used for radiomics analysis included the prostatic index tumor. Radiomics extraction yielded 165 features using a special evaluation version of RadiomiX [RadiomiX Research Toolbox version 20180831 (OncoRadiomics SA, Liège, Belgium)] for non-clinical use. Multivariable logistic regression with Elastic Net regularization was utilised using 10 times repeated 10-fold cross-validation to select the best model hyperparameters, optimizing for area under the receiver operating characteristic curve (AUC). RESULTS: The average (out of sample) performance based on the repeated cross validation using the ONESE model yielded an AUC of 0.60±0.2. Shape-based features were the most prominent in the model. CONCLUSION: The development of a radiomics hypoxia model using T2 weighted MR images, standard in the staging of prostate cancer, is possible.

Prostate cancer radiogenomics reveals proliferative gene expression programs associated with distinct MRI-based hypoxia levels.

BACKGROUND AND PURPOSE: The biology behind individual hypoxia levels in patient tumors is poorly understood. Here, we used radiogenomics to identify associations between magnetic resonance imaging (MRI)-based hypoxia levels and biological processes derived from gene expression data in prostate cancer. MATERIALS AND METHODS: For 85 prostate cancer patients, MRI-based hypoxia images were constructed by combining diffusion-weighted images reflecting oxygen consumption and supply. The ability to differentiate hypoxia levels in these images was verified by comparison with matched biopsy sections stained for the hypoxia marker pimonidazole. For MRI-defined hypoxia levels, corresponding hypoxic fractions were calculated and correlated with biopsy gene expression profiles. Biological processes were predicted by gene set enrichment analysis (GSEA) and validated by immunohistochemistry (Ki67 proliferation marker, reactive stroma grade) and RT-PCR (MYC). RESULTS: Genes with correlation between expression level and hypoxic fraction were identified for 56 MRI-based hypoxia levels. At all levels, GSEA identified proliferation as the predominant biological process enriched among the correlating genes. Two independent proliferative gene signatures were developed. The Peak1 signature, upregulated at moderate/severe hypoxia, reflected MYC upregulation and high Ki67-proliferation index of cancer cells in pimonidazole-positive regions. The Peak2 signature, upregulated at mild to non-hypoxic levels, was associated with fibroblast gene signature and reactive stroma grade. High scores of both Peak1 and Peak2 indicated elevated risk of biochemical recurrence in multiple cohorts. CONCLUSION: Radiogenomics identified two gene expression programs activated at different hypoxia levels, reflecting proliferation of cancer cells and stroma cells. Genes involved in these programs could be candidate targets for intervention.

Weighted lasso with data integration.

The lasso is one of the most commonly used methods for high-dimensional regression, but can be unstable and lacks satisfactory asymptotic properties for variable selection. We propose to use weighted lasso with integrated relevant external information on the covariates to guide the selection towards more stable results. Weighting the penalties with external information gives each regression coefficient a covariate specific amount of penalization and can improve upon standard methods that do not use such information by borrowing knowledge from the external material. The method is applied to two cancer data sets, with gene expressions as covariates. We find interesting gene signatures, which we are able to validate. We discuss various ideas on how the weights should be defined and illustrate how different types of investigations can utilize our method exploiting different sources of external data. Through simulations, we show that our method outperforms the lasso and the adaptive lasso when the external information is from relevant to partly relevant, in terms of both variable selection and prediction.

Gene dosage, expression, and ontology analysis identifies driver genes in the carcinogenesis and chemoradioresistance of cervical cancer.

Integrative analysis of gene dosage, expression, and ontology (GO) data was performed to discover driver genes in the carcinogenesis and chemoradioresistance of cervical cancers. Gene dosage and expression profiles of 102 locally advanced cervical cancers were generated by microarray techniques. Fifty-two of these patients were also analyzed with the Illumina expression method to confirm the gene expression results. An independent cohort of 41 patients was used for validation of gene expressions associated with clinical outcome. Statistical analysis identified 29 recurrent gains and losses and 3 losses (on 3p, 13q, 21q) associated with poor outcome after chemoradiotherapy. The intratumor heterogeneity, assessed from the gene dosage profiles, was low for these alterations, showing that they had emerged prior to many other alterations and probably were early events in carcinogenesis. Integration of the alterations with gene expression and GO data identified genes that were regulated by the alterations and revealed five biological processes that were significantly overrepresented among the affected genes: apoptosis, metabolism, macromolecule localization, translation, and transcription. Four genes on 3p (RYBP, GBE1) and 13q (FAM48A, MED4) correlated with outcome at both the gene dosage and expression level and were satisfactorily validated in the independent cohort. These integrated analyses yielded 57 candidate drivers of 24 genetic events, including novel loci responsible for chemoradioresistance. Further mapping of the connections among genetic events, drivers, and biological processes suggested that each individual event stimulates specific processes in carcinogenesis through the coordinated control of multiple genes. The present results may provide novel therapeutic opportunities of both early and advanced stage cervical cancers.

Targeted Therapy on the Screen: Do We Hit the Target?

A phase II trial, investigating whether the antidiabetic drug metformin could reduce hypoxia in cervical cancer, used imaging to preselect patients and test the biological hypothesis behind the drug effect. This trial design would be of importance for the implementation of targeted treatment in the clinic. See related article by Han et al., p. 5263.

Risk of recurrence after chemoradiotherapy identified by multimodal MRI and 18F-FDG-PET/CT in locally advanced cervical cancer.

BACKGROUND AND PURPOSE: MRI, applying dynamic contrast-enhanced (DCE) and diffusion-weighted (DW) sequences, and 18F-fluorodeoxyglucose (18F-FDG) PET/CT provide information about tumor aggressiveness that is unexploited in treatment of locally advanced cervical cancer (LACC). We investigated the potential of a multimodal combination of imaging parameters for classifying patients according to their risk of recurrence. MATERIALS AND METHODS: Eighty-two LACC patients with diagnostic MRI and FDG-PET/CT, treated with chemoradiotherapy, were collected. Thirty-eight patients with MRI only were included for validation of MRI results. Endpoints were survival (disease-free, cancer-specific, overall) and tumor control (local, locoregional, distant). Ktrans, reflecting vascular function, apparent diffusion coefficient (ADC), reflecting cellularity, and standardized uptake value (SUV), reflecting glucose uptake, were extracted from DCE-MR, DW-MR and FDG-PET images, respectively. By applying an oxygen consumption and supply-based method, ADC and Ktrans parametric maps were voxel-wise combined into hypoxia images that were used to determine hypoxic fraction (HF). RESULTS: HF showed a stronger association with outcome than the single modality parameters. This association was confirmed in the validation cohort. Low HF identified low-risk patients with 95% precision. Based on the 50th SUV-percentile (SUV50), patients with high HF were divided into an intermediate- and high-risk group with high and low SUV50, respectively. This defined a multimodality biomarker, HF/SUV50. HF/SUV50 increased the precision of detecting high-risk patients from 41% (HF alone) to 57% and showed prognostic significance in multivariable analysis for all endpoints. CONCLUSION: Multimodal combination of MR- and FDG-PET/CT-images improves classification of LACC patients compared to single modality images and clinical factors.

miR-200a/b/-429 downregulation is a candidate biomarker of tumor radioresistance and independent of hypoxia in locally advanced cervical cancer.

Many patients with locally advanced cervical cancer experience recurrence within the radiation field after chemoradiotherapy. Biomarkers of tumor radioresistance are required to identify patients in need of intensified treatment. Here, the biomarker potential of miR-200 family members was investigated in this disease. Also, involvement of tumor hypoxia in the radioresistance mechanism was determined, using a previously defined 6-gene hypoxia classifier. miR-200 expression was measured in pretreatment tumor biopsies of an explorative cohort (n = 90) and validation cohort 1 (n = 110) by RNA sequencing. Publicly available miR-200 data of 79 patients were included for the validation of prognostic significance. A score based on expression of the miR-200a/b/-429 (miR-200a, miR-200b, and miR-429) cluster showed prognostic significance in all cohorts. The score was significant in multivariate analysis of central pelvic recurrence. No association with distant recurrence or hypoxia status was found. Potential miRNA target genes were identified from gene expression profiles and showed enrichment of genes in extracellular matrix organization and cell adhesion. miR-200a/b/-429 overexpression had a pronounced radiosensitizing effect in tumor xenografts, whereas the effect was minor in vitro. In conclusion, miR-200a/b/-429 downregulation is a candidate biomarker of central pelvic recurrence and seems to predict cell adhesion-mediated tumor radioresistance independent of clinical markers and hypoxia.