Validation of a gene expression profile predictive of the risk of radiation-induced fibrosis in women treated with breast conserving therapy

The transcriptomic revolution and radiation biology

PURPOSE

This article will briefly review the origins and evolution of functional genomics, first describing the experimental technology, and then some of the approaches applied to data analysis and visualization. It will emphasize application of functional genomics to radiation biology, using examples from the author's work to illustrate several key types of analysis. It concludes with a look at non-coding RNA, alternative reading of the genome, and single-cell transcriptomics, some of the innovative areas that may help to shape future research in radiation biology and oncology.

CONCLUSIONS

Transcriptomic approaches have provided insight into many areas of radiation biology and medicine, and innovations in technology and data analysis approaches promise continued contributions to radiation science in the future.

Molecular profiling of neuroendocrine tumours to predict response and toxicity to peptide receptor radionuclide therapy

Peptide receptor radionuclide therapy (PRRT) is a type of radiotherapy that targets peptide receptors and is typically used for neuroendocrine tumours (NETs). Some of the key challenges in its use are the prediction of efficacy and toxicity, patient selection, and response optimisation. In this Review, we assess current knowledge on the molecular profile of NETs and the strategies and tools used to predict, monitor, and assess the toxicity of PRRT. The few mutations in tumour genes that can be evaluated (eg, ATM and DAXX) are limited to pancreatic NETs and are most likely not informative. Assays that are transcriptomic or based on genes are effective in the prediction of radiotherapy response in other cancers. A blood-based assay for eight genes (the PRRT prediction quotient [PPQ]) has an overall accuracy of 95% for predicting responses to PRRT in NETs. No molecular markers exist that can predict the toxicity of PRRT. Candidate molecular targets include seven single nucleotide polymorphisms (SNPs) that are susceptible to radiation. Transcriptomic evaluations of blood and a combination of gene expression and specific SNPs, assessed by machine learning with algorithms that are tumour-specific, might yield molecular tools to enhance the efficacy and safety of PRRT.

Validation of a normal tissue complication probability model for late unfavourable aesthetic outcome after breast-conserving therapy

PURPOSE

To validate a normal tissue complication probability (NTCP) model for late unfavourable aesthetic outcome (AO) after breast-conserving therapy.

MATERIALS/METHODS

The BCCT.core software evaluated the AO using standardized photographs of patients treated at the University Hospitals Leuven between April 2015 and April 2016. Dose maps in 2 Gy equivalents were calculated assuming α/β = 3.6 Gy. The discriminating ability of the model was described by the AUC of the receiver operating characteristic curve. A 95% confidence interval (CI) of AUC was calculated using 10,000 bootstrap replications. Calibration was evaluated with the calibration plot and Nagelkerke R². Patients with unfavourable AO at baseline were excluded. Patient, tumour and treatment characteristics were compared between the development and the validation cohort. The prognostic value of the characteristics in the validation cohort was further evaluated in univariable and multivariable analysis.

RESULTS

Out of 175 included patients, 166 were evaluated two years after RT and 44 (26.51%) had unfavourable AO. AUC was 0.66 (95% CI 0.56; 0.76). Calibration was moderate with small overestimations at higher risk. When applying all of the univariable significant clinicopathological and dosimetrical variables from the validation cohort in a multivariable model, the presence of a seroma and V45 were selected as significant risk factors for unfavourable AO (Odds Ratio 4.40 (95% CI 1.96; 9.86) and 1.14 (95% CI 1.03; 1.27), p-value <.001 and .01, respectively).

CONCLUSIONS

The NTCP model for unfavourable AO shows a moderate discrimination and calibration in the present prospective validation cohort with a small overestimation in the high risk patients.

Validation of genetic predictors of late radiation-induced morbidity in prostate cancer patients

INTRODUCTION

Normal tissue morbidity sets the dose limit for radiotherapy (RT) in cancer treatment and has importance for quality of life for cancer survivors. A previous study of prostate cancer patients treated with RT generated clinical data for radiation-induced morbidity measured by anorectal physiological methods and validated questionnaires. Other studies have identified genetic predictors associated with late radiation-induced morbidity outcome. We have expanded biobank material aiming to validate single nucleotide polymorphisms (SNPs) and a gene expression classifier with endpoints on patient-reported outcomes and biomechanical properties of the anorectum from our cohort matching originally published endpoints.

MATERIALS AND METHODS

The present cohort of prostate cancer patients was treated with RT curative intent in 1999-2007. Nine SNPs associated with late radiation-induced morbidity were tested in 96 patients (rs2788612, rs1800629, rs264663, rs2682585, rs2268363, rs1801516, rs13035033, rs7120482 and rs17779457). A validated gene expression profile predictive of resistance to radiation-induced skin fibrosis was tested in 42 patients. An RT-induced anorectal dysfunction score (RT-ARD) served as a fibrosis-surrogate and a measure of overall radiation-induced morbidity.

RESULTS

The lowest p-value found in the genotype analyses was for SNP rs2682585 minor allele (A) in the FSHR gene and the RT-ARD score with odds ratios (OR) = 1.76; 95% CI (0.98-3.17) p = .06, which was out of concordance with original data showing a protective effect of the minor allele. The gene expression profile in patients classified as fibrosis-resistant was associated with high RT-ARD scores OR 4.18; 95% CI (1.1-16.6), p = .04 conflicting with the hypothesis that fibrosis-resistant patients would experience lower RT-ARD scores.

CONCLUSIONS

We aimed to validate nine SNPs and a gene expression classifier in a cohort of prostate cancer patients with unique scoring of radiation-induced morbidity. One significant association was found, pointing to the opposite direction of originally published data. We conclude that the material was not able to validate previously published genetic predictors of radiation-induced morbidity.

Differential gene expression in primary fibroblasts induced by proton and cobalt-60 beam irradiation

INTRODUCTION

Proton beam therapy delivers a more conformal dose distribution than conventional radiotherapy, thus improving normal tissue sparring. Increasing linear energy transfer (LET) along the proton track increases the relative biological effectiveness (RBE) near the distal edge of the Spread-out Bragg peak (SOBP). The severity of normal tissue side effects following photon beam radiotherapy vary considerably between patients.

AIM

The dual study aim was to identify gene expression patterns specific to radiation type and proton beam position, and to assess whether individual radiation sensitivity influences gene expression levels in fibroblast cultures irradiated in vitro.

METHODS

The study includes 30 primary fibroblast cell cultures from patients previously classified as either radiosensitive or radioresistant. Cells were irradiated at three different positions in the proton beam profile: entrance, mid-SOBP and at the SOBP distal edge. Dose was delivered in three fractions × 3.5 Gy(RBE) (RBE 1.1). Cobalt-60 (Co-60) irradiation was used as reference. Real-time qPCR was performed to determine gene expression levels for 17 genes associated with inflammation response, fibrosis and angiogenesis.

RESULTS

Differences in median gene expression levels were observed for multiple genes such as IL6, IL8 and CXCL12. Median IL6 expression was 30%, 24% and 47% lower in entrance, mid-SOBP and SOBP distal edge groups than in Co-60 irradiated cells. No genes were found to be oppositely regulated by different radiation qualities. Radiosensitive patient samples had the strongest regulation of gene expression; irrespective of radiation type.

CONCLUSIONS

Our findings indicate that the increased LET at the SOBP distal edge position did not generally lead to increased transcriptive response in primary fibroblast cultures. Inflammatory factors were generally less extensively upregulated by proton irradiation compared with Co-60 photon irradiation. These effects may possibly influence the development of normal tissue damage in patients treated with proton beam therapy.