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Biomarkers with relevance for loco-regional therapy are needed in human papillomavirus negative aka HPV(-) head and neck squamous cell carcinoma (HNSCC). Based on the premise that DNA methylation pattern is highly conserved, we sought to develop a reliable and robust methylome-based classifier identifying HPV(-) HNSCC patients at risk for loco-regional recurrence (LR) and all-event progression after postoperative radiochemotherapy (PORT-C). The training cohort consisted of HPV-DNA negative HNSCC patients (n = 128) homogeneously treated with PORT-C in frame of the German Cancer Consortium-Radiation Oncology Group (DKTK-ROG) multicenter biomarker trial. DNA Methylation analysis was performed using Illumina 450 K and 850 K-EPIC microarray technology. The performance of the classifier was integrated with a series of biomarkers studied in the training set namely hypoxia-, 5-microRNA (5-miR), stem-cell gene-expression signatures and immunohistochemistry (IHC)-based immunological characterization of tumors (CD3/CD8/PD-L1/PD1). Validation occurred in an independent cohort of HPV(-) HNSCC patients, pooled from two German centers (n = 125). We identified a 38-methylation probe-based HPV(-) Independent Classifier of disease Recurrence (HICR) with high prognostic value for LR, distant metastasis and overall survival (P < 10-9 ). HICR remained significant after multivariate analysis adjusting for anatomical site, lymph node extracapsular extension (ECE) and size (T-stage). HICR high-risk tumors were enriched for younger patients with hypoxic tumors (15-gene signature) and elevated 5-miR score. After adjustment for hypoxia and 5-miR covariates, HICR maintained predicting all endpoints. HICR provides a novel mean for assessing the risk of LR in HPV(-) HNSCC patients treated with PORT-C and opens a new opportunity for biomarker-assisted stratification and therapy adaptation in these patients.

RDS data of models developed and reported for the article entitled "Integrated radiogenomics analyses allow for subtype classification and improved outcome prognosis of patients with locally advanced HNSCC". Software package version is also available in repository

Purpose: To develop and validate a CT-based radiomics signature for the prognosis of loco-regional tumour control (LRC) in patients with locally advanced head and neck squamous cell carcinoma (HNSCC) treated by primary radiochemotherapy (RCTx) based on retrospective data from 6 partner sites of the German Cancer Consortium – Radiation Oncology Group (DKTK-ROG). Material and methods: Pre-treatment CT images of 318 patients with locally advanced HNSCC were collected. Four-hundred forty-six features were extracted from each primary tumour volume and then filtered through stability analysis and clustering. First, a baseline signature was developed from demographic and tumour-associated clinical parameters. This signature was then supplemented by CT imaging features. A final signature was derived using repeated 3-fold cross-validation on the discovery cohort. Performance in external validation was assessed by the concordance index (C-Index). Furthermore, calibration and patient stratification in groups with low and high risk for loco-regional recurrence were analysed. Results: For the clinical baseline signature, only the primary tumour volume was selected. The final signature combined the tumour volume with two independent radiomics features. It achieved moderately good discriminatory performance (C-Index [95% confidence interval]: 0.66 [0.55-0.75]) on the validation cohort along with significant patient stratification (p=0.005) and good calibration. Conclusion: We identified and validated a clinical-radiomics signature for LRC of locally advanced HNSCC using a multi-centric retrospective dataset. Prospective validation will be performed on the primary cohort of the HNprädBio trial of the DKTK-ROG once follow-up is completed.

Identifying patients with locally advanced head and neck carcinoma on high risk of recurrence after definitive concurrent radiochemotherapy is of key importance for the selection for consolidation therapy and for individualized treatment intensification. In this multicenter study we analyzed recurrence-associated single-nucleotide polymorphisms (SNPs) in DNA repair genes in tumor DNA from 132 patients with locally advanced head and neck carcinoma (LadHnSCC). Patients were treated with definitive radiotherapy and simultaneous cisplatin-based chemotherapy at six partner sites of the German Cancer Consortium (DKTK) Radiation Oncology Group from 2005 to 2011. For validation, a group of 20 patients was available. Score selection method using proportional hazard analysis and leave-one-out cross-validation were performed to identify markers associated with outcome. The SNPs rs1799793 and rs13181 were associated with survival and the same SNPs and in addition rs17655 with freedom from loco-regional relapse (ffLRR) in the trainings datasets from all patients. The homozygote major rs1799793 genotype at the ERCC2 gene was associated with better (Hazard ratio (HR): 0.418 (0.234-0.744), p = 0.003) and the homozygote minor rs13181 genotype at ERCC2 with worse survival (HR: 2.074, 95% CI (1.177-3.658), p = 0.017) in comparison to the other genotypes. At the ffLRR endpoint, rs1799793 and rs13181 had comparable prognostic value. The rs1799793 and rs13181 genotypes passed the leave-one-out cross-validation procedure and associated with survival and ffLRR in patients with LadHnSCC treated with definitive radiochemotherapy. While findings were confirmed in a small validation dataset, further validation is underway within a prospective biomarker study of the DKTK.

The original version of this Article contained an error in the spelling of the author Eleni Gkika, which was incorrectly given as Eleni Gikka. As well as the author Stephanie E. Combs, this was incorrectly given as Stephanie Combs. Both have now been corrected in the PDF and HTML versions of the Article.

This comprehensive review written by experts in their field gives an overview on the current status of incorporating positron emission tomography (PET) into radiation treatment planning. Moreover, it highlights ongoing studies for treatment individualisation and per-treatment tumour response monitoring for various primary tumours. Novel tracers and image analysis methods are discussed. The authors believe this contribution to be of crucial value for experts in the field as well as for policy makers deciding on the reimbursement of this powerful imaging modality.

Introduction Within the hyperthermia community, consensus exists that clinical outcome of the treatment radiotherapy and/or chemotherapy plus hyperthermia (i.e. elevating tumor temperature to 40 − 44 °C) is related to the applied thermal dose; hence, treatment quality is crucial for the success of prospective multi-institution clinical trials. Currently, applicator quality assurance (QA) measurements are implemented independently at each institution using basic cylindrical phantoms. A multi-institution comparison of heating quality using magnetic resonance thermometry (MRT) and anatomical representative anthropomorphic phantoms provides a unique opportunity to obtain novel QA insights to fa

This article compares the expression and applicability of biomarkers, from single genes and gene signatures, identified in patients with locally advanced head and neck squamous cell carcinoma using the GeneChip Human Transcriptome Array 2.0, nCounter, and real-time PCR analyses. Two multicenter, retrospective cohorts of patients with head and neck squamous cell carcinoma from the German Cancer Consortium Radiation Oncology Group who received postoperative radiochemotherapy or primary radiochemotherapy were considered. Real-time PCR was performed for a limited number of 38 genes of the cohort who received postoperative radiochemotherapy only. Correlations between the methods were evaluated by the Spearman rank correlation coefficient. Patients were stratified based on the expression of putative cancer stem cell markers, hypoxia-associated gene signatures, and a previously developed seven-gene signature. Locoregional tumor control was compared between these patient subgroups using log-rank tests. Gene expressions obtained from nCounter analyses were moderately correlated to GeneChip analyses (median r Z approximately 0.68). A higher correlation was obtained between nCounter analyses and real-time PCR (median r Z 0.84). Significant associations with locoregional tumor control were observed for most of the considered biomarkers evaluated by GeneChip and nCounter analyses. In general, all applied biomarkers (single genes and gene signatures) classified approximately 70% to 85% of the patients similarly. Overall, gene signatures seem to be more robust and had a better transferability among different measurement methods.

Radiomics aims to characterise the tumour phenotype using advanced image features to predict patient-specific outcome. ...

For treatment individualisation of patients with locally advanced head and neck squamous cell carcinoma (HNSCC) treated with primary radiochemotherapy, we explored the capabilities of different deep learning approaches for predicting loco-regional tumour control (LRC) from treatment-planning computed tomography images. Based on multicentre cohorts for exploration (206 patients) and testing (85 patients), multiple deep learning approaches including extraction of deep features, transfer learning and complete training from scratch with 2D and 3D convolutional layers were assessed and compared to a clinical model including the tumour volume. Analyses were based on Cox proportional hazards regression and performance was assessed by the concordance index (C-index). While all 2D approaches showed similar or worse performance than the clinical model on the test cohort (C-index 0.39), 3D convolutional neural networks achieved improved discrimination (C-index 0.31) and patient stratification into high and low risk groups of tumour recurrence (p=0.001), in particular when using model ensembles instead of single models. Prospective validation of this result is planned.