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Patients with locally advanced head and neck squamous cell carcinoma (HNSCC) may benefit from personalised treatment, requiring biomarkers that characterize the tumour and predict treatment response. We integrate pre-treatment CT radiomics and whole-transcriptome data from a multicentre retrospective cohort of 206 patients with locally advanced HNSCC treated with primary radiochemotherapy to classify tumour molecular subtypes based on radiomics, develop surrogate radiomics signatures for gene-based signatures related to different biological tumour characteristics and evaluate the potential of combining radiomics features with full-transcriptome data for the prediction of loco-regional control (LRC). Using end-to-end machine-learning, we developed and validated a model to classify tumours of the atypical subtype (AUC [95% confidence interval]: 0.69 [0.53-0.83]) based on CT imaging, observed that CT-based radiomics models have limited value as surrogates for six selected gene signatures (AUC<0.60), and showed that combining a radiomics signature with a transcriptomics signature consisting of two metagenes representing the hedgehog pathway and E2F transcriptional targets improves the prognostic value for LRC compared to both individual sources (validation C-index [95% confidence interval], combined: 0.63 [0.55-0.73] vs radiomics: 0.60 [0.50-0.71] and transcriptomics: 0.59 [0.49-0.69]). These results underline the potential of multi-omics analyses to generate reliable biomarkers for future application in personalized oncology.

(1) Background: Patients with locally advanced head and neck squamous cell carcinoma (HNSCC) who are at biologically high risk for the development of loco-regional recurrences af-ter postoperative radiotherapy (PORT) but at intermediate risk according to clinical risk factors may benefit from additional concurrent chemotherapy. In this matched-pair study, we aimed to identify a corresponding predictive gene signature. (2) Methods: Gene expression analysis was performed on a multicentre retrospective cohort of 221 patients that were treated with postoper-ative radiochemotherapy (PORT-C) and 283 patients that were treated with PORT alone. Propen-sity score analysis was used to identify matched patient pairs from both cohorts. From differen-tial gene expression analysis and Cox regression, a predictive gene signature was identified. (3) Results: 108 patient matched patient pairs were selected. We identified a 2-metagene signature that stratified patients into risk groups in both cohorts. The comparison of the high-risk patients between the two types of treatment showed higher LRC after treatment with PORT-C (p<0.001), which was confirmed by a significant interaction term in Cox regression (p=0.027), i.e. the 2-metagene signature was indicative for the type of treatment. (4) Conclusion: We have identi-fied a novel gene signature that may be helpful to identify patients with high-risk HNSCC amongst those at intermediate clinical risk treated with PORT, who may benefit from additional concurrent chemotherapy.

Dendritic cells (DCs) play a key role in the orchestration of antitumor immunity. Activated DCs efficiently enhance antitumor effects mediated by natural killer cells and T lymphocytes. Conversely, tolerogenic DCs essentially contribute to an immunosuppressive tumor microenvironment. Thus, DCs can profoundly influence tumor progression and clinical outcome of tumor patients. To gain novel insights into the role of human DCs in pancreatic ductal adenocarcinoma (PDAC), we explored the frequency, spatial organization, and clinical significance of conventional DCs type 1 (cDC1s) and type 2 (cDC2s) and plasmacytoid DCs (pDCs) in primary PDAC tissues. A higher density of whole tumor area (WTA)- and tumor stroma (TS)-infiltrating cDC1s was significantly associated with better disease-free survival (DFS). In addition, an increased frequency of intraepithelial tumor-infiltrating cDC2s was linked to better DFS and overall survival (OS). Furthermore, an increased density of WTA- and TS-infiltrating pDCs tended to improve DFS. Moreover, a higher frequency of WTA- and TS-infiltrating cDC1s and pDCs emerged as an independent prognostic factor for better DFS and OS. These findings indicate that tumor-infiltrating DCs can significantly influence the clinical outcome of PDAC patients and may contribute to the design of novel treatment options that target PDAC-infiltrating DCs.

Purpose To assess the relation of the previously reported classification of molecular subtypes to the outcome of patients with HNSCC treated with postoperative radio(chemo)therapy (PORT-C), and to assess the association of these subtypes with gene expressions reflecting known mechanisms of radioresistance. Material and methods Gene expression analyses were performed using the GeneChip Human Transcriptome Array 2.0 on a multicentre retrospective patient cohort (N = 128) of the German Cancer Consortium Radiation Oncology Group (DKTK-ROG) with locally advanced HNSCC treated with PORT-C. Tumours were assigned to four molecular subtypes, and correlation analyses between subtypes and clinical risk factors were performed. In addition, the classifications of eight genes or gene signatures related to mechanisms of radioresistance, which have previously shown an association with outcome of patients with HNSCC, were compared between the molecular subtypes. The endpoints loco-regional control (LRC) and overall survival (OS) were evaluated by log-rank tests and Cox regression. Results Tumours were classified into the four subtypes basal (19.5%), mesenchymal (18.8%), atypical (15.6%) and classical (14.1%). The remaining tumours could not be classified (32.0%). Tumours of the mesenchymal subtype showed a lower LRC compared to the other subtypes (p = 0.012). These tumours were associated with increased epithelial-mesenchymal transition (EMT) and overexpression of a gene signature enriched in DNA repair genes. The majority of the eight considered gene classifiers were significantly associated to LRC or OS in the whole cohort. Conclusion Molecular subtypes, previously identified on HNSCC patients treated with primary radio(chemo)therapy or surgery, were related to LRC for patients treated with PORT-C, where mesenchymal tumours presented with worse prognosis. After prospective validation, subtype-based patient stratification, potentially in combination with other molecular classifiers

Purpose: To develop prognostic biomarker signatures for patients with locally advanced head and neck squamous cell carcinoma (HNSCC) treated by primary radiochemotherapy (RCTx) based on previously published molecular analyses of the retrospective biomarker study of the German Cancer Consortium – Radiation Oncology Group (DKTK-ROG).

Purpose: The aim of this study was to develop and validate a novel gene signature from full-transcriptome data using machine-learning approaches to predict loco-regional control (LRC) of patients with human papilloma virus (HPV)-negative locally advanced head and neck squamous cell carcinoma (HNSCC), who received postoperative radio(chemo)therapy (PORT-C). Materials and methods: Gene expression analysis was performed using Affymetrix GeneChip Human Transcriptome Array 2.0 on a multicentre retrospective training cohort of 128 patients and an independent validation cohort of 114 patients from the German Cancer Consortium - Radiation Oncology Group (DKTK-ROG). Genes were filtered based on differential gene expression analyses and Cox regression. The identified gene signature was combined with clinical parameters and with previously identified genes related to stem cells and hypoxia. Technical validation was performed using nanoString technology. Results: We identified a 6-gene signature consisting of four individual genes CAV1, GPX8, IGLV3-25, TGFBI, and one metagene combining the highly correlated genes INHBA and SERPINE1. This signature was prognostic for LRC on the training data (ci = 0.84) and in validation (ci = 0.63) with a significant patient stratification into two risk groups (p = 0.005). Combining the 6-gene signature with the clinical parameters T stage and tumour localisation as well as the cancer stem cell marker CD44 and the 15-gene hypoxia-associated signature improved the validation performance (ci = 0.69, p = 0.001). Conclusion: We have developed and validated a novel prognostic 6-gene signature for LRC of HNSCC patients with HPV-negative tumours treated by PORT-C. After successful prospective validation the signature can be part of clinical trials on the individualization of radiotherapy.

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