Search

Ziel/Aim The aim of the study was an independent evaluation of the prognostic value of a gene expression signature (EPPI) and the PET-derived tumor asphericity (ASP) in non-small cell lung cancer (NSCLC) patients. Methodik/Methods This was a retrospective evaluation of PET imaging and gene expression data from three public databases and two institutional datasets. Altogether 253 NSCLC patients were included, all treated with curative intent surgery. Clinical parameters, standard PET parameters and ASP were evaluated in all patients. Additional gene expression data was available for 120 patients. Univariate and multivariate Cox regression and Kaplan-Meier analysis were calculated for the primary endpoint progression-free survival (PFS) and additional endpoints. Ergebnisse/Results In the whole cohort a significant association with PFS was observed for ASP (p<0.001) and EPPI (p=0.012). On multivariate testing, EPPI remained significantly associated with PFS (p=0.018) in the subgroup of patients with additional gene expression data, while ASP was significantly associated with PFS in the whole cohort (p=0.012). In stage II patients, ASP was significantly associated with PFS (p=0.009) and a previously published cutoff value for ASP (19.5%) was successfully validated (p=0.008). In patients with additional gene expression data, EPPI showed a significant association with PFS, too (p=0.033). Exploratory combination of ASP and EPPI showed that the combinatory approach has potential to further improve patient stratification compared to the use of only one parameter. Schlussfolgerungen/Conclusions The combination of EPPI and ASP seems to be a very promising approach for improvement of risk stratification in a group of patients with urgent need for a more personalized treatment approach.

Background Tumor hypoxia is associated with resistance to radiotherapy and chemotherapy. In head and neck squamous cell carcinoma (HNSCC), nimorazole, an oxygen mimic, combined with radiotherapy (RT) enabled to improve loco-regional control (LRC) in some patients with hypoxic tumors but it is unknown whether this holds also for radio- chemotherapy (RCTx). Here, we investigated the impact of nimorazole combined with RCTx in HNSCC xenografts and explored molecular biomarkers for its targeted use. Methods Irradiations were performed with 30 fractions in 6 weeks combined with weekly cisplatin. Nimorazole was applied before each fraction, beginning with the first or after ten fractions. Effect of RCTx with or without addition of nimorazole was quantified as permanent local control after irradiation. For histological evaluation and targeted gene expression analysis, tumors were excised untreated or after ten fractions. Using quantitative image analysis, micromilieu parameters were determined. Results Nimorazole combined with RCTx significantly improved permanent local control in two tumor models, and showed a potential improvement in two additional models. In these four models, pimonidazole hypoxic volume (pHV) was significantly reduced after ten fractions of RCTx alone. Our results suggest that nimorazole combined with RCTx might improve TCR compared to RCTx alone if hypoxia is decreased during the course of RCTx but further experiments are warranted to verify this association. Differential gene expression analysis revealed 12 genes as potential for RCTx response. When evaluated in patients with HNSCC who were treated with primary RCTx, these genes were predictive for LRC. Conclusions Nimorazole combined with RCTx improved local tumor control in some but not in all HNSCC xeno-grafts. We identified prognostic biomarkers with the potential for translation to patients with HNSCC.

Purpose: Tumor hypoxia is a paradigmatic negative prognosticator of treatment resistance in head and neck squamous cell carcinoma (HNSCC). The lack of robust and reliable hypoxia classifiers limits the adaptation of stratified therapies. We hypothesized that the tumor DNA methylation landscape might indicate epigenetic reprogramming induced by chronic intratumoral hypoxia. Experimental Design: A DNA-methylome–based tumor hypoxia classifier (Hypoxia-M) was trained in the TCGA (The Cancer Genome Atlas)-HNSCC cohort based on matched assignments using gene expression–based signatures of hypoxia (Hypoxia-GES). Hypoxia-M was validated in a multicenter DKTK-ROG trial consisting of human papillomavirus (HPV)–negative patients with HNSCC treated with primary radiochemotherapy (RCHT). Results: Although hypoxia-GES failed to stratify patients in the DKTK-ROG, Hypoxia-M was independently prognostic for local recurrence (HR, 4.3; P ¼0.001) and overall survival (HR, 2.34; P ¼ 0.03) but not distant metastasis after RCHT in both cohorts. Hypoxia-M status was inversely associated with CD8 T-cell infiltration in both cohorts. Hypoxia-M was further prognostic in the TCGA-PanCancer cohort (HR, 1.83; P ¼0.04), underscoring the breadth of this classifier for predicting tumor hypoxia status. Conclusions: Our findings highlight an unexplored avenue for DNA methylation–based classifiers as biomarkers of tumoral hypoxia for identifying high-risk features in patients with HNSCC tumors.

Neural-network-based outcome predictions may enable further treatment personalization of patients with head and neck cancer. The development of neural networks can prove challenging when a limited number of cases is available. Therefore, we investigated whether multitask learning strategies, implemented through the simultaneous optimization of two distinct outcome objectives (multi-outcome) and combined with a tumor segmentation task, can lead to improved performance of convolutional neural networks (CNN) and vision transformers (ViT). Model training was conducted on two distinct multicenter datasets for the endpoints loco-regional control (LRC) and progression-free survival (PFS), respectively. The first dataset consisted of pre-treatment computed tomography (CT) imaging for 290 patients and the second dataset contained combined positron emission tomography (PET)/CT for 224 patients. Discriminative performance was assessed by the concordance index (C-index). Risk stratification was evaluated using log-rank tests. Across both datasets, CNN and ViT model ensembles achieved similar results. Multitask approaches showed favorable performance in most investigations. Multi-outcome CNN models trained with segmentation loss were identified as the optimal strategy across cohorts. On the PET/CT dataset, an ensemble of multi-outcome CNNs trained with segmentation loss achieved the best discrimination (C-index: 0.29, 95% confidence interval (CI): 0.22-0.36) and successfully stratified patients into groups with low and high risk of disease progression (p=0.003). On the CT dataset, ensembles of multi-outcome CNNs and of single-outcome ViTs trained with segmentation loss performed best (C-index: 0.26 and 0.26, CI: 0.18-0.34 and 0.18-0.35, respectively), both with significant risk stratification for LRC in independent validation (p=0.002 and p=0.011). Further validation of the developed multitask-learning models is planned based on a prospective validation study, which is currently

The aim of this retrospective multicenter study was an independent validation of a gene expression signature ECM-related prognostic and predictive indicator (EPPI) and the novel positron emission tomography (PET) parameter tumor asphericity (ASP) in non-small cell lung cancer (NSCLC) patients. The whole cohort comprised 253 NSCLC patients, all treated with surgery. Clinical and PET parameters were available for all patients, additional gene expression data for 120 patients. Univariate and multivariate Cox regression and Kaplan-Meier analyses were calculated for progression-free survival (PFS). A significant association with PFS was observed for ASP (p < 0.001) and EPPI (p = 0.012). Upon multivariate testing, ASP was significantly associated with PFS (p = 0.012), and EPPI (p = 0.018) in patients with additional gene data. In stage II patients, ASP was significantly associated with PFS (p = 0.009) and a previously published cutoff value for ASP (19.5%) was successfully validated (p = 0.008). EPPI showed a significant association with PFS in stage II patients, too (p = 0.033). Exploratory combination of ASP and EPPI showed potentially improved stratification. We report the first successful validation of EPPI and ASP in stage II NSCLC patients, combination of both parameters seems encouraging.

This dataset contains the model checkpoints, predictions and performance metrics for the multitask neural networks presented in the corresponding manuscript.

The new Medical Licensing Regulations 2025 (Ärztliche Approbationsordnung, ÄApprO) will soon be passed by the Federal Council (Bundesrat) and will be implemented step by step by the individual faculties in the coming months. The further development of medical studies essentially involves an orientation from fact-based to competence-based learning and focuses on practical, longitudinal and interdisciplinary training. Radiation oncology and radiation therapy are important components of therapeutic oncology and are of great importance for public health, both clinically and epidemiologically, and therefore should be given appropriate attention in medical education. This report is based on a recent survey on the current state of radiation therapy teaching at university hospitals in Germany as well as the contents of the National Competence Based Learning Objectives Catalogue for Medicine 2.0 (Nationaler Kompetenzbasierter Lernzielkatalog Medizin 2.0, NKLM) and the closely related Subject Catalogue (Gegenstandskatalog, GK) of the Institute for Medical and Pharmaceutical Examination Questions (Institut für Medizinische und Pharmazeutische Prüfungsfragen, IMPP). The current recommendations of the German Society for Radiation Oncology (Deutsche Gesellschaft für Radioonkologie, DEGRO) regarding topics, scope and rationale for the establishment of radiation oncology teaching at the respective faculties are also included.

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.

Correction to: Strahlenther Onkol 2021 https://doi.org/10.1007/s00066-021-01812-2

Human papillomavirus (HPV)-driven head and neck squamous cell carcinomas (HNSCC) generally have a more favourable prognosis. We hypothesized that HPV-associated HNSCC may be identified by an miRNA-signature according to their specific molecular pathogenesis, and be characterized by a unique transcriptome compared to HPV-negative HNSCC. We performed miRNA expression profiling of two p16/HPV DNA characterized HNSCC cohorts of patients treated by adjuvant radio(chemo)therapy (multicentre DKTK-ROG n = 128, single-centre LMU-KKG n = 101). A linear model predicting HPV status built in DKTK-ROG using lasso-regression was tested in LMU-KKG. LMU-KKG tumours (n = 30) were transcriptome profiled for differential gene expression and miRNA-integration. A 24-miRNA signature predicted HPV-status with 94.53% accuracy (AUC: 0.99) in DKTK-ROG, and 86.14% (AUC: 0.86) in LMU-KKG. The prognostic values of 24-miRNA- and p16/HPV DNA status were comparable. Combining p16/HPV DNA and 24-miRNA status allowed patient sub-stratification and identification of an HPV-associated patient subgroup with impaired overall survival. HPV-positive tumours showed downregulated MAPK, Estrogen, EGFR, TGFbeta, WNT signaling activity. miRNA-mRNA integration revealed HPV-specific signaling pathway regulation, including PD−L1 expression/PD−1 checkpoint pathway in cancer in HPV-associated HNSCC. Integration of clinically established p16/HPV DNA with 24-miRNA signature status improved clinically relevant risk stratification, which might be considered for future clinical decision-making with respect to treatment de-escalation in HPV-associated HNSCC.

(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.

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.

Background: Local ablative radiotherapy (aRT) of oligometastatic prostate cancer (PCa) is very promising and has become a focus of current clinical research. Objective: We hypothesize that aRT is safe and effective in gallium-68 prostate-specific membrane antigen targeted positron emission tomography (PSMA-PET)-staged oligometastatic PCa patients. Design, setting, and participants: A nonrandomized, prospective, investigator-initiated phase 2 trial recruited patients with oligometastatic PCa (five or fewer lymph node or osseous metastases) after local curative therapy, without significant comorbidity and androgen deprivation therapy (ADT), at two German centers from 2014 to 2018. Intervention: All PSMA-PET-positive metastases were treated with aRT. No systemic therapy was initiated. Outcome measurements and statistical analysis: The primary endpoint was treatment-related toxicity (grade ≥2) 24 mo after aRT. A one-sided single-sample test of proportions was planned to test whether the endpoint occurs in <15% of the patients. Key secondary endpoints were time to progression of prostate-specific antigen (PSA) and time to ADT, which were associated with potential prognostic factors by Cox regression. Results and limitations: Of 72 patients, 63 received aRT (13% dropout rate). The median follow-up was 37.2 mo. No treatment-related grade ≥2 toxicity was observed 2 yr after treatment. The median time to PSA progression and time to ADT were 13.2 and 20.6 mo, respectively. Of the patients, 21.4% were free of PSA progression after 3 yr. Conclusions: It was observed that aRT is safe, and midterm PSA progression and ADT-free time were achieved in one of five patients. Randomized clinical trials are indicated to further evaluate the option of delaying ADT in selected patients. Patient summary: In this clinical trial, 63 patients with up to five metastases of prostate cancer without androgen deprivation therapy were included. We showed that local ablative radiotherapy is safe and

Progression of prostate-specific antigen (PSA) values after curative treatment of prostate cancer patients is common. Prostate-specific membrane antigen (PSMA-) PET imaging can identify patients with metachronous oligometastatic disease even at low PSA levels. Metastases-directed local ablative radiotherapy (aRT) has been shown to be a safe treatment option. In this prospective clinical trial, we evaluated local control and the pattern of tumor progression. Between 2014 and 2018, 63 patients received aRT of 89 metastases (MET) (68 lymph node (LN-)MET and 21 bony (OSS-)MET) with one of two radiation treatment schedules: 50 Gy in 2 Gy fractions in 34 MET or 30 Gy in 10 Gy fractions in 55 MET. The mean gross tumor volume and planning target volume were 2.2 and 14.9 mL, respectively. The median follow-up time was 40.7 months. Local progression occurred in seven MET, resulting in a local control rate of 93.5% after three years. Neither treatment schedule, target volume, nor type of lesion was associated with local progression. Regional progression in the proximity to the LN-MET was observed in 19 of 47 patients with at least one LN-MET (actuarial 59.3% free of regional progression after 3 years). In 33 patients (52%), a distant progression was reported. The median time to first tumor-related clinical event was 16.6 months, and 22.2% of patients had no tumor-related clinical event after three years. A total of 14 patients (22%) had another aRT. In conclusion, local ablative radiotherapy in patients with PSMA-PET staged oligometastatic prostate cancer may achieve local control, but regional or distant progression is common. Further studies are warranted, e.g., to define the optimal target volume coverage in LN-MET and OSS-MET.

Purpose 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) is utilized for staging and treatment planning of head and neck squamous cell carcinomas (HNSCC). Some older publications on the prognostic relevance showed inconclusive results, most probably due to small study sizes. This study evaluates the prognostic and potentially predictive value of FDG-PET in a large multi-center analysis. Methods Original analysis of individual FDG-PET and patient data from 16 international centers (8 institutional datasets, 8 public repositories) with 1104 patients. All patients received curative intent radiotherapy/chemoradiation (CRT) and pre-treatment FDG-PET imaging. Primary tumors were semi-automatically delineated for calculation of SUVmax, SUVmean, metabolic tumor volume (MTV) and total lesion glycolysis (TLG). Cox regression analyses were performed for event-free survival (EFS), overall survival (OS), loco-regional control (LRC) and freedom from distant metastases (FFDM). Results FDG-PET parameters were associated with patient outcome in the whole cohort regarding clinical endpoints (EFS, OS, LRC, FFDM), in uni- and multivariate Cox regression analyses. Several previously published cut-off values were successfully validated. Subgroup analyses identified tumor- and human papillomavirus (HPV) specific parameters. In HPV positive oropharynx cancer (OPC) SUVmax was well suited to identify patients with excellent LRC for organ preservation. Patients with SUVmax of 14 or less were unlikely to develop loco-regional recurrence after definitive CRT. In contrast FDG PET parameters deliver only limited prognostic information in laryngeal cancer. Conclusion FDG-PET parameters bear considerable prognostic value in HNSCC and potential predictive value in subgroups of patients, especially regarding treatment de-intensification and organ-preservation. The potential predictive value needs further validation in appropriate control groups. Further research on advanced imaging appro

Background and purpose: Prognosis after chemoradiotherapy (CRT) for anal squamous cell carcinoma (ASCC) shows marked differences among patients according to TNM subgroups, however individualized risk assessment tools to better stratify patients for treatment (de-) escalation or intensified follow-up are lacking in ASCC. Materials and methods: Patients’ data from eight sites of the German Cancer Consortium - Radiation Oncology Group (DKTK-ROG), comprising a total of 605 patients with ASCC, treated with standard defini- tive CRT with 5-FU/Mitomycin C or Capecitabine/Mitomycin C between 2004–2018, were used to evalu- ate prognostic factors based on Cox regression models for disease-free survival (DFS). Evaluated variables included age, gender, Karnofsky performance score (KPS), HIV-status, T-category, lymph node status and laboratory parameters. Multivariate cox models were separately constructed for the whole cohort and the subset of patients with early-stage (cT1-2 N0M0) tumors. Results: After a median follow-up of 46 months, 3-year DFS for patients with early-stage ASCC was 84.9%, and 67.1% for patients with locally-advanced disease (HR 2.4, p < 0.001). T-category (HR vs. T1: T2 2.02; T3 2.11; T4 3.03), N-category (HR versus N0: 1.8 for N1-3), age (HR 1.02 per year), and KPS (HR 0.8 per step) were significant predictors for DFS in multivariate analysis in the entire cohort. The model per- formed with a C-index of 0.68. In cT1-2N0 patients, T-category (HR 2.14), HIV status (HR 2.57), age (1.026 per year), KPS (HR 0.7 per step) and elevated platelets (HR 1.3 per 100/nl) were associated with worse DFS (C-index of 0.7). Conclusion: Classical clinicopathologic parameters like T-category, N-category, age and KPS remain to be significant prognostic factors for DFS in patients treated with contemporary CRT for ASCC. HIV and plate- lets were significantly associated with worse DFS in patients with early stage ASCC.

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