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Radiogenomic markers enable risk stratification and inference of mutational pathway states in head and neck cancer

European Journal of Nuclear Medicine and Molecular Imaging, ISSN: 1619-7089, Vol: 50, Issue: 2, Page: 546-558
2023
  • 13
    Citations
  • 0
    Usage
  • 37
    Captures
  • 1
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    13
  • Captures
    37
  • Mentions
    1
    • News Mentions
      1
      • 1

Most Recent News

Head and neck cancer: Identifying markers to facilitate better treatment in the future

Malignant tumors in the head and neck region are very heterogeneous and therefore difficult to treat. In addition, the lack of prognostic markers is a significant impediment to personalized treatment. A joint study by MedUni Vienna and the Christian Doppler Laboratory for Applied Metabolomics focused on the development and identification of specific markers to improve risk assessment for patients.

Article Description

Purpose: Head and neck squamous cell carcinomas (HNSCCs) are a molecularly, histologically, and clinically heterogeneous set of tumors originating from the mucosal epithelium of the oral cavity, pharynx, and larynx. This heterogeneous nature of HNSCC is one of the main contributing factors to the lack of prognostic markers for personalized treatment. The aim of this study was to develop and identify multi-omics markers capable of improved risk stratification in this highly heterogeneous patient population. Methods: In this retrospective study, we approached this issue by establishing radiogenomics markers to identify high-risk individuals in a cohort of 127 HNSCC patients. Hybrid in vivo imaging and whole-exome sequencing were employed to identify quantitative imaging markers as well as genetic markers on pathway-level prognostic in HNSCC. We investigated the deductibility of the prognostic genetic markers using anatomical and metabolic imaging using positron emission tomography combined with computed tomography. Moreover, we used statistical and machine learning modeling to investigate whether a multi-omics approach can be used to derive prognostic markers for HNSCC. Results: Radiogenomic analysis revealed a significant influence of genetic pathway alterations on imaging markers. A highly prognostic radiogenomic marker based on cellular senescence was identified. Furthermore, the radiogenomic biomarkers designed in this study vastly outperformed the prognostic value of markers derived from genetics and imaging alone. Conclusion: Using the identified markers, a clinically meaningful stratification of patients is possible, guiding the identification of high-risk patients and potentially aiding in the development of effective targeted therapies. Graphical abstract: [Figure not available: see fulltext.].

Bibliographic Details

Spielvogel, Clemens P; Stoiber, Stefan; Papp, Laszlo; Krajnc, Denis; Grahovac, Marko; Gurnhofer, Elisabeth; Trachtova, Karolina; Bystry, Vojtech; Leisser, Asha; Jank, Bernhard; Schnoell, Julia; Kadletz, Lorenz; Heiduschka, Gregor; Beyer, Thomas; Hacker, Marcus; Kenner, Lukas; Haug, Alexander R

Springer Science and Business Media LLC

Medicine

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