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| Status |
Public on Jun 01, 2023 |
| Title |
Molecular subtypes of head and neck cancer – Prognostic impact and correlations with morphological characteristics |
| Organism |
Homo sapiens |
| Experiment type |
Expression profiling by array
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| Summary |
Aim Treatment options for patients with recurrent or metastatic head and neck squamous cell carcinoma (R/M-HNSCC) are limited. Therefore, prognostic and predictive biomarkers for the application of personalized therapies are urgently needed.
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| Overall design |
To this end, we designed, applied and evaluated a NanoString gene panel which revealed the subtype in R/M-HNSCC in order to identify potential treatment-relevant conditions and correlations with histomorphological characteristics. Material and Methods 130 formalin-fixed, paraffin-embedded samples from 95 treated CeFCiD trial patients with R/M-HNSCC were sequenced and analyzed. A customized NanoString panel composed of 231 genes was utilized to determine molecular subtypes and gene expression levels of potential predictive genes. For 67 patients, clinical data and H&E stained slides were available for additional comprehensive histomorphological analyses (e.g., histotype, grading, tumor cell budding (TCB), nuclear size, stroma content). Results 114 out of 130 (88%) samples passed quality control and we could successfully determine their molecular subtype in 103 of 114 (90%) cases. Gene expression levels of AREG were significantly higher for the basal and classical subtype compared to the mesenchymal subtype. Cases assigned to the classical subtype showed superior progression-free and overall survival rates compared to non-classical subtypes. Additionally, among histomorphological parameters high TCB was associated with poor outcomes. Conclusion The highly compact NanoString panel was able to determine the molecular subtype of R/M-HNSCC. The implications of molecular subtypes on prognosis and therapy prediction might aid in treatment planning of R/M-HNSCC patients. The prognostic significance of the histomorphological parameters TCB could be confirmed.
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| Contributor(s) |
Stögebauer F, Otto R, Jöhrens K, Tinhofer-Keilholz I, Keilholz U, Keller U, Leser U, Wichert W, Boxberg M, Klinghammer K |
| Citation missing |
Has this study been published? Please login to update or notify GEO. |
| Submission date |
Aug 25, 2022 |
| Last update date |
Jun 03, 2023 |
| Contact name |
Raik Otto |
| E-mail(s) |
fubioinf@googlemail.com
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| Organization name |
Humboldt-Universität zu Berlin
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| Department |
Computer Sciences
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| Lab |
AG Leser
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| Street address |
Rudower Chaussee 25
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| City |
Berlin |
| State/province |
Berlin |
| ZIP/Postal code |
12489 |
| Country |
Germany |
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| Platforms (1) |
| GPL32599 |
Nanostring nCounter HSNCC Custom Panel |
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| Samples (103)
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| Relations |
| BioProject |
PRJNA873742 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE212070_RAW.tar |
390.0 Kb |
(http)(custom) |
TAR (of RCC) |
| Processed data included within Sample table |
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