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| 024 | 7 | _ | |a 10.1016/j.jmoldx.2020.03.005 |2 doi |
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| 100 | 1 | _ | |a Schmidt, Stefan |0 P:(DE-HGF)0 |b 0 |
| 245 | _ | _ | |a Comparison of GeneChip, nCounter and real-time polymerase chain reaction based gene expressions predicting loco-regional tumour control after primary and postoperative radiochemotherapy in head and neck squamous cell carcinoma. |
| 260 | _ | _ | |a Amsterdam [u.a.] |c 2020 |b Elsevier |
| 336 | 7 | _ | |a article |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1595594607_30774 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
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| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 500 | _ | _ | |a 2020 Jun;22(6):801-810 |
| 520 | _ | _ | |a In this manuscript we compare the expression and applicability of biomarkers, from single genes and gene signatures, identified in patients with locally advanced head and neck squamous cell carcinoma (HNSCC) using the GeneChip Human Transcriptome Array 2.0, nCounter and real-time polymerase chain reaction (RT-PCR) analyses. Two multicentre retrospective HNSCC patient cohorts of the German Cancer Consortium Radiation Oncology Group (DKTK-ROG), who received postoperative radiochemotherapy (PORT-C) or primary radiochemotherapy (primary RCTx) were considered. RT-PCR was performed for a limited number of 38 genes of the PORT-C cohort only. Correlations between the methods were evaluated by the Spearman rank correlation coefficient ρ. Patients were stratified based on the expression of putative cancer stem cell markers, hypoxia-associated gene signatures and a previously developed 7-gene signature. Loco-regional tumour control (LRC) was compared between these patient subgroups using log-rank tests. Gene expressions obtained from nCounter analyses were moderately correlated to GeneChip analyses (median ρ≈0.68). A higher correlation was obtained between nCounter analyses and RT-PCR (median ρ=0.84). Significant associations to LRC were observed for most of the considered biomarkers evaluated by both GeneChip and nCounter analyses. In general, all applied biomarkers (single genes and gene signatures) classified about 70% to 85% of the patients similarly. Overall, gene signatures seem to be more robust and showed a better transferability between different measurement methods. |
| 536 | _ | _ | |a 315 - Imaging and radiooncology (POF3-315) |0 G:(DE-HGF)POF3-315 |c POF3-315 |f POF III |x 0 |
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| 700 | 1 | _ | |a Gudziol, Volker |b 4 |
| 700 | 1 | _ | |a Nowak, Alexander |b 5 |
| 700 | 1 | _ | |a Tinhofer, Ingeborg |0 P:(DE-HGF)0 |b 6 |
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| 700 | 1 | _ | |a Ganswindt, Ute |0 P:(DE-HGF)0 |b 16 |
| 700 | 1 | _ | |a Belka, Claus |0 P:(DE-HGF)0 |b 17 |
| 700 | 1 | _ | |a Pigorsch, Steffi |0 P:(DE-HGF)0 |b 18 |
| 700 | 1 | _ | |a Combs, Stephanie E |0 P:(DE-HGF)0 |b 19 |
| 700 | 1 | _ | |a Mönnich, David |0 P:(DE-He78)a71604d1adbf3bced939fcfcf2c7ff32 |b 20 |
| 700 | 1 | _ | |a Zips, Daniel |0 P:(DE-HGF)0 |b 21 |
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| 700 | 1 | _ | |a Buchholz, Frank |0 P:(DE-HGF)0 |b 23 |
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