Development and validation of a 6-gene signature for the prognosis of loco-regional control in patients with HPV-negative locally advanced HNSCC treated by postoperative radio(chemo)therapy. (June 2022)
- Record Type:
- Journal Article
- Title:
- Development and validation of a 6-gene signature for the prognosis of loco-regional control in patients with HPV-negative locally advanced HNSCC treated by postoperative radio(chemo)therapy. (June 2022)
- Main Title:
- Development and validation of a 6-gene signature for the prognosis of loco-regional control in patients with HPV-negative locally advanced HNSCC treated by postoperative radio(chemo)therapy
- Authors:
- Patil, Shivaprasad
Linge, Annett
Grosser, Marianne
Lohaus, Fabian
Gudziol, Volker
Kemper, Max
Nowak, Alexander
Haim, Dominik
Tinhofer, Inge
Budach, Volker
Guberina, Maja
Stuschke, Martin
Balermpas, Panagiotis
Rödel, Claus
Schäfer, Henning
Grosu, Anca-Ligia
Abdollahi, Amir
Debus, Jürgen
Ganswindt, Ute
Belka, Claus
Pigorsch, Steffi
Combs, Stephanie E.
Boeke, Simon
Zips, Daniel
Baretton, Gustavo B.
Baumann, Michael
Krause, Mechthild
Löck, Steffen - Abstract:
- Highlights: A novel 6-gene signature was developed based on full-transcriptome data for LRC prognosis in patients with HPV-negative HNSCC treated with PORT-C. The prognostic performance was improved by adding relevant clinical parameters, CD44 expression, and the 15-gene hypoxia classifier. The developed models were validated on an independent patient cohort. Successful technical validation was performed by nanoString technology. Abstract: 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,Highlights: A novel 6-gene signature was developed based on full-transcriptome data for LRC prognosis in patients with HPV-negative HNSCC treated with PORT-C. The prognostic performance was improved by adding relevant clinical parameters, CD44 expression, and the 15-gene hypoxia classifier. The developed models were validated on an independent patient cohort. Successful technical validation was performed by nanoString technology. Abstract: 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. … (more)
- Is Part Of:
- Radiotherapy and oncology. Volume 171(2022)
- Journal:
- Radiotherapy and oncology
- Issue:
- Volume 171(2022)
- Issue Display:
- Volume 171, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 171
- Issue:
- 2022
- Issue Sort Value:
- 2022-0171-2022-0000
- Page Start:
- 91
- Page End:
- 100
- Publication Date:
- 2022-06
- Subjects:
- Head and neck squamous cell carcinoma -- Gene signature -- Postoperative radiotherapy -- Hypoxia -- Cancer stem cells -- Machine learning
Oncology -- Periodicals
Radiotherapy -- Periodicals
Tumors -- Periodicals
Medical Oncology -- Periodicals
Neoplasms -- radiotherapy -- Periodicals
Radiotherapy -- Periodicals
Radiothérapie -- Périodiques
Cancérologie -- Périodiques
Tumeurs -- Périodiques
Electronic journals
616.9940642 - Journal URLs:
- http://www.sciencedirect.com/science/journal/01678140 ↗
http://www.clinicalkey.com/dura/browse/journalIssue/01678140 ↗
http://www.clinicalkey.com.au/dura/browse/journalIssue/01678140 ↗
http://www.estro.org/ ↗
http://www.elsevier.com/journals ↗
http://www.journals.elsevier.com/radiotherapy-and-oncology/ ↗ - DOI:
- 10.1016/j.radonc.2022.04.006 ↗
- Languages:
- English
- ISSNs:
- 0167-8140
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