Drug sensitivity prediction models reveal a link between DNA repair defects and poor prognosis in HNSCC
| Autor: | Martijn van der Heijden, Conchita Vens, Emily M. Ploeg, Harry Bartelink, Caroline V.M. Verhagen, Paul B. Essers, Michiel W. M. van den Brekel, C. René Leemans, Marcel Verheij, Reinout H. de Roest, R.H. Brakenhoff |
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| Přispěvatelé: | Maxillofacial Surgery (AMC), Graduate School, Otolaryngology / Head & Neck Surgery, CCA - Cancer biology and immunology, Radiation Oncology |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
0301 basic medicine
Cancer Research DNA Repair DNA damage DNA repair RAD51 Gene Expression Antineoplastic Agents Apoptosis Olaparib 03 medical and health sciences chemistry.chemical_compound 0302 clinical medicine SDG 3 - Good Health and Well-being Cell Line Tumor medicine Humans Gene Retrospective Studies Cisplatin business.industry Squamous Cell Carcinoma of Head and Neck Mitomycin C Chemoradiotherapy medicine.disease Prognosis Head and neck squamous-cell carcinoma Rad52 DNA Repair and Recombination Protein 030104 developmental biology Phenotype Oncology chemistry Head and Neck Neoplasms 030220 oncology & carcinogenesis Mutation Cancer research business medicine.drug DNA Damage Rare cancers Radboud Institute for Health Sciences [Radboudumc 9] |
| Zdroj: | Cancer Research, 79(21), 5597-5611. American Association for Cancer Research Inc. Essers, P B M, van der Heijden, M, Verhagen, C V M, Ploeg, E M, de Roest, R H, Leemans, C R, Brakenhoff, R H, van den Brekel, M W M, Bartelink, H, Verheij, M & Vens, C 2019, ' Drug sensitivity prediction models reveal a link between DNA repair defects and poor prognosis in HNSCC ', Cancer Research, vol. 79, no. 21, pp. 5597-5611 . https://doi.org/10.1158/0008-5472.CAN-18-3388 Essers, P B M, Van Der Heijden, M, Verhagen, C V M, Ploeg, E M, De Roest, R H, Leemans, C R, Brakenhoff, R H, Van Den Brekel, M W M, Bartelink, H, Verheij, M & Vens, C 2019, ' Drug sensitivity prediction models reveal a link between DNA repair defects and poor prognosis in HNSCC ', Cancer Research, vol. 79, no. 21, pp. 5597-5611 . https://doi.org/10.1158/0008-5472.CAN-18-3388 Cancer research, 79(21), 5597-5611. American Association for Cancer Research Inc. Cancer Research, 79, 21, pp. 5597-5611 Cancer Research, 79, 5597-5611 |
| ISSN: | 1538-7445 0008-5472 |
| DOI: | 10.1158/0008-5472.CAN-18-3388 |
| Popis: | Head and neck squamous cell carcinoma (HNSCC) is characterized by the frequent manifestation of DNA crosslink repair defects. We established novel expression-based DNA repair defect markers to determine the clinical impact of such repair defects. Using hypersensitivity to the DNA crosslinking agents, mitomycin C and olaparib, as proxies for functional DNA repair defects in a panel of 25 HNSCC cell lines, we applied machine learning to define gene expression models that predict repair defects. The expression profiles established predicted hypersensitivity to DNA-damaging agents and were associated with mutations in crosslink repair genes, as well as downregulation of DNA damage response and repair genes, in two independent datasets. The prognostic value of the repair defect prediction profiles was assessed in two retrospective cohorts with a total of 180 patients with advanced HPV-negative HNSCC, who were treated with cisplatin-based chemoradiotherapy. DNA repair defects, as predicted by the profiles, were associated with poor outcome in both patient cohorts. The poor prognosis association was particularly strong in normoxic tumor samples and was linked to an increased risk of distant metastasis. In vitro, only crosslink repair–defective HNSCC cell lines are highly migratory and invasive. This phenotype could also be induced in cells by inhibiting rad51 in repair competent and reduced by DNA-PK inhibition. In conclusion, DNA crosslink repair prediction expression profiles reveal a poor prognosis association in HNSCC. Significance: This study uses innovative machine learning-based approaches to derive models that predict the effect of DNA repair defects on treatment outcome in HNSCC. |
| Databáze: | OpenAIRE |
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