DNA Damage Response Mechanisms in Head and Neck Cancer: Significant Implications for Therapy and Survival.
Chara PapaloukaMaria AdamakiPanagiota BatsakiPanagiotis ZoumpourlisAntonis TsintarakisMaria GoulielmakiSotirios P FortisConstantin N BaxevanisVassilis ZoumpourlisPublished in: International journal of molecular sciences (2023)
Head and neck cancer (HNC) is a term collectively used to describe a heterogeneous group of tumors that arise in the oral cavity, larynx, nasopharynx, oropharynx, and hypopharynx, and represents the sixth most common type of malignancy worldwide. Despite advances in multimodality treatment, the disease has a recurrence rate of around 50%, and the prognosis of metastatic patients remains poor. HNCs are characterized by a high degree of genomic instability, which involves a vicious circle of accumulating DNA damage, defective DNA damage repair (DDR), and replication stress. Nonetheless, the damage that is induced on tumor cells by chemo and radiotherapy relies on defective DDR processes for a successful response to treatment, and may play an important role in the development of novel and more effective therapies. This review summarizes the current knowledge on the genes and proteins that appear to be deregulated in DDR pathways, their implication in HNC pathogenesis, and the rationale behind targeting these genes and pathways for the development of new therapies. We give particular emphasis on the therapeutic targets that have shown promising results at the pre-clinical stage and on those that have so far been associated with a therapeutic advantage in the clinical setting.
Keyphrases
- dna damage
- dna damage response
- oxidative stress
- dna repair
- genome wide
- healthcare
- squamous cell carcinoma
- ejection fraction
- early stage
- newly diagnosed
- combination therapy
- cancer therapy
- clinical trial
- radiation therapy
- preterm infants
- gene expression
- copy number
- dna methylation
- radiation induced
- genome wide identification
- bioinformatics analysis
- stress induced
- genome wide analysis