Oral oncology · 2019
Identification of markers predictive for response to induction chemotherapy in patients with sinonasal undifferentiated carcinoma.
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Takahashi Yoko, Gleber-Netto Frederico O, Bell Diana, Roberts Dianna, Xie Tong-Xin, Abdelmeguid Ahmed S, Pickering Curtis, Myers Jeffrey N, Hanna Ehab Y
Аннотация
OBJECTIVES: Sinonasal undifferentiated carcinoma (SNUC) is a rare, highly aggressive cancer. Despite aggressive multimodal therapy, its prognosis remains poor. Because of its locally advanced nature and high propensity for distant metastasis, we frequently use induction chemotherapy before definitive therapy in patients with SNUC. However, about 30% of patients do not respond to induction chemotherapy, and lack of response is associated with a poor survival rate. Therefore, in this study, we performed gene expression analysis of SNUC samples to identify prognostic markers for induction chemotherapy response.
MATERIALS AND METHODS: Formalin-fixed, paraffin-embedded SNUC tumor samples from previously untreated patients harvested before induction chemotherapy were used. Gene expression was performed using an oncology gene expression panel.
RESULTS: We identified 34 differentially expressed genes that distinguish the responders from the non-responders. Pathway analysis using these genes revealed alteration of multiple pathways between the two groups. Of these 34 genes, 24 distinguished between these two groups. Additionally, 16 gene pairs were associated with response to induction therapy.
CONCLUSION: We identified genes predictive of SNUC response to induction chemotherapy and pathways potentially associated with treatment outcome. This is the first report of identification of predictive biomarkers for response of SNUC to induction chemotherapy, and it may help us develop therapeutic strategies to improve the treatment outcomes of non-responders.
MATERIALS AND METHODS: Formalin-fixed, paraffin-embedded SNUC tumor samples from previously untreated patients harvested before induction chemotherapy were used. Gene expression was performed using an oncology gene expression panel.
RESULTS: We identified 34 differentially expressed genes that distinguish the responders from the non-responders. Pathway analysis using these genes revealed alteration of multiple pathways between the two groups. Of these 34 genes, 24 distinguished between these two groups. Additionally, 16 gene pairs were associated with response to induction therapy.
CONCLUSION: We identified genes predictive of SNUC response to induction chemotherapy and pathways potentially associated with treatment outcome. This is the first report of identification of predictive biomarkers for response of SNUC to induction chemotherapy, and it may help us develop therapeutic strategies to improve the treatment outcomes of non-responders.