Dataset Information

A response prediction model for taxane, cisplatin, and 5-fluorouracil chemotherapy in hypopharyngeal carcinoma.

ABSTRACT: Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer worldwide. The five-year survival rate of HNSCC has not improved even with major technological advancements in surgery and chemotherapy. Currently, docetaxel, cisplatin, and 5-fluoruracil (TPF) treatment has been the most popular chemotherapy method for HNSCC; but only a small percentage of HNSCC patients exhibit a good response to TPF treatment. Unfortunately, at present, no reasonably effective prediction model exists to assist clinicians with patient treatment. For this reason, patients have no other alternative but to risk neoadjuvant chemotherapy in order to determine their response to TPF. In this study, we analyzed the gene expression profile in TPF-sensitive and non-sensitive patient samples. We identified a gene expression signature between these two groups. We further chose 10 genes and trained a support vector machine (SVM) model. This model has 88.3% sensitivity and 88.9% specificity to predict the response to TPF treatment in our patients. In addition, four more TPF responsive and four more TPF non-sensitive patient samples were used for further validation. This SVM model has been proven to achieve approximately 75.0% sensitivity and 100% specificity to predict TPF response in new patients. This suggests that our 10-genes SVM prediction model has the potential to assist clinicians to personalize treatment for HNSCC patients.

SUBMITTER: Zhong Q

PROVIDER: S-EPMC6107664 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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Publications

A response prediction model for taxane, cisplatin, and 5-fluorouracil chemotherapy in hypopharyngeal carcinoma.

Zhong Qi Q Fang Jugao J Huang Zhigang Z Yang Yifan Y Lian Meng M Liu Honggang H Zhang Yixiang Y Ye Junhui J Hui Xinjie X Wang Yejun Y Ying Ying Y Zhang Qing Q Cheng Yingduan Y

Scientific reports 20180823 1

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer worldwide. The five-year survival rate of HNSCC has not improved even with major technological advancements in surgery and chemotherapy. Currently, docetaxel, cisplatin, and 5-fluoruracil (TPF) treatment has been the most popular chemotherapy method for HNSCC; but only a small percentage of HNSCC patients exhibit a good response to TPF treatment. Unfortunately, at present, no reasonably effective prediction model exist ...[more]

PMID: 30139993

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Project description:This study aimed to develop a novel gene expression signature that can predict tumor response to induction chemotherapy (IC) before treatment. RNA sequencing (RNA-seq) was used to screen the differentially expressed genes (DEGs) between response and non-response in 54 samples (discovery cohort). Random forest (RF) and receiver operating characteristic (ROC) analyses were performed to further screen principal genes using the RNA-seq data of 27 cases (training cohort). qRT-PCR was used to confirm the relative expression of the selected genes between 57 non-response tissues and 55 response tissues (validation cohort). K-means was used to stratify all patients into two clusters according to the 6-gene signature. Kaplan-Meier analysis was used to estimate overall survival in the two clusters. The log-rank survival test was performed to compare the differences between the two clusters. In the discovery phase, 107 DEGs were obtained. It effectively distinguished tumors from normal tissues and distinguished response tumors from non-response tumors by RNA sequencing. In the training phase, the top 50 genes were selected by RF, which showed distinct transcriptome segregation between response and non-response tumors. Then, the performance of the 50 genes was evaluated to predict the tumor response of IC using ROC analysis. Among them, 10 genes were chosen for which the area under the curve was more than 80%. In the validation phase, six genes (CD72, NRIP1, THBS4, ABCA9, SNED1, and GIMAP7) were significantly overexpressed in non-response tissues compared to response tissues (p < 0.05). Finally, the 6-gene signature was developed, which was highly accurate in predicting the short-term tumor response to IC (AUC= 0.949) and was also an independent prognostic factor for predicting the overall survival of locoregionally advanced laryngeal and hypopharyngeal carcinoma (LA-LHC) patients. The 6-gene signature can effectively predict tumor response to IC and overall survival, which lays the foundation for a more individualized therapeutic strategy for LA-LHC patients.

Dataset Information

A response prediction model for taxane, cisplatin, and 5-fluorouracil chemotherapy in hypopharyngeal carcinoma.

Publications

A response prediction model for taxane, cisplatin, and 5-fluorouracil chemotherapy in hypopharyngeal carcinoma.

Similar Datasets

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