Original Article
Prognostic model based on circular RNA circPDK1 for resected lung squamous cell carcinoma
Abstract
Background: Circular RNA has been revealed as a potential biomarker in multiple malignancies. However, few studies have focused on its potential to be prognostic markers in lung squamous cell carcinoma (LSCC). In this work, we aimed to build a prognostic model of resected LSCC based on circular RNA pyruvate dehydrogenase kinase 1 (circPDK1) and other clinicopathological factors.
Methods: circPDK1 was identified via next-generation sequencing. Three hundred two cases of LSCC tissue and their adjacent normal lung tissues were obtained from multiple medical centers and divided into study cohort (n=232) and validation cohort (n=70). The expression of circPDK1 was detected for analyzing its potential prognostic value for recurrence-free survival (RFS) and overall survival (OS) in LSCC. Finally, combined with circPDK1, T staging, lymph nodes (LN) metastasis status, age, and serum Squamous Cell Carcinoma Antigen (SCCAg), we built a prognostic model by nomograms method and confirmed it in the validation cohort.
Results: CircPDK1 was identified to be overexpressed (P<0.01) in LSCC. Through analysis in study cohort, circPDK1low patients (less than the mean expression, n=124) showed more lymph nodes metastasis (P=0.025), more vascular invasion (VI) (P=0.047), more visceral pleural invasion (VPI) (P=0.015) and poorer prognosis (P=0.003) than circPDK1high ones (n=108). Univariate and multivariate analysis showed that circPDK1, T staging, LN status, age, and SCCAg were significant prognostic factors for RFS and OS. The prognostic model based on these factors showed the concordance index (C-index) of 0.8214 and 0.8359 for predicting 5-year RFS and OS, respectively. Finally, the calibration curves were performed in the study cohort and a validation cohort to evaluate the model’s efficiency.
Conclusions: circPDK1 was identified as a potential biomarker of resected LSCC. The prognostic model including circPDK1, T staging, LN status, age, and SCCAg could effectively predict prognosis of resected LSCC.
Methods: circPDK1 was identified via next-generation sequencing. Three hundred two cases of LSCC tissue and their adjacent normal lung tissues were obtained from multiple medical centers and divided into study cohort (n=232) and validation cohort (n=70). The expression of circPDK1 was detected for analyzing its potential prognostic value for recurrence-free survival (RFS) and overall survival (OS) in LSCC. Finally, combined with circPDK1, T staging, lymph nodes (LN) metastasis status, age, and serum Squamous Cell Carcinoma Antigen (SCCAg), we built a prognostic model by nomograms method and confirmed it in the validation cohort.
Results: CircPDK1 was identified to be overexpressed (P<0.01) in LSCC. Through analysis in study cohort, circPDK1low patients (less than the mean expression, n=124) showed more lymph nodes metastasis (P=0.025), more vascular invasion (VI) (P=0.047), more visceral pleural invasion (VPI) (P=0.015) and poorer prognosis (P=0.003) than circPDK1high ones (n=108). Univariate and multivariate analysis showed that circPDK1, T staging, LN status, age, and SCCAg were significant prognostic factors for RFS and OS. The prognostic model based on these factors showed the concordance index (C-index) of 0.8214 and 0.8359 for predicting 5-year RFS and OS, respectively. Finally, the calibration curves were performed in the study cohort and a validation cohort to evaluate the model’s efficiency.
Conclusions: circPDK1 was identified as a potential biomarker of resected LSCC. The prognostic model including circPDK1, T staging, LN status, age, and SCCAg could effectively predict prognosis of resected LSCC.
