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Comprehensive analysis of the functions, prognostic and diagnostic values of RNA binding proteins in head and neck squamous cell carcinoma - 28/08/24

Doi : 10.1016/j.jormas.2024.101937 
Hai Liu a, b, Zhenqi Ye a, b, Xiaoying Wang d, e, Yaping Wu c, d, e, ⁎ , Chao Deng a, b, ⁎
a School of Stomatology, Wannan Medical College, Wuhu, China 
b Anhui Provincial Engineering Research Center for Dental Materials and Application, Wannan Medical College, Wuhu, China 
c Department of Oral and Maxillofacial Surgery, The Affiliated Stomatological Hospital of Nanjing Medical University, Nanjing, China 
d Jiangsu Key Laboratory of Oral Disease, Nanjing Medical University, Nanjing, China 
e Jiangsu Province Engineering Research Center of Stomatological Translational Medicine, Nanjing Medical University, Nanjing, China 

⁎Corresponding author at: Jiangsu Key Laboratory of Oral Disease, Nanjing Medical University, Jiangsu 210029, China.Jiangsu Key Laboratory of Oral DiseaseNanjing Medical UniversityJiangsu210029China⁎⁎Corresponding author at: School of Stomatology, Wannan Medical College, Anhui 241002, China.School of StomatologyWannan Medical CollegeAnhui241002China

Abstract

Background

Accumulating evidence has suggested that RNA binding protein (RBP) dysregulation plays an essential role during tumorigenesis. Here, we sought to explore the potential biological functions and clinical significance of RBP and develop diagnostic and prognostic signatures based on RBP in patients with head and neck squamous cell carcinoma (HNSCC).

Methods

The differently expressed RBPs between HNSCC samples and their normal counterparts were identified using the Limma package. The immunohistochemistry (IHC) images of several RBPs were collected from the Human Protein Atlas database. The diagnostic signature based on RBP was built by LASSO-logistic regression and random forest. The prognostic signature based on RBP was constructed by LASSO and stepwise Cox regression analysis in the training cohort and validated in the validation cohort.

Results

Eighty-four aberrantly expressed RBPs were obtained, comprising 41 up-regulated and 43 down-regulated RBPs. Seven RBP genes (CPEB3, PDCD4, ENDOU, PARP12, DNMT3B, IGF2BP1, EXO1) were identified as diagnostic-related hub genes. They were used to establish a diagnostic RBP signature risk score (DRBPS) model by the coefficients in least absolute shrinkage and selection operator (LASSO)-logistic regression analysis and showed high specificity and sensitivity in the training (area under the receiver operating characteristic curve (AUC) = 0.998), and in all validation cohorts (AUC > 0.95 for all). Similarly, seven RBP genes (MKRN3, ZC3H12D, EIF5A2, AFF3, SIDT1, RBM24, and NR0B1) were identified as prognosis-associated hub genes by LASSO and stepwise multiple Cox regression analyses and were used to construct the prognostic model named as PRBPS. The AUC of the time-dependent receiver operator characteristic curve of the prognostic model was 0.664 at 3 years and 0.635 at 5 years in the training cohort and 0.720, 0.777 in the validation cohort, showing a favorable predictive efficacy for prognosis in HNSCC.

Conclusions

Our results demonstrate the value of consideration of RBP in the diagnosis and prognosis for HNSCC and provide a novel insight into understanding the potential role of dysregulated RBP in HNSCC.

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Keywords : Head and neck squamous cell carcinoma, RNA-binding proteins, Prognostic signature, Diagnostic signature


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Vol 125 - N° 4S

Articolo 101937- settembre 2024 Ritorno al numero
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