Comprehensive Analysis of Prognostic Alternative Splicing Signatures in Oral Squamous Cell Carcinoma
BackgroundAlternative splicing (AS) plays an essential role in tumorigenesis and progression. This study aimed to develop a novel prognostic model based on the AS events to obtain more accurate survival prediction and search for potential therapeutic targets in oral squamous cell carcinoma (OSCC).MethodsSeven types of AS events in 326 OSCC patients with RNA-seq were obtained from the TCGA SpliceSeq tool and the TCGA database. Cox analysis, the least absolute shrinkage and selection operator Cox regression and random forest were employed to establish prognostic models. Genomics of Drug Sensitivity in Cancer (GDSC) was adopted to estimate the possible drug sensiticity. Prognostic splicing factor (SF)-AS network was constructed by Cytoscape.ResultsThe final model included 12 AS events, showing satisfactory performance. The area under the curve for 3- and 5-year survival in the training cohort was 0.83 and 0.82, respectively while that in internal validation was 0.83 and 0.82 accordingly. The calibration curve also indicated a satisfactory agreement between the observation and the predictive values. Low-risk patients stratified by the final model presented higher sensitivity to three chemo drugs. Besides, the prognostic SF-AS regulatory network contained five key SFs and 62 AS events.ConclusionsWe developed a powerful prognostic AS signature for OSCC and deepened the understanding of SF-AS network regulatory mechanisms. Low-risk patients tended to be more sensitive to the three chemo drugs while five key SFs including CELF2, TIA1, HNRNPC, HNRNPK, and SRSF9 were identified as potential prognostic biomarkers, which may offer new prospects for effective therapies of OSCC..
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2020 |
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| Erschienen: |
2020 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:10 |
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| Enthalten in: |
Frontiers in Oncology - 10(2020) |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Ruoyan Cao [VerfasserIn] |
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| Links: |
doi.org [kostenfrei] |
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| Themen: |
Alternative splicing |
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| doi: |
10.3389/fonc.2020.01740 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
DOAJ027306534 |
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| 520 | |a BackgroundAlternative splicing (AS) plays an essential role in tumorigenesis and progression. This study aimed to develop a novel prognostic model based on the AS events to obtain more accurate survival prediction and search for potential therapeutic targets in oral squamous cell carcinoma (OSCC).MethodsSeven types of AS events in 326 OSCC patients with RNA-seq were obtained from the TCGA SpliceSeq tool and the TCGA database. Cox analysis, the least absolute shrinkage and selection operator Cox regression and random forest were employed to establish prognostic models. Genomics of Drug Sensitivity in Cancer (GDSC) was adopted to estimate the possible drug sensiticity. Prognostic splicing factor (SF)-AS network was constructed by Cytoscape.ResultsThe final model included 12 AS events, showing satisfactory performance. The area under the curve for 3- and 5-year survival in the training cohort was 0.83 and 0.82, respectively while that in internal validation was 0.83 and 0.82 accordingly. The calibration curve also indicated a satisfactory agreement between the observation and the predictive values. Low-risk patients stratified by the final model presented higher sensitivity to three chemo drugs. Besides, the prognostic SF-AS regulatory network contained five key SFs and 62 AS events.ConclusionsWe developed a powerful prognostic AS signature for OSCC and deepened the understanding of SF-AS network regulatory mechanisms. Low-risk patients tended to be more sensitive to the three chemo drugs while five key SFs including CELF2, TIA1, HNRNPC, HNRNPK, and SRSF9 were identified as potential prognostic biomarkers, which may offer new prospects for effective therapies of OSCC. | ||
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| 653 | 0 | |a Neoplasms. Tumors. Oncology. Including cancer and carcinogens | |
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| 700 | 0 | |a Jiayu Zhang |e verfasserin |4 aut | |
| 700 | 0 | |a Jiayu Zhang |e verfasserin |4 aut | |
| 700 | 0 | |a Jiayu Zhang |e verfasserin |4 aut | |
| 700 | 0 | |a Laibo Jiang |e verfasserin |4 aut | |
| 700 | 0 | |a Laibo Jiang |e verfasserin |4 aut | |
| 700 | 0 | |a Laibo Jiang |e verfasserin |4 aut | |
| 700 | 0 | |a Yanting Wang |e verfasserin |4 aut | |
| 700 | 0 | |a Yanting Wang |e verfasserin |4 aut | |
| 700 | 0 | |a Yanting Wang |e verfasserin |4 aut | |
| 700 | 0 | |a Xianyue Ren |e verfasserin |4 aut | |
| 700 | 0 | |a Xianyue Ren |e verfasserin |4 aut | |
| 700 | 0 | |a Xianyue Ren |e verfasserin |4 aut | |
| 700 | 0 | |a Bin Cheng |e verfasserin |4 aut | |
| 700 | 0 | |a Bin Cheng |e verfasserin |4 aut | |
| 700 | 0 | |a Bin Cheng |e verfasserin |4 aut | |
| 700 | 0 | |a Juan Xia |e verfasserin |4 aut | |
| 700 | 0 | |a Juan Xia |e verfasserin |4 aut | |
| 700 | 0 | |a Juan Xia |e verfasserin |4 aut | |
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