This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Primary research
song jukun
Guizhou provinicial people's hospital
Corresponding Author
ORCiD: https://orcid.org/0000-0003-2542-9340
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background: Dysregulation of RNA-binding proteins (RBPs) playsan important role in controlling processes in cancer development.However, the function of RBPs has not been thoroughly and systematically documented in head and neck cancer.We aim to explore the role of RPB in the pathogenesis of HNSC.
Methods: We obtained HNSC gene expression data and corresponding clinical information from The Cancer Genome Atlas (TCGA) and the GEO databases, andidentified aberrantly expressed RBPs between tumors and normal tissues.Meanwhile, we performed a series of bioinformatics to explore the function and prognostic value of these RBPs.
Results: A total of 249 abnormally expressed RBPs were identified, including 101 down-regulated RBPs and 148 up-regulated RBPs.Using least absolute shrinkage and selection operator (LASSO) and univariate Cox regression analysis, the fifteen RPBs were identified as hub genes. With the fifteen RPBS, the prognostic prediction model was constructed.Further analysis showed that the high-risk score of the patients expressed a better survival outcome. The prediction model was validated in another HNSC dataset, and similar findings were observed.
Conclusions: Our results provide novel insights into the pathogenesis of HNSC. The fifteen RBP gene signature exhibited the predictive value of moderate HNSC prognosis, and have potential application value in clinical decision-making and individualized treatment.
Keywords
Head and Neck squamous cell carcinoma,The least absolute contraction and selection operator, RNA-binding proteins
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This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Primary research
song jukun
Guizhou provinicial people's hospital
Corresponding Author
ORCiD: https://orcid.org/0000-0003-2542-9340
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
Version 1
Posted 22 Jun, 2020
No community comments so far
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Cardiothoracic Surgery
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background: Dysregulation of RNA-binding proteins (RBPs) playsan important role in controlling processes in cancer development.However, the function of RBPs has not been thoroughly and systematically documented in head and neck cancer.We aim to explore the role of RPB in the pathogenesis of HNSC.
Methods: We obtained HNSC gene expression data and corresponding clinical information from The Cancer Genome Atlas (TCGA) and the GEO databases, andidentified aberrantly expressed RBPs between tumors and normal tissues.Meanwhile, we performed a series of bioinformatics to explore the function and prognostic value of these RBPs.
Results: A total of 249 abnormally expressed RBPs were identified, including 101 down-regulated RBPs and 148 up-regulated RBPs.Using least absolute shrinkage and selection operator (LASSO) and univariate Cox regression analysis, the fifteen RPBs were identified as hub genes. With the fifteen RPBS, the prognostic prediction model was constructed.Further analysis showed that the high-risk score of the patients expressed a better survival outcome. The prediction model was validated in another HNSC dataset, and similar findings were observed.
Conclusions: Our results provide novel insights into the pathogenesis of HNSC. The fifteen RBP gene signature exhibited the predictive value of moderate HNSC prognosis, and have potential application value in clinical decision-making and individualized treatment.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10
This is a list of supplementary files associated with this preprint. Click to download.
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