2020
DOI: 10.1101/2020.07.03.20145854
|View full text |Cite
Preprint
|
Sign up to set email alerts
|

MicroRNA-based cancer mortality risk scoring system and hTERT expression linked with risk-adjusted treatment strategy in early-stage oral squamous cell carcinoma

Abstract: We have developed and validated a novel microRNA (miRNA)-based prognostic model to predict survival outcome in oral squamous cell carcinoma (OSCC) patients who are already categorized into early-stage by the TNM system. A total of 836 early-stage OSCC patients were assigned the mortality risk scores. We evaluated the efficacy of various treatment regimens in terms of survival benefit compared to surgery only in patients stratified into high and low mortality risk categories. Within the high-risk group,… Show more

Help me understand this report
View published versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2022
2022
2022
2022

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
(1 citation statement)
references
References 42 publications
(79 reference statements)
0
1
0
Order By: Relevance
“…MiRNAs are 21-23 nucleotides long, highly conserved, noncoding small RNA molecules. Due to their effects on gene expression and association with disease conditions, they are being intensely researched as potential biomarkers (15)(16)(17). Since miRNAs are endogenous post-translational regulatory genes, they regulate gene expression by binding to mRNAs and promoting their degradation or translation.…”
Section: Introductionmentioning
confidence: 99%
“…MiRNAs are 21-23 nucleotides long, highly conserved, noncoding small RNA molecules. Due to their effects on gene expression and association with disease conditions, they are being intensely researched as potential biomarkers (15)(16)(17). Since miRNAs are endogenous post-translational regulatory genes, they regulate gene expression by binding to mRNAs and promoting their degradation or translation.…”
Section: Introductionmentioning
confidence: 99%