Dataset Information

MicroRNA-based risk scoring system to identify early-stage oral squamous cell carcinoma patients at high-risk for cancer-specific mortality.

ABSTRACT:

Background

For early-stage oral squamous cell carcinoma (OSCC), there is no existing risk-stratification modality beyond conventional TNM staging system to identify patients at high risk for cancer-specific mortality.

Methods

A total of 568 early-stage OSCC patients who had surgery only and also with available 5-year clinical outcomes data were identified. Signature microRNAs (miRNAs) were discovered using deep sequencing analysis and validated by qRT-PCR. The final 5-plex prognostic marker panel was utilized to generate a cancer-specific mortality risk score using the multivariate Cox regression analyses. The prognostic markers were validated in the internal and external validation cohorts.

Results

The risk score from the 5-plex marker panel consisting of miRNAs-127-3p, 4736, 655-3p, TNM stage and histologic grading stratified patients into four risk categories. Compared to the low-risk group, the high-risk group had 23-fold increased mortality risk (hazard ratio 23, 95% confidence interval 13-42), with a median time-to-recurrence of 6 months and time-to-death of 11 months (vs >60 months for each among low-risk patient; p < .001).

Conclusion

The miRNA-based 5-plex marker panel driven mortality risk score formula provides clinically practical and reliable measures to assess the prognosis of patients assigned to an early-stage OSCC.

SUBMITTER: Yoon AJ

PROVIDER: S-EPMC7369212 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:MicroRNA (miR) signatures may aid the diagnosis and prediction of cancer; therefore, miRs associated with the prognosis of esophageal squamous cell carcinoma (ESCC) were screened. miR‑sequencing (seq) and mRNA‑seq data from early‑stage ESCC samples were downloaded from The Cancer Genome Atlas (TCGA) database, and samples from subjects with a >6‑month survival time were assessed with Cox regression analysis for prognosis‑associated miRs. A further two miR expression datasets of ESCC samples, GSE43732 and GSE13937, were downloaded from the Gene Expression Omnibus database. Common miRs between prognosis‑associated miRs, and miRs in the GSE43732 and GSE13937, datasets were used for risk score calculations for each sample, and median risk scores were applied for the stratification of low‑ and high‑risk samples. A prognostic scoring system of signature miRs was subsequently constructed and used for survival analysis for low‑ and high‑risk samples. Differentially‑expressed genes (DEGs) corresponding to all miRs were screened and functional annotation was performed. A total of 34 prognostic miRs were screened and a scoring system was created using 10 signature miRs (hsa‑miR‑140, ‑33b, ‑34b, ‑144, ‑486, ‑214, ‑129‑2, ‑374a and ‑412). Using this system, low‑risk samples were identified to be associated with longer survival compared with high‑risk samples in the TCGA and GSE43732 datasets. Age, alcohol and tobacco use, and radiotherapy were prognostic factors for samples with different risk scores and the same clinical features. There were 168 DEGs, and the top 20 risk scores positively‑correlated and the top 20 risk scores negatively‑correlated DEGs were significantly enriched for six and 10 functional terms, respectively. 'Tight junction' and 'melanogenesis' were two significantly enriched pathways of DEGs. miR‑214, miR‑129‑2, miR‑37a and miR‑486 may predict ESCC patient survival, although further studies to validate this hypothesis are required.