Dear Authors,
If you believe that your paper was mistakenly rejected by other leading journals and you do not agree with final decision, the editors of Reports of Practical Oncology and Radiotherapy offer new fast track review. You may submit your manuscript to Reports of Practical Oncology and Radiotherapy together with all prior peer-reviews obtained from the other journal and your rebuttal letter. We guarantee review based decision within 72 hours from the time we will receive your manuscript.

Fast track submission process: Please submit the manuscript with all reviews and rebuttal letter by email to Dr. Michal Masternak (michal.masternak@ucf.edu) for fast review processing. To assure immediate attention the email title must to include: RPOR-fast track- Last Name First Name (of corresponding author).

Volume 23, Number 1, 2018

Characteristic miRNA expression signature and random forest survival analysis identify potential cancer-driving miRNAs in a broad range of head and neck squamous cell carcinoma subtypes

Yury O. Nunez Lopez, Berta Victoria, Pawel Golusinski, Wojciech Golusinski, Michal M. Masternak

Summary:

Aim

To characterize the miRNA expression profile in head and neck squamous cell carcinoma (HNSSC) accounting for a broad range of cancer subtypes and consequently identify an optimal miRNA signature with prognostic value.

Background

HNSCC is consistently among the most common cancers worldwide. Its mortality rate is about 50% because of the characteristic aggressive behavior of these cancers and the prevalent late diagnosis. The heterogeneity of the disease has hampered the development of robust prognostic tools with broad clinical utility.

Materials and methods

The Cancer Genome Atlas HNSC dataset was used to analyze level 3 miRNA-Seq data from 497 HNSCC patients. Differential expression (DE) analysis was implemented using the limma package and multivariate linear model that adjusted for the confounding effects of age at diagnosis, gender, race, alcohol history, anatomic neoplasm subdivision, pathologic stage, T and N stages, and vital status. Random forest (RF) for survival analysis was implemented using the randomForestSRC package.

Results

A characteristic DE miRNA signature of HNSCC, comprised of 11 upregulated (i.e., miR-196b-5p, miR-1269a, miR-196a-5p, miR-4652-3p, miR-210-3p, miR-1293, miR-615-3p, miR-503-5p, miR-455-3p, miR-205-5p, and miR-21-5p) and 9 downregulated (miR-376c-3p, miR-378c, miR-29c-3p, miR-101-3p, miR-195-5p, miR-299-5p, miR-139-5p, miR-6510-3p, miR-375) miRNAs was identified. An optimal RF survival model was built from seven variables including age at diagnosis, miR-378c, miR-6510-3p, stage N, pathologic stage, gender, and race (listed in order of variable importance).

Conclusions

The joint differential miRNA expression and survival analysis controlling for multiple confounding covariates implemented in this study allowed for the identification of a previously undetected prognostic miRNA signature characteristic of a broad range of HNSCC.

Signature: Rep Pract Oncol Radiother, 2018; 23(1) : 6-20


« back

 
INDEXED IN:

Indexed in: EMBASE®, the Excerpta Medica database, the Elsevier BIOBASE (Current Awareness in Biological Sciences) and in the Index Copernicus.

http://www.sciencedirect.com/science/journal/15071367/19/2