ABSTRACT: BACKGROUND:We utilized miRNAs expression and clinical data to develop a prognostic signature for patients with lung adenocarcinoma, with respect to their overall survival, to identify high-risk subjects based on their miRNA genomic profile. METHODS:MiRNA expressions based on miRNA sequencing and clinical data of lung adenocarcinoma patients (n?=?479) from the Cancer Genome Atlas were randomly partitioned into non-overlapping Model (n?=?320) and Test (n?=?159) sets, respectively, for model estimation and validation. RESULTS:Among the ten miRNAs identified using the univariate Cox analysis, six from miR-8, miR-181, miR-326, miR-375, miR-99a, and miR-10, families showed improvement of the overall survival chance, while two miRNAs from miR-582 and miR-584 families showed a worsening of survival chances. The final prognostic signature was developed with five miRNAs-miR-375, miR-582-3p, miR-326, miR-181c-5p, and miR-99a-5p-utilizing a stepwise variable selection procedure. Using the KEGG pathway analysis, we found potential evidence supporting their significance in multiple cancer pathways, including non-small cell lung cancer. We defined two risk groups with a score calculated using the Cox regression coefficients. The five-year survival rates for the low-risk group was approximately 48.76% (95% CI?=?(36.15, 63.93)); however, it was as low as 7.50% (95% CI?=?(2.34, 24.01)) for the high-risk group. Furthermore, we demonstrated the effect of the genomic profile using the miRNA signature, quantifying survival rates for hypothetical subjects in different pathological stages of cancer. CONCLUSIONS:The proposed prognostic signature can be used as a reliable tool for identifying high-risk subjects regarding survival based on their miRNA genomic profile.
