Independent validation of a mathematical genomic model for survival of glioma patients

Am J Cancer Res. 2016 Jun 1;6(6):1408-19. eCollection 2016.

Abstract

An independent cohort study was conducted to validate a mathematical genomic model for survival of glioma patients that was introduced previously. Of the 102 new subjects that were employed in this study, 40 were long-term survivors (survival ≥ 3 years), and 62 were short-term survivors (survival ≤ 1 year). Utilizing the gene expression of 5 genes as captured by mRNA sequencing of primary tumor tissue, obtained from the initial biopsy during the diagnosis, and prior to the administration of any treatment, the model classified correctly all but three of the 102 subjects. More specifically, of the 62 STS (short-term survivors), 61 were classified correctly (sensitivity = 98.4%); and of the 40 LTS (long-term survivors), 38 were classified correctly (specificity = 95.0%). The 5 gene expression input variables to the model were: FAM120AOS, MXI1, OCIAD2, PCDH15, and PDLIM4. Of the top 29 most significantly differentially expressed genes between STS and LTS subjects, as identified in the original study, all but one were highly significant. Furthermore, with respect to survival, the model - designed to operate at the molecular level (gene expression of tumor cells) - was also able to statistically differentiate between the two subgroups of the STS group, namely, the STS subjects with lower grade glioma and the STS subjects with glioblastoma; whereas variables either at the tissue level or at the organismal level were not able to do so. Based on these results, and taking into account that accurate clinical prognosis for short-term vs. long-term survival for glioma patients is currently nonexistent, this study provides further, independent evidence for the accuracy and the clinical utility of the model.

Keywords: FAM120AOS; Glioma; MXI1; OCIAD2; PCDH15; PDLIM4; cancer genomics; computational biology; survival.