title: A mathematical model for short-term vs. long-term survival in patients with glioma.
abstract: Gliomas, the most common primary brain tumors in adults, constitute clinically, histologically, and molecularly a most heterogeneous type of cancer. Owing to this, accurate clinical prognosis for short-term vs. long-term survival for patients with grade II or III glioma is currently nonexistent. A rigorous, multi-method bioinformatic approach was used to identify the top most differentially expressed genes as captured by mRNA sequencing of tumor tissue. Mathematical modeling was employed to develop the model, and three different and independent methods of validation were used to assess its performance. I present here a mathematical model that can identify with a high accuracy (sensitivity=92.9%, specificity=96.0%) those patients with glioma (grade II or III) who will experience short-term survival (≤ 1 year), as well as those with long-term survival (≥ 3 years), at the time of diagnosis and prior to surgery and adjuvant chemotherapy. The 5 gene input variables to the model are: FAM120AOS, PDLIM4, OCIAD2, PCDH15, and MXI1. MXI1, a transcriptional repressor, represents the top biomarker of survival and the most promising target for the development of a pharmacological treatment.
authors.affiliation: Genomix, Inc. Minneapolis, MN 55364, USA.
authors.forename: Jason B
authors.initials: JB
authors.lastname: Nikas
keywords: Glioma; RNA-Sequencing; cancer genomics; computational biology; mathematical modeling; survival; systems biology