Literature DB >> 27429853

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

Jason B Nikas1.   

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.

Entities:  

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

Year:  2016        PMID: 27429853      PMCID: PMC4937742     

Source DB:  PubMed          Journal:  Am J Cancer Res        ISSN: 2156-6976            Impact factor:   6.166


  11 in total

1.  A common variant in MTHFR influences response to chemoradiotherapy and recurrence of rectal cancer.

Authors:  Jason B Nikas; Janet T Lee; Elizabeth D Maring; Jill Washechek-Aletto; Donna Felmlee-Devine; Ruth A Johnson; Thomas C Smyrk; Patrick S Tawadros; Lisa A Boardman; Clifford J Steer
Journal:  Am J Cancer Res       Date:  2015-09-15       Impact factor: 6.166

2.  Comparison of analytical mathematical approaches for identifying key nuclear magnetic resonance spectroscopy biomarkers in the diagnosis and assessment of clinical change of diseases.

Authors:  Jason B Nikas; C Dirk Keene; Walter C Low
Journal:  J Comp Neurol       Date:  2010-10-15       Impact factor: 3.215

3.  ROC-supervised principal component analysis in connection with the diagnosis of diseases.

Authors:  Jason B Nikas; Walter C Low
Journal:  Am J Transl Res       Date:  2011-02-03       Impact factor: 4.060

4.  A mathematical model for short-term vs. long-term survival in patients with glioma.

Authors:  Jason B Nikas
Journal:  Am J Cancer Res       Date:  2014-11-19       Impact factor: 6.166

5.  Application of clustering analyses to the diagnosis of Huntington disease in mice and other diseases with well-defined group boundaries.

Authors:  Jason B Nikas; Walter C Low
Journal:  Comput Methods Programs Biomed       Date:  2011-05-06       Impact factor: 5.428

6.  APOBEC3B is an enzymatic source of mutation in breast cancer.

Authors:  Michael B Burns; Lela Lackey; Michael A Carpenter; Anurag Rathore; Allison M Land; Brandon Leonard; Eric W Refsland; Delshanee Kotandeniya; Natalia Tretyakova; Jason B Nikas; Douglas Yee; Nuri A Temiz; Duncan E Donohue; Rebecca M McDougle; William L Brown; Emily K Law; Reuben S Harris
Journal:  Nature       Date:  2013-02-06       Impact factor: 49.962

7.  Prognosis of treatment response (pathological complete response) in breast cancer.

Authors:  Jason B Nikas; Walter C Low; Paul A Burgio
Journal:  Biomark Insights       Date:  2012-05-08

8.  Linear Discriminant Functions in Connection with the micro-RNA Diagnosis of Colon Cancer.

Authors:  Jason B Nikas; Walter C Low
Journal:  Cancer Inform       Date:  2011-12-20

9.  Mathematical prognostic biomarker models for treatment response and survival in epithelial ovarian cancer.

Authors:  Jason B Nikas; Kristin L M Boylan; Amy P N Skubitz; Walter C Low
Journal:  Cancer Inform       Date:  2011-10-03

10.  Inflammation and immune system activation in aging: a mathematical approach.

Authors:  Jason B Nikas
Journal:  Sci Rep       Date:  2013-11-19       Impact factor: 4.379

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  5 in total

1.  Cellular and molecular architecture of hematopoietic stem cells and progenitors in genetic models of bone marrow failure.

Authors:  Stephanie Heidemann; Brian Bursic; Sasan Zandi; Hongbing Li; Sagi Abelson; Robert J Klaassen; Sharon Abish; Meera Rayar; Vicky R Breakey; Houtan Moshiri; Santhosh Dhanraj; Richard de Borja; Adam Shlien; John E Dick; Yigal Dror
Journal:  JCI Insight       Date:  2020-02-27

2.  Protocadherin 15 suppresses oligodendrocyte progenitor cell proliferation and promotes motility through distinct signalling pathways.

Authors:  Yilan Zhen; Carlie L Cullen; Raphael Ricci; Benjamin S Summers; Sakina Rehman; Zubair M Ahmed; Antoinette Y Foster; Ben Emery; Robert Gasperini; Kaylene M Young
Journal:  Commun Biol       Date:  2022-05-30

3.  Comprehensive Analysis of Enhancer RNAs Identifies LINC00689 and ELFN1-AS1 as Novel Prognostic Biomarkers in Uveal Melanoma.

Authors:  Su Zhao; Hao Jiang; Jing Liu; Dao-Yuan Li; Bing Li; Qiu-Rong Long; Lei Zheng; Hao Gu
Journal:  Dis Markers       Date:  2022-02-23       Impact factor: 3.434

4.  Ovarian carcinoma immunoreactive antigen domain 2 controls mitochondrial apoptosis in lung adenocarcinoma.

Authors:  Jeongmin Hong; Aya Shiba-Ishii; Yunjung Kim; Masayuki Noguchi; Noriaki Sakamoto
Journal:  Cancer Sci       Date:  2021-10-18       Impact factor: 6.716

5.  Identification and Validation of an Immune-Related eRNA Prognostic Signature for Hepatocellular Carcinoma.

Authors:  Shenglan Cai; Xingwang Hu; Ruochan Chen; Yiya Zhang
Journal:  Front Genet       Date:  2021-06-11       Impact factor: 4.599

  5 in total

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