Dataset Information

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

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.

SUBMITTER: Nikas JB

PROVIDER: S-EPMC4937742 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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

Nikas Jason B JB

American journal of cancer research 20160601 6

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 ...[more]

PMID: 27429853

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Project description:The University of Florida strawberry (Fragaria × ananassa) breeding program has implemented genomic prediction (GP) as a tool for choosing outstanding parents for crosses over the last five seasons. This has allowed the use of some parents 1 year earlier than with traditional methods, thus reducing the duration of the breeding cycle. However, as the number of breeding cycles increases over time, greater knowledge is needed on how multiple cycles can be used in the practical implementation of GP in strawberry breeding. Advanced selections and cultivars totaling 1,558 unique individuals were tested in field trials for yield and fruit quality traits over five consecutive years and genotyped for 9,908 SNP markers. Prediction of breeding values was carried out using Bayes B models. Independent validation was carried out using separate trials/years as training (TRN) and testing (TST) populations. Single-trial predictive abilities for five polygenic traits averaged 0.35, which was reduced to 0.24 when individuals common across trials were excluded, emphasizing the importance of relatedness among training and testing populations. Training populations including up to four previous breeding cycles increased predictive abilities, likely due to increases in both training population size and relatedness. Predictive ability was also strongly influenced by heritability, but less so by changes in linkage disequilibrium and effective population size. Genotype by year interactions were minimal. A strategy for practical implementation of GP in strawberry breeding is outlined that uses multiple cycles to predict parental performance and accounts for traits not included in GP models when constructing crosses. Given the importance of relatedness to the success of GP in strawberry, future work could focus on the optimization of relatedness in the design of TRN and TST populations to increase predictive ability in the short-term without compromising long-term genetic gains.

Dataset Information

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

Publications

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

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