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A four-gene transcript score to predict metastatic-lethal progression in men treated for localized prostate cancer: Development and validation studies.

ABSTRACT: BACKGROUND:Molecular studies have tried to address the unmet need for prognostic biomarkers in prostate cancer (PCa). Some gene expression tests improve upon clinical factors for prediction of outcomes, but additional tools for accurate prediction of tumor aggressiveness are needed. METHODS:Based on a previously published panel of 23 gene transcripts that distinguished patients with metastatic progression, we constructed a prediction model using independent training and testing datasets. Using the validated messenger RNAs and Gleason score (GS), we performed model selection in the training set to define a final locked model to classify patients who developed metastatic-lethal events from those who remained recurrence-free. In an independent testing dataset, we compared our locked model to established clinical prognostic factors and utilized Kaplan-Meier curves and receiver operating characteristic analyses to evaluate the model's performance. RESULTS:Thirteen of 23 previously identified gene transcripts that stratified patients with aggressive PCa were validated in the training dataset. These biomarkers plus GS were used to develop a four-gene (CST2, FBLN1, TNFRSF19, and ZNF704) transcript (4GT) score that was significantly higher in patients who progressed to metastatic-lethal events compared to those without recurrence in the testing dataset (P?=?5.7?×?10-11 ). The 4GT score provided higher prediction accuracy (area under the ROC curve [AUC]?=?0.76; 95% confidence interval [CI]?=?0.69-0.83; partial area under the ROC curve [pAUC]?=?0.008) than GS alone (AUC?=?0.63; 95% CI?=?0.56-0.70; pAUC?=?0.002), and it improved risk stratification in subgroups defined by a combination of clinicopathological features (ie, Cancer of the Prostate Risk Assessment-Surgery). CONCLUSION:Our validated 4GT score has prognostic value for metastatic-lethal progression in men treated for localized PCa and warrants further evaluation for its clinical utility.

SUBMITTER: Cheng A

PROVIDER: S-EPMC6715522 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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A four-gene transcript score to predict metastatic-lethal progression in men treated for localized prostate cancer: Development and validation studies.

Cheng Anqi A Zhao Shanshan S FitzGerald Liesel M LM Wright Jonathan L JL Kolb Suzanne S Karnes R Jeffrey RJ Jenkins Robert B RB Davicioni Elai E Ostrander Elaine A EA Feng Ziding Z Fan Jian-Bing JB Dai James Y JY Stanford Janet L JL

The Prostate 20190802 14

<h4>Background</h4>Molecular studies have tried to address the unmet need for prognostic biomarkers in prostate cancer (PCa). Some gene expression tests improve upon clinical factors for prediction of outcomes, but additional tools for accurate prediction of tumor aggressiveness are needed.<h4>Methods</h4>Based on a previously published panel of 23 gene transcripts that distinguished patients with metastatic progression, we constructed a prediction model using independent training and testing da ...[more]

PMID: 31376183

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Project description:BackgroundOne-carbon metabolism, which is crucial in DNA synthesis and genomic stability, is an interrelated network of biochemical reactions involved in several dietary and lifestyle factors. The development of the homocysteine score using these factors may be useful to reflect the status of one-carbon metabolism in large epidemiologic studies without biologic samples to measure homocysteine directly.ObjectiveThe aim of this study was to develop an homocysteine score that reflects one-carbon metabolism better than individual dietary or lifestyle factors.MethodsWe divided 2023 participants with measured plasma total homocysteine data in the Nurses' Health Study and the Health Professionals Follow-Up Study into training (n = 1619) and testing (n = 404) subsets. Using multivariable linear regression, we selected lifestyle determinants of plasma homocysteine in the training set and derived the homocysteine score weighted by the β coefficient for each predictor. The validation of the homocysteine score was assessed using the plasma homocysteine in the independent samples of the training set.ResultsIn the training set, smoking, multivitamin use, and caffeine, alcohol, and dietary and supplemental folate intake were significant independent determinants of plasma homocysteine in multivariable linear regression (P ≤ 0.01) and were included in the derivation of the homocysteine score. The Pearson correlation of the homocysteine score with plasma homocysteine was 0.30 in the testing subset (P < 0.001). The homocysteine score was positively associated with the plasma homocysteine concentration in the testing subset and in an independent population of women; the mean difference of plasma homocysteine concentration between the extreme quintiles of homocysteine score ranged from 0.83 μmol/L to 1.52 μmol/L. Population misclassification either from the lowest quintile of plasma homocysteine into the highest quintile of the homocysteine score or from the highest quintile of plasma homocysteine into the lowest quintile of the homocysteine score was ≤12%.ConclusionThese data indicate that the homocysteine score may be used with relatively inexpensive and simple questionnaires to rank an individual's one-carbon metabolism status when homocysteine data are not available.

Dataset Information

A four-gene transcript score to predict metastatic-lethal progression in men treated for localized prostate cancer: Development and validation studies.

Publications

A four-gene transcript score to predict metastatic-lethal progression in men treated for localized prostate cancer: Development and validation studies.

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