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Cell-Line Selectivity Improves the Predictive Power of Pharmacogenomic Analyses and Helps Identify NADPH as Biomarker for Ferroptosis Sensitivity.

ABSTRACT: Precision medicine in oncology requires not only identification of cancer-associated mutations but also effective drugs for each cancer genotype, which is still a largely unsolved problem. One approach for the latter challenge has been large-scale testing of small molecules in genetically characterized cell lines. We hypothesized that compounds with high cell-line-selective lethality exhibited consistent results across such pharmacogenomic studies. We analyzed the compound sensitivity data of 6,259 lethal compounds from the NCI-60 project. A total of 2,565 cell-line-selective lethal compounds were identified and grouped into 18 clusters based on their median growth inhibitory GI50 profiles across the 60 cell lines, which were shown to represent distinct mechanisms of action. Further transcriptome analysis revealed a biomarker, NADPH abundance, for predicting sensitivity to ferroptosis-inducing compounds, which we experimentally validated. In summary, incorporating cell-line-selectivity filters improves the predictive power of pharmacogenomic analyses and enables discovery of biomarkers that predict the sensitivity of cells to specific cell death inducers.

SUBMITTER: Shimada K

PROVIDER: S-EPMC4792701 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

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Cell-Line Selectivity Improves the Predictive Power of Pharmacogenomic Analyses and Helps Identify NADPH as Biomarker for Ferroptosis Sensitivity.

Shimada Kenichi K Hayano Miki M Pagano Nen C NC Stockwell Brent R BR

Cell chemical biology 20160204 2

Precision medicine in oncology requires not only identification of cancer-associated mutations but also effective drugs for each cancer genotype, which is still a largely unsolved problem. One approach for the latter challenge has been large-scale testing of small molecules in genetically characterized cell lines. We hypothesized that compounds with high cell-line-selective lethality exhibited consistent results across such pharmacogenomic studies. We analyzed the compound sensitivity data of 6, ...[more]

PMID: 26853626

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Project description:BackgroundBoth N6-methyladenosine (m6A) and ferroptosis-related genes are associated with the prognosis of lung adenocarcinoma. However, the predictive value of m6A-related ferroptosis genes remains unclear. Here, we aimed to identify the prognostic value of m6A-related ferroptosis genes in lung adenocarcinoma.MethodsLung adenocarcinoma sample data were downloaded from the University of California Santa Cruz Xena and Gene Expression Omnibus databases. Spearman's correlation analysis was used to screen for m6A-related ferroptosis genes. Univariate Cox regression, Kaplan-Meier, and Lasso analyses were conducted to identify prognostic m6A-related ferroptosis genes, and stepwise regression was used to construct a prognostic gene signature. The predictive value of the gene signature was assessed using a multivariate Cox analysis. In the validation cohort, survival analysis was performed to verify gene signature stability. The training cohort was divided into high- and low-risk groups according to the median risk score to assess differences between the two groups in terms of gene set variation analysis, somatic mutations, and tumor immune infiltration cells.ResultsSix m6A-related ferroptosis genes were used to construct a gene signature in the training cohort and a multivariate Cox analysis was conducted to determine the independent prognostic value of these genes in lung adenocarcinoma. In the validation cohort, Kaplan-Meier and receiver operating characteristic analyses confirmed the strong predictive power of this signature for the prognosis of lung adenocarcinoma. Gene set variation analysis showed that the low-risk group was mainly related to immunity, and the high-risk group was mainly related to DNA replication. Somatic mutation analysis revealed that the TP53 gene had the highest mutation rate in the high-risk group. Tumor immune infiltration cell analysis showed that the low-risk group had higher levels of resting CD4 memory T cells and lower levels of M0 macrophages.ConclusionOur study identified a novel m6A-related ferroptosis-associated six-gene signature (comprising SLC2A1, HERPUD1, EIF2S1, ACSL3, NCOA4, and CISD1) for predicting lung adenocarcinoma prognosis, yielding a useful prognostic biomarker and potential therapeutic target.

Dataset Information

Cell-Line Selectivity Improves the Predictive Power of Pharmacogenomic Analyses and Helps Identify NADPH as Biomarker for Ferroptosis Sensitivity.

Publications

Cell-Line Selectivity Improves the Predictive Power of Pharmacogenomic Analyses and Helps Identify NADPH as Biomarker for Ferroptosis Sensitivity.

Similar Datasets

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