DNA Methylation Markers Predict Recurrence-free Interval in Triple-Negative Breast Cancer.
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PROVIDER: PRJNA593505 | ENA |
REPOSITORIES: ENA
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Project description:We lack tools to risk-stratify triple-negative breast cancer (TNBC). Our goal was to develop molecular tools to predict disease recurrence. Methylation array analysis was performed on 110 samples treated by locoregional therapy obtained from Institutional cohorts. Discovered marker sets were then tested by Kaplan Meier analyses in a prospectively collected TNBC cohort of 49 samples from the no chemotherapy arms of IBCSG trials VIII and IX, and by logistic regression in a chemotherapy-treated cohort of 121 TNBCs from combined IBCSG trials and Institutional repositories. High methylation was associated with shorter recurrence-free interval in the no chemotherapy arm of the IBCSG studies, as well as in the chemotherapy-treated patients within the combined Institutional and IBCSG chemotherapy cohorts (100 marker panel, P=0.002; 30 marker panel, P=0.05). Chromosome 19 sites were enriched among these loci. In conclusion, our hypermethylation signatures identify increased recurrence risk independent of whether patients receive chemotherapy.
2019-12-05 | GSE141441 | GEO
Project description:We lack tools to risk-stratify triple-negative breast cancer (TNBC). Our goal was to develop molecular tools to predict disease recurrence. Methylation array analysis was performed on 110 samples treated by locoregional therapy obtained from institutional cohorts. Discovered marker sets were then tested by Kaplan-Meier analyses in a prospectively collected TNBC cohort of 49 samples from the no-chemotherapy arms of IBCSG trials VIII and IX, and by logistic regression in a chemotherapy-treated cohort of 121 TNBCs from combined IBCSG trials and institutional repositories. High methylation was associated with shorter recurrence-free interval in the no-chemotherapy arm of the IBCSG studies, as well as in the chemotherapy-treated patients within the combined institutional and IBCSG chemotherapy cohorts (100 marker panel, p = 0.002; 30 marker panel, p = 0.05). Chromosome 19 sites were enriched among these loci. In conclusion, our hypermethylation signatures identify increased recurrence risk independent of whether patients receive chemotherapy.
| S-EPMC6994477 | biostudies-literature
Project description:Integrative miRNA networks predict prostate cancer recurrence
| PRJNA559178 | ENA
Project description:Background:; One of the main fields of lung cancer research is identifying patients who are at high risk of post-resection recurrence. Individual recurrence risk evaluation by accurate but simple and reproducible method is needed for the clinical practice. Results:; The log-rank test and further selection by our criteria of assayability generated 87 genes from microarray data with significant level 5%. Of these, by PTQ-PCR, the expression of most significant 18 genes was obtained. Using these gene expression information and clinical parameters, by stepwise variable selection method, the recurrence prediction model, which composed of 6 genes (CALB1, MMP7, SLC1A7, GSTA1, CCL19, IFI44) and pStage and cell differentiation, were developed. Validation into the two independent cohorts showed good results of the proposed model (p=0.0314, 0.0305, respectively). The predicted median recurrence-free survival times for each patient were reflected real ones well. Conclusions:; Our method of individualized recurrence risk prediction is accurate, technically simple and reproducible to be used in clinical practice. Therefore, it would be useful in customizing the lung cancer management strategies. Experiment Overall Design: Methods: Experiment Overall Design: At first, we selected the statistically significant genes from the analysis of time-to-recurrence and censoring information from 138 whole-genome wide microarray data. Then, we further reduced the number of genes which could be reliably reproducible by RTQ-PCR. With these assayable genes and clinical parameters, construction of recurrence prediction model by Cox proportional hazard regression was done. After validation into two independent cohorts (n=59 and n=56), the model was transformed into recurrence prediction for the each patient.
2008-06-17 | E-GEOD-8894 | biostudies-arrayexpress
Project description:We compared the prediction powers for disease recurrence between gene set prognostic model and clinical prognostic model developed in a single large population to see whether genetic quantitative approach will have significant prognostic role in early cervical cancer patients who underwent radical hysterectomy with or without adjuvant therapies. Gene set model to predict disease free survival of early cervical cancer was developed using DASL assay dataset from the cohort of early cervical cancer patients who were treated with radical surgery with or without adjuvant therapies at the Samsung Medical Center of Sungkyunkwan University School of Medicine in Seoul, Korea, between January 2002 and September 2008. Clinical prediction model was also developed in the same cohort and the ability of predicting recurrence from each model was compared. Adequate DASL assay profiles were obtained in 300 patients and we selected 12 genes for the gene set model. When the proportions of patients were categorized as having a low or high risk by the prognostic scores using these genes from LOOCV procedure, the Kaplan-Meier curve showed significant different recurrence rate between two groups. Clinical model was developed using FIGO stage as well as post-surgical pathological findings.
2013-05-01 | E-GEOD-44001 | biostudies-arrayexpress
Project description:We compared the prediction powers for disease recurrence between gene set prognostic model and clinical prognostic model developed in a single large population to see whether genetic quantitative approach will have significant prognostic role in early cervical cancer patients who underwent radical hysterectomy with or without adjuvant therapies. Gene set model to predict disease free survival of early cervical cancer was developed using DASL assay dataset from the cohort of early cervical cancer patients who were treated with radical surgery with or without adjuvant therapies at the Samsung Medical Center of Sungkyunkwan University School of Medicine in Seoul, Korea, between January 2002 and September 2008. Clinical prediction model was also developed in the same cohort and the ability of predicting recurrence from each model was compared.
2013-05-01 | GSE44001 | GEO
Project description:Non-Invasive, Label-free Image Approaches to Predict Multimodal Molecular Markers in Pluripotency Assessment
| PRJNA1078901 | ENA
Project description:The DNA methylation value in early-stage hepatocellular carcinoma was undetermined. The Illumina Infinium 450k Human DNA methylation Beadchip was used to identify recurrence-related abbrent CpG methylation. This study was performed in a total of 66 early-stage HCC samples, including 29 recurrence samples and 37 recurrence-free samples
2017-04-30 | E-GEOD-75041 | biostudies-arrayexpress
Project description:The objective of this study is to identify a gene set to predict recurrence of colorectal cancer (CRC) patients. We generated RNA-seq data of 110 primary CRC samples and identified significant genes associated with recurrence of CRC. Through diverse statistical methods including generalized linear model likelihood ratio test, significant 10 genes were identified. In the validation cohorts, a risk classifier consisting of the 10 genes was an independent risk factor in colorectal cancers.
2019-10-29 | GSE107422 | GEO
Project description:Despite surgical treatment of stage I non-small cell lung cancer (NSCLC), one third of patients will eventually have a recurrence. Robust prognostic markers are required to better manage therapy options. MicroRNAs play important roles in human cancers. The purpose of this study is to identify miRNA expression profiles that would better predict prognosis. Small RNAs extracted from formalin-fixed and paraffin-embedded (FFPE) tumor tissues of 357 stage I NSCLC patients were profiled on the human MicroRNA expression profiling V2 panel (Illumina). The expression differences between cancer subtypes were compared by t tests. The association of miRNA expression profile with recurrence free survival (RFS) was assessed using partial Cox regression models. Two miRNA signatures that are highly predictive of RFS were identified. The first contained 32 miRNAs derived from 357 stage I NSCLC patients independent of cancer subtype; while the second containing 27 miRNAs was adenocarcinoma specific. Both of them were validated using FFPE and/or fresh frozen tissues in independent data set with 170 stage I patients. This has important prognostic or therapeutic implications for the management of patients. The identified miRNAs hold great potential as targets for histology-specific treatment or prevention and treatment of recurrent disease. Small RNAs extracted from formalin-fixed and paraffin-embedded (FFPE) tumor tissues of 357 stage I NSCLC patients were profiled on the human MicroRNA expression profiling V2 panel (Illumina).
2012-03-26 | E-GEOD-29135 | biostudies-arrayexpress