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  • American Society of Clinical Oncology (ASCO)  (4)
  • 1
    Online Resource
    Online Resource
    American Society of Clinical Oncology (ASCO) ; 2011
    In:  Journal of Clinical Oncology Vol. 29, No. 9 ( 2011-03-20), p. 1133-1139
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 29, No. 9 ( 2011-03-20), p. 1133-1139
    Abstract: Epigenetic alterations in tissues targeted for cancer play a causal role in carcinogenesis. Changes in DNA methylation in nontarget tissues, specifically peripheral blood, can also affect risk of malignant disease. We sought to identify specific profiles of DNA methylation in peripheral blood that are associated with bladder cancer risk and therefore serve as an epigenetic marker of disease susceptibility. Methods We performed genome-wide DNA methylation profiling on participants involved in a population-based incident case-control study of bladder cancer. Results In a training set of 112 cases and 118 controls, we identified a panel of 9 CpG loci whose profile of DNA methylation was significantly associated with bladder cancer in a masked, independent testing series of 111 cases and 119 controls (P 〈 .0001). Membership in three of the most methylated classes was associated with a 5.2-fold increased risk of bladder cancer (95% CI, 2.8 to 9.7), and a model that included the methylation classification, participant age, sex, smoking status, and family history of bladder cancer was a significant predictor of bladder cancer (area under the curve, 0.76; 95% CI, 0.70 to 0.82). CpG loci associated with bladder cancer and aging had neighboring sequences enriched for transcription-factor binding sites related to immune modulation and forkhead family members. Conclusion These results indicate that profiles of epigenetic states in blood are associated with risk of bladder cancer and signal the potential utility of epigenetic profiles in peripheral blood as novel markers of susceptibility to this and other malignancies.
    Type of Medium: Online Resource
    ISSN: 0732-183X , 1527-7755
    RVK:
    RVK:
    Language: English
    Publisher: American Society of Clinical Oncology (ASCO)
    Publication Date: 2011
    detail.hit.zdb_id: 2005181-5
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  • 2
    In: JCO Clinical Cancer Informatics, American Society of Clinical Oncology (ASCO), , No. 1 ( 2017-11), p. 1-15
    Abstract: Docetaxel has a demonstrated survival benefit for patients with metastatic castration-resistant prostate cancer (mCRPC); however, 10% to 20% of patients discontinue docetaxel prematurely because of toxicity-induced adverse events, and the management of risk factors for toxicity remains a challenge. Patients and Methods The comparator arms of four phase III clinical trials in first-line mCRPC were collected, annotated, and compiled, with a total of 2,070 patients. Early discontinuation was defined as treatment stoppage within 3 months as a result of adverse treatment effects; 10% of patients discontinued treatment. We designed an open-data, crowd-sourced DREAM Challenge for developing models with which to predict early discontinuation of docetaxel treatment. Clinical features for all four trials and outcomes for three of the four trials were made publicly available, with the outcomes of the fourth trial held back for unbiased model evaluation. Challenge participants from around the world trained models and submitted their predictions. Area under the precision-recall curve was the primary metric used for performance assessment. Results In total, 34 separate teams submitted predictions. Seven models with statistically similar area under precision-recall curves (Bayes factor ≤ 3) outperformed all other models. A postchallenge analysis of risk prediction using these seven models revealed three patient subgroups: high risk, low risk, or discordant risk. Early discontinuation events were two times higher in the high-risk subgroup compared with the low-risk subgroup. Simulation studies demonstrated that use of patient discontinuation prediction models could reduce patient enrollment in clinical trials without the loss of statistical power. Conclusion This work represents a successful collaboration between 34 international teams that leveraged open clinical trial data. Our results demonstrate that routinely collected clinical features can be used to identify patients with mCRPC who are likely to discontinue treatment because of adverse events and establishes a robust benchmark with implications for clinical trial design.
    Type of Medium: Online Resource
    ISSN: 2473-4276
    Language: English
    Publisher: American Society of Clinical Oncology (ASCO)
    Publication Date: 2017
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  • 3
    In: JCO Clinical Cancer Informatics, American Society of Clinical Oncology (ASCO), , No. 6 ( 2022-05)
    Abstract: The University of Kansas Cancer Center (KU Cancer Center) recently developed a data warehouse to Organize and Prioritize Trends to Inform KU Cancer Center (OPTIK). The OPTIK database aggregates and standardizes data collected across the bistate catchment area served by the KU Cancer Center. To improve the usability of the OPTIK database, we developed shinyOPTIK, a user-friendly, interactive web application for visualizing cancer risk factor and mortality rate data across the KU Cancer Center Catchment area. METHODS Data in the OPTIK database were first consolidated at the county level across the KU Cancer Center catchment area. Next, the shinyOPTIK development team met with the KU Cancer Center leadership to discuss the needs and priorities of the shinyOPTIK web application. shinyOPTIK was developed under the R Shiny framework and consists of a user interface (ui.R) and a web server (server.R). At present, s hinyOPTIK can be used to generate county-level geographical heatmaps; bar plots of demographic, screening, and risk factors; and line plots to visualize temporal trends at different Rural-Urban Continuum Codes (RUCCs), rural-urban status, metropolitan, or county levels across the KU Cancer Center catchment area. RESULTS Two examples, adult obesity prevalence and lung cancer mortality, are presented to illustrate how researchers can use shinyOPTIK. Each example is accompanied by post hoc visualizations to help explain key observations in terms of rural-urban disparities. CONCLUSION Although shinyOPTIK was developed to improve understanding of spatial and temporal trends across the population served by the KU Cancer Center, our hope is that the description of the steps involved in the creation of this tool along with open-source code for our application provided herein will serve as a guide for other research centers in the development of similar tools.
    Type of Medium: Online Resource
    ISSN: 2473-4276
    Language: English
    Publisher: American Society of Clinical Oncology (ASCO)
    Publication Date: 2022
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  • 4
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 41, No. 16_suppl ( 2023-06-01), p. 6062-6062
    Abstract: 6062 Background: Most patients with R/M SCCHN do not derive durable benefit from standard-of-care anti-PD-1-based therapy. The currently utilized biomarker, PD-ligand-1 combined proportion score is limited by the availability and heterogeneity of tumor samples. There is an unmet need to develop easily accessible peripheral blood-based biomarkers for response to immunotherapy. Methods: We are conducting a prospective multi-center study to identify peripheral blood derived DNA-based methylation biomarkers measured in patients with R/M SCCHN on treatment with FDA-approved anti-PD-1 based therapy. DNA isolated from these samples undergo bisulfite conversion, methylation profiling using Illumina EPIC microarray, and cellular deconvolution to generate peripheral blood immune profiles (PMID 35140201), including granulocytic (g) and monocytic (m) myeloid derived suppressor cell (MDSC) scores. Associations between baseline peripheral blood immune profiles before the start of treatment with progression-free survival (PFS) and overall survival (OS) were evaluated using Kaplan Meier curves and Cox proportional hazards models adjusted for age and sex. Additionally, logistic regression models adjusted for age and sex were utilized to investigate the baseline immune profiles between subgroups of patients who received anti-PD-1 monotherapy with durable clinical benefit for at least 1 year (Group A) versus progression or death within 100 days (Group B) from start of therapy. Results: 61 patients with R/M SCCHN who received anti-PD-1 based therapy as of Oct 31, 2022, were eligible for this preliminary analysis. Mean (SD) age of the entire population was 66.4 (11.8) years, 82% were male. gMDSC score was the only immune parameter with a statistically significant association with PFS (HR 2.6 (1.40 – 4.87) independent of age and sex, with higher scores stratified by median value associated with shorter PFS (Median PFS: 75 days vs. 145 days). Memory CD4 T cells, total CD4 T cells, percentage of T regulatory /CD4 cells, and absolute memory B cells were significantly associated with OS in this population, independent of age and sex (Table). Among the subgroup treated with anti-PD-1 monotherapy, Group A with durable benefit (n = 7, 86% male, mean age: 64.7 years) had significantly higher proportion of CD4 naïve/total CD4 cells (p = 0.03), and significantly lower gMDSC (p = 0.015) & mMDSC (p = 0.000049) scores, compared with Group B (n = 27, 78% male, mean age: 66.4 years). Conclusions: Peripheral blood DNA-based epigenetic immune profiling can recognize clinically relevant methylation biomarkers of benefit from anti-PD-1 therapy before the start of treatment. [Table: see text]
    Type of Medium: Online Resource
    ISSN: 0732-183X , 1527-7755
    RVK:
    RVK:
    Language: English
    Publisher: American Society of Clinical Oncology (ASCO)
    Publication Date: 2023
    detail.hit.zdb_id: 2005181-5
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