دورية أكاديمية
Incorporating SULF1 polymorphisms in a pretreatment CT-based radiomic model for predicting platinum resistance in ovarian cancer treatment.
| العنوان: | Incorporating SULF1 polymorphisms in a pretreatment CT-based radiomic model for predicting platinum resistance in ovarian cancer treatment. |
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| المؤلفون: | Yi X; Department of Radiology, Xiangya Hospital, Central South University, Changsha 410008, PR China; National Clinical Research Center for Geriatric Disorders (Xiangya Hospital), Central South University, Changsha 410008, PR China., Liu Y; Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, PR China; Institute of Clinical Pharmacology, Central South University, Hunan Key Laboratory of Pharmacogenetics, Changsha 410008, PR China; Engineering Research Center of Applied Technology of Pharmacogenomics, Ministry of Education, Changsha 410008, PR China; National Clinical Research Center for Geriatric Disorders, Changsha 410008, PR China., Zhou B; Xiangya School of Medicine, Central South University, Changsha 410013, PR China., Xiang W; Department of Radiology, Hunan Provincial Tumor Hospital, The Affiliated Tumor Hospital of Xiangya Medical School of Central South University, Changsha 410008, PR China., Deng A; Department of Radiology, Hunan Provincial Tumor Hospital, The Affiliated Tumor Hospital of Xiangya Medical School of Central South University, Changsha 410008, PR China., Fu Y; Department of Radiology, Hunan Provincial Tumor Hospital, The Affiliated Tumor Hospital of Xiangya Medical School of Central South University, Changsha 410008, PR China., Zhao Y; Department of Radiology, Hunan Provincial Tumor Hospital, The Affiliated Tumor Hospital of Xiangya Medical School of Central South University, Changsha 410008, PR China., Ouyang Q; Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, PR China; Institute of Clinical Pharmacology, Central South University, Hunan Key Laboratory of Pharmacogenetics, Changsha 410008, PR China; Engineering Research Center of Applied Technology of Pharmacogenomics, Ministry of Education, Changsha 410008, PR China; National Clinical Research Center for Geriatric Disorders, Changsha 410008, PR China., Liu Y; Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, PR China; Institute of Clinical Pharmacology, Central South University, Hunan Key Laboratory of Pharmacogenetics, Changsha 410008, PR China; Engineering Research Center of Applied Technology of Pharmacogenomics, Ministry of Education, Changsha 410008, PR China; National Clinical Research Center for Geriatric Disorders, Changsha 410008, PR China., Sun Z; Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, PR China; Institute of Clinical Pharmacology, Central South University, Hunan Key Laboratory of Pharmacogenetics, Changsha 410008, PR China; Engineering Research Center of Applied Technology of Pharmacogenomics, Ministry of Education, Changsha 410008, PR China; National Clinical Research Center for Geriatric Disorders, Changsha 410008, PR China., Zhang K; Hunan Provincial Tumor Hospital, The Affiliated Tumor Hospital of Xiangya Medical School of Central South University, Changsha 410008, PR China., Li X; Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, PR China; Institute of Clinical Pharmacology, Central South University, Hunan Key Laboratory of Pharmacogenetics, Changsha 410008, PR China; Engineering Research Center of Applied Technology of Pharmacogenomics, Ministry of Education, Changsha 410008, PR China; National Clinical Research Center for Geriatric Disorders, Changsha 410008, PR China., Zeng F; Department of Radiology, Xiangya Hospital, Central South University, Changsha 410008, PR China; National Clinical Research Center for Geriatric Disorders (Xiangya Hospital), Central South University, Changsha 410008, PR China. Electronic address: zengfeiyue@csu.edu.cn., Zhou H; Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, PR China; Institute of Clinical Pharmacology, Central South University, Hunan Key Laboratory of Pharmacogenetics, Changsha 410008, PR China; Engineering Research Center of Applied Technology of Pharmacogenomics, Ministry of Education, Changsha 410008, PR China; National Clinical Research Center for Geriatric Disorders, Changsha 410008, PR China., Chen BT; Department of Diagnostic Radiology, City of Hope National Medical Center, Duarte, CA, United States. |
| المصدر: | Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie [Biomed Pharmacother] 2021 Jan; Vol. 133, pp. 111013. Date of Electronic Publication: 2020 Nov 20. |
| نوع المنشور: | Journal Article; Validation Study |
| اللغة: | English |
| بيانات الدورية: | Publisher: Editions Scientifiques Elsevier Country of Publication: France NLM ID: 8213295 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1950-6007 (Electronic) Linking ISSN: 07533322 NLM ISO Abbreviation: Biomed Pharmacother Subsets: MEDLINE |
| أسماء مطبوعة: | Publication: Paris : Editions Scientifiques Elsevier Original Publication: New York, N.Y. : Masson Pub. USA, Inc., c1982- |
| مواضيع طبية MeSH: | Multidetector Computed Tomography* , Pharmacogenomic Testing* , Pharmacogenomic Variants* , Polymorphism, Single Nucleotide* , Radiation Genomics*, Antineoplastic Agents/*therapeutic use , Drug Resistance, Neoplasm/*genetics , Ovarian Neoplasms/*drug therapy , Platinum Compounds/*therapeutic use , Sulfotransferases/*genetics, Chemotherapy, Adjuvant ; Cytoreduction Surgical Procedures ; Female ; Humans ; Machine Learning ; Middle Aged ; Observer Variation ; Ovarian Neoplasms/diagnostic imaging ; Ovarian Neoplasms/genetics ; Predictive Value of Tests ; Reproducibility of Results ; Retrospective Studies |
| مستخلص: | Objective: Early detection of platinum resistance for ovarian cancer treatment remains challenging. This study aims to develop a machine learning model incorporating genomic data such as Single-Nucleotide Polymorphisms (SNPs) of Human Sulfatase 1 (SULF1) with a CT radiomic model based on pre-treatment CT images, to predict platinum resistance for ovarian cancer (OC) treatment. Methods: A cohort of 102 patients with pathologically confirmed OC was retrospectively enrolled into this study from January 2006 to February 2018. All patients had platinum-based chemotherapy after maximal cyto-reductive surgery. This cohort was separated into two groups according to treatment response, i.e., the group with platinum-resistant disease (PR group) and the group with platinum-sensitive disease (PS group). We genotyped 12 SNPs of SULF1 for all OC patients using Mass Array Method. Radiomic features, SNP data and clinicopathological data of the 102 patients were used to build the differentiation models. The study participants were divided into two cohorts: the training cohort (n = 71) and the validation cohort (n = 31). Feature selection and predictive modeling were performed using least absolute shrinkage and selection operator (LASSO), Random Forest Classifier and Support Vector Machine methods. Model performance for predicting platinum resistance was assessed with respect to its calibration, discrimination, and clinical application. Results: For prediction of platinum resistance, the approach combining the radiomics, clinicopathological data and SNP data demonstrated higher classification efficiency, with an AUC value of 0.993 (95 % CI: 0.83 to 0.98) in the training cohort and 0.967 (95 % CI: 0.83 to 0.98) in validation cohort, than the performance with only the SNPs of SULF1 model (AUC: training, 0.843 [95 %CI: 0.738-0.948]; validation, 0.815 [0.601-1.000]), or with only the radiomic model (AUC: training, 0.874 [95 %CI: 0.789-0.960]; validation, 0.832 [95 %CI: 0.687-0.976]). This integrated approach also showed good calibration and favorable clinical utility. Conclusions: A predictive model combining pretreatment CT radiomics with genomic data such as SNPs of SULF1 could potentially help to predict platinum resistance in ovarian cancer treatment. (Copyright © 2020 The Authors. Published by Elsevier Masson SAS.. All rights reserved.) |
| فهرسة مساهمة: | Keywords: Human sulfatase 1 (SULF1); Ovarian cancer; Pharmacogenomics; Platinum-resistance; Radiogenomics; Radiomics |
| المشرفين على المادة: | 0 (Antineoplastic Agents) 0 (Platinum Compounds) EC 2.8.2.- (SULF1 protein, human) EC 2.8.2.- (Sulfotransferases) |
| تواريخ الأحداث: | Date Created: 20201123 Date Completed: 20210224 Latest Revision: 20210224 |
| رمز التحديث: | 20231215 |
| DOI: | 10.1016/j.biopha.2020.111013 |
| PMID: | 33227705 |
| قاعدة البيانات: | MEDLINE |
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Full Text Finder | تدمد: | 1950-6007 |
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| DOI: | 10.1016/j.biopha.2020.111013 |