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PurposeThe hypoxic microenvironment is involved in the tumorigenesis of ovarian cancer (OC). Therefore, we aim to develop a non-invasive radiogenomics approach to identify a hypoxia pattern with potential application in patient prognostication.MethodsSpecific hypoxia-related genes (sHRGs) were identified based on RNA-seq of OC cell lines cultured with different oxygen conditions. Meanwhile, multiple hypoxia-related subtypes were identified by unsupervised consensus analysis and LASSO–Cox regression analysis. Subsequently, diversified bioinformatics algorithms were used to explore the immune microenvironment, prognosis, biological pathway alteration, and drug sensitivity among different subtypes. Finally, optimal radiogenomics biomarkers for predicting the risk status of patients were developed by machine learning algorithms.ResultsOne hundred forty sHRGs and three types of hypoxia-related subtypes were identified. Among them, hypoxia-cluster-B, gene-cluster-B, and high-risk subtypes had poor survival outcomes. The subtypes were closely related to each other, and hypoxia-cluster-B and gene-cluster-B had higher hypoxia risk scores. Notably, the low-risk subtype had an active immune microenvironment and may benefit from immunotherapy. Finally, a four-feature radiogenomics model was constructed to reveal hypoxia risk status, and the model achieved area under the curve (AUC) values of 0.900 and 0.703 for the training and testing cohorts, respectively.ConclusionAs a non-invasive approach, computed tomography-based radiogenomics biomarkers may enable the pretreatment prediction of the hypoxia pattern, prognosis, therapeutic effect, and immune microenvironment in patients with OC.

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p-Cresol sulfate (pCS) and indoxyl sulfate (IS) are protein-bound uremic toxins that accumulate in patients with chronic kidney disease (CKD). They are closely associated with the mortality rate of CKD and morbidity of cardiovascular disease. In the present study, we established a rapid method for determination of pCS and IS by HPLC-MS/MS in serum samples from 205 CKD patients undergoing peritoneal dialysis. In brief, serum was extracted by acetonitrile and spiked with hydrochlorothiazide. The prepared sample was eluted through HPLC column (Agilent Zorbax SB-C , 3.5 μm, 2.1 × 100 mm) with a mobile phase of acetonitrile and 10 mm ammonium acetate solution (10:90, v/v) for subsequent detection of pCS and IS by MS/MS. The linearity ranged from 50 to 10,000 ng/mL for pCS (r > 0.99), and from 500 to 10,000 ng/mL for IS (r > 0.99). The lower limit of quantification was 50 ng/mL for pCS, and 500 ng/mL for IS. Relative standard deviation (RSD) of intra- and inter-day precision was within ±15%. The results showed that pCS and IS levels were partially correlated with renal function in CKD patients, and IS was directly related to serum creatinine and estimated glomerular filtration rate.

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