ABSTRACT
Objective:To screen out the differentially regulated metabolites by the analysis of serum metabolic fingerprints, and to provide potential biomarkers for diagnosis of lung cancer.Methods:A total of 228 subjects were enrolled in Changhai Hospital from January 27, 2021 to June 4, 2021, including 97 newly diagnosed lung cancer patients and 131 healthy individuals. Serum samples were collected from the enrolled cohort according to a standard procedure, and the enrolled cohort was divided into a training set and a completely independent validation set by stratified random sampling. The metabolic fingerprints of serum samples were collected by previously developed nano-assisted laser desorption/ionization mass spectrometry (nano-LDI MS). After age and gender matching of the training set, a diagnostic model based on serum metabolic fingerprints was established by machine learning algorithm, and the classification performance of the model was evaluated by receiver operating characteristic (ROC) curve.Results:Serum metabolic fingerprint for each sample was obtained in 1 minute using a novel nano-LDI MS, with consumption of only 1 μl original serum sample. For the training set, the area under ROC curve (AUC) of the constructed classifier for diagnosis of lung cancer was 0.92 (95% CI 0.87-0.97), with a sensitivity of 89% and specificity of 89%. For the independent validation set, the AUC reached 0.96 (95% CI 0.90-1.00) with a sensitivity of 91% and specificity of 94%, which showed no significant decrease compared to training set. We also identified a biomarker panel of 5 metabolites, demonstrating a unique metabolic fingerprint of lung cancer patients. Conclusion:Serum metabolic fingerprints and machine learning were combined to establish a diagnostic model, which can be used to distinguish between lung cancer patients and healthy controls. This work sheds lights on the rapid metabolic analysis for clinical application towards in vitro diagnosis.
ABSTRACT
At present, there are no widely accepted specific biomarkers for the experimental diagnosis of chronic prostatitis / chronic pelvic pain syndrome (CP/CPPS). Recent studies show that many related biomarkers exist in expressed prostatic secretions (EPS) or semen, urine and blood or serum. The monocyte chemotactic protein-1 (MCP-1/CCL-2), macrophage-inflammatory-protein-1 alpha (MIP-1α/CCL-3), interleukin-6 (IL-6), interleukin-8 (IL-8), nerve growth factor (NGF) and B7-H3 in EPS, prostatic exosomal protein (PSEP) in the urine, and prostate-specific antigen (PSA), mean platelet volume (MPV) and macrophage migration inhibitory factor (MIF) in the serum are believed to be of significant clinical and research value, and expected to become important laboratory biomarkers for the diagnosis of CP/CPPS.
Subject(s)
Biomarkers , Chronic Pain/diagnosis , Pelvic Pain/diagnosis , Prostatitis/diagnosis , Humans , MaleABSTRACT
Objective To investigate dynamically characteristics of apparent diffusion coefficient (ADC) of MR diffusion-weighted imaging (DWI) in the rabbit VX-2 tumor model.Methods Forty New Zealand rabbits were included in the study and forty-seven rabbit VX-2 tumor models were raised by implanting directly and intrahepatically after abdominal cavity was opened.DWI was carried out periodically and respectively on seventh,fourteenth,and twenty-first day after implantation.Part samples of VX-2 tumors were studied by pathology.The distinction of VX-2 tumors on DWI was assessed by their ADC values.The statistical significance between different time groups,different area groups,or different b-value groups was calculated using SPSS12.0 software,respectively.Results ADC values of 47 VX-2 tumors in the area of tumor periphery,tumor center,and normal parenchyma around tumor were greater when b-value was 100 s/mm2 than those when b-value was 300 s/mm2 and the distinction of VX-2 tumor ADC in the area of tumor periphery,tumor center,and normal parenchyma around tumor between different b-value groups was significant,respectively( F =17.964,P ＜0.01 ; F =13.986,P ＜0.01 ; F =128.681,P ＜0.01 ).The ADC values in the area of normal liver parenchyma around tumor were greater than those in the area of VX-2 tumor periphery and tumor center when the b-value was 100 or 300 s/mm2.When b-value was the same( 100 or 300 s/mm2),the distinction of VX-2 tumor ADC between different areas was significant( F =176.586,P ＜0.01 ; F =55.089,P ＜0.01 ).The ADC of VX-2 tumor in the area of tumor periphery and tumor center became gradually low from seventh to fourteenth or twenty-first day after implantation and the distinction of ADC between different time groups but the area same (?) was significant( b =100 s/mm2,F =48.211,P ＜0.01 ;b =300 s/mm2,F =20.955,P ＜0.01 ).There were not obvious cellular necrosis in VX-2 tumors on seventh and fourteenth day after implantation but ADC of VX-2 tumor decreased unobviously because of cellular edemata in or around tumors.There were obvious cellular necrotic areas in VX-2 tumors on the twenty-first day after implantation.ADC of viable tumor cells in VX-2 tumors were lower on DWI than that in the area of normal liver parenchyma around tumor and ADC of dead tumor cells in VX-2 tumors were unequal,including high values,equal values,and low values but they were higher than that in the area of normal liver parenchyma around tumor after dead tumor cells had been liquified or had become cystic.Conclusions ADC is able to reflect objectively the diffusion of water molecules in the tumor and to reflect indirectly the degree of the growth and liquified necrosis of a tumor.ADC has an important and potential value in monitoring dynamical tumor growth and in evaluating malignant degree and therapeutic effect.