Objective·To identify and evaluate novel and reliable non-invasive serological biomarkers for detecting pancreatic ductal adenocarcinoma(PDAC).Methods·Sixty-seven PDAC patients(Ruijin cohort Ⅰ)were recruited at Pancreatic Center,Ruijin Hospital,Shanghai Jiao Tong University School of Medicine,from May 2018 to December 2019.Global proteome profiling of 67 PDAC tumor tissues and 67 matched adjacent normal tissues was performed using mass spectrum.Bioinformatics analysis on the proteomics data was conducted to identify new biomarkers,and receiver operating characteristic(ROC)curves and the area under the curve(AUC)were used to evaluate their value of detecting PDAC.The proteomic and mRNA sequencing data were further downloaded and analysed from the Clinical Proteomic Tumor Analysis Consortium(CPTAC)cohort for validation.In addition,the Ruijin Cohort Ⅱ,consisting of 47 PDAC patients and 75 healthy individuals,was recruited for a case-control study from June 2021 to June 2022.Enzyme-linked immunosorbent assay(ELISA)was used to detect the expression level of new biomarkers in the serum of patients and healthy individuals to evaluate the serological diagnostic values of them.Results·Collagen type Ⅻ α1 chain(COL12A1)was identified as a candidate biomarker for PDAC diagnosis based on differential expression analysis on the proteomic data and was validated to be higher in tumor tissues than in adjacent normal tissues in the CPTAC cohort.In addition,COL12A1 protein levels were significantly higher in the sera of PDAC patients than in those of healthy controls,showing good diagnostic performance with an AUC of 0.82,a sensitivity of 81%,and a specificity of 83%.ROC analysis revealed that COL12A1 improved the performance of carbohydrate antigen 199(CA199)in distinguishing PDAC patients from healthy individuals(AUCCA199=0.91 vs AUCCA199+COL12A1=0.95,P<0.05).Furthermore,COL12A1 also showed excellent ability to distinguish early-stage PDAC patients(stage Ⅰ?Ⅱ)from healthy individuals(AUCCOL12A1=0.83),and significantly improved the AUC of CA199 in early-stage PDAC patients(AUCCA199=0.92 vs AUCCA199+COL12A1=0.97,P<0.05).Conclusion·COL12A1 is a potential serological diagnostic marker that complements CA199 in detecting early-stage PDAC.

Objective·To identify and evaluate novel and reliable non-invasive serological biomarkers for detecting pancreatic ductal adenocarcinoma(PDAC).Methods·Sixty-seven PDAC patients(Ruijin cohort Ⅰ)were recruited at Pancreatic Center,Ruijin Hospital,Shanghai Jiao Tong University School of Medicine,from May 2018 to December 2019.Global proteome profiling of 67 PDAC tumor tissues and 67 matched adjacent normal tissues was performed using mass spectrum.Bioinformatics analysis on the proteomics data was conducted to identify new biomarkers,and receiver operating characteristic(ROC)curves and the area under the curve(AUC)were used to evaluate their value of detecting PDAC.The proteomic and mRNA sequencing data were further downloaded and analysed from the Clinical Proteomic Tumor Analysis Consortium(CPTAC)cohort for validation.In addition,the Ruijin Cohort Ⅱ,consisting of 47 PDAC patients and 75 healthy individuals,was recruited for a case-control study from June 2021 to June 2022.Enzyme-linked immunosorbent assay(ELISA)was used to detect the expression level of new biomarkers in the serum of patients and healthy individuals to evaluate the serological diagnostic values of them.Results·Collagen type Ⅻ α1 chain(COL12A1)was identified as a candidate biomarker for PDAC diagnosis based on differential expression analysis on the proteomic data and was validated to be higher in tumor tissues than in adjacent normal tissues in the CPTAC cohort.In addition,COL12A1 protein levels were significantly higher in the sera of PDAC patients than in those of healthy controls,showing good diagnostic performance with an AUC of 0.82,a sensitivity of 81%,and a specificity of 83%.ROC analysis revealed that COL12A1 improved the performance of carbohydrate antigen 199(CA199)in distinguishing PDAC patients from healthy individuals(AUCCA199=0.91 vs AUCCA199+COL12A1=0.95,P<0.05).Furthermore,COL12A1 also showed excellent ability to distinguish early-stage PDAC patients(stage Ⅰ?Ⅱ)from healthy individuals(AUCCOL12A1=0.83),and significantly improved the AUC of CA199 in early-stage PDAC patients(AUCCA199=0.92 vs AUCCA199+COL12A1=0.97,P<0.05).Conclusion·COL12A1 is a potential serological diagnostic marker that complements CA199 in detecting early-stage PDAC.

Objective:To investigate the application of patient-based real-time quality control (PBRTQC) using exponentially weighted moving average (EWMA) method in internal quality control (IQC) procedures of thyroid function tests.Methods:The serum thyroid function test results of outpatients and inpatients in the Second Hospital of Shandong University from December 1, 2022 to April 30, 2023 were collected. Based on the PBRTQC professional intelligent software system, normality correction, parameter setting, program preparation and real-time operation of test data were carried out. The results of all patients who underwent thyroid function testing between May 1, 2023 and August 31, 2023 were used as the validation dataset. The estimated EWMA value of thyroid function test results and the cumulative coefficient of variation ( CV) over 4 months were calculated. The cumulative CV was compared with the criteria of precision quality standard (1/3TEa) and the CV of IQC. Westgard 2-2s and 1-3s rules were used for alarm setting. The early warning information of the EWMA quality control program were recorded and the potential causes of performance changes were analyzed. DxLab Mind software was used to conduct normal distribution statistics for all data, and the Kolmogorov-Smirnov test was performed on the test results. Results:The items related to serum thyroid function of the patients were all positively skewed. After data correction by Box-Cox method, the PBRTQC data of free triiodothyronine (FT3) and free thyroxine (FT4) were normally distributed, and their cumulative precisions ( CV) of EWMA within 4 months were 6.26% and 2.86%, respectively, both of which were lower than the precision quality target of 8.33%. However, the data of thyroid-stimulating hormone (TSH), thyroid peroxidase antibodies (TPOAb) and thyroglobulin antibody (TgAb) were still positive skewed after modification. The EWMA cumulative CV of TSH, TPOAb and TgAb were 13.16%, 15.31% and 16.77%, which were higher than the precision quality targets of 8.33%, 10% and 10%, respectively. The EWMA QC program can detect different out-of-control alarms, including FT4 false alarms due to sample source concentration and TSH result bias caused by changes in reagent performance. In addition, the EWMA QC program can also detect differences in FT3 results between different DXI800 fully automated chemiluminescence instrument instruments. Conclusions:The EWMA program based on PBRTQC professional intelligent software tools can monitor the patient data of the detection system in real time and continuously, dynamically identify and monitor the errors generated during the analysis process and give early warning. It can be used as a useful supplement for the daily IQC of thyroid function items, especially FT3 and FT4, and has good clinical application value.