Dataset Information

Novel urinary protein biomarker panel for early diagnosis of gastric cancer.

ABSTRACT:

Background

With the goal of discovering non-invasive biomarkers for early diagnosis of GC, we conducted a case-control study utilising urine samples from individuals with predominantly early GC vs. healthy control (HC).

Methods

Among urine samples from 372 patients, age- and sex-matched 282 patients were randomly divided into three groups: 18 patients in a discovery cohort; 176 patients in a training cohort and 88 patients in a validation cohort.

Results

Among urinary proteins identified in the comprehensive quantitative proteomics analysis, urinary levels of TFF1 (uTFF1) and ADAM12 (uADAM12) were significantly independent diagnostic biomarkers for GC, in addition to Helicobacter pylori status. A urinary biomarker panel combining uTFF1, uADAM12 and H. pylori significantly distinguished between HC and GC patients in both training and validation cohorts. On the analysis for sex-specific biomarkers, this combination panel demonstrated a good AUC of 0.858 for male GC, whereas another combination panel of uTFF1, uBARD1 and H. pylori also provided a good AUC of 0.893 for female GC. Notably, each panel could distinguish even stage I GC patients from HC patients (AUC = 0.850 for males; AUC = 0.845 for females).

Conclusions

Novel urinary protein biomarker panels represent promising non-invasive biomarkers for GC, including early-stage disease.

SUBMITTER: Shimura T

PROVIDER: S-EPMC7686371 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Introduction and objectiveReliable urinary biomarker proteins would be invaluable in identifying children with ureteropelvic junction obstruction (UPJO) as the existing biomarker proteins are inconsistent in their predictive ability. Therefore, the aim of this study was to identify consistent and reliable urinary biomarker proteins in children with UPJO.MethodsTo identify candidate biomarker proteins, total protein from age-restricted (<2 years) and sex-matched (males) control (n = 22) and UPJO (n = 21) urine samples was analyzed by mass spectrometry. Proteins that were preferentially identified in UPJO samples were selected (2-step process) and ranked according to their diagnostic odds ratio value. The top ten proteins with highest odds ratio values were selected and tested individually by ELISA. The total amount of each protein was normalized to urine creatinine and the median with interquartile ranges for control and UPJO samples was determined. Additionally, fold change (UPJO/Control) of medians of the final panel of 5 proteins was also determined. Finally, we calculated the average + 3(SD) and average + 4(SD) values of each of the 5 proteins in the control samples and used it as an arbitrary cutoff to classify individual control and UPJO samples.ResultsIn the first step of our selection process, we identified 171 proteins in UPJO samples that were not detected in the majority of the control samples (16/22 samples, or 72.7%). Of the 171 proteins, only 50 proteins were detected in at least 11/21 (52.4%) of the UPJO samples and hence were selected in the second step. Subsequently, these 50 proteins were ranked according to the odds ratio value and the top 10 ranked proteins were validated by ELISA. Five of the 10 proteins - prostaglandin-reductase-1, ficolin-2, nicotinate-nucleotide pyrophosphorylase [carboxylating], immunoglobulin superfamily-containing leucine-rich-repeat-protein and vascular cell adhesion molecule-1 were present at higher levels in the UPJO samples (fold-change of the median protein concentrations ranging from 2.9 to 9.4) and emerged as a panel of biomarkers to identify obstructive uropathy. Finally, the order of prevalence of the 5 proteins in UPJO samples is PTGR1>FCN2>QPRT>ISLR>VCAM1.ConclusionIn summary, this unique screening strategy led to the identification of previously unknown biomarker proteins that when screened collectively, may reliably distinguish between obstructed vs. non-obstructed infants and may prove useful in identifying informative biomarker panels for biological samples from many diseases.