The identification and characterization of novel N-glycan-based biomarkers in gastric cancer.

BACKGROUND AND AIMS:To identify and validate N-glycan biomarkers in gastric cancer (GC) and to elucidate their underlying molecular mechanism of action. METHODS:In total, 347 individuals, including patients with GC (gastric cancer) or atrophic gastritis and healthy controls, were randomly divided into a training group (n=287) and a retrospective validation group (n=60). Serum N-glycan profiling was achieved with DNA sequencer-assisted/fluorophore-assisted carbohydrate electrophoresis (DSA-FACE). Two diagnostic models were constructed based on the N-glycan profiles using logistic stepwise regression. The diagnostic performance of each model was assessed in retrospective, prospective (n=60), and follow-up (n=40) cohorts. Lectin blotting was performed to determine total core-fucosylation, and the expression of genes involved in core-fucosylation in GC was analyzed by reverse transcriptase-polymerase chain reaction. RESULTS:We identified at least 9 N-glycan structures (peaks) and the levels of core fucose residues and fucosyltransferase were significantly decreased in GC. Two diagnostic models, designated GCglycoA and GCglycoB, were constructed to differentiate GC from control and atrophic gastritis. The areas under the receiver operating characteristic (ROC) curves (AUC) for both GCglycoA and GCglycoB were higher than those for CEA, CA19-9, CA125 and CA72-4. Compared with CEA, CA19-9, CA125 and CA72-4, the sensitivity of GCglycoA increased 29.66%, 37.28%, 56.78% and 61.86%, respectively, and the accuracy increased 10.62%, 16.82%, 25.67% and 28.76%, respectively. For GCglycoB, the sensitivity increased 27.97%, 35.59%, 55.09% and 60.17% and the accuracy increased 21.26%, 24.64%, 31.40% and 34.30% compared with CEA, CA19-9, CA125 and CA72-4, respectively. After curative surgery, the core fucosylated peak (peak 3) and the total core fucosylated N-glycans (sumfuc) were reversed. CONCLUSIONS:The results indicated that the diagnostic models based on N-glycan markers are valuable and noninvasive alternatives for identifying GC. We concluded that decreased core-fucosylation in both tissue and serum from GC patients may result from the decreased expression of fucosyltransferase

Elevated plasma D-dimer levels correlate with long term survival of gastric cancer patients.

BACKGROUND: Increasing evidence indicated plasma D-dimer could be regarded as a marker in cancers, however, its role in gastric cancer is still largely unknown. METHODS: Plasma D-dimer levels were measured by enzyme linked fluorescent immunoassays and evaluated by receiver operating characteristic (ROC) curves for peritoneal dissemination in gastric cancer and healthy subjects. The overall survival (OS) characteristics were determined using Kaplan-Meier and Cox regression analyses. RESULTS: The average of the plasma D-dimer levels for gastric cancer patients was significantly higher than the healthy subjects. A Spearman correlation analysis showed that plasma D-dimer levels correlated with the depth of invasion, lymph node metastasis, peritoneal dissemination, distant metastasis, tumor size and TNM stage. The mean plasma D-dimer level was 2.20 ± 1.51 µg/mL in peritoneal dissemination patients and 1.01 ± 0.79 µg/mL in non-peritoneal dissemination patients (P<0.001). Additionally, the mean plasma D-dimer concentration in patients alive at the final follow-up evaluation was 0.79 ± 0.72 µg/mL,which was significantly lower than the amounts determined for the deceased patients (1.36 ± 1.13 µg/mL) (P<0.001). The AUC of D-dimer was 0.833 (95%CI: 0.780-0.885). At a cut-off value of 1.465 µg/mL, the D-dimer measurement had a sensitivity of 78.00%, a specificity of 83.76% and an accuracy of 82.59%. The median OS was 48.10 months (95% CI: 43.88-52.31) in patients with plasma D-dimer levels less than 1.465 µg/mL and 22.39 months (95% CI: 16.95-27.82) in patients with plasma D-dimer levels exceeding 1.465 µg/mL (log-rank test, P<0.001). Importantly, plasma D-dimer levels exceeding 1.465 µg/mL were significantly associated with poor OS, as determined using a multivariate Cox regression analysis (hazard ratio [HR], 2.28; 95%CI: 1.36-3.81; P = 0.002). CONCLUSIONS: Plasma D-dimer levels are increased in gastric cancer patients and may be a valuable biomarker for peritoneal dissemination, with high D-dimer levels predicting poor outcomes for gastric cancer patients

Effectiveness and safety of acupuncture for postoperative ileus following gastrointestinal surgery: A systematic review and meta-analysis

Background Postoperative ileus (POI) is an important complication of gastrointestinal (GI) surgery. Acupuncture has been increasingly used in treating POI. This study aimed to assess the effectiveness and safety of acupuncture for POI following GI surgery. Methods Seven databases (PubMed, Embase, the Cochrane Library, China National Knowledge Infrastructure, Wan fang Data, VIP Database for Chinese Technical Periodicals, and Chinese Biomedical Literature Database) and related resources were searched from inception to May 30, 2021. Randomized controlled trials (RCTs) reporting the acupuncture for POI in GI were included. The quality of RCTs was assessed by the Cochrane Collaboration Risk of Bias tool, and the certainty of the evidence was evaluated by the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach. A meta-analysis was performed by using RevMan 5.4 software. Results Eighteen RCTs involving 1413 participants were included. The meta-analysis showed that acupuncture could reduce the time to first flatus (TFF) (standardized mean difference [SMD] = −1.14, 95% confidence interval [CI]: −1.54 to −0.73, P Conclusions Acupuncture showed a certain effect in reducing POI following GI surgery with very low-to-moderate quality of evidence. The overall safety of acupuncture should be further validated. More high-quality, large-scale, and multicenter original trials are needed in the future

Receiver operating characteristic (ROC) curve analyses for the prediction of gastric carcinoma (GC).

<div><p>(A) The ROC analysis for distinguishing between GC and control subjects using an N-glycan marker-based GC diagnostic model (GCglycoA), CEA, CA19-9, CA125 or CA72-4. The areas under the ROC curve (AUCs) indicate the diagnostic power: CEA (0.74), CA19-9 (0.76), CA125 (0.72), CA72-4 (0.67) and GCglycoA (0.88). The diagnostic model was constructed by using forward stepwise logistic regression analysis:</p> <p>GCglycoA = -1.072+0.957peak4-0.331peak6+0.646peak9. (B) The ROC analysis for distinguishing between GC and atrophic gastritis using the GCglycoB diagnostic model, CEA, CA19-9, CA125 or CA72-4. The AUCs indicate the diagnostic power: GCglycoB (0.82), CEA(0.65), CA19-9 (0.63), CA125 (0.69) and CA72-4 (0.64). The diagnostic model was constructed by using forward stepwise logistic regression analysis: GCglycoB=5.273-1.371peak2+0.781peak4-0.453peak6+0.221peak9.</p></div

A typical desialylated N-glycan profile of serum protein.

<p>At least 9 peaks can be identified. Peaks 1, 2, 5 and 9 increased (red arrows), and peaks 3, 6 and 7 decreased (green arrows) in gastric carcinoma compared with normal controls. The structures of the N-glycan peaks are shown below the chart. The open circles indicate b-linked galactose; the triangles, a/b-1,3/6-linked fucose; and the solid circles, a/b-linked mannose.</p

The abundance of total core fucosylated residues, α-1,6-fucosyltransferase (Fut8) and guanosine diphosphate (GDP)-fucose transporter (GDP-fuc-Tr) using lectin blotting and reverse transcription-polymerase chain reaction (RT-PCR).

<p>(A) Lectin blots of serum proteins probed with lens culinaris agglutinin A (LCA). The horizontal axis represents the experimental groups: control (n=20), atrophic gastritis (n=20), and gastric carcinoma (GC) (n=20); each pool consists of 3 homogenous samples. The vertical axis indicates the ratio of fucosylated protein to total protein. The difference between the groups was statistically significant (P <0.001). (B) Lectin blotting of tissue proteins probed with LCA. The horizontal axis represents the experimental groups: tumor tissue (n=20) and adjacent tissue (n=20). The vertical axis indicates the ratio of fucosylated protein to total protein. The difference between the groups was not statistically significant (P >0.05). (C) The relative messenger RNA (mRNA) expression of Fut8 in tissue as measured by RT-PCR. The horizontal axis represents the experimental groups: tumor tissue (n=20) and adjacent tissue (n=20). The vertical axis indicates the relative expression of Fut8. The difference between the groups was statistically significant (P <0.001). (D) The relative mRNA abundance of GDP-fuc-Tr in tissue as measured by RT-PCR. The horizontal axis represents the experimental groups: tumor tissue (n=20) and adjacent tissue (n =20). The vertical axis indicates the relative abundance of GDP-fuc-Tr. The difference between the groups was not statistically significant (P >0.05).</p

Demographic and baseline characteristics of the two patient groups.

<p>Demographic and baseline characteristics of the two patient groups.</p

Univariate analysis of the prognostic factors for gastric cancer patients using the Cox regression model.

<p>Univariate analysis of the prognostic factors for gastric cancer patients using the Cox regression model.</p

The diagnostic power of D-dimer in differentiating peritoneal dissemination from the non-peritoneal dissemination in the Prospective Training Group.

<p>Abbreviations: PD, peritoneal dissemination; +, positive; −, negative; PPV, positive predictive value; NPV, negative predictive value;.</p

ROC curve analysis for the prediction of peritoneal dissemination.

<p>The Area under the ROC curve (AUC) indicates the diagnostic power of D-dimer levels (AUC = 0.833).</p