Bile carcinoembryonic cell adhesion molecule 6 (CEAM6) as a biomarker of malignant biliary stenoses

Differentiating malignant from nonmalignant biliary stenoses is challenging. This could be facilitated by the measurement of cancer biomarkers in bile. We aimed at (i) identifying new cancer biomarkers by comparative proteomic analysis of bile collected from patients with a malignant or benign biliary stenosis (exploratory phase) and (ii) verifying the accuracy of the newly identified potential biomarkers for discriminating malignant versus nonmalignant biliary stenoses in a larger group of patients (confirmation phase). Overall, 66 proteins were found overexpressed (ratio > 1.5) in at least one cancer condition using proteomic analysis and 7 proteins were increased in all malignant/nonmalignant disease comparisons. Preliminary screening by immunoblot highlighted carcinoembryonic cell adhesion molecule 6 (CEAM6), a cell surface protein overexpressed in many human cancers, as an interesting candidate biomarker. ELISA subsequently confirmed CEAM6 as a potential bile biomarker for distinguishing malignant from benign biliary stenoses with a receiver operating characteristic (ROC) area under the curve (AUC) of 0.92 (specificity 83%, sensitivity 93%, positive predictive value 93%, and negative predictive value 83%). No significant difference in serum CEAM6 level was found between malignant and nonmalignant samples. Combining bile CEAM6 and serum CA19-9 in a panel further improved diagnostic accuracy for malignant stenoses (AUC 0.96, specificity 83%, sensitivity 97%, positive predictive value 93%, and negative predictive value 91%). CEAM6 measurement in bile could be clinically useful to discriminate between malignant and nonmalignant causes of biliary stenosis. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.     

Early Detection of Malignant Pleural Mesothelioma in Asbestos-Exposed Individuals with a Noninvasive Proteomics-Based Surveillance Tool

Background

Malignant pleural mesothelioma (MM) is an aggressive, asbestos-related pulmonary cancer that is increasing in incidence. Because diagnosis is difficult and the disease is relatively rare, most patients present at a clinically advanced stage where possibility of cure is minimal. To improve surveillance and detection of MM in the high-risk population, we completed a series of clinical studies to develop a noninvasive test for early detection.

Methodology/Principal Findings

We conducted multi-center case-control studies in serum from 117 MM cases and 142 asbestos-exposed control individuals. Biomarker discovery, verification, and validation were performed using SOMAmer proteomic technology, which simultaneously measures over 1000 proteins in unfractionated biologic samples. Using univariate and multivariate approaches we discovered 64 candidate protein biomarkers and derived a 13-marker random forest classifier with an AUC of 0.99±0.01 in training, 0.98±0.04 in independent blinded verification and 0.95±0.04 in blinded validation studies. Sensitivity and specificity at our pre-specified decision threshold were 97%/92% in training and 90%/95% in blinded verification. This classifier accuracy was maintained in a second blinded validation set with a sensitivity/specificity of 90%/89% and combined accuracy of 92%. Sensitivity correlated with pathologic stage; 77% of Stage I, 93% of Stage II, 96% of Stage III and 96% of Stage IV cases were detected. An alternative decision threshold in the validation study yielding 98% specificity would still detect 60% of MM cases. In a paired sample set the classifier AUC of 0.99 and 91%/94% sensitivity/specificity was superior to that of mesothelin with an AUC of 0.82 and 66%/88% sensitivity/specificity. The candidate biomarker panel consists of both inflammatory and proliferative proteins, processes strongly associated with asbestos-induced malignancy.

Significance

The SOMAmer biomarker panel discovered and validated in these studies provides a solid foundation for surveillance and diagnosis of MM in those at highest risk for this disease.     

Discovery and identification of Serum Amyloid A protein elevated in lung cancer serum

Two hundred and eighteen serum samples from 175 lung cancer patients and 43 healthy individuals were analyzed by using Surface Enhaced Laser Desorption/Ionization Time of Flight Mass Spectrome-try (SELDI-TOF-MS). The data analyzed by both Biomarker Wizard™ and Biomarker Patterns™ software showed that a protein peak with the molecular weight of 11.6 kDa significantly increased in lung cancer. Meanwhile, the level of this biomarker was progressively increased with the clinical stages of lung cancer. The candidate biomarker was then obtained from tricine one-dimensional sodium dodecyl sulfate-polyacrylamide gel electrophoresis by matching the molecular weight with peaks on WCX2 chips and was identified as Serum Amyloid A protein (SAA) by MALDI/MS-MS and database searching. It was further validated in the same serum samples by immunoprecipitation with commercial SAA antibody. To confirm the SAA differential expression in lung cancer patients, the same set of serum samples was measured by ELISA assay. The result showed that at the cutoff point 0.446 (OD value) on the Receiver Operating Characteristic (ROC) curve, SAA could better discriminate lung cancer from healthy individuals with sensitivity of 84.1% and specificity of 80%. These findings demonstrated that SAA could be characterized as a biomarker related to pathological stages of lung cancer.     

Serum miR-518e-5p is a potential biomarker for secondary imatinib-resistant gastrointestinal stromal tumor

Gastrointestinal stromal tumors (GISTs) are the most common mesenchymal tumor of the intestinal tract. Imatinib is used as first-line therapy for GIST patients; however, secondary imatinib resistance poses a significant clinical challenge. Here, we analyzed serum miRNA expression profiles to identify specific serum miRNAs that could be used as early diagnostic markers. Candidate miRNAs were validated using Taqman quantitative PCR with serum samples from secondary imatinib-resistant GIST patients (n?=?39), imatinib-sensitive GIST patients (n?=?37), and healthy controls (n?=?28). Serum miR-518e-5p and miR-548e levels were higher in secondary imatinib-resistant GIST than imatinib-sensitive GIST patients or healthy controls (P?<?0.0001). However, ROC analysis indicated that only miR-518e-5p could distinguish imatinib-resistant GIST. To discriminate imatinib-resistant from imatinib-sensitive GIST patients, the AUC for serum miR-518e-5p was 0.9938, with 99.8% sensitivity and 82.1% specificity. Serum miR-518e-5p could also discriminate imatinib-resistant GIST patients from healthy controls with 99.9% sensitivity and 97.4% specificity. These data indicate that serum miR-518e-5p is a potentially promising non-invasive biomarker for early detection and diagnosis of secondary imatinib-resistant GIST.     

Colorectal adenoma and cancer detection based on altered methylation pattern of SFRP1, SFRP2, SDC2, and PRIMA1 in plasma samples

Aberrant methylation is one of the most frequent epigenetic alterations that can contribute to tumor formation. Cell-free DNA can originate from tumor tissue; therefore, the evaluation of methylation markers in cell-free DNA can be a promising method for cancer screening. Our aim was to develop a panel of biomarkers with altered methylation along the colorectal adenoma-carcinoma sequence in both colonic tissue and plasma. Methylation of selected CpG sites in healthy colonic (n = 15), adenoma (n = 15), and colorectal cancer (n = 15) tissues was analyzed by pyrosequencing. MethyLight PCR was applied to study the DNA methylation of SFRP1, SFRP2, SDC2, and PRIMA1 gene promoters in 121 plasma and 32 biopsy samples. The effect of altered promoter methylation on protein expression was examined by immunohistochemistry. Significantly higher (P < 0.05) DNA methylation levels were detected in the promoter regions of all 4 markers, both in CRC and adenoma tissues compared with healthy controls. Methylation of SFRP1, SFRP2, SDC2, and PRIMA1 promoter sequences was observed in 85.1%, 72.3%, 89.4%, and 80.9% of plasma samples from patients with CRC and 89.2%, 83.8%, 81.1% and 70.3% from adenoma patients, respectively. When applied as a panel, CRC patients could be distinguished from controls with 91.5% sensitivity and 97.3% specificity [area under the curve (AUC) = 0.978], while adenoma samples could be differentiated with 89.2% sensitivity and 86.5% specificity (AUC = 0.937). Immunohistochemical analysis indicated decreasing protein levels of all 4 markers along the colorectal adenoma-carcinoma sequence. Our findings suggest that this methylation biomarker panel allows non-invasive detection of colorectal adenoma and cancer from plasma samples.     

The diagnostic and prognostic values of microRNA-196a in cancer

MicroRNA-196a (miR-196a) was previously reported to be up-regulated in cancers, and it has the diagnostic and prognostic values in cancers. Whereas, the conclusion was still unclear according to the published data. To assess such roles of miR-196a in cancers, the present study was conducted based on published data and online cancer-related databases. To identify the relevant published data, we searched articles in databases and then the relevant data were extracted to evaluate the correlation between miR-196a expression and diagnosis, prognosis for cancer patients. The pooled results showed that miR-196a was a valuable diagnostic biomarker in cancer (area under curve (AUC) = 0.87, 95% CI: 0.84–0.90; sensitivity (SEN) = 0.73, 95% CI: 0.64–0.81; specificity (SPE) = 0.90, 95% CI: 0.81–0.95), which was consistent with the data from databases (breast cancer: miR-196a-3p: AUC = 0.77, 95% CI: 0.74–0.79; miR-196a-5p: AUC = 0.71, 95% CI: 0.66–0.75; pancreatic cancer: miR-196a-3p: AUC = 0.80, 95% CI: 0.73–0.87; miR-196a-5p: AUC = 0.61, 95% CI: 0.51–0.71). In addition, the pooled result revealed that elevated miR-196a expression in tumor tissues (HR = 2.54, 95% CI: 1.79–3.61, P_{Heterogeneity}=0.000, I² = 75.8%) or serum/plasma (HR = 4.06, 95% CI: 2.67–6.18, P_{Heterogeneity}=0.668, I² = 0%) of patients was an unfavorable survival biomarker, which was consistent with the data from databases (adrenocortical carcinoma: HR = 5.70; esophageal carcinoma: HR = 1.93; brain lower grade glioma: HR = 2.91; {"type":"entrez-geo","attrs":{"text":"GSE40267","term_id":"40267"}}GSE40267: HR = 2.47, 95% CI: 1.2–5.07; TCGA: HR = 1.82, 95% CI: 1.21–2.74; {"type":"entrez-geo","attrs":{"text":"GSE19783","term_id":"19783"}}GSE19783: HR = 4.24, 95% CI: 1–18.06). In short, our results demonstrated that miR-196a in tumor tissue or serum/plasma could be used as a prognostic and diagnostic values for cancers.     

Exploration research on the fusion of multimodal spectrum technology to improve performance of rapid diagnosis scheme for thyroid dysfunction

The spectral fusion by Raman spectroscopy and Fourier infrared spectroscopy combined with pattern recognition algorithms is utilized to diagnose thyroid dysfunction serum, and finds the spectral segment with the highest sensitivity to further advance diagnosis speed. Compared with the single infrared spectroscopy or Raman spectroscopy, the proposal can improve the detection accuracy, and can obtain more spectral features, indicating greater differences between thyroid dysfunction and normal serum samples. For discriminating different samples, principal component analysis (PCA) was first used for feature extraction to reduce the dimension of high‐dimension spectral data and spectral fusion. Then, support vector machine (SVM), back propagation neural network, extreme learning machine and learning vector quantization algorithms were employed to establish the discriminant diagnostic models. The accuracy of spectral fusion of the best analytical model PCA‐SVM, single Raman spectral accuracy and single infrared spectral accuracy is 83.48%, 78.26% and 80%, respectively. The accuracy of spectral fusion is higher than the accuracy of single spectrum in five classifiers. And the diagnostic accuracy of spectral fusion in the range of 2000 to 2500 cm^?1 is 81.74%, which greatly improves the sample measure speed and data analysis speed than analysis of full spectra. The results from our study demonstrate that the serum spectral fusion technique combined with multivariate statistical methods have great potential for the screening of thyroid dysfunction.     

Serum DSG2 as a potential biomarker for diagnosis of esophageal squamous cell carcinoma and esophagogastric junction adenocarcinoma

Background: Exploration of serum biomarkers for early detection of upper gastrointestinal cancer is required. Here, we aimed to evaluate the diagnostic potential of serum desmoglein-2 (DSG2) in patients with esophageal squamous cell carcinoma (ESCC) and esophagogastric junction adenocarcinoma (EJA).Methods: Serum DSG2 levels were measured by enzyme-linked immunosorbent assay (ELISA) in 459 participants including 151 patients with ESCC, 96 with EJA, and 212 healthy controls. Receiver operating characteristic (ROC) curves were used to evaluate diagnostic accuracy.Results: Levels of serum DSG2 were significantly higher in patients with ESCC and EJA than those in healthy controls (P<0.001). Detection of serum DSG2 demonstrated an area under the ROC curve (AUC) value of 0.724, sensitivity of 38.1%, and specificity of 84.8% for the diagnosis of ESCC in the training cohort, and AUC 0.736, sensitivity 58.2%, and specificity 84.7% in the validation cohort. For diagnosis of EJA, measurement of DSG2 provided a sensitivity of 29.2%, a specificity of 90.2%, and AUC of 0.698. Similar results were observed for the diagnosis of early-stage ESCC (AUC 0.715 and 0.722, sensitivity 36.3 and 50%, and specificity 84.8 and 84.7%, for training and validation cohorts, respectively) and early-stage EJA (AUC 0.704, sensitivity 44.4%, and specificity 86.9%). Analysis of clinical data indicated that DSG2 levels were significantly associated with patient age and histological grade in ESCC (P<0.05).Conclusion: Serum DSG2 may be a diagnostic biomarker for ESCC and EJA.     

Multiplexed quantification of 63 proteins in human urine by multiple reaction monitoring-based mass spectrometry for discovery of potential bladder cancer biomarkers

Three common urological diseases are bladder cancer, urinary tract infection, and hematuria. Seventeen bladder cancer biomarkers were previously discovered using iTRAQ - these findings were verified by MRM-MS in this current study. Urine samples from 156 patients with hernia (n=57, control), bladder cancer (n=76), or urinary tract infection/hematuria (n=23) were collected and subjected to multiplexed LC-MRM/MS to determine the concentrations of 63 proteins that are normally considered to be plasma proteins, but which include proteins found in our earlier iTRAQ study. Sixty-five stable isotope-labeled standard proteotypic peptides were used as internal standards for 63 targeted proteins. Twelve proteins showed higher concentrations in the bladder cancer group than in the hernia and the urinary tract infection/hematuria groups, and thus represent potential urinary biomarkers for detection of bladder cancer. Prothrombin had the highest AUC (0.796), with 71.1% sensitivity and 75.0% specificity for differentiating bladder cancer (n=76) from non-cancerous (n=80) patients. The multiplexed MRM-MS data was used to generate a six-peptide marker panel. This six-peptide panel (afamin, adiponectin, complement C4 gamma chain, apolipoprotein A-II precursor, ceruloplasmin, and prothrombin) can discriminate bladder cancer subjects from non-cancerous subjects with an AUC of 0.814, with a 76.3% positive predictive value, and a 77.5% negative predictive value. This article is part of a Special Section entitled: Understanding genome regulation and genetic diversity by mass spectrometry.     

Phosphorylation of elongation factor-2 kinase differentially regulates the enzyme's stability under stress conditions

Chronic infection with hepatitis B virus (HBV) is associated with the majority of cases of hepatocellular carcinoma (HCC) in China. Despite this, there is no effective method for the early detection of HBV-induced liver cancer. Aberrant fucosylation is known to occur during the development of HCC. We, therefore, developed a method of applying matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) to analyze the relationship between aberrant fucosylation, tumor genesis and progression of HBV-associated HCC, and to establish proteomic profiling of serum for early diagnosis of HCC. The MALDI-TOF MS was based on Lens culinaris agglutinin (LCA) lectin magnetic beads and their affinity for separation. The method was applied initially to a 'training' cohort of 111 serum samples obtained from subjects in China with no liver disease (n=26), chronic hepatitis B without cirrhosis (n=21), HBV-infected cirrhosis (n=32), or HBV-infected HCC (n=32). In contrast to previous findings, the results of our profiling analysis demonstrated defucosylation on some of the glycoproteins involved in HCC. HCC was then diagnostically classified in a 'blind test' cohort (n=96). In this group we demonstrated that, HCC could be distinguished from all serum samples, HBV-associated chronic liver disease, and HBV-associated cirrhosis with a sensitivity/specificity of 70%/70%, 78%/74%, and 81%/82%, respectively. When combined with serum alpha-fetoprotein detection (AFP>20 ng/mL), the sensitivity/specificity improved to 78%/88%, 85%/88%, and 89%/91%, respectively. In conclusion, serum glycoprotein fucosylation abnormalities have diverse forms in patients with HCC. MALDI-TOF MS profiling of aberrant serum fucosylated glycoproteins distinguished HCC from controls with high accuracy.     

Discovery and identification of Serum Amyloid A pro-tein elevated in lung cancer serum

Two hundred and eighteen serum samples from 175 lung cancer patients and 43 healthy individuals were analyzed by using Surface Enhaced Laser Desorption/Ionization Time of Flight Mass Spectrome-try (SELDI-TOF-MS). The data analyzed by both Biomarker Wizard&#8482; and Biomarker Patterns&#8482; software showed that a protein peak with the molecular weight of 11.6 kDa significantly increased in lung cancer. Meanwhile,the level of this biomarker was progressively increased with the clinical stages of lung cancer. The candidate biomarker was then obtained from tricine one-dimensional sodium dodecyl sul-fate-polyacrylamide gel electrophoresis by matching the molecular weight with peaks on WCX2 chips and was identified as Serum Amyloid A protein (SAA) by MALDI/MS-MS and database searching. It was further validated in the same serum samples by immunoprecipitation with commercial SAA antibody. To confirm the SAA differential expression in lung cancer patients, the same set of serum samples was measured by ELISA assay. The result showed that at the cutoff point 0.446（OD value）on the Receiver Operating Characteristic (ROC) curve, SAA could better discriminate lung cancer from healthy indi-viduals with sensitivity of 84.1% and specificity of 80%. These findings demonstrated that SAA could be characterized as a biomarker related to pathological stages of lung cancer.     

Rapid analysis of disease state in liquid human serum combining infrared spectroscopy and “digital drying”

In recent years, the diagnosis of brain tumors has been investigated with attenuated total reflection‐Fourier transform infrared (ATR‐FTIR) spectroscopy on dried human serum samples to eliminate spectral interferences of the water component, with promising results. This research evaluates ATR‐FTIR on both liquid and air‐dried samples to investigate “digital drying” as an alternative approach for the analysis of spectra obtained from liquid samples. Digital drying approaches, consisting of water subtraction and least‐squares method, have demonstrated a greater random forest (RF) classification performance than the air‐dried spectra approach when discriminating cancer vs control samples, reaching sensitivity values higher than 93.0% and specificity values higher than 83.0%. Moreover, quantum cascade laser infrared (QCL‐IR) based spectroscopic imaging is utilized on liquid samples to assess the implications of a deep‐penetration light source on disease classification. The RF classification of QCL‐IR data has provided sensitivity and specificity amounting to 85.1% and 75.3% respectively.     

Plasma complement factor H is associated with disease activity of patients with ANCA-associated vasculitis

IntroductionIncreasing evidences have demonstrated that activation of alternative complement pathway plays an important role in the pathogenesis of anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV). The current study aimed to investigate the association of complement factor H (CFH), a key regulator of the alternative complement pathway, with the disease activity of AAV.MethodsPlasma CFH levels were measured in 82 patients with myeloperoxidase (MPO)-AAV in active stage. Of the 82 patients, plasma CFH levels of 27 patients were longitudinally measured. Serum anti-CFH autoantibodies were screened in AAV patients. Circulating complement activation profiles including C4d, Bb, C3a, C5a and soluble C5b-9 of AAV patients in active stage were further detected. Associations between plasma CFH levels and clinicopathological parameters as well as the prognosis were analyzed.ResultsPlasma CFH levels were significantly lower in active AAV patients compared with AAV patients in remission and normal controls. Correlation analysis showed that plasma CFH levels inversely correlated with initial serum creatinine, Birmingham Vasculitis Activity Score (BVAS), proportion of total crescents and cellular crescents in renal specimens, and circulating levels of C3a, C5a and Sc5b-9, meanwhile positively correlated with estimated glomerular filtration rate (eGFR), hemoglobin levels and circulating levels of C3. Moreover, multivariate survival analysis revealed that plasma CFH levels were independently associated with composite outcome of death or end stage renal disease (ESRD) in AAV patients, after adjusting for age, gender, hemoglobin level and urinary protein (P = 0.03, HR 0.85, 95 % CI 0.73–0.98) or adjusting for age, gender, total crescents (%) and urinary protein (P = 0.03, HR 0.85, 95 % CI 0.73–0.98), while not as an independent predictor after adjusting for age, gender, serum creatinine and urinary protein (P = 0.57, HR 0.96, 95 % CI 0.83–1.11).ConclusionIn conclusion, plasma CFH levels are associated with disease activity, and, to some extent, associated with composite outcomes of patients with MPO-ANCA-associated vasculitis.     

Raman spectroscopy‐based detection of RNA viruses in saliva: A preliminary report

Several non‐invasive Raman spectroscopy‐based assays have been reported for rapid and sensitive detection of pathogens. We developed a novel statistical model for the detection of RNA viruses in saliva, based on an unbiased selection of a set of 65 Raman spectral features that mostly attribute to the RNA moieties, with a prediction accuracy of 91.6% (92.5% sensitivity and 88.8% specificity). Furthermore, to minimize variability and automate the downstream analysis of the Raman spectra, we developed a GUI‐based analytical tool “RNA Virus Detector (RVD).” This conceptual framework to detect RNA viruses in saliva could form the basis for field application of Raman Spectroscopy in managing viral outbreaks, such as the ongoing COVID‐19 pandemic. ( http://www.actrec.gov.in/pi-webpages/AmitDutt/RVD/RVD.html ).     

Application of serum protein fingerprint in diagnosis of papillary thyroid carcinoma

To find new biomarkers and establish serum protein fingerprint models for early diagnosis and preoperative staging of papillary thyroid carcinoma, we employed SELDI-TOF-MS and bioinformatics tools. A total of 116 samples were analyzed in this study. The first 80 samples were analyzed by SELDI-TOF-MS and two biomarker patterns were identified. Pattern 1 distinguishes patients with papillary thyroid carcinoma from healthy individuals. Pattern 2 distinguishes papillary thyroid carcinoma from benign thyroid nodes. The remaining 29 samples were analyzed on the second day and served as an independent test set. The analysis of this independent test set yielded a specificity of 80.0% and a sensitivity of 88.9% for pattern 1 and a specificity of 80.0% and a sensitivity of 80.0% for pattern 2. Two additional biomarker patterns were identified to distinguish different stages of the papillary thyroid carcinoma (pattern 3) with an accuracy of 77.1% and different pathological types of thyroid carcinoma (pattern 4) with an accuracy of 88.1%. Taken together, the SELDI-TOF-MS technique combined with bioinformatics approaches can not only facilitate the discovery of better biomarkers for papillary thyroid carcinoma but also provide a useful tool for molecular diagnosis in the future.     

Circulating Level of Neutrophil Extracellular Traps Is Not a Useful Biomarker for Assessing Disease Activity in Antineutrophil Cytoplasmic Antibody-Associated Vasculitis

Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is a group of life-threatening disorders, and frequently affects the kidneys. This study investigated whether the circulating neutrophil extracellular traps (NETs) levels were associated with disease activity of AAV. We collected serum samples from 34 patients with AAV in active stage and 62 patients with AAV in remission. Cell free DNA in serum was quantified using the Quant-iT PicoGreen assay. NETs associated MPO-DNA complexes, citrullinated-histone H3-DNA (cit-H3-DNA) complexes and the concentration of deoxyribonuclease I (DNase I) were quantified using ELISA. The activity of DNase I was quantified using radial enzyme-diffusion method. Associations between circulating levels of NETs with clinico-pathological parameters were analyzed. Serum levels of NETs in active AAV patients were significantly higher than those in healthy controls, and the level of cell free DNA correlated with C-reactive protein (CRP). However, no correlation was found between MPO-DNA complexes or cit-H3-DNA complexes level and CRP. Also there was no significant correlation between NETs level and initial serum creatinine, estimated glomerular filtration rate (eGFR), crescents formation or Birmingham Vasculitis Activity Score (BVAS). Furthermore, there was no significant difference of serum levels of cell free DNA or MPO-DNA complexes between active stage and remission of AAV. In conclusion, circulating levels of NETs cannot be used as a biomarker to assess disease activity in AAV patients.     

Diagnostic Accuracy of Lipopolysaccharide-Binding Protein as Biomarker for Sepsis in Adult Patients: A Systematic Review and Meta-Analysis

IntroductionLipopolysaccharide-binding protein (LBP) is widely reported as a biomarker to differentiate infected from non-infected patients. The diagnostic use of LBP for sepsis remains a matter of debate. We aimed to perform a systematic review and meta-analysis to assess the diagnostic accuracy of serum LBP for sepsis in adult patients.MethodsWe performed a systematic review and meta-analysis to assess the accuracy of LBP for sepsis diagnosis. A systematic search in PubMed and EMBASE for studies that evaluated the diagnostic role of LBP for sepsis through December 2015 was conducted. We searched these databases for original, English language, research articles that studied the diagnostic accuracy between septic and non-septic adult patients. Sensitivity, specificity, and other measures of accuracy, such as diagnostic odds ratio (DOR) and area under the receiver operating characteristic curve (AUC) of LBP were pooled using the Hierarchical Summary Receiver Operating Characteristic (HSROC) method.ResultsOur search returned 53 reports, of which 8 fulfilled the inclusion criteria, accounting for 1684 patients. The pooled sensitivity and specificity of LBP for diagnosis of sepsis by the HSROC method were 0.64 (95% CI: 0.56–0.72) and 0.63 (95% CI: 0.53–0.73), respectively. The value of the DOR was 3.0 (95% CI: 2.0–4.0) and the AUC was 0.68 (95% CI: 0.64–0.72). Meta-regression analysis revealed that cut-off values accounted for the heterogeneity of sensitivity and sample size (> = 150) accounted for the heterogeneity of specificity.ConclusionsBased on the results of our meta-analysis, LBP had weak sensitivity and specificity in the detection of sepsis. LBP may not be practically recommended for clinical utilization as a single biomarker.     

癌胚抗原蛋白芯片的研发及其在肝癌检测中的评价

目的:研究建立一种简便、快速、特异性高、低成本的检测血清中癌胚抗原(CEA)浓度的蛋白芯片,并通过检测肝细胞肝癌(HCC)对其进行评价。方法:采用双抗体夹心法,制备能够形成捕获抗体-抗原-检测抗体的"三明治"结构的蛋白芯片检测血清中CEA浓度。通过用该蛋白芯片检测50例CEA阳性HCC患者血清和56例健康人血清,对其进行盲法验证。结果:以CEA5 ng/m L为阳性判定标准,得出CEA蛋白芯片的灵敏度为92%(46/50),特异度为100%(56/56)。受试者工作特征(ROC)曲线分析显示该蛋白芯片检测出血清CEA的ROC曲线下面积(AUC)为0.960,与0.5相比差异有统计学意义(P0.001),其判定CEA阳性的准确性较高。结论:成功建立检测血清中CEA浓度的蛋白芯片,为下一步研发多种标志物联合检测HCC的蛋白芯片提供候选血清标志物。