Diagnosis of pancreatic adenocarcinoma using protein chip technology

Thymosin β4, a potential marker of malignancy and prognosis in hepatocellular carcinoma

BACKGROUND

The lack of effective early diagnostic markers is an obstacle in clinical diagnosis and treatment of hepatocellular carcinoma (HCC). Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is an increasing popular approach for identification of clinically relevant parameters including biomarkers.

PATIENTS AND METHODS

540 subjects, including 274 HCC, 119 liver cirrhosis, 89 hepatitis, and 58 healthy volunteers were enrolled. MALDI-TOF MS was used to select potential novel biomarkers from serum of HCC patients. Its clinical application was evaluated by experiments and clinical data analysis.

RESULTS

We identified Thymosin β4 (Tβ4) in serum by MALDI-TOF MS. The expression of Tβ4 was detected up-regulating in HCC cells and tissues which enhanced motility of HCC cells. More important, the level of serum Tβ4 was significantly elevated in HCC patients. The AUROC showed the optimum diagnostic cut-off was 1063.6 ng/mL, ROC and 95% CI of Tβ4 (0.908; 0.880-0.935) were larger than that of serum AFP (0.712; 0.662-0.762; p < 0.001). The sensitivity (91.3% vs 83.1%) and specificity (81.2% vs 20.3%) of serum Tβ4 were higher than alpha-fetoprotein (AFP). In AFP-negative HCC, the sensitivity could reach to 80.5%. ROC analysis showed serum Tβ4 had a better performance compared with AFP in distinguishing early-stage and small HCC. Tβ4 is correlated with TNM stage (p = 0.016) and vascular invasion (p = 0.005). Survival analysis indicated the survival time of Tβ4 positive patients was shorter (p < 0.001). Cox analysis suggested Tβ4 could be an independent factor for HCC prognosis.

CONCLUSION

Tβ4 may serve as a novel biomarker for HCC diagnosis and prognosis.

Diagnostic value of serum carbohydrate antigen 19-9 in pancreatic cancer: a systematic review and meta-analysis

Carbohydrate antigen 19-9 (CA19-9) is the most widely used serum biomarker for detecting pancreatic cancer (PC). Since early diagnosis is important for improving PC prognosis, a comprehensive understanding of the diagnostic performance of CA19-9 is critical. This study focused on comprehensive evaluation of the efficacy of CA19-9 in PC diagnosis. Literature research was based on the seven databases. Studies released from January 2002 to January 2022 focused on the efficacy of CA19-9 in the detection of PC were included. Summarized sensitivity, specificity, and sROC/accuracy of discrimination (AUC) were estimated. Potential publication bias was measured with Funnel plot and Egger's test. Meta-regression was performed to detect possible causes of heterogeneity. Subgroup analysis was used to assess the diagnostic efficacy of CA19-9 under different conditions. The study is registered on PROSPERO (CRD42021253861). Seventy-nine studies containing 20 991 participants who met the criteria were included. The pooled sensitivity, specificity, and AUC of CA19-9 in diagnose PC were 72% (95% CI, 71-73%), 86% (95% CI, 85-86%), and 0.8474 (95% CI, 0.8272-0.8676). Subgroup analysis suggested that the diagnostic efficiency of CA19-9 in studies with healthy controls was the highest, followed by intraductal papillary mucinous neoplasm, in pancreatitis and diabetes were consistent with the overall result. Our analysis showed that serum CA19-9 had high and stable diagnostic efficacy for PC (not affected by diabetes). Subgroup analysis showed that serum CA19-9 yielded highest effectiveness in the diagnosis of pancreatic precancerous lesions, which indicated an irreplaceable clinical value in the early detection and warning value for PC.

Screening and identification of post-traumatic stress-related serum factors in children with Wilms' tumors

Wilms' tumors are one of the most common malignant, solid intra-abdominal tumors observed in children. Although potential tumor markers have been found, inflammatory cytokines interfere with the process of specific protein identification. The present study was undertaken to identify post-traumatic stress-related factors of Wilms' tumors and to verify the accuracy of early-stage tumor-specific serum protein markers. Serum samples were screened for differentially-expressed proteins using surface-enhanced laser desorption/ionization-time of flight mass spectrometry (SELDI-TOF-MS). Potential markers were isolated and purified using solid-phase extraction (SPE) and SDS-PAGE. Following enzymatic digestion of the protein samples, the peptide fragments were detected with high performance liquid chromatography-mass spectrometry. The obtained peptide mass fingerprint was searched in the Swiss-Prot protein sequence database via the Mascot search engine. Differentially-expressed proteins were verified using western blot analysis. Differentially-expressed proteins with a mass/charge of 5,816 were screened out using SELDI-TOF-MS, and significant differences between the tumor and control groups, and the trauma and control groups were observed. Target proteins were isolated and purified using SPE and SDS-PAGE. Thioredoxin 1 (Trx1) was found to be differentially expressed. In the serum of children with Wilms' tumors, there was an increase in the level of the post-traumatic stress-related inflammatory factor, Trx1, as compared with the normal control group. Thus, the results of this study indicate that Trx1 presents a potential post-traumatic stress-related factor of Wilms' tumors.

Detection of Serum Protein Biomarkers for the Diagnosis and Staging of Hepatoblastoma

The present study aimed to identify serum biomarkers for the detection of hepatoblastoma (HB). Serum samples were collected from 71 HB patients (stage I, n = 19; stage II, n = 19, stage III, n = 19; and stage IV, n = 14) and 23 age- and sex-matched healthy children. Differential expression of serum protein markers were screened using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS), and the target proteins were isolated and purified using HPLC and identified using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS), SEQUEST, and bioinformatics analysis. Differential protein expression was confirmed by enzyme-linked immunosorbent analysis (ELISA). SELDI-TOF-MS screening identified a differentially expressed protein with an m/z of 9348 Da, which was subsequently identified as Apo A–I; its expression was significantly lower in the HB group as compared to the normal control group (1546.67 ± 757.81 vs. 3359.21 ± 999.36, respectively; p < 0.01). Although the expression level decreased with increasing disease stage, pair-wise comparison revealed significant differences in Apo A–I expression between the normal group and the HB subgroups (p < 0.01). ELISA verified the reduced expression of Apo A–I in the HB group. Taken together, these results suggest that Apo A–I may represent a serum protein biomarker of HB. Further studies will assess the value of using Apo A–I expression for HB diagnosis and staging.

Screening and identification of apolipoprotein A-I as a potential hepatoblastoma biomarker in children, excluding inflammatory factors

The aim of the present study was to identify a child hepatoblastoma serum biomarker that is unaffected by inflammatory factors, with the ultimate aim of finding an effective method for the early diagnosis of hepatoblastoma. The magnetic bead-based weak cation exchange chromatography technique was used to process serum harvested from 30 children with hepatoblastoma, 20 children with systemic inflammatory response syndrome (SIRS) and 20 healthy children. Proteins differentially expressed in SIRS were excluded from consideration as biomarkers for hepatoblastoma. Proteins differentially expressed in hepatoblastoma and healthy controls were screened using surface-enhanced laser desorption/ionization-time of flight-mass spectrometry (SELDI-TOF-MS). Target proteins were purified by SDS-PAGE, and matrix-assisted laser desorption/ionization (MALDI)-TOF-MS was used to determine their amino acid sequences. Protein matches were searched in the SwissProt database. Quantitative polymerase chain reaction (qPCR) and ELISA were employed to confirm the expression of target proteins. Following screening to exclude inflammatory factors, SELDI-TOF-MS revealed a protein with a mass-to-charge ratio of 9,348 Da that was expressed at significantly lower levels in the serum of children with hepatoblastoma compared with healthy controls (P<0.01). Sequence analysis identified this protein as apolipoprotein A-1 (Apo A-I). qPCR and ELISA confirmed that the expression of Apo A-I mRNA and protein were significantly lower in children with hepatoblastoma compared with healthy controls (P<0.05). These results indicate that Apo A-I is a non-inflammatory protein marker for hepatoblastoma with the potential for use in early diagnosis of hepatoblastoma. In addition, the present study demonstrates the feasibility of proteomic screening for the identification of proteins that can serve as markers for a specific tumor.

Analysis of serum exosomal microRNAs and clinicopathologic features of patients with pancreatic adenocarcinoma

BACKGROUND

Altered expression of serum microRNAs (miRNAs) have been reported to correlate with carcinogenesis and progression of pancreatic adenocarcinoma (PC), but descriptions of serum exosomal miRNAs in PC are still lacking. This study was designed to evaluate serum exosomal miRNA levels in PC patients and to investigate their relationships with clinicopathologic features and prognosis.

METHODS

Four miRNAs (miR-17-5p, miR-21, miR-155 and miR-196a) related to PC were selected for examination in our research. Serum miRNA was examined by RT-PCR in a group of 49 patients, including 22 with PCs, 6 with benign pancreatic tumors, 7 with ampullary carcinomas, 6 with chronic pancreatitis and 8 healthy participants. The clinicopathologic data were also collected, and PC patients were classified according to the presence of metastasis, tumor differentiation and advanced stage.

RESULTS

There were low expressions of exosomal miR-155 and miR-196a in serum samples of PC patients when U-6 was used as a control. Serum exosomal miR-17-5p was higher in PC patients than in non-PC patients and healthy participants. High levels of miR-17-5p were significantly correlated with metastasis and advanced stage of PC. The serum exosomal miR-21 level in PC was higher than that in the normal and chronic pancreatitis groups, but was not significantly correlated with PC differentiation and tumor stage.

CONCLUSIONS

There were high expressions of serum exosomal miR-17-5p and miR-21 in PC patients. Examination of serum exosomal microRNA is a useful serum biomarker for PC diagnosis other than serum-free microRNA. It is postulated that exosomal miR-17-5p participates in the progression of PC.

Detection of pancreatic cancer using serum protein profiling

BACKGROUND

Currently, no suitable biomarkers for the early detection of pancreatic cancer (PC) are available. Proteins present in the serum could reflect a state of the disease. In this study, these profiles as a diagnostic marker for PC were evaluated.

METHODS

Serum samples were obtained from PC patients (n = 50 calibration set, n = 39 validation set) and healthy volunteers (n = 110 and n = 75 respectively) according to a uniform standardized collection and processing protocol. For peptide and protein isolation, automated solid-phase extraction (SPE) with Weak Cation Exchange (WCX) magnetic beads (MB) was performed using a 96-channel liquid handling platform. Protein profiles were obtained by mass spectrometry (MS) and evaluated by linear discriminant analysis with double cross-validation.

RESULTS

A discriminating profile for PC has been identified, with a sensitivity of 78% and a specificity of 89% in the calibration set with an area under the curve (AUC) of 90%. These results were validated with a sensitivity of 74% and a specificity of 91% (AUC 90%).

CONCLUSION

Serum profiles of healthy controls and PC can be discrimated between. Further research is warranted to evaluate specificity and whether this biosignature can be used for early detection in a high risk population.

Serum biomarkers identification by mass spectrometry in high-mortality tumors

Cancer affects millions of people worldwide. Tumor mortality is substantially due to diagnosis at stages that are too late for therapies to be effective. Advances in screening methods have improved the early diagnosis, prognosis, and survival for some cancers. Several validated biomarkers are currently used to diagnose and monitor the progression of cancer, but none of them shows adequate specificity, sensitivity, and predictive value for population screening. So, there is an urgent need to isolate novel sensitive, specific biomarkers to detect the disease early and improve prognosis, especially in high-mortality tumors. Proteomic techniques are powerful tools to help in diagnosis and monitoring of treatment and progression of the disease. During the last decade, mass spectrometry has assumed a key role in most of the proteomic analyses that are focused on identifying cancer biomarkers in human serum, making it possible to identify and characterize at the molecular level many proteins or peptides differentially expressed. In this paper we summarize the results of mass spectrometry serum profiling and biomarker identification in high mortality tumors, such as ovarian, liver, lung, and pancreatic cancer.

Identification of serum protein biomarkers in biliary atresia by mass spectrometry and enzyme-linked immunosorbent assay

OBJECTIVE

There is an urgent need to identify noninvasive and convenient biomarkers for early diagnosis of biliary atresia (BA). The aim of the present study was to identify potential protein biomarkers for BA.

METHODS

Serum samples from 42 infants with BA, 38 infants with non-BA neonatal cholestasis (NC), and 36 healthy controls (HC) were randomly divided into a training set and a test set. Serum proteomic profiles were measured using surface-enhanced desorption/ionization time-of-flight mass spectrometry. Candidate biomarkers were purified using high-performance liquid chromatography, identified using liquid chromatography tandem mass spectrometry, and validated using enzyme-linked immunosorbent assay.

RESULTS

A total of 2 protein peaks (m/z with 8697 and 9098  Da) with differential expression levels were found using surface-enhanced desorption/ionization time-of-flight mass spectrometry. These peaks were then analyzed by a support vector machine to construct a classification model in the training set. The sensitivity and specificity of the model were 94.1% and 91.8%, respectively, in the test set. One candidate biomarker (9098  Da) was identified as Apo C-II, and was found to be downregulated in BA samples compared with HC samples, and upregulated in BA samples compared with NC samples. The other candidate biomarker (8697  Da) was identified as Apo C-III, and was found to be upregulated in BA compared with NC and HC.

CONCLUSIONS

Apo C-II and Apo C-III may be potential protein biomarkers of BA and may be useful in distinguishing infants with BA from healthy and NC infants. Further studies with additional populations or using prediagnostic serum are needed to confirm the importance of these findings as diagnostic markers of infants with BA.

Identification of potential serum biomarkers for Wilms tumor after excluding confounding effects of common systemic inflammatory factors

Wilms tumor is the most common pediatric tumor of the kidney. Previous studies have identified several serum biomarkers for Wilms tumor; however, they lack sufficient specificity and may not adequately distinguish Wilms tumor from confounding conditions. To date, no specific protein biomarker has been confirmed for this pediatric tumor. To identify novel serum biomarkers for Wilms tumor, we used proteomic technologies to perform protein profiling of serum samples from pre-surgery and post-surgery patients with Wilms tumor and healthy controls. Some common systemic inflammatory factors were included to control for systemic inflammation. By comparing protein peaks among the three groups of sera, we identified two peaks (11,526 and 4,756 Da) showing significant differential expression not only between pre-surgery and control sera but also between pre-surgery and post-surgery sera. These two peaks were identified as serum amyloid A1 (SAA1) and apolipoprotein C-III (APO C-III). Western blot analysis confirmed that both proteins were expressed at higher levels in pre-surgery sera than in post-surgery and control sera. Using the method of leave-1-out for cross detection, we demonstrate that detection of these two candidate biomarkers had high sensitivity and specificity in discriminating pre-surgery sera from post-surgery and normal control sera. Taken together, these findings suggest that SAA1 and APO C-III are two potential biomarkers for Wilms tumor.

Analysis of urinary proteomic patterns for type 2 diabetic nephropathy by ProteinChip

OBJECTIVE

To detect urinary proteomic profiling of patients with type 2 diabetes by using ProteinChip array technology, for searching new potential biomarkers in early diagnosis of type 2 diabetic nephropathy (T2DN).

METHODS

A total of 95 urine samples from type 2 diabetic patients with normoalbuminuria (DM, n=30), microalbuminuria (DNl, n=25) and macroalbuminuria (DN2, n=20), and healthy controls (n=20) were analyzed by SELDI-TOF-MS (the surface-enhanced laser desorption/ionization time-of-flight mass spectrometry) technology combined with bioinformatics tools.

RESULTS

Over 300 proteins or peptides from 1 to 80 kDa were obtained using ProteinChip. About 40 of them with the m/z values from 2008.78 to 79176.55 Da were significantly differentiated between type 2 diabetic patients and control subjects. Four proteins of mass 2797.03, 4545.77, 4984.03 and 9083.71 Da were selected as the potential biomarkers for T2DN with sensitivity of 88% and specificity of 96.7%.

CONCLUSION

ProteinChip technology can help to discover new biomarkers and provide a novel non-invasive tool to early diagnosis of T2DN.

Detection and identification of potential biomarkers of breast cancer

PURPOSE

Noninvasive and convenient biomarkers for early diagnosis of breast cancer remain an urgent need. The aim of this study was to discover and identify potential protein biomarkers specific for breast cancer.

METHODS

Two hundred and eighty-two (282) serum samples with 124 breast cancer and 158 controls were randomly divided into a training set and a blind-testing set. Serum proteomic profiles were analyzed using SELDI-TOF-MS. Candidate biomarkers were purified by HPLC, identified by LC-MS/MS and validated using ProteinChip immunoassays and western blot technique.

RESULTS

A total of 3 peaks (m/z with 6,630, 8,139 and 8,942 Da) were screened out by support vector machine to construct the classification model with high discriminatory power in the training set. The sensitivity and specificity of the model were 96.45 and 94.87%, respectively, in the blind-testing set. The candidate biomarker with m/z of 6,630 Da was found to be down-regulated in breast cancer patients, and was identified as apolipoprotein C-I. Another two candidate biomarkers (8,139, 8,942 Da) were found up-regulated in breast cancer and identified as C-terminal-truncated form of C3a and complement component C3a, respectively. In addition, the level of apolipoprotein C-I progressively decreased with the clinical stages I, II, III and IV, and the expression of C-terminal-truncated form of C3a and complement component C3a gradually increased in higher stages.

CONCLUSIONS

We have identified a set of biomarkers that could discriminate breast cancer from non-cancer controls. An efficient strategy, including SELDI-TOF-MS analysis, HPLC purification, MALDI-TOF-MS trace and LC-MS/MS identification, has been proved very successful.

Detection and Identification of Potential Biomarkers of Non-small Cell Lung Cancer

The aim of this study was to discover and identify potential protein biomarkers specific for non-small cell lung cancer (NSCLC). Two hundred and thirty five (235) Serum samples with 112 NSCLC and 123 controls were randomly divided into a training set and a blind testing set. Serum proteomic profiles were analyzed using surface-enhanced laser desorption/ionization time-of-flight mass spectroscopy (SELDI-TOF-MS). Candidate protein biomarkers were purified by high Performance Liquid Chromatography (HPLC) and identified by liquid chromatography tandem mass spectrometry (LC-MS/MS) and validated using ProteinChip immunoassays. A total of 3 peaks ( m/z with 6628, 9191 and 11412 Da) were screened out by SVM to construct the classification model with the high discriminatory power in the training set. The sensitivity and specificity of the model were 96.56% and 94.79% respectively in the blind testing set. The candidate biomarker with m/z of 6628 Da was found down-regulated in NSCLC patients, and identified as apolipoprotein C-I. Another two candidate biomarkers (9191 and 11412 Da) were found up-regulated in serum of NSCLC patients and identified as haptoglobin alpha-1 chain and S100A4, respectively. We have identified a set of biomarkers that could discriminate NSCLC from non-cancer controls. An efficient strategy, including SELDI-TOF-MS analysis, HPLC purification, MALDI-TOF-MS trace and LC-MS/MS identification, has been proved successfully.

Discovery and identification of potential biomarkers of papillary thyroid carcinoma

Background

Thyroid carcinoma is the most common endocrine malignancy and a common cancer among the malignancies of head and neck. Noninvasive and convenient biomarkers for diagnosis of papillary thyroid carcinoma (PTC) as early as possible remain an urgent need. The aim of this study was to discover and identify potential protein biomarkers for PTC specifically.

Methods

Two hundred and twenty four (224) serum samples with 108 PTC and 116 controls were randomly divided into a training set and a blind testing set. Serum proteomic profiles were analyzed using SELDI-TOF-MS. Candidate biomarkers were purified by HPLC, identified by LC-MS/MS and validated using ProteinChip immunoassays.

Results

A total of 3 peaks (m/z with 9190, 6631 and 8697 Da) were screened out by support vector machine (SVM) to construct the classification model with high discriminatory power in the training set. The sensitivity and specificity of the model were 95.15% and 93.97% respectively in the blind testing set. The candidate biomarker with m/z of 9190 Da was found to be up-regulated in PTC patients, and was identified as haptoglobin alpha-1 chain. Another two candidate biomarkers (6631, 8697 Da) were found down-regulated in PTC and identified as apolipoprotein C-I and apolipoprotein C-III, respectively. In addition, the level of haptoglobin alpha-1 chain (9190 Da) progressively increased with the clinical stage I, II, III and IV, and the expression of apolipoprotein C-I and apolipoprotein C-III (6631, 8697 Da) gradually decreased in higher stages.

Conclusion

We have identified a set of biomarkers that could discriminate PTC from non-cancer controls. An efficient strategy, including SELDI-TOF-MS analysis, HPLC purification, MALDI-TOF-MS trace and LC-MS/MS identification, has been proved successful.