A panel of autoantibodies against multiple tumor-associated antigens in the immunodiagnosis of esophageal squamous cell cancer

From Basic Science to Clinical Practice: The Role of Cancerous Inhibitor of Protein Phosphatase 2A (CIP2A)/p90 in Cancer

Cancerous inhibitor of protein phosphatase 2A (CIP2A), initially reported as a tumor-associated antigen (known as p90), is highly expressed in most solid and hematological tumors. The interaction of CIP2A/p90, protein phosphatase 2A (PP2A), and c-Myc can hinder the function of PP2A toward c-Myc S62 induction, thus stabilizing c-Myc protein, which represents a potential role of CIP2A/p90 in tumorigeneses such as cell proliferation, invasion, and migration, as well as cancer drug resistance. The signaling pathways and regulation networks of CIP2A/p90 are complex and not yet fully understood. Many previous studies have also demonstrated that CIP2A/p90 can be used as a potential therapeutic cancer target. In addition, the autoantibody against CIP2A/p90 in sera may be used as a promising biomarker in the diagnosis of certain types of cancer. In this Review, we focus on recent advances relating to CIP2A/p90 and their implications for future research.

Anti-CXCL8 Autoantibody: A Potential Diagnostic Biomarker for Esophageal Squamous Cell Carcinoma

Background and Objectives: Esophageal squamous cell carcinoma (ESCC) is one of the most common malignancies. Anti-tumor associated antigen autoantibodies (TAAbs) can be used as biomarkers for tumor detection. The aim of this study was to identify a reliable TAAb as the diagnostic marker for ESCC. Materials and Methods: The Cancer Genome Atlas (TCGA) database was used to screen candidate genes. The mRNA expression of the key gene was then verified by micro array dataset GSE44021 from the Gene Expression Omnibus (GEO) database and the diag nostic value of the corresponding autoantibody to the key gene in ESCC was detected by enzyme-linked im muno sorbent assay (ELISA). Results: CXCL8 was identified as the key gene. The dataset GSE44021 showed that CXCL8 mRNA expression was prominently over-expressed in ESCC tissues compared with normal tissues. ELISA results showed that the level of anti-CXCL8 autoantibody in ESCC patients was significantly higher than in normal controls and the receiver operating char ac teristic (ROC) curve indicated that anti-CXCL8 autoantibody could discriminate ESCC patients from normal controls, with the area under the ROC curve (AUC) for the verification cohort, and the validation cohort were 0.713 and 0.751, respectively. Conclusions: Our study illustrated that anti-CXCL8 autoantibody had good diagnostic value, and may become a candidate biomarker for ESCC.

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.

Evaluating a Panel of Autoantibodies Against Tumor-Associated Antigens in Human Osteosarcoma

Background: The aim of this study was to identify a panel of candidate autoantibodies against tumor-associated antigens in the detection of osteosarcoma (OS) so as to provide a theoretical basis for constructing a non-invasive serological diagnosis method in early immunodiagnosis of OS. Methods: The serological proteome analysis (SERPA) approach was used to select candidate anti-TAA autoantibodies. Then, indirect enzyme-linked immunosorbent assay (ELISA) was used to verify the expression levels of eight candidate autoantibodies in the serum of 51 OS cases, 28 osteochondroma (OC), and 51 normal human sera (NHS). The rank-sum test was used to compare the content of eight autoantibodies in the sera of three groups. The diagnostic value of each indicator for OS was analyzed by an ROC curve. Differential autoantibodies between OS and NHS were screened. Then, a binary logistic regression model was used to establish a prediction logistical regression model. Results: Through ELISA, the expression levels of seven autoantibodies (ENO1, GAPDH, HSP27, HSP60, PDLIM1, STMN1, and TPI1) in OS patients were identified higher than those in healthy patients (p < 0.05). By establishing a binary logistic regression predictive model, the optimal panel including three anti-TAAs (ENO1, GAPDH, and TPI1) autoantibodies was screened out. The sensitivity, specificity, Youden index, accuracy, and AUC of diagnosis of OS were 70.59%, 86.27%, 0.5686, 78.43%, and 0.798, respectively. Conclusion: The results proved that through establishing a predictive model, an optimal panel of autoantibodies could help detect OS from OC or NHS at an early stage, which could be used as a promising and powerful tool in clinical practice.

Autoantibody Against Ferritin Light Chain is a Serum Biomarker for the Detection of Liver Cirrhosis but Not Liver Cancer

Purpose

Ferritin is a protein that plays an important role in iron metabolism, it consists of two subunits: heavy chain (FTH) and light chain (FTL). Elevated expression of FTL is observed in multiple malignancies. Recent studies have found that the frequency of circulating autoantibody against FTL (anti-FTL) increased significantly in hepatocellular carcinoma (HCC). The aim of this study is to verify circulating anti-FTL as a biomarker for the early detection of HCC.

Patients and Methods

A total of 1565 participants were enrolled and assigned to two independent validation cohorts, including 393 HCC patients, 379 liver cirrhosis (LC) patients, 400 chronic hepatitis (CH) patients, and 393 healthy subjects. The concentration of serum anti-FTL was measured by indirect Enzyme-Linked Immunosorbent Assay (ELISA). Kruskal–Wallis test was used to compare anti-FTL concentrations between HCC group and three control groups. Percentile 95 of anti-FTL absorbance value of healthy group was selected as the cut-off value to calculate the positive rate in each group. The area under receiver operating characteristic curve (AUC) was used to quantitatively describe its diagnostic value.

Results

The median concentration of anti-FTL in HCC patients was higher than that in CH patients and healthy subjects, but there was no difference between HCC patients and LC patients. Further analysis showed that there was no difference between early stage LC, advanced stage LC, Child-Pugh A HCC, Child-Pugh B HCC and Child-Pugh C HCC. The positive rate of anti-FTL was 12.2% (48/393) in HCC, 13.5% (51/379) in LC, 6.3% (25/400) in CH and 5.1% (20/393) in healthy subjects, respectively. The AUC of anti-FTL to distinguish LC from CH or healthy subjects were 0.654 (95% CI: 0.615–0.692) and 0.642 (95% CI: 0.602–0.681), respectively.

Conclusion

Anti-FTL is not a biomarker for the early diagnosis of HCC due to specificity deficiency, but may be helpful for the early detection of LC.

Tumor-associated autoantibodies in ESCC screening: Detecting prevalent early-stage malignancy or predicting future cancer risk?

BACKGROUND

To assess potential roles for tumor-associated autoantibodies (TAAs) in esophageal squamous cell carcinoma (ESCC) screening: detecting early-stage malignancy, and predicting future cancer risk.

METHOD

Thirteen candidate autoantibodies identified in previous literatures were measured using multiplex serological assays in sera from cases and matched controls nested in two population-level screening cohorts in China. To evaluate the role of TAAs in detecting prevalent esophageal malignant lesions, an identification set (150 cases vs. 560 controls) and an external validation set (34 cases vs. 121 controls) were established with pre-screening sera collected ≤ 12 months prior to screening-related diagnosis. To explore the role of TAAs in predicting future ESCC risk, an exploration set (105 cases vs. 416 controls) with pre-diagnostic sera collected > 12 months before clinical diagnosis was established. Two models, the questionnaire-based model and full model additionally incorporating TAA markers, were constructed. Area under the receiver operating characteristic curve (AUC) and net reclassification improvement (NRI) were calculated to compare the performance of the two models.

FINDINGS

In the identification set, NY-ESO-1 (OR=2·12, 95% CI=1·02-4·40) and STIP1 (OR=1·83, 95% CI=1·10-3·05) were positively associated with higher risk of esophageal malignancy. Elevated MMP-7 was associated with higher risk of malignancy in females (ORfemale=5·07, 95% CI=1·30-19·71). The estimates in validation set were consistent with these results, but were close to null in exploration set. Integration of selected TAAs improved the performance of questionnaire-based models in detecting prevalent esophageal malignancy (female: AUCfull model=0·745, 95% CI=0·675-0·814, AUCquestionnaire-based model=0·658, 95% CI=0·585-0·732, NRI=0·604, P<0·0001; male: AUCfull model=0·662, 95% CI=0·596-0·728, AUCquestionnaire-based model=0·619, 95% CI=0·548-0·690, NRI=0·357, P=0·0028). This improvement was also seen in validation set, but was not similarly effective in distinguishing long-term incident cases from healthy controls.

INTERPRETATION

Serological autoantibodies against NY-ESO-1, STIP1, and MMP-7 perform well in detecting early-stage esophageal malignancy, but are less effective in predicting future ESCC risks.

FUNDING

This work was supported by the National Science & Technology Fundamental Resources Investigation Program of China (2019FY101102), the National Natural Science Foundation of China (82073626), the National Key R&D Program of China (2016YFC0901404), the Beijing-Tianjin-Hebei Basic Research Cooperation Project (J200016), the Digestive Medical Coordinated Development Center of Beijing Hospitals Authority (XXZ0204), and the Natural Science Foundation of Beijing Municipality (7182033).

Immunodiagnostic Biomarkers for Hepatocellular Carcinoma (HCC): The First Step in Detection and Treatment

Hepatocellular carcinoma (HCC) exerts huge effects on the health burden of the world because of its high mortality and poor prognosis. HCC is often clinically detected late in patients. If HCC could be detected and treated earlier, the survival rate of patients will be greatly improved. Therefore, identifying specific biomarkers is urgent and important for HCC. The liver is also recognized as an immune organ. The occurrence of HCC is related to exacerbation of immune tolerance and/or immunosurveillance escape. The host immune system plays an important role in the recognition and targeting of tumor cells in cancer immunotherapy, as can be seen from the clinical success of immune checkpoint inhibitors and chimeric antigen receptor (CAR) T cells. Thus, there is a pressing medical need to discover immunodiagnostic biomarkers specific to HCC for understanding the pathological mechanisms of HCC, especially for immunotherapy targets. We have reviewed the existing literature to summarize the immunodiagnostic markers of HCC, including autoantibodies against tumor-associated antigens (TAAs) and exosomes, to provide new insights into HCC and early detection of this deadly cancer.

Identifying Novel Biomarkers Ready for Evaluation in Low-Prevalence Populations for the Early Detection of Upper Gastrointestinal Cancers: A Systematic Review

INTRODUCTION

Detecting upper gastrointestinal (GI) cancers in primary care is challenging, as cancer symptoms are common, often non-specific, and most patients presenting with these symptoms will not have cancer. Substantial investment has been made to develop biomarkers for cancer detection, but few have reached routine clinical practice. We aimed to identify novel biomarkers for upper GI cancers which have been sufficiently validated to be ready for evaluation in low-prevalence populations.

METHODS

We systematically searched MEDLINE, Embase, Emcare, and Web of Science for studies published in English from January 2000 to October 2019 (PROSPERO registration CRD42020165005). Reference lists of included studies were assessed. Studies had to report on second measures of diagnostic performance (beyond discovery phase) for biomarkers (single or in panels) used to detect pancreatic, oesophageal, gastric, and biliary tract cancers. We included all designs and excluded studies with less than 50 cases/controls. Data were extracted on types of biomarkers, populations and outcomes. Heterogeneity prevented pooling of outcomes.

RESULTS

We identified 149 eligible studies, involving 22,264 cancer cases and 49,474 controls. A total of 431 biomarkers were identified (183 microRNAs and other RNAs, 79 autoantibodies and other immunological markers, 119 other proteins, 36 metabolic markers, 6 circulating tumour DNA and 8 other). Over half (n = 231) were reported in pancreatic cancer studies. Only 35 biomarkers had been investigated in at least two studies, with reported outcomes for that individual marker for the same tumour type. Apolipoproteins (apoAII-AT and apoAII-ATQ), and pepsinogens (PGI and PGII) were the most promising biomarkers for pancreatic and gastric cancer, respectively.

CONCLUSION

Most novel biomarkers for the early detection of upper GI cancers are still at an early stage of matureness. Further evidence is needed on biomarker performance in low-prevalence populations, in addition to implementation and health economic studies, before extensive adoption into clinical practice can be recommended.

Identification of novel autoantibodies based on the protein chip encoded by cancer-driving genes in detection of esophageal squamous cell carcinoma

The purpose of this study was to identify novel autoantibodies against tumor-associated antigens (TAAbs) and explore the optimal diagnosis model based on the protein chip for detecting esophageal squamous cell carcinoma (ESCC). The human protein chip based on cancer-driving genes was customized to discover candidate TAAbs. Enzyme-linked immunosorbent assay was applied to verify and validate the expression levels of candidate TAAbs in the training cohort (130 ESCC and 130 normal controls) and the validation cohort (125 ESCC and 125 normal controls). Logistic regression analysis was adopted to construct the diagnostic model based on the expression levels of autoantibodies with diagnostic value. Twelve candidate autoantibodies were identified based on the protein chip according to the corresponding statistical methods. In both the training cohort and validation cohort, the expression levels of 10 TAAbs (GNA11, PTEN, P53, SRSF2, GNAS, ACVR1B, CASP8, DAXX, PDGFRA, and MEN1) in ESCC patients were higher than that in normal controls. The panel consisting of GNA11, ACVR1B and P53 demonstrated favorable diagnostic power. The sensitivity, specificity and accuracy of the model in the train cohort and the validation cohort were 71.5%, 93.8%, 79.6% and 77.6%, 81.6%, 70.8%, respectively. In either cohort, there was no correlation between positive rate of the autoantibody panel and clinicopathologic features for ESCC patients. Protein chip technology is an effective method to identify novel TAAbs, and the panel of 3 TAAbs (GNA11, ACVR1B, and P53) is promising for distinguishing ESCC patients from normal individuals.

Tumor-associated antigens and their antibodies in the screening, diagnosis, and monitoring of esophageal cancers

Despite the advances in the treatment and management, esophageal cancers continue to carry a dismal prognosis with an overall 5-year survival rate ranging from 15 to 25%. Delayed onset of symptoms and lack of effective screening methods and guidelines for diagnosis of the early disease contribute to the high mortality rate of esophageal cancers. Detection of esophageal cancer at their early stage is really a challenge for physicians including primary care physicians, gastroenterologists and oncologists. Although imaging, endoscopy and biopsy have been proved to be useful diagnostic tools for esophageal cancers, their diagnostic accuracy is unsatisfactory. In addition, expensive costs, invasiveness and special training operator have limited the clinical application of these tools. Recently, tumor-associated antigens (TAAs) and their antibodies have been reported to be potential markers in esophageal cancer screening, diagnosis, monitoring and prognostication. Because TAAs and their antibodies have the advantages of inexpensive cost, noninvasiveness and easy access, they have attracted much attention as an affordable option for early esophageal cancer diagnosis. In this review, we summarized the advances in TAAs and their antibodies in esophageal cancer screening, diagnosis, monitoring and prognostication.

Serological Biomarkers for Early Detection of Hepatocellular Carcinoma: A Focus on Autoantibodies against Tumor-Associated Antigens Encoded by Cancer Driver Genes

Substantial evidence manifests the occurrence of autoantibodies to tumor-associated antigens (TAAs) in the early stage of hepatocellular carcinoma (HCC), and previous studies have mainly focused on known TAAs. In the present study, protein microarrays based on cancer driver genes were customized to screen TAAs. Subsequently, autoantibodies against selected TAAs in sera were tested by enzyme-linked immunosorbent assays (ELISA) in 1175 subjects of three independent datasets (verification dataset, training dataset, and validation dataset). The verification dataset was used to verify the results from the microarrays. A logistic regression model was constructed within the training dataset; seven TAAs were included in the model and yielded an area under the receiver operating characteristic curve (AUC) of 0.831. The validation dataset further evaluated the model, exhibiting an AUC of 0.789. Remarkably, as the aggravation of HCC increased, the prediction probability (PP) of the model tended to decrease, the trend of which was contrary to alpha-fetoprotein (AFP). For AFP-negative HCC patients, the positive rate of this model reached 67.3% in the training dataset and 50.9% in the validation dataset. Screening TAAs with protein microarrays based on cancer driver genes is the latest, fast, and effective method for finding indicators of HCC. The identified anti-TAA autoantibodies can be potential biomarkers in the early detection of HCC.

Blood-based biomarkers for early detection of esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is a common malignant tumor of the digestive system worldwide, especially in China. Due to the lack of effective early detection methods, ESCC patients often present at an advanced stage at the time of diagnosis, which seriously affects the prognosis of patients. At present, early detection of ESCC mainly depends on invasive and expensive endoscopy and histopathological biopsy. Therefore, there is an unmet need for a non-invasive method to detect ESCC in the early stages. With the emergence of a large class of non-invasive diagnostic tools, serum tumor markers have attracted much attention because of their potential for detection of early tumors. Therefore, the identification of serum tumor markers for early detection of ESCC is undoubtedly one of the most effective ways to achieve early diagnosis and treatment of ESCC. This article reviews the recent advances in the discovery of blood-based ESCC biomarkers, and discusses the origins, clinical applications, and technical challenges of clinical validation of various types of biomarkers.

Prognostic Value of Circulating IGFBP2 and Related Autoantibodies in Children with Metastatic Rhabdomyosarcomas

Insulin-like growth factor-binding protein 2 (IGFBP2) is a tumor-associated protein measurable in patients’ biopsies and blood samples. Increased IGFBP2 expression correlates with tumor severity in rhabdomyosarcoma (RMS). Thus, we examined the plasmatic IGFBP2 levels in 114 RMS patients and 15 healthy controls by ELISA assay in order to evaluate its value as a plasma biomarker for RMS. Additionally, we looked for the presence of a humoral response against IGBFP2 protein measurable by the production of anti-IGFBP2 autoantibodies. We demonstrated that both circulating IGFBP2 protein and autoantibodies were significantly higher in RMS patients with respect to controls and their combination showed a better discriminative capacity. IGFBP2 protein identified metastatic patients with worse event-free survival, whereas both IGFBP2 and anti-IGFBP2 antibodies negatively correlated with overall survival. Our study suggests that IGFBP2 and anti-IGFBP2 antibodies are useful for diagnostic and prognostic purposes, mainly as independent negative prognostic markers in metastatic patients. This is the first study that reports a specific humoral response in RMS plasma samples and proves the value of blood-based biomarkers in improving risk assessment and outcome of metastatic RMS patients.

CD26-Related Serum Biomarkers: sCD26 Protein, DPP4 Activity, and Anti-CD26 Isotype Levels in a Colorectal Cancer-Screening Context

Current screening trials are showing reduction in colorectal cancer incidence and mortality. However, participation rates are often low, and blood-based tests could complement existing screening strategies. CD26 protein (sCD26) and its dipeptidyl peptidase IV (DPP4) enzymatic activity in circulation have been proposed as biomarkers for colorectal cancer and other diseases. However, changes in sCD26 and DPP4 levels show complex degrees of correlation, and their physiological or pathophysiological role is unclear. The aim of this study was to analyse if anti-CD26 autoantibodies are related to sCD26 and DPP4 and to determine their relevance in a context of colorectal cancer screening for complementing the value of sCD26 and DPP4 as biomarkers. These biomarkers were measured in a large prospective cohort (n = 497, except the anti-CD26 antibodies, evaluated in 125 samples) that included a subgroup of individuals that were positive for the faecal immunological occult blood test (FIT) (n = 86) and underwent a colonoscopy (n = 47). We confirmed for the first time higher DPP4 activity in men compared to women (Student's t test, p = 0.002), though this difference between sexes was not seen for serum sCD26 protein. These biomarkers correlated (R = 0.246, p = 0.003) only in women. Correlations were found between anti-CD26 isotypes but not with DPP4 activity or sCD26 concentration, except for a negative correlation only in men between anti-CD26 IgA isotype and sCD26 (R = -0.232, p = 0.044), and an almost significant negative correlation between anti-CD26 IgG and sCD26 limited to FIT-positive men. Interestingly, patients with advanced adenomas displayed the most elevated mean levels of anti-CD26 IgA, IgM, and particularly IgG (Mann-Whitney U test, p = 0.030) in comparison with the other FIT positives without adenomas, and these levels did not correlate with sCD26 or its DPP4 activity. Our preliminary results suggest that the combination of these measures using sex as confounder could perhaps be used as biomarkers for colorectal disease. It also suggests that events affecting the gut influence the levels of anti-CD26 antibodies, which show little or no effect in antigen clearance. These findings should be confirmed in a larger cohort of individuals with colonoscopy. The physiological origin of the sex differences observed should be further addressed.

A panel of autoantibodies against tumor-associated antigens in the early immunodiagnosis of lung cancer

OBJECTIVE

Lung cancer (LC) is one of the most common malignant tumors worldwide with low five-year survival rate due to lack of effective diagnosis. This study aims to find an optimal combination of autoantibodies for detecting of early-stage LC.

METHODS

Nine relatively novel autoantibodies against tumor-associated (TAAs) (PSIP1, TOP2A, ACTR3, RPS6KA5, HMGB3, MMP12, GREM1, ZWINT and NUSAP1) were detected by using ELISA. Diagnostic models were developed by using the training set (n = 644) and further validated in another independent set (n = 248). We also evaluated the diagnostic accuracy of the model to detect benign lung diseases (BLD) from the early-stage lung cancer.

RESULTS

The areas under the receiver operating characteristic curve (AUC) for the model with three TAAs panel (GREM1, HMGB3 and PSIP1) was 0.711(95% CI 0.674-0.746) in the training set and 0.858 (95% CI 0.808-0.899) in the validation set, which demonstrated a higher diagnostic capability. The AUC of this three TAAs model was 0.833 (95%CI 0.780-0.878) in discriminating LC from BLD. This model could identify early-stage LC patients from normal control (NC) individuals, with AUC of 0.687(95% CI 0.634-0.736) in training set and AUC of 0.920(95% CI 0.860-0.960) in validation set, and the overall AUC for early-stage LC was 0.779(95% CI 0.739-0.816) when the training set and validation set were combined.

CONCLUSIONS

The model with three TAAs panel would detect LC with higher effectiveness, and might be potential screening method for the early LC.

Autoantibodies: Potential clinical applications in early detection of esophageal squamous cell carcinoma and esophagogastric junction adenocarcinoma

Esophageal squamous cell carcinoma (ESCC) and esophagogastric junction adenocarcinoma (EGJA) are the two main types of gastrointestinal cancers that pose a huge threat to human health. ESCC remains one of the most common malignant diseases around the world. In contrast to the decreasing prevalence of ESCC, the incidence of EGJA is rising rapidly. Early detection represents one of the most promising ways to improve the prognosis and reduce the mortality of these cancers. Current approaches for early diagnosis mainly depend on invasive and costly endoscopy. Non-invasive biomarkers are in great need to facilitate earlier detection for better clinical management of patients. Tumor-associated autoantibodies can be detected at an early stage before manifestations of clinical signs of tumorigenesis, making them promising biomarkers for early detection and monitoring of ESCC and EGJA. In this review, we summarize recent insights into the iden-tification and validation of tumor-associated autoantibodies for the early detection of ESCC and EGJA and discuss the challenges remaining for clinical validation.

Using a panel of multiple tumor-associated antigens to enhance autoantibody detection for immunodiagnosis of gastric cancer

Autoantibodies against tumor-associated antigens (TAAs) are attractive non-invasive biomarkers for detection of cancer due to their inherently stable in serum. Serum autoantibodies against 9 TAAs from gastric cancer (GC) patients and healthy controls were measured by enzyme-linked immunosorbent assay (ELISA). A logistic regression model predicting the risk of being diagnosed with GC in the training cohort (n = 558) was generated and then validated in an independent cohort (n = 372). Area under the receiver operating characteristic curve (AUC) was used to assess the diagnostic performance. Finally, an optimal prediction model with 6 TAAs (p62, c-Myc, NPM1, 14-3-3ξ, MDM2 and p16) showed a great diagnostic performance of GC with AUC of 0.841 in the training cohort and 0.856 in the validation cohort. The proportion of subjects being correctly defined were 78.49% in the training cohort and 81.99% in the validation cohort. This prediction model could also differentiate early-stage (stage I-II) GC patients from healthy controls with sensitivity/specificity of 76.60%/72.34% and 80.56%/79.17% in the training and validation cohort, respectively, and the overall sensitivity/specificity for early-stage GC were 78.92%/74.70% when being combined with two cohorts. This prediction model presented no significant difference for the diagnostic accuracy between early-stage and late-stage (stage III - IV) GC patients. The model with 6 TAAs showed a high diagnostic performance for GC detection, particularly for early-stage GC. This study further supported the hypothesis that a customized array of multiple TAAs was able to enhance autoantibody detection in the immunodiagnosis of GC.

Circulating levels of autoantibodies against L1-cell adhesion molecule as a potential diagnostic biomarker in esophageal squamous cell carcinoma

BACKGROUND

Esophageal squamous cell carcinoma (ESCC) is a common malignant disease worldwide, especially in China. We aimed to determine the level of autoantibodies against L1CAM in patients with ESCC.

METHODS

Levels of circulating autoantibodies against L1CAM antigens were determined by an enzyme-linked immunosorbent assay in cohort 1 (191 patients with ESCC and 94 normal controls) and validated in cohort 2 (47 patients with ESCC and 47 normal controls). Receiver-operating characteristics were employed to calculate diagnostic accuracy. Cumulative survival time was calculated by the Kaplan-Meier method and analyzed by the log-rank test.

RESULTS

In cohorts 1 and 2, levels of autoantibodies against L1CAM were all significantly higher in sera of patients with ESCC compared to normal controls (P < 0.05). Detection of autoantibodies against L1CAM provided a sensitivity of 26.2%, a specificity of 90.4%, and an area under the curve (AUC) of 0.603 (95% CI 0.535-0.672) in diagnosing ESCC in cohort 1, and a sensitivity of 27.7%, a specificity of 91.5%, and an AUC of 0.628 (95% CI 0.516-0.741). Similar results were observed in the diagnosis of early stage ESCC (25.2% sensitivity, 90.4% specificity, and an AUC of 0.611 (95% CI 0.533-0.689) in cohort 1, and 33.3% sensitivity, 91.5% specificity, and an AUC of 0.636 (95% CI 0.439-0.832) in cohort 2). Moreover, positive rates of autoantibodies against L1CAM had no statistical correlation with clinical outcome of ESCC (P > 0.05).

CONCLUSIONS

Our results suggest that circulating autoantibodies against L1CAM is a potential biomarker for the early detection of ESCC.

Serum Autoantibodies against STIP1 as a Potential Biomarker in the Diagnosis of Esophageal Squamous Cell Carcinoma

Esophageal squamous cell carcinoma (ESCC) remains one of the leading causes of cancer-related mortality around the world. The identification of novel serum biomarkers is required for early detection of ESCC. This study was designed to elucidate whether autoantibodies against STIP1 could be a diagnostic biomarker in ESCC. An enzyme-linked immunosorbent assay was performed to detect serum levels of STIP1 autoantibodies in a training cohort (148 ESCC patients and 111 controls) and a validation cohort (60 ESCC patients and 40 controls). Mann-Whitney's U test showed that ESCC patients in two cohorts have higher levels of autoantibodies against STIP1 when compared to controls (P < 0.001). According to receiver operating characteristic analysis, the sensitivity, specificity, and area under the curve (AUC) of autoantibodies against STIP1 in ESCC were 41.9%, 90.1%, and 0.682 in the training cohort and 40.0%, 92.5%, and 0.710 in the validation cohort, respectively. Moreover, detection of autoantibodies against STIP1 could discriminate early-stage ESCC patients from controls, with sensitivity, specificity, and AUC of 35.7%, 90.1%, and 0.684 in the training cohort and 38.5%, 92.5%, and 0.756 in the validation cohort, respectively. Our findings indicated that autoantibodies against STIP1 might be a useful biomarker for early-stage ESCC detection.