Serine/threonine-protein kinase D2-mediated phosphorylation of DSG2 threonine 730 promotes esophageal squamous cell carcinoma progression.

Desmoglein-2 (DSG2) is a transmembrane glycoprotein belonging to the desmosomal cadherin family, which mediates cell-cell junctions; regulates cell proliferation, migration, and invasion; and promotes tumor development and metastasis. We previously showed serum DSG2 to be a potential biomarker for the diagnosis of esophageal squamous cell carcinoma (ESCC), although the significance and underlying molecular mechanisms were not identified. Here, we found that DSG2 was increased in ESCC tissues compared with adjacent tissues. In addition, we demonstrated that DSG2 promoted ESCC cell migration and invasion. Furthermore, using interactome analysis, we identified serine/threonine-protein kinase D2 (PRKD2) as a novel DSG2 kinase that mediates the phosphorylation of DSG2 at threonine 730 (T730). Functionally, DSG2 promoted ESCC cell migration and invasion dependent on DSG2-T730 phosphorylation. Mechanistically, DSG2 T730 phosphorylation activated EGFR, Src, AKT, and ERK signaling pathways. In addition, DSG2 and PRKD2 were positively correlated with each other, and the overall survival time of ESCC patients with high DSG2 and PRKD2 was shorter than that of patients with low DSG2 and PRKD2 levels. In summary, PRKD2 is a novel DSG2 kinase, and PRKD2-mediated DSG2 T730 phosphorylation promotes ESCC progression. These findings may facilitate the development of future therapeutic agents that target DSG2 and DSG2 phosphorylation. © 2024 The Pathological Society of Great Britain and Ireland.

Relationship between esophageal squamous cell carcinoma risk and alcohol-related ALDH2 and ADH1B polymorphisms: Evidence from a meta-analysis and Mendelian randomization analysis.

BACKGROUND: Previous studies have shown that ALDH2 and ADH1B genes may be associated with alcohol metabolism and the risk of esophageal squamous cell carcinoma (ESCC), with inconsistent results. This meta-analysis aimed at comprehensively assessing the associations between ALDH2 and ADH1B polymorphisms and the risk of ESCC to synthesize and clarify the evidence. METHODS: We calculated summary estimates of the associations between four genetic variants (rs671 and rs674 in ALDH2, and rs1229984 and rs1042026 in ADH1B) and the ESCC risk across 23 publications in the additive model and allelic model. Venice criteria, Bayesian false discovery probability (BFDP), and false-positive reporting probability (FPRP) were used to assess the strength of epidemiological evidence. Heterogeneity among studies was evaluated by using the Higgin's I2 statistic, and publication bias was assessed by using funnel plots and Begg's test. A Mendelian randomization (MR) analysis was performed to determine the causal association between alcohol intake and esophageal cancer risk. Data from the HaploReg v4.1 and PolyPhen-2 were analyzed for functional annotations. RESULTS: Of the four genetic variants, rs671 of ALDH2 was associated with a significantly reduced risk of ESCC (OR: 0.60, 95% CI: 0.50-0.73), whereas rs1229984 of ADH1B was associated with a significantly increased risk (2.50, 95% CI: 1.70-3.69) in the additive model. In the allelic model, the variant rs1229984 of ADH1B also increased the risk of ESCC (OR: 1.50; 95% CI: 1.21-1.87). The result for the variant rs671 was considered as strong epidemiological evidence. Functional annotations identified that the four variants were related to the enhancer histone marks and motif changes. The other two variants were not associated with the ESCC risk (rs674 of ALDH2 OR: 1.22, 95% CI: 0.71-2.12; rs1042026 of ADH1B OR: 1.28, 95% CI: 0.52-3.14) in the additive model. The MR analysis did not find a causal effect of alcohol on the esophageal cancer risk. CONCLUSIONS: The results showed that ADH1B rs1229984 was significantly associated with an increased the risk of ESCC.

Secreted proteins encoded by super enhancer-driven genes could be promising biomarkers for early detection of esophageal squamous cell carcinoma.

BACKGROUND: Early detection of cancer remains an unmet need in clinical practice, and high diagnostic sensitivity and specificity biomarkers are urgently required. Here, we attempted to identify secreted proteins encoded by super-enhancer (SE)-driven genes as diagnostic biomarkers for esophageal squamous cell carcinoma (ESCC). METHODS: We conducted an integrative analysis of multiple data sets including ChIP-seq data, secretome data, CCLE data and GEO data to screen secreted proteins encoded by SE-driven genes. Using ELISA, we further identified up-regulated secreted proteins through a small size of clinical samples and verified in a multi-centre validation stage (345 in test cohort and 231 in validation cohort). Receiver operating characteristic curves were used to calculate diagnostic accuracy. Artificial intelligence (AI) method named gradient boosting machine (GBM) were applied for model construction to enhance diagnostic accuracy. RESULTS: Serum EFNA1 and MMP13 were identified, and showed significantly higher levels in ESCC patients compared to normal controls. An integrated Five-Biomarker Panel (iFBPanel) established by combining EFNA1, MMP13, carcino-embryonic antigen, Cyfra21-1 and squmaous cell carcinoma antigen had AUCs of 0.881 and 0.880 for ESCC in test and validation cohorts, respectively. Importantly, the iFBPanel also exhibited good performance in detecting early-stage ESCC patients (0.872 and 0.864). Furthermore, the iFBPanel was further empowered by AI technology which showed excellent diagnostic performance in early-stage ESCC (0.927 and 0.907). CONCLUSIONS: Our study suggested that serum EFNA1 and MMP13 could potentially assist ESCC detection, and provided an easy-to-use detection model that might help the diagnosis of early-stage ESCC.

A novel nomogram based on clinical blood indicators for prognosis prediction in curatively resected esophagogastric junction adenocarcinoma patients.

Background: The incidence of esophagogastric junction adenocarcinoma (EJA) patients was increasing but their prognoses were poor. Blood-based predictive biomarkers were associated with prognosis. This study was to build a nomogram based on preoperative clinical laboratory blood biomarkers for predicting prognosis in curatively resected EJA. Methods: Curatively resected EJA patients, recruited between 2003 and 2017 in the Cancer Hospital of Shantou University Medical College, were divided chronologically into the training (n=465) and validation groups (n=289). Fifty markers, involving sociodemographic characteristics and preoperative clinical laboratory blood indicators, were screened for nomogram construction. Independent predictive factors were selected using Cox regression analysis and then were combined to build a nomogram to predict overall survival (OS). Results: Composed of 12 factors, including age, body mass index, platelets, aspartate aminotransferase-to-alanine transaminase ratio, alkaline phosphatase, albumin, uric acid, IgA, IgG, complement C3, complement factor B and systemic immune-inflammation index, we constructed a novel nomogram for OS prediction. In the training group, when combined with TNM system, it acquired a C-index of 0.71, better than using TNM system only (C-index: 0.62, p < 0.001). When applied in the validation group, the combined C-index was 0.70, also better than using TNM system (C-index: 0.62, p < 0.001). Calibration curves exhibited that the nomogram-predicted probabilities of 5-year OS were both in consistency with the actual 5-year OS in both groups. Kaplan-Meier analysis exhibited that patients with higher nomogram scores contained poorer 5-year OS than those with lower scores (p < 0.0001). Conclusions: In conclusion, the novel nomogram built based on preoperative blood indicators might be the potential prognosis prediction model of curatively resected EJA.

Nutritional and immune-related indicators-based Nomogram for predicting overall survival of surgical oral tongue squamous cell carcinoma.

Oral tongue squamous cell carcinoma (OTSCC) is one of the most aggressive oral tumors. The aim of this study was to establish a nomogram to predict overall survival (OS) of TSCC patients after surgery. 169 TSCC patients who underwent surgical treatments in the Cancer Hospital of Shantou University Medical College were included. A nomogram based on Cox regression analysis results was established and internally validated using bootstrap resampling method. pTNM stage, age and total protein, immunoglobulin G, factor B and red blood cell count were identified as independent prognostic factors to create the nomogram. The Akaike Information Criterion and Bayesian Information Criterion of the nomogram were lower than those of pTNM stage, indicating a better goodness-of-fit of the nomogram for predicting OS. The bootstrap-corrected concordance index of nomogram was higher than that of pTNM stage (0.794 vs. 0.665, p = 0.0008). The nomogram also had a good calibration and improved overall net benefit. Based on the cutoff value obtained from the nomogram, the proposed high-risk group had poorer OS than low-risk group (p < 0.0001). The nomogram based on nutritional and immune-related indicators represents a promising tool for outcome prediction of surgical OTSCC.

Association between IGFBP1 expression and cancer risk: A systematic review and meta-analysis.

Background: The results regarding the association between insulin-like growth factor binding protein 1 (IGFBP1) expression and cancer risk were controversial. We performed a meta-analysis to provide novel evidence on relationship between IGFBP1 expression and cancer risk. Methods: PubMed, Embase, Cochrane library and Web of science were searched for relevant cohort and case-control studies exploring the relationship between IGFBP1 expression and cancer risk. Odds ratios (ORs) were pooled in this meta-analysis using random model. Subgroup analyses were performed based on ethnicity, tumor types, publication year, study type, Newcastle-Ottawa Scale (NOS) score and sex. Results: A total of 27 studies including 16 cohort and 11 case-control studies were identified by literature search. No significant association was found between IGFBP1 expression and risk of various cancers [0.90, 95% confidence interval (CI): 0.79, 1.03]. The overall results showed that the pooled ORs were 0.71 (95% CI: 0.57, 0.88] for prostate cancer risk and 0.66 (95%CI: 0.44, 0.99) for colorectal cancer (CRC) risk. However, there is no significant association between IGFBP1 expression and risk for ovarian cancer (1.70, 95%CI: 0.41, 6.99), breast cancer (1.02, 95%CI: 0.85, 1.23), endometrial cancer (1.19, 95%CI: 0.64, 2.21), colorectal adenoma (0.93; 95%CI: 0.81, 1.07), lung cancer (0.81, 95%CI: 0.39, 1.68) or multiple myeloma (1.20, 95%CI: 0.98, 1.47). Conclusion: In this study, compared with individuals at low IGFBP1 expression adjusted for age, smoking status, alcohol intake and so on, risk of the prostate cancer and CRC were decreased among individuals of high IGFBP1 expression. There needs further study to confirm this issue.

A Nomogram Based on Nutrition-Related Indicators and Computed Tomography Imaging Features for Predicting Preoperative Lymph Node Metastasis in Curatively Resected Esophagogastric Junction Adenocarcinoma.

BACKGROUNDS: Preoperative noninvasive tools to predict pretreatment lymph node metastasis (PLNM) status accurately for esophagogastric junction adenocarcinoma (EJA) are few. Thus, the authors aimed to construct a nomogram for predicting PLNM in curatively resected EJA. METHODS: This study enrolled 638 EJA patients who received curative surgery resection and divided them randomly (7:3) into training and validation groups. For nomogram construction, 26 candidate parameters involving 21 preoperative clinical laboratory blood nutrition-related indicators, computed tomography (CT)-reported tumor size, CT-reported PLNM, gender, age, and body mass index were screened. RESULTS: In the training group, Lasso regression included nine nutrition-related blood indicators in the PLNM-prediction nomogram. The PLNM prediction nomogram yielded an area under the receiver operating characteristic (ROC) curve of 0.741 (95 % confidence interval [CI], 0.697-0.781), which was better than that of the CT-reported PLNM (0.635; 95% CI 0.588-0.680; p < 0.0001). Application of the nomogram in the validation cohort still gave good discrimination (0.725 [95% CI 0.658-0.785] vs 0.634 [95% CI 0.563-0.700]; p = 0.0042). Good calibration and a net benefit were observed in both groups. CONCLUSIONS: This study presented a nomogram incorporating preoperative nutrition-related blood indicators and CT imaging features that might be used as a convenient tool to facilitate the preoperative individualized prediction of PLNM for patients with curatively resected EJA.

Serum insulin-like growth factor binding protein 3 as a promising diagnostic and prognostic biomarker in esophagogastric junction adenocarcinoma.

BACKGROUND: Esophagogastric junction adenocarcinoma (EJA) lacks serum biomarkers to assist in diagnosis and prognosis. Here, we aimed to evaluate the diagnostic and prognostic value of serum insulin-like growth factor binding protein 3 (IGFBP3) in EJA patients. METHODS: 320 participants were recruited from November 2016 to January 2020, who were randomly divided into a training cohort (112 normal controls and 102 EJA patients including 24 early-stage patients) and a validation cohort (56 normal controls and 50 EJA patients including 12 early-stage patients). We used receiver operating characteristics curve (ROC) to evaluate diagnostic value. The predictive performance of the nomogram was evaluated by the concordance index (C-index). RESULTS: Serum IGFBP3 levels were significantly lower in early-stage EJA or EJA patients than those in controls (P < 0.01). Measurement of serum IGFBP3 demonstrated an area under curve of 0.819, specificity 90.18% and sensitivity 43.14% in training cohort. Similar results were observed in validation cohort (0.804, 87.50%, 42.00%). Importantly, serum IGFBP3 had a satisfactory diagnostic value for early-stage EJA (0.822, 90.18%, 45.83% and 0.811, 84.48%, 50.00% in training and validation cohorts, respectively). Furthermore, survival analysis demonstrated that lower serum IGFBP3 level was related to poor prognosis (P < 0.05). Cox multivariate analysis revealed that serum IGFBP3 was an independent prognostic factor (HR = 0.468, P = 0.005). Compared with TNM stage, a nomogram based on serum IGFBP3, tumor size and TNM stage indicated an improved C-index in prognostic prediction (0.625 vs. 0.735, P = 0.001). CONCLUSIONS: We found that serum IGFBP3 was a potential diagnostic and prognostic marker of EJA. Meanwhile, the nomogram might predict the prognosis of EJA more accurately and efficiently.

Serum insulin-like growth factor binding protein-3 as a potential biomarker for diagnosis and prognosis of oesophageal squamous cell carcinoma.

BACKGROUND: Insulin-like growth factor binding protein-3 (IGFBP3) has been reported to be related to the risk of some cancers. Here we focussed on serum IGFBP3 as a possible biomarker of diagnosis and prognosis for oesophageal squamous carcinoma (ESCC). METHODS: Enzyme-linked immunosorbent assay (ELISA) was used to measure the serum IGFBP3 level in the training cohort including 136 ESCC patients and 119 normal controls and the validation cohort with 55 ESCC patients and 42 normal controls. The receiver operating characteristics curve (ROC) was used to assess the diagnosis value. Cox proportional hazards model was applied to select factors for survival nomogram construction. RESULTS: Serum IGFBP3 levels were significantly lower in early-stage ESCC or ESCC patients than those in normal controls (p < .05). The specificity and sensitivity of serum IGFBP3 for the diagnosis of ESCC were 95.80% and 50.00%, respectively, with the area under the ROC curve (AUC) of 0.788 in the training cohort. Similar results were observed in the validation cohort (88.10%, 38.18%, and 0.710). Importantly, serum IGFBP3 could also differentiate early-stage ESCC from controls (95.80%, 52.54%, 0.777 and 88.10%, 36.36%, 0.695 in training and validation cohorts, respectively). Furthermore, Cox multivariate analysis revealed that serum IGFBP3 was an independent prognostic risk factor (HR = 2.599, p = .002). Lower serum IGFBP3 level was correlated with reduced overall survival (p < .05). Nomogram based on serum IGFBP3, TNM stage, and tumour size improved the prognostic prediction of ESCC with a concordance index of 0.715. CONCLUSION: We demonstrated that serum IGFBP3 was a potential biomarker of diagnosis and prognosis for ESCC. Meanwhile, the nomogram might help predict the prognosis of ESCC. Key MessageSerum IGFBP3 showed early diagnostic value in oesophageal squamous cell carcinoma with independent cohort validation. Moreover, serum IGFBP3 was identified as an independent prognostic risk factor, which was used to construct a nomogram with improved prognosis ability in oesophageal squamous cell carcinoma.

Prognostic value of IGFBP2 in various cancers: a systematic review and meta-analysis.

BACKGROUND: The prognostic significance of insulin-like growth factor binding protein 2 (IGFBP2) expression has been explored in plenty of studies in human cancers. Because of the controversial results, the meta-analysis was carried out to evaluate the relevance of IGFBP2 expression with the prognosis in various tumors. METHODS: The data searched from four databases (Pubmed, Embase, Cochrane library, and Web of science) was used to calculate pooled hazard ratios (HRs) in this meta-analysis. Subgroup analyses were stratified by ethnicity, cancer type, publication year, Newcastle-Ottawa Scale score, treatments, and populations. RESULTS: Twenty-one studies containing 5560 patients finally met inclusion criteria. IGFBP2 expression was associated with lower overall survival (HR = 1.57, 95% CI = 1.31-1.88) and progression-free survival (HR = 1.18, 95% CI = 1.04-1.34) in cancer patients, but not with disease-free survival (HR = 1.50, 95% CI = 0.91-2.46) or recurrence-free survival (HR = 1.50, 95% CI = 0.93-2.40). The subgroup analyses indicated IGFBP2 overexpression was significantly correlated with overall survival in Asian patients (HR = 1.42, 95% CI = 1.18-1.72), Caucasian patients (HR = 2.20, 95% CI = 1.31-3.70), glioma (HR = 1.36, 95% CI = 1.03-1.79), and colorectal cancer (HR = 2.52, 95% CI = 1.43-4.44) and surgery subgroups (HR = 1.97, 95% CI = 1.50-2.58). CONCLUSION: The meta-analysis showed that IGFBP2 expression was associated with worse prognosis in several tumors, and may serve as a potential prognostic biomarker in cancer patients.

Autoantibodies against p53, MMP-7, and Hsp70 as Potential Biomarkers for Detection of Nonmelanoma Skin Cancers.

Basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) are two predominant histological types of nonmelanoma skin cancer (NMSC), lacking effective early diagnostic markers. In this study, we assessed the diagnostic value of autoantibodies against p53, MMP-7, and Hsp70 in skin SCC and BCC. ELISA was performed to detect levels of autoantibodies in sera from 101 NMSC patients and 102 normal controls, who were recruited from the Cancer Hospital of Shantou University Medical College. A receiver operator characteristic curve was used to evaluate the diagnostic value. The serum levels of autoantibodies against p53, MMP-7, and Hsp70 were higher in NMSCs than those in the normal controls (all P < 0.01). The AUC of the three-autoantibody panel was 0.841 (95% CI: 0.788-0.894) with the sensitivity and specificity of 60.40% and 91.20% when differentiating NMSCs from normal controls. Furthermore, measurement of this panel could differentiate early-stage skin cancer patients from normal controls (AUC: 0.851; 95% CI: 0.793-0.908). Data from Oncomine showed that the level of p53 mRNA was elevated in BCC (P < 0.05), and the Hsp70 mRNA was upregulated in SCC (P < 0.001). This serum three-autoantibody panel might function in assisting the early diagnosis of NMSC.

A Panel of Tumor-associated Autoantibodies for the Detection of Early-stage Breast Cancer.

We previously found a panel of autoantibodies against multiple tumor-associated antigens (BMI-1, HSP70, MMP-7, NY-ESO-1, p53 and PRDX6) that might facilitate early detection of esophagogastric junction adenocarcinoma and esophageal squamous cell carcinoma. Here we aimed at assessing the diagnostic performance of these autoantibodies in breast cancer patients. Enzyme-linked immunosorbent assay was applied to detect sera autoantibodies in 123 breast cancer patients and 123 age-matched normal controls. We adopted logistic regression analysis to identify optimized autoantibody biomarkers for diagnosis and receiver-operating characteristics to analyze diagnostic efficiency. Five of six autoantibodies, BMI-1, HSP70, NY-ESO-1, p53 and PRDX6 demonstrated significantly elevated serum levels in breast cancer compared to normal controls. An optimized panel composed of autoantibodies to BMI-1, HSP70, NY-ESO-1 and p53 showed an area under the curve (AUC) of 0.819 (95% CI 0.766-0.873), 63.4% sensitivity and 90.2% specificity for diagnosing breast cancer. Moreover, this autoantibody panel could differentiate patients with early stage breast cancer from normal controls, with AUC of 0.805 (95% CI 0.743-0.886), 59.6% sensitivity and 90.2% specificity. Our findings indicated that the panel of autoantibodies to BMI-1, HSP70, NY-ESO-1 and p53 as serum biomarkers have the potential to help detect early stage breast cancer.

Nomogram based on nutritional and inflammatory indicators for survival prediction of small cell carcinoma of the esophagus.

OBJECTIVES: Small cell carcinoma of the esophagus (SCCE) is a rare type of esophageal cancer, and the parameters for prediction of SCCE outcome are unclear. This study aimed to construct a nomogram to predict the outcome of SCCE. METHODS: Patients who underwent treatments at the Sun Yat-Sen University Cancer Center were recruited and divided randomly into training and validation cohorts (61 and 32 patients, respectively). A Cox regression analysis was utilized to identify independent prognostic factors to establish a nomogram and predict overall survival (OS) and disease-free survival (DFS). RESULTS: Information on pretreatment nutritional candidate hemoglobin and inflammation-related neutrophil-to-lymphocyte ratio and platelet count were entered into the nomogram. In the training cohort, the concordance index of the nomogram for OS was 0.728, higher than that obtained by tumor/node/metastasis staging (0.614; P = 0.014). A significant difference was observed in the nomogram for DFS (0.668 vs tumor/node/metastasis stage: 0.616; P = 0.014). Similar results were found in the validation group. The decision curve analysis, net reclassification improvement, and integrated discrimination improvement showed moderate improvement of the nomogram in predicting survival. Based on the cut point calculated according to the constructed nomogram, the high-risk group had poorer OS and DFS than the low-risk group in both cohorts (all P < 0.05). Moreover, the DFS of patients receiving surgery in the high-risk group was better than that of patients receiving single radiation therapy or chemotherapy (P = 0.0111). CONCLUSIONS: A nomogram based on nutrition- and inflammation-related indicators was developed to predict the survival of patients with SCCE.

Circulating Levels of L1-cell Adhesion Molecule as a Serum Biomarker for Early Detection of Gastric Cancer and Esophagogastric Junction Adenocarcinoma.

Background: Low serum L1 cell adhesion molecule (L1CAM) has been found in several malignant tumors. Here, we aimed to evaluate the diagnostic potential for serum L1CAM in patients with gastric cancers (GC) and esophagogastric junction adenocarcinoma (EJA). Methods: Enzyme-linked immunosorbent assay (ELISA) was carried out to detect L1CAM level in sera of 148 GC patients, 59 EJA patients and 148 healthy controls. Receiver operating characteristics (ROC) was employed to evaluate diagnostic accuracy. Results: The concentrations of serum L1CAM were significantly lower in GC and EJA than those in healthy controls (P<0.001). Detection of L1CAM provided a sensitivity of 83.1%, a specificity of 62.2%, and an area under the curve (AUC) of 0.769 (95% CI: 0.715-0.823) in diagnosing GC, and a sensitivity of 66.1%, a specificity of 62.2%, and an AUC of 0.672 (95% CI: 0.590-0.755) in diagnosing EJA. Similar results were observed in the diagnosis of early-stage GC (0.681 (95%CI: 0.596-0.766)) and early-stage EJA (0.674 (95%CI: 0.528-0.820)). Analysis of clinical data showed that the levels of L1CAM were significantly associated with lymph node metastasis in GC (P<0.05). Conclusions: Our study showed that serum L1CAM might be a diagnostic biomarker for GC and EJA.

Blood-based Markers in the Prognostic Prediction of Esophagogastric Junction Cancer.

Esophagogastric junction cancer poses a great threat to human beings both in western countries and East Asia, especially in China and Japan, and its incidence has increased during recent decades. The 5-year survival rate of esophagogastric junction cancer is quite poor compared with that of other gastric cancer sites. Until now, the traditional TNM staging system has been widely used in clinical practice for prognosis. However, the TNM system is based on pathology after surgical resection or radiology using CT and MRI, not on blood markers. Evidently, some research has been reported concentrated on the prognostic value of blood-based markers with the character of non-invasive and non-radioactive in EJA. Hematologic, biochemical and coagulation parameters could be obtained from clinical data and utilized to analyze their prognostic values. Tumor-associated antigens, microRNAs and circulating tumor cells have also been reported in EJC prognosis. In this article, we review research focused on blood-based markers to evaluate their prognostic value in esophagogastric junction cancer, especially its main subtype adenocarcinoma.

Serum IGFBP-1 as a potential biomarker for diagnosis of early-stage upper gastrointestinal tumour.

BACKGROUND: Early detection would improve upper gastrointestinal cancer prognosis. We aimed to identify serum protein biomarker for the detection of early-stage upper gastrointestinal cancer. METHODS: We performed a three-tiered study including 2028 participants from three medical centres. First, we applied two different antibody arrays to screen candidate serum proteins that increased in 20 patients with oesophageal squamous cell carcinoma (ESCC) compared with 20 normal controls. We then evaluated the selected protein by enzyme-linked immunosorbent assay in 1064 participants including 731 upper gastrointestinal cancer patients (287 ESCCs, 237 oesophagogastric junction adenocarcinomas (EJAs), and 207 stomach cancers) and 333 normal controls. The diagnostic value of the selected protein was finally validated in two independent cohorts of ESCC patients and controls (n=472 and 452, respectively). The receiver operating characteristic was used to calculate diagnostic accuracy. FINDINGS: Serum insulin-like growth factor binding protein-1 (IGFBP-1) identified in both antibody arrays showed significantly elevated levels in upper gastrointestinal cancers, compared with normal controls. Serum IGFBP-1 provided high diagnostic accuracy of early-stage ESCC, EJA, stomach and cancer (areas under the curve: 0·898, 0·936 and 0·864, respectively). This protein maintained diagnostic performance for early-stage ESCC in independent cohorts 1 and 2 (0·849 and 0·911, respectively). Additionally, serum levels of IGFBP-1 dropped significantly after surgical resection of primary tumours, compared with the corresponding pre-operative ESCC samples (p < 0·05). INTERPRETATION: Serum IGFBP-1 represents a promising diagnostic biomarker to detect early-stage upper gastrointestinal cancer.

Serum Insulin-Like Growth Factor Binding Protein 7 as a Potential Biomarker in the Diagnosis and Prognosis of Esophagogastric Junction Adenocarcinoma.

Background/Aims: Esophagogastric junction adenocarcinoma (EJA) is a malignant tumor associated with high morbidity and has attracted increasing attention due to a rising incidence and low survival rate. Pathological biopsy is the gold standard for diagnosis, but noninvasive and effective tests are lacking, resulting in diagnoses at advanced stages. This study explored the diagnostic value of insulin-like growth factor binding protein 7 (IGFBP7) in EJA. Methods: A total of 120 EJA patients and 88 normal controls were recruited, and their serum levels of IGFBP7 were measured by enzymelinked immunosorbent assay. Receiver operating characteristic (ROC) curve analysis was used to assess the diagnostic value, and Pearson chi-square analysis was used to evaluate the correlation between IGFBP7 and clinical parameters. Kaplan- Meier survival analysis was carried out to assess the effect of IGFBP7 on overall survival (OS). Results: The levels of IGFBP7 were higher in both early- and late-stage EJA patients than in normal controls (p<0.001). The area under the ROC curve for EJA patients was 0.794 (95% confidence interval [CI], 0.733 to 0.854), with a cutoff value of 2.716 ng/mL, a sensitivity of 63.3% (95% CI, 54.0% to 71.8%) and a specificity of 90.9% (95% CI, 82.4% to 95.7%). For the diagnosis of early-stage EJA, the same cutoff value and specificity were obtained, but the sensitivity of IGFBP7 was 54.3% (95% CI, 36.9% to 70.8%). Patients with low IGFBP7 protein expression had lower OS than those with high expression (p=0.034). The multivariate analysis showed that IGFBP7 is an independent prognostic factor for EJA (p=0.011). Conclusions: Serum IGFBP7 acts as a potential diagnostic and prognostic marker for EJA.

Combined detection of serum autoantibodies as diagnostic biomarkers in esophagogastric junction adenocarcinoma.

BACKGROUND: We previously found that autoantibodies against a panel of six tumor-associated antigens (p53, NY-ESO-1, MMP-7, Hsp70, PRDX6 and Bmi-1) may aid in early detection of esophageal squamous cell carcinoma. Here we aimed to evaluate the diagnostic value of this autoantibody panel in esophagogastric junction adenocarcinoma (EJA) patients. METHODS: Serum autoantibody levels were measured by enzyme-linked immunosorbent assay in a training cohort and a validation cohort. We used receiver-operating characteristics (ROC) to calculate diagnostic accuracy. RESULTS: We recruited 169 normal controls and 122 EJA patients to the training cohort, and 80 normal controls and 70 EJA patients to the validation cohort. Detection of the autoantibody panel demonstrated an area under the curve (AUC) of 0.818, sensitivity 59.0% and specificity 90.5% in training cohort, and AUC 0.815, sensitivity 61.4% and specificity 90.0% in validation cohort in the diagnosis of EJA. Measurement of the autoantibody panel could distinguish early stage EJA patients from normal controls (AUC 0.786 and 0.786, sensitivity 50.0% and 56.0%, and specificity 90.5% and 90.0%, for training and validation cohorts, respectively). Moreover, a restricted panel consisting of autoantibodies against p53, NY-ESO-1 and Bmi-1 exhibited similar diagnostic performance for EJA (AUC 0.814 and 0.823, sensitivity 53.5% and 60.0%, and specificity 90.5% and 93.7%, for training and validation cohorts, respectively) and early stage EJA (AUC 0.744 and 0.773, sensitivity 55.6% and 52.0%, and specificity 90.5% and 93.7%, for training and validation cohorts, respectively). CONCLUSIONS: Autoantibodies against an optimized TAA panel as serum biomarkers appear to help identify the present of early stage EJA.

Robust Dimension Reduction for Clustering With Local Adaptive Learning.

In pattern recognition and data mining, clustering is a classical technique to group matters of interest and has been widely employed to numerous applications. Among various clustering algorithms, K-means (KM) clustering is most popular for its simplicity and efficiency. However, with the rapid development of the social network, high-dimensional data are frequently generated, which poses a considerable challenge to the traditional KM clustering as the curse of dimensionality. In such scenarios, it is difficult to directly cluster such high-dimensional data that always contain redundant features and noises. Although the existing approaches try to solve this problem using joint subspace learning and KM clustering, there are still the following limitations: 1) the discriminative information in low-dimensional subspace is not well captured; 2) the intrinsic geometric information is seldom considered; and 3) the optimizing procedure of a discrete cluster indicator matrix is vulnerable to noises. In this paper, we propose a novel clustering model to cope with the above-mentioned challenges. Within the proposed model, discriminative information is adaptively explored by unifying local adaptive subspace learning and KM clustering. We extend the proposed model using a robust l2,1 -norm loss function, where the robust cluster centroid can be calculated in a weighted iterative procedure. We also explore and discuss the relationships between the proposed algorithm and several related studies. Extensive experiments on kinds of benchmark data sets demonstrate the advantage of the proposed model compared with the state-of-the-art clustering approaches.

Diagnostic and prognostic value of serum L1-cell adhesion molecule in esophageal squamous cell carcinoma.

OBJECTIVE: L1 cell adhesion molecule (L1CAM) has been found to be dysregulated in several types of human cancers. Here, we aimed to determine the level of soluble L1CAM in serum of patients with esophageal squamous cell carcinoma (ESCC). METHODS: Serum levels of L1CAM were determined by an enzyme-linked immunosorbent assay (ELISA) in 191 patients with ESCC and 94 normal controls. Receiver operating characteristics (ROC) was employed to calculate diagnostic accuracy. Cumulative survival time was calculated by the Kaplan-Meier method and analyzed by the logrank test. RESULTS: Levels of L1CAM were significantly lower in all ESCC patients than in normal controls (P < 0.001). Detection of serum L1CAM provided a sensitivity of 28.3%, a specificity of 90.4% and an area under the curve (AUC) of 0.644 (95% CI: 0.579-0.710) in diagnosing ESCC. Similar results were observed in the diagnosis of early-stage ESCC (26.2% sensitivity, 90.4% specificity, and an AUC of 0.629). Moreover, decreased level of L1CAM was correlated with depth of tumor invasion (P < 0.05). Kaplan-Meier analysis showed that lower serum L1CAM level was significantly related to shorter overall survival time (P = 0.036) and disease-free survival time (P = 0.021) of ESCC patients. CONCLUSIONS: Our study demonstrated that serum L1CAM might serve as a potential biomarker for the diagnosis and prognosis of ESCC.