Novel metabolic biomarker for early detection and diagnosis to the patients with gastric cardia adenocarcinoma.

BACKGROUND: Gastric cardia adenocarcinoma (GCA) is classified as Siewert type II adenocarcinoma at the esophagogastric junction in Western countries. The majority of GCA patients do not exhibit early warning symptoms, leading to over 90% of diagnoses at an advanced stage, resulting in a grim prognosis, with less than a 20% 5-year survival rate. METHOD: Metabolic features of 276 GCA and 588 healthy controls were characterized through a widely-targeted metabolomics by UPLC-MS/MS analysis. This study encompasses a joint pathway analysis utilizing identified metabolites, survival analysis in both early and advanced stages, as well as high and negative and low expression of HER2 immunohistochemistry staining. Machine learning techniques and Cox regression models were employed to construct a diagnostic panel. RESULTS: A total of 25 differential metabolites were consistently identified in both discovery and validation sets based on criteria of p < 0.05, (VIP) ≥ 1, and FC ≥ 2 or FC ≤ 0.5. Early-stage GCA patients exhibited a more favorable prognosis compared to those in advanced stages. HER2 overexpression was associated with a more positive outcome compared to the negative and low expression groups. Metabolite panel demonstrated a robust diagnostic performance with AUC of 0.869 in discovery set and 0.900 in validation set. CONCLUSIONS: A total of 25 common and stable differential metabolites may hold promise as liquid non-invasive indicators for GCA diagnosis. HER2 may function as a tumor suppressor gene in GCA, as its overexpression is associated with improved survival. The downregulation of bile acid metabolism in GCA may offer valuable theoretical insights and innovative approaches for precision-targeted treatments in GCA patients.

Clinicopathological characteristics and postoperative prognosis of patients with nuclear pedigree of esophageal squamous cell carcinoma.

The aim of this work is to analyze the clinicopathological characteristics and prognostic factors of patients with nuclear pedigree of esophageal cancer. The clinicopathological data and follow-up information of 3,260 patients from different nuclear pedigree of esophageal cancer who underwent radical resection of esophageal cancer were collected, and the clinicopathological characteristics and prognostic factors of the patients were analyzed. The male to female ratio of 3,260 patients with esophageal cancer was 1.7:1. The diagnosis age was ranged from 32 to 85 (60.2 ± 8.1) years old. About 53.8% of the patients were ≥ 60 years old; About 88.8% of the patients came from the high incidence area of esophageal cancer; About 82.5% of the tumors were located in the middle and lower segments of esophagus; Poor, moderate and well differentiation accounted for 26.6%, 61.9% and 11.5% respectively; The surgical margin accounted for 94.3%; 47.6% of the tumors were shorter than 4 cm in length; Clinicopathological TNM stage (0+I) accounted for 15.2%, and stage II, III and IV accounted for 54.5%, 29.9% and 0.4%, respectively. Cox analysis showed that male, diagnosed age ≥ 60 years, tumor located in neck and upper esophageal segments, poor differentiation, tumor length ≥ 4 cm, and advanced TNM were independent risk factors for the prognosis of patients in nuclear pedigree with esophageal cancer. Gender, diagnosis age, tumor location, degree of differentiation, tumor length and TNM stage are the influencing factors for the prognosis of patients with nuclear pedigree of esophageal cancer, which will provide important data for the future study of esophageal cancer family aggregation.

Increases prognostic value of clinical-pathological nomogram in patients with esophageal squamous cell carcinoma.

Background: This study was intended to construct a brand new prognostic nomogram after combine clinical and pathological characteristics to increases prognostic value in patients with esophageal squamous cell carcinoma. Methods: A total of 1,634 patients were included. Subsequently, the tumor tissues of all patients were prepared into tissue microarrays. AIPATHWELL software was employed to explore tissue microarrays and calculate the tumor-stroma ratio. X-tile was adopted to find the optimal cut-off value. Univariate and multivariate Cox analyses were used to screen out remarkable characteristics for constructing the nomogram in the total populations. A novel prognostic nomogram with clinical and pathological characteristics was constructed on the basis of the training cohort (n=1,144). What's more performance was validated in the validation cohort (n=490). Clinical-pathological nomogram were assessed by concordance index, time-dependent receiver operating characteristic, calibration curve and decision curve analysis. Results: The patients can divide into two groups with cut-off value of 69.78 for the tumor-stroma ratio. It is noteworthy that the survival difference was noticeable (P<0.001). A clinical-pathological nomogram was constructed by combining clinical and pathological characteristics to predict the overall survival. In comparison with TNM stage, the concordance index and time-dependent receiver operating characteristic of the clinical-pathological nomogram showed better predictive value (P<0.001). High quality of calibration plots in overall survival was noticed. As demonstrated by the decision curve analysis, the nomogram has better value than the TNM stage. Conclusions: As evidently revealed by the research findings, tumor-stroma ratio is an independent prognostic factor in patients with esophageal squamous cell carcinoma. The clinical-pathological nomogram has an incremental value compared TNM stage in predicting overall survival.

Survival influence of gender on 42,345 patients with gastric cardia adenocarcinoma.

PURPOSE: Some studies indicated that gender is associated with prognostic of cancer, However, currently the prognostic value of gender for gastric cardia adenocarcinoma (GCA) survival is unclear. The aim of our study is to reveal the influence of gender on the prognosis of patients with GCA. PATIENTS AND METHODS: A total of 42,345 cases Chinese GCA patients were enrolled from our previously established GCA and esophageal cancer databases. The clinicopathological characteristics were retrieved from medical records in hospital. The follow-up was performed through letter, telephone or home interview. Among GCA patients, there were 32,544 (76.9%) male patients with the median age 62 years (range 17-97) and 9,801 (23.1%) female patients with the median age 61 years (range 17-95 years). The Chi-square test and Kaplan-Meier method were used to compare the continuous variables and survival. Cox proportional hazards model was used for competing risk analyses, hazard ratios (HRs) and 95% confidence intervals (CIs) were evaluated. RESULTS: Men had shorter GCA-specific survival than women by multivariate analysis (HR 1.114; 95% CI 1.061 to 1.169; P < 0.001). Whether premenopausal, perimenopausal or postmenopausal, the survival of women was better than that of men (premenopausal vs. male, P < 0.001; perimenopausal vs. male, P < 0.001; postmenopausal vs. male, P = 0.035). It was worth noting that in patients with stages I, II, III, and IV, female patients survive longer than male patients (P = 0.049; P = 0.011; P < 0.001; P = 0.044, respectively). CONCLUSION: Gender is an independent prognostic factor for patients with GCA. In comparison with men, women have a significantly better outcome. Smoking and drinking may be protective factors for male GCA patients.

Serum Metabolomic Profiling Reveals Biomarkers for Early Detection and Prognosis of Esophageal Squamous Cell Carcinoma.

Esophageal squamous cell carcinoma (ESCC) is one of the most common aggressive malignancies worldwide, particularly in northern China. The absence of specific early symptoms and biomarkers leads to late-stage diagnosis, while early diagnosis and risk stratification are crucial for improving overall prognosis. We performed UPLC-MS/MS on 450 ESCC patients and 588 controls consisting of a discovery group and two validation groups to identify biomarkers for early detection and prognosis. Bioinformatics and clinical statistical methods were used for profiling metabolites and evaluating potential biomarkers. A total of 105 differential metabolites were identified as reliable biomarker candidates for ESCC with the same tendency in three cohorts, mainly including amino acids and fatty acyls. A predictive model of 15 metabolites [all-trans-13,14-dihydroretinol, (±)-myristylcarnitine, (2S,3S)-3-methylphenylalanine, 3-(pyrazol-1-yl)-L-alanine, carnitine C10:1, carnitine C10:1 isomer1, carnitine C14-OH, carnitine C16:2-OH, carnitine C9:1, formononetin, hyodeoxycholic acid, indole-3-carboxylic acid, PysoPE 20:3, PysoPE 20:3(2n isomer1), and resolvin E1] was developed by logistic regression after LASSO and random forest analysis. This model held high predictive accuracies on distinguishing ESCC from controls in the discovery and validation groups (accuracies > 89%). In addition, the levels of four downregulated metabolites [hyodeoxycholic acid, (2S,3S)-3-methylphenylalanine, carnitine C9:1, and indole-3-carboxylic acid] were significantly higher in early cancer than advanced cancer. Furthermore, three independent prognostic markers were identified by multivariate Cox regression analyses with and without clinical indicators: a high level of MG(20:4)isomer and low levels of 9,12-octadecadienoic acid and L-isoleucine correlated with an unfavorable prognosis; the risk score based on these three metabolites was able to stratify patients into low or high risk. Moreover, pathway analysis indicated that retinol metabolism and linoleic acid metabolism were prominent perturbed pathways in ESCC. In conclusion, metabolic profiling revealed that perturbed amino acids and lipid metabolism were crucial metabolic signatures of ESCC. Both panels of diagnostic and prognostic markers showed excellent predictive performances. Targeting retinol and linoleic acid metabolism pathways may be new promising mechanism-based therapeutic approaches. Thus, this study would provide novel insights for the early detection and risk stratification for the clinical management of ESCC and potentially improve the outcomes of ESCC.

Long-term effect of hospital volume on the postoperative prognosis of 158,618 patients with esophageal squamous cell carcinoma in China.

Background: The impact of hospital volume on the long-term survival of esophageal squamous cell carcinoma (ESCC) has not been well assessed in China, especially for stage I-III stage ESCC. We performed a large sample size study to assess the relationships between hospital volume and the effectiveness of ESCC treatment and the hospital volume value at the lowest risk of all-cause mortality after esophagectomy in China. Aim: To investigate the prognostic value of hospital volume for assessing postoperative long-term survival of ESCC patients in China. Methods: The date of 158,618 patients with ESCC were collected from a database (1973-2020) established by the State Key Laboratory for Esophageal Cancer Prevention and Treatment, the database includes 500,000 patients with detailed clinical information of pathological diagnosis and staging, treatment approaches and survival follow-up for esophageal and gastric cardia cancers. Intergroup comparisons of patient and treatment characteristics were conducted with the X2 test and analysis of variance. The Kaplan-Meier method with the log-rank test was used to draw the survival curves for the variables tested. A Multivariate Cox proportional hazards regression model was used to analyze the independent prognostic factors for overall survival. The relationship between hospital volume and all-cause mortality was assessed using restricted cubic splines from Cox proportional hazards models. The primary outcome was all-cause mortality. Results: In both 1973-1996 and 1997-2020, patients with stage I-III stage ESCC who underwent surgery in high volume hospitals had better survival than those who underwent surgery in low volume hospitals (both P<0.05). And high volume hospital was an independent factor for better prognosis in ESCC patients. The relationship between hospital volume and the risk of all-cause mortality was half-U-shaped, but overall, hospital volume was a protective factor for esophageal cancer patients after surgery (HR<1). The concentration of hospital volume associated with the lowest risk of all-cause mortality was 1027 cases/year in the overall enrolled patients. Conclusion: Hospital volume can be used as an indicator to predict the postoperative survival of ESCC patients. Our results suggest that the centralized management of esophageal cancer surgery is meaningful to improve the survival of ESCC patients in China, but the hospital volume should preferably not be higher than 1027 cases/year. Core tip: Hospital volume is considered to be a prognostic factor for many complex diseases. However, the impact of hospital volume on long-term survival after esophagectomy has not been well evaluated in China. Based on a large sample size of 158,618 ESCC patients in China spanning 47 years (1973-2020), We found that hospital volume can be used as a predictor of postoperative survival in patients with ESCC, and identified hospital volume thresholds with the lowest risk of death from all causes. This may provide an important basis for patients to choose hospitals and have a significant impact on the centralized management of hospital surgery.

The prognostic value of keratin pearls in patients with esophageal squamous cell carcinoma.

Keratin pearls (KP) is an important indicator of the degree of tumor cell differentiation of esophageal squamous cell carcinomas (ESCC). However, the independent prognostic value of KP in ESCC patients remains unclear. The hematoxylin-eosin (H&E) stained tissue microarrays (TMAs) or whole slides of the patients were prepared to identify the existence of KP. Kaplan-Meier (KM) survival analysis as well as univariate and multivariate Cox regression analyses were used to evaluate the prognostic value of KP. A nomogram based on KP and other clinicopathologic characteristics was constructed. The C-index, calibration curve, Receiver Operating Characteristic (ROC) curve, and Decision Curve Analysis (DCA) were used to evaluate the nomogram. The results indicated KP is a protective factor against lymph node metastasis and is closely associated with the differentiation degree in ESCC patients. KM survival analysis showed that the overall survival (OS) of patients with KP was significantly better than for patients without KP. In addition, multivariate Cox regression analysis revealed that KP was an independent predictor of OS. Furthermore, ROC curve demonstrated that KP combined with differentiation degree could more accurately predict the 5-year survival rate than differentiation degree alone. Importantly, the nomogram showed good discrimination and calibration abilities in both training and validation groups, which could more accurately predict the 3-, 5-, and 10-year survival rates of ESCC patients and adds to the predictive value of TNM stage alone. In conclusion, KP is an independent predictor of prognosis in patients with ESCC and provides incremental prognostic value to degree of differentiation.

Development and validation of a prognostic nomogram model for Chinese patients with primary small cell carcinoma of the esophagus.

BACKGROUND: Primary small cell carcinoma of the esophagus (PSCE) is a highly invasive malignant tumor with a poor prognosis compared with esophageal squamous cell carcinoma. Due to the limited samples size and the short follow-up time, there are few reports on elucidating the prognosis of PSCE, especially on the establishment and validation of a survival prediction nomogram model covering general information, pathological factors and specific biological proteins of PSCE patients. AIM: To establish an effective nomogram to predict the overall survival (OS) probability for PSCE patients in China. METHODS: The nomogram was based on a retrospective study of 256 PSCE patients. Univariate analysis and multivariate Cox proportional hazards regression analysis were used to examine the prognostic factors associated with PSCE, and establish the model for predicting 1-, 3-, and 5-year OS based on the Akaike information criterion. Discrimination and validation were assessed by the concordance index (C-index) and calibration curve and decision curve analysis (DCA). Histology type, age, tumor invasion depth, lymph node invasion, detectable metastasis, chromogranin A, and neuronal cell adhesion molecule 56 were integrated into the model. RESULTS: The C-index was prognostically superior to the 7th tumor node metastasis (TNM) staging in the primary cohort [0.659 (95%CI: 0.607-0.712) vs 0.591 (95%CI: 0.517-0.666), P = 0.033] and in the validation cohort [0.700 (95%CI: 0.622-0.778) vs 0.605 (95%CI: 0.490-0.721), P = 0.041]. Good calibration curves were observed for the prediction probabilities of 1-, 3-, and 5-year OS in both cohorts. DCA analysis showed that our nomogram model had a higher overall net benefit compared to the 7th TNM staging . CONCLUSION: Our nomogram can be used to predict the survival probability of PSCE patients, which can help clinicians to make individualized survival predictions.

Cu(II)-assisted orange/green dual-emissive carbon dots for the detection and imaging of anthrax biomarker.

The spores of Bacillus anthracis are highly deadly to human beings and animals, and are concurrently potential biological warfare agents. Hence, the rapid and sensitive monitoring Bacillus anthracis biomarker, dipicolinic acid (DPA), is very desirable. Herein, orange/green dual-emissive carbon dots (OG-CDs) were synthesized via the hydrothermal approach. The OG-CDs not only emitted dual fluorescence at 527 and 590 nm under the single 503 nm excitation, but also exhibited excellent water solubility, good photostability and great salt tolerance. The fluorescence of the OG-CDs at 527 nm can be completely quenched when chelated with Cu(II). However, because of the stronger chelation between DPA and Cu(II), the fluorescence restored rapidly on subsequent addition of DPA. As such, the CD-Cu(II) system can be used for determination of DPA based on the fluorescence "off-on" response. Under optimum conditions, the detection limit for DPA was 56 nM, with a linear range of 0.5-12.5 µM. The established CD-Cu(II) based spectrofluorometric method has been applied to the analysis of DPA in real water samples with recoveries of 93.6%-104.3%. More remarkably, the CD-Cu(II) probe also has been successfully applied for the imaging of DPA in Escherichia coli with excellent bio-compatibility.