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

Construction and validation of serum Metabolic Risk Score for early warning of malignancy in esophagus

Using noninvasive biomarkers to identify high-risk individuals prior to endoscopic examination is crucial for optimization of screening strategies for esophageal squamous cell carcinoma (ESCC). We conducted a nested case-control study based on two community-based screening cohorts to evaluate the warning value of serum metabolites for esophageal malignancy. The serum samples were collected at enrollment when the cases had not been diagnosed. We identified 74 differential metabolites and two prominent perturbed metabolic pathways, and constructed Metabolic Risk Score (MRS) based on 22 selected metabolic predictors. The MRS generated an area under the receiver operating characteristics curve (AUC) of 0.815. The model performed well for the within-1-year interval (AUC: 0.868) and 1-to-5-year interval (AUC: 0.845) from blood draw to diagnosis, but showed limited ability in predicting long-term cases (>5 years). In summary, the MRS could serve as a potential early warning and risk stratification tool for establishing a precision strategy of ESCC screening.

Friend or Foe: Exploring the Relationship between the Gut Microbiota and the Pathogenesis and Treatment of Digestive Cancers

Digestive cancers are among the leading causes of cancer death in the world. However, the mechanisms of cancer development and progression are not fully understood. Accumulating evidence in recent years pointing to the bidirectional interactions between gut dysbiosis and the development of a specific type of gastrointestinal cancer is shedding light on the importance of this "unseen organ"-the microbiota. This review focuses on the local role of the gut microbiota imbalance in different digestive tract organs and annexes related to the carcinogenic mechanisms. Microbiota modulation, either by probiotic administration or by dietary changes, plays an important role in the future therapies of various digestive cancers.

Metabolites, Healthy Lifestyle, and Polygenic Risk Score Associated with Upper Gastrointestinal Cancer: Findings from the UK Biobank Study

Previous metabolomics studies have highlighted the predictive value of metabolites on upper gastrointestinal (UGI) cancer, while most of them ignored the potential effects of lifestyle and genetic risk on plasma metabolites. This study aimed to evaluate the role of lifestyle and genetic risk in the metabolic mechanism of UGI cancer. Differential metabolites of UGI cancer were identified using partial least-squares discriminant analysis and the Wilcoxon test. Then, we calculated the healthy lifestyle index (HLI) score and polygenic risk score (PRS) and divided them into three groups, respectively. A total of 15 metabolites were identified as UGI-cancer-related differential metabolites. The metabolite model (AUC = 0.699) exhibited superior discrimination ability compared to those of the HLI model (AUC = 0.615) and the PRS model (AUC = 0.593). Moreover, subgroup analysis revealed that the metabolite model showed higher discrimination ability for individuals with unhealthy lifestyles compared to that with healthy individuals (AUC = 0.783 vs 0.684). Furthermore, in the genetic risk subgroup analysis, individuals with a genetic predisposition to UGI cancer exhibited the best discriminative performance in the metabolite model (AUC = 0.770). These findings demonstrated the clinical significance of metabolic biomarkers in UGI cancer discrimination, especially in individuals with unhealthy lifestyles and a high genetic risk.

NMR and MS reveal characteristic metabolome atlas and optimize esophageal squamous cell carcinoma early detection

Metabolic changes precede malignant histology. However, it remains unclear whether detectable characteristic metabolome exists in esophageal squamous cell carcinoma (ESCC) tissues and biofluids for early diagnosis. Here, we conduct NMR- and MS-based metabolomics on 1,153 matched ESCC tissues, normal mucosae, pre- and one-week post-operative sera and urines from 560 participants across three hospitals, with machine learning and WGCNA. Aberrations in 'alanine, aspartate and glutamate metabolism' proved to be prevalent throughout the ESCC evolution, consistently identified by NMR and MS, and reflected in 16 serum and 10 urine metabolic signatures in both discovery and validation sets. NMR-based simplified panels of any five serum or urine metabolites outperform clinical serological tumor markers (AUC = 0.984 and 0.930, respectively), and are effective in distinguishing early-stage ESCC in test set (serum accuracy = 0.994, urine accuracy = 0.879). Collectively, NMR-based biofluid screening can reveal characteristic metabolic events of ESCC and be feasible for early detection (ChiCTR2300073613).

Glycerol kinase enzyme is a prognostic predictor in esophageal carcinoma and is associated with immune cell infiltration

The influence of lipid metabolism on tumorigenesis and progression has garnered significant attention. However, the role of Glycerol Kinase (GK), a key enzyme in glycerol metabolism, in Esophageal Carcinoma (ESCA) remains unclear. To further elucidate the relationship between GK and ESCA, we investigated GK expression levels using database information. Controlled studies employing immunohistochemistry were conducted on clinical ESCA tumor samples and normal specimens, confirming GK's elevated expression in ESCA. Analysis of The Cancer Genome Atlas (TCGA) data via Kaplan-Meier (KM) survival plots revealed that increased GK expression correlates with poorer ESCA patient outcomes, particularly in overall survival (OS) and disease-specific survival (DSS). Multiple regression analysis indicated that elevated GK expression is an independent risk factor affecting ESCA prognosis. Statistical analysis of prognostic data from clinical samples further corroborated this finding. Moreover, there appears to be a significant correlation between GK expression and immune infiltration, specifically involving certain T and B lymphocytes. In conclusion, elevated GK expression in ESCA is strongly linked to poor prognosis and increased immune cell infiltration, highlighting its potential as an independent prognostic biomarker and a viable therapeutic target.

Metabolomic biomarkers in liquid biopsy: accurate cancer diagnosis and prognosis monitoring

Liquid biopsy, a novel detection method, has recently become an active research area in clinical cancer owing to its unique advantages. Studies on circulating free DNA, circulating tumor cells, and exosomes obtained by liquid biopsy have shown great advances and they have entered clinical practice as new cancer biomarkers. The metabolism of the body is dynamic as cancer originates and progresses. Metabolic abnormalities caused by cancer can be detected in the blood, sputum, urine, and other biological fluids via systemic or local circulation. A considerable number of recent studies have focused on the roles of metabolic molecules in cancer. The purpose of this review is to provide an overview of metabolic markers from various biological fluids in the latest clinical studies, which may contribute to cancer screening and diagnosis, differentiation of cancer typing, grading and staging, and prediction of therapeutic response and prognosis.

Diagnosis of Esophageal Squamous Cell Carcinoma by High-Performance Serum Metabolic Fingerprints: A Retrospective Study

Esophageal squamous cell carcinoma (ESCC) is a highly prevalent and aggressive malignancy, and timely diagnosis of ESCC contributes to an increased cancer survival rate. However, current detection methods for ESCC mainly rely on endoscopic examination, limited by a relatively low participation rate. Herein, ferric-particle-enhanced laser desorption/ionization mass spectrometry (FPELDI MS) is utilized to record the serum metabolic fingerprints (SMFs) from a retrospective cohort (523 non-ESCC participants and 462 ESCC patients) to build diagnostic models toward ESCC. The PFELDI MS achieved high speed (≈30 s per sample), desirable reproducibility (coefficients of variation < 15%), and high throughput (985 samples with ≈124 200 data points for each spectrum). Desirable diagnostic performance with area-under-the-curves (AUCs) of 0.925-0.966 is obtained through machine learning of SMFs. Further, a metabolic biomarker panel is constructed, exhibiting superior diagnostic sensitivity (72.2-79.4%, p < 0.05) as compared with clinical protein biomarker tests (4.3-22.9%). Notably, the biomarker panel afforded an AUC of 0.844 (95% confidence interval [CI]: 0.806-0.880) toward early ESCC diagnosis. This work highlighted the potential of metabolic analysis for accurate screening and early detection of ESCC and offered insights into the metabolic characterization of diseases including but not limited to ESCC.

Lipid metabolism analysis in esophageal cancer and associated drug discovery

Esophageal cancer is an upper gastrointestinal malignancy with a bleak prognosis. It is still being explored in depth due to its complex molecular mechanisms of occurrence and development. Lipids play a crucial role in cells by participating in energy supply, biofilm formation, and signal transduction processes, and lipid metabolic reprogramming also constitutes a significant characteristic of malignant tumors. More and more studies have found esophageal cancer has obvious lipid metabolism abnormalities throughout its beginning, progress, and treatment resistance. The inhibition of tumor growth and the enhancement of antitumor therapy efficacy can be achieved through the regulation of lipid metabolism. Therefore, we reviewed and analyzed the research results and latest findings for lipid metabolism and associated analysis techniques in esophageal cancer, and comprehensively proved the value of lipid metabolic reprogramming in the evolution and treatment resistance of esophageal cancer, as well as its significance in exploring potential therapeutic targets and biomarkers.

Coptis chinensis and Berberine Ameliorate Chronic Ulcerative Colitis: An Integrated Microbiome-Metabolomics Study

Coptis chinensis Franch (RC), has historically been used for the treatment of "Xiao Ke" and "Xia Li" symptoms in China. "Xia Li" is characterized by abdominal pain and diarrhea, which are similar to the clinical symptoms of ulcerative colitis (UC). For the first time, this study aims to compare the anti-colitis effects of berberine (BBR) and total RC alkaloids (TRCA) and investigate the underlying metabolites and gut microbiota biomarkers. Metabolomics results showed that several colitis-related biomarkers, including lysophosphatidyl ethanolamine, lysophosphatidylcholine, scopolamine-methyl-bromide, N1-methyl-2-pyridone-5-carboxamide, 4-hydroxyretinoic acid, and malic acid, were significantly improved in model mice after BBR and TRCA treatments. High-dose BBR and TRCA treatments reversed the mouse colon shortening caused by dextran sodium sulfate (DSS), alleviated bowel wall swelling, and reduced inflammatory cell infiltration. BBR and TRCA restored the damaged mucosa integrity in colitis mice by upregulating claudin 1 and occludin, preventing colon epithelium apoptosis by inhibiting the cleavage of caspase 3. Additionally, BBR and TRCA significantly decreased the richness of the pathogenic bacteria Bacteroides acidifaciens but increased the abundance of the probiotic Lactobacillus spp. Notably, TRCA exhibited superior anti-colitis effects to those of BBR. Thus, this agent warrants further study and application in the treatment of inflammatory bowel disease in the clinic.

Development and Validation of the Oxidative Stress Related lncRNAs for Prognosis in Esophageal Squamous Cell Carcinoma

Esophageal squamous cell cancer (ESCC) is an aggressive disease associated with a poor prognosis. Long non-coding RNAs (lncRNAs) and oxidative stress play crucial roles in tumor progression. We aimed to identify an oxidative stress-related lncRNA signature that could predict the prognosis in ESCC. In the GSE53625 dataset, we identified 332 differentially expressed lncRNAs (DElncRNAs) between ESCC and control samples, out of which 174 were oxidative stress-related DElncRNAs. Subsequently, seven oxidative stress-related DElncRNAs (CCR5AS, LINC01749, PCDH9-AS1, TMEM220-AS1, KCNMA1-AS1, SNHG1, LINC01672) were selected based on univariate and LASSO Cox to build a prognostic risk model, and their expression was detected by RT-qPCR. The model exhibited an excellent ability for the prediction of overall survival (OS) and other clinicopathological traits using Kaplan-Meier (K-M) survival curves, receiver operating characteristic (ROC) curves, and the Wilcoxon test. Additionally, analysis of infiltrated immune cells and immune checkpoints indicated differences in immune status between the two risk groups. Finally, the in vitro experiments showed that PCDH9-AS1 overexpression inhibited proliferation ability and promoted apoptosis and oxidative stress levels in ESCC cells. In conclusion, our study demonstrated that a novel oxidative stress-related DElncRNA prognostic model performed favorably in predicting ESCC patient prognosis and benefits personalized clinical applications.

Identifying the Novel Gut Microbial Metabolite Contributing to Metabolic Syndrome in Children Based on Integrative Analyses of Microbiome-Metabolome Signatures

The pathogenesis of gut microbiota and their metabolites in the development of metabolic syndrome (MS) remains unclear. This study aimed to evaluate the signatures of gut microbiota and metabolites as well as their functions in obese children with MS. A case-control study was conducted based on 23 MS children and 31 obese controls. The gut microbiome and metabolome were measured using 16S rRNA gene amplicon sequencing and liquid chromatography-mass spectrometry. An integrative analysis was conducted, combining the results of the gut microbiome and metabolome with extensive clinical indicators. The biological functions of the candidate microbial metabolites were validated in vitro. We identified 9 microbiota and 26 metabolites that were significantly different from the MS and the control group. The clinical indicators of MS were correlated with the altered microbiota Lachnoclostridium, Dialister, and Bacteroides, as well as with the altered metabolites all-trans-13,14-dihydroretinol, DL-dipalmitoylphosphatidylcholine (DPPC), LPC 24: 1, PC (14:1e/10:0), and 4-phenyl-3-buten-2-one, etc. The association network analysis further identified three MS-linked metabolites, including all-trans-13,14-dihydroretinol, DPPC, and 4-phenyl-3-buten-2-one, that were significantly correlated with the altered microbiota. Bio-functional validation showed that all-trans-13, 14-dihydroretinol could significantly upregulate the expression of lipid synthesis genes and inflammatory genes. This study identified a new biomarker that may contribute to MS development. These findings provided new insights regarding the development of efficient therapeutic strategies for MS. IMPORTANCE Metabolic syndrome (MS) has become a health concern worldwide. Gut microbiota and metabolites play an important role in human health. We first endeavored to comprehensively analyze the microbiome and metabolome signatures in obese children and found the novel microbial metabolites in MS. We further validated the biological functions of the metabolites in vitro and illustrated the effects of the microbial metabolites on lipid synthesis and inflammation. The microbial metabolite all-trans-13, 14-dihydroretinol may be a new biomarker in the pathogenesis of MS, especially in obese children. These findings were not available in previous studies, and they provide new insights regarding the management of metabolic syndrome.

Postoperative Metabolic Phenoreversion in Clear Cell Renal Cell Carcinoma

The ultimate goal of surgical treatment in cancer is to remove the tumor mass for restoring a healthy state. A 16-lipid panel that discriminated healthy controls from clear cell renal cell carcinoma (ccRCC) patients in a prior study was evaluated in the present work in paired-serum samples collected from patients (n = 41) before and after nephrectomy. Changes in the lipid and metabolite fingerprints from ccRCC patients were investigated and compared with fingerprints from healthy individuals obtained by means of ultra-performance liquid chromatography-high-resolution mass spectrometry. The lipid panel differentiated phenotypes associated with metabolic restoration after surgery, representing a serum signature of phenoreversion to a healthy metabolic state. In particular, PC 16:0/0:0, PC 18:2/18:2, and linoleic acid allowed discriminating serum samples from ccRCC patients with poor prognosis from those with an improved outcome during the follow-up period. Ratios of PC 16:0/0:0 and PC 18:2/18:2 with linoleic acid levels may contribute as prognostic tools to support decision-making during the patient follow-up care. The preliminary character of these results should be validated with larger cohorts, including subjects with different ethnicities, life style, and diets. MetaboLights study references: MTBLS1839, MTBLS3838, and MTBLS4629.

Relationship between different forms of dietary choline and ovarian cancer survival: findings from the ovarian cancer follow-up study, a prospective cohort study

Higher levels of pre-diagnosis fat-soluble choline intake was associated with better overall survival of ovarian cancer, and this association was more attributed to phosphatidylcholine.

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.