Latest insights into the global epidemiological features, screening, early diagnosis and prognosis prediction of esophageal squamous cell carcinoma.

As a highly invasive carcinoma, esophageal cancer (EC) was the eighth most prevalent malignancy and the sixth leading cause of cancer-related death worldwide in 2020. Esophageal squamous cell carcinoma (ESCC) is the major histological subtype of EC, and its incidence and mortality rates are decreasing globally. Due to the lack of specific early symptoms, ESCC patients are usually diagnosed with advanced-stage disease with a poor prognosis, and the incidence and mortality rates are still high in many countries, especially in China. Therefore, enormous challenges still exist in the management of ESCC, and novel strategies are urgently needed to further decrease the incidence and mortality rates of ESCC. Although the key molecular mechanisms underlying ESCC pathogenesis have not been fully elucidated, certain promising biomarkers are being investigated to facilitate clinical decision-making. With the advent and advancement of high-throughput technologies, such as genomics, proteomics and metabolomics, valuable biomarkers with high sensitivity, specificity and stability could be identified for ESCC. Herein, we aimed to determine the epidemiological features of ESCC in different regions of the world, especially in China, and focused on novel molecular biomarkers associated with ESCC screening, early diagnosis and prognosis prediction.

Advances in diagnosis and management of cancer of the esophagus.

Esophageal cancer is the seventh most common malignancy worldwide, with over 470 000 new cases diagnosed each year. Two distinct histological subtypes predominate, and should be considered biologically separate disease entities.1 These subtypes are esophageal adenocarcinoma (EAC) and esophageal squamous cell carcinoma (ESCC). Outcomes remain poor regardless of subtype, with most patients presenting with late stage disease.2 Novel strategies to improve early detection of the respective precursor lesions, squamous dysplasia, and Barrett's esophagus offer the potential to improve outcomes. The introduction of a limited number of biologic agents, as well as immune checkpoint inhibitors, is resulting in improvements in the systemic treatment of locally advanced and metastatic esophageal cancer. These developments, coupled with improvements in minimally invasive surgical and endoscopic treatment approaches, as well as adaptive and precision radiotherapy technologies, offer the potential to improve outcomes still further. This review summarizes the latest advances in the diagnosis and management of esophageal cancer, and the developments in understanding of the biology of this disease.

Discovery and validation of combined biomarkers for the diagnosis of esophageal intraepithelial neoplasia and esophageal squamous cell carcinoma.

Early diagnosis and intervention of esophageal squamous cell carcinoma (ESCC) can improve the prognosis. The purpose of this study was to identify biomarkers for ESCC and esophageal precancerous lesions (intraepithelial neoplasia, IEN). Based on the proteomic and genomic data of esophageal tissue including previously reported data, up-regulated proteins with copy number amplification in esophageal cancer were screened as candidate biomarkers. Five proteins, including KDM2A, RAD9A, ECT2, CYHR1 and TONSL, were confirmed by immunohistochemistry on ESCC and normal esophagus (NE). Then, we investigated the expression of 5 proteins in 236 participants (60 NEs, 93 IENs and 83 ESCCs) which were randomly divided into training set and test set. When distinguishing ESCC from NE, the area under curve (AUC) of the multiprotein model was 0.940 in the training set, while the lowest AUC of a protein was 0.735. In the test set, the results were similar. When distinguishing ESCC from IEN or distinguishing IEN from NE, the diagnostic efficiency of the multi-protein models were also improved compared with that of single protein. Our findings suggest that combined detection of KDM2A, RAD9A, ECT2, CYHR1 and TONSL can be used as potential biomarkers for the early diagnosis of ESCC and precancerous lesion development prediction. SIGNIFICANCE: Candidate biomarkers including KDM2A, RAD9A, ECT2, CYHR1 and TONSL screened by integrating genomic and proteomic data from the esophagus can be used as potential biomarkers for the early diagnosis of esophageal squamous cell carcinoma and precancerous lesion development prediction.

[Development and validation of predictive models for esophageal squamous cell carcinoma and its precancerous lesions using terminal motif analysis in circulating cell-free DNA].

Objectives: To develop and validate predictive models for esophageal squamous cell carcinoma (ESCC) using circulating cell-free DNA (cfDNA) terminal motif analysis. The goal was to improve the non-invasive detection of early-stage ESCC and its precancerous lesions. Methods: Between August 2021 and November 2022, we prospectively collected plasma samples from 448 individuals at the Department of Endoscopy, Cancer Hospital, Chinese Academy of Medical Sciences for cfDNA extraction, library construction, and sequencing. We analyzed 201 cases of ESCC, 46 high-grade intraepithelial neoplasia (HGIN), 46 low-grade intraepithelial neoplasia (LGIN), 176 benign esophageal lesions, and 29 healthy controls. Participants, including ESCC patients and control subjects, were randomly assigned to a training set (n=284) and a validation set (n=122). The training cohort underwent z-score normalization of cfDNA terminal motif matrices and a selection of distinctive features differentiated ESCC cases from controls. The random forest classifier, Motif-1 (M1), was then developed through principal component analysis, ten-fold cross-validation, and recursive feature elimination. M1's efficacy was then validated in the validation and precancerous lesion sets. Subsequently, individuals with precancerous lesions were included in the dataset and participants were randomly allocated to newly formed training (n=243), validation (n=105), and test (n=150) cohorts. Using the same procedure as M1, we trained the Motif-2 (M2) random forest model with the training cohort. The M2 model's accuracy was then confirmed in the validation cohort to establish the optimal threshold and further tested by performing validation in the test cohort. Results: We developed two cfDNA terminal motif-based predictive models for ESCC and associated precancerous conditions. The first model, M1, achieved a sensitivity of 90.0%, a specificity of 77.4%, and an area under the curve (AUC) of 0.884 in the validation cohort. For LGIN, HGIN, and T1aN0 stage ESCC, M1's sensitivities were 76.1%, 80.4%, and 91.2% respectively. Notably, the sensitivity for jointly predicting HGIN and T1aN0 ESCC reached 85.0%. Both the predictive accuracy and sensitivity increased in line with the cancer's progression (P＜0.001). The second model, M2, exhibited a sensitivity of 87.5%, a specificity of 77.4%, and an AUC of 0.857 in the test cohort. M2's sensitivities for detecting precancerous lesions and ESCC were 80.0% and 89.7%, respectively, and it showed a combined sensitivity of 89.4% for HGIN and T1aN0 stage ESCC. Conclusions: Two predictive models based on cfDNA terminal motif analysis for ESCC and its precancerous lesions are developed. They both show high sensitivity and specificity in identifying ESCC and its precancerous stages, indicating its potential for early ESCC detection.

Non-invasive early detection on esophageal squamous cell carcinoma and precancerous lesions by microbial biomarkers combining epidemiological factors in China.

BACKGROUND: Microbiota may be associated with esophageal squamous cell carcinoma (ESCC) development. However, it is not known the predictive value of microbial biomarkers combining epidemiological factors for the early detection of ESCC and precancerous lesions. METHODS: A total of 449 specimens (esophageal swabs and saliva) were collected from 349 participants with different esophageal statuses in China to explore and validate ESCC-associated microbial biomarkers from genes level to species level by 16S rRNA sequencing, metagenomic sequencing and real-time quantitative polymerase chain reaction. RESULTS: A bacterial biomarker panel including Actinomyces graevenitzii (A.g_1, A.g_2, A.g_3, A.g_4), Fusobacteria nucleatum (F.n_1, F.n_2, F.n_3), Haemophilus haemolyticus (H.h_1), Porphyromonas gingivalis (P.g_1, P.g_2, P.g_3) and Streptococcus australis (S.a_1) was explored by metagenomic sequencing to early detect the participants in Need group (low-grade intraepithelial neoplasia, high-grade intraepithelial neoplasia and ESCC) vs participants without these lesions as the Noneed group. Significant quantitative differences existed for each microbial target in which the detection efficiency rate was higher in saliva than esophageal swab. In saliva, the area under the curve (AUC) based on the microbial biomarkers (A.g_4 ∩ P.g_3 ∩ H.h_1 ∩ S.a_1 ∩ F.n_2) was 0.722 (95% CI 0.621-0.823) in the exploration cohort. Combining epidemiological factors (age, smoking, drinking, intake of high-temperature food and toothache), the AUC improved to 0.869 (95% CI 0.802-0.937) in the exploration cohort, which was validated with AUC of 0.757 (95% CI 0.663-0.852) in the validation cohort. CONCLUSIONS: It is feasible to combine microbial biomarkers in saliva and epidemiological factors to early detect ESCC and precancerous lesions in China.

Plasma-based lipidomics reveals potential diagnostic biomarkers for esophageal squamous cell carcinoma: a retrospective study.

Background: Esophageal squamous cell carcinoma (ESCC) is highly prevalent and has a high mortality rate. Traditional diagnostic methods, such as imaging examinations and blood tumor marker tests, are not effective in accurately diagnosing ESCC due to their low sensitivity and specificity. Esophageal endoscopic biopsy, which is considered as the gold standard, is not suitable for screening due to its invasiveness and high cost. Therefore, this study aimed to develop a convenient and low-cost diagnostic method for ESCC using plasma-based lipidomics analysis combined with machine learning (ML) algorithms. Methods: Plasma samples from a total of 40 ESCC patients and 31 healthy controls were used for lipidomics study. Untargeted lipidomics analysis was conducted through liquid chromatography-mass spectrometry (LC-MS) analysis. Differentially expressed lipid features were filtered based on multivariate and univariate analysis, and lipid annotation was performed using MS-DIAL software. Results: A total of 99 differential lipids were identified, with 15 up-regulated lipids and 84 down-regulated lipids, suggesting their potential as diagnostic targets for ESCC. In the single-lipid plasma-based diagnostic model, nine specific lipids (FA 15:4, FA 27:1, FA 28:7, FA 28:0, FA 36:0, FA 39:0, FA 42:0, FA 44:0, and DG 37:7) exhibited excellent diagnostic performance, with an area under the curve (AUC) exceeding 0.99. Furthermore, multiple lipid-based ML models also demonstrated comparable diagnostic ability for ESCC. These findings indicate plasma lipids as a promising diagnostic approach for ESCC.

Minimal residual disease profiling predicts pathological complete response in esophageal squamous cell carcinoma.

Accurate presurgical prediction of pathological complete response (pCR) can guide treatment decisions, potentially avoiding unnecessary surgeries and improving the quality of life for cancer patients. We developed a minimal residual disease (MRD) profiling approach with enhanced sensitivity and specificity for detecting minimal tumor DNA from cell-free DNA (cfDNA). The approach was validated in two independent esophageal squamous cell carcinoma (ESCC) cohorts. In a cohort undergoing neoadjuvant, surgical, and adjuvant therapy (NAT cohort), presurgical MRD status precisely predicted pCR. All MRD-negative cases (10/10) were confirmed as pCR by pathological evaluation on the resected tissues. In contrast, MRD-positive cases included all the 27 non-pCR cases and only one pCR case (10/10 vs 1/28, P < 0.0001, Fisher's exact test). In a definitive radiotherapy cohort (dRT cohort), post-dRT MRD status was closely correlated with patient prognosis. All MRD-negative patients (25/25) remained progression-free during the follow-up period, while 23 of the 26 MRD-positive patients experienced disease progression (25/25 vs 3/26, P < 0.0001, Fisher's exact test; progression-free survival, P < 0.0001, log-rank test). The MRD profiling approach effectively predicted the ESCC patients who would achieve pCR with surgery and those likely to remain progression-free without surgery. This suggests that the cancer cells in these MRD-negative patients have been effectively eliminated and they could be suitable candidates for a watch-and-wait strategy, potentially avoiding unnecessary surgery.

Multimodal analysis of cfDNA methylomes for early detecting esophageal squamous cell carcinoma and precancerous lesions.

Detecting early-stage esophageal squamous cell carcinoma (ESCC) and precancerous lesions is critical for improving survival. Here, we conduct whole-genome bisulfite sequencing (WGBS) on 460 cfDNA samples from patients with non-metastatic ESCC or precancerous lesions and matched healthy controls. We develop an expanded multimodal analysis (EMMA) framework to simultaneously identify cfDNA methylation, copy number variants (CNVs), and fragmentation markers in cfDNA WGBS data. cfDNA methylation markers are the earliest and most sensitive, detectable in 70% of ESCCs and 50% of precancerous lesions, and associated with molecular subtypes and tumor microenvironments. CNVs and fragmentation features show high specificity but are linked to late-stage disease. EMMA significantly improves detection rates, increasing AUCs from 0.90 to 0.99, and detects 87% of ESCCs and 62% of precancerous lesions with >95% specificity in validation cohorts. Our findings demonstrate the potential of multimodal analysis of cfDNA methylome for early detection and monitoring of molecular characteristics in ESCC.

Effectiveness of Endoscopic Screening on Esophageal Cancer Incidence and Mortality: A 9-Year Report of the Endoscopic Screening for Esophageal Cancer in China (ESECC) Randomized Trial.

PURPOSE: To evaluate the effectiveness of endoscopic screening against incidence of and mortality from esophageal squamous cell carcinoma (ESCC). METHODS: From January 2012 to September 2016, we conducted a community-based cluster randomized controlled trial involving permanent residents age 45-69 years in a high-risk region for ESCC in northern China. A total of 668 targeted villages were randomly assigned in a 1:1 ratio to the screening group (offered Lugol's chromoendoscopy) or control group (no screening). Intention-to-treat and per-protocol analyses were performed to compare esophageal cancer (EC) incidence and mortality between the two groups. The per-protocol analysis adjusted for nonadherence to the screening procedure. RESULTS: A total of 33,847 participants were included in the analysis: 17,104 in the screening group, 15,165 (88.7%) of whom underwent screening, and 16,743 in the control group. During a maximum follow-up of 9 years, EC incidence in the screening and control groups were 60.9 and 72.5 per 100,000 person-years, respectively; mortality in the screening and control groups were 29.7 and 32.4 per 100,000 person-years, respectively. Compared with the control group, the incidence and mortality of the screening group reduced by 19% (adjusted hazard ratio [aHR], 0.81 [95% CI, 0.60 to 1.09]) and 18% (aHR, 0.82 [95% CI, 0.53 to 1.26]), respectively, in the intention-to-treat analysis; and by 22% (aHR, 0.78 [95% CI, 0.56 to 1.10]) and 21% (aHR, 0.79 [95% CI, 0.49 to 1.30]), respectively, in the per-protocol analysis. CONCLUSION: With a 9-year follow-up, our trial suggests that chromoendoscopic screening induces modest reductions in EC incidence and mortality. A more efficient strategy for EC screening and subsequent patient management should be established to guarantee the effectiveness of endoscopic screening.

Combining fecal microbiome and metabolomics reveals diagnostic biomarkers for esophageal squamous cell carcinoma.

Esophageal squamous cell carcinoma (ESCC) is one of the most predominant subtypes of esophageal cancer. The characteristics of the gut microbiome and its metabolites from patients with ESCC have not been adequately studied and discussed. In this study, 40 fecal samples (20 from ESCC patients and 20 from healthy controls) were analyzed by 16S rRNA gene sequencing and untargeted metabolomics. The data sets were analyzed individually and synthesized using various bioinformatics methods. Alpha and beta diversity indicated significant differences in microbial diversity and abundance between ESCC and healthy control feces. At the genus level, the abundance of Phascolarctobacterium, Sutterella, and Streptococcus was significantly increased in ESCC. At the genus level, linear discriminant analysis effect size identified two biomarkers: Bacteroides_stercoris and Prevotella_copri. Untargeted metabolomics analysis revealed 307 differential metabolites between ESCC and healthy control feces, with indoles and derivatives, tropane alkaloids, lipids, and lipid-like molecules in higher relative abundance in ESCC feces than in healthy control feces. Kyoto Encyclopedia of Genes and Genomes enrichment analysis revealed that unsaturated fatty acids (FAs), ascorbate and aldarate metabolism, and hypoxia-inducible factor 1 signaling pathway were significantly associated with differential metabolite. Phenylethanolamine and despropionyl p-fluoro fentanyl could be used as reliable biomarkers to differentiate ESCC from healthy control. The correlation analysis showed that Prevotella may be involved in the synthesis of fatty acyl, carboxylic acids and derivatives, benzenes and substituted derivatives, organic oxygenates, and indoles and derivatives as metabolites. Fusicatenibacter and Lachnospira may be involved in the degradation of indoles and derivatives. Alistipes, Agathobacter, and Parabacteroides may be involved in the synthesis of indoles and derivatives with strong contributions. There is an intricate relationship between the gut microbiome and the levels of several metabolites (e.g., fatty acyls, carboxylic acids and derivatives, indoles, and derivatives). Microbial-associated metabolites can be used as diagnostic biomarkers in therapeutic exploration. Further analysis revealed that Prevotella, Alistipes, Agathobacter, and Parabacteroides might promote ESCC by regulating the synthesis of indoles and their derivatives. The results of this study provide favorable evidence for the early diagnosis of ESCC and subsequent individualized treatment and targeted interventions.IMPORTANCEWe describe for the first time the differences in fecal microbiome composition and metabolites between patients with esophageal squamous cell carcinoma (ESCC) and healthy controls by 16S rRNA gene sequencing and untargeted metabolomics. The results of this study provide a favorable basis for the early diagnosis of ESCC and subsequent targeted interventional therapy.

Liquid biopsy of oesophageal squamous cell carcinoma: implications in diagnosis, prognosis, and treatment monitoring.

Oesophageal squamous cell carcinoma (ESCC) is a common malignant tumour of the gastrointestinal tract. Early detection and access to appropriate treatment are crucial for the long-term survival of patients. However, limited diagnostic and monitoring methods are available for identifying early stage ESCC. Endoscopic screening and surgical resection are commonly used to diagnose and treat early ESCC. However, these methods have disadvantages, such as high recurrence, lethality, and mortality rates. Therefore, methods to improve early diagnosis of ESCC and reduce its mortality rate are urgently required. In 1961, Gary et al. proposed a novel liquid biopsy approach for clinical diagnosis. This involved examining exosomes, circulating tumour cells, circulating free DNA, and circulating free RNA in body fluids. The ability of liquid biopsy to obtain samples repeatedly, wide detection range, and fast detection speed make it a feasible option for non-invasive tumour detection. In clinical practice, liquid biopsy technology has gained popularity for early screening, diagnosis, treatment efficacy monitoring, and prognosis assessment. Thus, this is a highly promising examination method. However, there have been no comprehensive reviews on the four factors of liquid biopsy in the context of ESCC. This review aimed to analyse the progress of liquid biopsy research for ESCC, including its classification, components, and potential future applications.

Early-onset esophageal squamous cell carcinoma with achalasia: A case report.

RATIONALE: Individuals afflicted with achalasia of the cardia (AC) are more susceptible to the development of esophageal cancer (EC). However, the presence of esophageal retention obscured observation, making it difficult to detect EC early, which leads to misdiagnosis and poor prognosis in AC patients with EC. Besides, the persistence of high-risk factors may have contributed to the rapid progression of EC shortly after per-oral endoscopic myotomy (POEM). Therefore, it is imperative to alert clinicians to this extremely rare and instructive early-onset cancer. PATIENT CONCERNS: The patient was a 67-year-old male who developed dysphagia 3 years ago without obvious causes, with intermittent onset and aggravating trend, accompanied by weight loss. He usually eats high-temperature foods and pickled foods, and has a family history of esophageal squamous cell carcinoma. DIAGNOSIS AND INTERVENTIONS: The patient was initially diagnosed with AC 2 years ago and subsequently underwent POEM surgery. One year after surgery, he was found to have mid-upper EC during follow-up and underwent partial esophagectomy in time. OUTCOMES: The patient's symptoms have significantly improved with weight gain, and he is still adhering to regular follow-up and endoscopic examination. LESSONS: In rare cases, EC develops early in patients with achalasia after POEM surgery. To avoid missed diagnosis, a comprehensive examination to improve the accuracy to diagnose achalasia and identify possible early-onset cancer is very important in clinical practice. Especially for patients with AC who have a family history of EC or other high-risk factors may develop EC early after POEM surgery. Therefore, regular endoscopic follow-up after POEM surgery is essential.

Cardiac substructures dosimetric predicts cardiac toxicity and prognosis in esophageal squamous cell cancer treated by radiotherapy.

PURPOSE: To look into the relationship between cardiac substructures (CS) dosimetric parameters and cardiac events (CE) or overall survival (OS) in patients undergoing radiation therapy (RT) for esophageal squamous cell carcinoma (ESCC). METHODS AND MATERIALS: A retrospective study included 350 patients with ESCC receiving definitive chemoradiotherapy or radiotherapy (d-CRT/d-RT) or neoadjuvant chemoradiotherapy (NCRT) from March 2013 to May 2022. Our study examined the adverse cardiac events of any grade or G3+, as defined by the Common Terminology Criteria for Adverse Events (CTCAE) version 5.0. Competing risk analysis and Cox regression analysis were used to assess the relationship between CS doses and CEs or OS. RESULTS: 201 (57.4 %) patients received any grade CEs over a median follow-up time of 22.50 months (IQR, 12.40-45.60), and 24 (6.86 %) patients suffered G3+ CEs. On landmark analysis, patients with any grade CEs had significantly lower OS (P = 0.003). Multivariable analysis revealed that any grade CEs were predicted by the dose of CSs in all populations. In addition, for G3+ cardiac events, arrhythmic and small probability of cardiac events, LAD V20 ((HR: 1.02, 95 % CI: 1.00-1.03, P = 0.012; HR: 1.01, 95 % CI: 1.00-1.02, P = 0.005; HR; 1.01, 95 % CI: 1.00-1.02, P = 0.012) was also an independent predictive factor. LAD V50 (HR: 1.07, 95 % CI: 1.03-1.10, P <0.001) predicted pericardium effusion events. Moreover, the multivariable analysis revealed that OS was predicted by LAD V30 (HR: 1.03; 95 % CI, 1.01-1.05, P = 0.015). CONCLUSIONS: In the population of ESCC patients receiving RT, we showed that the CS factors had a substantial predictive value for the various types and grades of CEs. The elevated radiation dose of LAD was a significant contributor to a higher rate of cardiac events and a worse prognosis.

Appraising the value of CircRNAs for the diagnosis and prognosis of esophageal squamous cell cancer: An updated meta-analysis.

OBJECTIVE: The purpose of this study was to thoroughly assess the relevance of circular RNAs (circRNAs) in the diagnosis and prognosis of esophageal squamous cell carcinoma (ESCC)， and design a systematic review and meta-analysis. METHODS: Using Stata 14.0 software, a meta-analysis was carried out by looking for pertinent studies up to February 20, 2023, in the online databases PubMed, Embase, Web of Science, and CNKI. The clinicopathologic and prognostic data were evaluated using the combined advantage ratio (OR) and combined hazard ratio (HR), respectively. The threshold effects and publication bias were quantified using Spearman's correlation and the Deeks funnel plot asymmetry tests, respectively. RESULTS: A total of 36 pertinent studies with a literature quality score of 7 or above were included in this study. Of them, 22 papers dealt with clinicopathological characterization, 15 dealt with prognostic analysis, and 13 dealt with diagnostic analysis. The findings demonstrated that high expression of upregulated circRNAs was associated with worse clinicopathological features (tumor size: OR=3.61, 95% CI:1.45-5.78; TNM stage: OR=2.12, 95% CI:1.41-2.83; lymph node metastasis: OR=2.87, 95% CI:1.67-4.07) and worse OS (HR=1.49, 95% CI:1.26-1.77). High downregulated circRNAs expression was linked to improved clinicopathologic characteristics (TNM staging: OR=0.35, 95% CI:0.13- 0.95) and longer survival (HR=0.48, 95% CI:0.27-0.84); combined sensitivity was 0.77 (95% CI: 0.71-0.82), specificity was 0.80 (95% CI:0.74-0.86), and area under the subject operating characteristic curve (AUC) was 0.86 (95% CI:0.82- 0.88). CONCLUSION: CircRNAs are useful for ESCC patient diagnosis and prognosis, and they are anticipated to be unique potential biomarkers for ESCC clinical diagnosis.

An emerging biomarker for the diagnosis and treatment of esophageal squamous cell carcinoma - Aurora A.

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is a prominent form of esophageal cancer. Aurora A (AURKA), an enzyme that phosphorylates serine and threonine, has a vital function in controlling the process of separating chromosomes during cell division. The contribution of this entity has been documented in the advancement of malignant proliferations, including tumors occurring in the breast, stomach, and ovaries. METHODS: The potential molecular mechanism of AURKA is comprehensively examined through the analysis of bulk RNA-seq and single-cell RNA-seq data obtained from publicly available databases. This analysis encompasses various aspects such as expression levels, prognosis, and functional pathways, among others. RESULTS: The upregulation of AURKA in ESCC has been found to be correlated with the overall survival of patients. The functional annotation and pathway enrichment analysis conducted in this study lead to the conclusion that AURKA participates in the regulation of a number of malignant processes connected to cell proliferation, such as cell cycle control, apoptosis, and the p53 signaling pathway. Additionally, AURKA has been found to be associated with drug sensitivity and has an impact on the infiltration of tumor-infiltrating immune cells in ESCC. CONCLUSIONS: AURKA exhibits potential as a prognostic and therapeutic biomarker linked to the regulation of cell cycle and cell proliferation.

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.

A screened predictive model for esophageal squamous cell carcinoma based on salivary flora data.

Esophageal squamous cell carcinoma (ESCC) is a malignant tumor of the digestive system in the esophageal squamous epithelium. Many studies have linked esophageal cancer (EC) to the imbalance of oral microecology. In this work, different machine learning (ML) models including Random Forest (RF), Gaussian mixture model (GMM), K-nearest neighbor (KNN), logistic regression (LR), support vector machine (SVM) and extreme gradient boosting (XGBoost) based on Genetic Algorithm (GA) optimization was developed to predict the relationship between salivary flora and ESCC by combining the relative abundance data of Bacteroides, Firmicutes, Proteobacteria, Fusobacteria and Actinobacteria in the saliva of patients with ESCC and healthy control. The results showed that the XGBoost model without parameter optimization performed best on the entire dataset for ESCC diagnosis by cross-validation (Accuracy = 73.50%). Accuracy and the other evaluation indicators, including Precision, Recall, F1-score and the area under curve (AUC) of the receiver operating characteristic (ROC), revealed XGBoost optimized by the GA (GA-XGBoost) achieved the best outcome on the testing set (Accuracy = 89.88%, Precision = 89.43%, Recall = 90.75%, F1-score = 90.09%, AUC = 0.97). The predictive ability of GA-XGBoost was validated in phylum-level salivary microbiota data from ESCC patients and controls in an external cohort. The results obtained in this validation (Accuracy = 70.60%, Precision = 46.00%, Recall = 90.55%, F1-score = 61.01%) illustrate the reliability of the predictive performance of the model. The feature importance rankings obtained by XGBoost indicate that Bacteroides and Actinobacteria are the two most important factors in predicting ESCC. Based on these results, GA-XGBoost can predict and diagnose ESCC according to the relative abundance of salivary flora, providing an effective tool for the non-invasive prediction of esophageal malignancies.