Esophageal ganglioneuromatosis; a rare cause of intractable esophageal stenosis: a case report.

BACKGROUND: Ganglioneuromatosis is a rare type of benign neurogenic tumor that usually affects the sites of the major sympathetic ganglia in the retroperitoneum and the posterior mediastinum. Affection of the gastrointestinal tract is rare, and involvement of the esophagus is exceptional. To the best of our knowledge, only 4 cases of esophageal ganglioneuromatosis in adults were reported in the literature. No cases have been reported in the pediatric age group. CASE PRESENTATION: An 11-year-old boy presented with dysphagia due to severe esophageal stenosis caused by esophageal ganglioneuromatosis. CONCLUSIONS: Despite its rarity, the present case implies that ganglioneuromatosis should be considered in children with idiopathic esophageal stenosis.

Small cell carcinoma esophagus-A tertiary cancer center experience of a rare variant.

BACKGROUND: Esophageal cancer is quite prevalent worldwide and usually carries a poor prognosis. Histologically, although squamous cell carcinoma and adenocarcinoma predominate, small cell carcinoma (SmCC) cases have been reported. Overall, there is a paucity of literature regarding this variant. In this article, we aim to highlight this uncommon entity of carcinoma esophagus and share our experience of SmCC patients seen over a decade at our institute. METHOD: Records of patients with SmCC histology from 2010 to 2020 were assessed. Patients' demographic characteristics, clinical characteristics, treatment received, and outcomes were taken into consideration. Results were analyzed statistically using SPSS version 22. RESULTS: Fourteen patients (nine males and five females) with a median age of 57 years (range: 35 - 72 years) were analyzed. The majority of the patients 10/14 (71.4%) received palliative radiotherapy of either 30Gy/10 fractions or 35Gy/15 fractions. Only 1/14 (7.14%) patients received neoadjuvant chemotherapy and concurrent chemoradiation (CCRT). Overall, partial response was noted in all 11 patients (78.6%) who received treatment. The average median survival was 5 months (range: 1-11 months). CONCLUSION: Although the small sample size of the study prevents us from drawing a firm conclusion, we propose national and international collaborative prospective studies for framing definitive oncologic management strategies for this rare histological variant of esophageal cancer.

Genome-Scale Multimodal Analysis of Cell-Free DNA Whole-Methylome Sequencing for Noninvasive Esophageal Cancer Detection.

PURPOSE: Simultaneous profiling of cell-free DNA (cfDNA) methylation and fragmentation features to improve the performance of cfDNA-based cancer detection is technically challenging. We developed a method to comprehensively analyze multimodal cfDNA genomic features for more sensitive esophageal squamous cell carcinoma (ESCC) detection. MATERIALS AND METHODS: Enzymatic conversion-mediated whole-methylome sequencing was applied to plasma cfDNA samples extracted from 168 patients with ESCC and 251 noncancer controls. ESCC characteristic cfDNA methylation, fragmentation, and copy number signatures were analyzed both across the genome and at accessible cis-regulatory DNA elements. To distinguish ESCC from noncancer samples, a first-layer classifier was developed for each feature type, the prediction results of which were incorporated to construct the second-layer ensemble model. RESULTS: ESCC plasma genome displayed global hypomethylation, altered fragmentation size, and chromosomal copy number alteration. Methylation and fragmentation changes at cancer tissue-specific accessible cis-regulatory DNA elements were also observed in ESCC plasma. By integrating multimodal genomic features for ESCC detection, the ensemble model showed improved performance over individual modalities. In the training cohort with a specificity of 99.2%, the detection sensitivity was 81.0% for all stages and 70.0% for stage 0-II. Consistent performance was observed in the test cohort with a specificity of 98.4%, an all-stage sensitivity of 79.8%, and a stage 0-II sensitivity of 69.0%. The performance of the classifier was associated with the disease stage, irrespective of clinical covariates. CONCLUSION: This study comprehensively profiles the epigenomic landscape of ESCC plasma and provides a novel noninvasive and sensitive ESCC detection approach with genome-scale multimodal analysis.

Esophageal cancer: current status and new insights from inflammatory markers - a brief review.

Esophageal cancer (EC) poses a significant challenge to the healthcare system due to its profound impact on cancer-related morbidity and mortality worldwide. This malignancy ranks among the most arduous conditions confronting the surgeon. EC arises from a complex interplay of genetic predispositions and environmental factors. While the incidence of esophageal adenocarcinoma (EAC) is on the rise in the West, esophageal squamous cell carcinoma (ESCC) remains prevalent in the East. Chronic inflammation plays a pivotal role in the initiation and progression of EC. Accordingly, serum inflammatory markers, growth factors, and cytokines have been shown to be clinically useful. Thus, evaluating serum cytokine levels for EC prediction is a safe and feasible screening method. Given the aggressive nature and poor prognosis of the disease, innovative approaches to diagnosis, prognosis, and management of EC are indispensable. This review discusses the major risk factors and the current landscape of EC, with a specific focus on the potential contributions of new inflammatory markers to enhance disease management and improve patient outcomes.

Non-invasive diagnosis of esophageal cancer by a simplified circulating cell-free DNA methylation assay targeting OTOP2 and KCNA3: a double-blinded, multicenter, prospective study.

BACKGROUND: Esophageal cancer (EC) is a highly lethal disease lacking early detection approaches. We previously identified that OTOP2 and KCNA3 were specifically hypermethylated in circulating cell-free DNA from patients with EC. We then developed a blood-based methylation assay targeting OTOP2 and KCNA3 (named "IEsohunter") for esophageal cancer noninvasive detection. This double-blinded, multicenter, prospective study aimed to comprehensively evaluate its clinical diagnostic performance. METHODS: Participants with EC, high-grade intraepithelial neoplasia (HGIN), other malignancies, benign gastrointestinal lesions, or no abnormalities were prospectively enrolled from 5 tertiary referral centers across China. Peripheral blood samples were collected, followed by plasma cell-free DNA methylation analysis using the IEsohunter test based on multiplex quantitative polymerase chain reaction adopting an algorithm-free interpretation strategy. The primary outcome was the diagnostic accuracy of IEsohunter test for EC. RESULTS: We prospectively enrolled 1116 participants, including 334 patients with EC, 71 with HGIN, and 711 controls. The areas under the receiver operating characteristic curves of the IEsohunter test for detecting EC and HGIN were 0.903 (95% CI 0.880-0.927) and 0.727 (95% CI 0.653-0.801), respectively. IEsohunter test showed sensitivities of 78.5% (95% CI 69.1-85.6), 87.3% (95% CI 79.4-92.4), 92.5% (95% CI 85.9-96.2), and 96.9% (95% CI 84.3-99.8) for stage I-IV EC, respectively, with an overall sensitivity of 87.4% (95% CI 83.4-90.6) and specificity of 93.3% (95% CI 91.2-94.9) for EC detection. The IEsohunter test status turned negative (100.0%, 47/47) after surgical resection of EC. CONCLUSIONS: The IEsohunter test showed high diagnostic accuracy for EC detection, indicating that it could potentially serve as a tool for noninvasive early detection and surveillance of EC.

[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.

Esophageal schwannoma mimicking non-functional parathyroid adenoma on 99mTc-sestamibi imaging: a case report.

Technetium-99m sestamibi single-photon emission computed tomography/computed tomography (99mTc-sestamibi SPECT/CT) is a mainstay of the pre-operative localization of parathyroid lesions. We report here the case of a 30 year-old woman with a fortuitously discovered 2 cm cervical mass for which a parathyroid origin was originally suspected due to its retro-thyroidal localization and a personal history of nephrolithiasis. Normal serum calcium and parathyroid hormone (PTH) levels excluded primary hyperparathyroidism, raising suspicion of a non-functional parathyroid adenoma, and SPECT/CT imaging showed that the mass was 99mTc-sestamibi-avid. Fine-needle aspiration (FNA) was performed; cytology was non-diagnostic but the needle washout was negative for thyroglobulin, calcitonin and PTH, arguing against a thyroidal or parathyroidal origin of the mass. Core needle biopsy revealed a schwannoma, ostensibly originating from the recurrent laryngeal nerve; upon surgical resection, it was finally found to arise from the esophageal submucosa. This case illustrates the fact that endocrinologists, radiologists, nuclear medicine, head and neck, and other specialists investigating patients with cervical masses should be aware that schwannomas need to be considered in the differential diagnosis of focal 99mTc-sestamibi uptake in the neck region.

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.

Optimal number of images and 2-year interval affect cancer detection in screening esophagogastroduodenoscopy: An observational study.

We aimed to identify quality indicator for esophagogastroduodenoscopy for detecting upper gastrointestinal (UGI) cancer. Data from 43,526 consecutive health checkups from August 2012 to January 2022 were retrospectively collected. The study ultimately analyzed 42,387 examinations by 12 endoscopists who performed more than 1000 examinations, including all cancers detected. These endoscopists were classified either into fast/slow group based on their mean examination time for a normal finding of esophagogastroduodenoscopy during their first year of the examination, or small/large group based on number of endoscopic images, respectively. The association between UGI cancer detection rate and examination time or the number of images was analyzed, using 5 minutes or 50 images as cutoff values. The detection rate of overall (8 pharyngeal, 39 esophageal, 69 gastric) cancers in the fast, slow, small, and large groups were 0.17%, 0.32%, 0.21%, and 0.31%, respectively. On multivariable analysis, endoscopists in the fast group or the small group were less likely to detect overall UGI cancer (OR: 0.596, 95% CI: 0.373-0.952, P = .030; OR: 0.652, 95% CI: 0.434-0.979, P = .039). Additionally, repeated endoscopy within 2 years had a higher overall cancer detection rate, compared with repeated screening after 2 years. In a sub-analysis, a significant negative relationship was found between the detection rate of gastric cancer and the number of gastric images < 35 (OR: 0.305, 95% CI: 0.189-0.492, P = .000). There was also a negative correlation trend between the detection rate of pharyngeal and esophageal cancers and the number of esophageal images < 11 (OR: 0.395, 95% CI: 0.156-1.001, P = .050). The optimal number of images and screening 2-year interval are considered useful quality indicators for detecting UGI cancer. This study also suggests that a total of 50 images, or 35 images of the stomach are suitable for detecting UGI cancer, or gastric cancer, during screening endoscopy.

Screening of co-expressed genes in hypopharyngeal carcinoma with esophageal carcinoma based on RNA sequencing and Clinical Research.

To explore the hub comorbidity genes and potential pathogenic mechanisms of hypopharyngeal carcinoma with esophageal carcinoma, and evaluate their diagnostic value for hypopharyngeal carcinoma with co-morbid esophageal carcinoma. We performed gene sequencing on tumor tissues from 6 patients with hypopharyngeal squamous cell carcinoma with esophageal squamous cell carcinoma (hereafter referred to as "group A") and 6 patients with pure hypopharyngeal squamous cell carcinoma (hereafter referred to as "group B"). We analyzed the mechanism of hub genes in the development and progression of hypopharyngeal squamous cell carcinoma with esophageal squamous cell carcinoma through bioinformatics, and constructed an ROC curve and Nomogram prediction model to analyze the value of hub genes in clinical diagnosis and treatment. 44,876 genes were sequenced in 6 patients with group A and 6 patients with group B. Among them, 76 genes showed significant statistical differences between the group A and the group B.47 genes were expressed lower in the group A than in the group B, and 29 genes were expressed higher. The top five hub genes were GABRG2, CACNA1A, CNTNAP2, NOS1, and SCN4B. GABRG2, CNTNAP2, and SCN4B in the hub genes have high diagnostic value in determining whether hypopharyngeal carcinoma patients have combined esophageal carcinoma (AUC: 0.944, 0.944, 0.972). These genes could possibly be used as potential molecular markers for assessing the risk of co-morbidity of hypopharyngeal carcinoma combined with esophageal carcinoma.

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.

The TEOGIC study project: a comprehensive characterization of early onset gastrointestinal cancer in the Northern area of Spain.

BACKGROUND: Gastrointestinal cancers represent one of the most prevalent diseases worldwide. Strikingly, the incidence of Early Onset Gastrointestinal Cancer (EOGIC) has been rising during the last decades and changes in lifestyle and environmental exposure seem to play a role. EOGIC has been defined as a different entity compared to on-average gastrointestinal cancer, with distinct clinical and molecular characteristics. Inherent to the particularities of younger age, there is an unmet need for a tailored approach for the management of these patients. The TEOGIC proposes a comprehensive study to characterize EOGIC patients in the northern of Spain. METHODS: Patients with histologically confirmed new diagnosis of colorectal, gastroesophageal and pancreatic adenocarcinoma will be considered for two cohorts: EOGIC (≤ 50 years old) and non-EOGIC (60-75 years old), with a ratio of 1:2. Two hundred and forty patients will be recruited in 4 Public Hospitals from northern Spain. After receiving unified informed consent, demographic and clinical data of the patients will be collected in a REDCap database. Lifestyle related data will be obtained in questionnaires assessing diet, physical activity and the general quality of life of the patients before diagnosis. Biological samples prior to any onco-specific treatment will be obtained for the analyses of circulating inflammatory proteins, gut microbiota, and the proteome of the tumor microenvironment. Histologic characteristics and routine biomarkers will be also collected. Thereafter, data will be integrated and analyzed to assess tumor specific, pan-tumor and sex-associated differential characteristics of EOGIC. DISCUSSION: The underlying risk factors and differential characteristics of EOGIC remain poorly studied, particularly in our geographical area. Although limited by the exploratory nature and the small sample size estimated to be recruited, TEOGIC represents the first attempt to comprehensively characterize these young patients, and thus attend to their special needs. Findings derived from this study could contribute to raise awareness and preventive behaviors in the population. In parallel, molecular studies could lead to the identification of potential novel non-invasive biomarkers and therapeutic targets that would help in the development of the tailored clinical management of these patients, focusing on screening programs for early diagnosis and precision medicine.

Effective Endoscopic Submucosal Dissection of a Huge Esophageal Liposarcoma: A Case Report.

This case report presents the successful endoscopic submucosal dissection (ESD) of a well-differentiated esophageal liposarcoma in a 51-year-old male with persistent dysphagia. The cause was initially diagnosed as a 10 cm pedunculated lesion extending from the upper esophageal sphincter to the mid-esophagus. An ESD was chosen over traditional surgery because it is less invasive. The procedure involved a precise submucosal injection and excision with special techniques to manage bleeding from a central vessel. Despite the extraction challenges owing to the size of the lesion, it was successfully removed orally. A histopathological examination of the 8.3×4.2×2.3 cm specimen revealed the characteristic features of a well-differentiated liposarcoma, including MDM2 and CDK4 positivity. The follow-up revealed no recurrence, and active surveillance has been performed since. This report highlights the versatility of ESD in treating significant esophageal tumors and provides evidence for its efficacy as a minimally invasive alternative.

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 Diagnostic, Staging, and Restaging Evaluation of Esophageal and Gastric Cancer.

The initial endoscopic and staging evaluation of esophagogastric cancers must be accurate and comprehensive in order to select the optimal therapeutic plan for the patient. Esophageal and gastric cancers (and treatment paradigms) are delineated by their proximity to the cardia (within 2 cm). The most frequent and important symptom that informs the initial staging evaluation is dysphagia, which is associated with at least cT3 or locally advanced disease. Endoscopic ultrasound is often needed if earlier stage disease is suspected, preferably in combination with endoscopic mucosal or submucosal resection or fine-needle aspiration of suspicious lymph nodes to enhance staging accuracy.

Challenges in Diagnosis of Esophageal Tuberculosis.

Esophageal tuberculosis (TB) is a rare manifestation of extrapulmonary TB, accounting for <0.2% of all TB cases. Esophageal TB most commonly presents with dysphagia, odynophagia, retrosternal pain, and systemic symptoms like decreased appetite, loss of weight, and low-grade fever as associated or other presentations. We report a similar case recently encountered as an elderly male patient presented with chronic dysphagia to solids, loss of appetite, and significant loss of weight. Radiological and endoscopy pictures looked like esophageal cancer with histopathological examination (twice) negative for the same. Diagnosis of esophageal TB was confirmed by GeneXpert Ultra of biopsy sample and histopathological examination was suggestive of granulomatous esophagitis. The patient improved on 6 months antitubercular therapy. The unique aspect of this case was how the lesion mimicked an esophageal carcinoma on imaging which posed a diagnostic challenge.

Using Machine Learning and miRNA for the Diagnosis of Esophageal Cancer.

BACKGROUND: Esophageal cancer (EC) remains a global health challenge, often diagnosed at advanced stages, leading to high mortality rates. Current diagnostic tools for EC are limited in their efficacy. This study aims to harness the potential of microRNAs (miRNAs) as novel, noninvasive diagnostic biomarkers for EC. Our objective was to determine the diagnostic accuracy of miRNAs, particularly in distinguishing miRNAs associated with EC from control miRNAs. METHODS: We applied machine learning (ML) techniques in WEKA (Waikato Environment for Knowledge Analysis) and TensorFlow Keras to a dataset of miRNA sequences and gene targets, assessing the predictive power of several classifiers: naïve Bayes, multilayer perceptron, Hoeffding tree, random forest, and random tree. The data were further subjected to InfoGain feature selection to identify the most informative miRNA sequence and gene target descriptors. The ML models' abilities to distinguish between miRNA implicated in EC and control group miRNA was then tested. RESULTS: Of the tested WEKA classifiers, the top 3 performing ones were random forest, Hoeffding tree, and naïve Bayes. The TensorFlow Keras neural network model was subsequently trained and tested, the model's predictive power was further validated using an independent dataset. The TensorFlow Keras gave an accuracy 0.91. The WEKA best algorithm (naïve Bayes) model yielded an accuracy of 0.94. CONCLUSIONS: The results demonstrate the potential of ML-based miRNA classifiers in diagnosing EC. However, further studies are necessary to validate these findings and explore the full clinical potential of this approach.

Raman spectroscopy for esophageal tumor diagnosis and delineation using machine learning and the portable Raman spectrometer.

Esophageal cancer is one of the leading causes of cancer-related deaths worldwide. The identification of residual tumor tissues in the surgical margin of esophageal cancer is essential for the treatment and prognosis of cancer patients. But the current diagnostic methods, either pathological frozen section or paraffin section examination, are laborious, time-consuming, and inconvenient. Raman spectroscopy is a label-free and non-invasive analytical technique that provides molecular information with high specificity. Here, we report the use of a portable Raman system and machine learning algorithms to achieve accurate diagnosis of esophageal tumor tissue in surgically resected specimens. We tested five machine learning-based classification methods, including k-Nearest Neighbors, Adaptive Boosting, Random Forest, Principal Component Analysis-Linear Discriminant Analysis, and Support Vector Machine (SVM). Among them, SVM shows the highest accuracy (88.61 %) in classifying the esophageal tumor and normal tissues. The portable Raman system demonstrates robust measurements with an acceptable focal plane shift of up to 3 mm, which enables large-area Raman mapping on resected tissues. Based on this, we finally achieve successful Raman visualization of tumor boundaries on surgical margin specimens, and the Raman measurement time is less than 5 min. This work provides a robust, convenient, accurate, and cost-effective tool for the diagnosis of esophageal cancer tumors, advancing toward Raman-based clinical intraoperative applications.