Recent advances in multidisciplinary therapy for adenocarcinoma of the esophagus and esophagogastric junction

Prognostic significance and risk factors of mediastinal lymph node metastasis in esophagogastric junction cancer: a single-center, retrospective study

BACKGROUND

Although the optimal extent of lymph node dissection in esophagogastric junction cancer (EGJC) has been reported, the efficacy of mediastinal lymph node dissection remains unclear. We aimed to identify risk factors for mediastinal lymph node metastasis and its prognostic impact in patients with EGJC.

METHODS

A total of 100 consecutive patients who underwent curative surgery for EGJC were eligible. We examined the rates of metastasis, prognosis, and therapeutic value index at each mediastinal lymph node station. In addition, multivariate analyses were performed to identify risk factors for mediastinal lymph node metastasis.

RESULTS

The rates of upper, middle, and lower mediastinal lymph node metastases were 12.0%, 20.7%, and 13.2%, respectively. The 5-year overall survival rate was lower in patients with mediastinal lymph node metastasis than in those without mediastinal lymph node metastasis (11.1% vs. 59.2%, p < 0.01). The therapeutic value index was 0 in patients with upper/middle mediastinal lymph node metastasis, and mediastinal lymph node metastasis was an independent prognostic factor (hazard ratio 6.59, 95% confidence interval [CI] 2.48-17.9, p < 0.01). Additionally, the length of esophageal invasion and the presence of hiatal hernia were independent predictors of mediastinal lymph node metastasis (odds ratio 8.21, 95%CI 1.44-46.8, p = 0.02 and odds ratio 7.13, 95%CI 1.22-41.8, p = 0.03).

CONCLUSION

No survival benefit of mediastinal lymph node dissection was observed. Intensive multidisciplinary treatment could be considered in patients with predicted mediastinal lymph node metastasis, such as those with longer esophageal invasion and those with hiatal hernia.

Current trends in the management of Gastro-oEsophageal cancers: Updates to the ESSO core curriculum (ESSO-ETC-UGI-WG initiative)

Gastro-oEsophageal Cancers (GECs) are severe diseases whose management is rapidly evolving. The European Society of Surgical Oncology (ESSO) is committed to the generation and spread of knowledge, and promotes the multidisciplinary management of cancer patients through its core curriculum. The present work discusses the approach to GECs, including the management of oligometastatic oesophagogastric cancers (OMEC), the diagnosis and management of peritoneal metastases from gastric cancer (GC), the management of Siewert Type II tumors, the importance of mesogastric excision, the role of robotic surgery, textbook outcomes, organ preserving options, the use of molecular markers and immune check-point inhibitors in the management of patients with GECs, as well as the improvement of current clinical practice guidelines for the management of patients with GECs. The aim of the present review is to provide a concise overview of the state-of-the-art on the management of patients with GECs and, at the same time, to share the latest advancements in the field and to foster the debate between surgical oncologists treating GECs worldwide. We are sure that our work will, at the same time, give an update to the advanced surgical oncologists and help the training surgical oncologists to settle down the foundations for their future practice.

Construction of a novel nomogram for predicting overall survival in patients with Siewert type II AEG based on LODDS: a study based on the seer database and external validation

Background

In recent years, the incidence of adenocarcinoma of the esophagogastric junction (AEG) has been rapidly increasing globally. Despite advances in the diagnosis and treatment of AEG, the overall prognosis for AEG patients remains concerning. Therefore, analyzing prognostic factors for AEG patients of Siewert type II and constructing a prognostic model for AEG patients is important.

Methods

Data of primary Siewert type II AEG patients from the SEER database from 2004 to 2015 were obtained and randomly divided into training and internal validation cohort. Additionally, data of primary Siewert type II AEG patients from the China Medical University Dandong Central Hospital from 2012 to 2018 were collected for external validation. Each variable in the training set underwent univariate Cox analysis, and variables with statistical significance (p < 0.05) were added to the LASSO equation for feature selection. Multivariate Cox analysis was then conducted to determine the independent predictive factors. A nomogram for predicting overall survival (OS) was developed, and its performance was evaluated using ROC curves, calibration curves, and decision curves. NRI and IDI were calculated to assess the improvement of the new prediction model relative to TNM staging. Patients were stratified into high-risk and low-risk groups based on the risk scores from the nomogram.

Results

Age, Differentiation grade, T stage, M stage, and LODDS (Log Odds of Positive Lymph Nodes)were independent prognostic factors for OS. The AUC values of the ROC curves for the nomogram in the training set, internal validation set, and external validation set were all greater than 0.7 and higher than those of TNM staging alone. Calibration curves indicated consistency between the predicted and actual outcomes. Decision curve analysis showed moderate net benefit. The NRI and IDI values of the nomogram were greater than 0 in the training, internal validation, and external validation sets. Risk stratification based on the nomogram's risk score demonstrated significant differences in survival rates between the high-risk and low-risk groups.

Conclusion

We developed and validated a nomogram for predicting overall survival (OS) in patients with Siewert type II AEG, which assists clinicians in accurately predicting mortality risk and recommending personalized treatment strategies.

Decoding common genetic alterations between Barrett's esophagus and esophageal adenocarcinoma: A bioinformatics analysis

Background

Esophageal adenocarcinoma (EAC) is a common cancer with a poor prognosis in advanced stages. Therefore, early EAC diagnosis and treatment have gained attention in recent decades. It has been found that various pathological changes, particularly Barrett's Esophagus (BE), can occur in the esophageal tissue before the development of EAC. In this study, we aimed to identify the molecular contributor in BE to EAC progression by detecting the essential regulatory genes that are differentially expressed in both BE and EAC.

Materials and methods

We conducted a comprehensive bioinformatics analysis to detect BE and EAC-associated genes. The common differentially expressed genes (DEGs) and common single nucleotide polymorphisms (SNPs) were detected using the GEO and DisGeNET databases, respectively. Then, hub genes and the top modules within the protein-protein interaction network were identified. Moreover, the co-expression network of the top module by the HIPPIE database was constructed. Additionally, the gene regulatory network was constructed based on miRNAs and circRNAs. Lastly, we inspected the DGIdb database for possible interacted drugs.

Results

Our microarray dataset analysis identified 92 common DEGs between BE and EAC with significant enrichment in skin and epidermis development genes. The study also identified 22 common SNPs between BE and EAC. The top module of PPI network analysis included SCEL, KRT6A, SPRR1A, SPRR1B, SPRR3, PPL, SPRR2B, EVPL, and CSTA. We constructed a ceRNA network involving three specific mRNAs, 23 miRNAs, and 101 selected circRNAs. According to the results from the DGIdb database, TD101 was found to interact with the KRT6A gene.

Conclusion

The present study provides novel potential candidate genes that may be involved in the molecular association between Esophageal adenocarcinoma and Barrett's Esophagus, resulting in developing the diagnostic tools and therapeutic targets to prevent progression of BE to EAC.

The development and validation of automated machine learning models for predicting lymph node metastasis in Siewert type II T1 adenocarcinoma of the esophagogastric junction

Background

Lymph node metastasis (LNM) is considered an essential prognosis factor for adenocarcinoma of the esophagogastric junction (AEG), which also affects the treatment strategies of AEG. We aimed to evaluate automated machine learning (AutoML) algorithms for predicting LNM in Siewert type II T1 AEG.

Methods

A total of 878 patients with Siewert type II T1 AEG were selected from the Surveillance, Epidemiology, and End Results (SEER) database to develop the LNM predictive models. The patients from two hospitals in Suzhou were collected as the test set. We applied five machine learning algorithms to develop the LNM prediction models. The performance of predictive models was assessed using various metrics including accuracy, sensitivity, specificity, the area under the curve (AUC), and receiver operating characteristic (ROC) curve.

Results

Patients with LNM exhibited a higher proportion of male individuals, a poor degree of differentiation, and submucosal infiltration, with statistical differences. The deep learning (DL) model demonstrated relatively good accuracy (0.713) and sensitivity (0.868) among the five models. Moreover, the DL model achieved the highest AUC (0.781) and sensitivity (1.000) in the test set.

Conclusion

The DL model showed good predictive performance among five AutoML models, indicating the advantage of AutoML in modeling LNM prediction in patients with Siewert type II T1 AEG.

Effect of two surgical approaches on the lung function and prognosis of patients with combined esophagogastric cancer

BACKGROUND

Adenocarcinoma of the esophagogastric junction has a center of origin within 5 cm of the esophagogastric junction. Surgical resection remains the main treatment. A transthoracic approach is recommended for Siewert I adenocarcinoma of the esophagogastric junction and a transabdominal approach is recommended for Siewert III adenocarcinoma of the esophagogastric junction. However, there is a need to determine the optimal surgical approach for Siewert II adenocarcinoma of the esophagogastric junction to improve lung function and the prognosis of patients.

AIM

To investigate and compare the surgical effects, postoperative changes in pulmonary function, and prognoses of two approaches to treating combined esophagogastric cancer.

METHODS

One hundred and thirty-eight patients with combined esophagogastric cancer treated by general and thoracic surgeries in our hospital were selected. They were divided into group A comprising 70 patients (transabdominal approach) and group B comprising 68 patients (transthoracic approach) based on the surgical approach. The indexes related to surgical trauma, number of removed lymph nodes, indexes of lung function before and after surgery, survival rate, and survival duration of the two groups were compared 3 years after surgery.

RESULTS

The duration of surgery, length of hospital stay, and postoperative drainage duration of the patients in group A were shorter than those of the patients in group B, and the volume of blood loss caused by surgery was lower for group A than for group B (P < 0.05). At the one-month postoperative review, the first second, maximum ventilation volume, forceful lung volume, and lung volume values were higher for group A than for group B (P < 0.05). Preoperatively, the QLQ-OES18 scale scores of the patients in group A were higher than those in group B on re-evaluation at 3 mo postoperatively (P < 0.05). The surgical complication rate of the patients in group A was 10.00%, which was lower than that of patients in group B, which was 23.53% (P < 0.05).

CONCLUSION

Transabdominal and transthoracic surgical approaches are comparable in treating combined esophagogastric cancer; however, the former results in lesser surgical trauma, milder changes in pulmonary function, and fewer complications.