Background: Noninvasive detection of early stage cancers with accurate prediction of tumor tissue-of-origin could improve patient prognosis. Because miRNA profiles differ between organs, circulating miRNomics represent a promising method for early detection of cancers, but this has not been shown conclusively. Methods: A serum miRNA profile (miRNomes)–based classifier was evaluated for its ability to discriminate cancer types using advanced machine learning. The training set comprised 7931 serum samples from patients with 13 types of solid cancers and 5013 noncancer samples. The validation set consisted of 1990 cancer and 1256 noncancer samples. The contribution of each miRNA to the cancer-type classification was evaluated, and those with a high contribution were identified. Results: Cancer type was predicted with an accuracy of 0.88 (95% confidence interval [CI] = 0.87 to 0.90) in all stages and an accuracy of 0.90 (95% CI = 0.88 to 0.91) in resectable stages (stages 0-II). The F1 score for the discrimination of the 13 cancer types was 0.93. Optimal classification performance was achieved with at least 100 miRNAs that contributed the strongest to accurate prediction of cancer type. Assessment of tissue expression patterns of these miRNAs suggested that miRNAs secreted from the tumor environment could be used to establish cancer type–specific serum miRNomes. Conclusions: This study demonstrates that large-scale serum miRNomics in combination with machine learning could lead to the development of a blood-based cancer classification system. Further investigations of the regulating mechanisms of the miRNAs that contributed strongly to accurate prediction of cancer type could pave the way for the clinical use of circulating miRNA diagnostics.

The tumor–node metastasis (TNM) classification, originally developed in 1943 and subsequently adopted by the Union for International Cancer Control and the American Joint Committee on Cancer, is regularly updated based on new information and developments. The TNM classification system is the main tool used for both clinical and pathological staging of cancers worldwide. The 8th edition of the TNM classification for esophageal and esophagogastric junction (EGJ) cancer, released in 2017, was updated from the 7th edition based on additional data supplied by the Worldwide Esophageal Cancer Collaboration group. We summarize the main changes between the 7th and 8th editions of this TNM classification. Notable changes included separate clinical, pathological and pathological prognostic staging for adenocarcinomas and squamous cell carcinomas. Pathological prognostic staging was also improved by updating the T- and N-factors regarding histopathological differentiation and tumor location, respectively. The definition of EGJ cancer was changed from tumors centered within 5 cm to tumors within 2 cm of the EGJ. These updates to the TNM classification will help to improve the personalized management and treatment of patients with esophageal and EGJ cancers.

The purposes of this study were to determine the role of surgical treatment and to identify factors affecting survival of patients undergoing resection of pulmonary metastatic tumors from esophageal carcinoma. We reviewed 33 patients who had undergone resection of pulmonary metastatic tumors from esophageal carcinoma after definitive treatment. The operative morbidity rate was only 5%, no patients died within 30 days after resection, and complete resection was achieved in 30 patients. The overall 1-, 3- and 5-year survival rates after pulmonary metastasectomy were 79.4, 47.8 and 43.0%, respectively, and the median survival time was 17.9 months. The factors found on univariate analysis to affect survival significantly were disease-free interval <16 months and nodal involvement of the primary tumor. The most frequent pattern of initial recurrence after pulmonary resection was distant metastasis (70%). We demonstrated the safety and effectiveness of surgical resection for selected patients with pulmonary metastatic tumors from esophageal carcinoma. However, with a high recurrence rate in patients with negative prognostic factors, adjuvant systemic chemotherapy after pulmonary resection should be considered.