ObjectiveThis article aims to summarize the historical evolution of thyroid cancer classification and explore the establishment of a precise classification system based on molecular characteristics and its impact on clinical applications.MethodsA literature review was conducted to analyze and organize the recent influences of molecular classification of thyroid cancer on clinical diagnosis and treatment. ResultsIn recent years, the classification of thyroid cancer has introduced molecular features such as BRAF and RAS mutations, highlighting the close association between these molecular characteristics and prognosis. For example, the BRAF V600E mutation is associated with high aggressiveness in papillary thyroid cancer, while RAS mutations suggest malignant potential in follicular tumors. With the advancement of multi-omics research, classification strategies based on multi-omics have shown significant value in the diagnosis, monitoring, treatment, and prognostic assessment of thyroid cancer. Although multi-omics integration has significantly improved the accuracy of prognostic assessments in thyroid cancer, there are still limitations, including imprecise detection of tumor heterogeneity and insufficient sensitivity and specificity of molecular biomarker detection. ConclusionsThe classification of thyroid cancer is developing towards the integration of molecular features to achieve more precise diagnosis and treatment. To accomplish this goal, it is necessary to overcome the challenges of tumor heterogeneity and the limitations of detection technologies in the future, and to promote the practical application of molecular classification in clinical settings.
Pulmonary adenocarcinoma in situ is reclassified as precursor glandular lesions in the fifth edition of WHO classification of thoracic tumours, causing widespread attention and heated debate among domestic thoracic oncologists, radiologists, pathologists and surgeons. We would like to comment on the topic and make a few suggestions on the management of pulmonary nodule during lung cancer screening. We are open to all suggestion and welcome debates.
ObjectiveTo assess the accuracy of CT features of lung nodules (≤3 cm) in predicting the accuracy of the pathological subtype and degree of infiltration of adenocarcinoma. Methods We retrospectively analyzed the clinical data of 333 patients with non-cavitary pulmonary nodules diagnosed as adenocarcinoma by surgery and pathology in the China-Japan Friendship Hospital from 2011 to 2018, including 108 males and 225 females, aged 16-82 (59.57±10.16) years. The basic clinical data and CT characteristics of the patients were recorded. ResultsWhen the average CT value was ≥−507 Hu, the maximum diameter of the lung window was ≥14.5 mm, and the solid component ratio was ≥5.0%, it indicated more likely the invasive adenocarcinoma (IAC). The higher the average CT value of the nodule, the larger the maximum diameter of the lung window, and the more solid components, the higher the degree of infiltration. CT morphological features (including burrs, lobes, vascular signs, bronchial signs, pleural stretch or depression signs) were more common in IAC. Among them, burrs were more common in acinar adenocarcinoma and papillary adenocarcinoma. In invasive adenocarcinoma, the higher the risk of recurrence of the pathological subtype, the greater the average CT value. When the average CT value of IAC was >−106 Hu, and the proportion of solid components was ≥70.5%, the histological subtypes were more inclined to micropapillary/solid predominant adenocarcinoma. Conclusion The evaluation of CT features of lung nodules can improve the predictive value of histopathological types of lung adeno- carcinoma, thereby optimizing clinical treatment decisions and obtaining more ideal therapeutic effects.