Predicting the risk of recurrence of esophageal squamous cell carcinoma (ESCC)
by clinicopathological features is a complex but crucial process involving multiple considerations. The following are some key clinicopathological features and their relationship to the risk of ESCC recurrence:
1. Tumor staging and depth of invasion: According to the TNM staging system of the American Cancer Society (AJCC), the stage of ESCC is an important factor affecting the risk of recurrence. Patients with advanced ESCC (eg, T3, T4) have a higher risk of recurrence than those with early ESCC (eg, Tis, T1). Depth of invasion: Tumor invasion into deeper layers of the esophageal wall (e.g., muscularis propria or deeper) is generally associated with a higher risk of recurrence.
2. Lymph node metastasis: The risk of recurrence in ESCC patients with lymph node metastasis was significantly increased. The number and location of lymph node metastases (e.g., paratracheal, neck, etc.) May also affect the risk of recurrence. Lymphatic vessel invasion: Lymphatic vessel invasion is one of the risk factors for lymph node metastasis and an important factor in predicting the risk of recurrence. Although lymphatic invasion has not been identified as an independent prognostic factor in some studies, it is often associated with poor outcomes.
3. Location and length of the tumor Location of the tumor: Different locations of the tumor in the esophagus (such as cervical, upper thoracic, middle thoracic and lower thoracic) may affect the risk of recurrence. Some studies have found a higher rate of local recurrence in the upper and middle thoracic segments and a higher rate of distant recurrence in the lower thoracic segment. Tumor length: Longer tumors are generally associated with a higher risk of recurrence. For example, patients with tumors greater than 3 cm or 4 cm in length tend to have lower survival rates.
4. Tumor differentiation degree and margin status Tumor differentiation degree: The prognosis of well-differentiated and moderately differentiated squamous cell carcinoma was relatively good, while the prognosis of poorly differentiated squamous cell carcinoma was poor. The degree of differentiation is usually inversely correlated with T stage, that is, the lower the degree of differentiation, the higher the T stage, and the higher the risk of recurrence. Margin status: Proximal and distal esophageal margins are less positive than circumferential margins (basal margins or vertical margins), but circumferential margins are usually associated with poor prognosis.
5. Other clinicopathological features Age: Older patients may have a higher risk of recurrence. Neurologic invasion: Patients with ESCC who have neurologic invasion generally have a higher risk of recurrence. Expression of immune proteins: In recent years, studies have found that the expression level of some immune proteins (such as IDO1) in the tumor microenvironment can predict the risk of recurrence and distant metastasis of ESCC patients. Predictive models and risk assessment Based on the above clinicopathological characteristics, predictive models can be constructed to assess the risk of recurrence in patients with ESCC. For example, GeoMx DSP spatial protein detection and analysis technology can be used to detect the expression profile of immune proteins in tumor areas and tumor microenvironment, and to establish a scoring model for predicting local recurrence/distant metastasis of patients after operation. In addition, other biomarkers and clinical information, such as gene mutations and tumor marker levels, can be combined to further improve the accuracy of prediction. To sum up, through the comprehensive consideration of multiple clinicopathological features, we can more accurately predict the recurrence risk of ESCC patients, and provide an important basis for the development of personalized treatment. However, it should be noted that the specific situation of each patient is unique, so the comprehensive evaluation should be combined with the individual situation of patients in practical application.
