PPIO-009 Tumor Regression Grade and Tumor Location in Esophageal Cancer

Oesophageal cancer is the eighth most common cancer globally (934,870 new cases) and the sixth most common cause of cancer death (287,270 new deaths).The incidence, prevalence, and histological type of oesophageal cancer vary geographically , with about 75% of cases occurring in Asia, with China having the highest share, accounting for about 50% of the total cases and cancer-specific deaths. According to the National Bureau of Statistics of China, Statistics 2022, there were 252,500 cases of oesophageal cancer and 193,900 deaths in China in 2016, making oesophageal cancer the sixth most common cancer and the fifth leading cause of cancer death in China . The etiology of the two most common histological subtypes (esophageal squamous cell carcinoma [ESCC] and adenocarcinoma) varies widely. In the West, heavy alcohol consumption and smoking and their synergistic effects are the main risk factors for ESCC . However, in low-income countries, such as parts of Asia and sub-Saharan Africa, the main risk factors for ESCC, which typically accounts for more than 90% of all oesophageal cancer cases, have not been elucidated.

Preclinical studies have shown that the PD-1/PD-L1 axis can be activated early in solid tumours , and a durable protective effect may occur with preoperative induction of the immune response. Considering the dramatic decrease in tumour antigens after surgical resection and the removal of intact blood vessels and lymph nodes delivering the drug may affect the immunotherapeutic efficacy, the use of immunotherapy preoperatively may be more effective. Several phase 1/2 and phase 2 studies have shown a manageable safety profile and preliminary demonstration of efficacy when PD-1/PD-L1 inhibitors were added to perioperative therapy in resectable EC subjects. PD-1 inhibitors have demonstrated significant benefit in both second-line therapy and first-line therapy. Given the evidence of antitumour activity of immunotherapy in patients with ESCC and the continuing need to improve survival and reduce recurrence rates in resectable oesophageal cancer, a number of studies exploring the antitumour activity of immunotherapy in the treatment of resectable disease have tentatively shown promise as a neoadjuvant therapy.

Currently, after patients receive neoadjuvant therapy, tumour cell regression can occur with a variety of histological changes, such as tumour cell necrosis and apoptosis, fibrous tissue proliferation, inflammatory cell infiltration, foam cell aggregation, cell-free mucus production and formation of mucus pools, as well as calcified foci formation. However, not all tumours produce the above regression reactions after treatment, fibrohistiocytosis and inflammatory cell infiltration are the most common histological regression changes, and in order to assess the clinical therapeutic efficacy of the tumour, tumour regression needs to be graded quantitatively.TRG is a quantitative analysis of the pathology of tumours resected after neoadjuvant chemotherapy to clarify the therapeutic efficacy of chemotherapy or targeted drugs on tumours and to predict the patient's postoperative recurrence and metastasis. Metastasis. It was firstly used to assess the efficacy of oesophageal cancer after concurrent radiotherapy; and then gradually used to assess the efficacy of oesophageal cancer. The current assessment of post-radiotherapy samples is mainly based on the proportion of residual tumour components and fibrosis to grade pathological regression. Currently, the main methods for TRG scoring after neoadjuvant radiotherapy include NCCN, AJCC and other standards.

Currently, based on the data of pre-surgical clinical studies, the remission rate after neoadjuvant therapy varies in different oesophageal segments, which may indicate that the difference in blood supply of oesophageal cancer in different segments affects the blood drug concentration, leading to different clinical outcomes in patients with oesophageal cancer in different segments. In order to better treat patients in different segments, it is necessary to establish a prediction model based on the clinical data of patients in different oesophageal segments for better clinical decision-making.