Selecting Patients Who May Benefit From Immunotherapy by Tissue-based Biomarkers
We have established a machine learning model based on effective TIIC signature which could select GC patients who may benefit from immunotherapy. The current study aims to enroll 300 GC patients as a validation cohort to vertify the accuracy of TIIC signature in predicting immunotherapy efficacy
• Having signed informed consent
• Age:18-80 years old
• Histologically confirmed gastric adenocarcinoma
• Unresectable recurrent or metastatic gastric cancer
• Previous neo-adjuvant or adjuvant treatment for gastric cancer, if applicable, more than 6 months
• Measurable disease according to the RECIST criteria
• Karnofsky performance status ≥70
• Life expectancy of ≥3 month
• No prior radiotherapy except radiotherapy at non-target lesion of the study more than 4 weeks
• ALT and AST\<2.5 times ULN (≤5 times ULN in patients with liver metastases)
• Serum albumin level ≥3.0g/dL
• Serum AKP \< 2.5 times ULN
• Serum creatinine \<ULN, and CCr \< 60ml/min
• Bilirubin level \< 1.5 ULN
• WBC\>3,000/mm3, absolute neutrophil count ≥2000/mm3, platelet\>100,000/mm3, Hb\>9g/dl