You will be shown an abstract from a biomedical research paper. Given this abstract, your task is to extract all unique entities of the following types: ["HealthCareActivity", "InjuryOrPoisoning", "BodySubstance", "IntellectualProduct", "AnatomicalStructure", "SpatialConcept", "Chemical", "Bacterium", "MedicalDevice", "Organization", "BiomedicalOccupationOrDiscipline", "Finding", "BiologicFunction", "Virus", "ResearchActivity", "ClinicalAttribute", "PopulationGroup", "Eukaryote", "BodySystem", "Food", "ProfessionalOrOccupationalGroup"].

Please return the output as a JSON object of the format: {"Virus": ["HIV", ...], "Bacterium": ["MRSA", ...], "AnatomicalStructure": ["Lung", ...], "BodySystem": ["CNS", ...], "BodySubstance": ["Serum", ...], "Finding": ["Headache", ...], "InjuryOrPoisoning": ["Fracture", ...], "BiologicFunction": ["Death", ...], "HealthCareActivity": ["Biopsy", ...], "ResearchActivity": ["Clinical trial", ...], "MedicalDevice": ["Lenses", ...], "SpatialConcept": ["Camps", ...], "BiomedicalOccupationOrDiscipline": ["Forensic medicine", ...], "Organization": ["WHO", ...], "ProfessionalOrOccupationalGroup": ["Provider", ...], "PopulationGroup": ["Swimmers", ...], "Chemical": ["Gold", ...], "Food": ["Rice", ...], "IntellectualProduct": ["RPAM", ...], "ClinicalAttribute": ["Biomarker", ...], "Eukaryote": ["Dogs", ...]}. The keys should be entity types and values should be lists of extracted entities belonging to the corresponding type. If you cannot find entities belonging to a specific type, the value should be [].

Only output the JSON object and do not include any additional text.

Abstract:

Expressions of CD8 + TILs, PD-L1 and Foxp3 + TILs in stage I NSCLC guiding adjuvant chemotherapy decisions Currently, adjuvant chemotherapy is recommended for patients with high risk stage I non-small cell lung cancer (NSCLC). However, identifying high risk patients remains a challenge. This study aims to identify the patient cohorts more likely to benefit from adjuvant chemotherapy based on the tumor micro-immune environment. CD8 + TILs significantly associated with disease-free survival (DFS) and overall survial (OS) (p=0.002; 0.040). Patients with high risk factors may also predict shorter DFS (P=0.056). When compared together, patients with high - CD8 + TILs showed better DFS than patients with low - CD8 + TILs, no matter their risk factors status. There's no correlation between PD-L1 expressions and survival. PD-L1 was highly expressed in men, squamous and well differentiated carcinoma. In addition, Foxp3 + TILs alone didn't show any prognostic effects, but low - Foxp3 / high - CD8 + TILs were associated with prolonged DFS (p=0.031). A total of 126 patients with surgically resected stage I NSCLC were included to perform immunohistochemistry of CD8 + tumor infiltrating lymphocytes (TILs), programmed death ligand-1 (PD-L1) and forkhead box P3 (Foxp3)+ TILs. CD8 + TILs are effective prognostic predictors. Patients with surgically resected stage I NSCLC showing low CD8 + TILs could be considered for adjuvant chemotherapy, even if they have no high risk features.
{"AnatomicalStructure": ["tumor infiltrating lymphocytes", "TILs"], "Bacterium": [], "BiologicFunction": ["stage I NSCLC", "Expressions", "expressed", "tumor", "stage I non-small cell lung cancer", "expressions", "NSCLC", "carcinoma", "decisions"], "BiomedicalOccupationOrDiscipline": [], "BodySubstance": [], "BodySystem": [], "Chemical": ["CD8", "Foxp3", "forkhead box P3", "PD-L1", "programmed death ligand-1"], "ClinicalAttribute": [], "Eukaryote": [], "Finding": ["high risk", "no correlation"], "Food": [], "HealthCareActivity": ["immunohistochemistry", "adjuvant chemotherapy"], "InjuryOrPoisoning": [], "IntellectualProduct": [], "MedicalDevice": [], "Organization": [], "PopulationGroup": ["men", "cohorts"], "ProfessionalOrOccupationalGroup": [], "ResearchActivity": ["study"], "SpatialConcept": ["environment"], "Virus": []}