RESUMO
BACKGROUND: We aim to implement an immune cell score model in routine clinical practice for resected non-small-cell lung cancer (NSCLC) patients (NCT03299478). Molecular and genomic features associated with immune phenotypes in NSCLC have not been explored in detail. PATIENTS AND METHODS: We developed a machine learning (ML)-based model to classify tumors into one of three categories: inflamed, altered, and desert, based on the spatial distribution of CD8+ T cells in two prospective (n = 453; TNM-I trial) and retrospective (n = 481) stage I-IIIA NSCLC surgical cohorts. NanoString assays and targeted gene panel sequencing were used to evaluate the association of gene expression and mutations with immune phenotypes. RESULTS: Among the total of 934 patients, 24.4% of tumors were classified as inflamed, 51.3% as altered, and 24.3% as desert. There were significant associations between ML-derived immune phenotypes and adaptive immunity gene expression signatures. We identified a strong association of the nuclear factor-κB pathway and CD8+ T-cell exclusion through a positive enrichment in the desert phenotype. KEAP1 [odds ratio (OR) 0.27, Q = 0.02] and STK11 (OR 0.39, Q = 0.04) were significantly co-mutated in non-inflamed lung adenocarcinoma (LUAD) compared to the inflamed phenotype. In the retrospective cohort, the inflamed phenotype was an independent prognostic factor for prolonged disease-specific survival and time to recurrence (hazard ratio 0.61, P = 0.01 and 0.65, P = 0.02, respectively). CONCLUSIONS: ML-based immune phenotyping by spatial distribution of T cells in resected NSCLC is able to identify patients at greater risk of disease recurrence after surgical resection. LUADs with concurrent KEAP1 and STK11 mutations are enriched for altered and desert immune phenotypes.
Assuntos
Carcinoma Pulmonar de Células não Pequenas , Neoplasias Pulmonares , Humanos , Carcinoma Pulmonar de Células não Pequenas/genética , Carcinoma Pulmonar de Células não Pequenas/cirurgia , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/cirurgia , Estudos Retrospectivos , Proteína 1 Associada a ECH Semelhante a Kelch/genética , Estudos Prospectivos , Fator 2 Relacionado a NF-E2/genética , Fator 2 Relacionado a NF-E2/metabolismo , Recidiva Local de Neoplasia , Prognóstico , Fenótipo , Mutação , Quinases Proteína-Quinases Ativadas por AMPRESUMO
AIMS: Macrophage colony-stimulating factor (M-CSF) binds to colony-stimulating factor-1 receptor (CSF-1R) and stimulates proliferation and differentiation of monocytes, macrophages and their bone marrow progenitors. M-CSF, CSF-1R, the macrophage marker CD68, and the pan T-lymphocyte marker CD3 are increased in many human cancers. Their prognostic importance in primary prostatic carcinoma has not been fully delineated. The aim was to compare the expression of M-CSF, CSF-1R, CD68 and CD3 in metastatic and non-metastatic prostatic cancer. METHODS AND RESULTS: Digital video analysis of tumour cell areas and tumour stromal areas was performed in 59 cancer specimens: 32 patients with metastases and 27 patients without metastases. Expression of M-CSF and CSF-1R was recorded as 0 (negative immunoreactivity), 1 (weak), 2 (moderate) or 3 (strong reactivity). Macrophages (CD68) and T lymphocytes (CD3) were detected as proportions of moderately or strongly immunoreactive cells. Patients with metastatic primary cancers showed higher expression of M-CSF (P < 0.0001, P = 0.005), CSF-1R (both P < 0.0001) and CD3 (P = 0.007, P < 0.0001) in both tumour cell areas and tumour stromal areas, compared with the non-metastatic cancers. CONCLUSION: This study suggests that expression of M-CSF, CSF-1R and CD3 is a significant prognostic factor in primary prostatic cancers by predicting the development of metastases.