Validation of a radiomic approach to decipher NSCLC immune microenvironment in surgically resected patients.
Aged
B7-H1 Antigen
/ genetics
CD8 Antigens
/ genetics
Carcinoma, Non-Small-Cell Lung
/ diagnostic imaging
Disease-Free Survival
Female
Humans
Lung
/ diagnostic imaging
Lymphocytes, Tumor-Infiltrating
/ metabolism
Male
Neoplasm Staging
Prognosis
Tomography, X-Ray Computed
Tumor Microenvironment
/ genetics
CT imaging
immune contexture
prognostic signature
radiomics
Journal
Tumori
ISSN: 2038-2529
Titre abrégé: Tumori
Pays: United States
ID NLM: 0111356
Informations de publication
Date de publication:
Feb 2022
Feb 2022
Historique:
pubmed:
19
3
2021
medline:
19
2
2022
entrez:
18
3
2021
Statut:
ppublish
Résumé
Radiomics has emerged as a noninvasive tool endowed with the potential to intercept tumor characteristics thereby predicting clinical outcome. In a recent study on resected non-small cell lung cancer (NSCLC), we identified highly prognostic computed tomography (CT) -derived radiomic features (RFs), which in turn were able to discriminate hot from cold tumor immune microenvironment (TIME). We aimed at validating a radiomic model capable of dissecting specific TIME profiles bearing prognostic power in resected NSCLC. The validation cohort included 31 radically resected NSCLCs clinicopathologically matched with the training set (n = 69). TIME was classified in hot and cold according to a multiparametric immunohistochemical analysis involving PD-L1 score and incidence of immune effector phenotypes among tumor infiltrating lymphocytes (TILs). High- throughput radiomic features (n = 841) extracted from CT images were correlated to TIME parameters to ultimately define prognostic classes. We confirmed PD-1 to CD8 ratio as best predictor of clinical outcome among TIME characteristics. Significantly prolonged overall survival (OS) was observed in patients carrying hot (median OS not reached) vs cold (median OS 22 months; hazard ratio 0.28, 95% confidence interval 0.09 -0.82; p = 0.015) immune background, thus validating the prognostic impact of these two TIME categories in resected NSCLC. Importantly, in the validation setting, three out of eight previously identified RFs sharply distinguishing hot from cold TIME were endorsed. Among signature-related RFs, Wavelet-HHH_gldm_HighGrayLevelEmphasis highly performed as descriptor of hot immune contexture (area under the receiver operating characteristic curve 0.94, 95% confidence interval 0.81 -1.00; p = 0.01). Based on our findings, Radiomics may decipher specific TIME profiles providing a noninvasive prognostic approach in resected NSCLC and an exploitable predictive strategy in advanced cases.
Identifiants
pubmed: 33730957
doi: 10.1177/03008916211000808
doi:
Substances chimiques
B7-H1 Antigen
0
CD274 protein, human
0
CD8 Antigens
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM