期刊
LUNG CANCER
卷 172, 期 -, 页码 19-28出版社
ELSEVIER IRELAND LTD
DOI: 10.1016/j.lungcan.2022.08.007
关键词
Lung adenocarcinoma; Adenocarcinoma patterns of growth; Translational pathology; Immune microenvironment; Multiplatform profiling; Predictors of immunotherapy response
资金
- NIH CCSG Award [CA016672]
- Translational Molecular Pathology-Immunoprofiling Moonshot Platform (TMP-IL) at the Department Translational Molecular Pathology
- University of Texas MD Anderson Cancer Center
- Lung Specialized Programs of Research Excellence [P50 CA070907]
- Happy Lungs Project
- University Cancer Foundation
- Cancer Prevention and Research Institute of Texas
- Exon20 Group, Rexanna's Foundation for Fighting Lung Cancer
- Waun Ki Hong Lung Cancer Research Fund
- MD Anderson's Lung Cancer Moon Shot
- Petrin Fund
- RETpositive
- LUNGevity
In this study, the relationship between growth patterns of early-stage lung adenocarcinoma (LUAD) and the tumor immune microenvironment was investigated. The poorly differentiated tumors were found to have a distinct immunogenic tumor microenvironment, which predicts a response to immune agents, including checkpoint inhibitors, in early-stage lung adenocarcinoma. These findings are important for the design of immunotherapy studies in LUAD.
Objectives: Pathologists have routinely observed distinct histologic patterns of growth in early-stage lung adenocarcinoma (LUAD), which have been suggested to be associated with prognosis. Herein, we investigated the relationship between LUAD patterns of growth, as defined by the updated international association for the study of lung cancer (IASLC) grading criteria, and differences in the tumor immune microenvironment to identify predictors of response to immunotherapy. Methods: 174 resected stage I-III LUAD tumors were classified by histologic pattern of growth (i.e. solid, micropapillary, acinar, papillary, and lepidic) and then grouped as well differentiated, moderately differentiated, and poorly differentiated. Comprehensive multiplatform analysis including whole exome sequencing, gene expression profiling, immunohistochemistry, CIBERSORT, and T-cell receptor sequencing was performed and groups were compared for differences in genomic drivers, immune cell infiltrate, clonality, and survival. Finally, multivariate analysis was performed adjusting for pathologic stage and smoking status. Results: Poorly differentiated tumors demonstrated a strong association with smoking relative to moderately differentiated or well differentiated tumors. However, unlike in prior reports, poorly differentiated tumors were not associated with a worse survival after curative-intent resection. Genomic analysis revealed that poorly differentiated tumors are associated with high tumor mutation burden but showed no association with oncogenic drivers. Immune analyses revealed that poorly differentiated tumors are associated with increased T-cell clon-ality, expression of PD-L1, and infiltration by cytotoxic CD8 T-cells, activated CD4 T-cells, and pro-inflammatory (M1) macrophages. Finally, multivariate analysis controlling for stage and smoking status confirmed indepen-dence of immune differences between IASLC grade groups. Conclusions: Poorly differentiated tumors, as defined by the updated IASLC grading criteria, are associated with a distinct immunogenic tumor microenvironment that predicts for therapeutic response to immune agents, including checkpoint inhibitors, and should be included in the clinical trial design of immunotherapy studies in early-stage lung adenocarcinoma.
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