Interaction between CAF and CD8+ T cells in non-small cell lung cancer affects prognosis and efficacy of immunotherapy.

Authors

null

Xinlong Zheng

Fujian University of Traditional Chinese Medicine, Fuzhou, China

Xinlong Zheng , Dongqiang Zeng , Wenying Peng , Pansong Li , Lifeng Li , Xuan Gao , Zhipeng Zhou , Jing Bai , Junhui Li , Jianming Ding , Deqiang Wang , Suya Zheng , Qian Miao , Kan Jiang , Biao Wu , Feng Long , Chao Li , Haipeng Xu , Yi Yin , Lin Gen

Organizations

Fujian University of Traditional Chinese Medicine, Fuzhou, China, Southern Medical University, Guangzhou, China, Hunan Cancer Hospital, the Affiliated Cancer Hospital of Xiangya Medical School, Central South University, Changsha, China, Geneplus-Beijing Institute, Beijing, China, National Protein Science Center, Beijing, China, Fujian Provincial Cancer Hospital, Fuzhou, China, Department of Medical Oncology, Cancer Therapy Center, Affiliated Hospital of Jiangsu University, Zhenjiang, China, Fuzhou Second Hospital, Fuzhou, China, Fujian Cancer Hospital, Fujian Medical University Cancer Hospital, Fuzhou, China, Depatment of Pathology, Fujian Medical University Cancer Hospital, Fuzhou, China

Research Funding

No funding received
None

Background: Cancer-related fibroblasts (CAFs) are important components of the tumor microenvironment (TME) and play a key role in tumor progression. There is growing evidence that CAF levels in tumors are highly correlated with treatment response and prognosis. However, the effect of CAFs on immunotherapy response remains unknown. Methods: RNA-seq and clinical data were downloaded from TCGA and GEO. The SVA package ComBat function was used to remove batch effects. The ssGSEA algorithm was used to assess the level of cell infiltration in each sample. OS (overall survival) and DFS (disease free survival) were analyzed using the Kaplan–Meier method. GO enrichment analysis was used to assess the biological processes of subgroup differential genes. The Tumor Immune Dysfunction and Exclusion (TIDE) algorithm and subclass mapping were used to predict the clinical response to immune checkpoint blockade. Results: We evaluated the infiltration abundance of 24 types of immune cells and fibroblasts in 1768 NSCLC samples and found that almost all IMFRs (immune cells / fibroblasts) are beneficial to the prognosis. This phenomenon is called “CAFs-mediated immune resistance pattern (CMIRP)”. We evaluated the infiltration abundance of 24 types of immune cells and fibroblasts in 1768 NSCLC samples and found that almost all IMFRs (immune cells / fibroblasts) are beneficial to the prognosis. This phenomenon is called “CAFs-mediated immune resistance pattern (CMIRP)”. The prognosis according to CD8+ T cells was not strong, but CD8+ T cells / fibroblasts (CFR) were significant protective prognostic factors [n = 1588; hazard ratio (HR), 0.66; 95% confidence interval (CI), 0.56–0.78; P < 0.001]. Multivariate analysis revealed that the CFR was an independent prognostic biomarker. The TCGA pan-cancer cohort confirmed the widespread presence of CMIRP in cancer. We further defined the CFR high and CFR low subgroups. CFR high samples were enriched with immune activation pathways including T cell activation, cytolysis, and antigen presentation, while CFR low was associated with immunosuppression including activation of transforming growth factor β, epithelial-mesenchymal transition, and angiogenesis pathways. Finally, we combined TIDE and submap to speculate that CFR is a potential prognostic marker of immunotherapy for NSCLC. Conclusions: We proposed the term “CMIRP” to shed light on a more accurate assessment of immune status. CFR is a potential marker for prognosis and predictive efficacy of immunotherapy in NSCLC.

Disclaimer

This material on this page is ©2024 American Society of Clinical Oncology, all rights reserved. Licensing available upon request. For more information, please contact licensing@asco.org

Abstract Details

Meeting

2020 ASCO Virtual Scientific Program

Session Type

Poster Session

Session Title

Lung Cancer—Non-Small Cell Metastatic

Track

Lung Cancer

Sub Track

Biologic Correlates

Citation

J Clin Oncol 38: 2020 (suppl; abstr 9536)

DOI

10.1200/JCO.2020.38.15_suppl.9536

Abstract #

9536

Poster Bd #

302

Abstract Disclosures

Similar Abstracts

First Author: Matthew Lee

First Author: Bhavika Patel