Identification of CNKSR1 as a biomarker for “cold” tumor microenvironment in lung adenocarcinoma: An integrative analysis based on a novel workflow

• Published in: Heliyon Vol. 10; no. 8; p. e29126
• Main Authors: Cai, Qidong, Peng, Mou
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 30-04-2024; Elsevier
• Subjects: CNKSR1; Immunotherapy; Lung adenocarcinoma; Machine learning; PD-L1; Tumor microenvironment; PD-L1; CNKSR1; Lung adenocarcinoma; Tumor microenvironment; Immunotherapy; Machine learning
• ISSN: 2405-8440; 2405-8440
• DOI: 10.1016/j.heliyon.2024.e29126

Therapies targeting PD1/PD-L1 pathway have revolutionized the treatment of lung cancer. However, anti-PD1/PD-L1 therapies have proven beneficial for only a select group of lung adenocarcinoma (LUAD) patients and generally do not work for immuno-cold tumors characterized by a lack of immune cell infiltration. Identifying novel biomarkers is vital to broad therapeutic options for LUAD patients with no response to anti-PD1/PD-L1 immunotherapies.
Our study has developed a novel strategy to identify a promising biomarker that addresses the limitations of anti-PD1/PD-L1 immunotherapy in treating immunological cold tumors. We exacted LUAD RNA-seq data from the Cancer Genome Atlas database (TCGA). Using several machine learning methods, we identified the candidate biomarker. Based on the expression level of PD-L1 and the identified biomarker, samples were categorized into four groups. We further used ESTIMATE, ssGSEA, and CIBERSORT algorithms to calculate the immune infiltration level of each group. The results were validated in three independent bulk datasets and one scRNA-seq dataset. Immunohistochemistry (IHC) assessments were performed in clinical samples to further evaluate the coexpression of CNKSR1 and PD-L1, and to compare CD8 + T cell infiltration among groups.
After comprehensive analyses, CNKSR1 was identified as a novel promising biomarker for immuno-cold LUAD. CNKSR1 mRNA expression levels exhibited a negative correlation with both PD-L1 mRNA expression and the extent of immune cell infiltration in LUAD. Besides, in contrast to the significant association between the expression of PD-L1 and the majority of other well-established or widely studied immune checkpoint molecules, a mutually exclusive expression pattern is observed between CNKSR1 and these molecules. The aforementioned results were consistent in validation datasets. The prognostic model built based on the CNKSR1 coexpression module also showed robust predictive performance. Additionally, IHC assessments have confirmed that the coexpression of CNKSR1 and PD-L1 is rare in LUAD samples. Notably, LUADs in the high-CNKSR1 group, characterized by high CNKSR1 but low PD- L1 expression, demonstrated reduced infiltration of CD8+ T cells.
In summary, CNKSR1 emerges as a promising biomarker for immune-cold LUADs, and the study into CNKSR1 modulating T-cell infiltration may lead to the identification of compensatory molecules to enhance the effectiveness of current immunotherapy for LUAD.