Dataset Information

Dysregulated Immune and Metabolic Microenvironment Is Associated with the Post-Operative Relapse in Stage I Non-Small Cell Lung Cancer.

ABSTRACT: The underlying mechanism of post-operative relapse of non-small cell lung cancer (NSCLC) remains poorly understood. We enrolled 57 stage I NSCLC patients with or without relapse and performed whole-exome sequencing (WES) and RNA sequencing (RNA-seq) on available primary and recurrent tumors, as well as on matched tumor-adjacent tissues (TATs). The WES analysis revealed that primary tumors from patients with relapse were enriched with USH2A mutation and 2q31.1 amplification. RNA-seq data showed that the relapse risk was associated with aberrant immune response and metabolism in the microenvironment of primary lesions. TATs from the patients with relapse showed an immunosuppression state. Moreover, recurrent lesions exhibited downregulated immune response compared with their paired primary tumors. Genomic and transcriptomic features were further subjected to build a prediction model classifying patients into groups with different relapse risks. We show that the recurrence risk of stage I NSCLC could be ascribed to the altered immune and metabolic microenvironment. TATs might be affected by cancer cells and facilitate the invasion of tumors. The immune microenvironment in the recurrent lesions is suppressed. Patients with a high risk of relapse need active post-operative intervention.

SUBMITTER: Zhang S

PROVIDER: S-EPMC9265031 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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Dysregulated Immune and Metabolic Microenvironment Is Associated with the Post-Operative Relapse in Stage I Non-Small Cell Lung Cancer.

Zhang Shirong S Xiao Xiao X Zhu Xiuli X Chen Xueqin X Zhang Xiaochen X Xiang Jingjing J Xu Rujun R Shao Zhuo Z Bai Jing J Xun Yanping Y Jiang Yanping Y Chen Zhengzheng Z Xia Xuefeng X Jiang Hong H Ma Shenglin S

Cancers 20220622 13

The underlying mechanism of post-operative relapse of non-small cell lung cancer (NSCLC) remains poorly understood. We enrolled 57 stage I NSCLC patients with or without relapse and performed whole-exome sequencing (WES) and RNA sequencing (RNA-seq) on available primary and recurrent tumors, as well as on matched tumor-adjacent tissues (TATs). The WES analysis revealed that primary tumors from patients with relapse were enriched with <i>USH2A</i> mutation and 2q31.1 amplification. RNA-seq data s ...[more]

PMID: 35804832

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Project description:For small cell lung cancer (SCLC) therapy, immunotherapy might have unique advantages to some extent. Galectin-9 (Gal-9) plays an important role in antitumor immunity, while little is known of its function in SCLC. By mean of immunohistochemistry (IHC), we tested the expression level of Gal-9 and other immune markers on both tumor cells and tumor-infiltrating lymphocytes (TILs) in 102 surgical-resected early stage SCLC clinical samples. On the basis of statistical analysis and machine learning results, the Gal-9-based immune risk score model was constructed and its predictive performance was evaluated. Then, we thoroughly explored the effects of Gal-9 and immune risk score on SCLC immune microenvironment and immune infiltration in different cohorts and platforms. In the SCLC cohort for IHC, the expression level of Gal-9 on TILs was statistically correlated with the levels of program death-1 (p=0.001), program death-ligand 1 (PD-L1) (p<0.001), CD3 (p<0.001), CD4 (p<0.001), CD8 (p<0.001), and FOXP3 (p=0.047). High Gal-9 protein expression on TILs indicated better recurrence-free survival (30.4 months, 95% CI: 23.7-37.1 vs 39.4 months, 95% CI: 31.6-47.3, p=0.009). The immune risk score model which consisted of Gal-9 on TILs, CD4, and PD-L1 on TILs was established and validated so as to differentiate high-risk or low-risk patients with SCLC. The prognostic predictive performance of immune risk score model was better than single immune biomarker (area under the curve 0.671 vs 0.621-0.644). High Gal-9-related enrichment pathways in SCLC were enriched in immune system diseases and rheumatic disease. Furthermore, we found that patients with SCLC with low immune risk score presented higher fractions of activated memory CD4 T cells than patients with high immune risk score (p=0.048). Gal-9 is markedly related to tumor-immune microenvironment and immune infiltration in SCLC. This study emphasized the predictive value and promising clinical applications of Gal-9 in stage I-III SCLC.

Project description:BackgroundMacrophages are critical players in regulating innate and adaptive immunity in the tumor microenvironment (TME). The prognostic value of macrophages and their heterogeneous phenotypes in non-small cell lung cancer (NSCLC) is still uncertain.MethodsSurgically-resected samples of 681 NSCLC cases were stained by multiplex immunofluorescence to examine macrophage phenotypes as well as the expression levels of program death-ligand 1 (PD-L1) on them in both tumor nest and tumor stroma, including pan-macrophage (CD68+), M1 (CD68+CD163-), and M2 macrophages (CD68+CD163+). Various other immune cell markers, including CD4, CD8, CD20, CD38, CD66B, FOXP3, and CD133, were also evaluated. Machine learning algorithm by Random Forest (RF) model was utilized to screen the robust prognostic markers and construct the CD68-based immune-related risk score (IRRS) for predicting disease-free survival (DFS).ResultsThe expression levels of CD68 were moderately correlated with the levels of PD-L1 (P<0.001), CD133 (P<0.001), and CD8 (P<0.001). Higher levels of CD68 (OR 1.03, 95% CI: 1.01-1.05, P<0.001) as well as M1 macrophage (OR 1.04, 95% CI: 1.01-1.06, P<0.001) indicated shorter DFS. Despite without statiscial significance, intratumoral M2 macrophage (OR 1.05, 95% CI: 0.99-1.10, P=0.081) was also associated with worse DFS. IRRS incorporating three intratumoral CD68-related markers and four intrastromal markers was constructed and validated to predict recurrence (high-risk group vs. low-risk group: OR 2.52, 95% CI: 1.89-3.38, P<0.001). The IRRS model showed good accuracy [area under the curve (AUC) =0.670, 0.709, 0.695, 0.718 for 1-, 3-, 5-year, and overall DFS survival, respectively] and the predictive performance was better than the single-marker model (area under the curve 0.718 vs. 0.500-0.654). A nomogram based on clinical characteristics and IRRS for relapse prediction was then established and exhibited better performance than the tumor-node-metastasis (TNM) classification and IRRS system (C-index 0.76 vs. 0.69 vs. 0.60, 0.74 vs. 0.67 vs. 0.60, 0.81 vs. 0.74 vs. 0.60 of the entire, training, testing cohort, respectively).ConclusionsOur study suggested close interactions between CD68 and other immune markers in TME, demonstrating the prognostic value of CD68 in relapse prediction in resectable NSCLC.

Dataset Information

Dysregulated Immune and Metabolic Microenvironment Is Associated with the Post-Operative Relapse in Stage I Non-Small Cell Lung Cancer.

Publications

Dysregulated Immune and Metabolic Microenvironment Is Associated with the Post-Operative Relapse in Stage I Non-Small Cell Lung Cancer.

Similar Datasets

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