The association between white blood cell count and relative risk of non-small cell lung cancer

Abstract

Background: High abundance of eosinophils has been proved to associated with favorable disease progression in non-small cell lung cancer (NSCLC) in the previous observational studies, but the causal relationship remains unclear. It is also unclear whether white blood cell (WBC) counts are essential for the risk of NSCLC.

Methods: Using multiple methods of Mendelian randomization (MR), we assessed the causality of WBC count, particularly basophil, eosinophil, monocyte, lymphocyte, and neutrophil counts on the risk of NSCLC, which includes squamous carcinoma and adenocarcinoma. Single cell RNA-sequencing and RNA-sequencing analysis illustrate the underline mechanism of the causality and its biological effects.

Results: Univariable MR analysis indicated the protective effect of elevated eosinophil counts on NSCLC and adenocarcinoma subtype. The protective effect of eosinophils persisted even after adjusting. The protective functions mainly effected by immune activating, and it contribute to better survival and favorable response to immune therapy. Univariate MR analysis also states the risk role of neutrophil. Sequencing based analysis proved the immune inhibit functions of neutrophil, which lead to worse survival and immune treatment response.

Conclusion: Our study indicated a correlation between circulating eosinophil counts, neutrophil counts, and the development of NSCLC. And sequencing analysis confirm this relationship and illustrated the underline mechanism.

Keywords: Eosinophils; Mendelian randomization; NSCLC; Single-cell RNA sequencing; WBC.

Fig. 1

Design flowchart for this study

Fig. 2

Univariate Mendelian randomization analysis for Circulating WBCs and NSCLC risk. Forest plot showing univariate MR results in the training FinnGen court (A) and validation ILCCO court (B)

Fig. 3

Sequencing analysis reveal the protect function of eosinophils. A The UMAP plot of eosinophils distribution. B The feature plot of eosinophil marker genes. C The UMAP plot of eosinophil tissue origins. D The UMAP plot of five eosinophil subclusters. E The cell development locus of eosinophil. F Distribution of developmental trajectories of eosinophils from different sources. G Functional enrichment based on pseudotime. H Eosinophil enrichment difference between LUAD and LUSC. I Differences in eosinophilic infiltration in various treatment responses. Comparative survival analysis revealed eosinophil infiltration-dependent prognostic disparities across NSCLC (J), LUAD (K) and LUSC (L)

Fig. 4

Bulk RNA-seq and scRNA-seq analysis of neutrophil. The UMAP plot of different cell types (A), pathological classification (B), treatment (C) and treatment response (D). E The immune cell infiltration differences between LUAD and LUSC. F The immune inhibitory functions of immune cells. Infiltration of neutrophils with different immunotherapy effects in scRNA-seq (G) and RNA-seq (H). Survival analysis based on neutrophil infiltration in NSCLC (I), LUAD (J) and LUSC (K)