Impact of Pulmonary microbiota on lung cancer treatment-related pneumonia

Abstract

Background: The use of immunotherapy is progressively expanding for the treatment of lung cancer, either alone or in combination with radiotherapy. However, treatment-related adverse events, especially pneumonia, significantly limit the drug's effectiveness in treating lung cancer. The occurrence of lung cancer, immunotherapy, and pulmonary radiotherapy can all contribute to the imbalance in the pulmonary microbiota, rendering the lungs more susceptible to inflammatory reactions. Methods: Mouse models of lung transplantation tumor were treated with either PD-1 monoclonal antibody or radiotherapy alone, or in combination. The differences in lung inflammation among the different treatment groups were regularly observed by micro-CT. Further, bronchoalveolar lavage fluid was extracted for macrogenomic and cytokine detection. The transcriptional genome of tumor-filled lung tissue was also sequenced. Results: When treated with a combination of PD-1 and radiotherapy, the CT scans showed more severe pulmonary inflammation. However, with the addition of continuously administered antibiotics, no exacerbation of pneumonia signs was observed. Moreover, the differential gene expression and cytokine profiles in the combination treatment group differed from those in the PD-1 monotherapy group and the radiotherapy monotherapy group. This discrepancy does not seem to be a straightforward superimposition of radiation-induced pneumonia and immune-related pneumonia. Further exploration of changes in pulmonary microbiota revealed specific bacterial interactions with DEGs and cytokines. Conclusions: The underlying causes of this susceptibility are intricate and may be associated with the complexity of pulmonary microbiota imbalance, along with fluctuations in the abundance of specific microbiota species.

Keywords: PD-1; lung cancer; microbiota; pneumonia; radiotherapy.

Figure 1

Micro-CT images of lung metastases in tumor-bearing mice across the eight experimental groups. A. control; B. PD-1; C. Radiotherapy; D. antibiotic; E. PD-1 + Radiotherapy; F. PD-1 + antibiotic; G. Radiotherapy + antibiotic; H. PD-1 + Radiotherapy + antibiotic. The bright blue arrows point to areas of inflammation in the lungs, and the bright red circle shows the tumor.

Figure 2

DEGs analysis among different treatment groups. A. DEGs are shown in the heatmap. B-I: Displaying a volcano plot for DEGs in each group: the horizontal axis represents log2FoldChange, and the vertical axis represents -log10(p-value). Two vertical dashed lines in the plot indicate a 2-fold expression difference threshold, while the horizontal dashed line represents the P-value=0.05 threshold. Orange dots represent upregulated genes in the group, blue dots represent downregulated genes in the group. The genes relevant for subsequent screening are annotated. C. A vs B; D. A vs C; E. A vs D; F. A vs E; G. A vs F; H. A vs G; I. A vs H. A. The GO and KEGG of DEGs, group PD-1 vs the combination (I), group radiotherapy vs the combination (J), group PD-1 with radiotherapy vs the group PD-1 with radiotherapy plus antibiotic (K). The specific grouping information for the mice was provided in the methods.

Figure 3

Pulmonary microbiotas vary across different treatment groups. A. Heat map illustrating the differences in microbial communities among different groups. B. Interactions among various microbiotas that are from five phylums, the red line represents a positive correlation, while the green line represents a negative correlation. C-E. The Venn diagram illustrating different microbiotas with or without the addition of antibiotics. The specific grouping (A-H) information for the mice was provided in the methods.

Figure 4

Interactions among pulmonary microbiota, genes, and cytokines. Purple rhombus represents microbial species; upregulated and downregulated cytokines are shown in red and green respectively; genes that are upregulated are in orange-yellow, while those that are downregulated are shown in blue. Interactions among microbial species, genes, and cytokines. Information of specific grouping (A-H) of the mice was provided in the methods. (A) The network of all gene-microbe-cytokine Spearman correlations. The gene-microbe-cytokine Spearman correlations network when group F is compared with group B (B), group G with group C (D), and lastly group H with group E (D).