Lung cancer progression alters lung and gut microbiomes and lipid metabolism

Abstract

Despite advances in medical technology, lung cancer still has one of the highest mortality rates among all malignancies. Therefore, efforts must be made to understand the precise mechanisms underlying lung cancer development. In this study, we conducted lung and gut microbiome analyses and a comprehensive lipid metabolome analysis of host tissues to assess their correlation. Alternations in the lung microbiome due to lung cancer, such as a significantly decreased abundance of Firmicutes and Deferribacterota, were observed compared to a mock group. However, mice with lung cancer had significantly lower relative abundances of Actinobacteria and Proteobacteria and higher relative abundances of Cyanobacteria and Patescibacteria in the gut microbiome. The activations of retinol, fatty acid metabolism, and linoleic acid metabolism metabolic pathways in the lung and gut microbiomes was inversely correlated. Additionally, changes occurred in lipid metabolites not only in the lungs but also in the blood, small intestine, and colon. Compared to the mock group, mice with lung cancer showed that the levels of adrenic, palmitic, stearic, and oleic (a ω-9 polyunsaturated fatty acid) acids increased in the lungs. Conversely, these metabolites consistently decreased in the blood (serum) and colon. Leukotriene B4 and prostaglandin E2 exacerbate lung cancer, and were upregulated in the lungs of the mice with lung cancer. However, isohumulone, a peroxisome proliferator-activated receptor gamma activator, and resolvin (an ω-3 polyunsaturated fatty acid) both have anti-cancer effects, and were upregulated in the small intestine and colon. Our multi-omics data revealed that shifts in the microbiome and metabolome occur during the development of lung cancer and are of possible clinical importance. These results reveal one of the gut-lung axis mechanisms related to lung cancer and provide insights into potential new targets for lung cancer treatment and prophylaxis.

Keywords: Gut-lung axis; Lipid; Lung cancer; Metabolome; Microbiome.

Fig. 1

Lewis lung cancer (LLC) cells metastasize selectively to the lungs and cause lung cancer (A) C57BL/6J mice received LLC cells (1 × 10⁶) via tail injection. (B and C) body weight (B) results are presented as mean ± standard deviation (SD) and survival rate (C). Mock, n = 10; LLC cell-injected mice, n = 30. (D, E, and F) Tumor colony counts in the lungs (D), tumor volume in the lungs (E), weight of the lungs (F). Mock group mice and the LLC cell-injected mice were sacrificed on days 0, 7, 14, 21, 28, and 32 (n = 5 or 3). Results are presented as mean ± SD. Each dot represents an individual mouse. (G) Representative lung histological images on day 28 after LLC cell injection (scale bar, 100 mm at the bottom right). Black arrow shows tumor nodules (left). Three images from right were derive from different mice, respectively. Results were considered statistically significant if the p value was <0.05 (****p < 0.001, ***p < 0.001, **p < 0.01).

Fig. 2

Lung cancer alters the lung and gut microbiomes (A) C57BL/6J mice received Lewis lung cancer (LLC) cells (1 × 10⁶) via tail injection. Mock, n = 5; lung cancer mice were sacrificed on days 21 (n = 4) and 28 (n = 4). (B) Bacterial composition in the lungs (left) and gut (right) at the phylum level. (C) Comparison of the Chao1 index of different groups. The box and whiskers represent the smallest and largest values, with the median in the center of each box. Results were considered statistically significant if the p value was <0.05 (*p < 0.05; ns indicates not significant). (D) Principal coordinates analysis (PCoA) based on weighted UniFrac distances among three groups (mock, lung cancer sacrificed on day 21, and lung cancer sacrificed on day 28). Each dot represents an individual mouse. See also Fig. S2.

Fig. 3

Lung cancer alters metabolism in the lungs (A) Heatmap representing the ratio of the mock group to the relative abundance of the metabolic functions in the lung and gut microbiome. C57BL/6J mice received LLC cells (1 × 10⁶) via tail injection. Mock, n = 5; lung cancer mice sacrificed on days 21 (n = 4) and 28 (n = 4). (B) Effect of lung cancer on relative abundance of the metabolic functions in the lung microbiome. Results are presented as mean ± standard deviation (SD). Each dot represents an individual mouse. Results were considered statistically significant if the p value was <0.05 (**p < 0.01, *p < 0.05; ns indicates not significant). See also Fig. S3.

Fig. 4

Lung cancer changes metabolic profiles in host lung, blood, small intestine, and colon (A) C57BL/6J mice received LLC cells (1 × 10⁶) via tail injection. Mock, n = 7; lung cancer mice sacrificed on day 28, n = 8. (B, C, D, and E) Linear discriminant analysis (LDA) score (Log2) of lipid metabolites that show significantly different peak areas between the mock and lung cancer mouse groups in the lungs (B), blood (serum) (C), small intestine (D), and colon (E). Results are presented as mean of LDA score. See also Fig. S4.

Fig. 5

Proposed mechanisms to show the correlation between the lung and gut in lung cancer mice Lung cancer induces inflammation and changes in the microbiome. These factors promote lipid metabolism in the lungs. Additionally, lung cancer upregulates ω-6 polyunsaturated fatty acids (PUFAs) (adrenic acid), pro-inflammatory lipid mediators, and their sources, long-chain fatty acids, such as oleic, palmitic, and stearic acids, to promote lung cancer progression. However, the gut decreases the production of these metabolites, thereby reducing their supply to the lungs. Instead, the gut upregulates anti-inflammatory lipid metabolites, such as resolvins. Alterations in lipid metabolism can also affect the gut microbiome.