Integrated microbiome, metabolome, and proteome analysis identifies a novel interplay among commensal bacteria, metabolites and candidate targets in non-small cell lung cancer.

BACKGROUND: Accumulation of evidence suggests that the gut microbiome, its specific metabolites, and differentially expressed proteins (DEPs) are related to non-small cell lung cancer (NSCLC) pathogenesis. We now report the influences of the gut microbiota, metabolites, and DEPs on the mediation of NSCLC's chronic inflammation and immune dysregulation. METHODS: We conducted 16S ribosomal RNA sequencing for the gut microbiome in healthy volunteers and NSCLC patients. Liquid chromatography-mass spectrometry (LC-MS) analysis was employed to explore differences between metabolites and DEPs in serum samples. Additionally, LC-MS-based metabolomic analysis was conducted in 40 NSCLC tissues and 40 adjacent tissues. The omics data were separately analysed and integrated by using Spearman's correlation coefficient. Then, faecal microbiota transplantation (FMT) assay was used to assess the effects of the gut microbiome and specific metabolites in mice. RESULTS: Faecal microbiome analysis revealed gut microflora dysbiosis in NSCLC patients with Prevotella, Gemmiger, and Roseburia significantly upregulated at the genus level. Then, we identified that nervonic acid/all-trans-retinoic acid level was negatively related to Prevotella. Additionally, a total of core 8 DEPs were selected in the proteome analysis, which mainly participated in the production of IL-8 and NF-κB pathways. CRP, LBP, and CD14 were identified as potential biomarkers for NSCLC. Transplantation of faecal microbiota from patients with NSCLC or Prevotella copri-colonized recipient in mice resulted in inflammation and immune dysregulation. In turn, nervonic acid/all-trans-retinoic acid treatment improved the phenotype of C57BL/6 mice bearing P. copri-treated Lewis lung cancer (LLC). CONCLUSIONS: Overall, these results pointed out that P. copri-nervonic acid/all-trans-retinoic acid axis may contribute to the pathogenesis of NSCLC.

Application of Multigroup Technology in Non-Small-Cell Lung Cancer with Qi Stagnation and Blood Stasis Syndrome.

OBJECTIVE: To explore the basic characteristics of intestinal flora, metabolomics, and proteomics of non-small cell lung cancer (NSCLC) in patients with Qi stagnation and blood stasis syndrome. METHODS: Twelve NSCLC patients with Qi stagnation and blood stasis syndrome were selected for the QZXY group and 15 healthy volunteers were selected for the control group. Fecal samples from the two groups were collected to evaluate intestinal microecology using the 16s rDNA technique. Serum samples were collected to compare the differences in metabolomics and proteomics between the two groups using liquid chromatography-mass spectrometry (LC-MS). Another 34 NSCLC patients with other syndromes were selected for the nQZXY group and their serum samples were collected. Metabolomics differences between the QZXY and nQZXY groups were compared using LC-MS, and four metabolites with the most obvious differences were selected for receiver operation characteristic curve representation. Finally, multigroup results were analyzed using the WGCNA software. RESULTS: There were two significantly different types of bacteria (Aerococcaceae and Abiotrophia), 11 different proteins (six upregulated and five downregulated), and 38 different metabolites (nine upregulated, 29 downregulated) between the QZXY and control groups. There was a correlation between differential bacteria, proteins, and metabolites. The conjoint analysis found that the different substances were related to MAPK, PI3K/Akt, Ras signaling pathway, cancer pathways, and cytokine-cytokine receptor interaction. There were four significant differences in metabolites (Pseudouridine, phenlacetyl-C0A, L-glutamic, and phospho-anandamide) between the QZXY and nQZXY groups. CONCLUSIONS: NSCLC with Qi stagnation and blood stasis syndrome had specific intestinal flora and protein and metabolites, which were closely related to the occurrence and development of tumors.

[Establishment of sleeve gastrectomy model in diet-induced obese Sprague-Dawley rats].

OBJECTIVE: To establish sleeve gastrectomy(SG) rats model of obese type 2 diabetes mellitus(T2DM) for the research of hypoglycemic mechanism. METHODS: Nine male Sprague-Dawley (6-week-old) rats were fed with high-sucrose and high-fat diet for 4 weeks, developing diet-induced obesity (DIO) rats model. The rats were then randomly divided into two groups. Six rats of them underwent sleeve gastrectomy(SG) as the sleeve gastrectomy group[SGG, body weight (471.8±17.9) g] and the other three rats underwent a laparotomy and stomach manipulation as the sham operative group[SOG, body weight (467.0±8.4) g]. The body weight, caloric intake and peripheral blood concentration of total ghrelin of rats were recorded after operation. RESULTS: The weight of all the rats declined progressively after operation. The weight of the rats in SOG began to rise on the 5th postoperative day(POD) and regain their preoperative levels on the average 22nd POD. However, the weight of the rats in SGG began to rise slowly from the 9th POD, but was still lower than that of SOG[(487.4±10.1) g] and preoperative levels[(471.8±17.9) g] on the 28th POD[(420.1±18.6) g](P=0.001). Average caloric intake of rats in SGG was significantly lower than that of SOG after operation, but there was no significant difference between the two groups(P=0.121). The ghrelin level of SGG showed a continuous decreasing trend after intervention, decreased by 17.4% compared with the preoperative level (1595.1±14.4 ng/L) on the 28th POD[(1316.8±14.8) ng/L]. The ghrelin level of SOG did not change obviously before and after operation and both groups differ statistically(P=0.000). CONCLUSIONS: A SG rat model is successfully established. This model can be used for the further study of mechanism analysis of T2DM resolution after surgery.