Gut microbiota and short-chain fatty acid alterations in cachectic cancer patients

Abstract

Background: Cancer cachexia is characterized by a negative energy balance, muscle and adipose tissue wasting, insulin resistance, and systemic inflammation. Because of its strong negative impact on prognosis and its multifactorial nature that is still not fully understood, cachexia remains an important challenge in the field of cancer treatment. Recent animal studies indicate that the gut microbiota is involved in the pathogenesis and manifestation of cancer cachexia, but human data are lacking. The present study investigates gut microbiota composition, short-chain fatty acids (SCFA), and inflammatory parameters in human cancer cachexia.

Methods: Faecal samples were prospectively collected in patients (N = 107) with pancreatic cancer, lung cancer, breast cancer, or ovarian cancer. Household partners (N = 76) of the patients were included as healthy controls with similar diet and environmental conditions. Patients were classified as cachectic if they lost >5% body weight in the last 6 months. Gut microbiota composition was analysed by sequencing of the 16S rRNA V4 gene region. Faecal SCFA levels were quantified by gas chromatography. Faecal calprotectin was assessed with enzyme-linked immunosorbent assay. Serum C-reactive protein and leucocyte counts were retrieved from medical records.

Results: Cachexia prevalence was highest in pancreatic cancer (66.7%), followed by ovarian cancer (25%), lung cancer (20.8%), and breast cancer (17.3%). Microbial α-diversity was not significantly different between cachectic cancer patients (N = 33), non-cachectic cancer patients (N = 74), or healthy controls (N = 76) (species richness P = 0.31; Shannon effective index P = 0.46). Community structure (β-diversity) tended to differ between these groups (P = 0.053), although overall differences were subtle and no clear clustering of samples was observed. Proteobacteria (P < 0.001), an unknown genus from the Enterobacteriaceae family (P < 0.01), and Veillonella (P < 0.001) were more abundant among cachectic cancer patients. Megamonas (P < 0.05) and Peptococcus (P < 0.001) also showed differential abundance. Faecal levels of all SCFA tended to be lower in cachectic cancer patients, but only acetate concentrations were significantly reduced (P < 0.05). Faecal calprotectin levels were positively correlated with the abundance of Peptococcus, unknown Enterobacteriaceae, and Veillonella. We also identified several correlations and interactions between clinical and microbial parameters.

Conclusions: This clinical study provided the first insights into the alterations of gut microbiota composition and SCFA levels that occur in cachectic cancer patients and how they are related to inflammatory parameters. These results pave the way for further research examining the role of the gut microbiota in cancer cachexia and its potential use as therapeutic target.

Keywords: Breast cancer; Cachexia; Inflammation; Lung cancer; Pancreatic cancer; Weight loss.

Figure 1

Microbial richness and diversity in cachectic cancer patients (yellow, N = 33), non‐cachectic cancer patients (blue, N = 74), and healthy control subjects (green, N = 76). (A) Observed species richness and (B) Shannon effective index; both indices of α‐diversity were similar between the groups. (C) The non‐metric multidimensional scaling plot showed no clear clustering of samples from cachectic cancer patients, non‐cachectic cancer patients, or healthy controls.

Figure 2

Microbiota composition on phylum level. (A) Relative abundances of all phyla present in the study population. (B) Log₂ abundance of Proteobacteria. Statistically significant differences according to the Wald test (α = 0.05) are marked with asterisks. Proteobacteria were significantly elevated in cachectic cancer patients compared with non‐cachectic cancer patients and healthy controls.

Figure 3

Genera with altered abundance in cachectic vs. non‐cachectic cancer patients and/or healthy controls. The log₂ abundance of genera, which differed significantly between the groups, is depicted. Statistically significant differences according to the Wald test (α = 0.05) are marked with asterisks.

Figure 4

Faecal levels of total short‐chain fatty acids (SCFA) and acetate, butyrate, propionate, and valerate separately. Acetate levels were found to be reduced in cachectic cancer patients (N = 30) compared with non‐cachectic cancer patients (N = 64) and healthy controls (N = 71). P‐values from Kruskal–Wallis test are shown.

Figure 5

Faecal levels of calprotectin were not different in cachectic cancer patients (N = 30) compared with non‐cachectic cancer patients (N = 68) or healthy controls (N = 70).

Figure 6

Correlation analyses of the significant variables from differential analyses of bacterial taxa and total short‐chain fatty acids as well as relevant clinical parameters in pairwise comparisons. Factors under investigation are depicted in the diagonal line. The relationships of abundances of four bacterial taxa, acetic acid, calprotectin, body mass index (BMI), and weight loss were estimated using Kendall's tau correlation coefficient (τ). In the upper panels, significant correlations are indicated with asterisks (^* P < 0.05, ^** P < 0.01, and ^*** P < 0.001). In the lower panels, scatter plots of pairwise correlations are shown. Yellow dots represent cachectic cancer patients, blue dots depict non‐cachectic cancer patients, and green dots indicate healthy controls.

Figure 7

Estimated co‐occurrence of Megamonas, Peptococcus, Veillonella, and an unknown genus from the Enterobacteriaceae family in cachectic cancer patients vs. non‐cachectic cancer patients (A) and cachectic cancer patients vs. healthy controls (B). Green lines represent a positive association, while orange marks a negative association between these genera. An edge is displayed if the 90% credibility interval does not contain zero.