Microbiological colonization of the pancreatic tumor affects postoperative complications and outcome after pancreatic surgery

Abstract

Background: The patient´s microbiome has become a focal point in cancer research. Even for pancreatic cancer, alterations in the microbiome appear to influence cancer formation and progression. The aim of our single-center analysis was the examination of microbiological colonization of pancreas tissue at the time of surgery and its potential influence on complications and outcome.

Methods: We prospectively evaluated patients undergoing pancreatic surgery over a three-year period from June 2018 to June 2021. We focused on the microbiological colonization of pancreatic tissue which was acquired during pancreatic surgery. Tissue samples were cultivated at our institute of microbiology. Patients´ characteristics, complications and postoperative outcome were analyzed using a prospectively maintained SPSS database.

Results: Between June 2018 and June 2021, we collected pancreatic tissue samples of a total of 178 patients undergoing pancreas resections, mostly due to ductal adenocarcinoma (PDAC; 50.6%). We could cultivate bacterial or fungal species in pancreatic tissue samples of 50 of our patients (28.1%). The majority of cases were characterized by the presence of a single microbial species, but 20 patients (11.2%) showed colonization with up to four different species. Among the bacterial species detected were Enterococcus faecium, Enterococcus faecalis, Escherichia coli, Staphylococcus aureus, Enterobacter cloacae and Klebsiella pneumonia. We found significantly more microbiological culture growth in patients with a preoperative biliary stent (74.0% vs. 15.6%, p < 0.001). Concerning postoperative complications, we found no difference concerning pancreatic fistula, but colonization with E. coli was associated with a significantly higher rate of postpancreatectomy hemorrhage (30.0% vs. 8.9%, p = 0.032). Interestingly, survival of PDAC patients seems to be negatively affected by positive microbiological findings at the time of surgery, but without reaching statistical significance (p = 0.770).

Conclusion: In this first analysis of our patient cohort, we could show a microbiological colonization of pancreatic tumor tissue in almost a third of our patients. There seems to be only a minor impact on postoperative complications, but long-term outcome seems to be worse in patients with a positive pancreas microbiome. Further observation is needed to evaluate the influence of the tumor microbiome on the long-term oncological outcome in PDAC patients.

Keywords: microbiological colonization; mortality; pancreatic tumor; postoperative complications; survival.

Figure 1

Ratio of microbiological colonization in different tumor entities. Ratio (%) of microbiological colonization in conventional culture growth. PDAC, pancreatic ductal adenocarcinoma; IPMN, intrapapillary mucinous neoplasm; NET, neuroendocrine tumor.

Figure 2

Kaplan Meier curves of PDAC patients. (A) negative vs. positive microbiome (B) stented vs. non-stented patients.

Figure 3

Abundant phyla and genera according to microbial growth. Ten most abundant phyla (A) and genera (B) from 16S rDNA-sequencing grouped by the presence of microbial growth in culture (n=10 per group). The y-axis represents absolute abundance.

Figure 4

Abundant phyla and genera according to microbial growth in culture, grouped by family. Ten most abundant phyla (A) and genera (B) from 16S rDNA-sequencing grouped by the family of the cultured bacteria (Enterobacteriaceae n=5, Enterococcaceae n=4, Staphylococcaceae n=1) or by no observed growth (n=10). Read counts are normalized to the sample size (n) of each group. The y-axis represents absolute abundance. Heatmap of genera abundances that were cultured in the samples. Sample abundances were normalized using Cumulative Sum Scaling (CSS) (C).

Figure 5

Comparison of beta diversities of microbial communities of patient samples, grouped based on their culture growth. PCoA visualization of bacterial community composition of different bacterial culture growth groups grouped by the family of the cultured bacteria (Enterobacteriaceae n=5, Enterococcaceae n=4, Staphylococcaceae n=1) or by no observed growth (n=10). Beta diversity measured with Bray-Curtis Dissimilarity Distances and visualized using Principal Coordinates Analysis (PCoA) plot.

Figure 6

Alpha Diversity. Observed, Shannon, and InvSimpson Alpha Diversity. This boxplot showcases three alpha diversity indices across various patient groups: patients with and without stent (A), patients with and without microbial growth in culture (B), patients with post-surgery sepsis (C), and Clavien-Dindo classification groups (D). The central line within each box represents the median diversity value. The box spans the interquartile range (IQR), from the 25th to the 75th percentile, illustrating the middle 50% of the data. Whiskers extend to the smallest and largest values within 1.5 times the IQR from the quartiles. The Wilcoxon rank-sum test and the Kruskal-Wallis test showed no significant differences between the conditions for any of the alpha diversity indices.

Figure 7

Abundant phyla and genera according to stent presence. Ten most abundant phyla (A) and genera (B) identified in 16S rDNA-sequencing grouped according to stent presence. The y-axis represents absolute abundance. The central line within each box represents the median abundance value. The box spans the interquartile range (IQR), covering the 25th to 75th percentiles, thus illustrating the middle 50% of the data. Whiskers extend to the smallest and largest values within 1.5 times the IQR from the quartiles. Each point on the plot corresponds to one sample.