There were an estimated 60,000 new cases and approximately 50,000 deaths due to pancreatic cancer (PC) in 2022 (1). Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal of all cancers and is estimated to be the second highest cause of cancer-related mortality by 2030 (2). Endoscopic ultrasound (EUS) is used to evaluate the pancreas via transgastric and transduodenal imaging in high-risk individuals undergoing regular screening or in patients with a mass detected by other methods to confirm diagnosis (3). Samples are frequently taken for cytological analysis via fine needle aspiration (FNA) or histological assessment with core needle biopsy.

There has been an increase in the understanding of the gut and tumor microbiomes (TM) in cancer and their significant role in disease progression and responses to therapy (4–6). As a potential diagnostic tool, the gut microbiome was shown to be capable of identifying cases of PC amongst healthy controls and other benign diseases of the pancreas (7, 8). It was also determined that distinct TM signatures could be found between short- and long-term survivors of PC (4). In addition to the potential utility for diagnosis and determining prognostic factors, modulation of the gut and TM for greater immune activation and leverage against cancer has been postulated (9). PC is a heterogeneous disease process and precision oncology approaches will increasingly be required in the treatment of PC (10). In addition, manipulation of the TM by fecal microbial transplant is currently being investigated as a treatment modality against PC (NCT04975217). While the gut microbiome can be easily characterized, there is a deficiency of methods to detect the pancreatic TM prior to a surgical resection. Here we present the results of a pilot study to test feasibility of assessing bacteria and fungal populations in pancreatic tumors via EUS-FNA biopsy.

At least seven bacterial genera (11%) were identified in all five samples sequenced (Actinomyces, Campylobacter, Fusobacterium, Granulicatella, Haemophilus, Prevotella, and Veilonella), with Prevotella as the most abundant ( Figure 2A ). When compared to fresh frozen surgical pancreatic tissue from unmatched individuals with PC (n= 10), we observed at least 35 (54%) genera in common between these two sample types ( Figure 2B ). This similarity is noteworthy considering that the surgical specimens were obtained from different individuals and matched irrespective of the anatomical portion of the pancreas or the collection moment (pre or post-chemotherapy treatment).

Among the unique genera (n=30) identified in the FNA biopsy samples we cannot disregard that some or most of them might represent bacteria from the oropharynx, esophagus, stomach or duodenum that could contaminate the endoscope and the pancreatic biopsy tissue during the procedure and the route used. Previous studies have identified Oribacterium, Atopobium, Klebsiella, Butyvibrio, Pasteurella, Tanerella, and Coprococcus in the mucosa derived from either duodenum or stomach samples (24–27). Other genera such as Fusobacterium, Haemophilus, Actinobacillus, Eubacterium, Actinobaculum, Bifidobacterium, Blautia, Veilonella, Prevotella and Lactobacillus were also identified in duodenum and stomach samples but were found in the FNA and the pancreatic surgical specimens as well ( Supplementary Table S2 ) (24–27). These results are consistent with the notion that the human pancreas can share microbiota composition with gastrointestinal sites and ultimately the differential abundance of certain bacteria may be as relevant to consider as solely their presence or absence. The use of proper negative controls, amplification negative controls, and matched duodenum or stomach mucosa microbiome examination will help future decontamination strategies.

Recently, Nakano et al. (28) described the predominance of Acinetobacter and Pseudomonas in the pancreatic FNA samples in comparison to the duodenum and/or stomach mucosa from matched individuals, while in our study and many others (14, 29–31), these two genera were included on the putative contaminants list and were therefore excluded from the analysis. Additionally, these FNA samples were not compared to a matched resected tumor and it was not described whether the genera identified were solely in each sample type or shared among them (pancreatic FNA, mucosal duodenum, or stomach) (28). Similarly, Masi et al. (32) previously investigated the feasibility of using pancreatic formalin-fixed paraffin-embedded (FFPE) samples from a small number of EUS procedures to study the pancreatic microbiome and identified the existence of significant differences in the overall bacterial composition of the samples according to the route used for examination (duodenum or stomach), with Fusobacterium significantly enriched when the stomach route was used. In this sense, there is still a need to better comprehend the potential of the FNA pancreatic microbiome as a diagnostic tool for PC, including the bacterial composition of surrounding tissues and putative contaminants.

Additionally, in our cohort, two out of the five patients that underwent 16S sequencing successfully had their FNA fungal composition determined by ITS, supporting the efficacy of these minimally invasive endoscopically collected samples for complementary fungi-bacteria signature assessment. Despite the reduced number of FNAs tested, we observed relevant similarities in their fungal population even after decontamination, with high prevalence of Saccharomyces and Trichosporon ( Figure 3 ). As most genera remain unknown for PC, there is a need to overcome experimental biases in vivo and silico associated with fungal identification by ITS sequencing in tumors.

We report the successful characterization of the pancreatic microbiome using EUS-FNA biopsy, including the first report of ITS sequencing from EUS-FNA biopsy samples. This method of microbial biopsy could be explored for use in diagnosis and prognosis. It has become the standard of practice to perform next generation sequencing (NGS) in all patients diagnosed with PC for precision oncology approaches (33). In the future, monitoring and manipulating the TM could expand individualized treatments with the understanding that certain bacterial signatures are associated with a favorable prognosis (4).

Alam et al. found that in mice, the intratumoral mycobiome of pancreatic lesions affects secretion of IL-33 which in turn induces type 2 immunity in pancreatic cancer. Both anti-fungal treatment or IL-33 suppression decreased T_H2 infiltration and caused tumor regression (34, 35). These findings suggest alterations to the fungi, or mycobiome, in addition to intratumoral bacteria, may be another avenue of precision therapy.

Previously, duodenal fluid has been used as a surrogate marker for the pancreatic microbiome and it was found that patients with PDAC had lower microbial diversity in their duodenal fluid than controls with a normal pancreas (36). Techniques to accurately sample the microbiome of pancreatic lesions are urgently needed. Devices are being developed in order to meet this need (37), but conventional EUS-FNA biopsy may be a sufficient tool. It is also theoretically possible to perform immunoprofiling on the same EUS-FNA biopsy samples that are used to characterize the TM. Analysis of the microbiome and immune profile, in addition to the currently recommended NGS, could further inform directed therapies through multi-omic strategies.

We describe a characterization of the microbiome of pancreatic lesions using EUS-FNA biopsy combined with in silico decontamination. Our bacterial signature was conserved when compared to non-matched pancreatic tissue. We also used ITS sequencing to identify fungal species. Within a host-tissue background, direct sequencing of 16S rRNA and ITS amplicons offers a more direct and sensitive approach to assess microbial composition than whole-genome sequencing (WGS) or RNA-seq datasets, which are often dominated by host genomic DNA. Though samples are more routinely being taken for NGS in EUS-FNA for pancreatic lesions, the authors do not suggest extrapolating microbiome characterization from WGS data for the aforementioned reasons.

This proof of concept method could be utilized in the identification of the microbiome and mycobiome of pancreatic lesions prior to resection. Further investigation is needed with greater samples sizes, using mucosal tissue for normalization, and matched tissues for validation.

The data presented in the study are deposited in the SRA under accession PRJNA1008674. The data can be found here https://www.ncbi.nlm.nih.gov/sra/?term=PRJNA1008674.

The studies involving humans were approved by University of Texas MD Anderson Cancer Center- Institutional Review Board. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

RW: Conceptualization, Writing – original draft, Writing – review & editing. TB: Investigation, Methodology, Visualization, Conceptualization, Writing – original draft, Data curation, Formal Analysis. SB: Validation, Conceptualization, Formal Analysis, Investigation, Methodology, Visualization, Writing – original draft. JW: Data curation, Software, Writing – review & editing, Methodology, Validation, Visualization. MK: Investigation, Resources, Supervision, Writing – review & editing. MB: Conceptualization, Funding acquisition, Visualization, Writing – original draft, Investigation, Resources, Supervision, Writing – review & editing. FM: Methodology, Project administration, Validation, Conceptualization, Funding acquisition, Investigation, Supervision, Visualization, Writing – original draft, Writing – review & editing.