Benchmarking the Intratumoral Microbiome in Pancreatic Ductal Adenocarcinoma: A Longitudinal Assessment of Contamination Sources and Decontamination Strategies
- 1Universitatsmedizin Gottingen
Abstract
Pancreatic ductal adenocarcinoma (PDAC) harbors a distinct intratumoral microbiome. Yet rigorous characterization of its composition is hampered by pervasive environmental and procedural contamination. Sources of contamination have not been thoroughly explored, and the methods of decontamination have not been sufficiently evaluated in a benchmarking manner. We systematically collected >300 negative control (NCT) samples comprising paraffin from formalin-fixed paraffin-embedded (FFPE) samples, lysis buffer and sterile water over a period of four years processed by different laboratory persons (LP). All samples were sequenced using full-length 16S rRNA gene sequencing with Oxford-Nanopore Technologies. We benchmarked four decontamination methods (restrictive filtering, decontam, SCRuB, and the Nejman et al.-derived (Nj) pipeline) against fresh-frozen tumor samples (FF) from LSL-KrasG12D/+;LSL-Trp53R172H/+;Pdx-1-Cre (KPC) mice, using the abovementioned contamination assessment to calculate a composite score for the assessment. Further, we validated those methods via technical replicates. Microbial profiles of NCT samples were significantly determined by control type, LP, year and season reflecting complex batch effects. The 15 most abundant contaminants spanned well-characterized environmental taxa and human commensals from the oral cavity. The LP processing samples left a significant microbial trace highly contributing to the batch effect. Decontamination benchmarking demonstrated that the Nj method consistently outperformed alternatives in both composite score and inter-replicate concordance. Application of Nj to fresh frozen PDAC samples substantially reduced contaminant burden while preserving putative tumor-associated signals in FF but not FFPE samples. Our results support the adoption of the Nj decontamination approach for future intratumoral microbiome studies in fresh frozen tumor samples.
Related
- Molecular mechanisms by which the intratumoral microbiome drives pancreatic ductal adenocarcinoma progression and therapeutic response
- Machine learning models integrating 2D and 3D intratumoral heterogeneity features from multi-sequence MRI: accurate prediction of perineural invasion in pancreatic ductal adenocarcinoma
- Explainable machine learning integrating CT-derived intratumoral heterogeneity for histological subtype prediction in pure ground-glass lung adenocarcinoma: multicenter validation and transcriptomic characterization
- MRI-based intratumoral and peritumoral heterogeneity for predicting intracranial progression in EGFR-mutant lung adenocarcinoma patients with treatment-naive brain metastases receiving first-line third-generation EGFR-TKIs.
- Topologically distinct intratumoral heterogeneity scores for predicting high-risk pathological grades in invasive lung adenocarcinoma: A multicenter study across four institutions
BibTeX
@misc{dang2026benchmarking,
title = {{Benchmarking the Intratumoral Microbiome in Pancreatic Ductal Adenocarcinoma: A Longitudinal Assessment of Contamination Sources and Decontamination Strategies}},
author = {L. Dang and L. Eskelson and J. Hamm and J. Blumberg and U. Wegener and T. Beissbarth and V. Ellenrieder and A. Neesse and C. Ammer-Herrmenau},
howpublished = {bioRxiv},
year = {2026},
month = aug,
doi = {10.64898/2026.08.24.746744},
url = {https://www.biorxiv.org/content/10.64898/2026.08.24.746744v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - Benchmarking the Intratumoral Microbiome in Pancreatic Ductal Adenocarcinoma: A Longitudinal Assessment of Contamination Sources and Decontamination Strategies
AU - L. Dang
AU - L. Eskelson
AU - J. Hamm
AU - J. Blumberg
AU - U. Wegener
AU - T. Beissbarth
AU - V. Ellenrieder
AU - A. Neesse
AU - C. Ammer-Herrmenau
PY - 2026
DA - 2026/08/24
PB - bioRxiv
DO - 10.64898/2026.08.24.746744
UR - https://www.biorxiv.org/content/10.64898/2026.08.24.746744v1
AB - Pancreatic ductal adenocarcinoma (PDAC) harbors a distinct intratumoral microbiome. Yet rigorous characterization of its composition is hampered by pervasive environmental and procedural contamination. Sources of contamination have not been thoroughly explored, and the methods of decontamination have not been sufficiently evaluated in a benchmarking manner. We systematically collected >300 negative control (NCT) samples comprising paraffin from formalin-fixed paraffin-embedded (FFPE) samples, lysis buffer and sterile water over a period of four years processed by different laboratory persons (LP). All samples were sequenced using full-length 16S rRNA gene sequencing with Oxford-Nanopore Technologies. We benchmarked four decontamination methods (restrictive filtering, decontam, SCRuB, and the Nejman et al.-derived (Nj) pipeline) against fresh-frozen tumor samples (FF) from LSL-KrasG12D/+;LSL-Trp53R172H/+;Pdx-1-Cre (KPC) mice, using the abovementioned contamination assessment to calculate a composite score for the assessment. Further, we validated those methods via technical replicates. Microbial profiles of NCT samples were significantly determined by control type, LP, year and season reflecting complex batch effects. The 15 most abundant contaminants spanned well-characterized environmental taxa and human commensals from the oral cavity. The LP processing samples left a significant microbial trace highly contributing to the batch effect. Decontamination benchmarking demonstrated that the Nj method consistently outperformed alternatives in both composite score and inter-replicate concordance. Application of Nj to fresh frozen PDAC samples substantially reduced contaminant burden while preserving putative tumor-associated signals in FF but not FFPE samples. Our results support the adoption of the Nj decontamination approach for future intratumoral microbiome studies in fresh frozen tumor samples.
ER -