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The Inflammatory Response of Human Pancreatic Cancer Samples Compared to Normal Controls

Kathryn J. Brayer, Joshua A. Hanson, Shashank Singham, Cathleen Martinez, Scott A. Ness, Ian Rabinowitz 


Pancreatic ductal adenocarcinoma (PDAC) is a poor prognosis cancer with an aggressive growth profile that is often diagnosed at late stage and that has few curative or therapeutic options. PDAC growth has been linked to alterations in the pancreas microbiome, which could include the presence of the fungus Malassezia. We used RNA-sequencing to compare 14 matched tumor and normal (tumor adjacent) pancreatic cancer samples and found Malassezia RNA in both the PDAC and normal tissues. Although the presence of Malassezia was not correlated with tumor growth, a set of immune- and inflammatory-related genes were up-regulated in the PDAC compared to the normal samples, suggesting that they are involved in tumor progression. Gene set enrichment analysis suggests that activation of the complement cascade pathway and inflammation could be involved in pro PDAC growth.


Pancreatic cancer (PDAC) is the 9th most common cancer in the US but is the 4th most common cause of cancer related death (~54,000/year and ~44,000/year respectively). The median 5 year survival for stage 4 disease is 9% [1]. The high death rate with respect to the prevalence rate is due to poor early detection and a lack of meaningful advancement in systemic therapeutics. The most common somatic mutations, Kirsten rat sarcoma viral oncogene (KRAS), tumor protein p53 (TP53), cyclin dependent kinase inhibitor 2 A (CDKN2A), and SMAD family member 4 (SMAD4) have been identified by whole-exome and -genome sequencing of large PDAC cohorts and form the majority of unique mutations in patients with PDAC [2]. The tumor microenvironment (TME), which represents a complex ecosystem involving interactions between immune cells, cancer cells, stromal cells, and the extracellular matrix, can support tumor proliferation, survival, and metastasis and can be highly immunosuppressive [3–5]. In one paper, they found in patients with a resected PDAC and a higher tumor microbial diversity did better than resected PDAC with a lower microbial diversity. They also showed that patients who carried the long term survival (LTS) microbiome signature, namely (Pseudoxanthomonas, Streptomyces, and Saccharopolyspora) lived a long time. There was no microbiome signature for the patients who had a short term survival (STS). Patients with high diversity and low diversity had overall survival of 9.66 vs. 1.66 years respectively using univariate Cox proportional hazard models. 


RNA isolation and sequencing

Total RNA was extracted from FFPE slices using the RNeasy FFPE kit (Qiagen) and the manufacture’s protocol. Synthesis of cDNA and library preparation were performed using the SMARTer Universal Low Input RNA Kit for Sequencing (Clontech) and the Ion Plus Fragment Library Kit (ThermoFisher) as previously described [10, 31, 32]. Sequencing was performed using the Ion Proton S5/XL systems (ThermoFisher) in the Analytical and Translational Genomics Shared Resource at the UNM Comprehensive Cancer Center. RNA sequencing data is available for download from the NCBI BioProject database using study accession number PRJNA940178.

Data analysis

Prior to alignment, non-human RNA-seq reads were identified and removed from analysis using the kraken2 taxonomic sequence classification system against a library containing human, fungal, bacterial and viral genomes [11–13] and final genera level abundances were calculated using Bracken (v2.5.0, [14]. High-quality, trimmed reads classified as human, were aligned to GRCh38 (hg38) using tmap (v5.10.11). Exon counts were calculated using HTseq (v0.11.1, [33] against a BED file containing non-overlapping exons from UCSC genome hg38 and gene counts were generated by summing counts across exons. Samples were normalized for library size using DEseq2 (v1.34.0, [34]) and low expressing genes were excluded from the final analysis using a filtering threshold of 20 reads in 9 samples. Multi-dimensional scaling (MSC) was performed using plotMDS from the limma package (v3.50.0) and the base stats package was used for unsupervised heirachrical clustering [35]. 


Microbiome results

Using optimized methods [10], we used RNA-seq analysis on matched tumor-normal PDAC tissue samples derived from formalin-fixed paraffin embedded (FFPE) slices for 15 patients obtained from UNM Tissue Repository, generating high quality data for 14 patients, with an average of 32 x 10^-6 reads per sample (Tables 1 and 2). After sequencing, reads were taxonomically classified using kraken2 [11–13] and braken [14] against a library containing human, viral, bacterial, and fungal genomes, including the genomes of several Malassezia species. The fungus Malassezia was present in all tumor samples at varying concentrations (Tables 1 and 2). We also detected Malassezia in all of the normal tissue samples, which is in contrast to a previous study (Tables 1 and 2) [8]. Despite reports that PDAC tumors have a lower microbial diversity than normal pancreatic tissues [6], we found no significant difference in the number of microbial genera present in normal samples versus tumor samples (Table 1).


We explored the TME in the samples and found overexpression of C2, Dectin-1, and Galectin-3 represented in box plot analysis. There was no literature about the role of C2 in pancreatic cancer, but there was data showing C2 has a role in amplifying BCR signal transduction in each subpopulation of B-2 cells, but not B-1 cells, as noted above. Dectin-1 and Galectin-3 can augment PDAC progression as noted above. These two molecules can propagate the growth of the PDAC in vivo and mice models, but this must be looked at in the context of a multi molecular array, some inhibiting and some promoting PDAC growth. We also compared the gene expression profiles of PDAC patient tumor samples to the normal sample and found several differential expressed genes. These genes were enriched for genes that are known to be involved in the complement cascade and inflammation, as well as genes involved in epithelial-mesenchyme transition, KRAS signaling, and known PDAC genes. From this we were able to identify one gene (PLAUR) that sits at the intersection of these pathways and may be a potential target for PDAC treatment. 

Citation: Brayer KJ, Hanson JA, Cingam S, Martinez C, Ness SA, Rabinowitz I (2023) The inflammatory response of human pancreatic cancer samples compared to normal controls. PLoS ONE 18(11): e0284232.

Publisher: Hilary A. Coller, UC Los Angeles: University of California Los Angeles, UNITED STATES

Received: April 5, 2023; Accepted: September 1, 2023; Published: November 1, 2023

Copyright: © 2023 Brayer et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting information files. Genomics Shared Resource at the UNM Comprehensive Cancer Center. RNA sequencing data is available for download from the NCBI BioProject database using study accession number PRJNA940178 (

Funding: This research was partially supported by the University of New Mexico Comprehensive Cancer Center Support Grant NCI University of New Mexico Cancer Research & Treatment Center P30CA118100(IR) and the Analytical and Translational Genomics Shared Resource, which receives additional support for the State of New Mexico.(SN,KB) R01DE023222, U2CCA252973,KB) and University of New Mexico Comprehensive Cancer Center Support Grant NCI University of New Mexico Cancer Research & Treatment Center P30CA118100(SN,KB) and by Department of Defence grant: Defence Threat Reduction Agency,KB). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.



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