CXCL10/CXCR3 signaling contributes to an inflammatory microenvironment and its blockade enhances progression of murine pancreatic precancerous lesions.

Abstract

The development of pancreatic cancer requires recruitment and activation of different macrophage populations. However, little is known about how macrophages are attracted to the pancreas after injury or an oncogenic event, and how they crosstalk with lesion cells or other cells of the lesion microenvironment. Here, we delineate the importance of CXCL10/CXCR3 signaling during the early phase of murine pancreatic cancer. We show that CXCL10 is produced by pancreatic precancerous lesion cells in response to IFNγ signaling, and that inflammatory macrophages are recipients for this chemokine. CXCL10/CXCR3 signaling in macrophages mediates their chemoattraction to the pancreas, enhances their proliferation and maintains their inflammatory identity. Blocking of CXCL10/CXCR3 signaling in vivo shifts macrophage populations to a tumor promoting (Ym1+, Fizz+, Arg1+) phenotype, increases fibrosis and mediates progression of lesions, highlighting the importance of this pathway in PDA development. This is reversed when CXCL10 is overexpressed in PanIN cells.

Data availability

All data generated or analysed during this study are included in the manuscript and supporting files. Source data have been included for all Figures and Supplemental Figures.

Article and author information

Author details

  1. Veethika Pandey

    Cancer Biology, Mayo Clinic, Jacksonville, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Alicia Fleming-Martinez

    Cancer Biology, Mayo Clinic, Jacksonville, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Ligia Bastea

    Cancer Biology, Mayo Clinic, Jacksonville, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Heike R Doeppler

    Cancer Biology, Mayo Clinic, Jacksonville, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Jillian Eisenhauer

    Cancer Biology, Mayo Clinic, Jacksonville, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Tam Le

    Cancer Biology, Mayo Clinic, Jacksonville, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Brandy Edenfield

    Cancer Biology, Mayo Clinic, Jacksonville, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. Peter Storz

    Cancer Biology, Mayo Clinic, Jacksonville, United States
    For correspondence
    storz.peter@mayo.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0132-5128

Funding

National Cancer Institute (CA229560)

  • Peter Storz

National Cancer Institute (CA200572)

  • Peter Storz

National Cancer Institute (P50CA102701)

  • Peter Storz

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Animal experimentation: This study was performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. All animal experiments were conducted under IACUC approved protocols (A50214-14-R17, A30615-15-R18) and were run in accordance with institutional guidance and regulation.

Copyright

© 2021, Pandey et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 4,262
    views
  • 541
    downloads
  • 43
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Veethika Pandey
  2. Alicia Fleming-Martinez
  3. Ligia Bastea
  4. Heike R Doeppler
  5. Jillian Eisenhauer
  6. Tam Le
  7. Brandy Edenfield
  8. Peter Storz
(2021)
CXCL10/CXCR3 signaling contributes to an inflammatory microenvironment and its blockade enhances progression of murine pancreatic precancerous lesions.
eLife 10:e60646.
https://doi.org/10.7554/eLife.60646

Share this article

https://doi.org/10.7554/eLife.60646

Further reading

    1. Cancer Biology
    2. Computational and Systems Biology
    Aurélie Anne-Gaëlle Gabriel, Julien Racle ... David Gfeller
    Research Advance

    Assay for Transposase-Accessible Chromatin sequencing (ATAC-Seq) is a widely used technique to explore gene regulatory mechanisms. For most ATAC-Seq data from healthy and diseased tissues such as tumors, chromatin accessibility measurement represents a mixed signal from multiple cell types. In this work, we derive reliable chromatin accessibility marker peaks and reference profiles for most non-malignant cell types frequently observed in the microenvironment of human tumors. We then integrate these data into the EPIC deconvolution framework (Racle et al., 2017) to quantify cell-type heterogeneity in bulk ATAC-Seq data. Our EPIC-ATAC tool accurately predicts non-malignant and malignant cell fractions in tumor samples. When applied to a human breast cancer cohort, EPIC-ATAC accurately infers the immune contexture of the main breast cancer subtypes.

    1. Cancer Biology
    2. Immunology and Inflammation
    Akashdip Singh, Alberto Miranda Bedate ... Linde Meyaard
    Research Article

    Despite major successes with inhibitory receptor blockade in cancer, the identification of novel inhibitory receptors as putative drug targets is needed due to lack of durable responses, therapy resistance, and side effects. Most inhibitory receptors signal via immunoreceptor tyrosine-based inhibitory motifs (ITIMs) and previous studies estimated that our genome contains over 1600 ITIM-bearing transmembrane proteins. However, testing and development of these candidates requires increased understanding of their expression patterns and likelihood to function as inhibitory receptor. Therefore, we designed a novel bioinformatics pipeline integrating machine learning-guided structural predictions and sequence-based likelihood models to identify putative inhibitory receptors. Using transcriptomics data of immune cells, we determined the expression of these novel inhibitory receptors, and classified them into previously proposed functional categories. Known and putative inhibitory receptors were expressed across different immune cell subsets with cell type-specific expression patterns. Furthermore, putative immune inhibitory receptors were differentially expressed in subsets of tumour infiltrating T cells. In conclusion, we present an inhibitory receptor pipeline that identifies 51 known and 390 novel human inhibitory receptors. This pipeline will support future drug target selection across diseases where therapeutic targeting of immune inhibitory receptors is warranted.