Stromal HIF2 Regulates Immune Suppression in the Pancreatic Cancer Microenvironment

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Abstract

BACKGROUND & AIMS:

Pancreatic ductal adenocarcinoma (PDAC) has a hypoxic, immunosuppressive stroma that contributes to its resistance to immune checkpoint blockade therapies. The hypoxia-inducible factors (HIFs) mediate the cellular response to hypoxia, but their role within the PDAC tumor microenvironment remains unknown.

METHODS:

We used a dual recombinase mouse model to delete Hif1α or Hif2α in α-smooth muscle actin–expressing cancer-associated fibroblasts (CAFs) arising within spontaneous pancreatic tumors. The effects of CAF HIF2 α expression on tumor progression and composition of the tumor microenvironment were evaluated by Kaplan-Meier analysis, reverse transcription quantitative real-time polymerase chain reaction, histology, immunostaining, and by both bulk and single-cell RNA sequencing. CAF-macrophage crosstalk was modeled ex vivo using conditioned media from CAFs after treatment with hypoxia and PT2399, an HIF2 inhibitor currently in clinical trials. Syngeneic flank and orthotopic PDAC models were used to assess whether HIF2 inhibition improves response to immune checkpoint blockade.

RESULTS:

CAF-specific deletion of Hif2α, but not Hif1α, suppressed PDAC tumor progression and growth, and improved survival of mice by 50% (n ¼ 21–23 mice/group, Log-rank P ¼ .0009). Deletion of CAF-HIF2 modestly reduced tumor fibrosis and significantly decreased the intratumoral recruitment of immunosuppressive M2 macrophages and regulatory T cells. Treatment with the clinical HIF2 inhibitor PT2399 significantly reduced in vitro macrophage chemotaxis and M2 polarization, and improved tumor responses to immunotherapy in both syngeneic PDAC mouse models.

CONCLUSIONS:

Together, these data suggest that stromal HIF2 is an essential component of PDAC pathobiology and is a druggable therapeutic target that could relieve tumor microenvironment immunosuppression and enhance immune responses in this disease.

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Most cited references 49

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RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome

Bo Li, Colin Dewey (2011)

Background RNA-Seq is revolutionizing the way transcript abundances are measured. A key challenge in transcript quantification from RNA-Seq data is the handling of reads that map to multiple genes or isoforms. This issue is particularly important for quantification with de novo transcriptome assemblies in the absence of sequenced genomes, as it is difficult to determine which transcripts are isoforms of the same gene. A second significant issue is the design of RNA-Seq experiments, in terms of the number of reads, read length, and whether reads come from one or both ends of cDNA fragments. Results We present RSEM, an user-friendly software package for quantifying gene and isoform abundances from single-end or paired-end RNA-Seq data. RSEM outputs abundance estimates, 95% credibility intervals, and visualization files and can also simulate RNA-Seq data. In contrast to other existing tools, the software does not require a reference genome. Thus, in combination with a de novo transcriptome assembler, RSEM enables accurate transcript quantification for species without sequenced genomes. On simulated and real data sets, RSEM has superior or comparable performance to quantification methods that rely on a reference genome. Taking advantage of RSEM's ability to effectively use ambiguously-mapping reads, we show that accurate gene-level abundance estimates are best obtained with large numbers of short single-end reads. On the other hand, estimates of the relative frequencies of isoforms within single genes may be improved through the use of paired-end reads, depending on the number of possible splice forms for each gene. Conclusions RSEM is an accurate and user-friendly software tool for quantifying transcript abundances from RNA-Seq data. As it does not rely on the existence of a reference genome, it is particularly useful for quantification with de novo transcriptome assemblies. In addition, RSEM has enabled valuable guidance for cost-efficient design of quantification experiments with RNA-Seq, which is currently relatively expensive.

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Integrating single-cell transcriptomic data across different conditions, technologies, and species

Rahul Satija, Efthymia Papalexi, Peter Smibert … (2018)

Computational single-cell RNA-seq (scRNA-seq) methods have been successfully applied to experiments representing a single condition, technology, or species to discover and define cellular phenotypes. However, identifying subpopulations of cells that are present across multiple data sets remains challenging. Here, we introduce an analytical strategy for integrating scRNA-seq data sets based on common sources of variation, enabling the identification of shared populations across data sets and downstream comparative analysis. We apply this approach, implemented in our R toolkit Seurat (http://satijalab.org/seurat/), to align scRNA-seq data sets of peripheral blood mononuclear cells under resting and stimulated conditions, hematopoietic progenitors sequenced using two profiling technologies, and pancreatic cell 'atlases' generated from human and mouse islets. In each case, we learn distinct or transitional cell states jointly across data sets, while boosting statistical power through integrated analysis. Our approach facilitates general comparisons of scRNA-seq data sets, potentially deepening our understanding of how distinct cell states respond to perturbation, disease, and evolution.

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Tumor-associated macrophages: from mechanisms to therapy.

Roy Noy, Jeffrey W Pollard (2014)

The tumor microenvironment is a complex ecology of cells that evolves with and provides support to tumor cells during the transition to malignancy. Among the innate and adaptive immune cells recruited to the tumor site, macrophages are particularly abundant and are present at all stages of tumor progression. Clinical studies and experimental mouse models indicate that these macrophages generally play a protumoral role. In the primary tumor, macrophages can stimulate angiogenesis and enhance tumor cell invasion, motility, and intravasation. During monocytes and/or metastasis, macrophages prime the premetastatic site and promote tumor cell extravasation, survival, and persistent growth. Macrophages are also immunosuppressive, preventing tumor cell attack by natural killer and T cells during tumor progression and after recovery from chemo- or immunotherapy. Therapeutic success in targeting these protumoral roles in preclinical models and in early clinical trials suggests that macrophages are attractive targets as part of combination therapy in cancer treatment. Copyright © 2014 Elsevier Inc. All rights reserved.

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Author and article information

Journal

Journal ID (nlm-journal-id): 0374630

Journal ID (pubmed-jr-id): 3841

Journal ID (nlm-ta): Gastroenterology

Journal ID (iso-abbrev): Gastroenterology

Title: Gastroenterology

ISSN (Print): 0016-5085

ISSN (Electronic): 1528-0012

Publication date Nihms-submitted: 7 May 2022

Publication date (Print): June 2022

Publication date (Electronic): 22 February 2022

Publication date PMC-release: 13 July 2022

Volume: 162

Issue: 7

Pages: 2018-2031

Affiliations

[1 ]Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas

[2 ]UTHealth Graduate School of Biomedical Sciences, The University of Texas MD Anderson Cancer Center Houston, Texas

[3 ]School of Medicine, University of Puerto Rico Medical Sciences Campus, San Juan, Puerto Rico

[4 ]Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas

[5 ]Division of Translational Cancer Research, German Cancer Research Center and German Cancer Consortium, Heidelberg, Germany

[6 ]Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas

Author notes

[*]

Authors share co-first authorship.

Correspondence Address correspondence to Cullen M. Taniguchi, MD, PhD, The University of Texas MD Anderson Cancer Center, Division of Radiation Oncology, 1515 Holcombe Boulevard, Unit 1050, Houston, Texas 77030–4000. ctaniguchi@ 123456mdanderson.org .

Article

Manuscript ID: NIHMS1782934

DOI: 10.1053/j.gastro.2022.02.024

PMC ID: 9278556

PubMed ID: 35216965

SO-VID: 66007e69-646f-4d6f-9f20-f72d4cb45838

License:

This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/).

Stromal HIF2 Regulates Immune Suppression in the Pancreatic Cancer Microenvironment

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Abstract

BACKGROUND & AIMS:

METHODS:

RESULTS:

CONCLUSIONS:

Graphical Abstract

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Karger: Gastroenterology

Most cited references 49

RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome

Integrating single-cell transcriptomic data across different conditions, technologies, and species

Tumor-associated macrophages: from mechanisms to therapy.

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