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

  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  Is a corresponding author
  1. Department of Cancer Biology, Mayo Clinic Comprehensive Cancer Center, Mayo Clinic, United States
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Cite this article as: eLife 2021;10:e60646 doi: 10.7554/eLife.60646

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.

Introduction

Pancreatic cancer is difficult to target because its fibrotic microenvironment not only acts as a barrier for delivery of tumor cell targeting drugs, but it also generates an anti-inflammatory environment and prevents immunotherapy (Balachandran et al., 2019). One of the current paradigms for treatment of PDA focuses on combining chemotherapy with immune modulators that reprogram tumor-promoting macrophages toward a pro-inflammatory phenotype (Bastea et al., 2019; Mitchem et al., 2013; Pandey and Storz, 2019). A deeper understanding of the mechanisms that play a role in macrophage polarization can provide insights to develop such new interventions.

Genetic mouse models have shown that pancreatic ductal adenocarcinoma (PDA) most likely originates from precancerous pancreatic intraepithelial neoplasm (PanIN) lesions (reviewed in Storz, 2017). The development and progression of these early lesions is dependent on crosstalk between a multitude of host cells in their microenvironment. Of these, inflammatory (M1-polarized) and alternatively activated (M2-polarized) macrophages are the most consequential cell types.

The initial influx of macrophages, which induces local inflammation, occurs in response to an aberrant release of chemokines from pancreatic cells undergoing transformation (Liou et al., 2015). However, local inflammation alone is not an efficient driver of oncogenic progression and requires additional inflammatory signaling, genetic alterations, and downregulation of factors that maintain acinar cell identity (Carrière et al., 2011; Cobo et al., 2018; Guerra et al., 2011; Guerra et al., 2007).

Inflammatory macrophages contribute to pre-neoplastic lesion formation via secretion of inflammatory mediators, which regulate reorganization of the acinar microenvironment and initiate acinar-to-ductal metaplasia (ADM) (Liou et al., 2015; Liou et al., 2013; Sawey et al., 2007). While pro-inflammatory M1 macrophages are important for the initiation of precancerous lesions, this population dwindles and M2 macrophages become more predominant (Liou et al., 2017). These M2 macrophages are chitinase-like protein 3 (Ym1/Chil3), arginase-1 (Arg1), resistin-like alpha (Fizz1/Retnla), and interleukin-1 receptor antagonist protein (IL-1ra) positive and promote lesion growth, drive fibrogenesis, and block T-cell infiltration (Bastea et al., 2019; Liou et al., 2017). Later, at the tumor stage, alternatively activated macrophages represent approximately 85% of tumor-associated macrophages (TAMs) in the microenvironment (Partecke et al., 2013). For full-blown pancreatic cancer, tissue-resident macrophages have been suggested to shape fibrotic responses (Zhu et al., 2017), while infiltrating monocytes generate an immunosuppressive environment (Zhang et al., 2017; Zhu et al., 2017).

C-X-C motif chemokine 10 (CXCL10), also known as IFNγ-induced protein 10 (IP-10), acts through its cognate receptor C-X-C motif chemokine receptor 3 (CXCR3) (Groom and Luster, 2011) and regulates the chemotaxis of CXCR3+ immune cells such as macrophages, T cells, and natural killer (NK) cells (Luster and Ravetch, 1987; Tomita et al., 2016; Zhou et al., 2010). With respect to cancer aggressiveness and patient prognosis, the presence of CXCL10 and CXCR3 has shown conflicting results depending on the type and stage of the disease (Fulton, 2009; Jacquelot et al., 2018; Li et al., 2015). In pancreatic cancer, both CXCL10 and CXCR3 are expressed in tumor tissue (Delitto et al., 2015), and their presence has been correlated with poor prognosis (Liu et al., 2011; Lunardi et al., 2014). However, the role of CXCL10/CXCR3 signaling during early development of the disease has not been addressed.

In our present study, we show that CXCL10, produced by precancerous lesions cells, is involved in the onset of inflammation by chemoattracting macrophages. We further show that CXCL10 signaling to CXCR3 is a key event for inflammatory macrophage identity and that inhibition of CXCL10/CXCR3 signaling leads to a polarization shift to an alternatively activated phenotype. In vivo, we demonstrate the importance of CXCL10/CXCR3 signaling in the maintenance of an inflammatory microenvironment, and that its blockage drives tumor progression.

Results

Pre-neoplastic ADM and PanIN lesions produce CXCL10

To identify factors that are released by precancerous lesion cells, we performed a cytokine/chemokine assay. Therefore, we used SM3 cells, which have been isolated from the precancerous epithelium of a KC mouse and form lesions with PanIN features when cultivated on extracellular matrix (Agbunag et al., 2006; Liou et al., 2017). In this screen limited to these in vitro lesion cells (Figure 1—figure supplement 1A), besides known factors such as C-C motif chemokine 5 (CCL5) and metalloproteinase inhibitor 1 (TIMP-1), we found strong expression of CXCL10, which has previously been identified as a chemoattractant for macrophages (Tomita et al., 2016; Zhou et al., 2010). We then used fluorescent in situ hybridization (FISH) to determine whether Cxcl10 is produced in pancreatic precancerous lesion areas of Ptf1a/p48cre;LSL-KrasG12D (KC) mice. While Cxcl10 was undetectable in normal adjacent acini (Figure 1—figure supplement 1B), we found significant expression of Cxcl10 in ADM and PanIN1 lesions (Figure 1A). Quantification analyses of samples stained for Cxcl10 mRNA by ISH indicated approximately fivefold higher expression in ADM than in PanIN (Figure 1B, Figure 1—figure supplement 1C). Next, we isolated primary pancreatic acinar cells from LSL-KrasG12D mice and adenovirally infected them with either GFP (control) or Cre-GFP, to test whether Cxcl10 expression is upregulated during the KRasG12D-driven ADM process (Figure 1—figure supplement 1D). However, expression of KRasG12D was unable to increase Cxcl10 expression, indicating an external stimulus as a driver.

Figure 1 with 1 supplement see all
Pre-neoplastic ADM and PanIN lesions express CXCL10.

(A) ‘Normal’ acinar cells (data shown in Figure 1—figure supplement 1B), ADM areas and PanIN lesions of pancreata from KC mice were analyzed for Cxcl10 expression. Shown are representative pictures of H and E staining (overview and marked region) and FISH for Cxcl10 mRNA expression (red dots) combined with DAPI in the marked regions. Images shown represent whole-slide analysis of staining. The scale bar represents 100 μm. (B) Quantification of relative Cxcl10 expression (as determined by ISH shown in Figure 1—figure supplement 1C) in ‘normal’ acini, ADM, and PanIN regions of KC mice (n = 3 biological replicates) using a positive pixel algorithm on whole slides for each mouse analyzed, using the image scope software. Statistical analysis was done using the Student’s t-test. *Statistical significance as compared to ‘normal’ acini (for ADM p-value = 0.023; PanIN p-value = ns), **Statistical significance for PanIN as compared to ADM (p-value=0.033). Error bars indicate standard deviation. (C, D, E) SM3 cells were stimulated with 10 ng/ml IFNγ for 4 days and an increase in CXCL10 expression was determined by qPCR (C), western blot (D), and in the media supernatants (E). For (C, D), results are representative of data from three independent, reproducible experiments. Statistical analysis was done using the Student’s t-test. The asterisk indicates statistical significance (C: p-value < 0.0001; E: p-value = 0.0004). Error bars indicate standard deviation. (E) shows two biological repeats. (F) SM3 cells were treated with NVP-BSK805 (10 μM, 1 hr) and then stimulated with 10 ng/ml IFNγ for 24 hr. Samples were subjected to SDS-PAGE and analyzed by western blotting for pY701-STAT1, STAT1, and CXCL10 expression as indicated. Immunoblotting for GAPDH served as a control for equal loading. Results shown represent reproducible data obtained from three independent experiments. (G) Pancreata of KC mice were subjected to IF-IHC for CD4, CD8, and NKG2D combined with FISH for Ifng. Images shown are representative of IF and FISH done on 2 KC mice (biological replicates). The scale bar represents 10 μm.

Figure 1—source data 1

Quantification of Cxcl10 in KC tissue and IFNɣ-stimulated SM3 cells (panels B, C, and E).

https://cdn.elifesciences.org/articles/60646/elife-60646-fig1-data1-v2.xlsx

CXCL10 (also IP-10, interferon gamma-inducible protein 10) expression has previously been shown to be induced by interferon gamma (IFNγ) via activation of signal transducer and activator of transcription 1 (STAT1) (Han et al., 2010; Luster and Ravetch, 1987). Therefore, we tested if this pathway is active in PanIN cells. Treatment of SM3 cells with IFNγ induced an over 60-fold increase in Cxcl10 mRNA (Figure 1C), as well as increased CXCL10 protein production (Figure 1D) and secretion (Figure 1E). To test whether CXCL10 expression is indeed mediated through STAT1 signaling, we combined IFNγ stimulation with the pan-JAK inhibitor NVP-BSK805. We found that IFNγ stimulation led to phosphorylation of STAT1 at Y701 (activating phosphorylation), increased expression of CXCL10, and that pre-treatment with NVP-BSK805 inhibited IFNγ-induced pY701-STAT1 and CXCL10 expression (Figure 1F). T cells and NK cells are known IFNγ producers in the pancreatic microenvironment (Brauner et al., 2010; Chapoval et al., 2001; Loos et al., 2009). To determine whether these cells could be an in vivo source for IFNγ in our mouse model, we performed an ISH for Ifng combined with IHC for T-cell surface glycoprotein CD4 (CD4), T-cell surface glycoprotein CD8 (CD8), or NKG2-D type II integral membrane protein (NKG2D) markers. As expected from published data, we found both T cells and NK cells as a potential source for IFNγ (Figure 1G).

Inflammatory macrophages are the recipients for CXCL10

With respect to early events leading to development of PDA, the influx of macrophages into the pancreas has been demonstrated following injury and during development and progression of pancreatic lesions (Gea-Sorlí and Closa, 2009; Liou et al., 2015). Moreover, CXCL10 has been demonstrated as a chemoattractant for macrophages along with other immune cells (Liu et al., 2011). This prompted us to test whether macrophages are responsive to CXCL10. We found that non-polarized peritoneal macrophages express high levels of the CXCL10 receptor Cxcr3, while M1-polarized (inflammatory) macrophages express moderate levels, and M2-polarized (alternatively activated) macrophages do not express this receptor (Figure 2A). Transwell invasion assays using both peritoneal and bone marrow-derived macrophages suggest that CXCL10 can act as a chemoattractant for M1-polarized macrophages (Figure 2BFigure 2—figure supplement 1A). However, since tissue-resident macrophages have been attributed important roles in established pancreatic cancer (Zhu et al., 2017), we also determined if this population can be the recipients for CXCL10. Approximately 80% of tissue resident macrophages in normal mouse pancreas express CXCR3 (Figure 2—figure supplement 1A), but when isolated, these cells do not proliferate in response to CXCL10 (Figure 2—figure supplement 1B). In sum, our in vitro data suggests that CXCL10 may drive the chemoattraction of inflammatory macrophages to the pancreas.

Figure 2 with 1 supplement see all
Inflammatory macrophages are the recipients for CXCL10.

(A) Primary peritoneal macrophages were isolated and either left non-polarized or were polarized to M1 and M2 macrophages. CXCR3 expression was determined by qPCR. Results shown are representative of reproducible data from three independent experiments. Statistical analysis using the Student’s t-test indicates significance (marked by an asterisk). Error bars indicate standard deviation. (B) Transwell assay. 0.5 × 105 non-polarized, M1- or M2-polarized peritoneal macrophages were plated into transwell inserts. 500 ng/ml CXCL10 in media was placed in the bottom wells, and chemoattraction of macrophages was determined after 20 hr. Data shown here represents reproducible results from peritoneal macrophages obtained from three different mice (biological replicates). Statistical analysis using the Student’s t-test indicates significance (marked by an asterisk) for nonpolarized (p-value=0.034) and M1 (p-value=0.0003) macrophages. Error bars indicate standard deviation. (C) CD3+ T cells and F4/80+ macrophages were sorted from digested pancreas of KC mice using FACS and analyzed for the expression of CXCR3. The bars indicate the percentage of CXCR3+ cells among the two cell types sorted. Data represents analyses done on three mice (biological replicates). Statistical analysis was done using Student’s t-test. Error bars indicate standard deviation. (D) CXCR3 expression in M1 (F4/80+;pSTAT1+) or M2 (F4/80+;Ym1+) macrophages in pancreatic tissue of KC mice was determined by immunofluorescence. Images shown here represent whole slide analysis of staining done on the tissue of 2 KC mice (biological replicates). The scale bar indicates 10 μm. (E) Patient tumor tissue stained by ISH for Cxcr3 and overlaying immunofluorescence for inflammatory (CD68+,iNOS+) macrophages. Images shown represent whole slide analysis of staining done on the tissue from 10 patient samples. The scale bar indicates 100 μm. (F) Quantification of Cxcr3+;CD68+;iNOS+ cells in patient samples (n = 10). Statistical analysis was done using Student’s t-test. Error bars indicate standard deviation.

Figure 2—source data 1

Cxcr3 expression and migration in response to CXCL10 for polarized macrophages, CXCR3 expression in T cells and macrophages, and quantification of CXCR3+ M1 macrophages (panels A, B, C, and F).

https://cdn.elifesciences.org/articles/60646/elife-60646-fig2-data1-v2.xlsx

Next, we determined if pancreatic macrophages or T cells express CXCR3 in KC mice. Therefore, we sorted for pancreatic CD3+ or F4/80+ cells and then for the presence of CXCR3. We found that approximately 40% of pancreatic macrophages in KC mice express CXCR3 (Figure 2C). Moreover, an in situ IF-IHC analysis of pancreata of KC mice indicated that inflammatory (F4/80+;pY701-STAT1+) macrophages express CXCR3, while alternatively activated (F4/80+;Ym1+) macrophages do not express this receptor (Figure 2D), which also confirmed above in vitro data. An overlay between an ISH for Cxcr3 and IF-IHC for inflammatory macrophages (CD68+;iNOS+) in human patient tumors showed that ~70% of CXCR3+ cells are M1 macrophages and confirmed this population as a potential recipient for CXCL10 (Figure 2E,F).

CXCL10/CXCR3 signaling maintains the inflammatory phenotype of macrophages

Next, we tested the impact of blocking CXCL10/CXCR3 signaling on the inflammatory macrophage population. We isolated peritoneal primary macrophages, polarized them to inflammatory (F4/80+;iNOS+) macrophages (Figure 3—figure supplement 1A), and then blocked CXCL10/CXCR3 signaling with a CXCR3 neutralizing antibody (CXCR3 NAB). We found that upon CXCR3 neutralization, M1 macrophages, although still iNOS positive, start to express Ym1 (Figure 3A), which we previously have identified as a bona fide marker for M2 alternatively activated macrophages in precancerous abnormal pancreas lesions (Bastea et al., 2019). A more thorough analysis using qRT-PCR indicated a significant decrease in CD38, which is a distinct M1 macrophage marker (Jablonski et al., 2015), and an upregulation of Ym1, Arg1 and Fizz1 (Figure 3B), which are all markers of the alternatively activated macrophage population that previously has been shown to drive fibrosis during pancreatic lesion progression (Liou et al., 2017). CXCR3 neutralization in M1 macrophages also slightly increased Il4ra and Stat6 mRNA expression, and increased nuclear localization of active Y641-phosphorylated STAT6 (Figure 3—figure supplement 1B,C), which are additional indicators of M2 polarization (Yushi et al., 2016).

Figure 3 with 1 supplement see all
CXCL10/CXCR3 signaling maintains the inflammatory phenotype of macrophages.

(A) Peritoneal macrophages were isolated, polarized to M1, and then treated with 500 μg/ml CXCR3 NAB or isotype control IgG. After 48 hr treatment, samples were analyzed for expression of iNOS or Ym1 using immunofluorescence. Images shown are representative of three independent experiments done on peritoneal macrophages obtained from three mice (biological replicates). The scale bar indicates 100 μm. (B) Peritoneal macrophages were isolated, polarized to M1, and treated with 500 μg/ml CXCR3 NAB or isotype control IgG. After 48 hr, samples were analyzed by qPCR for expression of M1 macrophage marker Cd38 and M2 macrophage markers Ym1/Chil3, Arg1, and Fizz1/Retnla. Results shown are representative of three independent experiments done on peritoneal macrophages obtained from three mice (biological replicates). Statistical analysis using the Student’s t-test indicates significance (marked by an asterisk, Cd38: p-value=0.0009, Ym1/Chil3: p-value<0.0001, Arg1: p-value<0.0001, Fizz1/Retnla: p-value<0.0001). Error bars indicate standard deviation. (C) Pancreatic abnormal areas from KC mice treated with CXCR3 NAB or isotype control IgG were analyzed for presence of inflammatory macrophages (co-immunofluorescence for F4/80 and pY701-STAT1). Shown is a representative area from staining and analysis done on three mice per group. The H and E staining highlights the region analyzed. The scale bar indicates 50 μm. (D) Quantification of pY701-STAT1+ macrophages in pancreata from KC mice (n = 3 mice per treatment group) treated with CXCR3 NAB or isotype control IgG. Cells were counted in three representative fields per mouse. The arcsin transformation was done on the proportion of macrophages which were pY701-STAT1+. Statistical analysis using the Student’s t-test indicates significance between biological replicates (indicated by an asterisk, p-value=0.0004). Error bars indicate standard deviation.

Figure 3—source data 1

qPCR forCd38,Ym1/Chil3,Arg1, and Fizz1/Retnlain M1 polarized macrophages treated with CXCR3 NAB or isotype control IgG, and quantification of pY701-STAT1+ macrophages in KC mice treated with CXCR3 NAB or isotype control IgG (panels B and D).

https://cdn.elifesciences.org/articles/60646/elife-60646-fig3-data1-v2.xlsx

The interferon regulatory factors (IRFs) IRF4 and IRF5 have been shown to be key regulators of macrophage polarization (Bastea et al., 2019; Günthner and Anders, 2013). M1-polarized macrophages subjected to CXCR3 inhibition upregulated IRF4, a transcription factor for M2 macrophage polarization, and downregulated the M1 transcription factor IRF5 (Figure 3—figure supplement 1D), indicating a potential mechanism of how pancreatic macrophage populations may shift when CXCR3 is blocked.

To test whether neutralization of CXCL10/CXCR3 signaling also decreases inflammatory macrophages in vivo, we treated KC mice with a CXCR3 neutralization antibody (CXCR3 NAB) or an isotype control IgG antibody over a period of 9 weeks (Figure 3—figure supplement 1E). While overall numbers of macrophages remained unchanged (Figure 3—figure supplement 1F), IF-IHC analyses for F4/80+;pY701-STAT1+ cells indicated a >50% decrease in inflammatory macrophages in the CXCR3 NAB-treated mice (Figure 3C,D).

Neutralization of CXCL10/CXCR3 signaling increases alternatively activated pancreatic macrophages, SMA-positive fibroblasts, and areas of pancreatic lesions

We then determined if the decrease in inflammatory macrophages after neutralization of CXCL10/CXCR3 signaling can lead to an increase in Ym1+ alternatively activated macrophages. The presence of Ym1+ macrophages in the pancreas was increased by approximately threefold when KC mice were treated with a CXCR3 NAB, as compared to treatment with the isotype control IgG (Figure 4A,B). Similar effects on this macrophage population were observed when KC mice were treated with a CXCL10 NAB, as compared to treatment with the isotype control IgG (Figure 4—figure supplement 1A–C).

Figure 4 with 3 supplements see all
Neutralization of CXCR3 signaling increases alternatively activated pancreatic macrophages and progresses pancreatic lesions.

(A) Pancreatic abnormal areas from KC mice treated with CXCR3 NAB or isotype control IgG were analyzed by IHC for presence of Ym1+ macrophages. Shown is a representative area and H and E staining on serial sections of the tissue. The scale bar indicates 100 μm. (B) Quantification of Ym1+ macrophages in pancreata from KC mice (n = 3 mice per treatment group) treated with CXCR3 NAB or isotype control IgG. Ym1+ cells were counted in three representative fields per mouse, and reported as the fold change relative to the average of the isotype control IgG treatment group. Statistical analysis was done using the Student’s t-test. The asterisk indicates statistical significance (p-value=0.025). Error bars indicate standard deviation. (C) Pancreatic abnormal areas from KC mice treated with CXCR3 NAB or isotype control IgG were analyzed by IHC for the fibrosis marker smooth muscle actin (SMA). Shown is a representative area and H and E staining on serial sections of the tissue. The scale bar indicates 100 μm. (D) Quantification of SMA content in pancreata from KC mice (n = 3 per treatment group) treated with CXCR3 NAB or isotype control IgG. Quantification was performed with the Image scope positive pixel algorithm. Abnormal areas were manually traced on the tissue, and the algorithm was run. The resulting pixel values were divided by the area analyzed to obtain staining per area of abnormal tissue. Statistical analysis was done using the Student’s t-test. The asterisk indicates statistical significance (p-value=0.038). Error bars indicate standard deviation. (E) Representative images of H and E stained pancreata from non-transgenic (ntg) or KC mice treated with CXCR3 NAB or isotype control IgG. The scale bar indicates 100 μm. (F) Quantification of the abnormal pancreatic surface area in pancreata from KC mice (n = 4 per treatment group) treated with CXCR3 NAB or isotype control IgG. For quantification, abnormal areas were manually traced out and values were normalized to the total pancreatic area to obtain abnormal area per area of pancreatic tissue analyzed. For statistical analysis, data were transformed via arcsin transformation before a t-test was performed. The asterisk indicates statistical significance (p-value=0.037). Error bars indicate standard deviation. (G) Pie graph showing the percentage distribution of the types of lesions found in the abnormal surface areas of mice from both treatment groups. Percentages (with standard error) shown are from analysis done on four mice per group.

Figure 4—source data 1

Quantification of Ym1, SMA, abnormal area, and lesion type in CXCR3 NAB and isotype control IgG treated KC mice (panels B, D, F, and G).

https://cdn.elifesciences.org/articles/60646/elife-60646-fig4-data1-v2.xlsx

Previously, Ym1+ macrophages in the KC animal model have been shown to drive fibrosis during pancreatic cancer development (Liou et al., 2017), and after neutralization of CXCR3, or alternatively neutralization of CXCL10, we observed a correlating increase in fibrosis (Figure 4C,D and Figure 4—figure supplement 1D,E). In line with increased presence of alternatively activated macrophages and increased fibrosis, abnormal areas (lesions and stroma) increased approximately twofold when KC mice were treated with CXCR3 NAB (Figure 4E,F). Of note, neutralization of CXCR3 in non-transgenic (ntg) mice did not show any change in the normal pancreatic tissue (Figure 4E). Quantification of different lesion types from both treatment groups indicated slight, but not statistically significant differences in the distribution of ADM (80.7 ± 3.8% in control-treated versus 75.2 ± 4% CXCR3 NAB-treated) and PanIN1 (19.3 ± 3.8% in control-treated versus 24.6 ± 4% CXCR3 NAB-treated) lesions (Figure 4G).

Neutralization of CXCL10/CXCR3 signaling does not significantly affect the presence of T cells

In addition to macrophages, T cells can be chemoattracted via CXCR3 signaling (Dufour et al., 2002). Since approximately 15% of CD3+ T cells express CXCR3 in our KC animal model (see Figure 2C), we also tested the effect of CXCL10/CXCR3 neutralization on T-cell populations in pancreata of KC mice. After neutralization of CXCR3, we detected a slight (approximately 20%) decrease in pancreatic CD3+ cells (Figure 4—figure supplement 2A), but did not observe any changes in NK (NKG2D+;CD3) cells (Figure 4—figure supplement 2B) or production of IFNγ (Figure 4—figure supplement 2C). Moreover, neutralization of CXCL10 did not result in a decrease of CD3+;CD4+ or CD3+;CD8+ T cells (Figure 4—figure supplement 2D,E).

T cells do not contribute to CXCL10/CXCR3-mediated effects on macrophage populations or abnormal pancreatic lesions

To test whether effects on macrophage populations or abnormal pancreatic lesion areas are due to the presence of T cells, we performed a T-cell depletion followed by CXCR3 neutralization (Figure 4—figure supplement 3A). T cells in KC mice were depleted using previously described antibodies that target CD8α and CD4 (Laky and Kruisbeek, 2016). Regardless of T cells being depleted or present (Figure 4—figure supplement 3B), CXCR3 neutralization increased abnormal pancreatic area (Figure 4—figure supplement 3C), decreased M1 macrophages (Figure 4—figure supplement 3D), and increased Ym1+ macrophages (Figure 4—figure supplement 3E). Moreover, T-cell depletion led to a slight but non-significant decrease in Ifng, suggesting that T cells are not the only source for IFNγ in this experimental system (Figure 4—figure supplement 3F).

To rigorously test a direct effect of CXCL10/CXCR3 signaling on macrophages in a system absent of T cells, we expressed CXCL10 in SM3 PanIN cells and implanted them into the pancreas of T cell-deficient athymic nude mice (Figure 4—figure supplement 3G). Therefore, we infected SM3 PanIN cells (described in Liou et al., 2017) with a lentivirus carrying CXCL10 (SM3-CXCL10) or a control lentivirus carrying eGFP (SM3-control), tested them for secretion of CXCL10 (Figure 4—figure supplement 3H), and generated PanIN organoids by plating them in Matrigel for 2 days (Figure 4—figure supplement 3I). Organoids were recovered from Matrigel and, together with activated stellate cells, implanted into the pancreas of nude mice. Two weeks after implantation, SM3-CXCL10 implanted mice had approximately half as much abnormal tissue area (lesions and fibrosis) as compared to SM3-control implanted mice (Figure 5A,B). Analysis of SMA content showed significantly reduced fibrosis in the SM3-CXCL10 implanted mice (Figure 5C). As expected from the reverse experiment in which we had blocked CXCR3 (Figure 3D), expression of CXCL10 increased the presence of F4/80+ macrophages (Figure 5D). Further analysis of macrophage polarization types indicated an increase of M1 and a decrease of M2 phenotypes when CXCL10 was present (Figure 5E).

Overexpression of CXCL10 in pancreatic lesions increases inflammatory macrophages and decreases lesion formation in the pancreas.

(A) Athymic nude mice were orthotopically implanted with PanIN organoids obtained from lentivirally infected SM3-CXCL10 or SM3-control cells (see Figure 4—figure supplement 3G–I). Mice were euthanized 2 weeks post-surgery, and pancreatic tissue was analyzed. Shown are representative images of abnormal areas in the pancreas. The scale bar represents 500 μm. (B) Abnormal areas (lesions and stroma) were manually traced for quantification and normalized to total pancreatic area analyzed (n = 3 mice per group). For statistical analysis, data were transformed via arcsin transformation before a t-test was performed. The asterisk indicates statistical significance (p-value=0.011). Error bars indicate standard deviation. (C) Fibrotic content was analyzed using SMA as a marker (n = 3 mice per group). Quantification was performed with the Image scope positive pixel algorithm as described in Figure 4 and normalized to the total areas analyzed. Statistical analysis was done using the Student’s t-test. The asterisk indicates statistical significance (p-value=0.032). Error bars indicate standard deviation. (D) Tissue was analyzed for infiltration of total macrophages between groups using F4/80 as a marker (n = 3 mice per group). Staining was quantified using the positive pixel algorithm and normalized to the total areas analyzed. Statistical analysis was done using the Student’s t-test. The asterisk indicates statistical significance (p-value=0.0096). Error bars indicate standard deviation. (E) Detailed analysis of tissue with F4/80 and pY701-STAT1 (M1 macrophage population) and Ym1 (M2 macrophage population). Quantification was performed either manually (M1) on three representative fields for each mouse tissue analyzed or using the positive pixel algorithm (M2) and then normalized to the total areas analyzed (n = 3 mice per group). Statistical analysis was done using Student’s t-test. The asterisk indicates statistical significance (M1: p-value=0.019, M2: p-value=0.028). Error bars indicate standard deviation. (F) Schematic diagram of how CXCL10/CXCR3 signaling impacts pancreatic lesion progression. IFNγ released from immune cells (T and NK) in the pancreatic tissue stimulates CXCL10 release from early lesions (ADM, PanIN1). CXCL10 stimulates chemoattraction and proliferation of peritoneal macrophages and helps maintain their inflammatory phenotype. Blocking the ligand–receptor interaction with a CXCR3 NAB leads to loss of M1 identity, resulting in an increase in the Ym1+ macrophage population, along with more lesions and a higher fibrotic content.

Figure 5—source data 1

Quantification of abnormal area, SMA, F4/80, M1 macrophages, and M2 macrophages in athymic nude mice orthotpically implanted with lentivirally infected SM3-CXCL10 or SM3-control PanIN organoids (panels B-E).

https://cdn.elifesciences.org/articles/60646/elife-60646-fig5-data1-v2.xlsx

Discussion

While inflammatory and alternatively activated macrophages have important functions in different stages of pancreatic cancer development (Stone and Beatty, 2019; Storz, 2017), little is known about how these populations are regulated after injury or an oncogenic event, and how they crosstalk with lesion cells or other cells of the lesion microenvironment. In this study, we delineate the importance of CXCL10/CXCR3 signaling during the early phase of pancreatic cancer development.

The CXCL10/CXCR3 signaling axis has been implicated in generating inflammation in various diseases including pancreatitis (Lee et al., 2017; Liu et al., 2011; Singh et al., 2007). This is because it regulates the chemotaxis of CXCR3+ immune cells such as macrophages, T cells, and NK cells (Luster and Ravetch, 1987; Taub et al., 1993; Tomita et al., 2016; Zhou et al., 2010). With respect to cancer, gastric cancer patients with upregulated CXCR3 expression showed better survival (Chen et al., 2019; Li et al., 2015). Also, high expression of CXCL10 and other CXCR3 ligands in ovarian, esophageal, and non-small cell lung carcinoma indicate favorable prognoses (Bronger et al., 2016; Cao et al., 2017; Sato et al., 2016). In contrast, in pancreatic cancer, expression of both CXCL10 and CXCR3 in tumor tissue has been correlated with a poor prognosis (Liu et al., 2011; Lunardi et al., 2014) mostly due to increased chemoresistance (Delitto et al., 2015). However, the role of CXCL10/CXCR3 signaling during early development of the disease has not been addressed.

Using the KC mouse model, we show that CXCL10 is produced by cells of precancerous ADM and PanIN1 lesions (Figure 1A,B). CXCL10 is also known as interferon gamma-inducible protein-10 (IP-10) (Luster et al., 1985; Ohmori and Hamilton, 1993), suggesting IFNγ as a potential factor sufficient to drive CXCL10 expression. Indeed, SM3 PanIN cells showed upregulation of CXCL10 expression in response to IFNγ (Figure 1C–E). This was mediated through JAK-STAT1 signaling (Figure 1F), which has been previously described to be upregulated and activated via IFNγ in acinar cells (Gallmeier et al., 2005). Many cell types, including T cells and NK cells in the pancreatic microenvironment, have been shown to secrete IFNγ (Brauner et al., 2010; Castro et al., 2018; Corthay et al., 2005; Fogar et al., 2011), and analysis for CD4+, CD8+, and NKG2D+ cells indicated T cells and NK cells in the vicinity of lesions as a potential source for IFNγ in our model (Figure 1G).

Our in vitro data implicate peritoneal or bone-marrow-derived inflammatory macrophages as major recipients for CXCL10, where CXCL10 can act as a chemoattractant (Figure 2B, Figure 2—figure supplement 1A). This is important because influx of macrophages is a major driver of pancreatic inflammation (Gea-Sorlí and Closa, 2009). This correlates with in vivo data showing that in the KC model CXCR3 is expressed by pancreatic inflammatory macrophages, but not by Ym1+ M2 macrophages (Figure 2D). In patient tissue, we found that approximately 70% of CXCR3 expressing cells are inflammatory (CD68+;iNOS+) macrophages (Figure 2E,F).

Unlike other factors contributing to macrophage chemoattraction into the pancreas, such as sICAM1 (Liou et al., 2015), the expression of CXCL10 from acinar cells is not driven by the activation of oncogenic KRas (Figure 1—figure supplement 1D). This finding is supported by other studies that have shown CXCL10 upregulation in chronic pancreatitis patients, which occurs in the absence of oncogenic mutations (Singh et al., 2007).

The importance of CXCL10/CXCR3 signaling in inflammatory macrophages is underscored by the fact that blocking this interaction causes them to lose their identity, as evident by upregulation of markers for alternatively activated macrophages (Figure 3A–C). Even though neutralizing CXCR3 did not simultaneously decrease iNOS expression while increasing M2 markers (Figure 3A, Figure 3—figure supplement 1B), there was a marked drop in Cd38, a distinct marker for M1 polarized macrophages (Jablonski et al., 2015), indicating a loss in M1 identity (Figure 3B). Mechanistically, this shift in polarization upon CXCR3 neutralization may be explained by upregulation of the M2 transcription factor Irf4 and downregulation of the M1 transcription factor Irf5 (Figure 3—figure supplement 1D). Interestingly, the resulting alternatively activated macrophage population is characterized by expression of markers (Ym1, Fizz1, Arg1) that previously have been attributed to a subset of pancreatic macrophages (usually described as Ym1+ macrophages) that drive fibrinogenesis and tumor progression (Liou et al., 2017).

In support of this explant data, neutralizing CXCR3 in vivo also led to a decrease in inflammatory (F4/80+;pY701-STAT1+) macrophages (Figure 3C,D) and an increase in Ym1+ macrophages (Figure 4A,B). This accompanied increased fibrosis at the pancreatic lesion areas and more abnormal regions in the pancreas overall (Figure 4C, D, and F). Our data is in line with a recent study in which it was reported that Cxcr3−/ mice show an abundance of M2 macrophages in breast tumors (Oghumu et al., 2014). Specifically, similar to what we observed after CXCR3 neutralization, Cxcr3−/− macrophages from these mice had reduced ability to upregulate iNOS and showed a predisposition for M2 polarization (Oghumu et al., 2014). Since there are other ligands described that can engage the receptor CXCR3 (Van Raemdonck et al., 2015), we also neutralized CXCL10 in KC mice and found similar trends of increased presence of Ym1+ macrophages and increased fibrosis (Figure 4—figure supplement 1). In a reverse experiment, enhanced expression of CXCL10 in PanIN cells significantly decreased overall abnormal lesion areas, fibrosis, and presence of M2 macrophages, but increased the presence of M1 macrophages (Figure 5).

CXCL10 is known to chemoattract cell types other than macrophages, mainly T cells, and approximately 15% of pancreatic T cells in KC mice are positive for CXCR3 (Figure 2C). However, our in vivo study in which we overexpressed CXCL10 in PanIN cells and observed reverse effects to CXCR3 or CXCL10 neutralization was performed in nude mice which lack T cells (Figure 4—figure supplement 2). In addition, depletion of CD4+ and CD8+ T cells in immunocompetent KC mice had no impact on total abnormal tissue area or M1 and M2 macrophage abundance after CXCR3 neutralization (Figure 4—figure supplement 3A–E). Taken together these data suggest no significant role for T cells in CXCL10/CXCR3-driven development of pancreatic cancer.

During pancreatic cancer development, inflammatory macrophages are predominantly located at ADM lesions, driving the transdifferentiation process (Liou et al., 2015; Liou et al., 2013). Our data now indicate that cells undergoing ADM (and to some extent low-grade PanIN) express CXCL10 to chemoattract inflammatory macrophages and that CXCL10/CXCR3 signaling is crucial for the sustenance of their inflammatory identity (Figure 5F). More progressed PanIN1 lesions have been shown to express the anti-inflammatory cytokine interleukin-13 (IL-13), which causes a polarization shift from M1 toward an alternatively activated, Ym1+ phenotype (Liou et al., 2017). Given the importance of CXCL10/CXCR3 interaction in the maintenance of the inflammatory identity of macrophages in our study, the reduced CXCL10 expression by PanIN as compared to ADM lesions (Figure 1A,B) may leave macrophages more susceptible to M2 polarization by cytokines like IL-13.

Considering our results, use of agonists for the receptor CXCR3 at stages of low-grade lesions may be useful to modulate macrophage polarization in the microenvironment such that a predominantly inflammatory population (M1) can be sustained. However, it needs to be noted that in pancreatic cancer expression of both CXCL10 and CXCR3 in tumor tissue have been correlated with metastasis and poor prognosis (Cannon et al., 2020; Hirth et al., 2020; Liu et al., 2011; Lunardi et al., 2014; Romero et al., 2020). Therefore, it is unclear if treatment of pancreatic tumors with a CXCR3 agonist will result in a polarization switch of tumor-associated macrophages that renders the lesion microenvironment less supportive for tumors, and increases efficiency of chemotherapy, or if it has a tumor-promoting effect. This will be addressed in future studies.

Materials and methods

Cells, antibodies, and reagents

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SM3 primary duct-like cells were isolated from pancreata of 6 week old KC mice as previously described (Agbunag et al., 2006; Liou et al., 2017). The genotype of these cells has been verified, and cells are routinely tested for mycoplasma infection. SM3 cells were maintained in DMEM/F12 media (Sigma-Aldrich, St. Louis, MO) containing 5% Nu Serum IV culture supplement (Corning, Corning, NY), 25 μg/ml bovine pituitary extract (Gibco/Thermo Scientific, Waltham, MA), 20 ng/ml EGF, 0.1 mg/ml soybean trypsin inhibitor type I (AMRESCO, Solon, OH), 5 mg/ml d-glucose (Sigma-Aldrich), 1.22 mg/ml nicotinamide (Sigma-Aldrich), 5 nM triiodo-l-thyronine (Sigma-Aldrich), 1 μM dexamethasone (Sigma-Aldrich), 100 ng/ml cholera toxin (Sigma-Aldrich), 5 ml/l insulin-transferrin-selenium (Corning), and 100 U/ml penicillin/streptomycin (Gibco/Thermo Scientific). Collagenase I was from MilliporeSigma (St. Louis, MO). Rat tail collagen I was from BD Biosciences (San Diego, CA). All antibodies used for western blotting, immunohistochemistry and immunofluorescence were from the following sources: Peprotech (Rocky Hill, NJ), Abcam (Cambridge, MA), Cell Signaling Technologies (Danvers, MA), Dako (Santa Clara, CA), STEMCELL Technologies (Vancouver, Canada), Biorad (Hercules, CA), and LifeSpan BioSciences (Seattle, WA), BD Biosciences (Franklin Lakes, NJ), BioLegend (San Diego, CA), GeneTex (Irvine, CA), Miltenyi Biotec (Auburn, CA) and are described in detail in Key Resources Table. All neutralizing antibodies that have been used in animal studies are described in detail in Materials and methods section for these experiments as well as in Key Resources Table. Secondary HRP-linked anti-mouse or anti-rabbit antibodies were from Jackson ImmunoResearch (West Grove, PA). DAPI and LPS were from Sigma-Aldrich. IL4, IFNγ, and CXCL10 were from PeproTech (Rocky Hill, NJ).

Isolation of primary macrophages (peritoneal or bone marrow derived) and polarization

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Peritoneal macrophages: Non-transgenic mice were injected with 2–3 ml of 5% aged thioglycollate. Five days later, mice were euthanized and peritoneal macrophages were collected immediately. A small incision was made in the peritoneum and RPMI-1640 media with 10% FBS was flushed through the peritoneal cavity using a sterile transfer pipette. The peritoneal wash was centrifuged, washed with fresh RPMI1640 + 10% FBS media, and cells were plated onto 10 cm dishes. After 2–3 hr, once macrophages completely adhered to the plates, cells were washed two to three times to remove non-adherent cells and fresh media was added. Cells were allowed to acclimatize overnight before harvesting and experimental manipulation. Bone marrow-derived macrophages (BMDM): Femurs of non-transgenic mice were cut proximal to the joints on both ends and washed twice in cold, sterile PBS (without calcium and magnesium) to remove excess blood and muscle. Using forceps, the bones were held over a sterile 50 ml tube, and the bone cavity was flushed twice with 5 ml cold PBS using a 25G needle and syringe. The bones were discarded, and the bone marrow was pelleted (10 min, 500 × g, RT), then gently resuspended to single cells in 10 ml warm macrophage complete medium (DMEM-F12 with l-glutamine + 10% FBS + 100 U/ml penicillin + 100 µg/ml streptomycin + 100 U/ml of M-CSF) (Zhang et al., 2008). After counting, 4 × 105 cells were added to 10 cm dishes in 10 ml macrophage complete medium. On days 3 and 5, 5 ml of medium was replaced with fresh complete medium. On day 7, the cells were polarized. Polarization of peritoneal or bone marrow-derived macrophages to M1 or M2 phenotypes was obtained by stimulation with LPS + IFNγ (M1 polarization) and/or with IL-4 (M2 polarization) for 24 hr as previously described (Liou et al., 2017).

Isolation of pancreas tissue resident macrophages

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Pancreata from 8 week old, non-transgenic mice were harvested by washing the pancreas in HBSS, mincing the tissue, centrifuging (931 × g, 4°C, 2 min), and then dissociating the tissue in collagenase (2 mg/ml, 5 ml, 37°C, 20 min, 220 rpm). To stop dissociation, HBSS + 5% FBS was added to the pancreas–collagenase mixture and washed two additional times with HBSS + 5% FBS (931 × g, 4°C, 2 min). Pancreas cells were then filtered through 500 μm and 105 μm meshes prior to adding the cell suspension to HBSS + 30% FBS and centrifuging (233 × g, 4°C, 2 min) to obtain a cell pellet. Cells were then labeled with F4/80 magnetic beads (Miltenyi Biotec, Auburn, CA) to isolate pancreas-resident macrophages. Cells were filtered through a 40 μm mesh to obtain a single-cell suspension, and then cells were incubated with F4/80 magnetic beads in MACS buffer (15 min, 4°C, as per the manufacturer’s instructions) (MACS buffer: PBS, 0.5% BSA, 2 mM EDTA). Cells were washed with MACS buffer (300 × g, 4°C, 10 min), filtered through 40 μm mesh, and then applied to pre-washed LS Columns (Miltenyi Biotec, Auburn, CA). Per column instructions, magnetically labeled cells were acquired and plated in DMEM-F12 + 10% FBS + 1% l-glutamine + penicillin/streptomycin + 0.1 μg/ml macrophage colony stimulating factor (Peprotech, Rocky Hill, NJ).

Genetic animal model and treatments

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Ptf1a/p48cre/+ and LSL-KrasG12D/+ mouse strains and genotyping of mice have been described previously (Liou et al., 2015). Seven to 8 week old Ptf1a/p48cre;LSL-KrasG12D (KC) or non-transgenic (ntg) mice with the same background were injected intraperitoneally (IP) with a CXCR3 neutralizing antibody (CXCR3 NAB; BE0249) (Bio X Cell, West Lebanon, NH) or an isotype control IgG; BE0091 (Bio X Cell) at 200 µg/mouse for 9 weeks. Males and females were randomly allocated to different groups since there are no sex-based differences observed in this model. 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.

For T-cell depletion, 6 week old Ptf1a/p48cre;LSL-KrasG12D mice were intraperitoneally injected with both anti-mouse CD4 (BP0003, Bio X Cell) and anti-mouse CD8α (BP0061, Bio X Cell) antibodies, or their IgG2b isotype control (BP0090, Bio X Cell). Two hundred micrograms of each antibody was injected per mouse for five consecutive days. After T-cell depletion, mice were segregated into different groups and injected with CXCR3 NAB (BE0249, Bio X Cell) or IgG isotype control antibodies (BE0091, Bio X Cell).

Human pancreatic tissue samples

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Patient tissues were obtained from archival materials in accordance with institutional guidelines and prior institutional review board (IRB) approval.

Immunofluorescence on cells and tissue

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For paraffin-embedded tissue, slide sections were deparaffinized, and antigen retrieval was performed with 10 mM sodium citrate buffer (pH 6.0) for 25 min at 100°C. Then, they were treated with 3% H2O2 for 15 min at room temperature, rinsed with PBS, and blocked with serum-free Protein Block (DAKO, Santa Clara, CA) for 1 hr at room temperature. Slides were incubated with primary antibodies diluted in 150 µl per slide of Antibody Diluent (Dako) overnight. Slides were washed three times with 0.5% Tween20 in PBS and incubated with appropriate Alexa-Fluor labeled secondary antibodies (Invitrogen, Carlsbad, CA) at 1:500 and DAPI at 125 µg/ml for 1 hr. Slides were washed three times with 0.5% Tween20 in PBS followed by cover-slipping with PermaFluor mounting media (Thermo Fisher Scientific, Waltham, MA). For imaging, whole slides were scanned using the Aperio fluorescence scanner (Leica, Buffalo Grove, IL) or the Pannoramic 250 Flash III (3DHISTECH).

For cellular staining, cells grown in ibidi chamber slides were washed with cold PBS and fixed with 4% paraformaldehyde (PFA) for 15 min at 37°C. Fixed cells were washed with PBS and permeabilized with 0.1% Triton X-100 for 10 min at room temperature. Then, cells were blocked with 3% BSA + 0.05% Tween in PBS for 30 min at room temperature. Incubation with primary antibodies was done overnight at 4°C. Cells were washed with PBS and incubated with secondary antibodies at 1:500 and DAPI at 125 µg/ml for 2 hr. Cells were washed, and mounting media was added to the wells, followed by imaging on a fluorescence microscope (Carl Zeiss, Thornwood, NY).

Flow cytometry

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Murine pancreata were resected, and tissue was dissociated using the mouse tumor dissociation kit (Miltenyi, Bergisch Gladbach, Germany) per the manufacturer’s protocol. Dissociated tissue was sequentially passed through 500 μm (Repligen, Boston, MA), 105 μm (Repligen), and 40 μm (Thermo Fisher Scientific) filters to acquire a single-cell suspension before magnetic isolation of CD45+ cells. Cells were incubated with CD45+ MicroBeads (Miltenyi) followed by magnetic separation using LS Columns (Miltenyi) on a QuadroMACS magnet (Miltenyi) per the manufacturer’s protocol. CD45+ cells were then labeled with LIVE/DEAD Fixable Violet Dead Cell Stain Kit (Thermo Fisher Scientific) before subsequent fixation and staining using the PerFix-nc kit (Beckman Coulter, Brea, CA) as per the manufacturer’s protocol. Antibodies are described in detail in Key Resources Table. The Attune NxT (Thermo Fisher Scientific) was used for multicolor flow cytometric detection, and analysis was done using FlowJo (BD Biosciences).

In situ hybridization

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The procedure for ISH has been described in detail previously (Bastea et al., 2019). Briefly, ISH was performed using RNAscope Assay 2.5 HD Reagent Kit–Brown or RNAscope Multiplex Fluorescent Reagent Kit v2 (Advanced Cell Diagnostics, Hayward, CA). Formalin-fixed, paraffin-embedded (FFPE) sections (5 μm) were baked at 60°C for 1 hr, deparaffinized in xylene for 15 min, dehydrated in 100% ethanol, and dried at room temperature overnight in a desiccator. Next day, slides were treated with hydrogen peroxide for 10 min, followed by target retrieval for 8 min. Protease treatment was done for 15 min at 40°C in a hybridization oven. Next, slides were incubated with the appropriate probe for 2 hr. RNAscope target probes used were Cxcl10 (Mm-Cxcl10 408921), Cxcr3 (Mm-Cxcr3 4025110), CXCR3 (Hs-CXCR3 539251), and Ifng (Mm-Ifng 311391). After probe hybridization, amplification steps were followed according to the manufacturer’s protocol, except Amp 5 step, which was modified to 1 hr incubation in the DAB procedure (RNAscope Assay 2.5 HD Reagent Kit–Brown). Slides were counterstained with hematoxylin, dehydrated, and mounted.

When followed by IF, slides were treated with boiling 10 mM citrate buffer (pH 6.0) for 10 min to repeat antigen retrieval and the regular IF protocol was followed. Primary antibodies were used at concentrations listed in Key Resources Table.

For the fluorescent detection (RNAscope Multiplex Fluorescent Reagent Kit v2), following AMP1, 2 and 3 steps according to the manufacturer’s protocol, probes were labeled using the Opal 690 fluorophore reagent pack (Perkin Elmer, Waltham, MA). Next, regular IF procedure was performed for co-staining. Samples were counterstained with DAPI and mounted. For imaging, whole slides were scanned at 40× magnification using the Aperio fluorescence scanner (Leica).

Isolation of primary acinar cells

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Pancreas was removed quickly following euthanasia and placed in cold HBSS media. After washing in cold HBSS media twice, pancreas was minced into small 1–5 mm pieces and digested with collagenase I in a 37°C shaker for 20 min. After 20 min, the digestion was stopped by adding an equal volume of cold HBSS media with 5% FBS. The digested pieces were passed through a 500 μm mesh. More 5% FBS media was passed through the mesh with digested pieces to further strain them. The filtrate was then passed through a 105 μm mesh. The filtrate from this step was added dropwise to a tube containing HBSS media with 30% FBS. The cell suspension was centrifuged at 205 × g for 2 min at 4°C. Acinar cells were then resuspended in complete Waymouth’s media (1% FBS, 0.1 mg/ml soybean trypsin inhibitor, 1 μg/ml dexamethasone).

3D collagen explant culture of pancreatic acinar cells

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Cell culture plates were coated with collagen I in Waymouth media without supplements. Freshly isolated primary pancreatic acinar cells were added as a mixture with collagen I/Waymouth media on the top of this layer (3D on-top method). Furthermore, Waymouth complete media was added on top of the cell/gel mixture and replaced the following day and then every other day. When inhibitors, peptides, or proteins were added, the compound of interest was added to both, the cell/gel mixture and the media on top. To express proteins using adenovirus, acinar cells were infected with adenovirus of interest and incubated for 3–5 hr before embedding in the collagen I/Waymouth media mixture. At day 6 or 7 (dependent on time course of duct formation), numbers of ducts were counted under a microscope, and photos were taken to document structures.

Adenoviral infection of acinar cells

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For adenoviral infection, Adeno-cre-GFP or Adeno-null-GFP viruses (Vector Biolabs, Malvern, PA) were added to the resuspended acinar cells in Waymouth’s complete media in a non-adherent dish. Infection was carried out for 3 hr with gentle swirling every 15 min during the first hour. After the 3 hr infection, cell suspension was mixed with Rat tail collagen-Type I (BD Biosciences, San Jose, CA) and plated.

Lentiviral infection of PanIN lesion cells, organoid formation, and orthotopic implantation in athymic nude mice 

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SM3 PanIN cells were infected using control lenti-eGFP (LPP-EGFP-Lv105-025-C) or lenti-cxcl10 (LPP-Mm03214-Lv105-100) lentiviral particles (Genecopoeia, Rockville, MD) with 5 μg/ml of polybrene (Santa Cruz Biotechnology, Dallas, TX) at 70–80% confluency. Infected cells were incubated at 4°C for 2 hr and then at 37°C overnight. On the following day, media containing lentiviral particles and polybrene was removed and replaced with fresh media to allow the cells to recover. Next day, selection media containing 2.5 µg/ml puromycin was added to the cells and was replaced every 2–3 days. After 11 days of selection, cells were harvested and embedded in Matrigel (Corning, Corning, NY) with regular media without puromycin. After 2 days, cells formed duct-like PanIN organoid structures. Using a non-enzymatic cell dissociation reagent (Corning), PanIN organoids were harvested and mixed with activated primary pancreatic stellate cells at a ratio of 1:4. Cell mixture was resuspended in phenol-red free Matrigel, and 50 µl (25,000 organoid cells + 100,000 activated primary stellate cells) was injected directly into the pancreas of athymic nude (Foxn1nu) mice (Jackson laboratory, Bar Harbor, ME). Wound was closed using 4–0 Vicryl sutures and 7 mm wound clips. After 1 week of recovery, wound clips were removed, and ultrasound imaging was performed to ensure implantation of cells.

RNA extraction and quantitative PCR

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Cells were washed with cold PBS, and RNA extraction was done using the RNeasy PLUS Mini Kit (Qiagen, Germantown, MD). cDNA was prepared using the High Capacity cDNA RT Kit (Applied Biosystems, Foster City, CA). TaqMan Fast Mix 2x (Applied Biosystems) was used to prepare qPCR along with the primer/probe sets described in Key Resources Table. Reactions were run on the QuantStudio 7 Flex Real-Time PCR System (Applied Biosystems). All CT values were normalized to Gapdh, and the ΔΔCT method was used to calculate fold changes.

Protein isolation and western blot

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Cells were washed with cold PBS (140 mM NaCl, 2.7 mM KCl, 8 mM Na2HPO4, and 1.5 mM KH2PO4 [pH 7.2]) twice and lysed using RIPA buffer with a protease inhibitor cocktail (Sigma-Aldrich). Lysates were incubated on ice for 30 min followed by centrifugation at 13,000 rpm for 15 min at 4°C on a table top centrifuge. Protein supernatant was separated from cell debris, and concentration was measured using the BioRad Protein Assay (BioRad, Hercules, CA). Samples were run on SDS-PAGE gels and transferred to nitrocellulose membranes. Proteins of interest were detected using the appropriate primary antibodies at indicated concentrations (Key Resources Table) and horseradish peroxidase (HRP)-conjugated secondary antibodies.

Transwell chemoattraction assays

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Peritoneal or bone marrow-derived macrophages were seeded in serum-free RPMI media on 5 μm transwell permeable inserts (Corning, Corning, NY). Six hundred microliters of control media or media containing 500 ng/ml of CXCL10 was placed in the bottom wells. Experiments were conducted in triplicates for each condition. Cells were incubated for the indicated time. Inserts were then carefully removed, washed with PBS, and fixed in 4% PFA for 15 min at 37°C. After gently washing the inserts twice, cells were permeabilized with 0.1% Triton X-100 for 10 min at room temperature and stained with DAPI for counting.

MTT proliferation assay

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Proliferation of pancreas-resident macrophages was analyzed via MTT assay (Sigma, St. Louis, MO), where wells were incubated with MTT labeling reagent (4 hr, 37°C, 5% CO2). Following MTT labeling, cells were incubated with solubilization solution (10% SDS in 0.01 M HCl) overnight (37°C, 5% CO2), and absorbance was read the following morning at 500 nm (Synergy HT plate reader, BioTek, Winooski, VT).

Cytokine array

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The cytokines secreted by SM3 cells were determined using the Proteome Profiler Mouse Cytokine Array Kit (R and D Systems) according to the manufacturer’s instructions.

Quantification and statistical analysis

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All cell biological and biochemical experiments have been performed at least three times. For animal experiments, if not stated otherwise in the figure legends, pancreatic samples from n = 3 mice have been used for quantification analyses. IHC data was quantified by manual counting of positive cells or by using the Aperio Positive Pixel Count Algorithm. Data are presented as mean ± standard deviation (SD). If not stated otherwise in the figure legends, p-values were acquired with the unpaired student’s t-test with Welch’s correction using Graph Pad software (GraphPad Inc, La Jolla, CA). For all experiments in which pancreatic areas were compared, we transformed the data via arcsin transformation (ASIN(SQRT(proportion of abnormal tissue area to total tissue area))*180/PI) before a t-test was performed. p<0.05 was considered statistically significant.

Appendix 1

Appendix 1—key resources table
Reagent type (species) or resourceDesignationSource or referenceIdentifiersAdditional information
Antibodyanti-CD3
(Rabbit polyclonal)
AbcamCat# ab5690, RRID:AB_305055IHC (1:400), IF (1:400)
AntibodyAnti-CD3 (Rat monoclonal)AbcamCat# ab11089, RRID:AB_2889189IF (1:200)
Antibodyanti-CD3 (Rat monoclonal)BioLegendCat# 100222, RRID:AB_2242784FC (0.2 µg/1 × 106 cells)
Antibodyanti-CD4 (Rabbit monoclonal)AbcamCat# ab183685, RRID:AB_2686917IF (1:1000)
Antibodyanti-CD4 (Rat monoclonal)BioLegendCat# 100456, RRID:AB_2565845FC (0.2 µg/1 × 106 cells)
Antibodyanti-CD45 (Rat monoclonal)BioLegendCat# 103137, RRID:AB_2561392FC (0.3 µg/1 × 106 cells)
Antibodyanti-CD45 Microbeads (Rat monoclonal)Miltenyi BiotecCat# 130-052-301, RRID:AB_2877061MACS (10 µL/1 × 107 cells)
Antibodyanti-CD68 (Mouse monoclonal)DAKO/AgilentCat# M0876, RRID:AB_2074844IF (1:100)
Antibodyanti-CD8 alpha (Rabbit monoclonal)AbcamCat# ab209775, RRID:AB_2860566IF (1:500)
Antibodyanti-CD8a (Rat monoclonal)BioLegendCat# 100747, RRID:AB_11219594FC (0.2 µg/1 × 106 cells)
Antibodyanti-CD80 (Armenian hamster monoclonal)BioLegendCat# 104705, RRID:AB_313126FC (1 µg/1 × 106 cells)
Antibodyanti-CXCL10 (Rabbit polyclonal)PeproTechCat# 500-P129bt-50ug, RRID:AB_148105WB (1:2000)
Antibodyanti-CXCR3 (Rabbit polyclonal)LifeSpan BiosciencesCat# LS-C332293, RRID:AB_2891301IF (1:50)
Antibodyanti-CXCR3 (Armenian hamster monoclonal)BD BiosciencesCat# 742274, RRID:AB_2871450FC (0.2 µg/1 × 106 cells)
Antibodyanti-F4/80 (Rat monoclonal)Bio-RadCat# MCA497R, RRID:AB_323279IHC (1:250), IF (1:250)
Antibodyanti-F4/80 (Rat monoclonal)BioLegendCat# 123133, RRID:AB_2562305FC (0.3 µg/1 × 106 cells)
Antibodyanti-F4/80 MicroBeads (Mouse monclonal)Miltenyi BiotecCat# 130-110-443, RRID:AB_2858241MACS (10 µl/1 × 107 cells)
Antibodyanti-GAPDH (Rabbit monoclonal)Cell Signaling TechnologyCat# 5174, RRID:AB_10622025WB (1:1000)
Antibodyanti-iNOS (Rabbit polyclonal)AbcamCat# ab3523, RRID:AB_303872IF (1:200)
Antibodyanti-iNOS (Mouse monoclonal)AbcamCat# ab49999, RRID:AB_881438IF (1:100)
Antibodyanti-NKG2D (Rabbit polyclonal)GeneTexCat# GTX50988, RRID:AB_2891302IF (1:200)
Antibodyanti-SMA (Rabbit polyclonal)AbcamCat# ab5694, RRID:AB_2223021IHC (1:200)
Antibodyanti-pY641-STAT6 (Rabbit monoclonal)Cell Signaling TechnologyCat# 56554, RRID:AB_2799514IF (1:400)
Antibodyanti-pY701-STAT1 (Rabbit monoclonal)Cell Signaling TechnologyCat# 9167, RRID:AB_561284IF (1:400)
Antibodyanti-pY701-STAT1 (Mouse monoclonal)AbcamCat# ab29045, RRID:AB_778096IF (1:200), WB (1:1000)
Antibodyanti-STAT1 (Rabbit polyclonal)Cell Signaling TechnologyCat# 9172, RRID:AB_2198300WB (1:1000)
Antibodyanti-YM1 (Rabbit polyclonal)STEMCELL TechnologiesCat# 60130, RRID:AB_2868482IF (1:200)
Antibodyanti-YM1/2 (Rabbit monoclonal)AbcamCat# ab205491, RRID:AB_2891303FC (1 µg/1 × 106 cells), IF (1:100)
AntibodyCXCL10 neutralizing antibody (NAB; Rat monoclonal)R and D SystemsCat# MAB466, RRID:AB_2292486CXCL10 NAB
AntibodyIsotype control IgG2A antibody (Rat monoclonal)R and D SystemsCat# MAB006, RRID:AB_357349CXCL10 NAB control
AntibodyCXCR3 neutralizing antibody (NAB; Armenian hamster monoclonal)Bio X CellCat# BE0249, RRID:AB_2687730CXCR3 NAB
AntibodyIsotype control IgG antibody (Armenian hamster polyclonal)Bio X CellCat# BE0091, RRID:AB_1107773CXCR3 NAB control
Antibodyanti-CD4 (Rat monoclonal)Bio X CellCat# BP0003-1, RRID:AB_2891358T-cell depletion
Antibodyanti-CD8α (Rat monoclonal)Bio X CellCat# BP0061, RRID:AB_2891359T-cell depletion
AntibodyIsotype control IgG2b antibody (Rat monoclonal)Bio X CellCat# BP0090, RRID:AB_2891360T-cell depletion control
Cell line (Mus musculus)SM3Agbunag et al., 2006; Liou et al., 2017Primary duct-like cells from KC mouse
Chemical compound, drugNVP-BSK805SelleckchemCat# S2686pan-JAK inhibitor
Commercial assay or kitMouse tumor dissociation kitMiltenyi BiotecCat# 130-096-730
Commercial assay or kitRNAscope Assay 2.5 HD Reagent Kit- BrownAdvanced Cell DiagnosticsIn situ hybridization (brown)
Commercial assay or kitRNAscope Multiplex Fluorescent Reagent Kit v2Advanced Cell DiagnosticsIn situ hybridization (fluorescent)
Peptide, recombinant proteinRecombinant murine CXCL10PeprotechCat# 250–16
Peptide, recombinant proteinRecombinant murine IL-4PeprotechCat# 214–14
Peptide, recombinant proteinRecombinant murine IFNɣPeprotechCat# 315–05
Sequence-based reagentArg1TaqMan (Thermo Fisher Scientific)Mm00475988_m1qPCR probe
Sequence-based reagentChil3TaqMan (Thermo Fisher Scientific)Mm00657889_mHqPCR probe
Sequence-based reagentCxcl10TaqMan (Thermo Fisher Scientific)Mm00445235_m1qPCR probe
Sequence-based reagentCxcr3TaqMan (Thermo Fisher Scientific)Mm99999054_s1qPCR probe
Sequence-based reagentIrf4TaqMan (Thermo Fisher Scientific)Mm00516431_m1qPCR probe
Sequence-based reagentIrf5TaqMan (Thermo Fisher Scientific)Mm00496477_m1qPCR probe
Sequence-based reagentGapdhTaqMan (Thermo Fisher Scientific)Mm99999915_g1qPCR probe
Sequence-based reagentRetnlaTaqMan (Thermo Fisher Scientific)Mm0045109_m1qPCR probe
Software, algorithmAperio ImageScopeLeica BiosystemsTissue analysis
Software, algorithmAperio ImageScope Positive Pixel AlgorithmLeica BiosystemsTissue analysis
Software, algorithmFlowJoBD BiosciencesFlow cytometry analysis
Software, algorithmGraphPadGraphPad, IncStatistical analysis
OtherAperio AT2 Digital ScannerLeica BiosystemsBrightfield tissue scans
OtherAperio FL Slide ScannerLeica BiosystemsFluorescent tissue scans
OtherPannoramic 250 Flash III3DHISTECHFluorescent tissue scans
OtherAttune NxT Flow CytometerThermo Fisher Scientific
OtherCxcl10 ISH probe (mouse)Advanced Cell DiagnosticsCat# 408921In situ hybridization probe
OtherCxcr3 ISH probe (mouse)Advanced Cell DiagnosticsCat# 402511In situ hybridization probe
OtherCxcr3 ISH probe (human)Advanced Cell DiagnosticsCat#539251In situ hybridization probe
OtherIfng ISH probe (mouse)Advanced Cell DiagnosticsCat# 311391In situ hybridization probe
OtherLipopolysaccharides (LPS)Sigma-AldrichCat# L4391Lipopolysaccharides from Escherichia coli O111:B4; γ-irradiated; suitable for cell culture
OtherAdeno-Cre-GFPVector BiolabsCat# 1700Adenovirus
OtherAdeno-Null-GFPVector BiolabsCat# 1300Adenovirus
OtherCXCL10GeneCopoeiaLPP-EGFP-Lv105-025-CLentiviral particles
OthereGFP (control)GeneCopoeiaLPP-Mm03214-Lv105-100Lentiviral particles
OtherProteome Profiler Mouse Cytokine Array KitR and D SystemsCat# ARY006Cytokine array

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 Figure supplements.

References

    1. Li K
    2. Zhu Z
    3. Luo J
    4. Fang J
    5. Zhou H
    6. Hu M
    7. Maskey N
    8. Yang G
    (2015)
    Impact of chemokine receptor CXCR3 on tumor-infiltrating lymphocyte recruitment associated with favorable prognosis in advanced gastric Cancer
    International Journal of Clinical and Experimental Pathology 8:14725–14732.

Decision letter

  1. Matthew G Vander Heiden
    Reviewing Editor; Massachusetts Institute of Technology, United States
  2. Tadatsugu Taniguchi
    Senior Editor; Institute of Industrial Science, The University of Tokyo, Japan
  3. Mara Sherman
    Reviewer; Oregon Health & Science University, United States

In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.

Acceptance summary:

This manuscript reports a role for the CXCL10/CXCR3 signaling axis in pancreatic preneoplastic lesions in promoting inflammatory macrophages phenotypes. The authors provide data to support a causal role of CXCL10 and CXCR3 in the recruitment and polarization of macrophages in the pancreas, as well as the degree of fibrosis in PanIN lesions. The work provides insight into mechanisms that affect tumor formation.

Decision letter after peer review:

Thank you for submitting your article "CXCL10/CXCR3 contributes to an inflammatory microenvironment and its blockade enhances pancreatic cancer development" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Tadatsugu Taniguchi as the Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Mara Sherman (Reviewer #3).

The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

This manuscript reports a role for the CXCL10/CXCR3 signaling axis in pancreatic preneoplastic lesions in promoting inflammatory macrophages phenotypes. The authors provide data to support a causal role of CXCL10 and CXCR3 in the recruitment and polarization of macrophages in the pancreas, as well as the degree of fibrosis in PanIN lesions. The work provides potential insight into mechanisms that affect tumor formation.

All reviewers agreed that the data were interesting and potentially appropriate for publication in eLife. With that said, the reviewers were also in agreement that some conclusions were overstated, and the data presentation needs to be improved included more attention to controls and statistical analysis. I have included all comments from the reviewers, however when submitted a revised manuscript it is essential to address the following points:

1. Please clarify the statistical methods used and provide information on replicates for all data.

2. The reviewers all agreed that the CXCL10 data comprises the core of the findings, but though those findings could be strengthened with further experiments. The current eLife policy also allows limiting the claims if new experiments are not possible. Specifically, to support the claim that CXCL10/CXCR3 blockade enhances cancer development, one suggested additional experiment is to evaluate tumor formation in KC mice upon longer treatment with CXCR3 Nab. However, this experiment would take a long time and thus may not be feasible. In the absence of further support that CXCL10/CXCR3 blockade enhances cancer development, and alternative would be to focus your conclusions on the role of CXCL10 in promoting an inflammatory macrophage identity. This latter option likely would include adjusting the title of the manuscript which refers to a role in tumor development.

3. Please address the questions raised by reviewers around the source of the macrophages as this speaks to the central claims of the study.

4. Address overstatements suggested by the reviewers.

5. Some reviewers questioned how much the IRF4/5 data added to the paper? One possibility is to focus entirely on the role of CXCL10 in promoting an inflammatory macrophage identity, others thought this was interesting but perhaps is better included as supplementary data.Reviewer #1 (Recommendations for the authors):

General assessment of the work:

Overall, the manuscript addresses one piece of a major question in the pancreatic cancer field – how the inflammatory microenvironment of these tumors is sculpted through paracrine signaling pathways. In general, while the data reported are supportive of their conclusions, in most cases alternative explanations were not ruled out. This could be addressed with additional experiments. In particular, the question of the initial trigger for the CXCL10/CXCR3 pathway did not exclude other explanations and this was a major component of the story. In addition, there were a number of technical concerns and questions that limit our ability to interpret the data. These could be remedied in a resubmission but require careful attention to detail.

Substantive concerns:

1. Utilized ISH data as proof for protein expression. While necessary in order to identify which cell synthesize secreted proteins like CXCL10, it would be informative to see paired protein staining or Western blots for those experiments that don't already include them, as mRNA expression isn't always indicative of protein expression/levels.

2. In figure 1, the authors conclude that IFNγ is responsible for activation fo CXCL10 expression. Treatment with IFNγ did induce CXCL10, but this only proves that the pathway is sufficient and does not address whether it is necessary. To learn this, one could use an anti-IFNγ antibody and see if this blocks CXCL10 activation. Otherwise, the conclusions drawn from this experiment should be stated in a more constrained manner.

3. Similarly, the conclusions drawn regarding T cell and NK cell involvement in the CXCL10/CXCR3 pathway are not fully supported.

– The combined ISH/IF experiment in Figure 1G is an elegant technical approach to studying the source-cell of a secreted protein. However, not a single control was presented for this experiment, making it impossible to interpret these results.

– Presence of T cells and NK cells in the area around precursor cells, and the knowledge that T cells and NK cells express IFNγ is not sufficient to conclude that T cells and NK cells are responsible for initiation of CXCL10 expression. It is a potential explanation, but no work was done to rule out other unknown factors.

– Additionally, when done in a T cell free environment, the pathway still functioned and the authors themselves claim that there is "no significant role of T cells in CXCL10/CXCR3 driven development of pancreatic cancer." IFNγ from T cells cannot be both the initial driver and also not significant.

4. In Figure 2B, was the migration assay performed on M2 macrophages? One would expect them not to be responsive based on 2A, but this should be examined.

5. The conclusion that macrophage polarization occurred through the IRF4/5 transition is not sufficiently supported. It is not clear that the reported observation should even be included is it is not integral to the overall message of the paper.

6. Please provide a statistical analysis of the data in 4G, particularly with regard to the incidence of higher grade lesions. Given the variance in the extent of PanIN lesions that present in the KC model, it is generally necessary to analyze far more than 4 animals per group to assess impact on this type of phenotype.

7. In general, for many experiments it was not clear how many replicates were performed and whether these were technical or biological replicates. It is important that this be stated the legend for each panel in each figure, otherwise it is impossible to provide an informed analysis of the data.

8. Related to the prior point, the data representation in most figures utilized outdated approaches (eg. bar plots) that communicate a minimum amount of information about distribution, variance, and replicates. We strongly recommend the adoption of more modern, informative data display conventions, such as those described in PMID: 32346721.

9. Additionally, it is important to indicate which statistical test was utilized in each figure. The blanket statement in the Methods that Student's T was used is not sufficient as this is not always the appropriate test. For example, in Figure 4B, the authors present normalized ratiometric data (% positive area). A Student's T is not an appropriate test for this comparison because ratiometric data violate the assumption of a normal distribution required by this test. We strongly suggest the authors review every experiment with a biostatistician.

Reviewer #2 (Recommendations for the authors):

CXCL10/CXCR3 contributes to an inflammatory microenvironment and its blockade enhances pancreatic cancer development

In this manuscript, Pandey et al., reports a novel CXCL10/CXCR3 signaling axis between pancreatic preneoplastic lesions and inflammatory macrophages to shape the microenvironment of PanIN. The authors provide strong in vivo experimental data to support a causal role of CXCL10 and CXCR3 in the recruitment and polarization of macrophages in the pancreas, as well as the degree of fibrosis in PanIN lesions. Addressing the following concerns will further strengthen the manuscript:

1. CXCL10 has previously been reported to be the major chemokine produced by pancreatic stellate cells (PSCs) in the PDA tumor microenvironment. CAFs expressing IP10 are thought to recruit Tregs to promote immune evasion and tumorigenesis. CXCL10 levels have also been shown to positively correlate with stromal content in human PDAC (PMID25415223). In the current manuscript, the authors report a very robust increase in fibrosis in PanIN (using SMA as a marker) when the CXCL10/CXCR3 axis is supressed using neutralizing antibodies. This raises the interesting question of whether CXCL10 exhibit opposite functions during premalignant vs malignant stages of tumorigenesis. This can be addressed using a syngeneic orthotopic model of PDA to evaluate the effect of CXCL10/CXCR3 inhibition in established tumors. Alternatively, the authors may consider revising the title of their manuscript to focus on the effect of CXCL10/CXCR3 in preneoplastic lesions as opposed to pancreatic cancer. CXCR3 Nab did not lead to a significant change in % of PanIN or ADM in mice (Figure 4G) so it is hard to extrapolate from the current data what the role of this signaling axis is in the context of cancer unless additional data is provided beyond the current timepoints to evaluate tumorigenesis.

2. What is the spatial relationship between interferon-γ-producing T cells and PanIN lesions? A multiplex FISH of CXCL10 and IFNγ will strengthen the model that short-distance-acting IFNγ from T cells within the pancreatic parenchyma induces CXCL10 production in neighbouring acinar/ADM cells. Along the same lines, what is the percentage of T cells in PanIN and ADM-bearing pancreata?

3. Tumor associated macrophages are generally thought to originate from circulating monocytes derived from bone marrow HSCs. While thioglycollate activated peritoneal macrophages is a tractable experimental model, they are phenotypically very different from non-elicited, resident peritoneal macrophages, or naïve bone marrow derived macrophages, and as such do not serve as a proper control for "non-polarized" macrophages. Experiments presented in Figure 2A and B should also be done using naïve (M0) and M1 , M2 macrophages derived from the bone marrow. Experimental evidence showing that CXCR3-expressing macrophages in the pancreas originated from the peritoneum is currently absent, the authors should therefore refrain from drawing conclusions on the origin of these macrophages.

4. The authors should extend their characterization of the effect of CXCR3 in fibrosis by using pan-CAF markers (eg podoplanin) and markers for other CAF populations eg inflammatory CAFs (iCAFs). Is collagen deposition also increased upon CXCR3 inhibition?

Reviewer #3 (Recommendations for the authors):

In this manuscript by Pandey and colleagues, the authors investigate regulation of macrophage phenotype during pancreatic cancer initiation. While prior studies have demonstrated significant pro- and anti-tumorigenic roles for macrophages during pancreatic tumorigenesis, mechanistic insights are mostly limited to those promoting pro-tumorigenic macrophage phenotypes, with little known about heterocellular interactions that promote a potentially tumoricidal or tumor-suppressive macrophage state. The data presented here support the novel hypothesis that a CXCL10-CXCR3 axis promotes an inflammatory macrophage identity and suppresses tumor initiation. The work is significant in providing insights into tissue homeostatic mechanisms that limit tumor formation. However, the authors' claims that peritoneal macrophages are the relevant macrophage pool for the phenotypes reported and that CXCL10-CXCR3 signaling controls inflammatory macrophage abundance via chemoattraction are not convincingly supported by the results in the manuscript. A limited number of edits and additional analyses would be helpful in clarifying the authors' findings.

Specific comments:

1. While the authors convincingly demonstrate that the CXCL10/CXCR3 axis regulates macrophage phenotype in vitro and in vivo, the significance of chemoattraction for the reported phenotypes is not clear. Tissue-resident macrophages express CXCR3 and are known to play significant roles in pancreatic tumor progression, proliferate in situ during tumor progression, and contribute to fibrosis, consistent with a phenotypic switch in these tissue-resident cells upon CXCL10-CXCR3 inhibition as the underlying mechanism as opposed to recruitment of peritoneal macrophages. Either the chemoattraction and recruitment model should be addressed experimentally in vivo, or text should be edited to accommodate this alternative model.

2. Total F4/80+ cells should be quantified in the genetically engineered KC model treated with CXCR3 NAB (results in Figure 3D) to address the impact of the CXCL10/CXCR3 axis on total macrophage abundance in these tissues and assess, in the presence of a functional immune system, whether macrophage phenotype alone is altered or if total abundance is also impacted by CXCL10-CXCR3 inhibition.

3. Several key references are absent from the introduction and should be added and briefly discussed in the context of this study, including prior studies of CXCL10 in PDAC (Hirth, Kuner et al., Gastroenterology, 2020; Romero, Gallinger et al., Clinical Cancer Research, 2020) and of macrophages/macrophage heterogeneity in pancreatic tumor initiation (Zhang, Pasca di Magliano et al., Gut, 2017; Zhu, DeNardo et al., Immunity, 2017).

https://doi.org/10.7554/eLife.60646.sa1

Author response

1. Please clarify the statistical methods used and provide information on replicates for all data.

In the revised version of our manuscript we have revised the paragraph on Quantification and Statistical Analysis in the Experimental Procedures section to provide more detailed information. In addition to this, in each figure legend, we now provide information on replicates, statistical analyses and p-value.

2. The reviewers all agreed that the CXCL10 data comprises the core of the findings, but though those findings could be strengthened with further experiments. The current eLife policy also allows limiting the claims if new experiments are not possible. Specifically, to support the claim that CXCL10/CXCR3 blockade enhances cancer development, one suggested additional experiment is to evaluate tumor formation in KC mice upon longer treatment with CXCR3 Nab. However, this experiment would take a long time and thus may not be feasible. In the absence of further support that CXCL10/CXCR3 blockade enhances cancer development, and alternative would be to focus your conclusions on the role of CXCL10 in promoting an inflammatory macrophage identity. This latter option likely would include adjusting the title of the manuscript which refers to a role in tumor development.

One reviewer suggested an additional experiment to evaluate tumor formation in KC mice upon longer treatment with a CXCR3-NAB. Although we agree with the reviewer that this would be an interesting experiment, we feel that conducting this experiment would take a long time and require excessive resources (large quantities of CXCR3 NAB) and thus is not feasible at this point. Instead, as suggested by the editors, we now focus our conclusions on the role of CXCL10/CXCR3 signaling in promoting an inflammatory macrophage identity and promoting occurrence of precancerous low-grade lesions. We also adjusted the title of the manuscript, which now reads:

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

3. Please address the questions raised by reviewers around the source of the macrophages as this speaks to the central claims of the study.

We agree with the editors and reviewers that this is an important question, with tissue resident macrophages, bone marrow-derived macrophages or peritoneal macrophages as potential responders to CXCL10.

With respect to early events leading to development of PDA, the influx of macrophages into the pancreas has been demonstrated following injury and during development and progression of pancreatic lesions [1,2]. Moreover, CXCL10 has been demonstrated as a chemoattractant for macrophages along with other immune cells [3]. Transwell invasion assays using both peritoneal and bone marrow-derived macrophages (M0, M1, M2) suggest that CXCL10 can act as a chemoattractant for M1-polarized macrophages (Figure 2B; Figure 2—figure supplement 1A).

However, since tissue resident macrophages have been attributed important roles in established pancreatic cancer (Zhu et al., 2017), we also determined if this population can be the recipients for CXCL10. Approximately 80% of tissue resident macrophages in normal mouse pancreas express CXCR3 (Figure 2—figure supplement 1B), but these cells when isolated do not proliferate in response to CXCL10 (Figure 2-figure supplement 1C). In sum, our in vitro data suggests that CXCL10 may drive the chemoattraction of inflammatory macrophages to the pancreas.

References for this response:

1. Gea-Sorli, S. and D. Closa, in vitro, but not in vivo, reversibility of peritoneal macrophages activation during experimental acute pancreatitis. BMC Immunol, 2009. 10: p. 42.

2. Liou, G.Y., et al., Mutant KRAS-induced expression of ICAM-1 in pancreatic acinar cells causes attraction of macrophages to expedite the formation of precancerous lesions. Cancer Discov, 2015. (1): p. 52-63.

3. Liu, M., S. Guo, and J.K. Stiles, The emerging role of CXCL10 in cancer (Review). Oncol Lett, 2011. 2(4): p. 583-589.

4. Address overstatements suggested by the reviewers.

We addressed all these points in the revised version of our manuscript (see responses to each reviewer below).

5. Some reviewers questioned how much the IRF4/5 data added to the paper? One possibility is to focus entirely on the role of CXCL10 in promoting an inflammatory macrophage identity, others thought this was interesting but perhaps is better included as supplementary data.

The data on IRF4/5 is based on previous published work in which it was shown that the balance between these two transcription factors determines if macrophages are M1 or M2 polarized [1, 2]. M2 macrophages mainly express IRF4, which is a key factor for their polarization phenotype [3]. Depletion of IRF4 in M2 macrophages results in a polarization change towards M1 macrophages [1]. Therefore, we feel, that the CXCR3-induced changes in IRF4 and IRF5 expression in M1 macrophages are a valid explanation for their change towards M2 polarization. But we also agree with the reviewers (and the editors) that this data is better included in the Supplemental Data (now Figure 3—figure supplement 1F).

References for this response:

1. Bastea, L.I., et al., Pomalidomide Alters Pancreatic Macrophage Populations to Generate an Immune-Responsive Environment at Precancerous and Cancerous Lesions. Cancer Res, 2019. 79(7): p. 1535-1548.

2. Gunthner, R. and H.J. Anders, Interferon-regulatory factors determine macrophage phenotype polarization. Mediators Inflamm, 2013. 2013: p. 731023.

3. Satoh, T., et al., The Jmjd3-Irf4 axis regulates M2 macrophage polarization and host responses against helminth infection. Nat Immunol, 2010. 11(10): p. 936-44.

Reviewer #1 (Recommendations for the authors):

General assessment of the work:

Overall, the manuscript addresses one piece of a major question in the pancreatic cancer field – how the inflammatory microenvironment of these tumors is sculpted through paracrine signaling pathways. In general, while the data reported are supportive of their conclusions, in most cases alternative explanations were not ruled out. This could be addressed with additional experiments. In particular, the question of the initial trigger for the CXCL10/CXCR3 pathway did not exclude other explanations and this was a major component of the story. In addition, there were a number of technical concerns and questions that limit our ability to interpret the data. These could be remedied in a resubmission but require careful attention to detail.

Substantive concerns:

1. Utilized ISH data as proof for protein expression. While necessary in order to identify which cell synthesize secreted proteins like CXCL10, it would be informative to see paired protein staining or Western blots for those experiments that don't already include them, as mRNA expression isn't always indicative of protein expression/levels.

In our opinion ISH is the method of choice to determine the cells that produce proteins that are secreted. In our experience simple IHC analyses does not provide reliable information if the protein of interest is produced by a cell or if it is bound to its target cell. The alternative, to perform Western blot analyses for protein expression from tissue would require precise microdissection, or the analyses of primary cells (i.e. SM3 cells for PanIN1), which are representative of the lesion that is to be analyzed. Whenever possible, we performed such analyses. However, we would like to point out that antibodies used for IHC need to be rigorously tested for non-specific signaling. For detection of IFNγ, for example, the antibodies we have tested for IHC (e.g. Bioss #0480R) failed our test.

2. In figure 1, the authors conclude that IFNγ is responsible for activation fo CXCL10 expression. Treatment with IFNγ did induce CXCL10, but this only proves that the pathway is sufficient and does not address whether it is necessary. To learn this, one could use an anti-IFNγ antibody and see if this blocks CXCL10 activation. Otherwise, the conclusions drawn from this experiment should be stated in a more constrained manner.

We would like to point out that there is a whole body of published work showing that IFNγ can induce CXCL10. CXCL10 is widely known in the literature as the interferon γ-inducible protein 10 (IP-10) and previously has been shown to be induced by IFNγ via activation of signal transducer and activator of transcription 1 (STAT1). Our data confirms this for SM3 PanIN cells. However, as suggested by the reviewer, in the revised version of our manuscript, we state the conclusions drawn from this set of experiments in a more constrained manner in the Results and Discussion sections.

3. Similarly, the conclusions drawn regarding T cell and NK cell involvement in the CXCL10/CXCR3 pathway are not fully supported.

– The combined ISH/IF experiment in Figure 1G is an elegant technical approach to studying the source-cell of a secreted protein. However, not a single control was presented for this experiment.

This experiment has neighboring negative cells included as internal controls. For example, we show CD8+ cells that express IFNγ and neighboring CD8- cells that do not express IFNγ.

– Presence of T cells and NK cells in the area around precursor cells, and the knowledge that T cells and NK cells express IFNγ is not sufficient to conclude that T cells and NK cells are responsible for initiation of CXCL10 expression. It is a potential explanation, but no work was done to rule out other unknown factors.

We absolutely agree with the reviewer on this point and since presence of IFNγ in the pancreatic microenvironment is well established, there may be more cell types besides T cells and NK cells that produce IFNγ. Since the focus of our study was not to delineate/establish all the IFNγ producers in the tumor microenvironment, following the guidance of this reviewer, we have modified the text of our manuscript and suggest that T cells or NK cells could be a potential source of IFNγ in our experimental system. We also changed the model in Figure 5F and added “or other sources in the pancreas microenvironment”.

– Additionally, when done in a T cell free environment, the pathway still functioned and the authors themselves claim that there is "no significant role of T cells in CXCL10/CXCR3 driven development of pancreatic cancer." IFNγ from T cells cannot be both the initial driver and also not significant.

We agree with the reviewer that T cells cannot be both, “the initial driver” and also “not significant” at the same time. In a T cell free environment effects can be explained by presence of other IFNγ producing sells (such as NK cells) in the microenvironment.

4. In Figure 2B, was the migration assay performed on M2 macrophages? One would expect them not to be responsive based on 2A, but this should be examined.

We agree with the reviewer that this is an important control. In the revised manuscript (New Figure 2B) we have included a migration assay performed on M2 macrophages. We found that migration of M2-polarized macrophages is not affected by CXCL10. Since this macrophage population does not express CXCR3 (See Figure 2A) this is an expected result.

5. The conclusion that macrophage polarization occurred through the IRF4/5 transition is not sufficiently supported. It is not clear that the reported observation should even be included is it is not integral to the overall message of the paper.

This is based on previous published work in which it was shown that the balance between these two transcription factors determines if macrophages are M1 or M2 polarized [1, 2]. M2 macrophages express IRF4, which is a key factor for their polarization phenotype [3]. Depletion of IRF4 in M2 macrophages results in a polarization change towards M1 macrophages [1]. Therefore, we feel, that the CXCR3-induced changes in IRF4 and IRF5 expression in M1 macrophages are a valid explanation for their change towards M2 polarization. But we also agree with the reviewer (and the editors) that this data is better included in the Supplemental Data (now Figure 3—figure supplement 1D).

References for this response:

1. Bastea, L.I., et al., Pomalidomide Alters Pancreatic Macrophage Populations to Generate an Immune-Responsive Environment at Precancerous and Cancerous Lesions. Cancer Res, 2019. 79(7): p. 1535-1548.

2. Gunthner, R. and H.J. Anders, Interferon-regulatory factors determine macrophage phenotype polarization. Mediators Inflamm, 2013. 2013: p. 731023.

3. Satoh, T., et al., The Jmjd3-Irf4 axis regulates M2 macrophage polarization and host responses against helminth infection. Nat Immunol, 2010. 11(10): p. 936-44.

6. Please provide a statistical analysis of the data in 4G, particularly with regard to the incidence of higher grade lesions. Given the variance in the extent of PanIN lesions that present in the KC model, it is generally necessary to analyze far more than 4 animals per group to assess impact on this type of phenotype.

We absolutely agree with the reviewer that to obtain significant data on progression towards tumors when CXCR3 is neutralized would need not only more mice per experimental group, but also additional animal experiments where treatment occurs over a longer time span. We feel that this is beyond the scope of our manuscript. Therefore, we have removed the following paragraph from page 11:

“However, we found very few PanIN2 and PanIN3 lesions in mice treated with CXCR3 NAB (Figure 4G), but not in mice that were control treated. Although this has to be rigorously tested in futures studies, the occurrence of these high-grade lesions indicates that CXCL10/CXCR3 signaling may act protective for low grade lesions, and when neutralized may promote the formation of pancreatic cancer”.

We also changed Figure 4G and summarized further progressed lesions as “other”.

7. In general, for many experiments it was not clear how many replicates were performed and whether these were technical or biological replicates. It is important that this be stated the legend for each panel in each figure, otherwise it is impossible to provide an informed analysis of the data.

We absolutely agree with the reviewer that this information is essential for data analysis. All replicates mentioned in the manuscript refer to biological replicates. In the revision of our manuscript, this is clearly stated for each figure in the figure legend.

8. Related to the prior point, the data representation in most figures utilized outdated approaches (eg. bar plots) that communicate a minimum amount of information about distribution, variance, and replicates. We strongly recommend the adoption of more modern, informative data display conventions, such as those described in PMID: 32346721.

We thank the reviewer for this excellent point. in the current revision, we re-plotted all the bar plots and now provide 38 updated plots that communicate information about distribution, variance, and replicates.

9. Additionally, it is important to indicate which statistical test was utilized in each figure. The blanket statement in the Methods that Student's T was used is not sufficient as this is not always the appropriate test. For example, in Figure 4B, the authors present normalized ratiometric data (% positive area). A Student's T is not an appropriate test for this comparison because ratiometric data violate the assumption of a normal distribution required by this test. We strongly suggest the authors review every experiment with a biostatistician.

We absolutely agree with the reviewer and have worked with our biostatistician Dr. Yan Asmann (Associate Professor of BioMedical Informatics, Mayo Clinic) on the statistical analyses of all experiments. For example, for all experiments in which pancreatic areas were compared (previous Figures 4F and 5B), since % values are not normally distributed, we transformed the data via arcsin transformation before a t-test was performed. The statistical analysis used for each subfigure is now included in the revised figure legends.

Reviewer #2 (Recommendations for the authors):

CXCL10/CXCR3 contributes to an inflammatory microenvironment and its blockade enhances pancreatic cancer development

In this manuscript, Pandey et al., reports a novel CXCL10/CXCR3 signaling axis between pancreatic preneoplastic lesions and inflammatory macrophages to shape the microenvironment of PanIN. The authors provide strong in vivo experimental data to support a causal role of CXCL10 and CXCR3 in the recruitment and polarization of macrophages in the pancreas, as well as the degree of fibrosis in PanIN lesions. Addressing the following concerns will further strengthen the manuscript:

1. CXCL10 has previously been reported to be the major chemokine produced by pancreatic stellate cells (PSCs) in the PDA tumor microenvironment. CAFs expressing IP10 are thought to recruit Tregs to promote immune evasion and tumorigenesis. CXCL10 levels have also been shown to positively correlate with stromal content in human PDAC (PMID25415223). In the current manuscript, the authors report a very robust increase in fibrosis in PanIN (using SMA as a marker) when the CXCL10/CXCR3 axis is supressed using neutralizing antibodies. This raises the interesting question of whether CXCL10 exhibit opposite functions during premalignant vs malignant stages of tumorigenesis. This can be addressed using a syngeneic orthotopic model of PDA to evaluate the effect of CXCL10/CXCR3 inhibition in established tumors. Alternatively, the authors may consider revising the title of their manuscript to focus on the effect of CXCL10/CXCR3 in preneoplastic lesions as opposed to pancreatic cancer. CXCR3 Nab did not lead to a significant change in % of PanIN or ADM in mice (Figure 4G) so it is hard to extrapolate from the current data what the role of this signaling axis is in the context of cancer unless additional data is provided beyond the current timepoints to evaluate tumorigenesis.

We agree with the reviewer that investigating whether CXCL10 exhibits opposite functions during premalignant versus malignant stages of tumorigenesis is an exciting question. However, we feel that animal experiments to address this question rigorously are beyond the scope of the current manuscript. Therefore, we followed the reviewer’s suggestion and revised the title of our manuscript to focus on the effect of CXCL10/CXCR3 in preneoplastic lesions as opposed to pancreatic cancer. The new title is:

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

In the revised manuscript we also addressed the possible opposite functions of CXCL10 in pre-malignant versus malignant stages in the last paragraph of the Discussion section on page 17. It reads:

“Considering our results, use of agonists for the receptor CXCR3 at stages of low-grade lesions may be useful to modulate macrophage polarization in the microenvironment such that a predominantly inflammatory population (M1) can be sustained. However, it needs to be noted that in pancreatic cancer expression of both CXCL10 and CXCR3 in tumor tissue has been correlated with poor prognosis (Liu et al., 2011; Lunardi et al., 2014). Therefore, it is unclear if treatment of pancreatic tumors with a CXCR3 agonist will result in a polarization switch of tumor associated macrophages that renders the lesion microenvironment less supportive for tumors, and increases efficiency of chemotherapy, or if it has a tumor promoting effect. This will be addressed in future studies”

2. What is the spatial relationship between interferon-γ-producing T cells and PanIN lesions? A multiplex FISH of CXCL10 and IFNγ will strengthen the model that short-distance-acting IFNγ from T cells within the pancreatic parenchyma induces CXCL10 production in neighbouring acinar/ADM cells. Along the same lines, what is the percentage of T cells in PanIN and ADM-bearing pancreata?

We agree with the reviewer that quantifying the T cell populations that produce IFNγ at ADM or PanIN lesions, as well as measuring their spatial proximity to these lesions is interesting, but we feel that this does not really belong into the current manuscript and requires a thorough analysis, which will be a separate project. However, we would like to point out the following to answer above reviewer questions: Multiple cell types within the pancreatic microenvironment, including T cells and NK cells, have been shown to secrete IFNγ [1-3]; and in Figure 1G we show that all of these are present and produce IFNγ. With respect to T cells, we (and others) previously have shown that they occur in proximity to ADM/PanIN areas in the KC model. For example, in Liou et al., Cell Reports, 2017 [4], we show in Supplemental Figure S3A that CD3- and CD4-positive cells are present in ADM/PanIN areas. Similarly, in Liou et al., Cancer Discovery, 2015 [5], we show in Supplemental Figure S1B, panel B7, that CD3-positive cells are present in ADM/PanIN areas. Moreover, in a more recent paper from Bastea et al., Cancer Research, 2019 [6], in Figures 6H and 6I we demonstrate the presence of CD3+;CD4+;IFNγ+ and CD3+;CD8+;IFNγ+ T cell populations in the pancreas of KC mice. An additional analysis of this data suggests that the percentage for CD3+;CD4+;IFNγ+ cells in ADM/PanIN bearing pancerata (n=3) is approximately 0.33% -/+ 0.28% of all cells and for CD3+;CD8+;IFNγ+ cells in ADM/PanIN bearing pancreata (n=3) is approximately 0.02% -/+ 0.02% of all cells.

References for this response:

1. Brauner, H., et al., Distinct phenotype and function of NK cells in the pancreas of nonobese diabetic mice. J Immunol, 2010. 184(5): p. 2272-80.

2. Castro, F., et al., Interferon-Γ at the Crossroads of Tumor Immune Surveillance or Evasion. Front Immunol, 2018. 9: p. 847.

3. Corthay, A., et al., Primary antitumor immune response mediated by CD4+ T cells. Immunity, 2005. 22(3): p. 371-83.

4. Liou, G.Y., et al., The Presence of Interleukin-13 at Pancreatic ADM/PanIN Lesions Alters Macrophage Populations and Mediates Pancreatic Tumorigenesis. Cell Rep, 2017. 19(7): p. 1322-1333.

5. Liou, G.Y., et al., Mutant KRAS-induced expression of ICAM-1 in pancreatic acinar cells causes attraction of macrophages to expedite the formation of precancerous lesions. Cancer Discov, 2015. 5(1): p. 52-63.

6. Bastea, L.I., et al., Pomalidomide Alters Pancreatic Macrophage Populations to Generate an Immune-Responsive Environment at Precancerous and Cancerous Lesions. Cancer Res, 2019. 79(7): p. 1535-1548.

3. Tumor associated macrophages are generally thought to originate from circulating monocytes derived from bone marrow HSCs. While thioglycollate activated peritoneal macrophages is a tractable experimental model, they are phenotypically very different from non-elicited, resident peritoneal macrophages, or naïve bone marrow derived macrophages, and as such do not serve as a proper control for "non-polarized" macrophages. Experiments presented in Figure 2A and B should also be done using naïve (M0) and M1 , M2 macrophages derived from the bone marrow. Experimental evidence showing that CXCR3-expressing macrophages in the pancreas originated from the peritoneum is currently absent, the authors should therefore refrain from drawing conclusions on the origin of these macrophages.

This is an excellent point. For the revised version of our manuscript we performed additional experiments using naïve and M1-polarized or M2-polarized macrophages derived from the bone marrow, and obtained data (shown in New Figure 2—figure supplement 1A) consistent with previous data obtained with polarized peritoneal macrophages. We also agree that there is no experimental evidence of the origin of the chemoattracted macrophages and made appropriate changes throughout the text to refrain from implicating that they originate in the peritoneum.

4. The authors should extend their characterization of the effect of CXCR3 in fibrosis by using pan-CAF markers (eg podoplanin) and markers for other CAF populations eg inflammatory CAFs (iCAFs). Is collagen deposition also increased upon CXCR3 inhibition?

We agree with the reviewer that determining effects on different CAF populations will be an interesting question. However, the major point in our manuscript (Figure 4) is to determine the effects of CXCR3 signaling on alternatively-activated (M2) macrophage populations. We have included an analysis of SMA+ fibroblasts (see Figures 4A and 4B) because we previously have shown that in the KC model M2 macrophages (marked by expression of Ym1) regulate this population, and a depletion of M2 macrophages decreases fibrosis as measured by staining for SMA [1]. This is why we used IHC for SMA as readout for fibrosis affected by the M2 macrophage population. A detailed analysis of effects of CXCR3 signaling on different CAF populations is clearly beyond the scope of the current study since there are no single markers for these populations described. Such analyses need co-staining for several markers (i.e. IF-IHC for podoplanin and SMA; or IHC for podoplanin combined with ISH for CXCL12) to distinguish myCAFs from non-myCAFs or to determine changes in iCAFs by analyzing CD45-/Ly6c+ population changes. We feel that this is a project by itself and will be addressed in future studies.

References for this response:

1. Liou, G.Y., et al., The Presence of Interleukin-13 at Pancreatic ADM/PanIN Lesions Alters Macrophage Populations and Mediates Pancreatic Tumorigenesis. Cell Rep, 2017. 19(7): p. 1322-1333.

Reviewer #3 (Recommendations for the authors):

In this manuscript by Pandey and colleagues, the authors investigate regulation of macrophage phenotype during pancreatic cancer initiation. While prior studies have demonstrated significant pro- and anti-tumorigenic roles for macrophages during pancreatic tumorigenesis, mechanistic insights are mostly limited to those promoting pro-tumorigenic macrophage phenotypes, with little known about heterocellular interactions that promote a potentially tumoricidal or tumor-suppressive macrophage state. The data presented here support the novel hypothesis that a CXCL10-CXCR3 axis promotes an inflammatory macrophage identity and suppresses tumor initiation. The work is significant in providing insights into tissue homeostatic mechanisms that limit tumor formation. However, the authors' claims that peritoneal macrophages are the relevant macrophage pool for the phenotypes reported and that CXCL10-CXCR3 signaling controls inflammatory macrophage abundance via chemoattraction are not convincingly supported by the results in the manuscript. A limited number of edits and additional analyses would be helpful in clarifying the authors' findings.

Specific comments:

1. While the authors convincingly demonstrate that the CXCL10/CXCR3 axis regulates macrophage phenotype in vitro and in vivo, the significance of chemoattraction for the reported phenotypes is not clear. Tissue-resident macrophages express CXCR3 and are known to play significant roles in pancreatic tumor progression, proliferate in situ during tumor progression, and contribute to fibrosis, consistent with a phenotypic switch in these tissue-resident cells upon CXCL10-CXCR3 inhibition as the underlying mechanism as opposed to recruitment of peritoneal macrophages. Either the chemoattraction and recruitment model should be addressed experimentally in vivo, or text should be edited to accommodate this alternative model.

In normal pancreata of 7-8 weeks old mice we detect only very few tissue resident macrophages, with an average of 5.51 -/+ 4.06 macrophages per mm2. Of those approximately 80% were also CXCR3+ (New Figure 2—figure supplement 1B). However, tissue resident macrophages after isolation and stimulation with CXCL10 did not show altered proliferation (New Figure 2—figure supplement 1C).

For the KC model, we feel that we have shown in previous papers that inflammatory macrophages can be attracted to the pancreas and contribute to development of early lesions (e.g. Liou et al., Cancer Discovery, 2015; [1]). However, we also agree with the reviewers that it is unclear if these originate from the bone marrow or the peritoneum. Here, for CXCL10, we show that it attracts both BMD and peritoneal macrophages (Figure 2B and New Figure 2—figure supplement 1A).

In the revised version of our manuscript, we follow the reviewer’s guidance and have edited the text to discuss the potential source of macrophages in more detail. The new text is included on pages 7/8 and reads: “Transwell invasion assays using both, peritoneal and bone marrow-derived macrophages suggest that CXCL10 can act as a chemoattractant for M1-polarized macrophages (Figure 2B; Figure 2—figure supplement 1A). However, since tissue resident macrophages have been attributed important roles in established pancreatic cancer (Zhu et al., 2017), we also determined if this population can be the recipients for CXCL10. Approximately 80% of tissue resident macrophages in normal mouse pancreas express CXCR3 (Figure 2—figure supplement 1A), but these cells, when isolated do not proliferate in response to CXCL10 (Figure 2—figure supplement 1B). In sum our in vitro data suggests that CXCL10 may drive the chemoattraction of inflammatory macrophages to the pancreas”.

References for this response:

1. Liou, G.Y., et al., Mutant KRAS-induced expression of ICAM-1 in pancreatic acinar cells causes attraction of macrophages to expedite the formation of precancerous lesions. Cancer Discov, 2015. 5(1): p. 52-63.

2. Total F4/80+ cells should be quantified in the genetically engineered KC model treated with CXCR3 NAB (results in Figure 3D) to address the impact of the CXCL10/CXCR3 axis on total macrophage abundance in these tissues and assess, in the presence of a functional immune system, whether macrophage phenotype alone is altered or if total abundance is also impacted by CXCL10-CXCR3 inhibition.

This is an excellent point and we have included a quantification of total F4/80+ cells in the New Figure 3—figure supplement 1F.

3. Several key references are absent from the introduction and should be added and briefly discussed in the context of this study, including prior studies of CXCL10 in PDAC (Hirth, Kuner et al., Gastroenterology, 2020; Romero, Gallinger et al., Clinical Cancer Research, 2020) and of macrophages/macrophage heterogeneity in pancreatic tumor initiation (Zhang, Pasca di Magliano et al., Gut, 2017; Zhu, DeNardo et al., Immunity, 2017).

We thank the reviewer for pointing out these references and apologize for having missed them in our initial manuscript. In our revision these publications are now included.

https://doi.org/10.7554/eLife.60646.sa2

Article and author information

Author details

  1. Veethika Pandey

    Department of Cancer Biology, Mayo Clinic Comprehensive Cancer Center, Mayo Clinic, Jacksonville, United States
    Contribution
    Conceptualization, Data curation, Formal analysis, Validation, Visualization, Writing - original draft, Writing - review and editing
    Competing interests
    No competing interests declared
  2. Alicia Fleming-Martinez

    Department of Cancer Biology, Mayo Clinic Comprehensive Cancer Center, Mayo Clinic, Jacksonville, United States
    Contribution
    Data curation, Formal analysis, Validation, Investigation, Methodology, Writing - review and editing
    Competing interests
    No competing interests declared
  3. Ligia Bastea

    Department of Cancer Biology, Mayo Clinic Comprehensive Cancer Center, Mayo Clinic, Jacksonville, United States
    Contribution
    Data curation, Formal analysis, Validation, Investigation, Writing - review and editing
    Competing interests
    No competing interests declared
  4. Heike R Doeppler

    Department of Cancer Biology, Mayo Clinic Comprehensive Cancer Center, Mayo Clinic, Jacksonville, United States
    Contribution
    Data curation, Formal analysis, Validation, Investigation
    Competing interests
    No competing interests declared
  5. Jillian Eisenhauer

    Department of Cancer Biology, Mayo Clinic Comprehensive Cancer Center, Mayo Clinic, Jacksonville, United States
    Contribution
    Data curation, Formal analysis
    Competing interests
    No competing interests declared
  6. Tam Le

    Department of Cancer Biology, Mayo Clinic Comprehensive Cancer Center, Mayo Clinic, Jacksonville, United States
    Contribution
    Data curation
    Competing interests
    No competing interests declared
  7. Brandy Edenfield

    Department of Cancer Biology, Mayo Clinic Comprehensive Cancer Center, Mayo Clinic, Jacksonville, United States
    Contribution
    Data curation, Visualization
    Competing interests
    No competing interests declared
  8. Peter Storz

    Department of Cancer Biology, Mayo Clinic Comprehensive Cancer Center, Mayo Clinic, Jacksonville, United States
    Contribution
    Conceptualization, Resources, Funding acquisition, Validation, Investigation, Writing - original draft, Project administration, Writing - review and editing
    For correspondence
    storz.peter@mayo.edu
    Competing interests
    No competing interests declared
    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.

Acknowledgements

We thank Dr. Yan Asmann (Associate Professor of BioMedical Informatics, Mayo Clinic) for advice on the statistical analyses. We also thank our colleagues in the Storz laboratory and Department for Cancer Biology for helpful discussions. We also thank the Champions For Hope (Funk-Zitiello Foundation) and Gary Chartrand Foundation for their continuous support.

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.

Senior Editor

  1. Tadatsugu Taniguchi, Institute of Industrial Science, The University of Tokyo, Japan

Reviewing Editor

  1. Matthew G Vander Heiden, Massachusetts Institute of Technology, United States

Reviewer

  1. Mara Sherman, Oregon Health & Science University, United States

Publication history

  1. Received: July 2, 2020
  2. Accepted: July 29, 2021
  3. Accepted Manuscript published: July 30, 2021 (version 1)
  4. Version of Record published: August 12, 2021 (version 2)

Copyright

© 2021, Pandey et al.

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

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