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Hamon Center for Therapeutic Oncology Research, University of Texas Southwestern Medical Center, Dallas, TexasCancer Biology Graduate Program, University of Texas Southwestern Medical Center, Dallas, Texas
Hamon Center for Therapeutic Oncology Research, University of Texas Southwestern Medical Center, Dallas, TexasDivision of Surgical Oncology, Department of Surgery, University of Texas Southwestern Medical Center, Dallas, Texas
Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TexasQuantitative Biomedical Research Center, Department of Population and Data Science, University of Texas Southwestern Medical Center, Dallas, TexasChildren’s Research Institute, University of Texas Southwestern Medical Center, Dallas, Texas
Hamon Center for Therapeutic Oncology Research, University of Texas Southwestern Medical Center, Dallas, TexasCancer Biology Graduate Program, University of Texas Southwestern Medical Center, Dallas, TexasDivision of Surgical Oncology, Department of Surgery, University of Texas Southwestern Medical Center, Dallas, Texas
Hamon Center for Therapeutic Oncology Research, University of Texas Southwestern Medical Center, Dallas, TexasChildren’s Research Institute, University of Texas Southwestern Medical Center, Dallas, Texas
Hamon Center for Therapeutic Oncology Research, University of Texas Southwestern Medical Center, Dallas, TexasDivision of Surgical Oncology, Department of Surgery, University of Texas Southwestern Medical Center, Dallas, Texas
Hamon Center for Therapeutic Oncology Research, University of Texas Southwestern Medical Center, Dallas, TexasSimmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TexasDepartment of Pharmacology, University of Texas Southwestern Medical Center, Dallas, Texas
Hamon Center for Therapeutic Oncology Research, University of Texas Southwestern Medical Center, Dallas, TexasCancer Biology Graduate Program, University of Texas Southwestern Medical Center, Dallas, TexasDivision of Surgical Oncology, Department of Surgery, University of Texas Southwestern Medical Center, Dallas, TexasSimmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TexasDepartment of Pharmacology, University of Texas Southwestern Medical Center, Dallas, Texas
Corresponding author. Address for correspondence: John D. Minna, MD, Hamon Center for Therapeutic Oncology Research, UT Southwestern Medical Center, 6000 Harry Hines Boulevard, Dallas, TX 75390-8593.
Hamon Center for Therapeutic Oncology Research, University of Texas Southwestern Medical Center, Dallas, TexasCancer Biology Graduate Program, University of Texas Southwestern Medical Center, Dallas, TexasSimmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TexasDepartment of Pharmacology, University of Texas Southwestern Medical Center, Dallas, TexasDepartment of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas
Macrophage phenotype in the tumor microenvironment correlates with prognosis in NSCLC. Immunosuppressive macrophages promote tumor progression, whereas proinflammatory macrophages may drive an antitumor immune response. How individual NSCLCs affect macrophage phenotype is a major knowledge gap.
Methods
To systematically study the impact of lung cancer cells on macrophage phenotypes, we developed an in vitro co-culture model that consisted of molecularly and clinically annotated patient-derived NSCLC lines, human cancer-associated fibroblasts, and murine macrophages. Induced macrophage phenotype was studied through quantitative real-time polymerase chain reaction and validated in vivo using NSCLC xenografts through quantitative immunohistochemistry and clinically with The Cancer Genome Atlas (TCGA)–“matched” patient tumors.
Results
A total of 72 NSCLC cell lines were studied. The most frequent highly induced macrophage-related gene was Arginase-1, reflecting an immunosuppressive M2-like phenotype. This was independent of multiple clinicopathologic factors, which also did not affect M2:M1 ratios in matched TCGA samples. In vivo, xenograft tumors established from high Arginase-1–inducing lines (Arghi) had a significantly elevated density of Arg1+ macrophages. Matched TCGA clinical samples to Arghi NSCLC lines had a significantly higher ratio of M2:M1 macrophages (p = 0.0361).
Conclusions
In our in vitro co-culture model, a large panel of patient-derived NSCLC lines most frequently induced high-expression Arginase-1 in co-cultured mouse macrophages, independent of major clinicopathologic and oncogenotype-related factors. Arghi cluster-matched TCGA tumors contained a higher ratio of M2:M1 macrophages. Thus, this in vitro model reproducibly characterizes how individual NSCLC modulates macrophage phenotype, correlates with macrophage polarization in clinical samples, and can serve as an accessible platform for further investigation of macrophage-specific therapeutic strategies.
Given the limitations of chemotherapy and oncoprotein-targeted therapy in NSCLC, considerable effort has been directed toward immunotherapeutic approaches. Remarkable advances in Food and Drug Administration–approved immune checkpoint blockade therapies have yielded improvements in objective response and overall survival.
Nevertheless, overall long-term benefit from immune checkpoint blockade only occurs in a few of patients, highlighting a critical need to identify additional mechanisms of immunosuppression including those in the tumor microenvironment (TME), which may affect the efficacy of immunotherapy.
Macrophages are among the most abundant immune cells in the TME, and their activity is implicated in tumor progression through multiple mechanisms, including cytokine or chemokine production, promotion of chronic inflammation, angiogenesis, response to hypoxia, and immunosuppression.
In physiological and malignant processes, macrophages exist on a spectrum between an “M1-like” proinflammatory, immunostimulatory phenotype, and an “M2-like” anti-inflammatory, angiogenic, immunosuppressive phenotype.
The type of macrophage present in the NSCLC TME carries clinical significance; the presence of M2-like macrophages in NSCLC stroma is associated with poor prognosis.
As such, therapeutics that target macrophages are being developed. For example, inhibition of macrophage-derived Arginase-1, an arginine-depleting enzyme that curtails T-cell proliferation, is under preclinical investigation and in early phase clinical trials.
A phase I/II study of safety and efficacy of the arginase inhibitor INCB001158 plus chemotherapy in patients (Pts) with advanced biliary tract cancers.
Thus, it would be important to understand and potentially target the underlying mechanisms generating immunosuppressive macrophage phenotypes, particularly those originating in individual NSCLC. In fact, studies suggest that oncogenic driver mutations in NSCLC cells contribute to macrophage M2-like phenotype by promoting an immunosuppressive milieu.
It is likely that distinct NSCLCs differentially affect macrophage phenotype in the TME. Although large, molecularly annotated data sets of bulk NSCLC tumors including tumor cells and their TME, including new multiomics and single-cell RNA sequencing (RNAseq) studies of NSCLC, are becoming available, what is still needed is a preclinical model system to identify and mechanistically reveal specific NSCLC–macrophage connections. Furthermore, such a system would be useful as a preclinical testing platform for potential therapies to overcome such immunosuppressive mechanisms. Thus, we need an accessible and reproducible preclinical model that can be manipulated to dissect how individual NSCLC cell line generates specific macrophage phenotypes. This model could then serve as a platform to investigate therapeutic strategies for modulating macrophage phenotype. In addition, the most useful preclinical model would be one that could be widely available and easily used in multiple laboratories.
This led us to explore using a large panel of patient-derived NSCLC cell lines and xenografts that have been clinically annotated, molecularly characterized, and widely distributed to the lung cancer translational research community. We aimed to develop a reproducible and physiologically relevant in vitro co-culture model to investigate tumor cell and TME factors involved in macrophage polarization and to investigate possible therapeutics. Although similar co-culture studies have been published, none have interrogated a large panel of patient-derived NSCLC cell lines with a broad spectrum of molecular subtypes on induced macrophage phenotype.
Thus, we established a multicellular co-culture model involving an extensive repository of 72 distinct patient-derived NSCLC cells, human cancer-associated fibroblasts (CAFs), and mouse bone marrow-derived macrophages (BMDMs). We found that each NSCLC cell line reproducibly induced unique gene expression profiles in co-cultured mouse macrophages, most frequently the immunosuppressive high Arginase-1 (Arghi) phenotype. Importantly, this macrophage phenotype induced in vitro was also identified in murine macrophages populating the NSCLC xenografts in vivo. Furthermore, patient-derived clinical samples deposited in The Cancer Genome Atlas (TCGA) database, whose tumors were molecularly “matched” by RNA expression and tumor mutations to our NSCLC cell lines which had induced the Arghi macrophage phenotype in the co-culture assay system, also exhibited a higher ratio of immunosuppressive M2 macrophages. Surprisingly, this in vitro model system revealed that the induced macrophage phenotypes did not correlate with standard clinical factors, demographics, and oncogenotypes, indicating the possibility of using this system to identify previously unidentified features and mechanisms that did lead to the induced macrophage phenotypes.
Materials and Methods
Patient-Derived Cell Cultures
Patient-derived NSCLC lines and CAFs have been generated at the National Cancer Institute (NCI) or the Hamon Center for Therapeutic Oncology Research at UT Southwestern (HCC) or obtained from the American Type Culture Collection. These cultures or lines have, in large part, been deposited at the American Type Culture Collection or are available from the HCC. The HCC4210F CAF line was derived from a 68-year-old white female, former smoker, with lung adenocarcinoma (TTF-1+, Napsin A+) at the time of surgical resection without any prior treatment. Cell lines were maintained in Roswell Park Memorial Institute 1640 (GIBCO, 2.05 mM L-glutamine) supplemented with 5% fetal bovine serum (FBS) (GIBCO). Previously characterized normal human bronchial epithelial-derived cell lines were maintained in keratinocyte serum-free media supplemented with human recombinant epidermal growth factor and bovine pituitary extract at the time of use.
All cell lines were maintained in a humidified environment in the presence of 5% CO2 at 37°C. All cell lines were DNA fingerprinted (PowerPlex Fusion Kit, Promega) for provenance and found to be mycoplasma free (Myco Kit, Boca Scientific).
Mouse BMDM Isolation and Differentiation
Mouse BMDMs were isolated and differentiated using the established Cold Spring Harbor Protocol.
Mouse L929 cells were grown in T175 flasks with 30 mL of DMEM (Dulbecco’s modified Eagle’s medium) (11995040, GIBCO) + 10% FBS. After the cells were grown to 100% confluency, the media were changed and then cells were cultured for 48 hours. Conditioned media were collected, and new media were added. This collection cycle was repeated four times. Collection media (1× phosphate-buffered saline + 5% FBS + 1× penicillin or streptomycin) and macrophage media (20% L929 condition media + 20% FBS + 0.5× sodium pyruvate + 1× minimum essential medium + 1× nonessential amino acid + 1× Glut Max in Dulbecco’s modified Eagle’s medium without glutamine) were used. Tibias and femurs were isolated from 6- to 8-week-old C57BL/6J mice and cleaned in 70% ethanol. Epiphyseal heads were transected to expose the bone marrow-containing medullary cavity. Lumens were flushed with collection media using syringes. Collected bone morrow was spun down (5 min × 1000 rotations per minute at 4°C), supernatant was removed, and the cell pellet was resuspended in macrophage media and filtered with a 70-micron filter followed by centrifugation (5 min × 1000 rotations per minute at 4°C). Cells were seeded on Petri dishes in 8 mL of macrophage media (3 plates per mouse) or frozen down (90% FBS, 10% DMSO). Fresh macrophage media (4 mL) were added after 3 days. After an additional 2 days of culture, macrophages were collected and used for co-culture assays.
Multicellular Co-Cultures
Multicellular co-cultures were composed of BMDMs, CAFs, and NSCLC cells at a 1:10:50 ratio, respectively. We chose these ratios based on immunohistochemistry (IHC) quantification of patients with NSCLC which reflected the tumor or TME composition.
NSCLC and CAF cell lines were trypsinized and plated with BMDMs into 6-well plates at 1.5 × 105 total cells per well. Cells were incubated for 40 hours and harvested for quantitative real-time polymerase chain reaction (qRT-PCR, primers given in Supplementary Table 3) analysis of the mouse expression of macrophage polarization markers (Arginase-1, iNos, interleukin [Il]-6, Il-1b, Ym1, Socs3).
Macrophages alone were seeded at 1.0 × 105 cells per well. Lipopolysaccharide (LPS) (20 ng/mL, 4-h stimulation) or IL-4 (40 ng/mL, 18-h stimulation) treatments were used as positive controls for macrophage polarization into M1-like and M2-like phenotypes, respectively. All qPCR data processing was completed in R (see Supplementary File 2: “Co-culture qPCR R code.R”). Primers were designed using the National Institutes of Health nBlast tool against genes of interest specific to Mus musculus (house mouse) transcriptome. To ensure quality control, all primer sets were evaluated by the National Institutes of Health Primer-BLAST to ensure no reactivity with the Homo sapiens transcriptome. In addition, primer sets were tested with human cell lines to ensure no activity and in polarized macrophages for predicted outcomes.
Xenograft Studies
NSCLC cell lines A427, NCI-H1666, NCI-H2009, NCI-H460, Calu-6, NCI-H1373, and NCI H2073 were grown as subcutaneous xenografts. Tumor cells (1 × 106) suspended in 100 μL of phosphate-buffered saline were injected subcutaneously into the right posterior flank of 8-week-old female athymic nude mice. Tumor dimensions and volumes were measured weekly, and mice were killed when tumor volumes reached 1000 to 1500 mm3. Tumors were harvested for quantitative IHC interrogation of macrophage polarization. All mouse experiments were performed under a UT Southwestern Institutional Animal Care and Use Program–approved protocol.
Blocking solutions, primary antibodies, secondary antibodies, and relevant information are available in the Supplementary Methods. Images were captured at 40× magnification using a Vectra Polaris Slide Scanner (AKOYA Biosciences, DE). Images were deconvoluted and restitched using Phenochart and inForm software (Akoya Biosciences). Reconstituted images underwent multiplex quantitative analysis using HALO software (Akoya Biosciences).
Overview of the Discovery Approach and Macrophage Characterization Platform
To evaluate the contribution of specific cancer cell characteristics to macrophage polarity, we used archival molecular and clinicopathologic data on our cell line repository and corroborated these findings with publicly available data from the TCGA (Fig. 1A–C, Table 1, Supplementary Tables 1 and 2).
Whole-exome and bulk RNA sequencing from NSCLC (n = 72) and SCLC (n = 2) cell lines were used to characterize total mutation burden, copy number variants, and somatic mutations. These data were then used to perform a TCGA “matchup” (Supplementary Table 2 and Supplementary Methods). Although the individual NSCLC line was not derived from the TCGA tumor samples, the comparison of mRNA expression and DNA mutation profiles provided quantitative, objective correlation between our NSCLC lines and the TCGA tumor samples. CIBERSORT immune deconvolution software was then used to estimate immune cell populations within the TCGA patient-derived tumor specimens (lung adenocarcinoma n = 490, squamous cell carcinoma n = 490).
From the CIBERSORT analysis, we used M1-like and M2-like macrophage cell counts for further analyses and then compared the macrophage phenotype counts in the TCGA samples with the induced macrophage phenotypes engendered by the NSCLC lines best matched to the individual TCGA tumor. In addition, we assessed the contribution of clinicopathologic covariates including pathologic subtype, sex, age, smoking status, clinical stage, and anatomical origin of cell line (i.e., primary tumor, metastatic lymph node, distant metastasis) on macrophage polarity in lung cancer co-culture and TCGA samples.
Figure 1Overview of study of induced macrophage phenotypes in NSCLC co-culture system. Flowchart revealing analytical workflows, integrating molecular and clinicopathologic characteristics with macrophage phenotypes induced in the lung cancer multicellular co-culture model and the NSCLC cell line information with TCGA data sets. (A) Lung cancer co-culture system assay. We performed co-cultures of NSCLC lines, CAFs, and mouse bone marrow-derived macrophages and assayed by quantitative mRNA expression of mouse macrophage genes by using species-specific primers at 40 hours to evaluate the induced macrophage phenotype. (B) Clinicopathologic and demographic analyses. We investigated whether clinicopathologic and demographic data features or specific mutations or mRNA expression patterns found in the NSCLC lines were correlated with the induced macrophage phenotypes. (C) Oncogenotype analysis and clinical correlation. Total mutational burden, copy number variants, and somatic mutation profiling data were abstracted from whole-exome and RNAseq analysis from each NSCLC line. These molecular data were “matched” against TCGA molecular data in NSCLC clinical samples by comparing mRNA expression and specific mutations (see Methods) to assign a correlation (ranging from 0.0 to 1.0) between each NSCLC line and TCGA tumor sample. We then performed immune deconvolution using CIBERSORT to estimate immune cell populations in the TCGA bulk tumor data, focusing specifically on M2 and M1 macrophages and tested whether the NSCLC cell line-induced macrophage phenotypes were similar to macrophage phenotypes found in TCGA tumor samples most closely matched to each cell line. BMDM, bone marrow-derived macrophage; CAF, cancer-associated fibroblast; EMT, epithelial-mesenchymal transition; LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma; qRT-PCR, quantitative real-time polymerase chain reaction; RNAseq, RNA sequencing; TCGA, The Cancer Genome Atlas.
Table 1Available Clinical and Demographic Characteristics of Patient-Derived Cell Lines With Respect to Induced Macrophage Phenotype in the In Vitro Co-Culture Model
All statistical analyses were performed with GraphPad Prism (version 9) unless otherwise stated. All qPCR data processing was completed using R (R Core Team, Vienna, Austria).
NSCLC Cells Induce Distinct Macrophage Phenotypes in a Multicellular (Human Tumor Cells, CAFs, and Mouse Macrophages) Co-Culture Model, Most Frequently High Arginase-1
We established a three component, multicellular, co-culture model of mouse BMDMs, patient-derived NSCLC cells, and patient CAFs to determine the impact of tumor cells on macrophage polarization (Fig. 2A). Because macrophages were derived from mouse bone marrow, we used a panel of mouse-specific primers for qPCR analysis of expression of macrophage-relevant genes (Arginase-1, Il-1β, Socs3, iNos, Il-6, Ym-1) to assess macrophage phenotype. We interrogated 72 distinct NSCLC cell lines and a patient-derived NSCLC CAF line. We note that inclusion of a CAF line (such as HCC4210F) in the co-culture system was required to identify changes in macrophage phenotype (Fig. 2A and B). Overall, the large panel of NSCLC cell lines most frequently induced increased expression of Arginase-1, Il-1β, and Socs3, compared with macrophages alone. The specific macrophage phenotype induced by each NSCLC cell line was reproducible within assays through multiple technical replicates and stable over time when we repeated testing at different passages (multiple biological replicates) of any one NSCLC cell line (Supplementary Fig. 1A and Supplementary Methods). To characterize high versus low expression of any given gene in an unbiased manner between biological replicates and cell lines, we defined high expression as more than or equal to 75-fold change compared with gene expression from macrophages cultured alone and less than 75-fold change as low expression. With this approach, high expression of Arginase-1 (Arghi), classically associated with the immunosuppressive M2-like phenotype, was the most frequently induced phenotype (32% of lines) (Fig. 2C), followed by high Il-1β and then high Socs3. Because elevated expression of ARG by myeloid cells including macrophages has been directly associated with immunosuppression and T-cell dysfunction in NSCLC, we focused on further clinicopathologic and molecular characterization of Arghi versus Arglow clusters to investigate factors which may be associated with high expression of Arginase-1 in co-cultured macrophages.
Figure 2NSCLC cells induce heterogeneous macrophage phenotypes in a multicellular in vitro co-culture model, most frequently, high expression of immunosuppressive Arginase-1. (A) Schematic of the NSCLC multicellular co-culture model setup. Co-cultures consisted of the following: mouse macrophages (MΦ) isolated and differentiated from mouse bone marrow hematopoietic stem cells (5%) using mouse L929 conditioned media from published methods,
human CAFs (25%), and cancer cell lines isolated from patients with NSCLC (70%). RNA was extracted from individual co-cultures and qRT-PCR for mouse macrophage-specific genes was conducted. (B) Comparison of dual co-cultures and multicellular co-cultures highlights the effects of addition of CAFs to induced macrophage phenotype. qRT-PCR transcriptional analysis of macrophage markers using species-specific primers: Arginase-1, Il-6, and iNos. Cultures are dual co-cultures (2 cell types, CAFs and macrophages, or tumor cells and macrophages) or multicellular co-cultures (3 cell types, tumor cells, CAFs, and macrophages) using H2009 and H1819 NSCLC cell lines as examples (results from duplicate assays illustrated as dots in each bar graph). (C) Heatmap of quantitative mRNA expression changes by qRT-PCR analysis of six mouse macrophage-related genes after NSCLC, CAF, macrophage co-culture compared with culturing the macrophages alone (see Supplementary Materials and Methods). Raw fold change data were normalized to gene expression from macrophages alone. Each experiment included positive controls of macrophages alone treated with IL-4 (strong M2 phenotype induction) or LPS (strong M1 phenotype induction). Each row represents macrophage expression phenotype results average from technical quadruplicates and three biological replicates for the indicated NSCLC cell line (see Supplementary Fig. 1B, e.g., of fold changes in macrophage gene expression in the co-cultures). High expression of any given gene was characterized as relative fold change more than or equal to 75 from baseline, and low expression was characterized as relative fold change less than 75 from baseline. Of 75 lines, 24 (32%) induced high expression of Arginase-1. Furthermore, 72 NSCLC cell lines, two SCLC lines, and three benign individual cell lines were studied. (D) qPCR findings of induced macrophage gene expression are conserved in bulk RNAseq analyses. Relative gene expression of six macrophage-relevant genes was correlated with expression in bulk RNAseq samples submitted for a large panel of NSCLC co-cultures. Human reads were filtered out, and mouse gene expression of each target gene was correlated with our qPCR panel through Pearson correlation coefficient analyses. Arginase-1, Il1b, Il6, and iNos expressions were strongly consistent between qPCR and RNAseq analyses. Furthermore, 15 individual NSCLC cell lines were tested. BMDM, bone marrow-derived macrophage; CAF, cancer-associated fibroblast; DMEM, Dulbecco’s modified Eagle’s medium; FBS, fetal bovine serum; MEM, minimum essential medium; NEAA, nonessential amino acid; qRT-PCR, quantitative real-time polymerase chain reaction; RNAseq, RNA sequencing.
To quantitatively investigate macrophage gene expression differences between Arghi and Arglow cluster lines, we compared expression of each gene between clusters. Only one macrophage gene, Il-6, was found to be expressed at higher levels in the Arghi compared with Arglow cohort (median fold change 14.5 versus 5.3, respectively, p < 0.0001) (Supplementary Fig. 1B). We note in syngeneic mouse models and human tumors that Rab37-regulated secretion of IL-6 by macrophages is associated with M2-like phenotype, promotion of STAT3-dependent PD-1 expression in CD8+ T-cells, and poor prognosis in patients with NSCLC.
In addition to qRT-PCR measurement of mouse macrophage gene expression, bulk RNAseq was performed on a panel of 15 NSCLC co-cultures, with human reads filtered out, to compare the qRT-PCR and RNAseq results. We found that our qPCR findings of high Arginase-1 expression in macrophages across this panel correlated significantly with macrophage expression patterns observed in our RNAseq samples of the same NSCLC co-culture (r = 0.85, p = 1.6E-5) (Fig. 2D). To further study whether the findings from our mouse macrophage platform could be recapitulated using human macrophages, we used macrophages differentiated from patient umbilical cord blood-derived monocytes co-cultured with two Arghi (H1373 and H2009) and two Arglow (H647 and H441) cell lines. On flow cytometric analysis, we found that Arghi cell lines similarly polarized co-cultured human macrophages toward an M2-like state (CD68+/CD206+) (Supplementary Fig. 1C). Thus, we found through this co-culture model that 72 distinct patient-derived NSCLC cell lines reproducibly (for each cell line model) induce differential expression patterns in co-cultured mouse macrophages, most frequently the immunosuppressive Arghi phenotype.
High Expression of Arginase-1+ Macrophages Is Recapitulated in Arghi NSCLC-Derived Xenografts In Vivo
To investigate whether induced macrophage phenotype by Arghi cluster lines was also observed in vivo, we established athymic nude mice subcutaneous xenografts derived from Arghi (5 cell lines) and Arglow lines (6 cell lines) to determine the phenotypes of host mouse macrophages. Tumors were grown to 1000 to 1500 mm3 in diameter and harvested for IHC analysis of the mouse macrophage phenotype in the TME (Fig. 3A and Supplementary Fig. 2A). Median tumor area was not significantly different between cohorts (Supplementary Fig. 2B). We found that compared with NSCLC xenografts established from Arglow cluster lines, those established from Arghi lines had significantly higher median density of total macrophages (characterized as F4/80+) (1245 versus 414 cells/mm2, p < 0.0001) and higher density of Arg1+ macrophages (Arg+/F4/80+) (142 versus 44 cells/mm2, p = 0.0007) (Fig. 3A). Thus, we observed that xenograft tumors derived from Arghi NSCLC cell lines had significantly higher density of host mouse Arg1+ macrophages in the tumor stroma, providing an independent in vivo confirmation of our in vitro findings.
Figure 3Macrophage phenotypes induced in vitro are observed in vivo and in clinical samples from the TCGA. (A) Immunohistochemical staining of NSCLC xenografts for macrophage markers. NSCLC xenografts were established from five Arghi cluster lines (A427, H1373, H1666, H2009, H522) and six Arglow cluster lines (H1993, Calu-6, H460, H647, H2073, H441) using athymic nude mice with subcutaneously injected tumor cells (1 × 106 cells/mouse) into the right flank to investigate induced macrophage phenotype in vivo (2–7 mice/NSCLC line). As an example, NSCLC xenograft NCI-H2073 was sectioned, immunohistochemically stained, and quantified for macrophage ARG1 expression. F4/80 was used as a co-localizing murine pan-macrophage marker, whereas staining for human pan-cytokeratin identified epithelial tumor cells. Those xenografts established from Arghi cluster lines had significantly median greater density of total F4/80+ macrophages and ARG+ macrophages. This was consistent with prior qRT-PCR mRNA macrophage expression results from the in vitro co-cultures. Significance was determined using Mann-Whitney U tests between cohorts. (B) M2-macrophage phenotypes found in NSCLC TCGA data by CIBERSORT analysis correlate with matched NSCLC line-induced macrophage phenotypes. B (left portion): Our NSCLC cell lines were matched to TCGA clinical samples through assessment of RNA expression and mutational profiles to generate a matching score between an individual NSCLC cell line and a “matched” TCGA patient sample (see Supplementary Methods: TCGA Matchup); 36 molecular matches were established. B (right portion): A significantly higher M2:M1 ratio of macrophages was identified through immune deconvolution (CIBERSORT) of TCGA patient data derived from samples that were “matched” (by mRNA expression and DNA mutation profiles) to NSCLC cell lines from the Arghi cluster. Significance was determined using a two-sided t test. Mean ± SD. LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma; qRT-PCR, quantitative real-time polymerase chain reaction; TCGA, The Cancer Genome Atlas.
TCGA-Deposited Clinical NSCLC Specimens Molecularly Matched to Co-Cultured NSCLC Lines Exhibit Similar Tumor-Associated Macrophage Phenotypes
To evaluate the external validity of induced macrophage phenotypes in our co-culture system in clinical samples, we investigated RNA expression and mutation data from our patient-derived NSCLC cell lines to “matched” individual patient tumor specimens having similar mRNA expression and DNA mutation profiles in the TCGA database (Fig. 3B [left], Supplementary Table 2, and Supplementary Methods). We then used the bulk RNAseq expression data from the TCGA and CIBERSORT
to quantify relative M1-like and M2-like macrophages in the TME of these clinical specimens. This approach allowed us to correlate the induced macrophage phenotypes in our NSCLC co-culture system with the ratio of M2:M1 macrophages in clinical samples. We found that the co-culture–induced macrophage expression patterns from any one NSCLC cell line correlated significantly with the macrophage phenotypes (from CIBERSORT RNA expression analyses) found in molecularly matched TCGA patient tumors. Those TCGA specimens matched to Arghi cluster NSCLC cell lines had a significantly higher mean M2:M1 ratio compared with specimens matched to Arglow lines (0.01 versus −0.03, p = 0.0361) (Fig. 3B [right]). These findings indicate that patient-derived NSCLC lines in our co-culture system induce macrophage phenotypes that are not only found for the same NSCLC lines in xenografts in vivo but also correlate with macrophage phenotypes found in TCGA-derived patient tumor specimens with similar mRNA and mutational profiles. This highlighted that our model has the potential to provide a clinically pertinent platform from which to investigate tumor cell and TME factors that modulate macrophage phenotype.
Clinicopathologic and Molecular Characteristics of NSCLC Cell Lines Do Not Correlate With Induced Macrophage Phenotypes
We asked whether there was any correlation between clinicopathologic or demographic factors and induced macrophage phenotypes in our NSCLC models. Prior studies have suggested that multiple clinicopathologic factors may modulate the TME landscape, including macrophage phenotype.
To date, no large-scale investigation of the impact of these factors across multiple NSCLC tumors or patient-derived cell lines on macrophage phenotype has been performed. Surprisingly, none of the standard clinical or molecular variables correlated significantly with either Arghi or Arglow NSCLC line clusters. These included age, sex, race, smoking status, clinical stage, oncogenotype, total mutation burden, histologic subtype, and epithelial or mesenchymal phenotype (Table 1, Fig. 4A [top], and Supplementary Fig. 2C and D).
Figure 4Total mutation burden and key driver mutations characteristics of the NSCLC cell lines do not correlate with their induced macrophage phenotype in neither co-cultures nor clinical samples. (A) Total mutation burden. (Upper) Comparative analyses revealed no significant differences in median total mutation burden between Arghi and Arglow cohorts between induced macrophage phenotype between cohorts through Mann-Whitney U tests. (Lower) Total mutational burden was investigated against TCGA-deposited patient samples which contained macrophages with higher M2:M1 (M2) or M1:M2 (M1) ratios on CIBERSORT analysis. No significant differences in total mutation burden were noted on Mann-Whitney U analysis, similar to the findings in our NSCLC co-culture panel. (B) Key individual driver mutations. Frequency of key driver mutations and combinations of mutations were abstracted from cell lines in each cohort. The most often mutated genes regardless of cohort included TP53, KRAS, TP53/KRAS, STK11, and EGFR. No significant differences were noted in frequency of oncogene mutations between cohorts for any given single or combination of mutated oncogenes. Significance was determined using two-sided t tests. Mean ± SD. (C) Histology and key driver mutations in TCGA data and associated macrophages. Macrophage M1:M2 ratio determined by immune deconvolution (CIBERSORT) in TCGA NSCLC patient samples was not correlated with mutation status for TP53, KRAS, EGFR, STK11, and KEAP1. M2:M1 ratios between groups were compared through Mann-Whitney U tests. For all cell line analyses, 72 individual NSCLC cell lines were used. Available data from a total of 980 patient lung cancer samples were used for TCGA analyses. TCGA, The Cancer Genome Atlas.
Looking at specific NSCLC oncogenotypes, we found in both Arghi and Arglow cohorts that the most frequently identified gene mutations were TP53 (83, 84%, respectively), KRAS (58, 44%), TP53/KRAS (50, 34%), STK11 (29, 36%), and EGFR (25, 12%), similar to prior studies (Fig. 4B).
Nevertheless, no significant differences were identified between cohorts with respect to oncogenotype frequency. We further investigated macrophage Arginase-1 expression quantitatively across our panel of lung cancer lines against presence of key mutant oncogenes individually (TP53, KRAS, STK11, KEAP1) or in combination with one another and did not identify any significant differences (Supplementary Fig. 3). Given the absence of significant correlations between NSCLC oncogenotype and macrophage Arginase-1 expression in our in vitro co-culture model, we also asked whether these findings were observed in TCGA-deposited clinical NSCLC samples. We assessed M2:M1 macrophage phenotype ratio in clinical samples using CIBERSORT analysis against the aforementioned demographic, clinical, and molecular characteristics and similarly found no significant differences in the M2:M1 ratio with respect to sex, histologic subtype, age, total mutation burden, or oncogenotype (Fig. 4A [bottom] and C and Supplementary Fig. 2E). Thus, surprisingly, we found that established clinicopathologic, demographic, and molecular characteristics of NSCLC cell lines co-cultured with macrophages were not associated with high or low induction of macrophage Arginase-1 expression, nor were these factors correlated with macrophage phenotypes in the TCGA data set.
Discussion
In this study, we used an in vitro multicellular co-culture model of NSCLCs, CAFs, and mouse BMDMs to reveal that a large panel (N = 72) of patient-derived NSCLC lines reproducibly induced heterogeneous macrophage gene expression signatures, most frequently the high expression of immunosuppressive Arginase-1. The NSCLC cell lines used in this study are widely available and used by the lung cancer translational research community, and the patient-derived CAFs used will be made freely available.
Likewise, the methods for harvesting and using mouse BMDMs are most often used. The protocol we developed for these assays described in the Methods section should be straightforward for other laboratories to implement and can readily be extended to test the effects of the multiple new lung cancer lines, including those from NSCLC, SCLC, and patient-derived xenografts.
We point out that there have been similar co-culture protocols published by other investigators. Nevertheless, none have been used to interrogate a large panel of NSCLC cell lines as described here.
Differences in induced expression patterns suggest different polarized functions of macrophages in co-culture that serve as a foundational resource for further investigation into how to modulate these phenotypes for potential clinical benefit. Indeed, elevated macrophage Arginase-1 activity is classically associated with an immunosuppressive phenotype that impairs T-cell function and facilitates tumor immune evasion. As expected, this phenotype is associated with poor prognosis.
An epithelial-mesenchymal transition gene signature predicts resistance to EGFR and PI3K inhibitors and identifies Axl as a therapeutic target for overcoming EGFR inhibitor resistance.
A phase I/II study of safety and efficacy of the arginase inhibitor INCB001158 plus chemotherapy in patients (Pts) with advanced biliary tract cancers.
Through xenograft studies, we revealed that the Arghi phenotype found in vitro was also recapitulated by the same NSCLC tumors grown in vivo. To further evaluate the validity and generalizability of the co-culture model to patient tumor specimens, we compared the induced macrophage phenotypes in vitro with those found in molecularly matched NSCLC patient samples in TCGA database. We found that TCGA samples molecularly matched to the NSCLC lines that stimulated high macrophage Arginase-1 expression also had significantly elevated levels of M2-like macrophages. The differences in M2:M1 ratio were modestly but significantly different between cohorts, perhaps reflecting that macrophage phenotypes in the TME are complex and are not completely captured by the traditional M2 (high Arg1) or M1 (high iNos) characterization. To this point, none of our lung cancer lines significantly induced high iNos expression while variably expressing other genetic markers even in Arghi lines, highlighting the principle that macrophages behave on a spectrum between these states. Because our co-culture system characterizes macrophage activity by specific gene signatures a specific biological context, it serves as a useful model that is not encumbered by this traditional classification while still potentially reflecting clinical validity. In aggregate, these findings reflect the utility of this in vitro co-culture platform to investigate macrophage phenotype in the NSCLC TME.
Previous studies have suggested that sex, ethnicity, smoking status, lung cancer subtype, oncogenotype, and tumor mutation burden may alter the TME landscape.
Therefore, we abstracted these salient characteristics for each cell line studied in the co-culture model and investigated their impact on macrophage phenotype. To our surprise, we did not identify any significant clinicopathologic characteristics that predicted macrophage phenotype in our co-culture system, including anatomical origin, sex, smoking status, mutational burden, subtype, or stage. Thus, we were interested in the results of a comparable study of 80 resected NSCLC tumor specimens, where Jackute et al.
found that although increased M2 macrophage density was associated with poorer survival compared with M1 macrophage density, no significant differences were identified between M1 or M2 macrophage density with respect to sex, age, histopathologic diagnosis, or stage.
The authors did identify more M2 macrophages in poorly differentiated tumors and a higher number of total tumor and stroma-infiltrating M1 and M2 macrophages in samples from smoking versus nonsmoking patients.
We also found that tumor cell oncogenotype did not correlate with co-culture–induced macrophage phenotype. KRAS, one of the most frequently mutated oncogenes in NSCLC, was identified in nearly 50% of tested NSCLC lines. Prior studies suggest that KRASG12D mutations may be associated with M2-like human macrophage gene signatures, including ARGINASE-1.
Nevertheless, we found that KRAS mutations were evenly distributed between Arghi and Arglow cluster lines. Prior patient tumor analyses have revealed that EGFR mutations in NSCLC do not distinctly affect infiltration of macrophages, consistent with our findings.
High tumour islet macrophage infiltration correlates with improved patient survival but not with EGFR mutations, gene copy number or protein expression in resected non-small cell lung cancer.
similarly revealed that although M2-like macrophage density was greater in EGFR wild-type tumors, the fraction of M2 to total macrophages was similar between EGFR-mutant versus wild-type tumors, smokers versus nonsmokers, and between adenocarcinoma versus squamous cell carcinoma subtypes. Thus, the in vitro data from our co-culture model are consistent with these findings.
Our study has several limitations. We used mouse macrophages in the co-culture model to leverage the species specificity and generate mouse-specific primers to evaluate changes in macrophage phenotype. We investigated four of our cell lines in a co-culture system with macrophages derived from patient umbilical cord blood-derived macrophage samples with flow cytometry and found that those cell lines that induced high Arginase-1 expression in mouse macrophages similarly polarized human macrophages to an M2-like phenotype. Although these findings validate our co-culture system, further investigation of macrophage activity using human-derived cells is warranted. We note that we recapitulated these findings in a smaller panel of NSCLC cell lines. This was substantially more time consuming and significantly more expensive with respect to financial cost and the need to use patient samples, which required consent, monocyte isolation, and a challenging maturation process. As such, we believe that our in vitro co-culture system using mouse macrophages is an accessible, efficient, and biologically consistent initial platform to explore macrophage biology. If meaningful findings are identified, these can be further evaluated in downstream studies. The study of the function of CAFs in the NSCLC TME as they relate to macrophage phenotype is necessary. We have so far studied CAFs from five patients with NSCLC and have not found major differences but are continuing to actively investigate the role of CAFs in macrophage polarization in the NSCLC TME. Although our studies were performed in 2D co-cultures, organoid-type cultures should be performed. Furthermore, although the xenograft studies were completed on subcutaneous tumors, it will be necessary to study orthotopic models (in the lung and at metastatic sites) as well. Most importantly, the features of individual NSCLC line which led to the up-regulation of Arginase-1 and other genes in this panel need further investigation.
In conclusion, our co-culture system is an accessible, focused, and reproducible model of macrophage activity in the NSCLC TME. We find that a large panel of patient-derived NSCLC lines, when co-cultured with CAFs and mouse macrophages, most frequently induce high expression of immunosuppressive Arginase-1, independent of major clinical-, demographic-, and molecular oncogenotype-related factors. These phenotypes are recapitulated in xenografts in vivo and are further clinically validated in TCGA-deposited tumor data sets. This co-culture model is an effective tool for early investigation of macrophage biology in the NSCLC TME and an easy-to-use system to investigate genetic expression profiles, clinicopathologic correlates, and early validation of planned in vivo studies and to screen for novel compounds, which may target macrophage activity. Thus, our co-culture model serves as a robust, physiologically consistent platform from which to interrogate tumor cell and TME features and novel therapeutics that may affect macrophage phenotype.
Ling Cai: Data curation, formal analysis, visualization.
Debolina Ganguly: Validation and formal analysis.
Huiyu Li: Investigation and formal analysis.
Jason E. Toombs: Investigation.
Luc Girard: Data curation, formal analysis.
John D. Minna: Conceptualization, resources, supervision, funding acquisition, writing—review and editing.
Rolf A. Brekken: Conceptualization, resources, supervision, funding acquisition, writing—original draft, writing—review and editing.
Acknowledgments
This work was supported by the National Institutes of Health grants R01 CA243577 and U54 CA210181 (to Dr. Brekken); National Institutes of Health SPORE P50 CA070907, U54 CA224065, and CPRIT RP160652 (to Dr. Minna); the Effie Marie Cain Foundation (to Dr. Brekken), National Cancer Institute (NCI) T32 CA124334 (principal investigator: J. Shay) (to Dr. Park), Cancer Center Support Grant P30 CA142543 (Dr. Cai), and the Burroughs-Wellcome Fund (Dr. Chandra). The results published here are in part based on data generated by the TCGA Research Network: https://www.cancer.gov/tcga. The authors thank Novogene Bioinformatics Technology Co. Ltd. (Beijing, People’s Republic of China) for conducting the RNA sequencing, Simmons Cancer Center Tissue Resource (supported by NCI grant P30 CA142543), McDermott Sequencing, Microarray & Immune Phenotyping Core. The authors are indebted to Dr. Boning Gao for developing the patient-derived cancer-associated fibroblasts, Elizabeth McMillan for discussion and consultation on biostatistical analyses of this study, and Hyunsil Park for the assistance with mouse studies during the coronavirus disease 2019 pandemic and thank members of the Brekken and Minna laboratories for comments and advice during the development and execution of this project.
A phase I/II study of safety and efficacy of the arginase inhibitor INCB001158 plus chemotherapy in patients (Pts) with advanced biliary tract cancers.
An epithelial-mesenchymal transition gene signature predicts resistance to EGFR and PI3K inhibitors and identifies Axl as a therapeutic target for overcoming EGFR inhibitor resistance.
High tumour islet macrophage infiltration correlates with improved patient survival but not with EGFR mutations, gene copy number or protein expression in resected non-small cell lung cancer.
Drs. Park and Chandra contributed equally to this work.
Disclosure: Dr. Minna receives licensing fees from the National Institutes of Health and UT Southwestern for distribution of human tumor cell lines. The remaining authors declare no conflict of interest.
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