Lung Cancer Subtypes Generate Unique Immune Responses

Abstract

Lung cancer – the leading cause of cancer-related deaths worldwide – is a heterogeneous disease comprised of multiple histologic subtypes that harbor disparate mutational profiles. Immune-based therapies have shown initial promise in the treatment of lung cancer patients but are currently limited by low overall response rates. We sought to determine whether the host immune response to lung cancer is predicated, at least in part, by histologic and genetic differences, as such correlations would have important clinical ramifications. Using mouse models of lung cancer, we show that small cell lung cancer (SCLC) and lung adenocarcinoma (ADCA) exhibit unique immune cell composition of the tumor microenvironment. The total amount of leukocyte content was markedly reduced in SCLC compared to lung ADCA, which was validated in human lung cancer specimens. We further identified key differences in immune cell content using three models of lung ADCA driven by mutations in Kras, Tp53, and Egfr. Although Egfr-mutant cancers displayed robust myeloid cell recruitment, they failed to mount a CD8⁺ immune response. In contrast, Kras-mutant tumors displayed significant expansion of multiple immune cell types, including CD8⁺ cells, regulatory T cells, IL17A-producing lymphocytes, and myeloid cells. A human tissue microarray annotated for KRAS and EGFR mutations validated the finding of reduced CD8⁺ content in human lung adenocarcinoma. Taken together, these findings establish a strong foundational knowledge of the immune cell contexture of lung ADCA and SCLC and suggest that molecular and histological traits shape the host immune response to cancer.

INTRODUCTION

Despite decades of research, small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) remain among the world's deadliest diseases (1). SCLC, in which RB1 and TP53 mutations are common (2), accounts for 10-20% of lung cancer diagnoses (3). Over half of NSCLC cases are classified as lung adenocarcinomas (ADCA), in which KRAS, EGFR, and TP53 mutations are the predominant genetic drivers (4, 5). Although patients with EGFR mutations initially respond to targeted therapies, drug resistance typically develops within the first year (6). SCLC and KRAS-mutant ADCA have proven less tractable, as scant progress has been made towards the development of targeted therapeutics for these patients (7). Novel immunotherapeutic strategies have offered new hope for the management of NSCLC (8-10) and SCLC (11), but the clinical success of immunomodulatory agents will depend on a strong foundational knowledge of the cells that comprise the lung tumor microenvironment (TME) in these molecularly and histologically distinct diseases.

Inflammation is a key attribute of neoplasia (12). The host immune response to cancer is an intricate web of both pro- and anti-tumorigenic signals (13). CD8⁺ T cells, also known as cytotoxic T lymphocytes (CTL), are the body's main immunological barrier to cancer, as they are capable of recognizing and killing tumor cells. However, CTL activity is curbed by tumor cells expressing immune checkpoint ligands (e.g. PD-L1), as well as an influx of immune-suppressive cells (i.e. regulatory T cells, macrophages, monocytes, and neutrophils) into the TME (14, 15). Newly developed immune checkpoint inhibitors (ICI; e.g. ipilimumab and nivolumab) seek to reverse this suppression and unleash an anti-tumor response (16).

Although some lung cancer patients have experienced remarkable tumor regression upon commencing ICI therapy, overall response rates have peaked around 20% (9, 10). These disparate outcomes may in part be explained by findings that tumor immune cell composition and function vary between anatomical sites and histological origins (17). In lung cancer, for example, squamous cell carcinoma (SCC) patients have exhibited longer progression-free survival with ipilimumab treatment than have ADCA patients (8). However, even within histological subgroups, response rates vary widely, raising the question of what other tumor attributes might predict clinical outcome.

The oncogenic functions of mutant RAS and EGFR in cancer include the production of pro-inflammatory cytokines, such as IL8, that help to shape the TME (18-21). TP53 has similarly demonstrated non-cell-autonomous behaviors during tumorigenesis (22, 23). The discrete impact of molecular signatures, such as KRAS, EGFR, TP53, and RB1 mutations, on the immune cell composition of lung cancer nevertheless remains largely undefined. To address this question, we profiled the TME of three genetically engineered mouse (GEM) models of NSCLC – Kras^LSL-G12D, Kras^LSL-G12D;Trp53^Fl/Fl, and Egfr^L858R – as well as the Rb1^Fl/Fl;Trp53^Fl/Fl model of SCLC. Here we show that the molecular and histological subtypes of lung cancer predict immune cell composition and may, therefore, demand specific immunotherapeutic regimens.

MATERIALS AND METHODS

Mice

All animal experiments utilized aged-matched mice on approved IACUC protocols at the Fred Hutchinson Cancer Research Center. TetO-Egfr^L858R mice (24) were obtained from the Mouse Models of Human Cancer Consortium on C57BL/6 background. Ccsp-rtTA mice (25) on FVB background were provided by Jeff Whitsett (University of Cincinnati). Kras^LSL-G12D (i.e. Kras) (26), Trp53^Fl/Fl (p53) (27), RORγt^GFP (RORγt) (28), and Tcrd^−/− (Tgd) (29) mice were obtained from Jackson Labs on C57BL/6 background. TetO-Egfr^L858R;Ccsp-rtTA (Egfr), Kras^LSL-G12D;Trp53^Fl/Fl (Kp53), Kras^LSL-G12D;RORγt^GFP (K.RORγt), and Kras^LSL-G12D;Tcrd^−/− (K.Tgd) mice were generated by simple cross-breeding. Rb1^Fl/Fl mice (30) were crossed with Trp53^Fl/Fl to generate Rb1^Fl/Fl;Trp53^Fl/Fl (Rbp53) mice on a mixed C57BL/6x129 background.

Egfr and single-transgene control mice (Ccsp-rtTA or TetO-Egfr^L858R) were fed 200 mg/kg doxycycline-impregnated food (Harlan, Indianapolis, IN, USA). Kras, Kp53, p53, and wild-type (wt) C57BL/6 animals received an intratracheal dose of 2.5×10⁷ pfu Adenoviral Cre Recombinase (AdCre; University of Iowa Viral Vector Core, Iowa City, IA, USA), as described (31). Each cohort was studied over a time course of 6, 10, and 14-weeks post initiation of doxycycline or infection with AdCre. Additional cohorts of K.RORγt and K.Tgd animals were similarly subjected to AdCre infection (2.5×10⁷ pfu) and examined 14-weeks post initiation or when moribund. Rb^Fl/Fl;Trp53^Fl/Fl mice received 1×10⁸ pfu AdCre; given the long latency period, Rbp53 animals were studied 9 months post-induction.

CTLA4 antibody, clone 9D9 (MedImmune) or isotype control (mIgG2b) was administered to an additional cohort of Kras mice twice weekly via intraperitoneal injection for a total of four weeks – starting at 8 weeks post AdCre – at a dose of 10mg/kg.

Tissue collection and histology

Lung tissue specimens were collected and processed as described (32). Briefly, the left lung was ligated and snap-frozen for later analysis. The right lung was inflated with 10% neutral buffered formalin (NBF) at 25 cm H₂0 pressure before fixing in NBF overnight. 5-μm paraffin-embedded sections were stained for hematoxylin and eosin (H&E) or immunostained for CD45 (BD Bioscience, San Diego, CA, USA), FoxP3 (eBioscience, San Diego, CA, USA), or CD3 (Serotec, Raleigh, NC, USA) using 3,3”-diaminobenzidine development and hematoxylin counter-staining. Global adjustments to white balance, brightness and/or contrast were made to some photomicrographs using Photoshop (Adobe Systems, San Jose, CA, USA).

Slides were imaged with an Eclipse 80i microscope (Nikon Instruments Inc., Melville, NY, USA), excluding the whole lobe images presented in Figure 1A, which were collected at 20X magnification with an Aperio digital pathology slide scanner (Leica Biosystems, Buffalo Grove, IL, USA). Total lung and tumor area (μm²) were measured from H&E stained slides using NIS-Elements Advanced Research software (Nikon). Results are expressed as % lung occupied by tumor ((area tumor ÷ area lung) × 100). Each lung was also scored for tumor grade, as described (33). FoxP3 and CD3 stained lung lobes (n = 5 mice/genotype) were scored for the presence or absence of cells within three locations: tumor-associated, tumor-infiltrating, or within a lymphoid aggregate (LA).

Figure 1.

Egfr, Kras and Kp53 mice develop lung tumors and associated inflammation. (A, B) All models chronologically develop atypical alveolar hyperplasia, adenoma, and adenocarcinoma 6, 10, and 14 weeks post tumor induction. Normal lung from a non-tumor bearing wild-type mouse is depicted in the lower right corner. H&E sections, scale bars = 2 mm (A) and 500 μm (B), except lower wild-type panel = 1 mm. (C) Spectrum of disease in murine ADCA models. Data are presented as percent of mice exhibiting ≥ 1 indicated lesion at each time point post-induction (n ≥ 5 mice per group). All genotypes exhibited hyperplasia at all time points examined (not shown). Analysis of 14-week Kras ^LSL/+;Trp53^Fl/Fl mice was precluded by early mortality. (D) Percent tumor area was calculated at the indicated time points in a minimum of at least 3 representative lungs from Egfr, Kras, and Kp53 mice. (E) Body mass of tumor-bearing female mice (n ≥ 5) compared to non-tumor bearing littermate controls (n ≥ 3) at each time point post-induction.

Lung tissue single cell preparation

Single-cell suspensions were generated from saline-perfused mouse lungs using mechanical disruption followed by 1 hr digestion at 37°C in RPMI-1640 containing 10% FCS and penicillin/streptomycin along with 80 U/ml DNase, 300 U/ml Collagenase Type 1 (both Worthington Biochemical Corporation, Lakewood, NJ, USA), and 60 U/ml hyaluronidase (Sigma, St Louis, MO, USA). Digested lungs were sheared through a 19g needle, strained through 70-μm nylon mesh, centrifuged, lysed (RBC), washed, strained through 40-μm mesh, centrifuged, and resuspended in DPBS + 2% FCS. Cell viability was determined using trypan blue staining and a TC20™ Automated Cell Counter (BioRad, Hercules, CA, USA). We obtained two SCLC and five ADCA surgical specimens, each with non-adjacent normal lung tissue, using an approved IRB file in association with FHCRC, University of Washington Medical Center, and Northwest BioTrust. Single-cell suspensions were generated using the above digestion protocol.

Flow cytometry

Single-cell suspensions were incubated with 1.0 μg/10⁶ cells Mouse TruStain FcX™ or 1.0 μl/10⁶ cells Human TruStain FcX™ (Biolegend, San Diego, CA, USA) prior to immunostaining. Twenty-seven fluorochrome-labeled antibodies were used among four multicolor panels for mouse specimens (all flow antibodies detailed in Supplemental Table I). Immunostaining was performed for 30 min on ice, protected from light. Dead cells were excluded with Fixable Viability Dye eFluor^® 780 (FVD; eBioscience), per manufacturer's protocol. Stained cells were washed, fixed with IC Fixation Buffer (eBioscience), and stored at 4°C until analysis.

Intracellular cytokine production was assessed using PMA (25 ng/ml), ionomycin (1 μg/ml; both from Sigma), and monensin (1.5 μl/ml; BD Bioscience) stimulation for 5 hr at 37°C, 5% CO₂. An unstimulated sample was incubated without PMA and ionomycin. After stimulation, cells were washed, stained with FVD, fixed, and permeabilized with the Transcription Factor Buffer Set (BD) prior to immunostaining.

Samples were analyzed on a LSR II flow cytometer with FACSDiva™ software (BD), recording ≥ 1×10⁵ events per sample. Data were compensated and analyzed with FlowJo software (TreeStar, Ashland, OR, USA). Gates were defined by fluorescence-minus-one (FMO) samples and verified with appropriate isotype controls. The unstimulated control was used to define cytokine gates. Total cell content was calculated by multiplying the overall number of live cells recovered from each animal (i.e. the trypan-blue-negative hemacytometer count) by the percentage of live cells for each gated parameter. Cytokine-producing T cell subsets were calculated by multiplying the percent parent gate to the previously determined parent population count. Median fluorescence intensity (Med.F.I.) of NKG2D-BV421 and PDL1-BV421 parameters was calculated in FlowJo, with Med.F.I. of the relevant FMO control being subtracted from all experimental values for normalization.

CFSE assay

Splenocytes from wild-type mice were labeled with 50 μM CFSE (Molecular Probes, Eugene, OR, USA), per manufacturer's instructions. 1×10⁶ CFSE-labeled splenocytes were transferred to 6-well tissue culture plates coated with anti-CD3/anti-CD28 antibodies (Biolegend). Cells were incubated with 200 μg homogenate – generated from 10-week Egfr, Kras, or wt lungs – at 37°C, 5% CO₂ for 4 days. Lymphocyte proliferation was determined by harvesting the cells, staining with CD8a-BV421 (Biolegend) and FVD, and measuring ≥ 1×10³ live CD8⁺ cells on a LSR II flow cytometer.

Gene Expression Analysis

Total RNA was isolated from frozen mouse lungs using TRIzol reagent (Life Technologies, Carlsbad, CA, USA) and subsequently purified with the RNeasy Mini Kit (Qiagen, Hilden, Germany). cDNA was generated from 2 μg total RNA using SuperScript II Reverse Transcriptase and Oligo(dT) (Life Technologies). The expression of indicated target genes was analyzed using a StepOnePlus Real Time PCR machine and TaqMan primer/probe sets (Applied Biosystems, Foster City, CA, USA), with all reactions run in triplicate. ΔCt values were calculated using Gapdh as the endogenous housekeeping gene.

Tissue Microarray

A lung ADCA cohort on tissue microarray (TMA), consisting of 135 cases, was obtained from the University of Pittsburgh Cancer Institute. Patient identifiers were removed and the study therefore considered “not human subjects” research (i.e. IRB exempt). Each case was previously annotated as either EGFR mutant (n = 31), KRAS mutant (n = 69), or wild-type for both EGFR and KRAS (n = 35). Formalin-fixed, paraffin-embedded sections were stained with an anti-human CD8 antibody (Abcam #ab4055, Cambridge, MA). Immunohistochemical (IHC)-stained TMA slides were scanned in brightfield at a 20X objective using NanoZoomer Digital Pathology System (Hamamatsu, Hamamatsu City, Japan). Twenty TMA cases (n = 5 EGFR and 16 KRAS) were excluded as lost, non-informative (e.g. poorly stained or non-tumorous), or exhibiting high inter-punch variability (i.e. SEM ≥ 50% of mean). The number of CD8⁺ cells per TMA core was recorded blind to genotype and normalized to core area. Individual core counts from 2 or more replicates were available for most cases, and CD8⁺ cell counts/mm² were averaged across replicates. Cut-off values of low versus high CD8⁺ cell content were defined by the midpoint. Comparison of TMA cohorts was conducted using the Fisher's exact test with one-tailed P value.

Statistical analysis

Significant differences between experimental groups were determined in Prism 6 (GraphPad Software, La Jolla, CA, USA) using unpaired t-tests or, for comparing ≥ 3 groups, one-way ANOVA with indicated post-hoc test for correction of multiple comparisons. Incidence of CD3⁺ and/or FoxP3⁺ cells per lobe was compared between genotypes using the chi-square test. Unless indicated otherwise, data are presented as mean ± SEM. P < 0.05 was considered statistically significant.

RESULTS

Egfr- and Kras-driven ADCA induce a strong inflammatory response

Lung tumor development and associated inflammation were assessed in TetO-Egfr^L858R;Ccsp-rtTA (Egfr), Kras^LSL-G12D (Kras) and Kras^LSL-G12D;Trp53^Fl/Fl (Kp53) mice. To allow for the dynamic assessment of tumor-associated immune responses, lung tumor-bearing animals and appropriate littermate controls were studied over a time course of 6, 10, and 14 weeks post initiation. Consistent with previous studies (24, 26, 34), Egfr, Kras, and Kp53 mice developed neoplastic lesions reminiscent of human disease, from benign hyperplasia and adenomas to malignant ADCA (Fig. 1A-C). Hyperplasia was observed at all time points, although it was less prevalent in Egfr mice than in Kras-mutant mice (data not shown). The introduction of a secondary mutation in Trp53 increased ADCA formation and amplified tumor growth. Accordingly, tumor burden in 10-week Kras mice was significantly less than observed in age-matched Kp53 mice (Fig. 1D; P = 0.0231). Analysis of Kp53 mice at the 14-week time point was precluded by early mortality, but Kras mice remained viable and exhibited 38% lung tumor burden. Body mass measurements, used to non-invasively monitor lung tumor-associated morbidity, correlated with tumor burden for all genotypes (Fig. 1E).

Previous investigations of pulmonary inflammation have been largely based on the assessment of bronchoalveolar lavage (BAL) fluid. Although a well-accepted methodology, BAL studies confine analysis to the airway compartment and limit the number of immune cell types that can be identified. Therefore, to more thoroughly investigate the immune cell composition of the TME, we performed flow cytometric analyses on single-cell suspensions generated from whole lung tissues. Using the gating strategy shown in Figure 2A, we identified 13 unique leukocyte populations defined by 16 antibody markers (see Methods and Supplemental Table I). Kras, Kp53, and Egfr mutant mice all display a robust immune response, as evidence by 3 to 5-fold elevations in total CD45⁺ cell content as compared to normal lung (Fig. 2B-G).

Figure 2.

Flow cytometric analysis of the inflammatory response to lung tumorigenesis. (A) Representative dot plots demonstrate the strategy used to characterize the mouse lung TME. Single cell gates (not shown) were initially applied to remove doublet cells. All subsequent gating utilized a viability marker followed by gating on the CD45⁺ population. Ly6G identified neutrophils (PMN), while remaining myeloid cells were classified as macrophage (Mac; SiglecF⁺CD11c⁺), eosinophil (Eos; SiglecF⁺CD11c⁻) or monocyte (Mono; SiglecF^loCD11b^hiLy6C⁺) from the Ly6G⁻ population. A size gate was applied for lymphocyte analysis followed by staining to identify B cells (CD3⁻CD19⁺), T cells (CD3⁺CD19⁻), and NK cells (CD3⁻CD19⁻NK1.1⁺). T cells were further classified into γδ T cells (γδTCR⁺), CD4 cells (CD4⁺CD8⁻), and CD8 cells (CD8⁺CD4⁻). T cell subtypes were identified as TH1 (CD4⁺IFNγ⁺), Treg (CD4⁺CD25⁺FoxP3⁺), and IL17A-producing T cells (CD3⁺IL17A⁺). Major lung immune cell populations in (B) Egfr mice 10 weeks post tumor induction (n ≥ 6), (C) Egfr at 14 weeks (n ≥ 4), (D) Kras at 10 weeks (n = 14), (E) Kras at 14 weeks (n = 11), (F) Kp53 at 6 weeks (n = 8), and (G) Kp53 at 10 weeks (n ≥ 8), compared to non-tumor bearing control mice (white bars, n ≥ 3). Early and late time points for each genotype are depicted with gray and black bars, respectively. Data for each cell type are displayed as the total number of live cells present within the mouse lung. (H) NKG2D median fluorescence intensity (i.e. Med.F.I.) on NK cells was examined in Egfr, Kras, and Kp53 mutant lungs compared to normal lung controls at indicated time points (n ≥ 3 per group). Asterisks indicate P < 0.05.

Macrophages were by far the most prevalent immune cell type in the lungs of the three murine ADCA models. Ten weeks after starting doxycycline, Egfr mice exhibited 11-fold increases in macrophage content compared to controls (Fig. 2B). Similarly, by 6 weeks post-Cre induction in Kp53 and 10 weeks in Kras animals, total macrophage cell counts had increased 14- and 17-fold (Fig. 2D and F). Of note, macrophage content increased with time only in Kras and Kp53 animals (Supplemental Table II). Since myeloid derived suppressor cells (MDSC) are comprised of monocytic (M-MDSC) and granulocytic (G-MDSC) subsets, we simply defined these cells as monocytes (CD11b⁺Ly6C⁺) and neutrophils (CD11b⁺Ly6G⁺). We observed small but significant differences in neutrophil content in 10- and 14-week Egfr (Fig. 2B and C) as well as 14-week Kras tumor-bearing lungs (Fig. 2E). By 6- and 10-weeks, tumor-associated neutrophil content increased 2- and 5-fold, respectively, in Kp53 animals compared to control (Fig. 2F and G). Indeed, neutrophil counts in Kp53 lungs were statistically increased compared to all other genotypes at the 10-week time point (Supplemental Table III). However, this neutrophil signature may merely reflect overall tumor burden, as statistical analysis of cohorts with approximately matched tumor area (i.e. 6-week Kp53, 10-week Kras, and 14-week Egfr) failed to identify significant differences in pulmonary PMN content.

Impaired natural killer cell function in Kras-driven ADCA

Natural killer (NK) cells are lymphocytes of the innate immune system that play an important role in the host defense against inhaled pathogens (35). NK cell counts in non-tumor bearing lungs were comparable to those of macrophages and granulocytes (Fig. 2). Unlike the myeloid cell expansion observed with ADCA development, however, NK populations remained largely unaltered in tumor-bearing lungs. When significant increases were identified (Fig. 2B, D-G), the fold changes were small, and NK cell counts decreased over time in Kras animals (Supplemental Table II). NK cells are required for effective tumor immunosurveillance (36), but cancer cells have developed multiple strategies to escape NK cell-mediated cytotoxicity, including downregulation of the natural killer group 2, member D receptor (NKG2D, also known as CD314) (37, 38). Surface expression of NKG2D on NK cells was significantly decreased in both Kras and Kp53 tumor-bearing animals at all time points, but exhibited no change in Egfr mice (Fig. 2H). Thus, these murine models of Kras-driven lung ADCA recapitulate an immune escape mechanism previously described in human lung cancer (39).

Oncogenic drivers dictate lymphocyte recruitment into the ADCA microenvironment

The majority of immunotherapeutic approaches are premised on the ability of the adaptive immune system to infiltrate tumors and identify tumor-specific antigens. Therefore, we comprehensively surveyed the lymphocyte subpopulations present within the TME. B cell populations remained unaltered in tumor-bearing Egfr mice (Fig. 2B and C) but increased at least 2-fold in Kras and Kp53 mice at all time points (Fig. 2D-G). CD3⁺ populations were significantly increased in multiple groups (Fig. 2B, D-H), but T cell counts were demonstrably greater in Kras and Kp53 compared to Egfr mice (Supplemental Table III), even after controlling for tumor burden.

CD4⁺ helper T cell expansion was observed in both Kras-driven tumor models but was limited in Egfr mice (Fig. 3A-F). This pattern was reflected in regulatory T cell (Treg) content, which was significantly lower in tumor-bearing lungs from Egfr mice compared to Kras mice (Supplemental Table III). Interestingly, Treg content increased over time in both Kras and Kp53 animals (Supplemental Table II), the only cell type other than macrophages and neutrophils to exhibit such dynamic behavior. Expression of IFNγ by CD4⁺ T cells (TH1 cells) and IL17A by CD3⁺ T cells were also significantly upregulated in Kras and Kp53 animals compared to control at early and late time points (Fig. 3C-F), but exhibited little to no increase in Egfr animals (Fig. 3A and B). Direct comparison of tumor-bearing lungs from all genotypes found higher TH1 and CD3⁺IL17A⁺ cell counts in both Kras-driven models compared to the Egfr mice (Supplemental Table III). Despite repeated attempts, we were unable to identify IL4-positive TH2 cells in our animals (Supplemental Fig. 1); it remains unclear whether this deficiency reflects a true biological absence or, more likely, a technical barrier.

Figure 3.

Oncogenic drivers dictate lymphocyte recruitment into the ADCA microenvironment. CD3⁺ T lymphocyte subpopulations in (A) Egfr mice 10 weeks post tumor induction (n ≥ 6), (B) Egfr at 14 weeks (n = 6), (C) Kras at 10 weeks (n ≥ 10), (D) Kras at 14 weeks (n = 11), (E) Kp53 at 6 weeks (n = 8), and (F) Kp53 at 10 weeks (n ≥ 6), compared to non-tumor bearing control mice (white bars, n ≥ 4). Data for each cell type are displayed as the total number of live cells present within the mouse lung. (G-J) CD3 immunostaining revealed that tumor-associated T cells (G, arrowheads) were commonly located at the edges of neoplastic lesions. Infiltration of CD3⁺ T cells into the tumor mass is indicated with arrows (H); note that large clusters of TA CD3⁺ cells were also present in the periphery of this lesion. CD3⁺ lymphoid aggregates formed within the vicinity of a tumor (I, dashed line, Tu) and were typically associated with airways and/or blood vessels. Although FoxP3⁺ Tregs were seldom observed infiltrating tumor masses (J), they constituted a significant portion of cells present in lymphoid aggregates. Scale bar = 250 μm. (K-L) Quantification of immune cell localization in matched tumor burden 14-week Egfr (n = 6), 10-week Kras (n = 5), and 6-week Kp53 (n = 5) mice. Results are expressed as the percent of lung lobes that contained at least one occurrence of (K, left) tumor-associated CD3⁺ cells, (center) tumor-infiltrating CD3⁺ cells, (right) CD3⁺ cells in lymphoid aggregates, or (L, left) tumor-associated FoxP3⁺ cells, (center) tumor-infiltrating FoxP3⁺ cells, or (right) FoxP3⁺ cells in lymphoid aggregates. (M) Expression of cytokine and chemokine genes in tumor-bearing lungs from 14-week Egfr and 10-week Kras mice (n = 4 per genotype). Data are presented as mean 1/ΔCt with 95% CI. Asterisks indicate P < 0.05.

To assess the spatial relationship between lymphocytes and tumor cells, we performed IHC staining for CD3 and FoxP3 on Egfr, Kras, and Kp53 tumor bearing mice. For each model of lung ADCA, immune cell location was assigned to three categories: 1) tumor-associated (i.e. TA, or peripheral), 2) tumor-infiltrating (TI), or 3) within a neighboring lymphoid aggregate (LA). Examples of each are provided in Figure 3G-J. Staining for CD3 illustrated key differences by genotype, as Egfr mutant mice displayed markedly less tumor-associated CD3⁺ T cell content than Kras and Kp53 specimens (Fig. 3K, left). Tumor-infiltrating CD3⁺ cells were identified in all ADCA models, although they were more prevalent in Kp53 mice (Fig. 3K, center). Similarly, CD3⁺ cells were present in all LAs, but LAs were significantly less common in Egfr mice, whereas they were uniformly present in the other genotypes (Fig. 3K, right). Approximately 15% of lobes from Egfr mice displayed the presence of tumor-associated Tregs, compared to about 40% for Kras mice (Fig. 3L, left). The primary location of Tregs in all genotypes was within LA structures (Fig. 3L, right), with essentially no tumor infiltration observed (Fig. 3L, center). Taken together, the IHC studies confirm the flow cytometry data showing that Egfr mice contain fewer Tregs than the other genotypes and, moreover, demonstrate a paucity of tumor-infiltrating lymphocytes, especially when compared to Kp53 tumors.

CD8⁺ lymphocyte content and function differ by lung ADCA subtype

CD8⁺ T cells are capable of detecting and discriminately eliminating tumor cells (40). Notably, CD8⁺ cell content differed significantly between models driven by mutant Kras versus Egfr. Expansion of CD8⁺ cells was observed at all time points in Kras and Kp53 mice but did not occur in the Egfr-mutant cohort (Fig. 3A-F). Even after controlling for tumor burden, Kras-mutant mice displayed greater CD8⁺ cell content than found in Egfr mice (Supplemental Table III). Therefore, we carried out a number of experiments in attempt to determine the mechanistic basis for this finding and to translate this observation to human disease. Initially, we performed quantitative real-time PCR (qPCR) for key CC and CXC chemokines known to impact immune cell recruitment. Notably, we identified an increase in Cxcl-9 and -10 in Kras mutant lungs compared to Egfr (Figure 3M), which may at least partially explain the differences in lymphocyte content seen between the two lung ADCA models.

In order to translate these findings to human disease, we performed immunohistochemical staining for CD8 on a lung ADCA TMA annotated for KRAS (n = 53 cases) and EGFR (n = 26) mutational status. The frequency of KRAS and EGFR mutations present in the cases displaying high versus low CD8 content (the top and bottom 50% of cases, respectively) were assessed, and EGFR mutations were found to be significantly overrepresented in the CD8 low cohort (Fig. 4A). Specifically, 65.4% of EGFR-mutant cases were scored as CD8-low versus 41.5% of KRAS-mutant cases. Thus, similar to the findings in genetically engineered mouse models presented above, EGFR mutant lung adenocarcinomas exhibit reduced CD8⁺ lymphocyte infiltration in human lung cancers as compared to KRAS mutant lung ADCA.

Figure 4.

CD8⁺ cell content and function correlates with lung ADCA subtype. (A) The number of CD8⁺ cells/mm² was tabulated for each core section present on a TMA of lung ADCA cases annotated for EGFR and KRAS mutational status. Cases were ranked from lowest to highest CD8 content prior to unblinding for genotype. Shown are representative images of EGFR- (left) and KRAS-mutant (right) ADCA. Scale bar = 100 μm. 65.4% (17 of 26) of EGFR-mutant cases were scored as CD8-low versus 41.5% (22 of 53) of KRAS-mutant cases (Fisher's exact test, P = 0.0392). (B) PDL1 Med.F.I. was assessed on pulmonary EpCAM⁺ epithelial cells and macrophages from 10-week Egfr (n = 5) and 14-week Kras mice (n = 4). Expression compared to normal lung (n ≥ 4) is shown in bottom panels. (C) Splenocytes from non-tumor bearing wild-type mice were labeled with CFSE and incubated with protein homogenate generated from wild-type normal lung (NL) or tumor-bearing lung from 10 week Kras or Egfr mice, or with media alone. The cells were subsequently stained with anti-CD8 and a viability marker and analyzed for CFSE intensity; representative plots are shown. For each genotype (n ≥ 3) the percentage of proliferating CD8⁺ T cells was determined after normalization to the media control. Statistical differences were assessed by one-way ANOVA with Tukey's post-test. (D) Flow cytometric analysis of T cell function in Egfr mice compared to wild-type control, gated from single, live, CD45⁺CD3⁺ parent population. Lymphocytes were gated as CD62L⁺CD44⁻ (i.e. Naïve), CD62L⁺CD44⁺ (T_CM, central memory), and CD62L⁻CD44⁺ (T_EM/Eff, effector memory/effector). PD1 expression was assessed on CD8⁺ T cells only. CD8⁺ and CD4⁺ T cell populations were examined at 10 (E, F) and 14 weeks (G, H) post-induction of mutant Egfr (n = 6 tumor-bearing lungs and n ≥ 3 controls per group), respectively. (I) Percent lung tumor area of Kras mice treated with anti-CTLA4 (n = 7) or isotype (n = 6) with representative H&E sections. Scale bar = 500 μm. (J, K) Flow cytometric analysis of CD8⁺ and CD4⁺ T cell populations in anti-CTLA4 and isotype-treated Kras mice (n = 5 per group). Asterisks indicate P < 0.05.

Because CD8⁺ responses can be blunted by immune checkpoint ligands, we measured PDL1 expression on both macrophages and tumor cells (EpCAM⁺) by flow cytometry. Interestingly, although PDL1 expression was decreased in tumor-bearing versus control lungs for both Egfr and Kras mice, there was no difference in PDL1 expression between oncogenic subtypes (Figure 4B). Since other tumor microenvironmental factors can perturb lymphocyte function, we assessed whether the TME of Egfr mice was more suppressive to lymphocyte proliferation than that found in Kras mice. Both Egfr and Kras tumor homogenates reduced CD8⁺ T cell proliferation using CFSE-labeled lymphocytes, but the Egfr homogenates were not found to be more suppressive than Kras (Fig. 4C).

As the intriguing lack of CD8⁺ cell expansion in Egfr mutant tumors suggests a failure of CD8⁺ cell activation in Egfr mice, we performed a detailed assessment of T cell effector and memory status at the 10 and 14-week time points using the markers CD62L, CD44, and PD1 (Figure 4D). No evidence of CD8⁺ T cell activation was observed, as evidenced by lack of an increase in CD8⁺PD1⁺ cells in tumor bearing Egfr mice (Figure 4E, G). Additionally, the proportion of central memory (CD62L⁺CD44⁺) and effector/effector memory (CD62L⁻CD44⁺) CD8⁺ T cells was unchanged, with the majority of these cells still falling into the naïve (CD62L⁺CD44⁻) category in Egfr mice. In contrast, and consistent with the small but significant increase in helper T cells shown in Figure 3A-B, CD4⁺ T cells demonstrated a significant increase in effector/effector memory populations in both 10 and 14-week Egfr mice (Figure 4F, H).

Given the robust increase in CD8⁺ T cell content observed in tumor-bearing lungs from Kras mice compared to control, we elected to assess the status and functionality of the lymphocyte populations in Kras mice using an CTLA4 mIgG2b (clone 9D9) antibody (MedImmune). Although administration of anti-CTLA4 increased the proportion of both CD8⁺ (Figure 4J) and CD4⁺ (Figure 4K) effector/effector memory cells, this cellular phenotype failed to translate into an altered tumor burden in Kras mice (Figure 4I). Thus, despite an activated CD8⁺ T cell response in Kras mutant mice, tumor progression continued unabated.

Role of IL17A-producing γδ T cells in Kras-driven lung ADCA

Given the robust expansion of IL17A⁺ T cells in Kras mutant tumor-bearing mice and the known pro-tumor role of TH17 cells in lung ADCA (41), we elected to examine the cellular sources of IL17A in the lungs of our Kras mutant mouse models. Surprisingly, the predominant source of IL17A was found to be γδ T cells rather than CD4⁺ TH17 cells (Fig. 5A-B). An attempt to interrogate the role of IL17A in lung tumorigenesis by crossing Kras mutant mice to mice lacking the transcription factor for IL17A (i.e. RORγt) (42) was stymied by the frequent occurrence of lymphoid neoplasms in these animals. The spontaneously arising lymphomas exhibited both thymic (Fig. 5C) and splenic (Fig. 5D) involvement as well as diffuse infiltration of the liver (Fig. 5E) and lungs (Fig. 5F). Previous investigations of a related mouse model of RORγt deficiency (43) similarly observed a high incidence of lymphoma but did not indicate the occurrence of the pulmonary metastases that, unfortunately, preclude the use of this model in lung tumorigenesis studies. Further efforts to interrogate the specific role of γδ T cells in Kras mutant lung ADCA revealed that deletion of γδ T cells impacted neither tumor burden (Fig. 5G) nor the immune cell composition of the tumor microenvironment (Fig. 5H).

Figure 5.

IL17A cytokine production and impact in Kras mutant lung ADCA. (A) Representative dot plot demonstrating the relative production of IL17A by γδ T and non-γδ T cells; gated from single, live, CD45⁺CD3⁺ parent population. (B) Quantification of IL17A cytokine's cellular source in 14 week Kras tumor-bearing lungs (n = 5). (C-F) Spontaneously arising lymphomas occurred at high frequency in K.RORγt animals, commonly impacting (C) thymus, (D) spleen, (E) liver, and (F) lung tissues. H&E sections, scale bars = 250 μm, except lung panel (F) = 500 μm. (G) Representative H&E images from 14-week Kras and Kras.Tgd mice. Scale bar = 500 μm. (H) Flow cytometric analysis of lungs from tumor-bearing Kras and Kras.Tgd mice (n = 6 each) at 14 weeks post-induction. Data for each cell type are displayed as the total number of live cells present within the mouse lung. Asterisks indicate P < 0.05.

A paucity of tumor-infiltrating leukocytes in murine and human SCLC

The immune cell composition present within the SCLC TME has not been previously investigated to any extent. Therefore, we profiled the immune content of SCLC, using cohorts of Rbp53 mice infected with AdCre. As described previously (44), lung tumors of mainly neuroendocrine histology arose within 40 to 50 weeks of AdCre administration (Fig. 6A). Flow cytometric analysis of SCLC tumor-bearing lungs (gated as shown in Fig. 2) identified a small but noteworthy inflammatory presence in Rbp53 mice compared to control (Fig. 6B). The total number of CD45⁺ leukocytes was increased 2-fold in SCLC, and tumor-associated CD45⁺ cells were also visible by IHC staining (Fig. 6C). Unlike Kras- and Egfr-mutant animals (Fig. 1A and B), SCLC tumors presented as large, discrete foci, and little hyperplasia was observed. CD45⁺ cells were consequently clustered at the periphery of the SCLC lesions (Fig. 6D), without the inflammatory “field effect” frequently observed in the ADCA models. Few tumor-infiltrating leukocytes were detected (Fig. 6E).

Figure 6.

Tumor-associated inflammation in SCLC. (A) Rbp53 mice develop SCLC tumors within 1 year of AdCre exposure. H&E section, scale bar = 1 mm. (B) Flow cytometric analysis of lungs from tumor-bearing Rbp53 mice (n = 4) and non-Cre exposed control mice (n = 3), approximately 10 months after tumor induction. IHC staining reveals that CD45⁺ immune cells are generally located in the SCLC tumor periphery (arrowheads, C), with some clustering of cells into organized lymphoid structures (arrows, D). Some large CD45⁺ cells, likely macrophages, were observed in alveolar spaces (arrowheads, D) proximal to the tumor. Little to no leukocyte tumor infiltration was observed (E). Scale bars = 1 mm (C) and 100 μm (D, E). (F) The ratio of CD3⁺ T cells to sum myeloid population in SCLC mice was significantly increased compared to three ADCA models, as assessed by one-way ANOVA with Tukey's post-test. (G) The percentage of CD45⁺ live cells present in two resected specimens of human SCLC was greatly reduced compared to five human ADCA specimens. (H) Leukocyte population summary of the flow cytometric analyses, shown as percent of live cells, for a representative normal mouse lung, 10-week Egfr, Kras, and Kp53 ADCA and mouse SCLC are displayed. Abbreviations: NL, non-adjacent normal lung; Tu, tumor. Asterisks indicate P < 0.05.

The major immune component of SCLC was found to be CD3⁺ T lymphocytes (Fig. 6B). This population included a 7-fold increase in the number of γδ T cells and a strong trend toward increased CD4⁺ helper T cells (P = 0.0698). In marked contrast to the ADCA models, expansion of innate immune cells in SCLC tumor-bearing lungs was minimal, with only a 2-fold increase observed in macrophages and a non-significant increase in neutrophils (P = 0.0886). To further investigate this phenomenon, we compared the ratio of CD3⁺ T cells to myeloid cells (macrophages, neutrophils, monocytes, and eosinophils) and found a pronounced lymphocyte-dominant signature in SCLC versus all ADCA models (Fig. 6F). Egfr mice presented with the smallest CD3:myeloid ratio and were also significantly different from Kras mice.

As part of an ongoing study of the immune composition of human lung cancer, we obtained two surgical specimens with confirmed small cell pathology. Since resecting SCLC is rarely clinically indicated, these two specimens represented a unique opportunity to measure the immune cell composition present within the SCLC TME. Therefore, we performed flow cytometry analyses on single cell suspensions generated from these two cases. Similar to the findings in the GEM models, tumor-associated inflammation was discernibly lower in SCLC compared to five ADCA specimens, as CD45⁺ cells comprised a mere 16.2% of live cells in the SCLC resections, compared to 81.9% in ADCA (Fig. 6G).

DISCUSSION

Lung cancer is a heterogeneous disease that can be divided into distinct subtypes based on both molecular and cellular characteristics (45). Herein we tested the hypothesis that these subtypes dictate the inflammatory response to cancer by immune-profiling the lung TME in a mouse model of SCLC and in three molecularly distinct models of NSCLC (summarized in Fig. 6H). We found that Egfr and Kras mutations give rise to distinct immune responses characterized by differential expansion of B cells, CD8⁺ T cells, Tregs, and IL17A-producing T cell populations. Although loss of Trp53 promoted malignancy, it had minimal effect on immune cell composition within the Kras TME. We further demonstrate that SCLC possesses an overall reduced inflammatory presence compared to NSCLC, and one in which lymphocytes predominate over myeloid lineage cells. Mutational profile and histological origin therefore actively shape the immune contexture of lung cancer, a finding that may have important clinical ramifications.

The strong macrophage field responses that occur in mutant Kras- and Egfr-driven mouse ADCA are seldom observed in human lung cancer and represent a potential limitation of these GEM models. In Kras mice, this phenomenon of alveolar macrophages flooding the airspaces has been likened to desquamative interstitial pneumonitis (DIP), a rare interstitial lung disease with similar pathology (46). Moreover, the conditional mouse models studied herein utilize varied induction methodologies, i.e. adenoviral Cre recombinase and doxycycline-regulated transgene expression. Although we cannot exclude potential confounding effects of viral infection or doxycycline consumption on the tumor immune response, we have attempted to correct for these variables by using adenovirus- or doxycycline-exposed wild-type animals for the relevant control cohorts.

Few gene-specific investigations of the mouse lung TME have been conducted, and no comprehensive effort has been made to compare and contrast different molecular and histological models of lung cancer. Our results do, however, validate findings from several earlier reports on lung tumor-associated inflammation. We were unsurprised to identify macrophages as the dominant immune cell presence in mouse ADCA given that strong tumor-associated macrophage responses have been previously identified in mutant Egfr (21) and Kras (19, 41, 47) mouse lung tumor models. Likewise, as we describe herein, neutrophils have been shown by others to be a modest but important component of Kras- but not Egfr-driven mouse lung ADCA (19, 21, 41). Since the majority of prior data in this regard relied on BAL cell counts, we employed flow cytometry to better define the quality of the immune response. Using this methodology, we found that recruitment of lymphoid lineage cells varies greatly between ADCA models, as Egfr^L858R mice exhibited a paucity of B cells, CD8⁺ T cells, Tregs, and IL17A-producing T cells when compared to the Kras and Kras;Trp53 lung TME.

The most clinically relevant finding in this study is the lack of a CD8⁺ lymphocyte response in both Egfr mutant mice and EGFR mutant human lung ADCA specimens when compared to KRAS mutant counterparts. Markers of effector/memory status failed to reveal any evidence of CD8⁺ T cell activation or differentiation in Egfr mice. This suggests that EGFR mutation may not elicit an antigen-driven immune response. Although the same could be said for mutant KRAS, we were able to demonstrate an increase in activated and effector-memory CD8⁺ cells in the Kras mouse model. Furthermore, tumor-infiltrating lymphocyte (TIL) populations that specifically target mutant KRAS^G12D have recently been identified in colon cancer (48). Despite the presence of activated CD8⁺ cells, tumor growth continued in Kras mice even with the addition of an anti-CTLA4 therapeutic antibody. Our interpretation of this data is that increases in activated CD8⁺ cells within the TME in Kras mutant mice will not impact tumor growth unless they are tumor reactive. Specifically in this case, tumor-derived chemokines, such as Cxcl-10 are likely to increase the number of tumor-associated lymphocytes. Whereas anti-CTLA4 antibody therapy drove an increase in effector T cells, these cells would not be expected to reduce tumor burden if they did not recognize a tumor-associated antigen. It is also possible that anti-CTLA4 monotherapy will prove ineffective but that combined immunotherapeutic regimens (e.g. anti-CTLA4 + anti-PDL1) would prove effective. With respect to human lung ADCA, the association of EGFR mutant cancers with never-smoker status would suggest that these tumors are genetically simplified and, unlike smoking-associated KRAS mutant cancers, may not possess sufficient mutational burden to harbor neo-antigens (49, 50). The mouse models described herein were not exposed to cigarette smoke or other carcinogens, eliminating this proposed explanation for the differential CD8⁺ responses we observed. At this time, however, we cannot exclude the possibility that KRAS mutant human and mouse lung ADCA have realized the same phenotype of high CD8⁺ T cell infiltration through different mechanisms of action.

Tregs and IL17A⁺ T cells have emerged as important cell populations in multiple mouse models of cancer (41, 51, 52), and both cell types exhibited notable patterns of expression or localization in the murine ADCA models. Although TGFβ and IL6 generate gradients leading independently to Treg or TH17 differentiation, we observed concurrent increases in both populations in Kras and Kp53 mutant tumor-bearing lungs. Notably, we found the major source of IL17A in Kras mutant ADCA to be γδ T cells and not TH17 cells. Since IL17A deficiency has been previously shown to reduce lung tumor growth (41) and IL17A-producing γδ T cells are known to promote breast (53) and pancreatic neoplasia (52), these findings suggested to us that expansion of a pulmonary IL17A-producing γδ T cell subset might overshadow the tumor-surveillance role traditionally ascribed to γδ T cells (54). However, Kras mutant, γδ T cell-deficient mice displayed equivalent lung tumor burden and strikingly similar immune profiles to their γδ T cell-competent counterparts. Therefore, although IL17A is an important signaling component in the immune landscape of lung ADCA, IL17A⁺ γδ T cells appear to contribute little to the process of lung tumorigenesis.

Tregs, in contrast, appear to play a particularly important role in the Kras mutant lung TME, as they were the only non-myeloid lineage population to expand over the course of tumor development. Moreover, Tregs display a unique anatomic location in lung ADCA. They are rarely associated with the tumor itself but are instead frequently found within lymphoid aggregate structures that are believed to function as a local site of antigen presentation and have been correlated with good clinical outcomes in NSCLC (55). The presence of Tregs in these structures has recently been shown to be detrimental to the generation of an effective immune response in murine lung ADCA (56), highlighting the importance of Treg targeting strategies for the clinical management of lung cancer patients.

The immune cell composition of SCLC has not been well studied. Our findings in Rbp53 mice point to a less robust but more lymphocyte-predominant host immune response to murine SCLC than to ADCA. Moreover, when we analyzed the immune cell content of two human SCLC cases, we identified a strikingly similar immune profile of sparse CD45⁺ cell content. Although we acknowledge the inherent limitations of n = 2 studies, patients diagnosed with SCLC seldom undergo lung resection (57), making access to such specimens exceedingly rare. Solid tumor malignancies demonstrating the best responses to current ICI therapies have been those with high mutational burdens and/or a history of cigarette smoke exposure (e.g. melanoma, head and neck SCC, and urinary bladder cancer), both traits common to SCLC (2). In light of these correlations, it is tempting to speculate that SCLC patients would exhibit good responses to ICI therapy. However, initial reports suggest that success rates to anti-PD1 therapy in SCLC are at best only comparable to NSCLC (58, 59). Our preliminary findings with respect to the immune cell composition in SCLC suggest that the presence of redundant immune suppressive factors would not be a likely source of treatment failure, which is almost certainly an important concept in NSCLC. These findings point to potentially unique features of the SCLC TME (e.g. matrix protein composition) that will require additional study.

A robust CD45⁺ immune response was observed in both the ADCA mouse models and human lung ADCA patients. Leukocytes account for nearly 75% of total cellular content in human ADCA, an even greater proportion than we identified in mice (~55%). With the exception of the aforementioned exaggerated macrophage responses, the robust and diverse immune landscape observed in GEM models of ADCA approximates that seen in human lung cancers (60). Driving mutations, such as in Egfr and Kras, substantially impact the TME through the release of bioactive molecules, which is very well reflected in these GEM models. One potential shortcoming of these models is the genetic simplicity of the tumors, which rely on a single driving mutation. In contrast, human NSCLC harbors an average of ~150 distinct mutations per case (61). Efforts are underway to construct mouse models of cancer that harbor a greater abundance of single nucleotide variations and, thus, potential neoantigens. However, EGFR mutant cancers in non-smokers are typically genetically simplified (5), such that the Egfr mutant mice described herein likely constitute an excellent representation of both the genetic component of the cancer cell and the immune composition of the TME.

The emergence of immune checkpoint inhibitors has been a tremendous advance, but unfortunately the majority of lung cancer patients in clinical trials have failed to respond to ICI therapy (8-11). In addition to the PD-1/PD-L1 based drugs currently in use, novel ICI agents are likely to emerge in the near future. Our findings argue that the cellular and molecular characteristics of lung cancer may provide an important framework for patient-targeted immunotherapy. Furthermore, preclinical testing of future immunotherapy agents should be performed in genetically and histologically diverse model systems to enable the assessment of tumor subtype-specific efficacy.

Abbreviations

ADCA

adenocarcinoma

AdCre

adenoviral Cre recombinase

BAL

bronchoalveolar lavage fluid

GEM

genetically engineered mouse

ICI

immune checkpoint inhibitor

NSCLC

non-small cell lung cancer

PMN

polymorphonuclear cell

SCLC

small cell lung cancer

TMA

tissue microarray

TME

tumor microenvironment

Treg

regulatory T cell