Lung adenocarcinoma-derived IFN-γ promotes growth by modulating CD8+ T cell production of CCR5 chemokines

Abstract

Because the lung is a mucosal barrier organ with a unique immunologic environment, mechanisms of immunoregulation in lung cancer may differ from those of other malignancies. Consistent with this notion, we found that CD8+ T cells played a paradoxical role in facilitating, rather than ameliorating, the growth of multiple lung adenocarcinoma models. These included spontaneous, carcinogen-induced, and transplantable tumor cell line models. Specifically, we found that CD8+ T cells promoted homing of CD4+Foxp3+ Tregs to the tumor bed by increasing the levels of CCR5 chemokines in the tumor microenvironment in an IFN-γ- and TNF-α-dependent manner. Contrary to their canonical role, these Th1 cytokines contributed to accelerated growth of murine lung adenocarcinomas, while suppressing the growth of other malignancies. Surprisingly, lung cancer cells themselves can serve as a dominant source of IFN-γ, and deletion of this cytokine from cancer cells using CRISPR/Cas9 decreases tumor growth. Importantly for translational applications, in patients with lung cancer, a high level of IFN-γ was also found at both the mRNA and protein levels. Our data outline what we deem a novel and previously undefined lung cancer-specific immunoregulatory pathway that may be harnessed to tailor immune-based therapy specifically for this malignancy.

Keywords: Adaptive immunity; Cell biology; Immunology; Lung cancer; Oncology; T cells.

Figure 1. CD8⁺ T cells accelerate lung adenocarcinoma growth.

(A) Number of tumors visible in the lungs of Kras G12D mice at age 12 weeks with and without CD8 depletion. Histological micrographs (original magnification, ×0.5 [low-power] and ×20 [high-power]) of lungs are below the graph, with arrows pointing to tumor foci (H&E staining). n = 14 per group. (B) Lung weights of i.v. injected LLC lung cancer and B16 melanoma cell lines in B6 versus B6^CD8dep mice. Micrographs of lungs are shown above the graph (n = 10 per group of LLC; n = 8 per group of B16). (C) Tumor growth curves in B6 and B6^CD8dep bearing subcutaneously injected non–lung tumor cell lines including EG7 lymphoma, B16-F10 melanoma, MC38 colon cancer, and CT26 colon cancer. (D) Tumor growth curves in B6 and B6^{CD8 dep} mice bearing subcutaneously injected lung tumor cell lines including LLC, CMT64 lung cancer, and LKR13 lung cancer. Statistical analysis used Student’s unpaired, 2-tailed t test with Welch’s correction. *P < 0.05, **P < 0.01, and ***P < 0.001. NS = P > 0.05. Data represent the mean ± SEM.

Figure 2. Phenotype of CD8⁺ T cells in murine melanoma compared with lung cancer.

(A) Flow cytometric analysis of the tumor beds of LLC- and B16-bearing mice 14 days after tumor injection. Representative flow plots (n = 5). (B) Histological analysis of flank tumors of LLC- and B16-bearing mice stained for DAPI, CD8, and CD31 with a merged image (all ×10 magnification) and a high-power image (original magnification, ×40). White arrow delineates blood vessel. Scale bar: 100 μm; n = 4 per group. (C) Flow cytometric analysis of CD8⁺ T cell phenotype in the tumor beds of LLC- and B16-bearing mice. Representative flow plots (n = 5). (D) Flow cytometric analysis of CD8⁺ T cell exhaustion markers and ovalbumin-specific T cell receptors in the tumor bed of LLC^ova- and B16^ova-bearing mice. n = 5 per group. (E) Representative histograms of transcription factor expression on CD8⁺ T cells found in the tumor bed of LLC- and B16-bearing mice. Two experiments with 11 per group total. Control isotype expression of each marker is denoted by a light gray peak for all representative histograms. Statistical analysis used Student’s unpaired, 2-tailed t test with Welch’s correction. **P < 0.01. NS = P > 0.05. Data represent the mean ± SEM.

Figure 3. CD8⁺ T cells promote Treg migration to the tumor microenvironment.

(A) Flow cytometric analysis of the tumor bed (left) and draining lymph nodes (right) of LLC- or B16-bearing mice with and without CD8 depletion. (B) Representative flow cytometric analysis of the T cell population within the tumor bed of LLC-bearing mice (n = 2). (C) Ratio of the percentage of CD4⁺Foxp3⁺GFP⁺ cells found in CD8⁺ T cell depleted mice to nondepleted mice in both the tumor bed and draining lymph node of tumor-bearing B6CD4^–/– mice that received adoptive transfer of Tregs 10 days prior. (D) Luminex analysis for chemokines in tumor bed (top) and draining lymph node (bottom) of flank LLC^ova- and B16^ova-bearing mice with and without CD8⁺ T cell depletion. (E) Tumor growth curves of LLC-bearing mice that received no depletion or treatment with maraviroc, CD8 depletion alone, maraviroc treatment, or both CD8 depletion and maraviroc treatment. (F) Percentage of CD4⁺Foxp3⁺ cells found in the tumor bed of LLC-bearing mice treated with or without maraviroc. Two-way ANOVA was used for (D) and (E), followed by unpaired, 2-tailed t test with Welch’s correction. Other plots were analyzed by Student’s unpaired, 2-tailed t test with Welch’s correction. *P < 0.05, **P < 0.01, and ***P < 0.001. Data represent the mean ± SEM.

Figure 4. Lung tumor microenvironment is enriched for IFN-γ.

(A) MFI of chemokines produced by CD8⁺ T cells and CD11b⁺ myeloid cells in the tumor bed of LLC^ova-bearing mice either with or without IFN-γ and TNF-α neutralization. (B) Cytoplex analysis of flank tumor beds indicating fold difference of cytokine levels for B6 and B6^CD8–/– mice bearing LLC^ova or B16^ova. All data were normalized for each cytokine based on the LLC^ova-bearing B6^CD8–/– mouse group, which was set as 1. (C) Ifng mRNA levels from samples in TCGA for patients with melanoma, colon, pancreatic, or lung cancer that received no preoperative treatment. (D) Matched tissue samples (tumor and normal) from patients at the University of Maryland School of Medicine taken during resection prior to any preoperative treatment (colorectal cancer, n = 7 patients; pancreatic cancer, n = 6 patients; and lung cancer, n = 11 patients). (E) Tumor growth of B16^ova and LLC^ova flank tumors in B6 mice with and without depletion of IFN-γ and TNF-α. Two-way ANOVA was used for (B), followed by unpaired, 2-tailed t test with Welch’s correction. Other plots were analyzed via Student’s unpaired, 2-tailed t test with Welch’s correction, with exception of Figure 4D, for which a paired, 2-tailed t test was used. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001. NS = P > 0.05. Data represent the mean ± SEM.

Figure 5. Lung cancer cells produce IFN-γ.

(A) Flow cytometric analysis of the tumor beds of mice subcutaneously injected with either LLC lung cancer or B16 melanoma to determine IFN-γ– and TNF-α– producing cells. The CD45⁺IFN-γ⁺ population is further stratified into CD8⁺ and CD4⁺ T cell expression and CD11b expression. Representative flow plots of 5 per group. (B) Schematic of the GFP-actin mouse model used to differentiate host (GFP⁺) cells and subcutaneously injected tumor cells (GFP^–). Representative gating strategy is depicted on the right (n = 16). (C) GFP-actin mice were subcutaneously injected with either LLC, CMT64 lung cancer, B16 melanoma, or MC38 colon cancer cells. Representative plots showing live cells gated on IFN-γ⁺ cells with control isotype expression of IFN-γ in the light gray peaks (top). GFP expression within the IFN-γ⁺ population was analyzed (bottom). n = 4 per tumor type. Student’s unpaired, 2-tailed t test with Welch’s correction was used in statistical analyses. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001. NS = P > 0.05. Data represent the mean ± SEM.

Figure 6. Lung cancer production of IFN-γ accelerates tumor growth.

(A) Percentage of live cells expressing the IFN-γ receptor after 72 hours in culture. (B) Relative expression of the Ifng gene in lung and non–lung cancer cell lines after 24 hours of IFN-γ treatment at 10 ng/mL compared with no treatment. (C) Protein expression of IFN-γ represented by IFN-γ MFI via flow cytometric analysis 24 hours after IFN-γ treatment compared with cells that did not receive IFN-γ treatment. (D) Representative flow cytometric plots of cell populations within the tumor beds of LLC-bearing and Ifng-KO LLC–bearing mice (left). Percentage of IFN-γ⁺CD45^– cells in these tumor beds (right). (E) ELISA of TNF-α levels in the tumor bed of parental LLC- and Ifng-KO LLC–bearing mice. (F) Tumor growth curves of LLC and Ifng-KO LLC with and without CD8 depletion. (G) Percentage of CD4⁺Foxp3⁺ cells found in the tumor bed of parental LLC- and Ifng-KO LLC–bearing mice. Two-way ANOVA was used for (F), followed by unpaired, 2-tailed t test with Welch’s correction. Other plots were analyzed by Student’s unpaired, 2-tailed t test with Welch’s correction. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001. NS = P > 0.05. Data represent the mean ± SEM.