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. 2024 Sep 18;12(9):e009126.
doi: 10.1136/jitc-2024-009126.

Spatial colocalization and combined survival benefit of natural killer and CD8 T cells despite profound MHC class I loss in non-small cell lung cancer

Remziye E Wessel  1 , Nardin Ageeb  2 , Joseph M Obeid  3 , Ileana S Mauldin  4 , Kate A Goundry  1 , Gabriel F Hanson  1 , Mahdin Hossain  5 , Chad Lehman  5 , Ryan D Gentzler  6 , Nolan A Wages  7 , Craig L Slingluff Jr  4 , Timothy N J Bullock  5   8 , Sepideh Dolatshahi  9   5 , Michael G Brown  5   10   11   12
Affiliations

Spatial colocalization and combined survival benefit of natural killer and CD8 T cells despite profound MHC class I loss in non-small cell lung cancer

Remziye E Wessel et al. J Immunother Cancer. .

Abstract

Background: Major histocompatibility complex class I (MHC-I) loss is frequent in non-small cell lung cancer (NSCLC) rendering tumor cells resistant to T cell lysis. NK cells kill MHC-I-deficient tumor cells, and although previous work indicated their presence at NSCLC margins, they were functionally impaired. Within, we evaluated whether NK cell and CD8 T cell infiltration and activation vary with MHC-I expression.

Methods: We used single-stain immunohistochemistry (IHC) and Kaplan-Meier analysis to test the effect of NK cell and CD8 T cell infiltration on overall and disease-free survival. To delineate immune covariates of MHC-I-disparate lung cancers, we used multiplexed immunofluorescence (mIF) imaging followed by multivariate statistical modeling. To identify differences in infiltration and intercellular communication between IFNγ-activated and non-activated lymphocytes, we developed a computational pipeline to enumerate single-cell neighborhoods from mIF images followed by multivariate discriminant analysis.

Results: Spatial quantitation of tumor cell MHC-I expression revealed intratumoral and intertumoral heterogeneity, which was associated with the local lymphocyte landscape. IHC analysis revealed that high CD56+ cell numbers in patient tumors were positively associated with disease-free survival (HR=0.58, p=0.064) and overall survival (OS) (HR=0.496, p=0.041). The OS association strengthened with high counts of both CD56+ and CD8+ cells (HR=0.199, p<1×10-3). mIF imaging and multivariate discriminant analysis revealed enrichment of both CD3+CD8+ T cells and CD3-CD56+ NK cells in MHC-I-bearing tumors (p<0.05). To infer associations of functional cell states and local cell-cell communication, we analyzed spatial single-cell neighborhood profiles to delineate the cellular environments of IFNγ+/- NK cells and T cells. We discovered that both IFNγ+ NK and CD8 T cells were more frequently associated with other IFNγ+ lymphocytes in comparison to IFNγ- NK cells and CD8 T cells (p<1×10-30). Moreover, IFNγ+ lymphocytes were most often found clustered near MHC-I+ tumor cells.

Conclusions: Tumor-infiltrating NK cells and CD8 T cells jointly affected control of NSCLC tumor progression. Coassociation of NK and CD8 T cells was most evident in MHC-I-bearing tumors, especially in the presence of IFNγ. Frequent colocalization of IFNγ+ NK cells with other IFNγ+ lymphocytes in near-neighbor analysis suggests NSCLC lymphocyte activation is coordinately regulated.

Keywords: Lung Cancer; Major histocompatibility complex - MHC; Natural killer - NK; T cell; Tumor infiltrating lymphocyte - TIL.

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Conflict of interest statement

Competing interests: CLS: Research support to the University of Virginia from Celldex (funding, drug), Merck (funding, drug), Theraclion (device staff support); Funding to the University of Virginia from Polynoma for PI role on the MAVIS Clinical Trial; Funding to the University of Virginia for roles on Scientific Advisory Boards for Immatics and CureVac. CLS also receives licensing fee payments through the UVA Licensing and Ventures Group for patents for peptides used in cancer vaccines. RDG: Research support to the University of Virginia from Pfizer, Amgen, Chugai, Merck, AstraZeneca, Janssen, Daiichi Sankyo, Alliance Foundation, Takeda, ECOG/ACRIN, Jounce Therapeutics, Bristol Myers Squibb, SWOG, Helsinn, Dizal Pharmaceuticals, and Mirati. RDG received payment for service on Scientific Advisory Boards including AstraZeneca, Takeda, Gilead, Janssen, Mirati, Daiichi Sankyo, Sanofi, Oncocyte, Jazz Pharmaceuticals, Blueprint Medicines, and Merus.

Figures

Figure 1
Figure 1. MHC-I expression exhibits intratumor and intertumor heterogeneity and correlates with lymphocyte occupancy. (A,D) MHC-I is variably expressed in tumors and across AdenoCA (A) and SCC (D) patients. (B,E) β2M expression correlates positively with MHC-I expression in AdenoCA (B) and SCC (E). (C,F) The heatmaps show Spearman correlations (R) among IHC features in AdneoCA (C) and SCC (F). Insignificant correlations (p>0.05) are shaded white; identity correlations are shaded gray. AdenoCA, adenocarcinoma; CT, central tumor; IHC, immunohistochemistry; MHC, major histocompatibility complex; PT, peripheral tumor; SCC, squamous cell carcinoma.
Figure 2
Figure 2. Survival probability increases with increasing CD8+ and CD56+ lymphocyte infiltrates. Kaplan-Meier analysis predicts DFS or OS with respect to tumor cell MHC-I HC expression (A,B), CD56+ cell counts (C,D), CD8+ cell counts (E,F), or coincident CD56+ and CD8+ counts (G,H) averaged between CT and PT. CT, central tumor; DFS, disease-free survival; MHC-I, major histocompatibility complex class I; OS, overall survival; PT, peripheral tumor.
Figure 3
Figure 3. mIF imaging reveals extent of MHC-I HC expression variation in resected patient tumor tissues. (A) Representative images exemplify MHC-I loss in AdenoCA and SCC. (B) Histograms of (%) MHC-I+ tumor cells in each region of AdenoCA and SCC. (C) The (%) MHC-I+ tumor cells in each region per patient for AdenoCA and SCC. AdenoCA, adenocarcinoma; MHC-I, major histocompatibility complex class I; mIF, multiplexed immunofluorescence; SCC, squamous cell carcinoma.
Figure 4
Figure 4. Tumor-infiltrated lymphocytes and IFNγ expression are associated with high tumor cell MHC-I expression. OPLSDA models discriminate between tumor regions with MHC-I+ tumor cell densities (cells/mm2) above or below the median in AdenoCA (A–D) and SCC (E–H). Significance was determined by a permutation test (p<0.001). (A,E) X scores plot, where each point represents one region projected onto latent variables 1 and 2 (LV1&LV2). (B,F) VIP scores are shown artificially oriented in the direction of loadings on LV1. |VIP|>1 indicates variables with greater than average influence on the separation between groups. (C,G) Spearman correlations among immunologic features in tumor (T) and stroma (S). Insignificant correlations (p>0.05) are shaded white, identity correlations are shaded gray. (D,H) Univariate comparisons between model features. Wilcoxon rank sum test with Benjamini-Hochberg correction (*p<0.05; **p<0.01; ***p<0.0001). Only features with padj<0.05 are shown. (I) Representative image shows variation in lymphocyte occupancy and IFNγ staining in MHC-I– (top) or MHC-I+ (bottom) regions of the same tumor. AdenoCA, adenocarcinoma; CV, cross-validation; MHC-I, major histocompatibility complex class I; OPLSDA, Orthogonalized Partial Least Squares Discriminant Analyses; SCC, squamous cell carcinoma; VIP, variable importance in projection.
Figure 5
Figure 5. NK cells and CD8 T cells colocalize in areas with IFNγ staining. Representative images show NK cells and CD8 T cells clustered near IFNγ in three patient tumors.
Figure 6
Figure 6. IFNγ+ NK cells and IFNγ+ CD8 T cells associate with other activated lymphocytes and MHC-I+ tumor cells. OPLSDA models discriminate IFNγ+/– NK cells (A–C) and IFNγ+/– CD8 T cells (E–G). Significance was determined by a permutation test (p<0.001). (A,E) X scores plot, where each point represents one region projected onto latent variables 1 and 2 (LV1&LV2). (B,F) VIP scores are shown artificially oriented in the direction of loadings on LV1. |VIP|>1 indicates a variable with greater than average influence on the separation between groups. (C,G) Univariate comparisons between model features. Wilcoxon rank sum test with Benjamini-Hochberg correction (*p<1×10−27; **p<1×10−30; ***p<1×10−50). (D,H) The average counts of MHC-I+ tumor cell neighbors for IFNγ+/– NK cells (D) or IFNγ+/– CD8 T cells (H) in tumor (T) or stroma (S) regions. (I) Representative mIF image showing a cluster of lymphocytes colocalized with IFNγ in an MHC-I– tumor nest. (J) The K function plotted against increasing radii for IFNγ+ NK cells and IFNγ+ CD8 T cells as the target cell and either MHC-I+ (red solid line) or MHC I– (red dashed line) center cells. Gray shading, 95% confidence interval (CI). Black line, Poisson (null) distribution. CV, cross-validation; MHC-I, major histocompatibility complex class I; mIF, multiplexed immunofluorescence; OPLSDA, Orthogonalized Partial Least Squares Discriminant Analysis; VIP, variable importance in projection.
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