Functional status and spatial interaction of T cell subsets driven by specific tumor microenvironment correlate with recurrence of non-small cell lung cancer

Abstract

Background: The anti-tumoral or pro-tumoral roles of CD4⁺ and CD8⁺ T cells typify the complexity of T cell subsets function in cancer. In the non-small cell lung cancer (NSCLC), the density and topology of distinct T cell phenotypes at the tumor center (TC) versus the invasive margin (IM) are largely unknown. Here, we investigated T cell subsets density and distribution within TC and IM regions in NSCLC and its impact on the prognosis.

Methods: We performed multiplex immunofluorescence using a tissue microarray of samples from 99 patients with locally advanced NSCLC to elucidate the distributions of tumor cell, T cell subpopulations (CD4/conventional CD4/regulatory CD4/CD8/cytotoxic CD8/pre-dysfunctional CD8/dysfunctional CD8), microvessel density (MVD), cancer-associated fibroblasts (CAFs) and hypoxia-inducible factor-1α (HIF-1α) in TC and IM tissues. Cell-to-cell nearest neighbor distances and interactions were analyzed using the phenoptrreports R package. Cox regression was used to evaluate the associations between T cell subsets density and proximity to tumor cells and recurrence-free survival (RFS). Correlations between different cell subsets were examined by Spearman's or Kruskal-Wallis tests.

Results: In the locally advanced NSCLC, the proportion of tumor cells and CAFs in IM is lower than in the TC, while MVD, CD4⁺, and CD8⁺ T lymphocytes were increased, and tumor cells were closer to T lymphocytes and their subsets. The density and proximity of CD4⁺ and CD8⁺ T cells in the TC and IM regions were not associated with RFS, but in the IM area, increased density of dysfunctional CD8 and closer regulatory CD4 to tumor cells were independent risk factors for recurrence (HR were 3.536 and 2.884, respectively), and were positively correlated with HIF-1α⁺CD8 (r = 0.41, P = 0.000) and CAFs (P = 0.017), respectively.s.

Conclusions: In locally advanced NSCLC, the functional status of T cells in the IM region is closely related to recurrence. The density of dysfunctional CD8 and the proximity of regulatory CD4 to tumor cells were independent risk factors for recurrence, and are positively correlated with the hypoxia response of CD8⁺ T cells and CAFs. Targeting hypoxia or CAFs is expected to further sensitize therapy.

Keywords: CD4; CD8; functional status; lung cancer; prognostic; spatial interaction.

Figure 1

Multiplex immunofluorescence (mIF) analysis of human locally advanced NSCLC. Examples of mIF images (A, B) and summary of each defined cell phenotype (C, D) and associated markers from the CD4 and CD8 panel. Scale bar, 25 μm.

Figure 2

The heterogeneity of TC and IM microenvironment in locally advanced NSCLC. (A) Representative composite images of TC and IM from an SCC patient. Scale bar, 100 μm. (B) Relative distribution of cell phenotypes in TC and IM. Relative distribution analysis of CD4 (C) or CD8 (D) subpopulations. Scale bar, 100 μm. Data is presented as the median. P values were computed by the Kruskal-Wallis test. *P < 0.05, **P < 0.01, ***P < 0.001.

Figure 3

High IM-CD8⁺ Tdys density was associated with the recurrence of the locally advanced NSCLC, and HIF-1α⁺CD8 may contribute to the accumulation of CD8⁺ Tdys. (A) Kaplan–Meier curves illustrate the associations between the expression levels of IM-CD8⁺ Tdys (high vs low) and the RFS of locally advanced NSCLC. P-values reflect comparisons of two groups by univariate analysis, using the log-rank test. (B) Representative image for poor RFS (left) and long RFS (right). Scale bar, 100 μm. (C–F) The heterogeneity of HIF-1α (C), HIF-1α⁺CK (D), HIF-1α⁺CD4 (E), and HIF-1α⁺CD8 (F) density between TC and IM regions. Scale bar, 100 μm. Significance was determined using the Mann-Whitney test, all data are presented as the median and interquartile ranges. (G) Spearman correlation between CD8⁺ Tdys and HIF-1α, MVD, CAFs density in the IM region.

Figure 4

Nearest neighbor distance (NND) analysis of T cells to tumor cells. (A, B) NND was calculated from each tumor cell to their nearest CD4 or CD8 (left) and individual value plot of the average NND (right). (C, D) NND was calculated from each tumor cell to their nearest CD4⁺ Tcon or CD4⁺ Treg (left) and individual value plot of the average NND (right). (E, F) NND was calculated from each tumor cell to their nearest CD8⁺ Tpre or CD8⁺ Tdys (left) and individual value plot of the average NND (right). Scale bar, 50 μm. P values were calculated with the Mann-Whitney test, and all data are presented as the median and interquartile ranges.

Figure 5

Higher IM-CD4⁺ Treg proximity to tumor cells was associated with significantly shorter RFS, and CAFs recruit CD4⁺ Treg infiltration. (A) Schematic diagram of proximity, the black line represents the interaction between tumor cells and T cells. (B) Kaplan-Meier survival analyses of the IM-CD4⁺Treg proximity. P-values reflect comparisons of two groups by univariate analysis, using the log-rank test. (C) Representative image for poor RFS (left) and long RFS (right). Pseudocolor illustrating Pan-CK (cyan), CD4 (green), FoxP3 (orange), and DAPI (blue) staining (composite image). The white line indicates that tumor cells and Treg are within 30 μm of each other (proximity image). Scale bar, 50 μm. (D) Schematic representing the parameters analyzed in (E, F). (E, F) The proximity of CAFs within 30 μm of cancer cells for each patient separated by cancer cells high or low adjacent CD4⁺ Treg. Pseudocolor illustrating Pan-CK (cyan), α-SMA (white), and DAPI (blue) staining (composite image). The white line indicates that tumor cells and CAFs are within 30 μm of each other (proximity image). Scale bar, 50 μm. P values were calculated with the Mann-Whitney test, and all data are presented as the median and interquartile ranges.