The tumor microenvironment of non–small cell lung cancer impairs immune cell function in people with HIV
Shruti S. Desai, … , Kurt Schalper, Brinda Emu
Shruti S. Desai, … , Kurt Schalper, Brinda Emu
Published June 3, 2025
Citation Information: J Clin Invest. 2025;135(14):e177310. https://doi.org/10.1172/JCI177310.
View: Text | PDF
Research Article AIDS/HIV Immunology Oncology

The tumor microenvironment of non–small cell lung cancer impairs immune cell function in people with HIV

Abstract

Lung cancer is the leading cause of cancer mortality among people with HIV (PWH), with increased incidence and poor outcomes. This study explored whether the tumor microenvironment (TME) of HIV-associated non–small cell lung cancer (NSCLC) limits tumor-specific immune responses. With a matched cohort of NSCLC samples from PWH and from people without HIV (PWOH), we used imaging mass cytometry, a linear mixed-effects model, and an artificial intelligence–based (AI-based) PageRank mathematical algorithm based on spectral graph theory to demonstrate that HIV-associated tumors have differential distribution of tumor-infiltrating CD8+ and CD4+ T cells, enriched for the expression of programmed cell death 1 (PD-1) and lymphocyte-activating gene 3 (LAG3), as well as activation and proliferation markers. We also demonstrate higher expression of immunoregulatory molecules (PD-L1, PD-L2, B7-H3, B7-H4, IDO1, and VISTA) among tumor-associated macrophages. Discrimination of cells between tumors from PWH versus those from PWOH was confirmed by spectral graph theory with 84.6% accuracy. Furthermore, we noted differences in spatial orientation of immune cells within the TME of PWH compared with PWOH. Additionally, cells from PWH, compared with those from PWOH, exhibited decreased tumor killing when exposed to HLA-matched NSCLC cell lines. In conclusion, our study demonstrates that the HIV-associated TME sustained a unique immune landscape, showing evidence of immune cells with enhanced immunoregulatory phenotypes and impaired antitumor responses, with implications for responses to immune checkpoint blocker therapies.

Authors

Shruti S. Desai, Syim Salahuddin, Ramsey Yusuf, Kishu Ranjan, Jianlei Gu, Lais Osmani, Ya-Wei Lin, Sameet Mehta, Ronan Talmon, Insoo Kang, Yuval Kluger, Hongyu Zhao, Kurt Schalper, Brinda Emu

×

Figure 3

T cell phenotype in the TME of NSCLC in PWH and PWOH.

Options: View larger image (or click on image) Download as PowerPoint
T cell phenotype in the TME of NSCLC in PWH and PWOH. (A and E) Mean exp...
(A and E) Mean expression value of single markers in CD8+ T cells (A) and CD4+ T cells (E) from IMC panels. *P < 0.05, *** P < 0.001, and ****P < 0.0001, by nonparametric Kruskal-Wallis test. Data are shown as the mean ± SEM. (B and F) Umbrella plots revealed markers with significant differences between PWH and PWOH with regard to CD8+ T cells (B) and CD4+ T cells (F), using a random-effects model. (C and G) Unsupervised clustering analysis reveals 7 unique clusters of CD8+ (C) and CD4+ (G) T cells as a t-distributed stochastic neighbor embedding (t-SNE) plot (top panels) and the distribution of cells by HIV status with cells from PWH (blue) and PWOH (red) (bottom panels). (D and H) Bar graphs representing the distribution of each CD8+ (D) and CD4+ (H) T cell cluster in tumors from PWH and PWOH. Fold-change graphs demonstrate the change in proportions for each subset in HIV-associated tumors from PWH compared with non-HIV tumors from PWOH. Heatmaps show the intensity of each marker across the different clusters, normalized from 0 to 1, with 1 being highest expression.