Immune Profiling of Incidental NSCLC Patients: Comparison Between Tumor Sections and TMA Cores

In the context of nonsmall cell lung cancer (NSCLC), the immune evasion strategy used by tumor cells involves the expression of immune checkpoint proteins, such as PD-L1, which suppress antitumor T-cell responses. The use of immune checkpoint inhibitors (ICIs) has significantly improved overall survival, overall response rate, and progression-free survival in NSCLC patients. This study aimed to evaluate the concordance of PD-L1 expression in NSCLC patients using tissue microarrays (TMA) as proxies for small biopsies. The degree of concordance among tissue cores and between the cores and the whole slide was reported. Furthermore, the presence of tumor-associated macrophages (TAMs) and tumor-infiltrating lymphocytes (TILs) was analyzed to investigate the correlation between PD-L1 expression and immune cell infiltration. The study included 13 paraffin-embedded tissue samples from patients incidentally diagnosed with lung cancer during COVID imaging studies. Tissue microarrays were constructed using a manual tissue arrayer, and 4 cores of 2 mm diameter of representative areas were selected from the hematoxylin-eosin-stained sections from lung tumor specimens. Immunohistochemical analyses were performed to assess PD-L1 positivity, tumor macrophage infiltrate, and T-cell infiltrate. The density of CD8+ T cells was evaluated as the overall percentage of the area within the borders of the tumors covered by positive immune cells. Results demonstrated that PD-L1 expression showed a high degree of concordance between TMA cores and whole tumor sections, suggesting that small samples could reliably represent whole tumor PD-L1 status. However, the densities of CD8+ T cells and CD68+ macrophages varied significantly. TMA cores typically underrepresented the density of these immune cells compared with whole sections, particularly for CD68+ macrophages, which exhibited lower densities in TMAs, used as proxies for small biopsies. This study contributes to the understanding of how the heterogeneity of PD-L1 expression and immune cell distribution can influence the detection and scoring of these parameters, highlighting the importance of comprehensive immune profiling in guiding personalized cancer immunotherapy.