1230 Enhancing tissue microarray design for immune profiling: tissue microarray vs whole-slide quantification of CD8 in non-small cell lung carcinoma

Background Tissue microarrays (TMAs) are efficient, high-throughput tools for tissue-based analyses, yet optimal design strategies for studying spatially heterogeneous markers such as immune infiltration remain undefined. 1 2 CD8+ T-cell density is associated with improved prognosis in non-small cell lung carcinoma (NSCLC), particularly at the tumor-stroma interface, termed the invasive margin (IM).3–5 There is currently no standardized operational definition of the IM in NSCLC6–8 and TMAs have traditionally been tailored to tumor-intrinsic features, rather than immune contexture.9–11 Methods CD8 immunohistochemistry was performed on 35 NSCLC whole-slide resection specimens and a corresponding TMA comprising 3 cores from the central tumor (CT) and from the IM (50% tumor: 50% stroma) per specimen. CD8 + cell densities were digitally mapped in 50-μm increments across the tumor-stroma boundary to empirically define the IM on the whole-slide resections. Actual and digitally-simulated TMA cores of varying number and size were assessed for concordance with whole-slide CD8+ cell densities and nearest-neighbor distances at the CT and IM to optimize core size and number.Results A characteristic CD8 + cell density peak was consistently observed within 200 µm beyond the tumor border, defining the extent of the tumor-immune interface. Accordingly, cores were required to contain ≥80% tumor by area (CT) or ≥10% stroma and 80%≥ tumor >0% (IM) (figure 1). TMA core inadequacy was significantly higher at the IM (56%) than at the CT (6.2%), primarily due to geographic displacement away from the 200-µm IM peak (χ2, p<0.001). Modeling showed that core radius (≥0.5 mm) more strongly affected nearest-neighbor measurements than core number, while returns diminished beyond 4 IM or 3 CT cores in CD8+ cell density sampling (figure 2). CD8+ clusters were smaller and more dispersed at the IM than in the CT, emphasizing the need for larger sampling areas to capture immune heterogeneity (figure 1B). We recommend designing 8 IM and 3 CT cores ≥0.5 mm in radius per specimen to anticipate core loss and ensure analytical fidelity in quantifying CD8+ cells.Conclusions This study defines the IM as the 200-μm stromal region beyond the tumor edge and provides a data-driven framework for optimizing TMA design to study heterogeneously expressed immunological markers in NSCLC, including strategy for TMA core quality assessment. By refining TMA strategies to account for spatial immune heterogeneity, we enhance the translational potential of TMAs, supporting their broader use in scaling immune-related biomarker monitoring across clinical trial cohorts and in evaluating immunotherapy responses in NSCLC and beyond.References Jones S, Prasad ML. Comparative evaluation of high-throughput small-core (0.6-mm) and large-core (2-mm) thyroid tissue microarray: is larger better? Archives of Pathology & Laboratory Medicine. 2021;136:199–203.Eckel-Passow JE, et al. Tissue microarrays: one size does not fit all. Diagnostic Pathology. 2010;5:48.Trojan A, et al. Immune activation status of CD8+ T cells infiltrating non-small cell lung cancer. Lung Cancer. 2004;44:143–147.Ghiringhelli F, et al. Immunoscore immune checkpoint using spatial quantitative analysis of CD8 and PD-L1 markers is predictive of the efficacy of anti- PD1/PD-L1 immunotherapy in non-small cell lung cancer. eBioMedicine. 2023;92.Donnem T, et al. Stromal CD8+ T-cell density—a promising supplement to TNM staging in non-small cell lung cancer. Clinical Cancer Research. 2015;21:2635–2643.Galon J, et al. Type, density, and location of immune cells within human colorectal tumors predict clinical outcome. Science. 2006;313:1960–1964.Gong C, et al. Quantitative characterization of CD8+ T cell clustering and spatial heterogeneity in solid tumors. Front Oncol. 2019;8:649.Marliot F, Lafontaine L, Galon J. Immunoscore assay for the immune classification of solid tumors: technical aspects, improvements and clinical perspectives. Methods Enzymol. 2020;636:109–128.Eskaros AR, et al. Larger core size has superior technical and analytical accuracy in bladder tissue microarray. Laboratory Investigation. 2017;97:335–342.Wampfler JA, et al. Determining the optimal numbers of cores based on tissue microarray antibody assessment in non-small cell lung cancer. Journal of Cancer Science and Therapy. 2011;3:120–124.Alkushi A. Validation of tissue microarray biomarker expression of breast carcinomas in Saudi women. Hematology/Oncology and Stem Cell Therapy. 2009;2:394–398.Ethics Approval This study was approved by Queen’s University Human Subjects Research Ethics Board (HSREB# ONGY-600-21).Abstract 1230 Figure 1Distinct CD8 patterns distinguish the IM from the CT on whole-slide specimens. A) A histogram of whole-slide CD8 density (normalized to the intratumoral mean) shows the 200-µm IM peak beyond the tumor border. B) A histogram of core placement relative to the tumor border shows cores that miss the IM peak due to geographic variationAbstract 1230 Figure 2Increasing core number improves whole-slide CD8+ cell density concordance and larger cores better approximate nearest-neighbor measurements. A) A heatmap displays CD8 density correlations (Spearman) between simulated cores and whole-slides. Mean density standard deviation (B) and nearest-neighbor distance error (C) are shown for simulated cores. D) An iteration of simulation is illustrated

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.