Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Pathobiology. 2023;90(1):1-12. doi: 10.1159/000523751. Epub 2022 May 24.
Representative regions of interest (ROIs) analysis from the whole slide images (WSI) are currently being used to study immune markers by multiplex immunofluorescence (mIF) and single immunohistochemistry (IHC). However, the amount of area needed to be analyzed to be representative of the entire tumor in a WSI has not been defined.
We labeled tumor-associated immune cells by mIF and single IHC in separate cohorts of non-small cell lung cancer (NSCLC) samples and we analyzed them as whole tumor area as well as using different number of ROIs to know how much area will be need to represent the entire tumor area.
For mIF using the InForm software and ROI of 0.33 mm2 each, we observed that the cell density data from five randomly selected ROIs is enough to achieve, in 90% of our samples, more than 0.9 of Spearman correlation coefficient and for single IHC using ScanScope tool box from Aperio and ROIs of 1 mm2 each, we found that the correlation value of more than 0.9 was achieved using 5 ROIs in a similar cohort. Additionally, we also observed that each cell phenotype in mIF influence differently the correlation between the areas analyzed by the ROIs and the WSI. Tumor tissue with high intratumor epithelial and immune cells phenotype, quality, and spatial distribution heterogeneity need more area analyzed to represent better the whole tumor area.
We found that at minimum 1.65 mm2 area is enough to represent the entire tumor areas in most of our NSCLC samples using mIF.
目前，通过多重免疫荧光（mIF）和单免疫组化（IHC），从全切片图像（WSI）中选择有代表性的感兴趣区域（ROI）来研究免疫标志物。然而，尚未确定代表 WSI 中整个肿瘤的代表性分析区域面积。
我们使用 mIF 和单独的 NSCLC 样本中的单 IHC 标记肿瘤相关免疫细胞，并将其作为整个肿瘤区域进行分析，同时使用不同数量的 ROI 来了解需要多少面积来代表整个肿瘤区域。
对于使用 InForm 软件的 mIF 和每个 ROI 为 0.33mm2 的情况，我们观察到，在 90%的样本中，从五个随机选择的 ROI 中获得的细胞密度数据足以实现 Spearman 相关系数大于 0.9。对于使用 Aperio 的 ScanScope 工具盒的单 IHC，我们发现，在类似的队列中，使用 5 个 ROI 即可达到大于 0.9 的相关值。此外，我们还观察到，mIF 中的每种细胞表型对 ROI 分析与 WSI 之间的相关性有不同的影响。肿瘤组织中上皮细胞和免疫细胞表型、质量和空间分布异质性较高，需要分析更多的区域，以更好地代表整个肿瘤区域。
我们发现，在大多数 NSCLC 样本中，使用 mIF 至少需要 1.65mm2 的面积即可代表整个肿瘤区域。
