A Comparison of Methods for Studying the Tumor Microenvironment's Spatial Heterogeneity in Digital Pathology Specimens.
A Comparison of Methods for Studying the Tumor Microenvironment's Spatial Heterogeneity in Digital Pathology Specimens.
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DOI：
10.4103/jpi.jpi_26_20
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发表时间：
2021
影响因子：
--
通讯作者：
Caie PD
中科院分区：
文献类型：
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作者：
Nearchou IP;Soutar DA;Ueno H;Harrison DJ;Arandjelovic O;Caie PD
肿瘤微环境是高度异质性的，据了解它会影响肿瘤的进展和患者的预后。许多研究报道了肿瘤浸润淋巴细胞和肿瘤萌芽在结直肠癌（CRC）中的预后意义。然而，这些特征在肿瘤免疫微环境（TIME）中空间分布的肿瘤内异质性的意义尚未被报道。评估这种肿瘤内异质性可能有助于理解TIME对患者预后的影响，以及识别新的侵袭性表型，这些表型可以进一步研究作为新治疗的潜在靶点。在这项研究中，我们提出并应用了两种空间统计方法来评估232例II期CRC病例中CD3 +和CD8 +淋巴细胞和肿瘤芽（TB）分布的肿瘤内异质性。Getis-Ord热点分析用于量化冷区和热点区，分别定义为每个感兴趣的特征数量显著低或显著高的区域。进一步开发了一种新的空间热图方法，用于量化每个感兴趣的特征的冷和热点，该方法考虑了患者间异质性和肿瘤内异质性。每个分析的结果数据，表征淋巴细胞和tb的肿瘤内空间异质性，用于开发两个新的高预后风险模型。我们的结果强调了应用空间统计来评估肿瘤内异质性的价值。Getis-Ord热点和我们提出的空间热图分析都广泛适用于其他组织类型以及其他感兴趣的特征。支持此发布的代码可以在https://doi.org/10.17630/c2306fe9-66e2-4442-ad89-f986220053e2上访问。
The tumor microenvironment is highly heterogeneous, and it is understood to affect tumor progression and patient outcome. A number of studies have reported the prognostic significance of tumor-infiltrating lymphocytes and tumor budding in colorectal cancer (CRC). However, the significance of the intratumoral heterogeneity present in the spatial distribution of these features within the tumor immune microenvironment (TIME) has not been previously reported. Evaluating this intratumoral heterogeneity may aid the understanding of the TIME's effect on patient prognosis as well as identify novel aggressive phenotypes which can be further investigated as potential targets for new treatment. In this study, we propose and apply two spatial statistical methodologies for the evaluation of the intratumor heterogeneity present in the distribution of CD3 + and CD8 + lymphocytes and tumor buds (TB) in 232 Stage II CRC cases. Getis-Ord hotspot analysis was applied to quantify the cold and hotspots, defined as regions with a significantly low or high number of each feature of interest, respectively. A novel spatial heatmap methodology for the quantification of the cold and hotspots of each feature of interest, which took into account both the interpatient heterogeneity and the intratumor heterogeneity, was further developed. Resultant data from each analysis, characterizing the spatial intratumor heterogeneity of lymphocytes and TBs were used for the development of two new highly prognostic risk models. Our results highlight the value of applying spatial statistics for the assessment of the intratumor heterogeneity. Both Getis-Ord hotspot and our proposed spatial heatmap analysis are broadly applicable across other tissue types as well as other features of interest. The code underpinning this publication can be accessed at https://doi.org/10.17630/c2306fe9-66e2-4442-ad89-f986220053e2.