Kaufmann Justus, Biscio Christophe A N, Bankhead Peter, Zimmer Stefanie, Schmidberger Heinz, Rubak Ege, Mayer Arnulf
Department of Radiation Oncology, University Medical Center of the Johannes Gutenberg University, 55131 Mainz, Germany.
Department of Mathematical Sciences, Aalborg University, Skjernvej 4A, 9220 Aalborg East, Denmark.
Cancers (Basel). 2021 Apr 16;13(8):1924. doi: 10.3390/cancers13081924.
(1) Background: The immune system has physiological antitumor activity, which is partially mediated by cytotoxic T lymphocytes (CTL). Tumor hypoxia, which is highly prevalent in cancers of the head and neck region, has been hypothesized to inhibit the infiltration of tumors by CTL. In situ data validating this concept have so far been based solely upon the visual assessment of the distribution of CTL. Here, we have established a set of spatial statistical tools to address this problem mathematically and tested their performance. (2) Patients and Methods: We have analyzed regions of interest (ROI) of 22 specimens of cancers of the head and neck region after 4-plex immunofluorescence staining and whole-slide scanning. Single cell-based segmentation was carried out in QuPath. Specimens were analyzed with the endpoints clustering and interactions between CTL, normoxic, and hypoxic tumor areas, both visually and using spatial statistical tools implemented in the R package Spatstat. (3) Results: Visual assessment suggested clustering of CTL in all instances. The visual analysis also suggested an inhibitory effect between hypoxic tumor areas and CTL in a minority of the whole-slide scans (9 of 22, 41%). Conversely, the objective mathematical analysis in Spatstat demonstrated statistically significant inhibitory interactions between hypoxia and CTL accumulation in a substantially higher number of specimens (16 of 22, 73%). It showed a similar trend in all but one of the remaining samples. (4) Conclusion: Our findings provide non-obvious but statistically rigorous evidence of inhibition of CTL infiltration into hypoxic tumor subregions of cancers of the head and neck. Importantly, these shielded sites may be the origin of tumor recurrences. We provide the methodology for the transfer of our statistical approach to similar questions. We discuss why versions of the Kcross and pcf.cross functions may be the methods of choice among the repertoire of statistical tests in Spatstat for this type of analysis.
(1) 背景:免疫系统具有生理抗肿瘤活性,部分由细胞毒性T淋巴细胞(CTL)介导。肿瘤缺氧在头颈部癌症中非常普遍,据推测它会抑制CTL对肿瘤的浸润。迄今为止,验证这一概念的原位数据仅基于对CTL分布的视觉评估。在此,我们建立了一套空间统计工具来从数学上解决这个问题并测试其性能。(2) 患者和方法:我们对22例头颈部癌症标本进行了四重免疫荧光染色和全切片扫描后分析了感兴趣区域(ROI)。在QuPath中进行基于单细胞的分割。使用R包Spatstat中实现的空间统计工具,从视觉和实际操作两方面对标本进行分析,分析终点为CTL、常氧和缺氧肿瘤区域之间的聚类和相互作用。(3) 结果:视觉评估表明在所有情况下CTL都有聚集。视觉分析还表明在少数全切片扫描中(22例中的9例,41%)缺氧肿瘤区域和CTL之间存在抑制作用。相反,Spatstat中的客观数学分析表明,在大量标本中(22例中的16例,73%)缺氧与CTL聚集之间存在统计学上显著的抑制相互作用。在其余样本中,除一个样本外,其他样本都呈现出类似趋势。(4) 结论:我们的研究结果提供了非显而易见但统计学上严谨的证据,证明CTL浸润到头颈部癌症的缺氧肿瘤亚区域受到抑制。重要的是,这些受保护的部位可能是肿瘤复发的根源。我们提供了将我们的统计方法应用于类似问题的方法。我们讨论了为什么Kcross和pcf.cross函数的版本可能是Spatstat中用于此类分析的统计测试方法中的首选方法。