作者: SChakra Chennubhotla , DanielM Spagnolo , Rekha Gyanchandani , Yousef Al-Kofahi , AndrewM Stern
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摘要: Background: Measures of spatial intratumor heterogeneity are potentially important diagnostic biomarkers for cancer progression, proliferation, and response to therapy. Spatial relationships among cells including stromal in the tumor microenvironment (TME) key contributors heterogeneity. Methods: We demonstrate how quantify from immunofluorescence pathology samples, using a set 3 basic breast as test case. learn dominant biomarker intensity patterns map distribution with network. then describe pairwise association statistics each pattern within network pointwise mutual information (PMI) visually represent two-dimensional map. Results: found salient 8 cellular phenotypes tissue microarray cohort containing 4 different subtypes. After computing PMI pair patient replicate, we visualize interactions that contribute resulting statistics. Then, potential biomarker, by comparing maps scores patients across Estrogen receptor positive invasive lobular carcinoma patient, AL13-6, exhibited highest score those tested, while estrogen negative ductal AL13-14, lowest score. Conclusions: This paper presents an approach describing heterogeneity, quantitative fashion (via PMI), which departs purely qualitative approaches currently used clinic. is generalizable highly multiplexed/hyperplexed images, well data complementary situ methods FISSEQ CyTOF, sampling many components TME. hypothesize will uncover TME disease proliferation progression.