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list of image analysis publications
Carey CD, Gusenleitner D, Lipschitz M, Roemer MGM, Stack EC, Gjini E, Hu X, Redd R, Freeman GJ, Neuberg D, Hodi FS, Liu XS, Shipp MA, Rodig SJ. Topological analysis reveals a PD-L1-associated microenvironmental niche for Reed-Sternberg cells in Hodgkin lymphoma. Blood. 2017 Nov 30;130(22):2420-2430. doi: 10.1182/blood-2017-03-770719. Epub 2017 Sep 11. PubMed PMID: 28893733.
This manuscript examines the TME by mIF in 20 cases of classical Hodgkin lymphoma, and demonstrates that CD4+ T cells and PD-L1+ macrophages form an immuno-suppressive niche around PD-L1+ HRS cells. This is also the genesis of the IrisSpatialFeatures software this package is based on, reporting measures of cell-cell contacts, nearest neighbors, and proximity to cells.
Keren L, Bosse M, Marquez D, Angoshtari R, Jain S, Varma S, Yang SR, Kurian A, Van Valen D, West R, Bendall SC, Angelo M. A Structured Tumor-Immune Microenvironment in Triple Negative Breast Cancer Revealed by Multiplexed Ion Beam Imaging. Cell. 2018 Sep 6;174(6):1373-1387.e19. doi: 10.1016/j.cell.2018.08.039. PubMed PMID: 30193111.
This manuscript examines the TME of 41 TNBC patients are imaged with a 36 protein panel, and reports spatial features defined as 'mixed' and 'compartmentalized' tumors. This paper uses their deep learning segmentation algorithm, and a method called 'Context-dependent spatial enrichment' to generate a 'mixing score' between tumor and immune cell derived from the number of immune-tumor interactions divided by the total number of immune interactions. Data is available from ionpath.
Gide TN, Quek C, Menzies AM, Tasker AT, Shang P, Holst J, Madore J, Lim SY, Velickovic R, Wongchenko M, Yan Y, Lo S, Carlino MS, Guminski A, Saw RPM, Pang A, McGuire HM, Palendira U, Thompson JF, Rizos H, Silva IPD, Batten M, Scolyer RA, Long GV, Wilmott JS. Distinct Immune Cell Populations Define Response to Anti-PD-1 Monotherapy and Anti-PD-1/Anti-CTLA-4 Combined Therapy. Cancer Cell. 2019 Feb 11;35(2):238-255.e6. doi: 10.1016/j.ccell.2019.01.003. PubMed PMID: 30753825.
This manuscript investigates response in anti PD-1 (n=63) and PD1-1 CTLA4 combo (n=57) treated patients by mIF, they look at CD8, PD-1, PD-L1, FOXP3, and SOX10 in both intra-tumor and stromal areas. They have both baseline and on-treatment data for some subjects. They find CD8 density both intra-tumor and peri-tumor associated with response, as well as both intra-tumor PD-L1 density and peri-tumor PD-L1 density.
Ehteshami Bejnordi B, Mullooly M, Pfeiffer RM, Fan S, Vacek PM, Weaver DL, Herschorn S, Brinton LA, van Ginneken B, Karssemeijer N, Beck AH, Gierach GL, van der Laak JAWM, Sherman ME. Using deep convolutional neural networks to identify and classify tumor-associated stroma in diagnostic breast biopsies. Mod Pathol. 2018 Oct;31(10):1502-1512. doi: 10.1038/s41379-018-0073-z. Epub 2018 Jun 13. PubMed PMID: 29899550.
Lin JR, Izar B, Wang S, Yapp C, Mei S, Shah PM, Santagata S, Sorger PK. Highly multiplexed immunofluorescence imaging of human tissues and tumors using t-CyCIF and conventional optical microscopes. Elife. 2018 Jul 11;7. pii: e31657. doi: 10.7554/eLife.31657. PubMed PMID: 29993362.
tissue-based cyclic immuno-fluorescence (t-CyCIF) on FFPE is an extension of their tissue culture imaging method. Computationally, methods include ImageJ and Matlab scripts, as well as their stitching and registration software. They have an explorer to view the images called omero from the Open Microscopy Environment group.