Semi-Automated Computational Assessment of Cancer Organoid Viability Using Rapid Live-Cell Microscopy.
Semi-Automated Computational Assessment of Cancer Organoid Viability Using Rapid Live-Cell Microscopy.
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DOI:
10.1177/11769351221100754
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发表时间:
2022
影响因子:
2
通讯作者:
Abdullah, Kalil G.
中科院分区:
文献类型:
--
作者:
Buehler, Joseph D.;Bird, Cylaina E.;Savani, Milan R.;Gattie, Lauren C.;Hicks, William H.;Levitt, Michael M.;El Shami, Mohamad;Hatanpaa, Kimmo J.;Richardson, Timothy E.;McBrayer, Samuel K.;Abdullah, Kalil G.
The creation of patient-derived cancer organoids represents a key advance in preclinical modeling and has recently been applied to a variety of human solid tumor types. However, conventional methods used to assess in vivo tumor tissue treatment response are poorly suited for the evaluation of cancer organoids because they are time-intensive and involve tissue destruction. To address this issue, we established a suite of 3-dimensional patient-derived glioma organoids, treated them with chemoradiotherapy, stained organoids with non-toxic cell dyes, and imaged them using a rapid laser scanning confocal microscopy method termed “Apex Imaging.” We then developed and tested a fragmentation algorithm to quantify heterogeneity in the topography of the organoids as a potential surrogate marker of viability. This algorithm, SSDquant, provides a 3-dimensional visual representation of the organoid surface and a numerical measurement of the sum-squared distance (SSD) from the derived mass center of the organoid. We tested whether SSD scores correlate with traditional immunohistochemistry-derived cell viability markers (cellularity and cleaved caspase 3 expression) and observed statistically significant associations between them using linear regression analysis. Our work describes a quantitative, non-invasive approach for the serial measurement of patient-derived cancer organoid viability, thus opening new avenues for the application of these models to studies of cancer biology and therapy.
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影响因子:
--
作者:
Pernik MN;Bird CE;Traylor JI;Shi DD;Richardson TE;McBrayer SK;Abdullah KG
通讯作者:
Abdullah KG
影响因子:
4.6
作者:
Bankhead P;Loughrey MB;Fernández JA;Dombrowski Y;McArt DG;Dunne PD;McQuaid S;Gray RT;Murray LJ;Coleman HG;James JA;Salto-Tellez M;Hamilton PW
通讯作者:
Hamilton PW
影响因子:
5.4
作者:
Bolck, Hella A.;Corro, Claudia;Moch, Holger
通讯作者:
Moch, Holger
影响因子:
64.5
作者:
Jacob F;Salinas RD;Zhang DY;Nguyen PTT;Schnoll JG;Wong SZH;Thokala R;Sheikh S;Saxena D;Prokop S;Liu DA;Qian X;Petrov D;Lucas T;Chen HI;Dorsey JF;Christian KM;Binder ZA;Nasrallah M;Brem S;O'Rourke DM;Ming GL;Song H
通讯作者:
Song H
影响因子:
5.8
作者:
Legland, David;Arganda-Carreras, Ignacio;Andrey, Philippe
通讯作者:
Andrey, Philippe