Integrating analysis of cellular heterogeneity in high-content dose-response studies

Methods in Molecular Biology

Volumn 1745, Issue , 2018, Pages 25-46

  Gough, Albert ^a,b   Shun, Tong Ying ^a   Taylor, D Lansing ^a,b,c   Schurdak, Mark ^a,b,c  

^a UNIVERSITY OF PITTSBURGH   (United States)

^b UNIVERSITY OF PITTSBURGH SCHOOL OF MEDICINE   (United States)

^c UNIVERSITY OF PITTSBURGH CANCER INSTITUTE   (United States)

Author keywords

Cellular heterogeneity; Drug discovery; High content screening; Phenotypic profiling; Systems biology

Indexed keywords

BIOLOGICAL MARKER;

BIOLOGICAL ACTIVITY; CELL HETEROGENEITY; DATA BASE; DATA MINING; QUALITY CONTROL; SOFTWARE; BIOASSAY; BIOLOGY; DRUG DEVELOPMENT; HIGH THROUGHPUT SCREENING; HUMAN; PROCEDURES; REPRODUCIBILITY; STANDARDS; STATISTICAL ANALYSIS; SYSTEMS BIOLOGY;

BIOLOGICAL ASSAY; COMPUTATIONAL BIOLOGY; DATA INTERPRETATION, STATISTICAL; DRUG DISCOVERY; HIGH-THROUGHPUT SCREENING ASSAYS; HUMANS; QUALITY CONTROL; REPRODUCIBILITY OF RESULTS; SYSTEMS BIOLOGY;

EID: 85042556250     PISSN: 10643745     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-1-4939-7680-5_2     Document Type: Chapter

References (25)

1. Tawfik DS (2010) Messy biology and the origins of evolutionary innovations. Nat Chem Biol 6(10):692–696. https://doi.org/10.1038/nchembio.441
2. Gough A, Stern AM, Maier J, Lezon T, Shun T-Y, Chennubhotla C, Schurdak ME, Haney SA, Taylor DL (2017) Biologically relevant heterogeneity: metrics and practical insights. SLAS Discov 22(3):213–237. https://doi.org/10.1177/2472555216682725
3. Huang S (2009) Non-genetic heterogeneity of cells in development: more than just noise. Development 136(23):3853–3862. https://doi.org/10.1242/dev.035139
4. Snijder B, Pelkmans L (2011) Origins of regulated cell-to-cell variability. Nat Rev Mol Cell Biol 12(2):119–125. https://doi.org/10.1038/nrm3044
5. Altschuler SJ, Wu LF (2010) Cellular heterogeneity: when do differences make a difference? Cell 141(4):559–563
6. Singh DK, Ku CJ, Wichaidit C, Steininger RJ 3rd, Wu LF, Altschuler SJ (2010) Patterns of basal signaling heterogeneity can distinguish cellular populations with different drug sensitivities. Mol Syst Biol 6:369
7. Gough AH, Chen N, Shun TY, Lezon TR, Boltz RC, Reese CE, Wagner J, Vernetti LA, Grandis JR, Lee AV, Stern AM, Schurdak ME, Taylor DL (2014) Identifying and quantifying heterogeneity in high content analysis: application of heterogeneity indices to drug discovery. PLoS One 9(7):e102678. https://doi.org/10.1371/journal.pone.0102678
8. Gascoigne KE, Taylor SS (2008) Cancer cells display profound intra- and interline variation following prolonged exposure to antimitotic drugs. Cancer Cell 14(2):111–122. https://doi.org/10.1016/j.ccr.2008.07.002
9. Janiszewska M, Liu L, Almendro V, Kuang Y, Paweletz C, Sakr RA, Weigelt B, Hanker AB, Chandarlapaty S, King TA, Reis-Filho JS, Arteaga CL, Park SY, Michor F, Polyak K (2015) In situ single-cell analysis identifies heterogeneity for PIK3CA mutation and HER2 amplification in HER2-positive breast cancer. Nat Genet 47(10):1212–1219. https://doi.org/10.1038/ng.3391
10. Niepel M, Spencer SL, Sorger PK (2009) Non-genetic cell-to-cell variability and the consequences for pharmacology. Curr Opin Chem Biol 13(5–6):556–561. https://doi.org/10.1016/j.cbpa.2009.09.015
11. Zhao B, Pritchard JR, Lauffenburger DA, Hemann MT (2014) Addressing genetic tumor heterogeneity through computationally predictive combination therapy. Cancer Discov 4(2):166–174. https://doi.org/10.1158/2159-8290.CD-13-0465
12. Pritchard JR, Bruno PM, Gilbert LA, Capron KL, Lauffenburger DA, Hemann MT (2013) Defining principles of combination drug mechanisms of action. Proc Natl Acad Sci USA 110(2):E170–E179. https://doi.org/10.1073/pnas.1210419110
13. Zhang J-H, Chung TDY, Oldenburg KR (1999) A simple statistical parameter for use in evaluation and validation of high throughput screening assays. J Biomol Screen 4(2): 67–73. https://doi.org/10.1177/108705719900400206
14. Steininger RJ, Rajaram S, Girard L, Minna JD, Wu LF, Altschuler SJ (2015) On comparing heterogeneity across biomarkers. Cytometry A 87(6):558–567. https://doi.org/10.1002/cyto.a.22599.
15. Ruiz C, Li J, Luttgen MS, Kolatkar A, Kendall JT, Flores E, Topp Z, Samlowski WE, McClay E, Bethel K, Ferrone S, Hicks J, Kuhn P (2015) Limited genomic heterogeneity of circulating melanoma cells in advanced stage patients. Phys Biol 12(1):016008. https://doi.org/10.1088/1478-3975/12/1/016008
16. Balluff B, Frese CK, Maier SK, Schone C, Kuster B, Schmitt M, Aubele M, Hofler H, Deelder AM, Heck A Jr, Hogendoorn PC, Morreau J, Maarten Altelaar AF, Walch A, McDonnell LA (2015) De novo discovery of phenotypic intratumour heterogeneity using imaging mass spectrometry. J Pathol 235(1):3– 13. https://doi.org/10.1002/path.4436
17. Schwarz RF, Trinh A, Sipos B, Brenton JD, Goldman N, Markowetz F (2014) Phylogenetic quantification of intra-tumour heterogeneity. PLoS Comput Biol 10(4):e1003535. https://doi.org/10.1371/journal.pcbi.1003535
18. Haney SA (2014) Rapid assessment and visualization of normality in high-content and other cell-level data and its impact on the interpretation of experimental results. J Biomol Screen. https://doi.org/10.1177/1087057114526432
19. Loo LH, Lin HJ, Steininger RJ 3rd, Wang Y, Wu LF, Altschuler SJ (2009) An approach for extensibly profiling the molecular states of cellular subpopulations. Nat Methods 6(10):759–765
20. Gingold JA, Coakley ES, Su J, Lee DF, Lau Z, Zhou H, Felsenfeld DP, Schaniel C, Lemischka IR (2015) Distribution Analyzer, a methodology for identifying and clustering outlier conditions from single-cell distributions, and its application to a Nanog reporter RNAi screen. BMC Bioinformatics 16:225. https://doi.org/10.1186/s12859-015-0636-7
21. Bhang HE, Ruddy DA, Krishnamurthy Radhakrishna V, Caushi JX, Zhao R, Hims MM, Singh AP, Kao I, Rakiec D, Shaw P, Balak M, Raza A, Ackley E, Keen N, Schlabach MR, Palmer M, Leary RJ, Chiang DY, Sellers WR, Michor F, Cooke VG, Korn JM, Stegmeier F (2015) Studying clonal dynamics in response to cancer therapy using high-complexity barcoding. Nat Med 21(5):440–448. https://doi.org/10.1038/nm.3841
22. Gough A, Shun TY, Lansing Taylor D, Schurdak M (2016) A metric and workflow for quality control in the analysis of heterogeneity in phenotypic profiles and screens. Methods 96:12–26. https://doi.org/10.1016/j.ymeth.2015.10.007
23. Young IT (1977) Proof without prejudice: use of the Kolmogorov-Smirnov test for the analysis of histograms from flow systems and other sources. J Histochem Cytochem 25(7): 935–941
24. Polyak K (2014) Tumor heterogeneity confounds and illuminates: a case for Darwinian tumor evolution. Nat Med 20(4):344–346. https://doi.org/10.1038/nm.3518
25. Kleppe M, Levine RL (2014) Tumor heterogeneity confounds and illuminates: assessing the implications. Nat Med 20(4):342–344. https://doi.org/10.1038/nm.3522