First proposal of minimum information about a cellular assay for regenerative medicine

Stem Cells Translational Medicine

Volumn 5, Issue 10, 2016, Pages 1345-1361

  Sakurai, Kunie ^a   Kurtz, Andreas ^b   Stacey, Glyn ^c   Sheldon, Michael ^d   Fujibuchi, Wataru ^a  

^a KYOTO UNIVERSITY   (Japan)

^b CHARITÉ UNIVERSITÄTSMEDIZIN BERLIN   (Germany)

^c NATIONAL INSTITUTE FOR BIOLOGICAL STANDARDS AND CONTROL   (United Kingdom)

^d RUTGERS UNIVERSITY   (United States)

Author keywords

Biological specimen banks; Information sharing; Quality control; Regenerative medicine; Standards; Stem cells

Indexed keywords

BIOBANK; HUMAN; HUMAN CELL; ONTOLOGY; QUALITY CONTROL; REGENERATIVE MEDICINE; REGISTER; STEM CELL; TAXONOMY; STANDARDS; STEM CELL RESEARCH; TISSUE BANK;

HUMANS; REGENERATIVE MEDICINE; REGISTRIES; STEM CELL RESEARCH; STEM CELLS; TISSUE BANKS;

EID: 84988596103     PISSN: 21576564     EISSN: 21576580     Source Type: Journal    
DOI: 10.5966/sctm.2015-0393     Document Type: Article

References (59)

1. Thomson JA, Itskovitz-Eldor J, Shapiro SS et al. Embryonic stem cell lines derived from human blastocysts. Science 1998; 282: 1145-1147.
2. Takahashi K, Tanabe K, OhnukiMet al. Induction of pluripotent stem cells from adult human fibroblasts by defined factors. Cell 2007; 131: 861-872.
3. Soares FAC, SheldonM, RaoMet al. International coordination of large-scale human induced pluripotent stem cell initiatives: Wellcome Trust and ISSCR workshops white paper. Stem Cell Rep 2014; 3: 931-939.
4. Chang HH, Hemberg M, Barahona M et al. Transcriptome-wide noise controls lineage choice in mammalian progenitor cells. Nature 2008; 453: 544-547.
5. Johnson MB, Wang PP, Atabay KD et al. Single-cell analysis reveals transcriptional heterogeneity of neural progenitors in human cortex. Nat Neurosci 2015; 18: 637-646.
6. Narsinh KH, Sun N, Sanchez-Freire V et al. Single cell transcriptional profiling reveals heterogeneity of human induced pluripotent stem cells. J Clin Invest 2011; 121: 1217-1221.
7. Rinkevich Y, Walmsley GG, Hu MS et al. Skin fibrosis. Identification and isolation of a dermal lineage with intrinsic fibrogenic potential. Science 2015; 348: aaa2151.
8. Brazma A, HingampP, Quackenbush J et al. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 2001; 29: 365-371.
9. Taylor CF, Field D, Sansone S-A et al. Promoting coherent minimumreporting guidelines for biological and biomedical investigations: The MIBBI project. Nat Biotechnol 2008; 26: 889-896.
10. Wiemann S, Mehrle A, Hahne F et al. MIACA-minimum information about a cellular assay, and the cellular assay objectmodel. Available at http://miaca.sourceforge.net. Accessed October 15, 2015.
11. Janetzki S, Britten CM, Kalos M et al. " MIATA"-minimal information about T cell assays. Immunity 2009; 31: 527-528.
12. Viti F, Scaglione S, Orro A et al. Guidelines for managing data and processes in bone and cartilage tissue engineering. BMC Bioinformatics 2014; 15(Suppl 1): S14.
13. Minimum information required for a DMET experiment. Available at http://mibbi. sourceforge.net/projects/MIDE.shtml. Accessed October 15, 2015.
14. Orchard S, Al-Lazikani B, Bryant S et al. Minimum information about a bioactive entity (MIABE). Nat Rev Drug Discov 2011; 10: 661-669.
15. Willyard C. The boom in mini stomachs, brains, breasts, kidneys and more. Nature 2015; 523: 520-522.
16. Edgar R, Barrett T. NCBI GEO standards and services for microarray data. Nat Biotechnol 2006; 24: 1471-1472.
17. Stacey G. Banking stem cells for research and clinical applications. Prog Brain Res 2012; 200: 41-58.
18. International Stem Cell Banking Initiative. Consensus guidance for banking and supply of human embryonic stem cell lines for research purposes. Stem Cell Rev 2009; 5: 301-314.
19. Pharmaceutical and Food Safety Bureau, Evaluation and Licensing Division, Ministry of Health, Labour and Welfare. Guideline to complete the application form for ensuring the quality and safety of pharmaceuticals and medical devices based on cells or tissue [in Japanese]. Yakushokushinsa-hatsu No. 0420-1, 2010.
20. Pharmaceutical and Food Safety Bureau, Ministry of Health, Labour and Welfare. Guideline on ensuring the quality and safety of human allogeneic induced pluripotent stem (-like) cells-derived medical devices or pharmaceuticals [in Japanese]. Yakushoku-hatsu No. 0907-4, 2012.
21. European Medical Agency, Committee for Advanced Therapies. Reflection paper on stem cell-based medicinal products. EMA/CAT/571134/2009, 2011.
22. U.S. Department of Health and Human Services, Food and Drug Administration, Center for Biologics Evaluation and Research. Draft guidance for industry: Potency tests for cellular and gene therapy products. 2011.
23. Vempati UD, Przydzial MJ, Chung C et al. Formalization, annotation and analysis of diverse drug and probe screening assay datasets using the BioAssay Ontology (BAO). PLoS One 2012; 7: e49198.
24. Seltmann S, Stachelscheid H, Damaschun Aet al. CELDA-an ontology for the comprehensive representation of cells in complex systems. BMC Bioinformatics 2013; 14: 228.
25. Hastings J, de Matos P, Dekker A et al. The ChEBI reference database and ontology for biologically relevant chemistry: Enhancements for 2013. Nucleic Acids Res 2013; 41: D456-D463.
26. Meehan TF, Masci AM, Abdulla A et al. Logical development of the cell ontology. BMC Bioinformatics 2011; 12: 6.
27. Ison J, Kalaŝ M, Jonassen I et al. EDAM: An ontology of bioinformatics operations, types of data and identifiers, topics and formats. Bioinformatics 2013; 29: 1325-1332.
28. Malone J, Holloway E, Adamusiak T et al. Modeling sample variables with an experimental factor ontology. Bioinformatics 2010; 26: 1112-1118.
29. Biological Imaging Methods Ontology. 2015. Available at http://cellimagelibrary.org. Accessed October 15, 2015.
30. Rosse C, Mejino JLV Jr. A reference ontology for biomedical informatics: The Foundational Model of Anatomy. J Biomed Inform 2003; 36: 478-500.
31. Bodenreider O, Nelson SJ, Hole WT et al. Beyond synonymy: Exploiting the UMLS semantics in mapping vocabularies. Proc AMIA Symp 1998; 1998: 815-819.
32. Whetzel PL, Parkinson H, Causton HC et al. The MGED Ontology: A resource for semantics-based description of microarray experiments. Bioinformatics 2006; 22: 866-873.
33. National Cancer Institute Thesaurus. Available at http://ncit.nci.nih.gov. Accessed October 15, 2015.
34. Brinkman RR, Courtot M, Derom D et al. Modeling biomedical experimental processes with OBI. J Biomed Semantics 2010; 1(Suppl 1): S7.
35. Mungall CJ, Torniai C, Gkoutos GV et al. Uberon, an integrative multi-species anatomy ontology. Genome Biol 2012; 13: R5.
36. U.S. National Library ofMedicine,National Institutes of Health. PubMed/MEDLINE. Available at http://www.ncbi.nlm.nih.gov/pubmed. Accessed October 15, 2015.
37. OkitaK,YamakawaT,MatsumuraYetal.An efficient nonviralmethod to generate integrationfree human-induced pluripotent stem cells from cord blood and peripheral blood cells. STEM CELLS 2013; 31: 458-466.
38. Nakagawa M, Taniguchi Y, Senda S et al. A novel efficient feeder-free culture system for the derivation of human induced pluripotent stem cells. Sci Rep 2014; 4: 3594.
39. Andrews PW, Baker D, Benvinisty N et al. Points to consider in the development of seed stocks of pluripotent stem cells for clinical applications: International Stem Cell Banking Initiative (ISCBI). Regen Med 2015; 10(Suppl): 1-44.
40. Luong MX, Auerbach J, Crook JM et al. A call for standardized naming and reporting of human ESC and iPSC lines. Cell Stem Cell 2011; 8: 357-359.
41. Litterman NK, Ekins S. Databases and collaboration require standards for human stem cell research. Drug Discov Today 2015; 20: 247-254.
42. International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use. The international guidelines for medicines. Available at http://www.ich.org/ home.html. Accessed October 15, 2015.
43. Liang-Chu MMY, Yu M, Haverty PM et al. Humanbiosampleauthenticationusing thehighthroughput, cost-effective SNPtrace(TM) system. PLoS One 2015; 10: e0116218.
44. Alston-Roberts C, Barallon R, Bauer SR et al. Cell line misidentification: The beginning of the end. Nat Rev Cancer 2010; 10: 441-448.
45. Earl J, Greenhalf W. Single-nucleotide polymorphism (SNP) analysis to associate cancer risk. Methods Mol Biol 2010; 576: 171-196.
46. Yao L, Tak YG,Berman BP et al. Functional annotation of colon cancer risk SNPs. Nat Commun 2014; 5: 5114.
47. Reardon S, Cyranoski D. Japan stem-cell trial stirs envy. Nature 2014; 513: 287-288.
48. Higashi H, BrüstleO,DaleyGQet al. The nomenclature system should be sustainable, but also practical. Cell Stem Cell 2011; 8: 606-607.
49. Seltmann S, Lekschas F, Müller R et al. hPSCreg-the human pluripotent stem cell registry. Nucleic Acids Res 2016; 44: D757-D763.
50. Yu M, Selvaraj SK, Liang-Chu MMY et al. A resource for cell line authentication, annotation and quality control. Nature 2015; 520: 307-311.
51. International Society For Stem Cell Research. Guidelines for stem cell science and clinical translation draft June 26, 2015. 2015. Available at http://www.isscr.org/docs/ default-source/hesc-guidelines/isscr-draftguidelines- for-stem-cell-science-and-clinicaltranslation. pdf?sfvrsn=2. Accessed October 15, 2015.
52. Stacey GN. The challenge of standardisation in stem cell research and development. In: Ilic D, ed. Stem cell banking. New York, NY: Springer, 2014: 11-18.
53. Hatano A, Chiba H,Moesa HA et al. CELLPEDIA: A repository for human cell information for cell studies and differentiation analyses. Database 2011; 2011: bar046.
54. Bendall SC, Simonds EF, Qiu P et al. Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum. Science 2011; 332: 687-696.
55. ZeiselA,Muñ oz-ManchadoAB,Codeluppi S et al. Brain structure. Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq. Science 2015; 347: 1138-1142.
56. Islam S, Kjällquist U, Moliner A et al. Highly multiplexed and strand-specific singlecell RNA 59 end sequencing. Nat Protoc 2012; 7: 813-828.
57. Integrated database project. Available at http://lifesciencedb.jp/. Accessed October 15, 2015.
58. Ferguson AR, Nielson JL, CraginMH et al. Big data from small data: Data-sharing in the ‘long tail’ of neuroscience. Nat Neurosci 2014; 17: 1442-1447.
59. Margolis R, Derr L, Dunn M et al. The National Institutes of Health’s Big Data to Knowledge (BD2K) initiative: Capitalizing on biomedical big data. J Am Med Inform Assoc 2014; 21: 957-958.