A technology platform to assess multiple cancer agents simultaneously within a patient's tumor

Science Translational Medicine

Volumn 7, Issue 284, 2015, Pages 284ra56-

  Klinghoffer, Richard A ^a   Bahrami, S Bahram ^b,g   Hatton, Beryl A ^a   Frazier, Jason P ^a   Moreno Gonzalez, Alicia ^a   Strand, Andrew D ^b   Kerwin, William S ^a   Casalini, Joseph R ^a   Thirstrup, Derek J ^a   You, Sheng ^a   Morris, Shelli M ^a   Watts, Korashon L ^a   Veiseh, Mandana ^b,h   Grenley, Marc O ^a   Tretyak, Ilona ^a   Dey, Joyoti ^a   Carleton, Michael ^a   Beirne, Emily ^a   Pedro, Kyle D ^b   Ditzler, Sally H ^a   Girard, Emily J ^b   Deckwerth, Thomas L ^a   Bertout, Jessica A ^a   Meleo, Karri A ^c   Filvaroff, Ellen H ^d   Chopra, Rajesh ^d   Press, Oliver W ^b   Olson, James M ^b,e,f   more..

^a Presage Biosciences   (United States)

^b Fred Hutchinson Cancer Research Center   (United States)

^c Florida Veterinary Specialists   (United States)

^d CELGENE CORPORATION   (United States)

^e UNIVERSITY OF WASHINGTON   (United States)

^f SEATTLE CHILDREN S HOSPITAL   (United States)

^g LAWRENCE BERKELEY NATIONAL LABORATORY   (United States)

^h PALO ALTO RESEARCH CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ANTINEOPLASTIC AGENT; CC 115; DOXORUBICIN; MAFOSFAMIDE; MAMMALIAN TARGET OF RAPAMYCIN INHIBITOR; PREDNISOLONE; RIDAFOROLIMUS; UNCLASSIFIED DRUG; VINCRISTINE; BIOLOGICAL MARKER; CYCLOPHOSPHAMIDE; MTOR PROTEIN, MOUSE; TARGET OF RAPAMYCIN KINASE;

ANIMAL EXPERIMENT; ANIMAL MODEL; ANIMAL TISSUE; ANTINEOPLASTIC ACTIVITY; ARTICLE; AUTOMATION; CANCER COMBINATION CHEMOTHERAPY; CANCER INHIBITION; CANCER RESISTANCE; CASE REPORT; CHEMOSENSITIVITY; CONTROLLED STUDY; DOG; DOSE RESPONSE; DRUG DELIVERY DEVICE; DRUG DEVELOPMENT; DRUG DISTRIBUTION; DRUG EFFICACY; DRUG RESPONSE; DRUG SAFETY; DRUG SCREENING; FEASIBILITY STUDY; HUMAN; IMAGE ANALYSIS; LARGE CELL LYMPHOMA; MICROINJECTION; MOUSE; MULTIDRUG RESISTANCE; NONHUMAN; PRIORITY JOURNAL; TECHNOLOGY; TUMOR XENOGRAFT; ANALOGS AND DERIVATIVES; ANIMAL; CANCER TRANSPLANTATION; CHEMISTRY; DRUG DELIVERY SYSTEM; DRUG EFFECTS; DRUG RESISTANCE; LYMPHOMA; METABOLISM; NEOPLASMS; NUDE MOUSE; PROCEDURES; SCID MOUSE; TUMOR CELL LINE;

ANIMALS; ANTINEOPLASTIC AGENTS; BIOMARKERS; CELL LINE, TUMOR; CYCLOPHOSPHAMIDE; DOGS; DOXORUBICIN; DRUG DELIVERY SYSTEMS; DRUG RESISTANCE, NEOPLASM; DRUG SCREENING ASSAYS, ANTITUMOR; HUMANS; LYMPHOMA; MICE; MICE, NUDE; MICE, SCID; NEOPLASM TRANSPLANTATION; NEOPLASMS; PREDNISOLONE; TOR SERINE-THREONINE KINASES; VINCRISTINE;

EID: 84928653972     PISSN: 19466234     EISSN: 19466242     Source Type: Journal    
DOI: 10.1126/scitranslmed.aaa7489     Document Type: Article

References (36)

1. I. Kola, J. Landis, Can the pharmaceutical industry reduce attrition rates? Nat. Rev. Drug Discov. 3, 711-715 (2004).
2. M. De Palma, D. Hanahan, The biology of personalized medicine: Facing individual complexities underlying hallmark capabilities. Mol. Oncol. 6, 111-127 (2012).
3. J. A. DiMasi, L. Feldman, A. Seckler, A. Wilson, Trends in risks associated with new drug development: Success rates for investigational drugs. Clin. Pharmacol. Ther. 87, 272-277 (2010).
4. L. Hutchinson, R. Kirk, High drug attrition rates - Where are we going wrong? Nat. Rev. Clin. Oncol. 8, 189-190 (2011).
5. Drug development costs jump to $2.6 billion. Cancer Discov. 5, OF2 (2015).
6. D. Gisselson, D. Lindgren, L. H. Mengelbier, I. Øra, H. Yeger, Genetic bottlenecks and the hazardous game of population reduction in cell line based research. Exp. Cell Res. 316, 3379-3386 (2010).
7. A. Li, J. Walling, Y. Kotliarov, A. Center, M. E. Steed, S. J. Ahn, M. Rosenblum, T. Mikkelsen, J. C. Zenklusen, H. A. Fine, Genomic changes and gene expression profiles reveal that established glioma cell lines are poorly representative of primary human gliomas. Mol. Cancer Res. 6, 21-30 (2008).
8. M. P. Shekhar, Drug resistance: Challenges to effective therapy. Curr. Cancer Drug Targets 11, 613-623 (2011).
9. O. Trédan, C. M. Galmarini, K. Patel, I. F. Tannock, Drug resistance and the solid tumor microenvironment. J. Natl. Cancer Inst. 99, 1441-1454 (2007).
10. S. B. Bahrami, M. Veiseh, J. M. Olson. Needle array assembly and method for delivering therapeutic agents, U.S. Patents 8,349,554; Y0178;8,475,412; Y0178;8,349,554; Y0178;8,672,887; Y0178;8,657,786; Y0178;8,834,428 (2012).
11. K. J. Patel, O. Trédan, I. F. Tannock, Distribution of the anticancer drugs doxorubicin, mitoxantrone and topotecan in tumors and normal tissues. Cancer Chemother. Pharmacol. 72,127-138 (2013).
12. F. J. Sharom, ABC multidrug transporters: Structure, function and role in chemoresistance. Pharmacogenomics 9, 105-127 (2008).
13. D. M. Vail, Veterinary Co-operative Oncology Group. Vet. Comp. Oncol. 2, 194 (2004).
14. N. E. Sharpless, R. A. Depinho, The mighty mouse: Genetically engineered mouse models in cancer drug development. Nat. Rev. Drug Discov. 5, 741-754 (2006).
15. F. T. Unger, I. Witte, K. A. David, Prediction of individual response to anticancer therapy: Historical and future perspectives. Cell. Mol. Life Sci. 72, 729-757 (2015).
16. L. A. Leone, P. A. Meitner, T. J. Myers, W. R. Grace, W. H. Gajewski, H. J. Fingert, B. Rotman, Predictive value of the fluorescent cytoprint assay (FCA): A retrospective correlation study of in vitro chemosensitivity and individual responses to chemotherapy. Cancer Invest. 9, 491-503 (1991).
17. B. U. Sevin, J. P. Perras, H. E. Averette, D. M. Donato, M. Penalver, Chemosensitivity testing in ovarian cancer. Cancer 71, 1613-1620 (1993).
18. N. Kopjar, V. Garaj-Vrhovac, I. Milas, Assessment of chemotherapy-induced DNA damage in peripheral blood leukocytes of cancer patients using the alkaline comet assay. Teratog. Carcinog. Mutagen. 22,13-30 (2002).
19. C.H.Bosken,Q.Wei,C.I.Amos,M.R.Spitz,AnanalysisofDNArepairasadeterminant of survival in patients with non-small-cell lung cancer. J. Natl. Cancer Inst. 94, 1091-1099 (2002).
20. S. B. Nadin, L. M. Vargas-Roig, G. Drago, J. Ibarra, D. R. Ciocca, DNA damage and repair in peripheral blood lymphocytes from healthy individuals and cancer patients: A pilot study on the implications in the clinical response to chemotherapy. Cancer Lett. 239, 84-97 (2006).
21. B. Majumder, U. Baraneedharan, S. Thiyagarajan, P. Radhakrishnan, H. Narasimhan, M. Dhandapani, N. Brijwani, D. D. Pinto, A. Prasath, B. U. Skanthappa, A. Thayakumar, R. Surendran, G. K. Babu, A. M. Shenoy, M. A. Kuriakose, G. Bergthold, P. Horowitz, M. Loda, R. Beroukhim, S. Agarwal, S. Sengupta, M. Sundaram, P. Majumder, Predicting clinical response to anticancer drugs using an ex vivo platform that captures tumour heterogeneity. Nat. Commun. 6, 6169-6182 (2015).
22. American Cancer Society. Global Cancer Facts & Figures (American Cancer Society, Atlanta, GA, ed. 2, 2011).
23. FDA Guidance for Industry. Exploratory IND Studies. Guidance (US Department of Health and Human Services, Food and Drug Administration, Center for Drug Evaluation and Research, Washington, DC, 2006).
24. Y. Sugiyama, S. Yamashita, Impact of microdosing clinical study - Why necessary and how useful? Adv. Drug Deliv. Rev. 63, 494-502 (2011).
25. M. G. Hollingshead, Antitumor efficacy testing in rodents. J. Natl. Cancer Inst. 100, 1500-1510 (2008).
26. J. J. Hanfelt, Statistical approaches to experimental design and data analysis of in vivo studies. Breast Cancer Res. Treat. 46, 279-302 (1997).
27. 31P MRS. Acad. Radiol. 14, 1531-1539 (2007).
28. A. E. Carpenter, T. R. Jones, M. R. Lamprecht, C. Clarke, I. H. Kang, O. Friman, D. A. Guertin, J. H. Chang, R. A. Lindquist, J. Moffat, P. Golland, D. M. Sabatini, CellProfiler: Image analysis software for identifying and quantifying cell phenotypes. Genome Biol. 7, R100 (2006).
29. P.Du, W.A. Kibbe,S.M. Lin,lumi: A pipeline for processing Illumina microarray. Bioinformatics 24, 1547-1548 (2008).
30. G. K. Smyth, Limma: Linear models for microarray data, in Bioinformatics and Computational Biology Solutions using R and Bioconductor, V. Carey, R. Gentleman, S. Dudoit, R. Irizarry, and W. Huber, Eds. (Springer, New York, NY, 2005), pp. 397-420.
31. A. Reiner, D. Yekutieli, Y. Benjamini, Identifying differentially expressed genes using false discovery rate controlling procedures. Bioinformatics 19, 368-375 (2003).
32. A. I. Saeed, V. Sharov, J. White, J. Li, W. Liang, N. Bhagabati, J. Braisted, M. Klapa, T. Currier, M. Thiagarajan, A. Sturn, M. Snuffin, A. Razantsev, D. Popov, A. Ryitsov, E. Kostukovich, I. Borisovsky, Z. Liu, A. Vinsavich, V. Trush, J. Quackenbush, TM4: A free, open-source system for microarray data management and analysis. Biotechniques 34, 374-378 (2003).
33. K. Y. Yeung, D. R. Haynor, W. L. Ruzzo, Validating clustering for gene expression data. Bioinformatics 17, 309-318 (2001).
34. D. W. Huang, B. T. Sherman, R. A. Lempicki, Systematic and integrative analysis of large gene lists using DAVID Bioinformatics Resources. Nat. Protoc. 4, 44-57 (2009).
35. D. W. Huang, B. T. Sherman, R. A. Lempicki, Bioinformatics enrichment tools: Paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res. 37, 1-13 (2009).
36. R. Edgar, M. Domrachev, A. E. Lash Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res. 30, 207-210 (2002).