Submitted Successfully!
To reward your contribution, here is a gift for you: A free trial for our video production service.
Thank you for your contribution! You can also upload a video entry or images related to this topic.
Version Summary Created by Modification Content Size Created at Operation
1 -- 1631 2023-07-07 03:22:20 |
2 layout -4 word(s) 1627 2023-07-07 04:01:11 | |
3 format Meta information modification 1627 2023-07-10 09:44:23 |

Video Upload Options

Do you have a full video?

Confirm

Are you sure to Delete?
Cite
If you have any further questions, please contact Encyclopedia Editorial Office.
Liu, X. Patient-Derived Cancer Models and Next-Generation Living Biobanks. Encyclopedia. Available online: https://encyclopedia.pub/entry/46545 (accessed on 18 May 2024).
Liu X. Patient-Derived Cancer Models and Next-Generation Living Biobanks. Encyclopedia. Available at: https://encyclopedia.pub/entry/46545. Accessed May 18, 2024.
Liu, Xuefeng. "Patient-Derived Cancer Models and Next-Generation Living Biobanks" Encyclopedia, https://encyclopedia.pub/entry/46545 (accessed May 18, 2024).
Liu, X. (2023, July 07). Patient-Derived Cancer Models and Next-Generation Living Biobanks. In Encyclopedia. https://encyclopedia.pub/entry/46545
Liu, Xuefeng. "Patient-Derived Cancer Models and Next-Generation Living Biobanks." Encyclopedia. Web. 07 July, 2023.
Patient-Derived Cancer Models and Next-Generation Living Biobanks
Edit

Biobanks provide a platform for innovative biomedical research. Recent scientific advances in cryopreservation have enabled the prospect of establishing “living biobanks” that store viable, functional tissue or replicable cell types for years to decades.

patient-derived cancer models living biobanks

1. Introduction

Traditional cancer models including cell lines and animal models have limited applications in both basic and clinical cancer research. Genomics-based precision oncology only help 2–20% patients with solid cancer. Functional diagnostics and patient-derived cancer models are needed for precision cancer biology. Researchers will summarize applications of conditional cell reprogramming (CR) in cancer research and next generation living biobanks (NGLB). Together with organoids, CR has been cited in two NCI (National Cancer Institute, USA) programs (PDMR: patient-derived cancer model repository; HCMI: human cancer model initiatives. HCMI will be distributed through ATCC). Briefly, the CR method is a simple co-culture technology with a Rho kinase inhibitor, Y-27632, in combination with fibroblast feeder cells, which allows researchersto rapidly expand both normal and malignant epithelial cells from diverse anatomic sites and mammalian species and does not require transfection with exogenous viral or cellular genes. Establishment of CR cells from both normal and tumor tissue is highly efficient. The robust nature of the technique is exemplified by the ability to produce 2 × 106 cells in five days from a core biopsy of tumor tissue. Normal CR cell cultures retain a normal karyotype and differentiation potential and CR cells derived from tumors retain their tumorigenic phenotype. CR also allows researchers to enrich cancer cells from urine (for bladder cancer), blood (for prostate cancer), and pleural effusion (for non-small cell lung carcinoma). The ability to produce inexhaustible cell populations using CR technology from small biopsies and cryopreserved specimens has the potential to transform biobanking repositories (NGLB: next-generation living biobank) and current pathology practice by enabling genetic, biochemical, metabolomic, proteomic, and biological assays, including chemosensitivity testing as a functional diagnostics tool for precision cancer medicine.

2. Patient-Derived Cancer Models and Cell Cultures are Needed for Precision Oncology

2.1. iPS (Induce Pluripotent Stem) Cells

Both embryonic and adult stem cells can be propagated in vitro and these cells retain a normal karyotype and can differentiate into several germ layers, providing great potential for applications in regenerative medicine [1][2]. Several recent review articles summarized applications if iPS in cancer modeling [3][4][5][6][7].

2.2. Organoid Cultures

The laboratories of Clevers, Kuo and others successfully established organoid cultures initially from mouse tissues [8][9][10][11][12][13]. These studies have now been extended to human specimens, both normal and tumor. Organoid cultures provide a platform to investigate basic biology for early stage cancers, to identify drug targets, and to study drug resistance [12][14][15][16][17][18][19][20][21]. Unlike monolayer cell lines that are grown on plastic, organoid cultures are established using three-dimensional growth of epithelial cells in Matrigel™. These cultures are fairly stable genetically, can be grown for a long period of time and are not clonal in selection, but rather capture partial heterogeneity of the original tumor. Paired normal and cancer organoids can be established from the same patient samples, thereby providing an opportunity for its application to personalized medicine and regenerative medicine. Precise tumor tissue sampling is very crucial for organoid cultures as this culture system propagates both normal and cancer cells. Additionally, these cultures are more suitable for low-throughput rather than high throughput drug screening [20][21]. Overall it takes 4-6 weeks to provide enough cells for drug screening [22].

2.3. Patient-Derived Xenografts (PDX)

In recent years patient-derived xenografts have emerged as a viable system for modeling human tumors in vitro [23][24]. Unlike cell lines, such as lack of stromal components, clonal selection, and genetic drift due to long-term culturing conditions, PDX models cross-talk between stromal components and epithelial tumor cells, appear to have high genetic stability, especially during early passages, and can preserve the molecular and cellular heterogeneity of the primary tumor. In addition, PDX models appear to predict metastatic potential and response too [25]. Currently, PDXs are still widely recognized as a more physiologically relevant preclinical model to standard cell line xenografts. PDX models faithfully recapitulate the original patient genetic profile, gene expression patterns and tissue histology. Despite their benefits, PDX models are limited by their inherent variability, lower throughput and lack of growth in vitro. The ability to generate cell lines from PDX models would enable high throughput chemosensitivity screens, ex vivo genetic manipulation and the development of novel orthotopic models. Development of stable PDX cell lines remains a challenge due to murine stromal outgrowth, lineage commitment and limited differentiation potential. Overall, it takes 2–5 month for PDX expansion at a relatively high cost of mice and their care.

2.4. Conditionally Reprogrammed Cells (CRCs)

It remains a challenge to establish a single model system that is rapid, simple to perform, and has a high rate of success. The CRC method researchers developed at Georgetown meets these needs. The culture method can rapidly convert normal and tumor cells to a state of “reprogrammed stem-like” in which the cells are highly proliferative and maintain their original karyotypes; moreover, the removal of these conditions restores the capacity for cell differentiation [26][27][28]. Thus, researchers named this method “conditional reprogramming”. As researchers have described below in the detailed protocols. Briefly, the tissue samples are first evaluated histologically by a pathologist to determine the composition of the sample (i.e., what percentage of the cells are tumor cells). The samples are then dispersed into single cells by enzymatic digestion and plated in a medium containing irradiated Swiss-3T3-J2 mouse fibroblasts (feeder cells) and 10 µM Y-27632. Epithelial colonies are readily observed at two days and usually proliferate rapidly to reach confluence in approximately five days. The conditional reprogramming method is applicable to many epithelial tissues including skin, prostate, lung, breast, kidney, salivary gland and liver cell types and it has recently been extended to neuroendocrine and endocrine tissues. Interestingly, the method seems generally applicable to many mammalian species such as mouse, rat, dog, ferret, horse, and cow [29][30][31][32][33][34]. An important feature is that these cultures can be used for establishing xenografts [26][27] and patient-derived xenograft cell lines [35] and can also be used to generate cell cultures from PDX and organoid cultures. Finally, conditionally reprogrammed cells retain cell lineage commitment and maintain the heterogeneity of cells present in a biopsy [26][27][36][37][38][39].

3. Next-Generation Living Biobanks (NGLB)

Living Biobanks will have a significant impact across basic biological research, medicine and the biopharma industry; however, the effects of such applications are underexplored. Recent approaches, for example, patient-derived xenograft models, organoids, conditionally reprogrammed cells, induced pluripotent cells, and other cancer precision medicine applications, represent an unexhausted resource of living biobanks. However, these concepts are applied in very many different ways by the academic and private sectors, representing an actively growing field that has yet to reach clinical consensus or maturity. Here researchers summarize application of CR technology in living biobanks.
28–29 March 2011, researchers first presented “bring biobank to life” at BRN 2011 Symposium “Advancing Cancer Research Through Biospecimen Science” of NCI when researchers started CR technology [26][40]. Editor in Chief of American Journal of Pathology proposed applications of CR technology in living biobanks [40]. Eventually, more and more articles came out for tumor living biobanks as the applications of CRC and organoid cultures [13][19][22][28][36][41][42][43][44][45][46][47][48][49][50][51][52][53][54][55][56][57][58]. However, that will be impossible task in terms of efforts, work load and cost if one would like to establish living biobanks from every patient in the hospital for the immediate use of personalized medicine. In order to balance of distribution of disease types for research and industry, it’s extremely important to cryopreserved tissue specimens and will generate cell cultures using CR and/or organoids technologies. Thus, researchers brought forth a new concept: next generation living biobank (NGLB) (Figure 1). Except for immediate use of personalized diagnostics and treatment, researchers suggest to collect and cryopreserve specimens including surgical specimens, core biopsies, needle biopsies, brushed cells, or cells from liquid biopsies (blood, urine, etc.). These specimens should be collected and stored together with their corresponding -omics (genomic, transcriptomic, proteomic, metabolomic, etc.) and clinical information. Then, CR technology will be used to generate an unexhausted cell cultures for living cell banks for future demands in drug discovery, disease modeling, regenerative medicine. These cryopreserved specimens, their corresponding CR cells and CRC- derivatives together compose of NGLB (Figure 1). Compared to regular living biobanks, this NGLB strategy would be a highly efficient platform with the minimal time, money, and other support, this may also avoid redundant cell lines from common diseases, for example, lung cancers. Most importantly, this NBLG includes cryopreserved specimens with broader coverage of disease types, which allow researchers to generate cell cultures from rare disease using CR or organoids cultures, since there are no available cell models or very few cell lines for many rare diseases, for example, adenoid cystic carcinoma (ACC), neuroendocrine cancer, etc. Researchers also list properties of conventional cell lines, CRC, organoids and PDX in basic and translational cancer research (Table 1).
Figure 1. Workflow of next generation living biobanks (NGLB). Specimens including surgical specimens, core biopsies, needle biopsies, brushed cells, or cells from liquid biopsies (blood, urine, etc.) from patients with disease and/or different stages of disease (for example, before and after treatment, primary or metastatic, etc.) will be collected, cryopreserved, and stored together with their corresponding -omics (genomic, transcriptomic, proteomic, metabolomic, etc.) and clinical information. CR technology will be used to generate an unexhausted cell cultures for living cell banks for future demands in drug discovery, disease modeling, regenerative medicine. CR cells can be used to generate other types of living biobanks such organoids or patient-derived xenografts (PDX) (for tumor).
Table 1. Comparison of a patient-derived cancer models.
  Conventional Cell Lines Organoids PDX CRC
Sample size
FNA +/− +++
Core Biopsy + +++
Surgical Specimens + +++ ++ +++
Timing dozen days 1-5 weeks 1-5mont 1-10 days
Success rate of initiation + 0–10% ++ (5–80%) ++ (2–30%) +++50–100%
Tumor type specific
Rapid Expansion +++ ++ + +++
Matched Normal con + - +
Karyotypic stability ++ N/A ++
3D growth + +++
Representation of tumor + ++ ++ ++
Genetic manipulation +++ ++ ++
Maintenance (passage) +++ ++ + +++
LT drug screens +++ + +++
HT drug screens +++ ++ +++
Heterogeneity ++ +++ ++
Tumor–stroma interaction ++

References

  1. Curry, E.L.; Moad, M.; Robson, C.N.; Heer, R. Using induced pluripotent stem cells as a tool for modelling carcinogenesis. World J. Stem Cells 2015, 7, 461–469.
  2. Seki, T.; Fukuda, K. Methods of induced pluripotent stem cells for clinical application. World J. Stem Cells 2015, 7, 116–125.
  3. Marin Navarro, A.; Susanto, E.; Falk, A.; Wilhelm, M. Modeling cancer using patient-derived induced pluripotent stem cells to understand development of childhood malignancies. Cell Death Discov. 2018, 4, 7.
  4. Shi, Y.; Inoue, H.; Wu, J.C.; Yamanaka, S. Induced pluripotent stem cell technology: A decade of progress. Nat. Reviews. Drug Discov. 2017, 16, 115–130.
  5. Rowe, R.G.; Daley, G.Q. Induced pluripotent stem cells in disease modelling and drug discovery. Nat. Rev. Genet. 2019, 20, 377–388.
  6. Papaetrou, E.P. Author Correction: Patient-derived induced pluripotent stem cells in cancer research and precision oncology. Nat. Med. 2019, 25, 861.
  7. Papapetrou, E.P. Patient-derived induced pluripotent stem cells in cancer research and precision oncology. Nat. Med. 2016, 22, 1392–1401.
  8. Boj, S.F.; Hwang, C.I.; Baker, L.A.; Chio, I.I.; Engle, D.D.; Corbo, V.; Jager, M.; Ponz-Sarvise, M.; Tiriac, H.; Spector, M.S.; et al. Organoid models of human and mouse ductal pancreatic cancer. Cell 2015, 160, 324–338.
  9. Drost, J.; van Jaarsveld, R.H.; Ponsioen, B.; Zimberlin, C.; van Boxtel, R.; Buijs, A.; Sachs, N.; Overmeer, R.M.; Offerhaus, G.J.; Begthel, H.; et al. Sequential cancer mutations in cultured human intestinal stem cells. Nature 2015, 521, 43–47.
  10. Li, X.; Nadauld, L.; Ootani, A.; Corney, D.C.; Pai, R.K.; Gevaert, O.; Cantrell, M.A.; Rack, P.G.; Neal, J.T.; Chan, C.W.; et al. Oncogenic transformation of diverse gastrointestinal tissues in primary organoid culture. Nat. Med. 2014, 20, 769–777.
  11. Nadauld, L.D.; Garcia, S.; Natsoulis, G.; Bell, J.M.; Miotke, L.; Hopmans, E.S.; Xu, H.; Pai, R.K.; Palm, C.; Regan, J.F.; et al. Metastatic tumor evolution and organoid modeling implicate TGFBR2 as a cancer driver in diffuse gastric cancer. Genome Biol. 2014, 15, 428.
  12. Sachs, N.; Clevers, H. Organoid cultures for the analysis of cancer phenotypes. Curr. Opin. Genet. Dev. 2014, 24, 68–73.
  13. van de Wetering, M.; Francies, H.E.; Francis, J.M.; Bounova, G.; Iorio, F.; Pronk, A.; van Houdt, W.; van Gorp, J.; Taylor-Weiner, A.; Kester, L.; et al. Prospective derivation of a living organoid biobank of colorectal cancer patients. Cell 2015, 161, 933–945.
  14. Cheung, K.J.; Gabrielson, E.; Werb, Z.; Ewald, A.J. Collective invasion in breast cancer requires a conserved basal epithelial program. Cell 2013, 155, 1639–1651.
  15. Ewald, A.J. 3D cell biology—the expanding frontier. J. Cell Sci. 2017, 130, 1.
  16. Shamir, E.R.; Ewald, A.J. Three-dimensional organotypic culture: Experimental models of mammalian biology and disease. Nat. Reviews. Mol. Cell Biol. 2014, 15, 647–664.
  17. Xu, H.; Lyu, X.; Yi, M.; Zhao, W.; Song, Y.; Wu, K. Organoid technology and applications in cancer research. J. Hematol. Oncol. 2018, 11, 116.
  18. Tuveson, D.; Clevers, H. Cancer modeling meets human organoid technology. Science 2019, 364, 952–955.
  19. Artegiani, B.; Clevers, H. Use and application of 3D-organoid technology. Hum. Mol. Genet. 2018, 27, R99–R107.
  20. Pauli, C.; Hopkins, B.D.; Prandi, D.; Shaw, R.; Fedrizzi, T.; Sboner, A.; Sailer, V.; Augello, M.; Puca, L.; Rosati, R.; et al. Personalized In Vitro and In Vivo Cancer Models to Guide Precision Medicine. Cancer Discov. 2017, 7, 462–477.
  21. Puca, L.; Bareja, R.; Prandi, D.; Shaw, R.; Benelli, M.; Karthaus, W.R.; Hess, J.; Sigouros, M.; Donoghue, A.; Kossai, M.; et al. Patient derived organoids to model rare prostate cancer phenotypes. Nat. Commun. 2018, 9, 2404.
  22. Xinaris, C. Organoids for replacement therapy: Expectations, limitations and reality. Curr. Opin. Organ. Transpl. 2019, 24, 555–561.
  23. Jin, K.; Teng, L.; Shen, Y.; He, K.; Xu, Z.; Li, G. Patient-derived human tumour tissue xenografts in immunodeficient mice: A systematic review. Clin. Transl. Oncol.: Off. Publ. Fed. Span. Oncol. Soc. Natl. Cancer Inst. Mex. 2010, 12, 473–480.
  24. Tentler, J.J.; Tan, A.C.; Weekes, C.D.; Jimeno, A.; Leong, S.; Pitts, T.M.; Arcaroli, J.J.; Messersmith, W.A.; Eckhardt, S.G. Patient-derived tumour xenografts as models for oncology drug development. Nat. Reviews. Clin. Oncol. 2012, 9, 338–350.
  25. Williams, S.A.; Anderson, W.C.; Santaguida, M.T.; Dylla, S.J. Patient-derived xenografts, the cancer stem cell paradigm, and cancer pathobiology in the 21st century. Lab. Investig. 2013, 93, 970–982.
  26. Liu, X.; Ory, V.; Chapman, S.; Yuan, H.; Albanese, C.; Kallakury, B.; Timofeeva, O.A.; Nealon, C.; Dakic, A.; Simic, V.; et al. ROCK inhibitor and feeder cells induce the conditional reprogramming of epithelial cells. Am. J. Pathol. 2012, 180, 599–607.
  27. Suprynowicz, F.A.; Upadhyay, G.; Krawczyk, E.; Kramer, S.C.; Hebert, J.D.; Liu, X.; Yuan, H.; Cheluvaraju, C.; Clapp, P.W.; Boucher, R.C., Jr.; et al. Conditionally reprogrammed cells represent a stem-like state of adult epithelial cells. Proc. Natl. Acad. Sci. USA. 2012, 109, 20035–20040.
  28. Liu, X.; Krawczyk, E.; Suprynowicz, F.A.; Palechor-Ceron, N.; Yuan, H.; Dakic, A.; Simic, V.; Zheng, Y.-L.; Sripadhan, P.; Chen, C.; et al. Conditional reprogramming and long-term expansion of normal and tumor cells from human biospecimens. Nat. Protoc. 2017, 12, 439.
  29. Alamri, A.M.; Kang, K.; Groeneveld, S.; Wang, W.; Zhong, X.; Kallakury, B.; Hennighausen, L.; Liu, X.; Furth, P.A. Primary cancer cell culture: Mammary-optimized vs conditional reprogramming. Endocr. Relat. Cancer 2016, 23, 535–554.
  30. Gardell, A.M.; Qin, Q.; Rice, R.H.; Li, J.; Kültz, D. Derivation and osmotolerance characterization of three immortalized tilapia (Oreochromis mossambicus) cell lines. PLoS ONE 2014, 9, e95919.
  31. Wang, L.; Ye, L.; Wei, G.; Chen, Y.; Ye, L.; Wu, X.; Zeng, Z.; Wang, Y.; Yin, G.; Long, X.; et al. Conditional reprogrammed human limbal epithelial cells represent a novel in vitro cell model for drug responses. Biochem. Biophys. Res. Commun. 2018, 499, 735–742.
  32. Alkhilaiwi, F.; Wang, L.; Zhou, D.; Raudsepp, T.; Ghosh, S.; Paul, S.; Palechor-Ceron, N.; Brandt, S.; Luff, J.; Liu, X.; et al. Long-term expansion of primary equine keratinocytes that maintain the ability to differentiate into stratified epidermis. Stem Cell Res. Ther. 2018, 9, 181.
  33. O’Malley, Y.; Rotti, P.G.; Thornell, I.M.; Vanegas Calderón, O.G.; Febres-Aldana, C.; Durham, K.; Yao, J.; Li, X.; Zhu, Z.; Norris, A.W.; et al. Development of a polarized pancreatic ductular cell epithelium for physiological studies. J. Appl. Physiol. 2018, 125, 97–106.
  34. Saffari, P.S.; Vapniarsky, N.; Pollack, A.S.; Gong, X.; Vennam, S.; Pollack, A.J.; Verstraete, F.J.M.; West, R.B.; Arzi, B.; Pollack, J.R. Most canine ameloblastomas harbor HRAS mutations, providing a novel large-animal model of RAS-driven cancer. Oncogenesis 2019, 8, 11.
  35. McAuliffe, P.F.; Evans, K.W.; Akcakanat, A.; Chen, K.; Zheng, X.; Zhao, H.; Eterovic, A.K.; Sangai, T.; Holder, A.M.; Sharma, C.; et al. Ability to Generate Patient-Derived Breast Cancer Xenografts Is Enhanced in Chemoresistant Disease and Predicts Poor Patient Outcomes. PLoS ONE 2015, 10, e0136851.
  36. Saeed, K.; Rahkama, V.; Eldfors, S.; Bychkov, D.; Mpindi, J.P.; Yadav, B.; Paavolainen, L.; Aittokallio, T.; Heckman, C.; Wennerberg, K.; et al. Comprehensive Drug Testing of Patient-derived Conditionally Reprogrammed Cells from Castration-resistant Prostate Cancer. Eur. Urol. 2016.
  37. Beglyarova, N.; Banina, E.; Zhou, Y.; Mukhamadeeva, R.; Andrianov, G.; Bobrov, E.; Lysenko, E.; Skobeleva, N.; Gabitova, L.; Restifo, D.; et al. Screening of Conditionally Reprogrammed Patient-Derived Carcinoma Cells Identifies ERCC3-MYC Interactions as a Target in Pancreatic Cancer. Clin. Cancer Res. 2016, 22, 6153–6163.
  38. Walters, B.J.; Diao, S.; Zheng, F.; Walters, B.J.; Layman, W.S.; Zuo, J. Pseudo-immortalization of postnatal cochlear progenitor cells yields a scalable cell line capable of transcriptionally regulating mature hair cell genes. Sci. Rep. 2015, 5, 17792.
  39. Brown, D.D.; Dabbs, D.J.; Lee, A.V.; McGuire, K.P.; Ahrendt, G.M.; Bhargava, R.; Davidson, N.E.; Brufsky, A.M.; Johnson, R.R.; Oesterreich, S.; et al. Developing in vitro models of human ductal carcinoma in situ from primary tissue explants. Breast Cancer Res. Treat. 2015, 153, 311–321.
  40. Lisanti, M.P.; Tanowitz, H.B. Translational discoveries, personalized medicine, and living biobanks of the future. Am. J. Pathol. 2012, 180, 1334–1336.
  41. Sachs, N.; de Ligt, J.; Kopper, O.; Gogola, E.; Bounova, G.; Weeber, F.; Balgobind, A.V.; Wind, K.; Gracanin, A.; Begthel, H.; et al. A Living Biobank of Breast Cancer Organoids Captures Disease Heterogeneity. Cell 2018, 172, 373–386 e310.
  42. Mullenders, J.; de Jongh, E.; Brousali, A.; Roosen, M.; Blom, J.P.A.; Begthel, H.; Korving, J.; Jonges, T.; Kranenburg, O.; Meijer, R.; et al. Mouse and human urothelial cancer organoids: A tool for bladder cancer research. Proc. Natl. Acad. Sci. USA 2019.
  43. Weeber, F.; Ooft, S.N.; Dijkstra, K.K.; Voest, E.E. Tumor Organoids as a Pre-clinical Cancer Model for Drug Discovery. Cell Chem. Biol. 2017.
  44. Mondal, A.M.; Ma, A.H.; Li, G.; Krawczyk, E.; Yuan, R.; Lu, J.; Schlegel, R.; Stamatakis, L.; Kowalczyk, K.J.; Philips, G.K.; et al. Fidelity of a PDX-CR model for bladder cancer. Biochem. Biophys. Res. Commun. 2019, 517, 49–56.
  45. Martini, A.; Sfakianos, J.P.; Galsky, M.D. Conditionally Reprogrammed Patient-derived Cells: A Step Forward Towards Personalized Medicine? Eur. Urol. 2019, 76, 435–436.
  46. Krawczyk, E.; Hong, S.H.; Galli, S.; Trinh, E.; Wietlisbach, L.; Misiukiewicz, S.F.; Tilan, J.U.; Chen, Y.S.; Schlegel, R.; Kitlinska, J. Murine neuroblastoma cell lines developed by conditional reprogramming preserve heterogeneous phenotypes observed in vivo. Lab. Investig. A J. Tech. Methods Pathol. 2019.
  47. Kettunen, K.; Bostrom, P.J.; Lamminen, T.; Heinosalo, T.; West, G.; Saarinen, I.; Kaipio, K.; Rantala, J.; Albanese, C.; Poutanen, M.; et al. Personalized Drug Sensitivity Screening for Bladder Cancer Using Conditionally Reprogrammed Patient-derived Cells. Eur. Urol. 2019, 76, 430–434.
  48. Jiang, S.; Wang, J.; Yang, C.; Tan, R.; Hou, J.; Shi, Y.; Zhang, H.; Ma, S.; Wang, J.; Zhang, M.; et al. Continuous culture of urine-derived bladder cancer cells for precision medicine. Protein Cell 2019.
  49. Yip, Y.L.; Lin, W.; Deng, W.; Jia, L.; Lo, K.W.; Busson, P.; Verillaud, B.; Liu, X.; Tsang, C.M.; Lung, M.L.; et al. Establishment of a nasopharyngeal carcinoma cell line capable of undergoing lytic Epstein-Barr virus reactivation. Lab. Investig. 2018, 98, 1093–1104.
  50. Saito, R.; Smith, C.C.; Utsumi, T.; Bixby, L.M.; Kardos, J.; Wobker, S.E.; Stewart, K.G.; Chai, S.; Manocha, U.; Byrd, K.M.; et al. Molecular Subtype-Specific Immunocompetent Models of High-Grade Urothelial Carcinoma Reveal Differential Neoantigen Expression and Response to Immunotherapy. Cancer Res. 2018, 78, 3954–3968.
  51. Jin, L.; Qu, Y.; Gomez, L.J.; Chung, S.; Han, B.; Gao, B.; Yue, Y.; Gong, Y.; Liu, X.; Amersi, F.; et al. Characterization of primary human mammary epithelial cells isolated and propagated by conditional reprogrammed cell culture. Oncotarget 2018, 9, 11503–11514.
  52. Alamri, A.M.; Liu, X.; Blancato, J.K.; Haddad, B.R.; Wang, W.; Zhong, X.; Choudhary, S.; Krawczyk, E.; Kallakury, B.V.; Davidson, B.J.; et al. Expanding primary cells from mucoepidermoid and other salivary gland neoplasms for genetic and chemosensitivity testing. Dis. Model. Mech. 2018, 11.
  53. Yuan, H.; Krawczyk, E.; Blancato, J.; Albanese, C.; Zhou, D.; Wang, N.; Paul, S.; Alkhilaiwi, F.; Palechor-Ceron, N.; Dakic, A.; et al. HPV positive neuroendocrine cervical cancer cells are dependent on Myc but not E6/E7 viral oncogenes. Sci. Rep. 2017, 7, 45617.
  54. Timofeeva, O.A.; Palechor-Ceron, N.; Li, G.; Yuan, H.; Krawczyk, E.; Zhong, X.; Liu, G.; Upadhyay, G.; Dakic, A.; Yu, S.; et al. Conditionally reprogrammed normal and primary tumor prostate epithelial cells: A novel patient-derived cell model for studies of human prostate cancer. Oncotarget 2017, 8, 22741–22758.
  55. Suprynowicz, F.A.; Kamonjoh, C.M.; Krawczyk, E.; Agarwal, S.; Wellstein, A.; Agboke, F.A.; Choudhury, S.; Liu, X.; Schlegel, R. Conditional cell reprogramming involves non-canonical beta-catenin activation and mTOR-mediated inactivation of Akt. PLoS ONE 2017, 12, e0180897.
  56. Mahajan, A.S.; Sugita, B.M.; Duttargi, A.N.; Saenz, F.; Krawczyk, E.; McCutcheon, J.N.; Fonseca, A.S.; Kallakury, B.; Pohlmann, P.; Gusev, Y.; et al. Genomic comparison of early-passage conditionally reprogrammed breast cancer cells to their corresponding primary tumors. PLoS ONE 2017, 12, e0186190.
  57. Chen, C.; Choudhury, S.; Wangsa, D.; Lescott, C.J.; Wilkins, D.J.; Sripadhan, P.; Liu, X.; Wangsa, D.; Ried, T.; Moskaluk, C.; et al. A multiplex preclinical model for adenoid cystic carcinoma of the salivary gland identifies regorafenib as a potential therapeutic drug. Sci. Rep. 2017, 7, 11410.
  58. Borodovsky, A.; McQuiston, T.J.; Stetson, D.; Ahmed, A.; Whitston, D.; Zhang, J.; Grondine, M.; Lawson, D.; Challberg, S.S.; Zinda, M.; et al. Generation of stable PDX derived cell lines using conditional reprogramming. Mol. Cancer 2017, 16, 177.
More
Information
Contributor MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register :
View Times: 299
Revisions: 3 times (View History)
Update Date: 10 Jul 2023
1000/1000