SciFed Drug Delivery Research Journal

Drug Sensitivity Tests for Personalized Cancer Therapy

Review Article

Received on: October 22, 2017

Accepted on: October 26, 2017

Published on: November 3, 2017

Johnny Kuan-Un Wong, *Ada Hang-Heng Wong

*Corresponding author: Ada Hang-Heng Wong, Cancer Centre, Faculty of Health Sciences, University of Macau, Macau. E-mail: adahhwong@umac. mo; Tel: +853-8822 4841



        Personalized cancer therapy is defned as the tailoring of therapies according to the genetic profle and molecular background of individual patients. Therapeutic strategy is designed based on empirical and bioinformatics analysis of each individual cancer sample. Personalized cancer therapy is proposed to be the future of cancer treatment that can provide patients with maximal treatment effciency and less toxicity.
          In the past, cancer treatment is administered to patients solely based on the origin and stage of cancer. However, researchers and doctors gradually realized that the same treatment that suits one patient might have a different outcome when treating another patient with the same cancer. In the late 1940s, Jane Cooke Wright, M.D., started to explore the tailoring of cancer treatment by correlating the in vitro and in vivo response of her patients' cancer biopsy [1]. Nevertheless, limited progress was achieved due to limited technology, insuffcient research and legislation issues on human subjects. The $215 million Precision Medicine Initiative®announced by former US president Barack Obama in his 2015 State of the Union address [2] promoted research and accelerated clinical drug approval. On one hand, the US Food and Drug Administration (FDA) have accelerated approval for drugs in targeted therapy and immunotherapy that have signifcant anti-cancer effect [3]. On the other hand, the US FDA rapidly approved clinical diagnostic tests including genetic tests [4], circulating tumor cell (CTC) harvesting kits [5,6], etc. which greatly improved personalization of cancer therapy in clinico. On the global scale, many countries have initiated funding programs towards personalized cancer therapy including China, the UK, and many countries in Europe. 
         Broadening of diagnostic and therapeutic spectra provided clinical doctors with more options (Table1). However, guidelines on making therapeutic decisions lagged behind. Unlike targeted therapy that has very specifc biomarkers to trace, the outcomes of many treatment options could hardly be predicted before treatment. Hence, evidence-based drug sensitivity tests emerged to address this issue.  
Chemotherapy: A Double-Edged Sword
            Among all types of cancer treatment methods, chemotherapy remains the most prevalent method due to its feasibility in most cancers and affordable cost. However, chemotherapy has diverse response in different cancer patients and strong side effects. Hence, drug sensitivity test to screen for effective chemotherapy drugs with low toxicity will optimize decision-making. 
         In order to carry out drug sensitivity tests, biopsy is usually carried out to retrieve primary cancerous tissues from patients. Liquid biopsy enables harvesting of large quantities of cancer cells in blood-borne cancers that can be directly used for drug screening. CTC extraction from liquid biopsy followed by in vitro amplifcation is vastly tested, but effcacy is mainly achieved in late-stage cancers. Needle biopsy on solid tumors followed by in vitro tumor amplification is applicable to early-stage cancers, but is limited to superfcial tumors. 
       Tumor amplifcation can be done by patient derived xenograft (PDX) models, two-dimensional (2D) monolayer cell culture and three-dimensional (3D) organoid culture. While PDX model is considered as a relevant in vivo model [9], the time consumption of more than 2-4 months [9, 10], low screening throughput and cost of model establishment remains the biggest concern for real-life applications. Some researchers thus proposed the use of PDX-derived cell lines as complementation for mouse models to perform high throughput drug screening. In parallel, humanized mouse models have been adapted to optimize tumor microenvironment. Alternatively, in vitro models have been developed for high throughput drug screening to circumvent the drawbacks of xenograft models. 2D monolayer cultured cell lines are derived from primary tumors [11] due to its capability to grow rapidly in vitro. However, monolayer cultured cells are considered less relevant nowadays with our enhanced knowledge of tumor micro-environment. In light of this, National Cancer Institute (NCI) announced abolishment of using NCI-60 cancer cell lines for future drug screening tests [ 12]. 3D organoid culture was frst developed in 1950s [ 13, 14], but did not gain attention in drug screening until recent years [15, 16]. The mimicry of 3D environment in organoid cultures is its major virtue, and proves it to be more closely representative of its primary tumor. Furthermore, researchers are also trying to optimize tumor microenvironment in organoid cultures by adding stromal cells and blood vessel-mimicking modules by architectural engineering of culture devices [17, 18]. However, these methods are still at its infant stage and cannot replace in vivo models up to date. 
        In contrast to tumor amplification, reducing sample requirement for high-throughput drug screening by application of microfluidic devices is an alternative approach. These methods mainly compensate for the long amplifcation time and limited sample quantity. For instance, a novel droplet microfluidics technique was adapted to screen multiple treatment conditions in parallel using human primary tumor dissociated cells suspended in nano-liter droplets with a rapid turnover between 16-24 hours [19]. Nevertheless, resuspended cancer cells lack the diversity of micro-environment. In order to assess the propensity of whole tissue response, insertional microfluidic device was developed for in situ drug screening by Jonas, et al [20]. Nevertheless, tissue screening had limited throughput and are barely feasible on tiny early- stage cancer samples. 
Conclusion and Insight 
          Although drug sensitivity tests were shown to provide insight to clinical decision, more research is needed to prove that any of the methods are reliable in clinico. A major hurdle is legal regulation on clinical trials. For countries where off-label drug administration is legal, the risk of medical liability deters many clinical doctors to try adopting treatment options suggested by drug sensitivity tests. Notwithstanding, collaboration between research institutes and hospitals is gaining momentum after government-initiated movements were engaged. In addition to efforts on fostering genetic sequencing and drug sensitivity tests, advancement in gene editing techniques like the CRISPR/Cas9 system [ 21] could greatly enhance the establishment of in vivo models for disease analysis. Immune hijacking by training the patients' own immune cells (CAR-T) provides an alternative route in personalized cancer therapy. However, application and limitation of immunotherapy remained elusive. Preliminary studies on combining meta-analysis of relevant medical records including treatment regimens and outcome in correlation to genetic tests, histopathology results, etc, have also been initiated in various countries. Nevertheless, the comprehensiveness and accuracy of medical recording systems typically varies, hence cautions on the interpretation of these data. 
       In conclusion, although drug sensitivity tests provide evidence-based insight for therapeutic decisionmaking, the combination of other analytic methods is critical. More research is needed to improve each method, and more relaxed legal regulation regarding clinical trials might promote these pursuits. 
       This research is supported by Macao Science and Technology Development Fund (FDCT) Grant FDCT/137/2016/A



  1. Longo DL (2013) Personalized Cancer Care Is Not New. Oncologist 18: 644-645.
  2. The Precision Medicine Initiative (2016) White House.
  3. Hematology/Oncology (Cancer) Approvals and Safety Notifcations (2017).
  4. FDA allows marketing of frst direct-to-consumer tests that provide genetic risk information for certain conditions. At   
  5. Ozkumur E et al (2013) Inertial Focusing for Tumor AntigenDependent and -Independent Sorting of Rare Circulating Tumor Cells Sci Transl Med 5.
  6. Yu M et al  (2014) Ex vivo culture of circulating breast tumor cells for individualized testing of drug susceptibility. 345: 216- 220.
  7. Lee DW et al  (2014) How I Treat: Current concepts in the diagnosis and management of cytokine release syndrome. Blood 124: 188-196.
  8. Hacein-Bey-Abina S (2003) LMO2-Associated Clonal T cell Proliferation in Two Patients after Gene Therapy for SCID-X1. Science 302: 415-419.
  9. Kim MP et al (2009) Generation of orthotopic and heterotopic human pancreatic cancer xenografts in immunodefcient mice. Nat Protoc 4: 1670-1680.
  10. Day CP, Merlino G, Van Dyke T (2015) Preclinical Mouse Cancer Models: A Maze of Opportunities and Challenges. Cell 163: 39-53.
  11. Scherer WF (1953) Studies on the Propagation in Vitro of Poliomyelitis Viruses: Iv. Viral Multiplication in a Stable Strain of Human Malignant Epithelial Cells (Strain Hela) Derived From an Epidermoid Carcinoma of the Cervix. J Exp Med 97: 695-710.
  12. Callaway E (2017) New concerns raised over value of genome-wide disease studies. Nature 546: 463-463.
  13. Earle WR et al (1951) Growth of Animal Tissue Cells on Three-Dimensional Substrates. JNCI J Natl Cancer Inst 12: 179-196.
  14. Leighton et al  (1968) Patterns of Three-dimensional Growth in Vitro in Collagen-coated Cellulose Sponge: Carcinomas and Embryonic Tissues. Cancer Res. 28: 286-296.
  15. Kupchik HZ et al  (1990) Chemotherapy screening assay using 3- dimensional cell culture. Cancer Lett 51: 11-16.
  16. Kopf-Maier P, Kolon B (1992) An organoid culture assay (OCA) for determining the drug sensitivity of human tumors. Int J Cancer 51: 99-107.
  17. Xu X et al  (2014) Three-Dimensional In Vitro Tumor Models for Cancer Research and Drug Evaluation. Biotechnol Adv. 32: 1256-1268.
  18. Quail D, Joyce J (2013) Microenvironmental regulation of tumor progression and metastasis. Nat Med 19: 1423-1437 .
  19. Wong, A. H.-H. et al  (2017) Drug screening of cancer cell lines and human primary tumors using droplet microfluidics. Sci Rep 7: 9109.
  20. Jonas O et al (2015) An implantable microdevice to perform high-throughput in vivo drug sensitivity testing in tumors. Sci Transl Med 7: 284.
  21. Wang H, et al  (2013) One-step generation of mice carrying mutations in multiple genes by CRISPR/cas-mediated genome engineering.