Category: Preclinical Development
Purpose: Lung cancer is the second most common cancer in both men and women around the world, and 85% of it is non-small cell lung cancer (NSCLC). There were estimated 234,030 cases of lung cancer and 154,050 deaths from lung cancer in 2018. The prognosis of lung cancer is poor (< 10% 5-year survival rate for advanced NSCLC), which can be partly attributed to limitations in bio-models that screen for drug candidates against lung cancer. Traditionally, the most commonly used in vitro method for screening therapeutic drugs is monolayer cultures of cancer cells, which are convenient and of low cost. However, monolayer cell culture models are unable to reproduce many properties of solid tumors in vivo, such as the morphological features and the microenvironment including cellular heterogeneity, cell-cell interactions, and gradients of oxygen, pH, and nutrients. Consequently, many drug candidates would display activities in such models that later cannot sustain in animal and clinical studies, which increases the overall time and cost to develop viable anticancer medications. Alternative in vitro models based on three-dimensional multicellular spheroids (MCS) have been developed to better mimic features of lung cancer in clinic. Compared to monolayer cells, the multicellular spheroids can better simulate drug penetration and drug resistance in solid tumors. Therefore, multicellular spheroids represent a promising in vitro model to evaluate the efficacy of anticancer drugs.
The purpose of this study is to systemically assess the activity of a number of anticancer drugs in both the monolayer and the multicellular spheroids of the human NSCLC cells, A549. The data will then be compared to the clinical outcome of the anticancer drugs to assess the ability of MCS and monolayer cell cultures to predict drug efficacy against lung cancer in clinic.
Methods: A549 cells (human lung cancer) were seeded in 96 well plates and 96 well ultra-low attachment plates at 5000 cells/well to grow into monolayers and multicellular spheroids, respectively. The monolayer cells and the multicellular spheroids were then treated with established anticancer agents (cisplatin, carboplatin, doxorubicin and gemcitabine) at a series of concentrations 24 hours and 5 days after seeding, respectively. The viability of the monolayer cells and the multicellular spheroids was assayed after 72 hours of continuous drug exposure to test and compare their sensitivity to the drug treatments.
Results: IC50 values of cisplatin in A549 monolayers and A549 MCS were 10.08 μM and 18.47 μM, respectively; those of carboplatin were 136.6 μM and 264.1 μM; those of doxorubicin are 0.41 μM and 8.61 μM; those of gemcitabine are 0.03 μM on monolayer and greater than 250 μM on MCS. Ratios of IC50 value in MCS to monolayers were also calculated for each anticancer drug, which were 1.83 folds in cisplatin, 1.93 folds in carboplatin and 21 folds in doxorubicin. (Data is shown in table 1 and representative figures are shown in figure 1 and 2.).
Cisplatin and Carboplatin are indicated in NSCLC cancer but require much higher concentration to inhibit 50% of monolayer cell growth than Doxorubicin, which is not indicated in NSCLC cancer. Although the IC50 values in the monolayer cell model would suggest doxorubicin as a more promising drug than platinum drugs against lung cancer, the ratio of doxorubicin’s IC50 values in MCS over monolayers is as high as 21 folds, which is 10 times as high as the two platinum drugs, which are clinically indicated against lung cancer.
Conclusion: Multicellular spheroids of A549 cells serve as a substantially better model to predict drug efficacy against non-small cell lung cancer than their monolayers and should serve as a more common platform to screen for new drug candidates against lung cancer.
Xinyu Pei– Stockton, California
Xinyu Pei– Stockton, California
Yifan Lu– University of the Pacific, Stockton, California
Mallika Vadlamudi– Stockton, California
Yingbo Huang– University of the Pacific, Stockton, California
Ruiqi Huang– Student, University of the Pacific, Stockton, California
Shen Zhao– Stockton, California
Zizhao Xu– Stockton, California
Zhongyue Yuan– stockton, California
Xin Guo– University of the Pacific, Stockton, California