Researchers at MD Anderson Cancer Center collaborated with the researchers at Mount Sinai, New York and Rice University Houston to report that the 3-dimensional scaffolds are effective in producing an endogenous tumor environment that can help in better visualization of tumor growth and response to anti-tumor therapy. The results are published in Proceedings of the National Academy of Sciences.
The 3-dimensional models designed in the Mikos lab helped in promotion and development of growth in tumor tissues by delivering suitable environmental conditions for the growth of Ewing’s sarcoma.
The discovery is helpful in producing a human tissue environment that can help researchers test anti-tumor drugs. Previously, plastic 2-dimensional surfaces were used to visualize the response of tumor cells to chemo drugs. However, since the latest research has proved that the 3-dimensional scaffolds provide a more efficient biochemical and morphologically similar environment to human cancer tissues, it will allow researchers to engineer specific models to see the response to chemo or radiotherapy in different tumors and tissues.
Antonios Mikos, the lead researcher from Rice University, collaborated with researcher and oncologist Joseph Ludwig from MD Anderson, who proposed that:
Tumors in vivo exist within a complex microenvironment consisting of several other cell types and extracellular matrix components. By taking the bottom-up approach and incorporating more components to this current model, we can add layers of complexities to make it increasingly reliable”
Ewing’s sarcoma is reportedly the second most common bone tumor in pediatric aged children, and the characteristics of tumor expression, display of tumor proteins, and growth characteristics are totally different from those that appear on 2- dimensional models. Moreover, the team of researchers also hypothesized that 2-D cultures may impair the expression or appearance of the mechanism of drug resistance that in turn affects the understanding of cellular biology, leading to thedevelopment of misunderstandings in the learning behavior of anti-cancer drugs.
With further research, this team of researchers is hopeful that developing future practical models will prove helpful in evaluating drug efficacy and in designing optimal treatment models for a variety of other cancers.