New 3-D Model May Accelerate Breakthroughs in Lung Cancer Research

Treatment & Doctors
Reading Time: 4 mins
Publication Date: 10/25/2012
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Rosenberg, J. (2020, October 16). New 3-D Model May Accelerate Breakthroughs in Lung Cancer Research. Retrieved February 5, 2023, from


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A newly developed research model allows scientists to cultivate lung cancer cells in three dimensions – which may lead to a deeper understanding of the disease’s development and behavior in patients.

Currently, researchers use a flat, 2-D flask to grow lung cancer samples and study patterns in the disease’s growth. But the new 3-D model, created by researchers at The Methodist Hospital and the University of Texas MD Anderson Cancer Center, offers a more accurate representation of the complex biological processes occurring within a lung cancer patient’s body.

Early tests of the 3-D model were recently published in the scientific journal PLOS One.

“New models for lung cancer research are crucial because current models frequently do not correlate with the findings of human trials,” explains Min Kim, M.D., the study’s principal investigator. “The challenge is creating a model that can accurately predict what will happen in patients with lung cancer.”

Initial findings show that the new modeling technique may do just that.

Using a natural matrix derived from the lung cells of rats, the Methodist-MD Anderson model serves as a miniature replica of the lungs. When human lung cancer is introduced, cells that stick to the matrix are nourished with an oxygenated, nutrient-rich broth that flows through the lung space. Over time, the matrix sprouts organized tumor nodules that mimic the structure and function of real lung cancer.

“We found that the 3-D model we devised worked in most respects much better than 2-D models currently being used in lung cancer research,” Kim adds.

Limitations of Previous Models

While 2-D models have significantly improved our understanding of how lung cancer tumors form and spread, they cannot reveal the complex interactions that take place between cancer cells and their microenvironment. Researchers have also investigated animal models, but the results don’t always correlate with the findings of human clinical trials.

Unlike the 3-D lung model, earlier techniques failed to recreate lung cancer growth and metastasis as it actually occurs in patients. The 2-D models won’t support the development of tumor nodules, which are believed to play a key role in the growth and progression of lung cancer.

Furthermore, 2-D models produce an unnaturally high number of cancer cells, which grow indiscriminately until no space remains. The Methodist-MD Anderson model provides more realistic features and growth patterns, including complex vasculature that transports nutrients and cells to the tumor site. In the study’s comparison of the two techniques, the 2-D model did not produce MMPs, a family of enzymes that plays a crucial role in human lung cancer development.

MMPs destroy important structural components of healthy tissue, which leads to tumor cell invasion and distant cancer spread. In lung cancer patients, elevated levels of MMP-9 in the blood are associated with poor survival. MMPs and other genetic molecules that control the development and progression of lung cancer, such as caspase-3 and ki-67, were observed in the new Methodist-MD Anderson model.

Impact on Future Research

Looking forward, this new technique shows great potential for advancing lung cancer research.

Historically, animal and 2-D research models have provided only meager improvements to lung cancer survival. The five-year survival rate for lung cancer was 13 percent in 1975, and increased to just 16 percent by 2005, the most recent year that offers reliable data.

“The lack of progress in finding effective treatments for lung cancer may be due, in part, to the lack of an accurate model that mimics the biological processes that occur in patients with lung cancer,” says Dhruva Mishra, Ph.D., one of the study’s co-authors.

With such promising results from early studies of the new model, it is likely that further research with the technique will provide greater insight into the puzzling biological mechanisms behind lung cancer growth and metastasis.

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