AI Article Synopsis

  • Traditional 2D cell cultures have limitations in studying cancer progression, making 3D systems more effective for simulating realistic cell interactions and tumor development.
  • Researchers created liver tumor spheroids using primary human liver cells, MSCs, and colon cancer cells in simulated microgravity, which led to rapid tumor growth and stroma formation.
  • The study found that while tumor organoids are sensitive to chemotherapeutics like 5-FU, their sensitivity decreases as they mature, highlighting their potential for modeling cancer progression and drug response.

Article Abstract

Despite having yielded extensive breakthroughs in cancer research, traditional 2D cell cultures have limitations in studying cancer progression and metastasis and screening therapeutic candidates. 3D systems can allow cells to grow, migrate, and interact with each other and the surrounding matrix, resulting in more realistic constructs. Furthermore, interactions between host tissue and developing tumors influence the susceptibility of tumors to drug treatments. Host-liver colorectal-tumor spheroids composed of primary human hepatocytes, mesenchymal stem cells (MSC) and colon carcinoma HCT116 cells were created in simulated microgravity rotating wall vessel (RWV) bioreactors. The cells were seeded on hyaluronic acid-based microcarriers, loaded with liver-specific growth factors and ECM components. Only in the presence of MSC, large tumor foci rapidly formed inside the spheroids and increased in size steadily over time, while not greatly impacting albumin secretion from hepatocytes. The presence of MSC appeared to drive self-organization and formation of a stroma-like tissue surrounding the tumor foci and hepatocytes. Exposure to a commonly used chemotherapeutic 5-FU showed a dose-dependent cytotoxicity. However, if tumor organoids were allowed to mature in the RWV, they were less sensitive to the drug treatment. These data demonstrate the potential utility of liver tumor organoids for cancer progression and drug response modeling.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7945991PMC
http://dx.doi.org/10.1088/1758-5090/aa7484DOI Listing

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