Home Medizin Big-Data-Analyse ebnet den Weg für eine personalisierte Behandlung von Eierstockkrebs

Big-Data-Analyse ebnet den Weg für eine personalisierte Behandlung von Eierstockkrebs

von NFI Redaktion

A recent study conducted by Hidenori Machino at the RIKEN Center for Advanced Intelligence Project (AIP) and the National Cancer Center Research Institute in Japan used a Big-Data Multi-Omics analysis to investigate changes in gene expression as cells from the human fallopian tubes become cancerous. Having identified misregulations in several biological signaling pathways, they were able to predict and test an effective treatment, with promising results. The study was published in the journal Experimental and Molecular Medicine.

Ovarian cancer is one of the most challenging cancers affecting the female reproductive system, with high-grade serous ovarian carcinoma (HGSOC) being the deadliest. Like many other types of cancer, this type is not caused by a single mutation, making treatment difficult. For this reason, the team focused not on examining DNA sequences, but on epigenetic profiles – the on/off switches within a specific type of cell that affect gene expression and in this case lead to tumor formation.

HGSOC arises in the fallopian tubes, with the most challenging cases not responding to chemotherapy. The researchers focused on this type of tumor by using cells from human fallopian tube epithelial cells which they cultured under different conditions and examined using a special integrative Omics analysis.

This analysis integrates and analyzes a vast amount of data from multiple high-throughput techniques including ATAC, ChIP and RNA sequencing to gain a comprehensive understanding of complex biological systems.

Hidenori Machino at the RIKEN Center for Advanced Intelligence Project

The Multi-Omics analysis predicted that certain factors controlling gene expression behave abnormally during tumor formation, precisely when cells transition from normal to cancerous. These predictions were verified by comparing the levels of proteins between normal and cancer cells. The predictions were confirmed, and the researchers found that certain proteins, the so-called AP-1 complex, were excessively active in cancer cells. These proteins play a role in promoting the growth and spread of cancer cells. Furthermore, it was found that another group of proteins, the GATA family, which normally helps control cell behavior, is less effective in cancer cells.

The analysis also identified specific genes – MAF, GATA6 and DAB2 – that play a crucial role in controlling cancer growth. In early tumor formation, these genes were epigenetically suppressed, thus contributing to tumor formation. By understanding how the suppression of these genes led to functional impairments, the researchers were able to develop a countermeasure. „We realized that the culprit was excessive Ras activation as a result of epigenetic gene suppression,“ says Machino, „and concluded that a drug that can block events in this signaling pathway would reverse the trend.“ In tests with Trametinib, a clinically applicable drug that can inhibit Ras signaling, signs of normal epigenetic control, including suppression of MAF and DAB2, were observed.

Drugs like Trametinib are called MEK inhibitors, and this study suggests that they could effectively prevent tumor formation in ovarian cancer. Furthermore, MAF, GATA6 and DAB2 suppression could be useful biomarkers. „The HGSOC biomarkers we discovered have the potential to be used for the early detection of ovarian cancer,“ Machino says. „The results also point to new therapeutic approaches that could have significant societal implications.“


Journal reference:

Machino, H., et al. (2023). Integrative analysis reveals early epigenetic changes in high-grade serous ovarian carcinomas. Experimental and Molecular Medicine. doi.org/10.1038/s12276-023-01090-1.

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