advertisement
Science News
from research organizations

A step closer to cancer precision medicine

Date:
November 14, 2019
Source:
University of Helsinki
Summary:
Researchers have developed a computational model, Combined Essentiality Scoring (CES), that enables accurate identification of essential genes in cancer cells for development of anti-cancer drugs.
Share:
advertisement

FULL STORY

Researchers from the Faculty of Medicine and the Institute for Molecular Medicine (FIMM) at the University of Helsinki have developed a computational model, Combined Essentiality Scoring (CES) that enables accurate identification of essential genes in cancer cells for development of anti-cancer drugs.

Why are the essential genes important in cancer?

Cancer is the leading cause of death worldwide. Cancer cells grow faster usually with the activation of certain genes. Targeted therapies aim at inhibiting these genes that are activated only in cancer cells, and thus minimizing side effects to normal cells.

High-throughput genetic screening has been established for evaluating the importance of individual genes for the survival of cancer cells. Such an approach allows researchers to determine the so-called gene essentiality scores for nearly all genes across a large variety of cancer cell lines.

However, challenges with replicability of the estimated gene essentiality have hindered its use for drug target discovery.

“shRNA CRISPR-Cas9 techniqu是两个常见es used to perform high-throughput genetic screening. Despite improved quality control, the gene essentiality scores from these two techniques differ from each other on the same cancer cell lines," explains Wenyu Wang, first author of the study.

How can we do better?

To harmonize genetic screening data, researchers proposed a novel computational method called Combined Essentiality Scoring (CES) that predicts cancer essential genes using the information from shRNA and CRISPR-Cas9 screens plus molecular features of cancer cells. The team demonstrated that CES could detect essential genes with higher accuracy than the existing computational methods. Furthermore, the team showed that two predicted essential genes were indeed correlated with poor prognosis separately for breast cancer and leukemia patients, suggesting their potential as drug targets.

"Improving gene essentiality scoring is just a beginning. Our next aim is to predict drug-target interactions by integrating drug sensitivity and gene essentiality profiles. Given the ever-increasing volumes of functional screening datasets, we hope to extend our knowledge of drug target profiles that will eventually benefit drug discovery in personalized medicine," says Assistant Professor Jing Tang, corresponding author of the study.

advertisement

Story Source:

Materialsprovided byUniversity of Helsinki.注意:内容可能被编辑风格d length.


Journal Reference:

  1. Wenyu Wang, Alina Malyutina, Alberto Pessia, Jani Saarela, Caroline A. Heckman, Jing Tang.Combined gene essentiality scoring improves the prediction of cancer dependency maps.EBioMedicine, 2019; DOI:10.1016/j.ebiom.2019.10.051

Cite This Page:

University of Helsinki. "A step closer to cancer precision medicine." ScienceDaily. ScienceDaily, 14 November 2019. .
University of Helsinki. (2019, November 14). A step closer to cancer precision medicine.ScienceDaily. Retrieved August 8, 2023 from www.koonmotors.com/releases/2019/11/191114115909.htm
University of Helsinki. "A step closer to cancer precision medicine." ScienceDaily. www.koonmotors.com/releases/2019/11/191114115909.htm (accessed August 8, 2023).

Explore More
from ScienceDaily

RELATED STORIES