Interpretation! How will the drug screening and CRISPR technology combine to help create a better cancer…

interpretation! How will the drug screening and CRISPR technology combine to help create a better cancer…

2020 7 November 27 hearing /Bio ValleyBIOON/ –recently, a study published in the International JournalMolecular Systems Biologyentitled“Drug mechanism‐of‐action discovery through the integration of pharmacological and CRISPR screens”study, from the UK Vail-Kom Foundation, the Sanger Institute and other institutions and scientists through research at the molecular level on cancer drug how to play the role of carried out the most comprehensive analysis, the article, researchers of the drug reaction data with CRISPRGeneticscreening technology combined with the hundreds of cancer cell lines for analysis, in-depth understanding of how drugs more precisely targeted to cancer cells.

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researchers in the detected 397 drug identified 50%of the drug mechanism of action, it may be able to help improve drug reactions behind biological understanding of the mechanisms of, so you can quickly and more effectively to promote novel cancer drug development, as well as the future for cancer patient’s individual chemotherapy development. Historically, the drug development success rate has been very low, only less than 10% of the desired compound can be entered to theclinical trialsin.

currently, the researchers and not on the molecular level to completely understand cancer drug is how to kill cancer cells, which means that a cancer drug may not be to the researcher expected to play a role, when a drug is used to target effect due to DNA mutations caused by cancer of the weaknesses, which there will be some problems, some drugs will be targeting a variety of proteins, and therefore it will tend to the patient more toxic, while others drug the not enough effectiveness, so its use in killing cancer cells and has no effect. In recent years, a variety of new methods can help improve the drug candidate’s success rate, such as cancer dependencies diagram Cancer of the Dependency Map and other items from the cancer patient of cancer cells in the model developed in the reference collection, while it also can be grown in the laboratory and widely used in research, these cell models one of the uses is for drug screening, which can detect anti-cancer activity of the drug thereby identify which sensitivity to a special cancer for a special compound to produce the reaction.

another study breakthrough is that researchers can use CRISPR-Cas9 technology to edit the cancer cell lines in the gene, by a a close gene to the determination of these genes for cancer cell survival the importance of this study, the researchers for the first time the CRISPR-Cas9 technology and pharmacological screening technologies in combination, on 484 cancer cell lines for 397 kinds of anti-cancer compound screening, includingFDAapproved cancer drugs, clinical development of drugs and the early development of the compound and the like. Search through the cover 484 cell lines between the two databases of the Association, the researchers analyzed the drug sensitivity and drug targets of CRISPR knock-out corresponding to the extent of, and eventually they identified the drug response and Gene dependency between 865 a significant Association.

researchers Emanuel Gon do? alves indicates, the destruction of a gene effect and inhibition of the gene produced a protein the effect is not the same, however, when a molecular pathway or function and Drug Response data sets CRISPR screening data associated with the data, we can more clearly at the molecular level to elucidate drug mechanism of action, can also be clearly found whether the drug will be like we expected to play a role. Researchers can determine for testing of 50%of the compound is how to kill cancer cells, although there are half of the drug’s mechanism of action is unclear, but this���Not mean that these compounds had no effect, the researchers may also need in-depth research to the molecular level understanding of the of these drugs mechanism of action.

in addition, the researchers also found some surprising results, such as inbreast cancercell lines found that MCL1 and MARCH5 gene Association between MCL1 in human cancer occurs in the change, and with chemotherapy resistance and cancer recurrence is directly related to, dependent on MCL1 and MARCH5 breast cancer cell lines, targeting MCL1 protein to inhibit its activity of the drug may be much more effective. In-depth understanding of the involved molecular pathways may help researchers understand why a drug on the part of the patient effective, such as in breast cancer MCL1 and MARCH5 between the Association will be able to reveal the researcher is not clearly an important molecule associated with, then can also help researchers to understand MCL1 protein inhibitors mechanism of action, as well as those drugs for which cancer patients benefit.

in-depth understanding of drug reactions behind biological mechanisms and the underlying genomic characteristics may help researchers identify new type ofbiomarkers, guidance, drug combination therapy and help ward off patients for cancer drug resistance; and finally researchers Mathew Garnett noted that precision medicine research areas a key challenge lies in understanding the special patient population in which drug is most effective, the key step is to fully understand a drug how in the cell play a role, by pharmacological techniques and CRISPR screening technologies are combined, researchers will hopefully reveal what kind of drug on which type of cancer play a role, this might also be the study of a deeper push to the precision of cancer research going. （生物谷Bioon.com

reference:

【1】Drug screens and CRISPR combine to help make better cancer drugs

【2】Helen Dowden et al. Trends in clinical success rates and therapeutic focus, Nature Reviews Drug Discovery (2019). DOI: 10.1038/d41573-019-00074-z

【3】Emanuel Gonçalves et al. Drug mechanism‐of‐action discovery through the integration of pharmacological and CRISPR screens, Molecular Systems Biology (2020). DOI:10.15252/msb. 20199405

Published at Sun, 26 Jul 2020 16:12:39 +0000