Scientists Use Big Data to Explain Development of Cancer Tumors

Big Data

A MRI Scanner. / Photo by: Jarmoluk via Pixabay


In what may change the current scientific viewpoint on how cancer tumors develop, researchers from The University of Texas Medical Branch at Galveston and Baylor College of Medicine turned to big data in discovering that the loss of a section of messenger ribonucleic acid that was previously suspected of transforming normal cells into cancerous ones actually blocked the human body’s ability in suppressing the growth of tumors, according to The UTMB Newsroom. 

Three-prime Untranslated Region

The section of messenger RNA, called the three-prime untranslated region or 3’UTR, can modify gene expression when shortened. Eric Wagner, an associate professor in the department of biochemistry and molecular biology at UTMB, stated that the expression of proto-oncogenes had historically been thought to have been caused by the 3’UTR shortening. 

Proto-oncogenes are normal genes altered by mutation or expressed too high, becoming oncogenes that can change a normal cell into a cancer cell. Wagner added that by combining computational approaches and cancer cell models, they were able to find out that 3’UTR shortening in tumors actually disables tumor-suppressing genes found in the human body. 

Big Data Analysis

Using big data analysis, the researchers reconstructed the RNA that form global regulatory networks within breast tumor cells and their matched normal tissues. Such an approach pointed to  3’UTRs playing an important role in regulating global regulatory networks found in breast tumor cells. There was an enrichment of 3′UTR shortening among transcripts that act as competing-endogenous RNAs. Armed with this new information, the researchers disrupted these networks within breast cancer cells to test the effects on tumor growth.

Results of the research have been published in the Nature Genetics journal.