Prognostic tool could identify high-risk breast cancer patients

In the journal Cell Chemical Biology, researchers led by UNC Lineberger's Xian Chen, PhD, report on potential prognostic tool that could be used to identify high-risk patients within particular subtypes of breast cancer.

Prognostic tool could identify high-risk breast cancer patients click to enlarge UNC Lineberger's Xian Chen, PhD.

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University of North Carolina Lineberger Comprehensive Cancer Center researchers and their collaborators have developed a new method to discover personalized cancer biomarkers for use in precision prognosis.

In the journal Cell Chemical Biology, researchers report on potential prognostic tool that could be used to identify high-risk patients within particular subtypes of breast cancer.

“Patients who are diagnosed with the same subtype of breast cancer can have dramatically different clinical outcomes,” said UNC Lineberger’s Xian Chen, PhD, an associate professor in the UNC School of Medicine Department of Biochemistry & Biophysics. “There are few markers available to precisely distinguish these patient sub-populations with different prognoses within a single subtype. We were looking for new markers to help us better predict treatment benefit and/or outcome with patient-specific or individualized precision.”

In their study, researchers drew upon “alternative splicing,” a phenomenon in which cells cut, or splice, particular genome areas in different ways to make new arrangements. With these different arrangements, the cell can produce different proteins from original genome, depending on how it’s differentially arranged. While this occurs in normal cells, emerging evidence show that cancer cells can take advantage of alternative splicing to help them grow or proliferate. Researchers used this concept to develop a method of sorting breast cancer cells according to the differences in certain proteins known as trans-factors that occurred in different breast cancer subtypes.

“Aberrant alternative splicing is a major hallmark of cancer, where RNA cis-acting splicing regulatory elements, such as intronic splicing enhancers, interact with particular trans-acting proteins, or trans-factors, to coordinately elicit the control of alterative splicing,” Chen said. “What we found is that in different breast cancer subtypes, the composition of trans-factors is different.”

They demonstrated that they could use biotinylated intronic splicing enhancer (ISE) RNA probes to sort an ISE-interacting trans-factor protein complex whose composition describes the predominant subtype in a heterogeneous tissue sample. This made it possible to resolve the issue of tumor heterogeneity.

“We then retrospectively identified patient-specific transcriptomic and genomic alterations in the genes that encode particular trans-factors showing increased ISE binding in the aggressive tumor type,” Chen said. “These alterations were found of prognostic values to distinguish breast cancer subpopulations with poor survival.”

The researchers linked functional proteomic findings to the genomic data with personalized alterations, resulting in a new technology that integrates “proteogenomics,” or multi-omics, and allowed them to discover new biomarkers of high pathological accuracy.    

“Triple-negative breast cancer patients may have dramatic differences in clinical outcomes,” Chen said. “There are very few markers that are able to distinguish those patient subpopulations with different prognosis.”

Researchers believe this finding of trans-factor gene expression markers that are linked to poor survival could be helpful for both physicians and patients.

They hope it can help with the problem of differences in outcomes for patients within individual subtypes of breast cancer.

“Before a doctor makes a treatment decision, we can check the expression of these (specific) genes,” Chen said. “If this particular patient co-overexpresses these genes, we know they are going to have poor survival.”

In addition to Chen, other authors include Li Wang, John A. Wrobel, Ling Xie, DongXu Li, Giada Zurlo, Huali Shen, Pengyuan Yang, Zefeng Wang, Harsha P. Gunawardena, Qing Zhang and Xian Chen.

The study was supported by grants from N.C. TraCS TTSA Phase I, the Chinese Science 973 fund, the National Institutes of Health, and the National Cancer Institute Clinical Proteomic Tumor Analysis Consortium. The researchers filed a provisional patent for their finding, and Chen is the founder of a related company called TransChromix LLC.