Novel Biomarker Predicts Cancer Outcomes Using Advanced Profiling Technology

Researchers from Fred Hutch Cancer Center and MD Anderson Cancer Center have identified a new biomarker that accurately predicts outcomes in meningioma brain tumors and breast cancers. The study, published in Science, utilized a new technology and computational method to uncover this significant finding.

The research team discovered that the amount of RNA Polymerase II (RNAPII) enzyme on histone genes correlates with tumor aggressiveness and recurrence. Elevated levels of RNAPII on these genes indicate cancer over-proliferation and may contribute to chromosomal changes. 

This breakthrough was made possible by a new profiling technology called Cleavage Under Targeted Accessible Chromatin (CUTAC), developed in Steven Henikoff's lab at Fred Hutch. CUTAC allows for better study of gene expression using formalin-fixed, paraffin-embedded (FFPE) samples, which are commonly used for long-term tissue storage but often yield lower-quality gene expression data due to RNA degradation.

The CUTAC technology focuses on small, fragmented DNA non-coding sequences where RNAPII binds, enabling direct measurement of gene transcription activity from DNA. Using this method, researchers found significantly higher expression of histone genes in tumor samples compared to normal tissue across various cancer types.

To test their hypothesis, the team examined 36 FFPE samples from meningioma patients using CUTAC profiling. They integrated this data with nearly 1,300 publicly available clinical samples and outcomes using a novel computational approach. The results showed that RNAPII signals on histone genes could distinguish between cancer and normal samples, correlate with clinical grades in meningiomas, and predict rapid recurrence and chromosome losses.

The technique was also applied to breast tumor FFPE samples from 13 patients with invasive breast cancer, successfully predicting cancer aggressiveness. Ye Zheng, co-first author of the study, emphasized the potential of this approach, stating, "Our novel approach, combining a new experimental technology and computational pipeline, establishes a comprehensive ecosystem that can leverage biopsy samples from multiple cancer types to enhance tumor diagnosis and prognosis."