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A groundbreaking discovery by researchers at Fred Hutch Cancer Center and The University of Texas MD Anderson Cancer Center has unveiled a biomarker capable of accurately predicting cancer aggressiveness. Utilizing a novel technology and computational method, scientists have found that the presence of RNA Polymerase II (RNAPII) on histone genes is linked to tumor severity and recurrence in meningioma brain tumors and breast cancers.
The study, published today in Science, highlights how elevated levels of RNAPII on histone genes indicate excessive tumor proliferation and may contribute to chromosomal abnormalities. This breakthrough presents a promising avenue for enhancing cancer diagnosis and prognosis through advanced genomic technology.
A New Approach to Cancer Diagnosis
“It has been overlooked that histone genes could be a rate-limiting factor in cell replication, and in turn, a strong indicator of tumor cell over-proliferation,” said Ye Zheng, Ph.D., co-first author and assistant professor of Bioinformatics and Computational Biology at MD Anderson.
Traditional RNA sequencing techniques have been unable to detect histone RNA due to its unique structure. This has led to a significant underestimation of its role in tumor development. The newly developed computational approach, paired with an innovative experimental technology, now allows researchers to leverage biopsy samples from various cancer types to improve diagnostic and prognostic precision.
Advancements in Gene Expression Analysis
The success of this study was largely enabled by Cleavage Under Targeted Accessible Chromatin (CUTAC), a profiling technology developed in the lab of Steven Henikoff, Ph.D., co-first author and professor in the Basic Sciences Division at Fred Hutch. CUTAC enhances gene expression analysis from formalin-fixed, paraffin-embedded (FFPE) tissue samples, which are commonly used for long-term cancer research but often suffer from RNA degradation over time.
By focusing on small, fragmented non-coding DNA sequences where RNAPII binds, CUTAC allows scientists to directly measure transcription activity from DNA, yielding higher-quality data from even decades-old preserved samples.
Predicting Cancer Severity with RNAPII
Researchers applied the CUTAC method to 36 FFPE samples from meningioma patients and integrated their findings with nearly 1,300 publicly available clinical data samples. Their analysis demonstrated that RNAPII levels on histone genes effectively distinguish between cancerous and normal tissues. Furthermore, these signals correlated with clinical tumor grades, accurately predicting recurrence and chromosomal abnormalities in meningiomas. Similar results were observed in breast cancer samples, suggesting the potential for widespread application.
“The technique we developed to examine preserved tumor samples now reveals a previously overlooked mechanism of cancer aggressiveness,” said Henikoff, who is also a Howard Hughes Medical Institute investigator. “Identifying this mechanism suggests it could be a new test to diagnose cancers and possibly treat them.”
Zheng and his colleagues plan to further validate this approach by analyzing FFPE samples from multiple cancer types. Their findings could lead to new precision oncology techniques and improved patient outcomes.
Disclaimer: The findings in this study represent early-stage research and require further validation. Patients should consult their healthcare providers for personalized medical advice and treatment options.
For more details, refer to the original study: Anna Lauko et al, Computational design of serine hydrolases, Science (2025). DOI: 10.1126/science.adu2454
