News
October 2, 2026
Congratulations to Qunzhi Xu on receiving the 2026 Conference of the Program in Quantitative Genomics Stellar Abstract Award for his work on "Rank-Preserving Alignment Unifies Single-Cell and Spatial Proteomics Across Platforms."
Congratulations to Xusheng Ai on receiving the 2026 Conference of the Program in Quantitative Genomics Registration Award for his work on "SHIFT: Synthesis and Harness-Guided Instruction Fine-Tuning for Biological Protocol Assistance."
August 17, 2026
Welcome Xusheng Ai, who accepted our return offer and joined our group as a postdoctoral fellow!
June 5, 2026
Ye Zheng’s review paper on “Enzyme tethering for in situ epigenomics” has been published in Nature Reviews Methods Primers.
April 15, 2026
Congratulations to Zhikang Liu on accepting the Statistics Ph.D. program offer from the University of Georgia!
January 10, 2026
Congratulations to Ye Zheng on receiving the Cancer Center Support Grant New Faculty Award!
2025
November 20, 2025
Welcome Qunzhi Xu to our group as the first postdoctoral fellow!
May 20, 2025
We are thrilled to announce that Ye Zheng’s paper on ADTnorm has been accepted for publication in Nature Communications. This work represents a significant advancement in the normalization and integration of CITE-seq data.
May 2, 2025
Congratulations to our new lab members! We are delighted to congratulate Gloria Song and Tian Le for receiving their master’s degrees in data science from the Department of Computer Science at Rice University. Both will be joining our group as research computational analysts.
March 10, 2025
Ye Zheng’s paper, Chromosome Arm Losses Predict Malignancy in Human Cancer, is published in PNAS. Ye Zheng has led a discovery that total whole-arm chromosome losses can predict malignancy across various cancer types. This revolutionary finding provides a new framework for understanding cancer development and progression.
February 19, 2025
Researchers from Fred Hutch Cancer Center and UT MD Anderson have developed a novel technique that directly measures gene transcription activity from DNA, revealing that hyper-elevated levels of RNA polymerase II (RNAPII) are linked to tumor aggressiveness.
January 15, 2025
Ye Zheng’s recent work, RNA Polymerase II hypertranscription at histone genes in cancer FFPE samples, is accepted by Science!
January 1, 2025
Congratulations to Yiyang Niu, who received a master’s degree in statistics from Rice University!
Congratulations to Zhikang Liu, who received a master’s degree in statistics from Rice University!
Our Research in the News
Scientists find new biomarker that predicts cancer aggressiveness
Using a new technology and computational method, researchers from Fred Hutch Cancer Center and The University of Texas MD Anderson Cancer Center have uncovered a biomarker capable of accurately predicting outcomes in meningioma brain tumors and breast cancers.
In the study, published today in Science, the researchers discovered that the amount of a specific enzyme, RNA Polymerase II (RNAPII), found on histone genes was associated with tumor aggressiveness and recurrence. The hyper-elevated levels of RNAPII on these histone genes indicate cancer over-proliferation and potentially contribute to chromosomal changes. These findings point to the use of a new genomic technology as a potential cancer diagnostic and prognostic tool, which could improve precision oncology approaches.
“It has been overlooked that histone genes could be a rate-limiting factor in cell replication and, hence, as 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. “This is because current RNA sequencing methods are unable to detect histone RNAs due to their unique structure, meaning these libraries have vastly underestimated their presence. 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.”
New technology produces better quality data from samples stored over decades
The results of the study were made possible by a new profiling technology developed in the lab of Steven Henikoff, Ph.D., co-first author and professor in the Basic Sciences Division at Fred Hutch, which enables researchers to better study gene expression using formalin-fixed, paraffin-embedded (FFPE) samples.
Tissue biopsies are commonly stored for long-term use as FFPE samples, but the sample RNA becomes increasingly unstable over time due to degradation, leading to potentially lower quality gene expression data.
The new technology – Cleavage Under Targeted Accessible Chromatin (CUTAC) – focuses on small, fragmented DNA non-coding sequences where RNAPII bind located on the same chromosome as the gene they regulate, allowing scientists to directly measure gene transcription activity from the DNA.
When examining clinical samples using CUTAC technology across various cancer types, the researchers found that the expression of histone genes was consistently significantly higher in tumor samples compared to normal tissue samples.
Histone proteins provide essential structural support for DNA in chromosomes, acting as spools around which DNA strands wrap. These proteins have been well studied, but most current tools to study gene expression rely on RNA sequencing. Histone RNA is unique in that its structure prevents them from being detected by current methods.
Thus, the expression of histone genes may be significantly underestimated in tumor samples. The researchers hypothesized that the increased proliferation of cancer cells leads to hypertranscription, or very elevated expression, of histones to meet the added demands of cell replication and division.
RNAPII expression correlates with and predicts cancer aggressiveness
To test their hypothesis, the researchers used CUTAC profiling to examine and map RNAPII, which transcribes DNA into precursors of messenger RNA. They studied 36 FFPE samples from patients with meningioma - a common and benign brain tumor - and used a novel computational approach to integrate this data with nearly 1,300 publicly available clinical data samples and corresponding clinical outcomes.
In tumor samples, the RNAPII enzyme signals found on histone genes was reliably able to distinguish between cancer and normal samples.
RNAPII signals on histone genes also correlated with clinical grades in meningiomas, accurately predicting rapid recurrence as well as the tendency of whole-arm chromosome losses. Using this technology on breast tumor FFPE samples from 13 patients with invasive breast cancer also predicted cancer aggressiveness.
“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 colleagues plan to use this technology on FFPE samples from multiple cancer types for further validation.
This research was supported by the Howard Hughes Medical Institute, the National Institutes of Health (HG012797), and the National Cancer Institute (T32CA009515). A full list of collaborating authors and their disclosures can be found here.
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