Liang Chen
University of Southern California, CA·Genetics
Cells check their messenger RNAs (mRNAs), the copies of genes used to build proteins, and destroy faulty ones through a process called nonsense-mediated mRNA decay (NMD). NMD also fine-tunes the levels of many normal genes.
- Fields
Genetics
Computer Science
Mathematics & Statistics
- Topics
nonsense-mediated mRNA decay
cancer genomics
post-transcriptional regulation
- Grants
- 1 known grant, through Apr 2031
What they work on
- Relate NMD's fine-tuning of gene expression to the genes cancer cells depend on, using NMD residual signatures built from DepMap cell line data and tested for predictive power in TCGA tumor samples.
- Identify inherited genetic variants that change NMD strength (NMD-QTLs), apart from mutations causing premature stop codons, using new statistical models of NMD quality control across cancers.
- Use NMD-QTL-based estimates of NMD strength to pinpoint patients who might benefit most from NMD-inhibition therapies.
- Discover new factors that modulate NMD and map how they interact with cancer-driver genes, using existing multi-omics cancer data.
More about the research
In cancer, NMD can help or hurt tumors, and drugs that block NMD are being explored. This project asks how NMD regulation shapes cancer biology and whether it can predict who responds to treatment. It relies entirely on existing large datasets and new statistical and computational models.
Why it matters
Cancer patients often respond unevenly to targeted drugs. By showing how NMD activity and inherited variants affect tumor gene dependencies, this work could help match patients to personalized treatments. In particular, it could flag patients likely to benefit from therapies that block NMD. The statistical tools could also be used to study other diseases.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Kathryn Oliver
Emory University, GA·Genetics
Determine how inhibiting specific ribosomal proteins, including RPL12 (uL11) and RPL8 (uL2), affects the biogenesis of CFTR premature termination codon variants such as W1282X and G542X.
Matthew Bailey
Brigham Young University, UT·Genetics
Identify and assess how known cancer predisposition (germline) mutations from curated databases appear in the All of Us whole-genome cohort, and quantify their impact on cancer occurrence.
Rendong Yang
Northwestern University, IL·Genetics
Build an integrated computational framework to detect and validate exitrons, coding-exon regions that can be spliced out like introns, using multi-omics data from several sequencing platforms, and identify splicing factors that favor exitron splicing in cancers.
The school
University of Southern California: 47 labs on PI Pages, $1.3B a year on research, 882 research doctorates a year.
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