Research Program
I study how RNA-binding proteins shape mRNA stability in cancer and how disruption of those networks contributes to metastasis, therapy resistance, and patient outcome. My work combines experimental and computational approaches to define post-transcriptional regulation as a mechanistic layer of cancer biology.
Using transcriptome-wide SLAM-seq, I measure mRNA stability across cancer cell lines and patient-derived models. This work led to the discovery of RBMS3 as a metastasis suppressor in breast cancer, with validation across six cancer models, three mouse models, and patient cohorts.
Science Advances paperI developed a high-throughput targeted CLIP-seq platform to map RNA-binding protein binding sites across about 67 RBPs in cancer cells. The resulting resource connects binding patterns to regulatory function and supports structure-aware computational modeling.
Manuscript in preparation.
My research program uses genetically and ancestrally diverse breast cancer models because many standard model systems do not reflect the patients most affected by metastatic disease. I treat that choice as part of rigorous experimental design, not as a separate add-on.
Metabolic RNA labeling approach that directly measures transcriptome-wide mRNA decay rates across thousands of transcripts at once.
Immunoprecipitation and sequencing approach that maps RNA-binding protein interaction sites on RNA at nucleotide resolution.
CRISPR interference screens used to test RBP regulatory programs and identify factors important for cancer cell survival and metastatic behavior.
Coming soon to bioRxiv: a high-resolution experimental platform for profiling RNA-binding protein interactions across diverse RBPs, paired with an interpretable structure-aware model that predicts RBP binding and variant effects from RNA sequence and structural context.
Aim 1
I want to define how mRNA stability landscapes are remodeled as ER+ breast cancers acquire resistance to CDK4/6 inhibitors, PI3K inhibitors, and endocrine therapies, then use CRISPRi to test the RBPs that drive those changes.
Aim 2
I plan to build a transcriptome-wide mRNA stability atlas across genetically and ancestrally diverse breast cancer models, including patient-derived xenografts and organoids, to identify regulatory programs that are conserved, divergent, or population-specific.
This section highlights earlier work that shaped my scientific training and led into my current research program.
Functional Characterization of Human LncRNA JPX
University of California, Irvine — PhD in Biological Sciences; dissertation research in the laboratory of Dr. Sha Sun; completed 2019.
My dissertation focused on the human long noncoding RNA JPX, a proposed activator of XIST during X chromosome inactivation. Through comparative sequence, RNA structure, and functional experiments, I showed that human JPX remains functionally conserved despite major divergence from its mouse homolog, including robust CTCF binding and rescue of Jpx-deficient mouse embryonic stem cells.
That work grounded my interest in RNA mechanism, structure-function relationships, and disease-relevant regulation.
Dissertation PDFPhD dissertation research
I studied how the human lncRNA JPX compares with its mouse homolog Jpx and asked whether function can be conserved despite sequence divergence. Using comparative sequence analysis, SHAPE RNA structure probing, RNA-protein binding assays, and mouse embryonic stem cell rescue experiments, I showed that human JPX retains core molecular function and can complement loss of Jpx.
PaperPhD dissertation chapter / cancer-focused extension of dissertation work
I extended the JPX work into ovarian cancer to ask whether X chromosome inactivation-linked lncRNAs might contribute to tumor biology. This project found reduced JPX and XIST expression in higher-grade ovarian cancer and early evidence linking XIST loss to increased proliferation, migration, and dysregulation of cancer-associated pathways.
Described in dissertation chapter.
Early research training
One of my earliest research projects examined why some colorectal cancer cells resist 5-FU. We found that resistant cells showed impaired caspase activation and that low-dose selenous acid could help restore apoptotic sensitivity.
PubMedEvery messenger RNA in a cell has a half-life. Some transcripts degrade within minutes, while others persist for hours. That turnover helps determine how much protein is produced from a gene. In cancer, those stability programs can shift in ways that prolong oncogene expression or reduce tumor suppressor expression.
SLAM-seq is a metabolic RNA labeling method that makes it possible to measure how quickly individual mRNAs are degraded across the transcriptome. It produces genome-scale stability measurements in a single experiment.
CLIP-seq uses UV crosslinking and immunoprecipitation to capture the RNAs bound by a given RNA-binding protein, then sequences those fragments to map binding sites at high resolution.
My main focus is breast cancer, especially metastatic disease and therapy resistance. The RBMS3 work spans ER+, triple-negative, and HER2+ models, and my broader program includes genetically and ancestrally diverse patient-derived systems.
My work asks how post-transcriptional regulation changes tumor behavior and patient outcome. In the RBMS3 project, the stability regulator I identified predicts metastasis-free survival in two independent patient cohorts, linking RNA regulation directly to clinically meaningful disease behavior.