Functional Characterization of PUR? and PUR? in ER+ Breast Cancer Using CRISPR Knockout and Transcriptomic Analysis
Romeo, Owen
Romeo, Owen
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Abstract
PUR? and PUR? are nucleic-acid binding proteins that preferentially bind purine-rich DNA and RNA sequences. They have been implicated in cancer progression and cellular stress responses. Increased expression of PUR family proteins has been observed in estrogen receptor-positive (ER+) breast cancer, suggesting potential roles in tumor growth and therapeutic response. The objective of this study was to investigate the functional consequences of PUR? and PUR? loss in ER+ breast cancer cells. CRISPR-mediated knockout cell lines were generated in the MCF-7 model system and gene disruption was validated using Western blot analysis and ssDNA sandwich ELISA assays. Functional characterization was performed using cytotoxicity assays to evaluate sensitivity to commonly used chemotherapeutic agents. PUR? knockout clones demonstrated increased resistance to tamoxifen relative to puromycin-resistant control lines, while no significant changes in sensitivity were observed following treatment with doxorubicin or etoposide. These findings suggest that PUR proteins may contribute to estrogen-dependent signaling pathways influencing therapeutic response. To further define the molecular mechanisms underlying these phenotypic changes, RNA sequencing (RNA-seq) analysis is being conducted to identify global transcriptional alterations associated with PUR protein loss. Transcriptomic profiling is expected to reveal compensatory regulatory networks, potential functional redundancy between PUR? and PUR?, and downstream pathways involved in cell cycle regulation and drug resistance. Overall, this work aims to clarify the role of PUR family proteins in ER+ breast cancer biology and to evaluate their potential relevance as targets for therapeutic intervention.
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Date
1/1/2026
Student Status
Senior (Graduating in 2026)
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Poster
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Program/Major
Biochemistry
College/School
College of Arts and Sciences
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Clinical Science