Ivy Tsz-Lo Wong

The paper shows ecDNA localizes to the nuclear periphery in cancer, resisting silencing and enhancing transcriptional output through interactions with the nuclear lamina.

Cycle-Extractor accurately reconstructs ecDNA structures from both short- and long-read sequencing data, outperforming existing methods in speed and completeness.

This study shows ecDNA copy number plasticity drives tumour evolution by generating functional heterogeneity and promoting drug resistance.

A genome-wide plasmid screen, Retain-seq, identifies thousands of CpG-rich promoter-like human elements that tether episomes to mitotic chromosomes, shape ecDNA structure, and lose function when methylated.

This study investigates the spatial-temporal evolution of extrachromosomal DNA (ecDNA) in glioblastoma, showing that EGFR ecDNA drives tumor evolution and identifies a potential therapeutic window for early intervention.

The paper introduces interSeg, a deep learning tool that accurately predicts oncogene amplification status from interphase FISH images, achieving high accuracy in detecting ecDNA and chromosomal amplifications.

This study shows that ecDNA mis-segregation leads to micronuclei formation, reduced oncogene transcription, and improved patient survival in neuroblastoma.

The paper shows that ecDNA-borne PVT1 fusions stabilize oncogenic mRNAs by interacting with SRSF1, enhancing RNA stability and supporting MYC dependency in cancer.

The paper introduces OM2BFB, an algorithm detecting BFB amplifications using OGMs, showing high precision and recall, and finds BFB events are common in certain cancers but not linked to intratumoral heterogeneity or rapid genome change.

This paper identifies transcription-replication conflict as a vulnerability in ecDNA-containing cancers and demonstrates that CHK1 inhibition selectively kills these tumors.

CoRAL improves ecDNA structure reconstruction using long-read sequencing, outperforming short-read methods in simulations and cell-line datasets.