Single-Cell Multi-omics 3D Genome Technology for Cancer Structure Variation and Enhancer Hijacking

Three-dimensional (3D) genome organization—including long-range enhancer–promoter (E–P) interactions— is essential for transcriptional regulation and is frequently disrupted in cancer through structural variations (SVs), enhancer hijacking, and epigenetic alterations. While bulk Chromosome Conformation Capture (3C) technologies have advanced our understanding of cancer genome architecture, they cannot resolve the cellular heterogeneity that underlies metastasis, relapse, and therapy resistance. Existing single-cell 3D genome methods suffer from poor efficiency in capturing long-range E–P interactions, low throughput, and prohibitive cost. Moreover, they cannot simultaneously measure all three key modalities—3D genome architecture, chromatin accessibility, and gene expression—from the same cell. As a result, integrative analyses rely on computational inference from separate datasets, lacking ground-truth tri-modal data from identical cells and often leading to inaccurate conclusions. Here, we propose to develop scHiCAR, the first single-cell tri-modal platform that simultaneously captures high-resolution 3D genome interactions (including E–P loops), chromatin accessibility, and transcriptomes from individual cells. Preliminary data using non-cancer cell lines demonstrate the feasibility and performance of scHiCAR, achieving 1,000× higher throughput, 100× lower cost per cell, and 20× greater enrichment for long-range E–P interactions compared to existing single-cell 3C methods. To establish scHiCAR for cancer research, we will (Aim 1) optimize the protocol for cancer cells, and develop robust scHiCAR tissue protocols for (Aim 2) primary and metastatic tumors in multiple tissues using genetically engineered mouse models (GEMMs) and (Aim 3) human primary and relapsed tumor biopsies. Successful development of scHiCAR will transform cancer 3D genome research by enabling accurate, high-throughput, and cost-effective analysis of gene regulatory mechanisms in heterogeneous tumor tissues. This technology will open new avenues for understanding cancer progression and therapy by providing deeper insights into cancer structural variation, enhancer hijacking, tumor heterogeneity, cellular plasticity, metastasis, and relapse, etc. Project Number: 1R33CA309685-01 | Fiscal Year: 2026 | NIH Institute/Center: National Cancer Institute (NCI) | Principal Investigator: Yarui Diao | Institution: DUKE UNIVERSITY, DURHAM, NC | Award Amount: $402,135 | Activity Code: R33 | Study Section: Special Emphasis Panel[ZRG1 BTC-N (55)] View on NIH RePORTER: https://reporter.nih.gov/project-details/11311002