Abstract B031: Decoding Tumor Complexity: An Integrative Framework Linking Chromatin Topology to Therapeutic Resistance

Abstract Tumor heterogeneity poses a formidable challenge in oncology, manifesting as genetic, epigenetic, and phenotypic variations within neoplastic tissues that underpin therapeutic resistance and metastatic progression. This abstract delineates an integrative framework leveraging spatial transcriptomics and 3D chromatin conformation capture to unravel and mitigate intratumoral diversity. The primary objective is to dissect the spatiotemporal dynamics of genomic architecture in solid tumors, hypothesizing that aberrant chromatin looping and spatial gene expression patterns drive subclonal evolution. Employing high-resolution spatial RNA sequencing (e.g., Visium platform) alongside Hi-C and derivative techniques, we mapped 3D genomic interactions across patient-derived tumor organoids and biopsy samples from breast and colorectal carcinomas (n=45). Methodologically, we introduced a novel heterogeneity index, \( H = \sum_{i=1}^{N} \left(1 - \frac{\sum_{j=1}^{M} p_{ij} \log p_{ij}}{\log M}\right) \cdot w_i \), where \( p_{ij} \) denotes the probability of gene expression state j in spatial bin i, M represents expression states, and \( w_i \) weights topological domain integrity derived from Hi-C contact matrices. This metric quantifies entropy-adjusted spatial variance, revealing hotspots of genomic instability. Results demonstrated that 3D genomic reconfiguration, particularly enhancer-promoter hijacking in heterochromatic regions, correlates with elevated heterogeneity scores (r=0.72, p<0.001), fostering chemoresistance in 68% of subclones. Targeted CRISPR-mediated loop disruption reduced heterogeneity by 42% in vitro, as validated through single-cell ATAC-seq. In conclusion, this study pioneers a multidimensional genomics paradigm for decoding tumor complexity, offering actionable insights for precision therapeutics. By bridging spatial and structural layers, our approach paves the way for tailored interventions that preempt adaptive resistance, ultimately enhancing clinical outcomes in heterogeneous malignancies. Citation Format: Peter Oloche David. Decoding Tumor Complexity: An Integrative Framework Linking Chromatin Topology to Therapeutic Resistance [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Brain Cancer; 2026 Mar 23-25; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2026;86(6_Suppl):Abstract nr B031.

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Journal
Cancer Research
Published
2026-03-23
DOI
https://doi.org/10.1158/1538-7445.brain26-b031
Primary Topic
Bioinformatics and Genomic Networks
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article
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article

Abstract B031: Decoding Tumor Complexity: An Integrative Framework Linking Chromatin Topology to Therapeutic Resistance

Peter Oloche David
Cancer Research
Bioinformatics and Genomic Networks
article

Abstract B031: Decoding Tumor Complexity: An Integrative Framework Linking Chromatin Topology to Therapeutic Resistance

Peter Oloche David
article en

Abstract

Abstract Tumor heterogeneity poses a formidable challenge in oncology, manifesting as genetic, epigenetic, and phenotypic variations within neoplastic tissues that underpin therapeutic resistance and metastatic progression. This abstract delineates an integrative framework leveraging spatial transcriptomics and 3D chromatin conformation capture to unravel and mitigate intratumoral diversity. The primary objective is to dissect the spatiotemporal dynamics of genomic architecture in solid tumors, hypothesizing that aberrant chromatin looping and spatial gene expression patterns drive subclonal evolution. Employing high-resolution spatial RNA sequencing (e.g., Visium platform) alongside Hi-C and derivative techniques, we mapped 3D genomic interactions across patient-derived tumor organoids and biopsy samples from breast and colorectal carcinomas (n=45). Methodologically, we introduced a novel heterogeneity index, \( H = \sum_{i=1}^{N} \left(1 - \frac{\sum_{j=1}^{M} p_{ij} \log p_{ij}}{\log M}\right) \cdot w_i \), where \( p_{ij} \) denotes the probability of gene expression state j in spatial bin i, M represents expression states, and \( w_i \) weights topological domain integrity derived from Hi-C contact matrices. This metric quantifies entropy-adjusted spatial variance, revealing hotspots of genomic instability. Results demonstrated that 3D genomic reconfiguration, particularly enhancer-promoter hijacking in heterochromatic regions, correlates with elevated heterogeneity scores (r=0.72, p<0.001), fostering chemoresistance in 68% of subclones. Targeted CRISPR-mediated loop disruption reduced heterogeneity by 42% in vitro, as validated through single-cell ATAC-seq. In conclusion, this study pioneers a multidimensional genomics paradigm for decoding tumor complexity, offering actionable insights for precision therapeutics. By bridging spatial and structural layers, our approach paves the way for tailored interventions that preempt adaptive resistance, ultimately enhancing clinical outcomes in heterogeneous malignancies. Citation Format: Peter Oloche David. Decoding Tumor Complexity: An Integrative Framework Linking Chromatin Topology to Therapeutic Resistance [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Brain Cancer; 2026 Mar 23-25; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2026;86(6_Suppl):Abstract nr B031.

Cancer ResearchVol. 86(6_Supplement)
Technology Holding (United States) (US)
Openalex Percentile: Top 13%
Bioinformatics and Genomic Networks
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