Abstract A083: Genomic Analysis of Structural Variations in Pancreatic Cancer Using Long-Read Sequencing

Abstract Objective: Structural variations (SVs) constitute the greatest source of genomic alterations leading to the oncogenesis of many cancers, including the deadliest pancreatic cancer (PC). However, SVs in PC remain largely undefined due to technological limitations of the traditional short-read sequencing. This study aims to establish a comprehensive signature of genomic SVs in PC. Methods: PacBio whole genome long-read sequencing was employed to investigate the genomic landscape of SVs in eight tissues from four pancreatic cancer patients. A variety of SVs callers, including pbsv, Sniffles, cuteSV, and svim, were comprehensively adopted to improve the accuracy of SVs detection. Many undefined characteristics of germline and somatic SVs were revealed by comparing with multiple previously published databases. Besides, the impacts of structural variations on 3D chromatin organization were analyzed by integrating multi-omics data including Hi-C, RNA seq and ChIP seq. Results: A total of 26,844 and 27,028 non-redundant SVs were identified in human pancreatic cancer and matched para-cancerous tissues, respectively. Notably, among these SVs, 23.97% were novel and had not been previously reported. Germline SVs were further characterized and found enriched in 25 well-known susceptible genes, such as TP63, PVT1, and ABO. Additionally, we proposed a panel of germline SVs with predicted highest pathogenicity, involving STOX1, DSPP, and WRN. Totally, 616 somatic SVs were identified and presented high burdens in patients with lymph node metastasis. We observed that somatic DELs and INSs were significantly more prevalent in repetitive regions than in non-repetitive regions. Interestingly, DELs showed a decrease in the proportion occurring in simple repeat regions but an increase in the proportion occurring in LINE and SINE regions compared to INSs. Moreover, it was observed that deletions within topologically associated domains were associated with local enhanced interactions and disrupted chromatin loops, which might influence H3K27ac modification of histone contributing to enhancer or silencer hijacking. Conclusion: This study provides insights into the genomic signature of SVs in human pancreatic cancer. These findings might shed new light on the complexity of SVs and their pathogenesis by interplaying with chromatin organization. Citation Format: Yongxing Du, Xiaohao Zheng, Yunjie Duan, Chengfeng Wang. Genomic Analysis of Structural Variations in Pancreatic Cancer Using Long-Read Sequencing [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr A083.

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Journal
Cancer Research
Published
2024-09-15
DOI
https://doi.org/10.1158/1538-7445.pancreatic24-a083
Primary Topic
Cancer Genomics and Diagnostics
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article

Abstract A083: Genomic Analysis of Structural Variations in Pancreatic Cancer Using Long-Read Sequencing

Yongxing Du, Yunjie Duan, Chengfeng Wang, Xiaohao Zheng
Cancer Research
Cancer Genomics and Diagnostics
article

Abstract A083: Genomic Analysis of Structural Variations in Pancreatic Cancer Using Long-Read Sequencing

Yongxing Du, Yunjie Duan, Chengfeng Wang, Xiaohao Zheng
article en

Abstract

Abstract Objective: Structural variations (SVs) constitute the greatest source of genomic alterations leading to the oncogenesis of many cancers, including the deadliest pancreatic cancer (PC). However, SVs in PC remain largely undefined due to technological limitations of the traditional short-read sequencing. This study aims to establish a comprehensive signature of genomic SVs in PC. Methods: PacBio whole genome long-read sequencing was employed to investigate the genomic landscape of SVs in eight tissues from four pancreatic cancer patients. A variety of SVs callers, including pbsv, Sniffles, cuteSV, and svim, were comprehensively adopted to improve the accuracy of SVs detection. Many undefined characteristics of germline and somatic SVs were revealed by comparing with multiple previously published databases. Besides, the impacts of structural variations on 3D chromatin organization were analyzed by integrating multi-omics data including Hi-C, RNA seq and ChIP seq. Results: A total of 26,844 and 27,028 non-redundant SVs were identified in human pancreatic cancer and matched para-cancerous tissues, respectively. Notably, among these SVs, 23.97% were novel and had not been previously reported. Germline SVs were further characterized and found enriched in 25 well-known susceptible genes, such as TP63, PVT1, and ABO. Additionally, we proposed a panel of germline SVs with predicted highest pathogenicity, involving STOX1, DSPP, and WRN. Totally, 616 somatic SVs were identified and presented high burdens in patients with lymph node metastasis. We observed that somatic DELs and INSs were significantly more prevalent in repetitive regions than in non-repetitive regions. Interestingly, DELs showed a decrease in the proportion occurring in simple repeat regions but an increase in the proportion occurring in LINE and SINE regions compared to INSs. Moreover, it was observed that deletions within topologically associated domains were associated with local enhanced interactions and disrupted chromatin loops, which might influence H3K27ac modification of histone contributing to enhancer or silencer hijacking. Conclusion: This study provides insights into the genomic signature of SVs in human pancreatic cancer. These findings might shed new light on the complexity of SVs and their pathogenesis by interplaying with chromatin organization. Citation Format: Yongxing Du, Xiaohao Zheng, Yunjie Duan, Chengfeng Wang. Genomic Analysis of Structural Variations in Pancreatic Cancer Using Long-Read Sequencing [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr A083.

Cancer ResearchVol. 84(17_Supplement_2)
Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
Openalex Percentile: Top 78%
Cancer Genomics and Diagnostics
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