Abstract B075: Detection of early gastric carcinoma by micronuclei DNA from erythrocytes

Abstract Background: Advancements in non-invasive diagnostic technologies for gastric carcinoma (GC), including serum microRNA and cell-free DNA assays, have shown promise but still face challenges in achieving consistent early detection. Micronuclei (MN), extranuclear bodies harboring fragmented chromosomal segments, are indicative of genomic instability and have been employed in genotoxicity assessments and cancer diagnostics. We have developed a novel technique (WO2021/228246 A1) for the purification and characterization of micronuclei DNA (MN-DNA) extracted from erythrocytes in peripheral blood. Here, we evaluated the potential of micronuclei DNA (MN-DNA) from 2ml peripheral blood for early gastric carcinoma detection and explored its application for early cancer diagnosis. Methods: We assembled a clinical cohort consisting of 425 healthy donors (HDs) and 282 gastric cancer patients, from whom 1-2 mL peripheral blood samples were collected. Participants were randomly allocated into training, validation, and independent test cohorts in a 7:2:1 ratio, ensuring similar distributions of cancer stages and gender. MN-DNA was isolated from erythrocytes and subjected to comprehensive whole-genome sequencing. Predictive machine learning models were constructed utilizing distinct tumor-associated MN-DNA features identified through genome-wide analysis to distinguish between HDs and GC. Results: Comprehensive genome-wide analysis of MN-DNA demonstrated pronounced disparities in distribution patterns between HDs and GC patients. The predictive model built on MN-DNA features achieved an AUC of 97.69% (95%CI: 95.57- 99.81%), with an 96.47% specificity and 91.07% sensitivity in the independent test cohort. The model identified early GC (stage 0-I) and advanced GC (stage II-IV) with sensitivities of 95.24% or 78.57%, respectively. Conclusions: Our results demonstrate that MN-DNA from 1-2mL peripheral blood enable accurate detection of GC, especially in early GC. As a type of cytoplasmic DNA, MN-DNA can provide a valuable tool for early cancer detection, offering different underlying mechanisms compared to current methods. Research sponsor: Timing Biotech. Citation Format: Yuehua Han, Xingyun Yao, Haobo Sun, Cheng Fang, Peiwei Li, Honghao Liang, Jie Jin, Xiaofei Gao. Detection of early gastric carcinoma by micronuclei DNA from erythrocytes [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B075.

Authors

Institutions

Publication Details

Journal
Clinical Cancer Research
Published
2024-11-13
DOI
https://doi.org/10.1158/1557-3265.liqbiop24-b075
Primary Topic
RNA modifications and cancer
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract B075: Detection of early gastric carcinoma by micronuclei DNA from erythrocytes

Yuehua Han, Peiwei Li, Xingyun Yao, Xiaofei Gao et al.
Clinical Cancer Research
RNA modifications and cancer
article

Abstract B075: Detection of early gastric carcinoma by micronuclei DNA from erythrocytes

Yuehua Han, Peiwei Li, Xingyun Yao, Xiaofei Gao, Honghao Liang, Haobo Sun, Jie Jin, Cheng Fang
article en

Abstract

Abstract Background: Advancements in non-invasive diagnostic technologies for gastric carcinoma (GC), including serum microRNA and cell-free DNA assays, have shown promise but still face challenges in achieving consistent early detection. Micronuclei (MN), extranuclear bodies harboring fragmented chromosomal segments, are indicative of genomic instability and have been employed in genotoxicity assessments and cancer diagnostics. We have developed a novel technique (WO2021/228246 A1) for the purification and characterization of micronuclei DNA (MN-DNA) extracted from erythrocytes in peripheral blood. Here, we evaluated the potential of micronuclei DNA (MN-DNA) from 2ml peripheral blood for early gastric carcinoma detection and explored its application for early cancer diagnosis. Methods: We assembled a clinical cohort consisting of 425 healthy donors (HDs) and 282 gastric cancer patients, from whom 1-2 mL peripheral blood samples were collected. Participants were randomly allocated into training, validation, and independent test cohorts in a 7:2:1 ratio, ensuring similar distributions of cancer stages and gender. MN-DNA was isolated from erythrocytes and subjected to comprehensive whole-genome sequencing. Predictive machine learning models were constructed utilizing distinct tumor-associated MN-DNA features identified through genome-wide analysis to distinguish between HDs and GC. Results: Comprehensive genome-wide analysis of MN-DNA demonstrated pronounced disparities in distribution patterns between HDs and GC patients. The predictive model built on MN-DNA features achieved an AUC of 97.69% (95%CI: 95.57- 99.81%), with an 96.47% specificity and 91.07% sensitivity in the independent test cohort. The model identified early GC (stage 0-I) and advanced GC (stage II-IV) with sensitivities of 95.24% or 78.57%, respectively. Conclusions: Our results demonstrate that MN-DNA from 1-2mL peripheral blood enable accurate detection of GC, especially in early GC. As a type of cytoplasmic DNA, MN-DNA can provide a valuable tool for early cancer detection, offering different underlying mechanisms compared to current methods. Research sponsor: Timing Biotech. Citation Format: Yuehua Han, Xingyun Yao, Haobo Sun, Cheng Fang, Peiwei Li, Honghao Liang, Jie Jin, Xiaofei Gao. Detection of early gastric carcinoma by micronuclei DNA from erythrocytes [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B075.

Clinical Cancer ResearchVol. 30(21_Supplement)
Westlake University (CN), Second Affiliated Hospital of Zhejiang University (CN)
Good health and well-being
Openalex Percentile: Top 82%
RNA modifications and cancer
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.