In one paragraphArticle in Cell communication and signaling : CCS, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from itWhat it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registryThe trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
3 · Its place in the literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
15 authors.
Xuanmei Luo *Clinical Biobank, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, No.1 Dahua Road, Dongcheng District, Beijing, 100730, China.ORCID http://orcid.org/0009-0006-5838-3579 Jian Cui *Department of General Surgery, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, No.1 Dahua Road, Dongcheng District, Beijing, 100730, China.ORCID http://orcid.org/0000-0002-7024-3468 Jinxin ShiDepartment of General Surgery, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, No.1 Dahua Road, Dongcheng District, Beijing, 100730, China.
Gaoyuan SunClinical Biobank, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, No.1 Dahua Road, Dongcheng District, Beijing, 100730, China.ORCID http://orcid.org/0009-0006-0250-0377 Lili ZhangClinical Biobank, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, No.1 Dahua Road, Dongcheng District, Beijing, 100730, China.ORCID http://orcid.org/0000-0002-3601-0150 Yayu LiClinical Biobank, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, No.1 Dahua Road, Dongcheng District, Beijing, 100730, China.ORCID http://orcid.org/0009-0005-6978-0775 Yingyu GuoClinical Biobank, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, No.1 Dahua Road, Dongcheng District, Beijing, 100730, China.ORCID http://orcid.org/0009-0009-9297-5115 Lu KuaiClinical Biobank, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, No.1 Dahua Road, Dongcheng District, Beijing, 100730, China.ORCID http://orcid.org/0000-0003-3828-8735 Tianhan SunDepartment of General Surgery, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, No.1 Dahua Road, Dongcheng District, Beijing, 100730, China.ORCID http://orcid.org/0009-0006-1301-8164 Qi LuoClinical Biobank, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, No.1 Dahua Road, Dongcheng District, Beijing, 100730, China.
Jiahui CaiClinical Biobank, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, No.1 Dahua Road, Dongcheng District, Beijing, 100730, China.ORCID http://orcid.org/0009-0003-9969-5024 Qi AnDepartment of General Surgery, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, No.1 Dahua Road, Dongcheng District, Beijing, 100730, China.ORCID http://orcid.org/0000-0001-8564-3344 Wei ZhangDepartment of Pathology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, No.1 Dahua Road, Dongcheng District, Beijing, 100730, China. zhangwei3392@bjhmoh.cn.ORCID http://orcid.org/0000-0003-1515-964X Fei XiaoClinical Biobank, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, No.1 Dahua Road, Dongcheng District, Beijing, 100730, China. xiaofei3965@bjhmoh.cn.ORCID http://orcid.org/0000-0003-2054-901X Gang ZhaoDepartment of General Surgery, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, No.1 Dahua Road, Dongcheng District, Beijing, 100730, China. zhaogang7563@163.com.ORCID http://orcid.org/0009-0000-9559-7513 Funding
Beijing Bethune Charitable Foundation mnzl202024Beijing Jingjian Foundation for the Advancement of Pathology JJTS2020-006CAMS Innovation Fund for Medical Sciences 2025-I2M-FGS-008National High Level Hospital Clinical Research Funding BJ-2024-095Special Research Fund for Central Universities, Peking Union Medical College, China 3332023090
6 · The paper itselfAbstract
backgroundDelayed detection of recurrence significantly contributes to colorectal cancer (CRC) mortality, underscoring the need for robust prognostic biomarkers. Although extrachromosomal circular DNA (eccDNA) is a known oncogenic driver, its prognostic utility in CRC remains largely unexplored.
methodsIn this 6-year prospective cohort study, full-length eccDNA profiling of 153 plasma samples was performed using Nanopore sequencing. Differential eccDNA signatures between recurrence (R, n = 20) and non-recurrence (NR, n = 133) patients enabled construction of predictive models for recurrence and mortality. Functional validation of eccDNAs was conducted in HCT116 cells.
resultsCompared to NR patients, R patients exhibited enrichment of eccDNAs derived from chromosome 9, shorter median eccDNA lengths, and reduced variability in eccDNA length. All 4.9-5.0 kb eccDNAs derived from CKM, while other eccDNAs showed a strong genomic distribution correlation between groups (Spearman's ρ = 0.73). Promoter-derived eccDNAs were enriched in R patients, particularly from the promoter of CARD9 (eccPromoter-CARD9, 10.4-fold increase). Overexpression of eccPromoter-CARD9 significantly promoted CRC cell proliferation and migration. R patients exhibited elevated eccDNAs harboring the hsa-mir-374c cluster in plasma and tissues, and their corresponding miRNAs demonstrated exceptional diagnostic accuracy in CRC-related TCGA cohorts. An eccDNA-based random forest classifier achieved superior recurrence prediction accuracy (AUC > 0.8), correlating with shorter time-to-recurrence (HR = 3.79) and elevated CA125 and CEA levels. Additional eccDNA-based models effectively predicted recurrence-associated mortality (AUC ≥ 0.93).
conclusionsThe plasma eccDNA landscape may serve as an early and powerful non-invasive biomarker for CRC prognostication, optimizing risk stratification and guiding personalized treatment.
Indexed as
Biomarkers, TumorColorectal NeoplasmsDNA, CircularExtrachromosomal DNAFemaleHCT116 CellsHumansMaleMiddle AgedNeoplasm Recurrence, LocalPrognosisBiomarkers, TumorDNA, CircularExtrachromosomal DNAColorectal cancerExtrachromosomal circular DNALiquid biopsyMortalityRecurrence
Identifiers
PMID41654905
PMCPMC12977730
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