Evidence map›Paper›PMID 39704423›Full record

ArticleCancer medicine2024

Non-Invasive Tumor-Naïve Minimal Residual Disease Detection of Liver Cancer by Incorporating Circulating Tumor DNA Features and Alpha-Fetoprotein: A Prospective Study.

Qingqi Ren, Shiyong Li, Guolin Zhong, Yunfei Li, Dao-Ling Huang, Liangliang Zhang, Yumin Feng, Guanghui Long, Mao Mao

Abstract read
In one paragraph

Article in Cancer medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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 registry

The trial behind it

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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 literature

Who cites it

3 citing papers in PubMed.

  1. Review
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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Qingqi RenDepartment of Hepatopancreatobiliary Surgery, Peking University Shenzhen Hospital, Shenzhen, China.
Shiyong LiResearch & Development, SeekIn Inc., Shenzhen, China.
Guolin ZhongResearch & Development, SeekIn Inc., Shenzhen, China.
Yunfei LiResearch & Development, SeekIn Inc., Shenzhen, China.
Dao-Ling HuangResearch & Development, SeekIn Inc., Shenzhen, China.
Liangliang ZhangClinical Laboratories, Shenyou Bio, Zhengzhou, China.
Yumin FengResearch & Development, SeekIn Inc., Shenzhen, China.
Guanghui LongDepartment of Hepatopancreatobiliary Surgery, Peking University Shenzhen Hospital, Shenzhen, China.
Mao MaoResearch & Development, SeekIn Inc., San Diego, California, USA.ORCID 0000-0002-8570-8571

Funding

Shenzhen High-level Hospital Construction Fund and Peking University Shenzhen Hospital Scientific Research Fund KYQD2023282
6 · The paper itself

Abstract

background and purposeLiver cancer has a high recurrence rate of 50%~70% for early-stage patients. Minimal residual disease (MRD) is strongly linked to liver cancer early recurrence. Identifying MRD through reliable prognostic biomarkers, such as circulating tumor DNA (ctDNA), could significantly benefit these patients by enabling timely intervention and improved outcomes. MATERIALS AND

methodsA prospective study enrolled 32 liver cancer patients undergoing radical surgery. Peripheral blood samples (8 mL) were collected before and after surgery. In this study, we expanded upon our previously developed multi-omics assay, initially designed for liver cancer early detection by calculating a cancer signal score (P

resultsOf the enrolled patients, 78.1% were in early stages, and before surgery, 87.5% of patients had successfully detected the cancer signal in blood. After radical surgery, 23 patients were MRD-negative, exhibiting better overall survival compared to the MRD-positive patients (n = 9, p < 0.01). Patients maintaining undetectable cancer signals pre- and post-surgery showed 100% survival, conversely, those keeping with detectable signals had a 55.6% mortality rate.

conclusionThis prospective study highlights the prognostic value of ctDNA-based tumor-naïve MRD detection through a multi-omics assay in early-stage liver cancer patients.

Indexed as

alpha-FetoproteinsBiomarkers, TumorCirculating Tumor DNALiver NeoplasmsNeoplasm, ResidualAdultAgedDNA Copy Number VariationsFemaleHumansMaleMiddle AgedPrognosisProspective StudiesAFP protein, humanalpha-FetoproteinsBiomarkers, TumorCirculating Tumor DNAAFPCNAfragment sizeliver cancerMRDsWGS

Identifiers

PMID39704423
PMCPMC11660314

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.