Evidence map›Paper›PMID 38498315›Full record

ArticleBiomolecules & biomedicine2024

Dynamic network biomarker C1QTNF1 regulates tumor formation at the tipping point of hepatocellular carcinoma.

Haoyuan Yu, Xijing Yan, Guanxing Chen, Rong Li, Zhou Yang, Zhixing Liang, Linsen Ye, Yunhao Chen, Yang Li

Open access · diamondAbstract read
In one paragraph

Article in Biomolecules & biomedicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 48% of its field
1 · What the graph read from it

What 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 registry

The 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 literature

Who cites it

2 citing papers in PubMed, 1 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

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 at 1 institution in 1 country.

Haoyuan YuDepartment of Hepatic Surgery and Liver Transplantation Center, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China; Guangdong Provincial Key Laboratory of Liver Disease Research, Guangzhou, China.
Xijing YanDepartment of Hepatic Surgery and Liver Transplantation Center, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China; Guangdong Provincial Key Laboratory of Liver Disease Research, Guangzhou, China.
Guanxing ChenArtificial Intelligence Medical Research Center, School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen, China.
Rong LiDepartment of Hepatic Surgery and Liver Transplantation Center, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China; Guangdong Provincial Key Laboratory of Liver Disease Research, Guangzhou, China.
Zhou YangDepartment of Hepatic Surgery and Liver Transplantation Center, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China; Guangdong Provincial Key Laboratory of Liver Disease Research, Guangzhou, China.
Zhixing LiangDepartment of Hepatic Surgery and Liver Transplantation Center, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China; Guangdong Provincial Key Laboratory of Liver Disease Research, Guangzhou, China.
Linsen YeDepartment of Hepatic Surgery and Liver Transplantation Center, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China; Guangdong Provincial Key Laboratory of Liver Disease Research, Guangzhou, China.
Yunhao ChenBiotherapy Center, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Yang LiDepartment of Hepatic Surgery and Liver Transplantation Center, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China; Guangdong Provincial Key Laboratory of Liver Disease Research, Guangzhou, China.
Sun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Identifying the precise moment before the onset of hepatocellular carcinoma (HCC) remains a significant challenge in the medical field. The existing biomarkers fall short of pinpointing the critical point preceding HCC formation. This study aimed to determine the exact tipping point for the transition from cirrhosis to HCC, identify the core Dynamic Network Biomarker (DNB), and elucidate its regulatory effects on HCC. A spontaneous HCC mouse model was established to mimic HCC formation in patients with chronic hepatitis. Using the DNB method, C1q and tumor necrosis factor (TNF) related 1 (C1QTNF1) protein was identified as the key DNB at the crucial tipping time of spontaneous HCC development. Both in vitro and in vivo studies showed that C1QTNF1 could inhibit tumor growth. Overexpression of C1QTNF1 before the tipping point effectively prevented HCC occurrence. Patients with elevated C1QTNF1 expression demonstrated improved overall survival (OS) (P = 0.03) and disease-free survival (DFS) (P = 0.03). The diagnostic value of C1QTNF1 was comparable to that of alpha-fetoprotein (AFP) (area under the curve [AUC] = 0.84; sensitivity 85%; specificity 80%). Furthermore, our research indicated that platelet-expressed C1QTNF1 is involved in cancer-associated signaling pathways. Our findings introduce a novel perspective by highlighting C1QTNF1 as the pivotal biomarker at the tipping point of primary HCC formation using DNB. We propose C1QTNF1 as a prognostic biomarker for HCC, potentially influencing tumor development through a platelet-related cancer signaling pathway.

Indexed as

Biomarkers, TumorCarcinoma, HepatocellularLiver NeoplasmsAnimalsCell Line, TumorComplement C1qFemaleHumansMaleMiceBiomarkers, TumorComplement C1q

Identifiers

PMID38498315
PMCPMC11293248
OpenAlexW4392893893

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.