Evidence map›Paper›PMID 41909879›Full record

ArticleBiotechnology reports (Amsterdam, Netherlands)2026

Identification of STEAP4, EPC1, and CLEC1B as non-invasive candidate biomarkers for hepatocellular carcinoma using integrated bioinformatics analysis.

Soheyla Khojand, Neda Zahmatkesh, Arezoo Hassani, Zahra Damerchiloo, Zahra Nikoo, Roozbeh Heidarzadehpilehrood

Abstract read
In one paragraph

Article in Biotechnology reports (Amsterdam, Netherlands), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Soheyla KhojandDepartment of Biotechnology and Plant Breeding, Science and Research Branch, Islamic Azad University, Tehran, Iran.
Neda ZahmatkeshDepartment of Genetics, Zanjan Branch, Islamic Azad University, Zanjan, Iran.
Arezoo HassaniDepartment of Genetics, Zanjan Branch, Islamic Azad University, Zanjan, Iran.
Zahra DamerchilooDepartment of Genetics, Faculty of Advanced Science and Technology, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran.
Zahra NikooDepartment of Genetics, Faculty of Advanced Science and Technology, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran.
Roozbeh HeidarzadehpilehroodDepartment of Obstetrics & Gynecology, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The high global mortality of hepatocellular carcinoma (HCC) underscores the need for reliable non-invasive diagnostic biomarkers. In this study, transcriptomic analyses were performed on peripheral blood mononuclear cell (PBMC) and tumor datasets from HCC patients to identify differentially expressed genes (DEGs) using an adjusted p-value 〈 0.01 and |log2FC| 〉 1. Functional enrichment analyses revealed predominant immune-related pathways in PBMCs and metabolic pathway dysregulation in tumor tissues. Integration of PBMC and tumor profiles identified STEAP4, EPC1, CLEC1B, and LCN2 as shared DEGs. Survival analyses indicated that elevated expression of STEAP4, EPC1, and CLEC1B was associated with poorer overall survival in HCC patients. Collectively, these findings highlight consistent transcriptional alterations in PBMCs and tumor tissues and suggest that STEAP4, EPC1, and CLEC1B may serve as potential non-invasive biomarkers with diagnostic and prognostic relevance in HCC.

Indexed as

Diagnostic biomarkerHepatocellular carcinomaNon-coding RNANon-invasive biomarkerPeripheral blood mononuclear cellsPrognostic biomarker

Identifiers

PMID41909879
PMCPMC13019070

What Socratic holds

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Registered trials

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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 Socratic graph.