Evidence map›Paper›PMID 42439272›Full record

ArticleMediators of inflammation2026

SRM Represents a Novel Prognosis Biomarker and Correlates With Inflammation and Immune Infiltration in Hepatocellular Carcinoma.

Bo-Wen Wu, Feng-Hong Wang, Lei Zhang, Ting Li, Jian-Qiang Zhang, Sheng-Bo Yang, Xue-Mei Wang, Ya-Nan Li

Abstract read
In one paragraph

Article in Mediators of inflammation, 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 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

8 authors.

Bo-Wen WuDepartment of Health Statistics, School of Public Health, Inner Mongolia Medical University, Hohhot, China, immu.edu.cn.ORCID https://orcid.org/0009-0009-0792-6301
Feng-Hong WangDepartment of Toxicology, School of Public Health, Inner Mongolia Medical University, Hohhot, China, immu.edu.cn.ORCID https://orcid.org/0009-0000-1367-0466
Lei ZhangDepartment of Occupational Health and Environmental Health, School of Public Health, Binzhou Medical University, Yantai, China, bzmc.edu.cn.ORCID https://orcid.org/0000-0001-9548-8325
Ting LiDepartment of Health Statistics, School of Public Health, Inner Mongolia Medical University, Hohhot, China, immu.edu.cn.ORCID https://orcid.org/0009-0007-5977-2127
Jian-Qiang ZhangDepartment of Health Statistics, School of Public Health, Inner Mongolia Medical University, Hohhot, China, immu.edu.cn.ORCID https://orcid.org/0009-0002-8503-4789
Sheng-Bo YangDepartment of Health Statistics, School of Public Health, Inner Mongolia Medical University, Hohhot, China, immu.edu.cn.ORCID https://orcid.org/0009-0006-7023-4429
Xue-Mei WangDepartment of Health Statistics, School of Public Health, Inner Mongolia Medical University, Hohhot, China, immu.edu.cn.ORCID https://orcid.org/0000-0003-0298-9695
Ya-Nan LiDepartment of Occupational Health and Environmental Health, School of Public Health, Inner Mongolia Medical University, Hohhot, China, immu.edu.cn.ORCID https://orcid.org/0009-0003-4907-2304

Funding

Research Initiation Grant for Talent Introduction to Inner Mongolia Medical University DC2400000598
6 · The paper itself

Abstract

Hepatocellular carcinoma (HCC) is widely recognized as one of the leading causes of cancer-related deaths worldwide. Although advances in screening, diagnosis, and treatment have been made, reliable biomarkers are urgently needed to monitor the disease. This study aims to investigate the association between spermidine synthase (SRM) and clinicopathological characteristics, inflammatory responses, and immune infiltration in HCC. RNA-seq data and clinical information for liver HCC (LIHC) were obtained from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases to assess SRM expression. The correlation between SRM expression and immune infiltration was analyzed using the TIMER algorithm. Comprehensive analyses of immune checkpoints (ICPs), microsatellite instability (MSI), and tumor mutational burden (TMB) were performed using R-based packages. KEGG analysis indicated SRM is involved in the IL-17 signaling pathway. This association was further supported by experimental validation of key markers via qPCR and western blot. Functional studies, including in vivo experiments, are needed to establish a causal relationship. Our results show that SRM expression is significantly elevated in HCC tissues compared to adjacent nontumor tissues and associated with adverse clinicopathological features and poor prognosis. SRM expression was significantly correlated with immune infiltration levels in LIHC, involving 22 immune cell subtypes, particularly tumor-associated macrophages (TAMs; CD86 and IL10). Moreover, SRM expression was closely associated with ICPs, TMB, and MSI. Based on transcriptomic data, KEGG pathway analysis of SRM-associated differentially expressed genes revealed significant enrichment in the IL-17 signaling pathway. These in vitro findings suggest a potential association among SRM, IL-8 expression, and pathways related to tumor progression and immune modulation, although further in vivo studies are required to confirm these observations. However, in vivo studies using animal models are required to evaluate whether targeting SRM has therapeutic effects on HCC and to further validate these mechanistic findings.

Indexed as

Biomarkers, TumorCarcinoma, HepatocellularInflammationLiver NeoplasmsFemaleGene Expression Regulation, NeoplasticHumansMalePrognosisBiomarkers, Tumorbioinformaticshepatocellular carcinomaimmune infiltrateinflammationSRM

Identifiers

PMID42439272
PMCPMC13359114

What Socratic holds

Textmetadata
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 Socratic graph.