Jan 2026· Mediators of Inflammation· Vol 2026· 0 citations· 37 references
Medicine
TL;DR
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.
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.
Identifying diagnostic and prognostic biomarkers and therapeutic targets for hepatocellular carcinoma (HCC) is essential to improve risk stratification, guide individualized treatment, and enhance therapeutic efficacy.The expression of SAMM50 (Sorting and Assembly Machinery Component 50) was initially analyzed in publicly accessible curated genomic and proteomic databases, such as the Cancer Cell Line Encyclopedia, the Human Protein Atlas, and other HCC-specific repositories. This analysis revealed differential expression patterns between HCC and non-neoplastic liver tissue. Subsequently, clinicopathological data and tissue specimens were collected from 200 HCC patients who underwent treatment at our institution. The protein and transcript levels of SAMM50 were experimentally measured in paired HCC and adjacent non-tumorous tissues using immunohistochemistry (IHC) and quantitative reverse transcription polymerase chain reaction (qRT-PCR). The association between SAMM50 expression and key clinicopathological features was further evaluated. Univariate and multivariate Cox proportional hazards analyses were performed to determine the independent prognostic value of SAMM50 expression in HCC. Based on these results, a reproducible and clinically applicable nomogram, supported by a forest plot, was constructed to facilitate prognostic prediction and support individualized therapeutic decision-making. Finally, in vitro and in vivo experiments were conducted to characterize the phenotypic alterations in HCC cells after SAMM50 knockdown, thereby confirming its involvement in critical oncogenic behaviors.This research demonstrated that the mRNA and protein levels of SAMM50 in HCC tissues were elevated compared to those in normal liver and adjacent tissues. Immunohistochemistry findings confirmed that SAMM50 protein levels were persistently higher in HCC tissues than in paired adjacent tissues. High expression of SAMM50 was correlated with unfavorable clinicopathological factors, encompassing pretreatment alpha-fetoprotein (AFP) levels, tumor size, T stage, American Joint Committee on Cancer (AJCC) stage, histological grade, and worse overall survival.Specifically, high expression of SAMM50 was linked to shorter overall survival (OS), progression-free survival (PFS), and disease-free survival (DFS). Moreover, univariate and multivariate Cox analyses were conducted to investigate the association between SAMM50 expression and clinicopathological features in HCC patients and to identify independent prognostic factors. The area under the receiver operating characteristic (ROC) curve (AUC) for SAMM50 was 0.863, suggesting its potential as a diagnostic marker for HCC, though further validation in independent cohorts is needed. Silencing of SAMM50 inhibited HCC cell proliferation, migration, and invasion, promoted apoptosis in vitro, and suppressed HCC growth in vivo.This research demonstrates that SAMM50 shows potential diagnostic value for HCC, though this observation requires further validation in larger, independent, and prospective cohorts. The results of this study not only contribute to the evaluation of baseline data and risk stratification in HCC but also offer novel approaches for the development of precise treatment strategies and targeted therapies.
To investigate the role of Intermediate Filament Family Orphan Protein 2
(IFFO2) in Liver Hepatocellular Carcinoma (LIHC), we systematically evaluated mRNA expression
and analyzed the correlation between IFFO2 expression and clinicopathological information, patient
prognosis, and the immune microenvironment. In this study, the influence of IFFO2 on LIHC proliferation,
clone formation, migration, and invasion was demonstrated using in vitro experiments. This
will provide a theoretical basis for IFFO2 to be developed into a biomarker and therapeutic target for
LIHC.
IFFO2 expression in pan-cancer and LIHC tissues was analyzed in the Cancer
Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. For assessing diagnostic
value, Receiver Operating Characteristic (ROC) curves were used, and Kaplan-Meier (KM)
and Cox regression were used for Prognostic analysis. The single-sample Gene Set Enrichment Analysis
(ssGSEA) algorithm was used to examine the relationship between IFFO2 expression and immune
cell infiltration. In vitro experiments used siRNA to knock down IFFO2 in HUH7 and HepG2
cells, followed by CCK-8 proliferation assays, clone formation, scratch wound-healing assays,
transwell invasion assays, and other experiments to examine changes in cellular behavior.
IFFO2 expression was obviously upregulated in the LIHC tissues (p < 0.05). The results of
the ROC analysis showed a high diagnostic ability, with an Area Under the Curve (AUC) of 0.790.
Increased IFFO2 is associated with high pathological stages, high levels of Alpha-Fetoprotein (AFP),
prolonged prothrombin time, and shortened overall survival (OS) (p < 0.05). Functional enrichment
analysis revealed that IFFO2 is significantly associated with immune regulation, cell cycle, and complement
activation pathways. Immune infiltration analysis demonstrated the presence of various immune
cell subtypes that exhibited both positive and negative correlations with IFFO2. In vitro experiments
have demonstrated that IFFO2 knockdown remarkably diminishes the proliferation, clone
formation, migration, and invasion capacities of LIHC cells (p < 0.05).
The findings suggest that IFFO2 functions as an oncogene in LIHC. Its strong association
with adverse prognosis and its potential to modulate the immune microenvironment underscore
its dual potential as a diagnostic biomarker and a promising therapeutic target, warranting further
mechanistic and clinical investigation.
IFFO2 is significantly upregulated in LIHC and promotes tumor progression; its expression
is associated with unfavorable prognostic outcomes, suggesting its potential utility as a biomarker
for diagnosis and a therapeutic target.
Qi Li, Shengke Wen, Hong Chen et al.· Current Cancer Therapy Revie...· 0 citations
Breast cancer (BC) is the most common malignant tumor among women worldwide. ULBP1 (UL16 binding protein 1), as a ligand of NKG2D, has been associated with poor prognosis in multiple cancers; however, its role in BC remains unclear.
TCGA and GEO datasets (TCGA-BRCA, GSE36295, and GSE1379) were used to evaluate the expression characteristics of ULBP1 and its association with prognosis. Functional enrichment analyses were subsequently performed to identify key biological pathways. The CIBERSORT and oncoPredict algorithms were applied to assess immune infiltration features and differences in drug sensitivity, respectively. In addition, qRT-PCR, western blotting, as well as CCK-8 and Transwell assays were conducted to validate ULBP1 expression in BC cells and to examine its effects on cellular functions.
Analysis of public datasets revealed that ULBP1 is significantly overexpressed in BC tissues, and its high expression was independently associated with shortened overall survival. GSEA revealed that high ULBP1 expression was significantly enriched in immune-related pathways, including natural killer cell–mediated cytotoxicity. Immune infiltration analysis indicated that high ULBP1 expression was closely associated with neutrophil enrichment and the upregulation of multiple immune checkpoint genes. Drug sensitivity prediction showed that patients with high ULBP1 expression may be more sensitive to olaparib and other agents.
In vitro
experiments further confirmed that ULBP1 was highly expressed in BC cell lines, and that knockdown of ULBP1 significantly suppressed MCF-7 cell viability and reduced migratory and invasive capacities.
ULBP1 may serve as a potential novel prognostic biomarker in BC, and targeting ULBP1 may provide a new therapeutic strategy for BC.
Qixin Mao, Yu Zheng, Shanqing Liu et al.· Frontiers in Oncology· 0 citations
Hepatocellular carcinoma (HCC) is one of the malignant tumors with high incidence and mortality rates worldwide. Given the poor prognosis of patients with HCC, it is crucial to explore the molecular mechanisms underlying HCC development and to evaluate prognostic markers. Differential expression analysis followed by univariate Cox, LASSO, and multivariate Cox regression identified four genes (EPO, SOCS2, IL18RAP, and KPNA2), and a Cox-based risk score was evaluated in the TCGA-LIHC cohort and externally in GSE14520 using Kaplan–Meier and time-dependent ROC analyses. Bulk, single-cell, and protein resources provided convergent expression context. Survival machine-learning analysis using observed overall-survival time and censoring status identified Cox–Ridge as the best-performing model in TCGA-LIHC, with more modest performance in GSE14520, and immune profiling revealed risk-group-associated differences in estimated immune and stromal components, immune-cell composition, and immune-checkpoint expression. The oncoPredict/GDSC2 screen highlighted five potential drug candidates for experimental prioritization. Because the drug screen is based on computationally predicted sensitivities, these findings should be regarded as hypothesis-generating and require validation in prospective cohorts and experimental systems before clinical translation.
Yuxian Liu, Xing-Jie Chen, Junyuan Zhang et al.· International Journal of Mol...· 0 citations
Background Changes in the tumor microenvironment (TME) are closely involved in hepatocellular carcinoma (HCC) development, and lipid metabolic disorders may take part in this process. STARD3NL is known to be related to cholesterol trafficking and lipid homeostasis. However, little is known about whether STARD3NL is linked to immune features of the HCC microenvironment. Methods We first explored STARD3NL expression and its prognostic relevance in HCC using The Cancer Genome Atlas (TCGA). To verify the bioinformatic findings, HCC tissue microarrays (TMAs) were analyzed by immunohistochemistry (IHC) for STARD3NL localization and survival evaluation. Multiplex immunohistochemistry (mIHC), combined with digital image analysis, was further used to characterize immune cell infiltration. Clinicopathological differences between tumors with high and low STARD3NL expression were also examined. In addition, spatial distance analysis was performed to assess how immune cells were arranged in STARD3NL-high regions. Results TCGA-based analysis and mIHC validation both showed higher STARD3NL expression in HCC tissues. Patients with increased STARD3NL expression had poorer survival (p = 0.029), and multivariable analysis supported STARD3NL as an independent risk factor. STARD3NL-high tumors showed increased proportions of CD68+ macrophages and FOXP3+ T cells (p < 0.005). Spatial analysis further indicated that Tregs were more frequently located near macrophages (p = 0.001), with a shorter mean macrophage-Treg distance (p = 0.027). This macrophage-Treg proximity was associated with worse prognosis (p = 0.030). Conclusion High STARD3NL expression is significantly associated with immune-suppressive features and unfavorable outcomes in HCC. These findings indicate that STARD3NL may have value as a prognostic biomarker associated with an immunosuppressive tumor microenvironment.
Di Li, Ziyu Liu, Lihe Xie et al.· Frontiers in Oncology· 0 citations
Hepatocellular carcinoma (HCC) poses a significant global health burden with limited therapeutic options, particularly for non-viral etiologies. The mitochondrial solute carrier SLC25A43 is implicated in cellular redox homeostasis, yet its role in HCC remains unclear. This study aimed to comprehensively investigate the expression pattern, clinical significance, biological function, and potential mechanisms of SLC25A43 in HCC. Utilizing multi-omics data from public databases (TCGA-LIHC, GEO, and HPA), we performed integrated bioinformatic analyses. SLC25A43 was consistently upregulated in HCC tissues compared with non-tumorous liver tissues and demonstrated strong diagnostic value (AUC = 0.861). High SLC25A43 expression was significantly associated with advanced tumor stage, metastasis, and adverse clinicopathological features. Survival analyses identified SLC25A43 as an independent prognostic risk factor for overall survival, progression-free interval, and disease-specific survival. Functional enrichment analyses suggested that SLC25A43 is involved in mitochondrial oxidative phosphorylation, energy metabolism, and immune-related pathways. Immune infiltration analyses using ssGSEA, xCell, and TIMER consistently revealed negative correlations between SLC25A43 expression and multiple antitumor immune cell populations, particularly CD8 + T cells. Experimental validation confirmed that SLC25A43 was significantly upregulated in HCC tissues at both mRNA and protein levels. Functional assays in Huh-7, Hep-LM3, MHCC97H, and LO2 cells demonstrated that SLC25A43 knockdown inhibited, whereas overexpression promoted, cell proliferation and migration. Rescue experiments further verified the specificity of these effects. Mechanistically, SLC25A43 regulated intracellular ATP production, ROS accumulation, and glutathione metabolism, indicating a role in redox homeostasis and energy metabolism. In addition, PBMC co-culture experiments showed that SLC25A43 suppressed CD8 + T-cell cytotoxic activity by reducing Granzyme B expression. A prognostic nomogram incorporating SLC25A43 exhibited favorable predictive performance and was successfully validated in two independent GEO cohorts. SLC25A43 is a novel diagnostic and prognostic biomarker for HCC. Its upregulation promotes tumor progression through metabolic reprogramming, redox homeostasis remodeling, and suppression of antitumor immune responses. These findings highlight SLC25A43 as a promising therapeutic target and provide new insights into the metabolic-immune regulatory network in hepatocellular carcinoma.
Dunzhen Chen, Li Yu, Xichang Zhou et al.· Scientific Reports· 0 citations