Loss of ficolin-3 expression is associated with poor prognosis in patients with hepatocellular carcinoma

Chen, Chia-Chi; Yu, Teng‐Hung; Wu, Cheng‐Ching; Hung, Wei‐Chin; Lee, Thung-Lip; Tang, Wei‐Hua; Tsai, I‐Ting; Chung, Fu‐Mei; Lee, Yau-Jiunn; Hsu, Chia‐Chang

doi:10.7150/ijms.84729

Cited by 4 publications

(3 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Interestingly, ficolin-3, to which MASP-3 is predominantly associated in human serum [41], also may act as a tumor-suppressor agent. It has been shown that the expression of the FCN3 gene is lower in the case of different cancers [250], and a recent study demonstrated that hepatocellular carcinoma patients with a high FCN3 expression had a significantly better overall survival [251]. Although the mechanism is far from clear [252], we can speculate whether MASP-3 may contribute to the tumor suppressor phenomenon in this case.…”

Section: Role In Cancermentioning

confidence: 58%

The Lectin Pathway of the Complement System—Activation, Regulation, Disease Connections and Interplay with Other (Proteolytic) Systems

Dobó,

Kocsis,

Farkas

et al. 2024

IJMS

View full text Add to dashboard Cite

The complement system is the other major proteolytic cascade in the blood of vertebrates besides the coagulation–fibrinolytic system. Among the three main activation routes of complement, the lectin pathway (LP) has been discovered the latest, and it is still the subject of intense research. Mannose-binding lectin (MBL), other collectins, and ficolins are collectively termed as the pattern recognition molecules (PRMs) of the LP, and they are responsible for targeting LP activation to molecular patterns, e.g., on bacteria. MBL-associated serine proteases (MASPs) are the effectors, while MBL-associated proteins (MAps) have regulatory functions. Two serine protease components, MASP-1 and MASP-2, trigger the LP activation, while the third component, MASP-3, is involved in the function of the alternative pathway (AP) of complement. Besides their functions within the complement system, certain LP components have secondary (“moonlighting”) functions, e.g., in embryonic development. They also contribute to blood coagulation, and some might have tumor suppressing roles. Uncontrolled complement activation can contribute to the progression of many diseases (e.g., stroke, kidney diseases, thrombotic complications, and COVID-19). In most cases, the lectin pathway has also been implicated. In this review, we summarize the history of the lectin pathway, introduce their components, describe its activation and regulation, its roles within the complement cascade, its connections to blood coagulation, and its direct cellular effects. Special emphasis is placed on disease connections and the non-canonical functions of LP components.

show abstract

Section: Role In Cancermentioning

confidence: 58%

The Lectin Pathway of the Complement System—Activation, Regulation, Disease Connections and Interplay with Other (Proteolytic) Systems

Dobó,

Kocsis,

Farkas

et al. 2024

IJMS

View full text Add to dashboard Cite

show abstract

“…patients with high FCN3 expression had a higher overall survival rate than those with low FCN3 expression (p = 0.031), which was consistent with our study. And high FCN3 expression in tumor tissue was independently associated with better overall survival (p = 0.042) (Chen et al 2023).…”

Section: Discussionmentioning

confidence: 99%

Identification of Hub Genes in Liver Hepatocellular Carcinoma Based on Weighted Gene Co-expression Network Analysis

Sun,

Zhang,

Cai

et al. 2024

Biochem Genet

View full text Add to dashboard Cite

Liver hepatocellular carcinoma (LIHC) is a malignant cancer with high incidence and poor prognosis. To investigate the correlation between hub genes and progression of LIHC and to provided potential prognostic markers and therapy targets for LIHC. Our study mainly used The Cancer Genome Atlas (TCGA) LIHC database and the gene expression profiles of GSE54236 from the Gene Expression Omnibus (GEO) to explore the differential co-expression genes between LIHC and normal tissues. The differential co-expression genes were extracted by Weighted Gene Co-expression Network Analysis (WGCNA) and differential gene expression analysis methods. The Genetic Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were carried out to annotate the function of differential genes. Then the hub genes were validated using protein-protein interaction (PPI) network. And the expression level and prognostic analysis were performed. The probable associations between the expression of hub genes and both tumor purity and infiltration of immune cells were explored by TIMER. A total of 68 differential co-expression genes were extracted. These genes were mainly enriched in complement activation (biological process), collagen trimer (cellular component), carbohydrate binding and receptor ligand activity (molecular function) and cytokine − cytokine receptor interaction. Then we demonstrated that the 10 hub genes (CFP, CLEC1B, CLEC4G, CLEC4M, FCN2, FCN3, PAMR1 and TIMD4) were weakly expressed in LIHC tissues, the qRT-PCR results of clinical samples showed that six genes were significantly downregulated in LIHC patients compared with adjacent tissues. Worse overall survival (OS) and disease-free survival (DFS) in LIHC patients were associated with the lower expression of CFP, CLEC1B, FCN3 and TIMD4. Ten hub genes had positive association with tumor purity. CFP, CLEC1B, FCN3 and TIMD4 could serve as novel potential molecular targets for prognosis prediction in LIHC.

show abstract

“…GDF11 expression was assessed using both IHC and histochemical scoring (H-score) methods, as described in previous studies [29,30]. Both cytoplasmic and membranous expressions were included and considered positive.…”

Section: Evaluation Of Immunohistochemical Stainingmentioning

confidence: 99%

Tissue Expression of Growth Differentiation Factor 11 in Patients with Breast Cancer

Chen,

Lee,

Tsai

et al. 2024

Diagnostics

Self Cite

View full text Add to dashboard Cite

Protein growth differentiation factor 11 (GDF11) plays crucial roles in cellular processes, including differentiation and development; however, its clinical relevance in breast cancer patients is poorly understood. We enrolled 68 breast cancer patients who underwent surgery at our hospital and assessed the expression of GDF11 in tumorous, ductal carcinoma in situ (DCIS), and non-tumorous tissues using immunohistochemical staining, with interpretation based on histochemical scoring (H-score). Our results indicated higher GDF11 expressions in DCIS and normal tissues compared to tumorous tissues. In addition, the GDF11 H-score was lower in the patients with a tumor size ≥ 2 cm, pathologic T3 + T4 stages, AJCC III-IV stages, Ki67 ≥ 14% status, HER2-negative, and specific molecular tumor subtypes. Notably, the patients with triple-negative breast cancer exhibited a loss of GDF11 expression. Spearman correlation analysis revealed associations between GDF11 expression and various clinicopathological characteristics, including tumor size, stage, Ki67, and molecular subtypes. Furthermore, GDF11 expression was positively correlated with mean corpuscular hemoglobin concentration and negatively correlated with neutrophil count, as well as standard deviation and coefficient of variation of red cell distribution width. These findings suggest that a decreased GDF11 expression may play a role in breast cancer pathogenesis.

show abstract

Loss of ficolin-3 expression is associated with poor prognosis in patients with hepatocellular carcinoma

Cited by 4 publications

References 31 publications

The Lectin Pathway of the Complement System—Activation, Regulation, Disease Connections and Interplay with Other (Proteolytic) Systems

The Lectin Pathway of the Complement System—Activation, Regulation, Disease Connections and Interplay with Other (Proteolytic) Systems

Identification of Hub Genes in Liver Hepatocellular Carcinoma Based on Weighted Gene Co-expression Network Analysis

Tissue Expression of Growth Differentiation Factor 11 in Patients with Breast Cancer

Contact Info

Product

Resources

About