FGL1 Human

What is FGL1 and what is its molecular classification?

Fibrinogen-like protein 1 (FGL1) is a protein structurally related to fibrinogen. In humans, it is encoded by the FGL1 gene. FGL1 belongs to the fibrinogen family of proteins, which includes fibrinogen, fibrinogen-like protein 2, and clotting factors V, VIII, and XIII. FGL1 serves as a major immune regulatory protein in the human body.

What are the primary tissue sources of FGL1 expression in humans?

FGL1 is predominantly secreted by hepatocytes in the liver. The expression pattern varies in pathological conditions, with significant implications for both liver disorders and immune regulation. Research indicates that liver-specific expression of FGL1 is crucial for understanding its biological functions in both normal physiological states and disease conditions.

How does FGL1 expression change in metabolic liver diseases?

Contrary to some earlier hypotheses, FGL1 expression shows a biphasic pattern in metabolic liver disease progression. Studies in mouse models demonstrate that Fgl1 mRNA expression is initially induced after 4 weeks on a Western diet but significantly decreases between weeks 4-8 of continued dietary challenge. Similar expression patterns have been observed in human patients with metabolic dysfunction-associated steatohepatitis (MASH) and hepatocellular carcinoma (HCC), where FGL1 expression is significantly reduced compared to healthy controls.

How do different LAG-3/FGL1 expression patterns affect cancer prognosis?

Research has identified four distinct LAG-3/FGL1 expression subtypes in tumors that significantly impact prognosis:

These expression patterns provide important stratification criteria for predicting immunotherapy outcomes.

What immunosuppressive features are associated with high FGL1 expression in tumors?

Tumors with high FGL1 expression demonstrate multiple immunosuppressive characteristics:

• Elevated expression of T-cell exhaustion markers (TIM-3, CD39, and NRP1)

• Increased CD4+ regulatory T-cell signatures

• Enhanced M2-like macrophage infiltration

• Upregulation of dendritic cell signatures

• Activation of immunosuppressive pathways including epithelial-mesenchymal transition (EMT), angiogenesis, and TGFβ signaling

These features create an immune-evasive microenvironment that contributes to therapy resistance.

What experimental techniques are recommended for evaluating FGL1 expression in tumor tissues?

Multiplex immunohistochemistry (mIHC) represents the gold standard for comprehensive FGL1 analysis in tumor tissues. This approach allows for simultaneous evaluation of multiple markers including:

• FGL1 expression in tumor cells

• LAG-3 expression on immune cells

• CD8+ T-cell infiltration

• CD4+ T-cell distribution

• Foxp3+ regulatory T-cells

• PanCK (for tumor cell identification)

Cell segmentation based on membrane staining (except for Foxp3, which requires nuclear staining) enables quantitative spatial analysis of the tumor microenvironment. Researchers should quantify cell density (cells/mm²) for all markers, including double-positive populations in both tumor and stromal compartments.

What are the current limitations in measuring FGL1 protein levels in human samples?

Despite the importance of FGL1 in various pathologies, standardized methods for reliable quantification of FGL1 protein levels in human samples remain underdeveloped. As noted in recent literature, "The study of FGL1 protein level in human will await the development of new analytical tools and standardized methods." Researchers should be aware of this methodological gap when designing FGL1-focused studies and consider validating any new analytical approaches thoroughly before implementation.

What animal models are available for studying FGL1 function?

Several genetic mouse models have been developed for studying FGL1 function:

• Fgl1tm1b(EUCOMM)Hmgu mice: Global knockout model available from the international mouse phenotyping consortium

• Fgl1fl/fl mice: Generated by crossing with FLPO recombinase-expressing mice to remove the EUCOMM cassette

• Fgl1LKO mice: Liver-specific knockout created by breeding Fgl1fl/fl mice with mice expressing CRE recombinase under the control of the albumin promoter

These models enable tissue-specific investigation of FGL1 function in metabolic disorders and cancer. Statistical analysis of results should employ appropriate tests (Student's t-test, ANOVA) with p<0.05 considered significant.

How does FGL1 expression affect spatial distribution of immune cells in the tumor microenvironment?

Quantitative spatial analysis using multiplex immunohistochemistry has revealed critical insights into how FGL1 expression affects immune cell organization:

The spatial relationship between stromal CD8+LAG-3+ cells and tumor FGL1+ cells is particularly significant for predicting response to PD-1 blockade. Patients categorized as stromal CD8+LAG-3+ high/tumor FGL1+ low demonstrated superior progression-free survival compared to those with stromal CD8+LAG-3+ high/tumor FGL1+ high profiles (p=0.006).

What molecular mechanisms explain the differential effects of FGL1 expression in cancer?

Differential gene expression analysis between LAG-3 high FGL1 low and LAG-3 high FGL1 high tumors has revealed several key molecular drivers of FGL1-mediated immunosuppression:

• Tumor microenvironment-related genes: Upregulation of NRP1, ECM2, STAT3, and CD163 in FGL1-high tumors

• TGF-β signaling pathway components: Elevated TGFB1, TGFB3, and TGFBR1 expression

• Epithelial-mesenchymal transition markers: Increased VIM, SNAL1, COL4A1/2, and ACTA2 expression

• Gene Set Enrichment Analysis (GSEA): Confirmation of enriched pathways including EMT, KRAS signaling, angiogenesis, and CD8+ T-cell exhaustion

Additionally, NRP1 expression (critical for regulatory T-cell function) shows positive correlation with CD4+Treg signature (r=0.493, p<0.001), suggesting a mechanism for maintaining immunosuppressive regulatory T-cell populations.

How do genetic alterations in tumor cells correlate with LAG-3/FGL1 expression patterns?

Distinct genetic alteration patterns correlate with different LAG-3/FGL1 expression subtypes:

• RB1 alterations (potential targets for CDK4/6 inhibition) show highest frequency in the LAG-3 high FGL1 low subgroup, followed by LAG-3 low FGL1 high and LAG-3 low FGL1 high subgroups (p=0.012)

• FGFR3 variations (targets for erdafitinib) are associated with LAG-3-low groups regardless of FGL1 expression level (p<0.001)

These genetic associations suggest potential combination therapy opportunities, integrating targeted therapies with immunotherapies based on LAG-3/FGL1 expression profiles.

How does the temporal expression of FGL1 change during disease progression?

FGL1 expression demonstrates dynamic changes during disease progression that contradict some previous reports. In metabolic liver disease models, Fgl1 mRNA expression is initially induced but subsequently decreases significantly during disease progression. This biphasic expression pattern has important implications:

• Early induction may represent a compensatory response

• Later suppression could contribute to disease progression

• Timing of therapeutic interventions targeting FGL1 may be crucial for efficacy

These temporal dynamics suggest that longitudinal monitoring of FGL1 expression could provide valuable prognostic information in both cancer and metabolic disorders.

How might targeting the LAG-3/FGL1 pathway enhance cancer immunotherapy outcomes?

The LAG-3/FGL1 pathway represents a promising target for enhancing immunotherapy efficacy, particularly in patients resistant to PD-(L)1 blockade. Research suggests several strategic approaches:

• LAG-3/FGL1 blockade may reverse immunosuppressive contextures, particularly in LAG-3 high FGL1 high tumors

• Combination therapies targeting both LAG-3/FGL1 and PD-(L)1 pathways could provide synergistic benefits

• Patient stratification based on LAG-3/FGL1 expression subtypes may optimize treatment selection

Given that LAG-3 expression and high FGL1 coexpression are important predictive factors of adverse oncological outcomes, therapeutic interventions targeting this pathway warrant further mechanistic and clinical studies.

What is the relationship between FGL1 and metabolic dysfunction in the liver?

Studies in liver-specific FGL1 knockout (Fgl1LKO) mice have revealed important connections between FGL1 and metabolic dysfunction:

• Fgl1LKO mice display increased body weight compared to wild-type littermates

• Under western diet conditions, Fgl1LKO mice exhibit increased liver damage

• Elevated AST, ALT, and triglyceride levels suggest enhanced sensitivity to diet-induced damage

• FGL1 expression patterns change during metabolic disease progression in both mice and humans

These findings indicate that FGL1 plays a protective role against metabolic liver injury, with important implications for conditions like metabolic dysfunction-associated steatohepatitis (MASH) and hepatocellular carcinoma (HCC).