Elicit: Adalimumab and Inflammatory Pathways

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Adalimumab and Inflammatory Pathways

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May 5, 2026

Adalimumab inflammatory signaling pathways

Adalimumab modulates NF-κB, JAK/STAT, TNFα-TGFβ, Notch-1, IL-17, and IL-12/23 signaling pathways through direct TNF-α blockade, with pathway-specific effects varying by cell type, disease context, and treatment duration, mediated by coordinated changes in gene expression, protein levels, and microRNA regulation.

Abstract

Adalimumab modulates multiple interconnected inflammatory signaling pathways through direct TNF-α blockade and subsequent downstream effects. In keratinocytes, adalimumab primarily targets NF-κB signaling by downregulating IKBKB, IRAK1, TRAF2, MAP3K7, and TNFAIP3, with IKBKB functioning as a central hub in protein-protein interaction networks. In T cells, the dominant mechanism involves JAK/STAT pathway modulation, with adalimumab increasing STAT6 phosphorylation and restoring STAT4 activation to healthy levels, while disrupting Th1, Th17, and Th22 pathways in psoriasis patients. Adalimumab also affects the TNFα-TGFβ signaling axis differentially depending on disease context, effectively decreasing downstream inflammation in extended-to-be juvenile idiopathic arthritis synoviocytes but showing paradoxical increases in persistent disease. A novel mechanism was identified in inflammatory bowel disease involving Notch-1, which binds directly to TNFα and mediates adalimumab’s effects on T cell cycling but not apoptosis. MicroRNAs including miR-1297, miR-30a, miR-95-5p, miR-125b, and miR-4329 emerged as important regulators that fine-tune pathway responses, with temporal dynamics showing initial broad transcriptional changes followed by progressive miRNA restriction.

These pathway modulations translate into reduced inflammatory mediator production (CRP, TNF, IL-6, GlycA) and clinical improvements in psoriasis and rheumatoid arthritis, though adverse effects on HDL metabolism occurred at 52 weeks. The heterogeneous findings across studies reflect cell type-specific inflammatory network architecture rather than contradictory results: keratinocytes rely on NF-κB signaling, T cells use JAK/STAT for differentiation, and synoviocytes employ the TNFα-TGFβ axis. Context-dependent responses suggest adalimumab is most effective when TNFα drives downstream inflammatory cascades, with limited efficacy in contexts where alternative pathways predominate or disease has progressed to TNFα-independent inflammation.

Methods

We analyzed 10 sources from an initial pool of 200, using 8 screening criteria. Each paper was reviewed for 7 key aspects that mattered most to the research question. More on methods

Records from Elicit search

n = 200

Papers screened using: Inflammatory Pathway Focus, Mechanistic Outcomes, Adalimumab Study Population, Study System Type, Pathway Analysis Inclusion, Adalimumab-Specific Data, Single Intervention Analysis, Publication Type

n = 200

Papers screened out

n = 190

Papers included for extraction

n = 10

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Paper search

We performed a semantic search across over 138 million academic papers from the Elicit search engine, which includes all of Semantic Scholar and OpenAlex.

We ran this query: “Adalimumab inflammatory signaling pathways”

The search returned 200 total results from Elicit.

We retrieved 200 papers most relevant to the query for screening.

Screening

We screened in sources based on their abstracts that met these criteria:

We considered all screening questions together and made a holistic judgement about whether to screen in each paper.

Data extraction

We asked a large language model to extract each data column below from each paper. We gave the model the extraction instructions shown below for each column.

Extract the experimental context for studying adalimumab effects on inflammatory signaling pathways, including:

Extract all inflammatory signaling pathways investigated in relation to adalimumab treatment, including:

Extract adalimumab treatment parameters used to study inflammatory pathway effects, including:

Extract how adalimumab affected inflammatory signaling pathways, including:

Extract the molecular mechanisms by which adalimumab modulates inflammatory pathways, including:

Extract the experimental methods used to assess inflammatory pathway changes with adalimumab, including:

Extract the downstream functional consequences of adalimumab-induced inflammatory pathway changes, including:

Results

Characteristics of Included Studies

The included studies investigated adalimumab effects on inflammatory signaling pathways across diverse experimental contexts, ranging from in vitro cell culture systems to clinical trials in patients with inflammatory diseases.

Study

Full text retrieved?

Experimental context

Cell type/tissue

Disease model

Inflammatory stimulus

N. Mehta et al., 2018

Yes

Randomized controlled trial

Patient samples

Psoriasis (moderate-to-severe)

Adalimumab (blocks TNF-α)

B. Grabarek et al., 2019

No

Cell culture

Normal human dermal fibroblasts

Psoriasis

None mentioned

B. Grabarek et al., 2018

No

Cell culture

Normal human dermal fibroblasts

None (healthy cells)

Adalimumab (8 µg/ml)

Paulina Buda et al., 2023

Yes

Cell culture

Human keratinocytes (HaCaT)

Psoriasis

Lipopolysaccharide A (LPS)

Aleksandra Plata-Babula et al., 2025

Yes

Cell culture

Immortalized keratinocytes (HaCaT)

Psoriasis

Lipopolysaccharide (LPS)

Megan M. Simonds et al., 2023

Yes

Ex vivo cell culture

Fibroblast-like synoviocytes

Juvenile idiopathic arthritis

Adalimumab (TNFα inhibitor)

Iwona Adwent et al., 2020

No

Cell culture

Normal human fibroblasts

General fibroblast response

Lipopolysaccharide (LPS)

N. Aerts et al., 2010

No

Patient samples

CD4+ T cells (PBMCs)

Rheumatoid arthritis

Anti-CD3/anti-CD28, IL-4, IL-12

L. Werner et al., 2011

No

Patient samples or ex vivo tissue

T cells

Inflammatory bowel disease

TNFα

Li Luan et al., 2015

No

Patient samples

Th1, Th17, Th22 cells (blood)

Psoriasis (moderate-to-severe)

None mentioned

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Treatment parameters varied across studies. In vitro studies typically used adalimumab concentrations of 8 µg/ml or 10 µg/ml for durations of 2, 8, and 24 hours. Clinical trials administered adalimumab subcutaneously with an initial dose of 80 mg followed by 40 mg every other week for 12 weeks, with one study extending treatment to 52 weeks. Several in vitro studies employed LPS pretreatment at 1 µg/ml for 8 hours before adalimumab addition.

Inflammatory Pathways Modulated by Adalimumab

NF-κB Signaling Pathway

The NF-κB pathway emerged as a central target of adalimumab modulation in keratinocytes. Adalimumab reversed LPS-induced upregulation of multiple NF-κB-associated genes, including IKBKB, IRAK1, TRAF2, MAP3K7, and TNFAIP3. STRING analysis identified IKBKB as a central hub in the protein-protein interaction network, coordinating immune and apoptotic signals. This downregulation occurred consistently across multiple timepoints (2, 8, and 24 hours), with early suppression of certain genes and broader inhibition at later timepoints. The NF-κB pathway also showed crosstalk with MAPK and JAK/STAT pathways, and participates in the TNF-α/IL-23/IL-17 axis that is central to psoriatic inflammation.

Gene ontology enrichment highlighted IκB kinase/NF-κB, TNF-mediated, and Toll-like receptor signaling pathways as primary targets. Adalimumab’s effects on NF-κB signaling were validated at both mRNA and protein levels, with marked reductions in protein concentrations following treatment. The IL-17 signaling pathway, which activates NF-κB and MAPK cascades, also showed significant modulation, with adalimumab affecting chemokine and cytokine signaling pathways most strongly.

JAK/STAT Signaling Pathway

JAK/STAT pathway modulation occurred across multiple experimental contexts. In normal human dermal fibroblasts, adalimumab affected 18 of 37 JAK/STAT-associated mRNAs, with time-dependent changes in regulatory microRNAs (20 miRNAs at 2 hours, 9 at 8 hours, and 3 at 24 hours). Specific pathway components showed distinct responses: in rheumatoid arthritis patients, adalimumab increased Th2-associated STAT6 phosphorylation in both freshly isolated and stimulated CD4+ T cells, while restoring Th1-associated STAT4 phosphorylation to levels observed in healthy individuals.

In LPS-stimulated keratinocytes, adalimumab’s effects on the IL-12/23-dependent JAK/STAT pathway were particularly notable. The treatment silenced SOCS3 and IL-6 expression while causing overexpression of STAT1, STAT3, STAT5, JAK3, and IL-6R. Strong regulatory connections were identified between JAK3 and hsa-miR-373-5p (target score 96), and between SOCS3/STAT5 and hsa-miR-1827 (target score 96). These changes were consistent regardless of exposure time, indicating sustained pathway modulation.

In fibroblasts exposed to LPS, adalimumab caused silencing of TNF-α, IFN-γ, IL-17, IL12A, IL12B, and IL23A expression, affecting genes dependent on IL-12 receptor interactions. The effects on TNF-α and IFN-γ were most pronounced, with lesser modulation of IL-17.

TNFα-TGFβ Signaling Axis

In juvenile idiopathic arthritis synoviocytes, adalimumab demonstrated differential effects on persistent versus extended-to-be (ETB) fibroblast-like synoviocytes. After 24 hours of treatment, persistent FLS showed significant elevation of TNFα (FC=1.2, p=0.001), TGFβ (FC=1.5, p=0.001), lymphotoxin alpha (FC=4.3, p=0.015), sTNFRI (FC=5.1, p=0.008), and sTNFRII (FC=3.8, p=0.025). In contrast, ETB FLS exhibited a different pattern, with TNFα slightly elevated (FC=1.04, p=0.023) but TGFβ significantly decreased (FC=1.03, p=0.037). This suggests that adalimumab effectively decreases inflammation downstream of initial TNFα signaling in ETB cells, as TNFα signaling is upstream of TGFβ, with TGFβ acting as an intermediary for MAPK and NF-κB activation.

Notch-1 Signaling Pathway

In inflammatory bowel disease, adalimumab revealed a novel mechanism involving Notch-1 signaling. Notch-1 mucosal expression increased in response to anti-TNFα treatment, and Notch-1 was found to bind directly to TNFα. Functionally, Notch-1 mediated the inhibitory effects of adalimumab on T cell cycling but not apoptosis, indicating pathway-specific regulation. Notch-1 inhibition prevented anti-TNFα-induced T cell cycle arrest while apoptosis induction remained intact. This demonstrates crosstalk between Notch-1 and TNFα pathways, with Notch-1 function being regulated by TNFα inhibitors.

Th1/Th17/Th22 Pathways

Clinical studies in psoriasis patients demonstrated that adalimumab disrupts multiple T helper cell pathways simultaneously. At baseline, psoriasis patients showed elevated frequencies of Th1, Th17, and Th22 cells compared to healthy controls, along with higher expression of associated transcription factors (T-bet, RORγt, AHR) and cytokines (IFN-γ, IL-17, IL-22, IL-6, TNF-α). After 12 weeks of adalimumab therapy, significant declines occurred in cell frequencies, transcription factor expression, and cytokine levels, indicating broad immunomodulation across these pathways.

Molecular Mechanisms of Pathway Modulation

Direct and Indirect Effects

Adalimumab’s primary direct mechanism involves blocking TNF-α through antibody binding, preventing TNF-α from interacting with its receptors. This direct inhibition triggers cascading indirect effects on downstream pathways. In keratinocytes, adalimumab directly affected NF-κB pathway gene expression, while in fibroblasts, it directly influenced JAK/STAT pathway genes. The IL-17 signaling pathway showed both direct effects on gene expression and indirect effects through modulation of six signaling pathways and 19 biological processes.

Gene Expression and Protein Level Changes

Adalimumab induced coordinated changes at transcriptional and translational levels. In LPS-stimulated keratinocytes, adalimumab downregulated NF-κB-associated genes (IKBKB, IRAK1, TRAF2, MAP3K7, TNFAIP3) with concordant protein-level reductions. Gene ontology analysis revealed enrichment in immune regulation, apoptosis, and NF-κB signaling pathways. However, discrepancies between mRNA and protein levels occurred in some cases, suggesting post-translational regulation. For example, in keratinocytes exposed to LPS and adalimumab, JAK3, SOCS3, and STAT5 showed overexpression at the mRNA level but decreased protein concentrations.

MicroRNA Involvement

MicroRNAs emerged as important mediators of adalimumab’s effects. In NF-κB pathway modulation, anti-inflammatory miRNAs including miR-1297, miR-30a, miR-95-5p, and miR-125b showed reciprocal expression changes consistent with anti-inflammatory activity, while pro-survival miRNAs like miR-4329 and miR-20b-3p were downregulated. In the JAK/STAT pathway, adalimumab altered miRNA expression in a time-dependent manner (20 miRNAs at 2 hours, 9 at 8 hours, 3 at 24 hours), suggesting dynamic regulation. Specific miRNA-mRNA interactions were identified, including hsa-miR-373-5p regulating JAK3 and hsa-miR-1827 regulating SOCS3 and STAT5.

Protein-Protein Interactions

STRING analysis and experimental data revealed critical protein-protein interactions affected by adalimumab. IKBKB functioned as a central hub in the NF-κB pathway protein-protein interaction network. In IL-12/23 signaling, JAK3, SOCS3, and STAT5 showed altered expression affecting JAK/STAT signaling dynamics. Direct binding between Notch-1 and TNFα was demonstrated, providing a mechanism for crosstalk between these pathways.

Functional Consequences of Pathway Modulation

Inflammatory Mediator Production

Adalimumab reduced key inflammatory markers across multiple studies. In psoriasis patients, treatment decreased serum CRP, IL-6, TNF, and glycoprotein acetylation (GlycA) at both 12 and 52 weeks. The reduction in these systemic inflammatory markers was statistically significant compared to placebo. At the cellular level, adalimumab caused silencing of mRNA and protein expression for TNF-α, IFN-γ, IL-17, IL12A, IL12B, and IL23A in LPS-exposed fibroblasts. In keratinocytes, adalimumab silenced SOCS3 and IL-6 expression.

However, context-dependent responses occurred. In juvenile idiopathic arthritis synoviocytes, persistent FLS showed increased TNFα, TGFβ, lymphotoxin alpha, sTNFRI, and sTNFRII after adalimumab treatment, while extended-to-be FLS exhibited decreased TGFβ alongside reduced G-CSF, IFNγ, IL-10, M-CSF, MIP-1-alpha, and MIP-1-delta. In psoriasis patients, while TNF and GlycA decreased, IL-6 levels paradoxically increased at the end of the 52-week extension period.

Effects on Cell Function

Adalimumab influenced T cell function through multiple mechanisms. In inflammatory bowel disease, treatment induced T cell apoptosis, inhibited activation, reduced cytokine secretion, and restricted cell cycling. The cell cycle restriction was mediated by Notch-1, while apoptosis occurred through a Notch-1-independent mechanism. In rheumatoid arthritis, IFN-γ production increased in adalimumab-treated patients compared to untreated individuals, while IL-4, IL-6, and IL-12 production remained unchanged.

In psoriasis, adalimumab treatment resulted in significant declines in Th1, Th17, and Th22 cell frequencies, indicating effects on T cell differentiation or proliferation. Transcription factor levels (T-bet, RORγt, AHR) decreased concordantly.

Clinical and Phenotypic Improvements

Clinical improvements correlated with pathway modulation. In psoriasis, adalimumab improved skin disease and systemic inflammation markers, with GlycA improvement potentially explaining beneficial effects observed in observational studies. Treatment led to clinical improvement concurrent with disruption of Th1, Th17, and Th22 pathways. In keratinocytes, adalimumab promoted resolution of inflammation and restoration of epidermal homeostasis, with potential restoration of apoptotic balance and normalization of epidermal architecture.

Biomarker Changes

Several biomarkers emerged as indicators of pathway activity. Modulation of IL-6 levels served as a marker of response to TNF-α inhibitor treatment. Changes in miRNA expression profiles (including hsa-miR-373-5p and hsa-miR-1827, as well as miR-1297, miR-30a, miR-95-5p, miR-125b, and miR-4329) showed potential as biomarkers for treatment monitoring and patient stratification. Increases in Notch-1 mucosal expression reflected anti-TNFα treatment response.

Adverse Effects

Adalimumab demonstrated potential adverse effects on lipid metabolism. At 52 weeks, cholesterol efflux and high-density lipoprotein particle count (HDL-p) were reduced, with no beneficial impact on metabolic markers including insulin, adiponectin, and leptin. Phototherapy showed more favorable effects on HDL-p at 12 weeks compared to adalimumab. These findings suggest that while adalimumab reduces systemic inflammatory markers, it may have unfavorable effects on HDL function and lipid metabolism.

Synthesis

The heterogeneous findings across studies can be reconciled by considering experimental context, disease model, and pathway-specific effects.

Context-Dependent Pathway Responses

The divergent effects of adalimumab on inflammatory mediators in different cell types reflect fundamental differences in cellular inflammatory programs. In juvenile idiopathic arthritis synoviocytes, persistent FLS showed paradoxical increases in TNFα, TGFβ, and soluble TNF receptors after adalimumab treatment, while extended-to-be FLS demonstrated the expected anti-inflammatory response with decreased TGFβ. This differential response occurs because persistent and extended-to-be JIA represent distinct disease phenotypes at the molecular level. Patients were classified before disease progression, and the synoviocytes from extended-to-be patients were already primed for more aggressive inflammation even before clinical extension occurred. The fact that adalimumab effectively suppresses inflammation in extended-to-be FLS but not persistent FLS suggests it is most beneficial in contexts where TNFα signaling drives downstream inflammatory cascades. In persistent disease, alternative pathways may predominate, rendering TNFα blockade less effective or even triggering compensatory inflammatory responses.

Cell Type-Specific Mechanisms

The molecular mechanisms by which adalimumab modulates pathways vary substantially by cell type. In keratinocytes, adalimumab primarily targets NF-κB signaling, downregulating IKBKB, IRAK1, TRAF2, MAP3K7, and TNFAIP3. In T cells, the dominant mechanism involves JAK/STAT pathway modulation, with increased STAT6 phosphorylation and restored STAT4 activation. In synoviocytes, the TNFα-TGFβ axis predominates. This heterogeneity reflects the cell type-specific wiring of inflammatory networks: keratinocytes, as barrier cells, rely heavily on NF-κB for antimicrobial and inflammatory responses; T cells use JAK/STAT for differentiation and effector function; and mesenchymal cells like synoviocytes employ TGFβ for tissue remodeling. These are not contradictory findings but rather demonstrate that adalimumab’s anti-TNFα activity has downstream consequences tailored to each cell type’s unique signaling architecture.

Temporal Dynamics of Response

Time-dependent effects reveal that pathway modulation by adalimumab follows distinct kinetics for different regulatory mechanisms. Gene expression changes occurred within 2 hours, but microRNA profiles showed progressive restriction over time (20 differentially expressed miRNAs at 2 hours, 9 at 8 hours, 3 at 24 hours). This temporal pattern suggests an initial broad transcriptional response followed by selective stabilization of specific regulatory programs. Protein-level changes lagged behind mRNA changes, consistent with the time required for protein turnover. Clinical studies demonstrated sustained effects at 12 weeks and 52 weeks, but with emergence of secondary changes such as increased IL-6 at later timepoints. This late IL-6 increase likely represents a compensatory response to chronic TNFα blockade, as cells attempt to restore inflammatory capacity through alternative pathways.

Disease Model Considerations

The use of LPS to model inflammation in several in vitro studies provides mechanistic insights but has limitations for extrapolating to human disease. LPS activates Toll-like receptor 4, triggering acute inflammatory responses that may not fully recapitulate chronic inflammatory conditions like psoriasis or rheumatoid arthritis. Studies using primary cells from patients showed different response patterns than LPS-stimulated normal cells, suggesting that chronic disease primes cells for distinct inflammatory responses. For example, in rheumatoid arthritis patients, STAT4 phosphorylation was absent in untreated patients but restored by adalimumab, whereas in LPS-stimulated fibroblasts, adalimumab simply suppressed LPS-induced gene expression. This indicates that adalimumab may correct disease-specific signaling defects in patient cells beyond simple anti-inflammatory effects.

Pathway Crosstalk and Network Effects

The observation that adalimumab affects multiple pathways simultaneously (NF-κB, JAK/STAT, IL-17, IL-12/23, Notch-1) reflects extensive crosstalk in inflammatory networks rather than off-target effects. TNFα sits at a central node in inflammatory signaling, and its blockade reverberates through interconnected pathways. For instance, NF-κB interacts with MAPK and JAK/STAT pathways, and the TNF-α/IL-23/IL-17 axis involves NF-κB signaling. TGFβ acts as an intermediary for MAPK and NF-κB activation downstream of TNFα. Notch-1 binds directly to TNFα and mediates specific downstream effects on cell cycling. These interactions mean that inhibiting TNFα does not simply shut down one linear pathway but rather reconfigures a network of interconnected signaling nodes. The specific consequences depend on which alternative pathways are available in each cell type and disease context.

MicroRNA-Mediated Fine-Tuning

The involvement of microRNAs in adalimumab’s effects provides an additional layer of regulation that reconciles some apparent contradictions. For example, JAK3, SOCS3, and STAT5 showed overexpression at the mRNA level but decreased protein concentrations in keratinocytes. The identification of miR-373-5p and miR-1827 as regulators of these genes explains this discrepancy: adalimumab induces compensatory transcriptional upregulation, but microRNAs suppress translation, resulting in net protein reduction. This post-transcriptional regulation allows cells to modulate pathway activity without proportional gene expression changes and may represent a mechanism for fine-tuning inflammatory responses. The observation that miRNA changes show distinct temporal dynamics compared to mRNA changes suggests they serve as a secondary regulatory layer that refines initial transcriptional responses.

Implications for Clinical Use

The context-dependent effects have implications for predicting clinical response. Adalimumab appears most effective when TNFα drives downstream inflammatory cascades through pathways like TGFβ, NF-κB, and JAK/STAT. In conditions where alternative cytokine pathways predominate or where disease has progressed to TNFα-independent inflammation, response may be limited or paradoxical. The differential response in persistent versus extended-to-be JIA synoviocytes exemplifies this principle: early intervention in patients whose disease is still TNFα-dependent may be more effective than treatment after alternative pathways are established. The adverse effects on HDL metabolism suggest that pathway modulation has trade-offs, with anti-inflammatory benefits potentially offset by metabolic complications in some patients. Biomarkers including IL-6 levels, miRNA profiles, and Notch-1 expression may help identify patients most likely to benefit from adalimumab and monitor pathway-specific responses during treatment.

References

B. Grabarek, D. Wcisło-Dziadecka, K. Bednarek, C. Kruszniewska-Rajs, J. Gola\ (2019).Assessment of transcriptional activity genes associated with the IL‐17 signaling pathway in skin fibroblasts under the influence of adalimumab. Dermatologic Therapy

B. Grabarek, D. Wcisło-Dziadecka, J. Gola, C. Kruszniewska-Rajs, L. Brzezińska-Wcisło, and 2 more\ (2018).Changes in the Expression Profile of JAK/STAT Signaling Pathway Genes and Mirnas Regulating their Expression Under the Adalimumab Therapy. Current Pharmaceutical Biotechnology

Paulina Buda, P. Michalski, Oliwia Warmusz, A. MICHALSKA-BAŃKOWSKA, T. Sirek, and 5 more\ (2023).Influence of adalimumab on interleukin 12/23 signalling pathways in human keratinocytes treated with lipopolysaccharide A. Advances in Dermatology and Allergology

Aleksandra Plata-Babula, Wojciech Kulej, Paweł Ordon, Julia Gajdeczka, Martyna Stefaniak, and 4 more\ (2025).Modulation of Nuclear Factor Kappa B Signaling and microRNA Profiles by Adalimumab in LPS-Stimulated Keratinocytes. International Journal of Molecular Sciences

Megan M. Simonds, Samuel T. Freer, L. Al-Jaberi, A. Brescia\ (2023).Adalimumab Effectively Decreases Inflammation Downstream of TNFα Signaling in Synoviocytes from Extended Oligoarticular Juvenile Idiopathic Arthritis. Rheumatology and Therapy

Iwona Adwent, M. Schweizer, B. Grabarek, D. Boroń\ (2020).Effect of adalimumab on the expression profile of mRNA, and protein associated with JAK/STAT signaling pathway in fibroblast exposed to lipopolysaccharide. Dermatologic Therapy

N. Aerts, D. Ebo, C. Bridts, Mlt, W. Stevens, and 1 more\ (2010).T cell signal transducer and activator of transcription (STAT) 4 and 6 are affected by adalimumab therapy in rheumatoid arthritis. Clinical and Experimental Rheumatology

L. Werner, U. Berndt, D. Paclik, S. Danese, A. Schirbel, and 1 more\ (2011).TNFα inhibitors restrict T cell activation and cycling via Notch-1 signalling in inflammatory bowel disease. Gut

Li Luan, Shixin Han, Hua Wang, Xiaoming Liu\ (2015).Down-regulation of the Th1, Th17, and Th22 pathways due to anti-TNF-α treatment in psoriasis. International Immunopharmacology

N. Mehta, D. Shin, A. Joshi, A. Dey, A. Armstrong, and 20 more\ (2018).Effect of 2 Psoriasis Treatments on Vascular Inflammation and Novel Inflammatory Cardiovascular Biomarkers: A Randomized Placebo-Controlled Trial. Circulation Cardiovascular Imaging

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Modulation of Nuclear Factor Kappa B Signaling and microRNA Profiles by Adalimumab in LPS-Stimulated Keratinocytes

Aleksandra Plata-Babula, Wojciech Kulej, Paweł Ordon, Julia Gajdeczka, Martyna Stefaniak, Artur Chwalba, Piotr Gościniewicz, Tomasz Kulpok, B. Grabarek

International Journal of Molecular Sciences·

2025·

2 citations

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Study Context

- Cell type or tissue studied: Immortalized human keratinocytes (HaCaT cells) - Disease model or patient population: Psoriasis - Experimental system type: Cell culture - Inflammatory stimulus used: Lipopolysaccharide (LPS)

Inflammatory Pathways

- Specific pathway names: NF-κB, MAPK, JAK/STAT, TNF-α signaling, IL-23/IL-17 axis - Key pathway components: IKBKB, IRAK1, TRAF2, MAP3K7, TNFAIP3, TNF-α, IL-23, IL-17 - Upstream and downstream pathway elements: TNF-α activates NF-κB; NF-κB regulates inflammatory gene expression - Pathway crosstalk: NF-κB interacts with MAPK and JAK/STAT pathways; TNF-α/IL-23/IL-17 axis involves NF-κB

Adalimumab Treatment

- Concentration or dose used: 8 µg/mL - Treatment duration and timing: Added after 8 hours of LPS stimulation, observed at 2, 8, and 24 hours post-addition - Route of administration: Directly added to cell culture medium - Treatment schedule: Single dose - Pretreatment or co-treatment conditions: Cells were stimulated with LPS (1 µg/mL) for 8 hours before adalimumab addition

Pathway Modulation

- Direction of effect: Downregulation - Magnitude of effect: Marked reduction in protein concentrations; consistent inhibition of transcription - Specific genes, proteins, or pathway components affected: IKBKB, IRAK1, TRAF2, MAP3K7, TNFAIP3, CXCL2, BIRC2, BIRC3 - Time-dependent effects: Early suppression at 2 h; broader inhibition at 8 h and 24 h - Comparison to controls or baseline levels: Counteracts LPS-induced inflammatory changes

Molecular Mechanisms

- Direct vs. indirect pathway effects: Adalimumab directly modulates NF-κB signaling by reversing the upregulation of associated genes and proteins. - Protein-protein interactions affected: IKBKB is identified as a central hub in the PPI network, affecting interactions with IRAK1, TRAF2, MAP3K7, and TNFAIP3. - Gene expression changes (mRNA levels): Downregulation of NF-κB-associated genes such as IKBKB, IRAK1, TRAF2, MAP3K7, and TNFAIP3. - Protein level changes and post-translational modifications: Reduction in proteins like BCL2L1, CXCL2, MAP3K7, BIRC2, BIRC3, TNFAIP3, and XIAP. - microRNA or other regulatory molecule involvement: Anti-inflammatory miRNAs (miR-1297, miR-30a, miR-95-5p, miR-125b) are restored, while pro-survival miRNAs (miR-4329, miR-20b-3p) are downregulated. - Epigenetic modifications: Not mentioned in the paper.

Measurement Methods

- Gene expression methods: mRNA and miRNA microarrays, RT-qPCR - Protein analysis techniques: ELISA - Functional pathway readouts: Gene Ontology (GO) enrichment analysis - Validation approaches: Systems-level STRING analysis

Functional Outcomes

- Changes in cytokine or inflammatory mediator production: Adalimumab reduces the expression of NF-κB-associated genes and proteins, such as IKBKB, IRAK1, TRAF2, MAP3K7, and TNFAIP3, indicating a decrease in inflammatory mediator production. - Effects on cell proliferation, apoptosis, or differentiation: Adalimumab may restore apoptotic balance and contribute to normalization of epidermal architecture, suggesting effects on cell survival and differentiation. - Clinical or phenotypic improvements related to pathway modulation: Adalimumab promotes resolution of inflammation and restoration of epidermal homeostasis. - Biomarker changes that reflect pathway activity: Adalimumab modulates miRNAs, such as miR-1297, miR-30a, miR-95-5p, miR-125b, and miR-4329, which are potential biomarkers for treatment monitoring and patient stratification. - Any adverse effects related to pathway modulation: Not mentioned in the paper.

Psoriasis is a chronic inflammatory skin disease characterized by keratinocyte hyperactivation and dysregulated cytokine signaling, with nuclear factor kappa B (NF-κB), a master transcription factor that regulates immune and inflammatory gene expression, playing a central role. Adalimumab, a monoclonal antibody that inhibits tumor necrosis factor alpha (TNF-α), is widely used in psoriasis therapy, yet its molecular effects on NF-κB-associated genes and microRNAs (miRNAs) in keratinocytes remain insufficiently defined. In this study, immortalized human keratinocytes (HaCaT cells) were exposed to lipopolysaccharide (LPS) to induce inflammatory stress and treated with adalimumab for 2, 8, and 24 h. Transcriptome-wide profiling was performed using messenger RNA (mRNA) and miRNA microarrays, followed by validation with reverse transcription quantitative polymerase chain reaction (RT-qPCR) and enzyme-linked immunosorbent assay (ELISA). Bioinformatic analyses included prediction of miRNA–mRNA interactions, construction of protein–protein interaction (PPI) networks, and gene ontology (GO) enrichment. Adalimumab reversed LPS-induced upregulation of NF-κB-associated genes, including inhibitor of nuclear factor kappa-B kinase subunit beta (IKBKB), interleukin-1 receptor-associated kinase 1 (IRAK1), TNF receptor-associated factor 2 (TRAF2), mitogen-activated protein kinase kinase kinase 7 (MAP3K7), and TNF alpha-induced protein 3 (TNFAIP3), with concordant changes observed at the protein level. Several regulatory miRNAs, notably miR-1297, miR-30a, miR-95-5p, miR-125b, and miR-4329, showed reciprocal expression changes consistent with anti-inflammatory activity. STRING analysis identified IKBKB as a central hub in the PPI network, while GO enrichment highlighted immune regulation, apoptosis, and NF-κB signaling. These findings demonstrate that adalimumab modulates NF-κB activity in keratinocytes through coordinated regulation of gene, protein, and miRNA expression, providing mechanistic insight into TNF-α blockade in psoriasis.

1.Introduction

Psoriasis is a common, chronic, immune-mediated inflammatory skin disorder that affects approximately 2-3% of the global population and imposes a substantial physical, psy-chological, and socioeconomic burden [1]. It is clinically characterized by well-demarcated, erythematous plaques with silvery scales, most frequently affecting the scalp, elbows, knees, and lower back [2, 3] . Although psoriasis primarily manifests in the skin, it is now recognized as a systemic disease associated with a broad spectrum of comorbidities, including psoriatic arthritis, metabolic syndrome, cardiovascular disorders, and mental health complications such as depression and suicidality [4].

Over the past two decades, therapeutic strategies for psoriasis have evolved from nonspecific immunosuppression to targeted molecular therapies [5,6]. Traditional approachesincluding topical corticosteroids, vitamin D analogs, phototherapy, and systemic agents such as methotrexate or cyclosporine-provide varying degrees of symptom control. The advent of biologic therapies, monoclonal antibodies specifically designed to neutralize proinflammatory cytokines, has revolutionized disease management [3, 7]. Among these, tumor necrosis factor alpha (TNF-α) inhibitors (adalimumab, etanercept, infliximab) and newer agents targeting interleukin (IL) (IL-12/23) (ustekinumab), IL-17 (secukinumab, ixekizumab), and IL-23 (guselkumab, risankizumab) have demonstrated remarkable clinical efficacy and safety in moderate-to-severe plaque psoriasis [8]. Despite these advances, longterm disease control remains challenging due to primary non-responsiveness, secondary resistance, and relapse after treatment discontinuation [1,9,10].

Adalimumab, a monoclonal antibody against TNF-α, is highly effective in moderateto-severe plaque psoriasis and psoriatic arthritis, improving Psoriasis Area and Severity Index (PASI) scores and patient quality of life [11]. By neutralizing TNF-α, it downregulates key inflammatory cascades, including nuclear factor kappa B (NF-κB), mitogen-activated protein kinases (MAPK), and Janus kinase/signal transducer and activator of transcription (JAK/STAT) signaling. However, the precise molecular effects of adalimumab on keratinocyte signaling under inflammatory stress remain incompletely defined [12][13][14].

At the molecular level, NF-κB acts as a central hub integrating upstream cytokine signals with downstream transcriptional responses in psoriasis [15,16]. NF-κB comprises transcription factors RelA (p65), RelB, c-Rel, p50, and p52, which are normally sequestered in the cytoplasm by inhibitors of κB (IκBs). Upon stimulation by TNF-α, IL-1β, or microbial products such as lipopolysaccharide (LPS), the IκB kinase (IKK) complex phosphorylates IκBα, leading to its proteasomal degradation. This releases NF-κB dimers to translocate into the nucleus, where they activate genes involved in inflammation, immune cell recruitment, angiogenesis, and cell survival [17,18].

In psoriatic skin, NF-κB signaling is constitutively activated in both keratinocytes and infiltrating immune cells, driving sustained expression of cytokines (e.g., IL-6, IL-8), chemokines (e.g., C-C motif chemokine ligand 20; CCL20), and antimicrobial peptides (e.g., psoriasin (S100A7) and human β-defensin-2 (hBD-2)) [19][20][21][22]. Moreover, NF-κB synergizes with Signal Transducer and Activator of Transcription 3 (STAT3), Activator Protein 1 (AP-1), and MAPK pathways, amplifying the inflammatory loop characteristic of chronic disease [19,20].

NF-κB also functions as both a driver and effector within the TNF-α/IL-23/IL-17 axis, the dominant pathogenic pathway in plaque psoriasis [23,24]. TNF-α activates NF-κB in keratinocytes and promotes IL-23 production in dendritic cells, sustaining Th17 differentiation and IL-17 secretion. IL-17A and TNF-α co-activate NF-κB, further enhancing keratinocyte inflammatory responses and fueling disease progression [25][26][27][28]. The genetic landscape of psoriasis reinforces the importance of NF-κB. Susceptibility genes such as NFKBIA (IκBα), TNFAIP3 (A20), TNIP1, and CARD14 regulate NF-κB activation or inhibition [29]. Gain-of-function mutations in Caspase Recruitment Domain Family Member 14 (CARD14) result in constitutive NF-κB activity in keratinocytes and psoriasis-like inflammation in murine models [30, 31] . Parallel to this, microRNAs (miRNAs)-short, non-coding RNAs that regulate gene expression post-transcriptionally-are increasingly recognized as key regulators of cutaneous homeostasis and immune balance in psoriasis [32]. Aberrant miRNA profiles have been reported in psoriatic lesional skin, serum, and immune cell subsets [33] [34][35][36]. Several miRNAs modulate NF-κB activity by targeting upstream or downstream effectors, including IKKβ, IκBα, and p65 [37][38][39]. Integration of miRNA biology into psoriasis pathogenesis provides novel opportunities for biomarker discovery and therapeutic targeting [40][41][42][43]. However, the effect of TNF-α inhibition on the keratinocyte gene-miRNA axis remains poorly understood.

Keratinocytes, once considered passive bystanders, are now recognized as active participants in psoriatic inflammation. In response to TNF-α, IL-17A, and pathogenassociated molecular patterns (PAMPs) such as lipopolysaccharide (LPS), a Toll-like receptor 4 (TLR4) agonist, they produce pro-inflammatory cytokines, chemokines, and antimicrobial peptides, thereby amplifying local immune responses [21,[44][45][46].

In this study, LPS was used to induce an inflammatory environment in keratinocytes in order to mimic the cellular stress conditions characteristic of psoriatic skin [46,47]. LPS is a well-defined TLR4 agonist that activates innate immune pathways [48], leading to the rapid induction of pro-inflammatory cytokines and chemokines such as TNF-α, IL-1β, IL-6, and C-X-C motif chemokine ligand (CXCL8), as well as activation of the NF-κB and MAPK signaling cascades [21,[44][45][46]. These molecular events closely parallel those observed in psoriatic epidermis, where keratinocytes exhibit enhanced responsiveness to inflammatory stimuli and sustained NF-κB activation [21]. Clinically, elevated expression of TLR4 has been detected in psoriatic lesions and in the peripheral blood of affected patients, suggesting that microbial components and endotoxins may amplify local inflammation and contribute to disease exacerbation [49,50]. Therefore, the use of LPS in vitro provides a reproducible and controllable model for studying keratinocyte-driven inflammation [51] and allows for precise evaluation of how adalimumab [52][53][54] modulates NF-κB-dependent transcriptional and post-transcriptional responses under conditions of innate immune activation [47]. This approach facilitates the dissection of molecular mechanisms underlying TNF-α blockade in epithelial cells, which are key contributors to the inflammatory milieu in psoriasis [21].

Although the NF-κB signaling pathway has been extensively characterized in keratinocytes, most studies have focused on canonical activation mechanisms or short-term inflammatory responses. However, the temporal dynamics and gene-miRNA interactions underlying NF-κB modulation during prolonged inflammatory stimulation remain poorly understood. Our study provides a comprehensive temporal analysis of NF-κB-related transcriptional and post-transcriptional responses in HaCaT cells exposed to LPS and adalimumab, thereby expanding the molecular landscape of NF-κB regulation in epidermal inflammation.

Therefore, in this study we aimed to investigate how adalimumab modulates the expression of NF-κB pathway-associated genes and their regulatory miRNAs in an LPSstimulated human immortalized keratinocyte (HaCaT) model.

2.1.Cytotoxicity Results

At the concentrations selected for the expression analyses-LPS 1 µg/mL and adalimumab 8 µg/mL-cell viability remained above 90%, indicating no significant cytotoxicity (p > 0.05, one-way analysis of variance ANOVA). Only the supratherapeutic adalimumab concentration (80 µg/mL) reduced viability to ~41% of control (p < 0.05, Tukey post hoc).

Based on these results, keratinocytes were stimulated with LPS (1 µg/mL) for 8 h to model an inflammatory state [55], thereafter, adalimumab (8 µg/mL; Humira ® , AbbVie, North Chicago, IL, USA)-a concentration corresponding to therapeutic plasma levels in psoriasis patients [55,56]-was added for 2, 8, or 24 h. Untreated cells served as negative controls, whereas cells exposed only to LPS were used as inflammatory controls [55,56].

2.2.Transcriptomic Profiling Reveals LPS-Induced NF-κB Activation and Its Attenuation by Adalimumab

Genome-wide microarray analysis revealed extensive transcriptional reprogramming of NF-κB-related genes in HaCaT keratinocytes following LPS stimulation and subsequent adalimumab treatment. Differentially expressed genes (DEGs) were defined by a fold change (|FC|) ≥ 2.0 and adjusted p < 0.05.

As expected, LPS stimulation strongly activated the NF-κB pathway compared with untreated controls (C), resulting in the upregulation of canonical signaling mediators such as IKBKB, IRAK1, TRAF2, SYK, MAP3K7, TNF, and CXCL2. In addition, several genes associated with anti-apoptotic activity and feedback inhibition of inflammation-including BIRC2, BIRC3, XIAP, and TNFAIP3-were significantly elevated, reflecting a robust proinflammatory and survival response.

Adalimumab markedly counteracted these LPS-induced changes at all examined time points (2 h, 8 h, and 24 h post-treatment), indicating consistent inhibition of NF-κB-dependent transcription. Specifically, 14 DEGs were identified in the H 2 vs. LPS comparison, 14 DEGs in H 8 vs. LPS, and 10 DEGs in H 24 vs. LPS (p < 0.05). Early suppression (H 2 ) was most pronounced for TNFAIP3, BCL2L1, TRAF2, and MAP3K7, whereas prolonged exposure (H 8 and H 24 ) led to broader inhibition encompassing CXCL2, BIRC2, and BIRC3. Downregulation of signal transducers such as SYK, TAB1, and TAB2 further confirmed that adalimumab attenuates NF-κB activation at multiple regulatory levels and time points.

The Venn diagram (Figure 1 ) illustrates the overlap and time-specific distribution of NF-κB-related DEGs following adalimumab treatment. The strongest intersection among all treatment times was observed for TRAF6, TAB1, and TNF, suggesting persistent modulation of these central NF-κB components. The heatmap (Figure 2 ) provides a global visualization of transcriptional changes across all experimental conditions. The complete list of DEGs for each time point is provided in Supplementary Table S1 , while the subset of key transcripts validated by RT-qPCR and ELISA is summarized in Table 1 .

A complete list of all differentially expressed genes identified by microarray analysis is provided in Supplementary Table S1 . In the main manuscript, Table 1 presents only those genes that were further validated at the mRNA level by RT-qPCR and whose protein products were quantified using ELISA, reflecting the core molecular targets analyzed in this study.

Gene abbreviations: CXCL2, C-X-C Motif Chemokine Ligand 2; MAP3K7, Mitogen-Activated Protein Kinase Kinase Kinase 7; BIRC2, Baculoviral IAP Repeat Containing 2; BIRC3, Baculoviral IAP Repeat Containing 3; TNFAIP3, Tumor Necrosis Factor Alpha-Induced Protein 3; XIAP, X-Linked Inhibitor of Apoptosis Protein. H 2 /H 8 /H 24 vs. LPS (adalimumab effects). Data are presented as mean values from three biological replicates (n = 3). Abbreviations: C, untreated control; LPS, lipopolysaccharide-stimulated cells; H 2 , H 8 , H 24 , adalimumab treatment for 2, 8, and 24 h, respectively. Gene abbreviations: IKBKB, Inhibitor of Nuclear Factor Kappa B Kinase Subunit Beta; TRAF2, TNF Receptor Associated Factor 2; IRAK1, Interleukin-1 Receptor-Associated Kinase 1; SYK, Spleen Tyrosine Kinase; PLAU, Plasminogen Activator, Urokinase; TAB2, TGF-Beta Activated Kinase 1 Binding Protein 2; MAPK14, Mitogen-Activated Protein Kinase 14 (p38α); PLCG1, Phospholipase C Gamma 1; PLCG2, Phospholipase C Gamma 2; BTK, Bruton's Tyrosine Kinase; TRAF6, TNF Receptor Associated Factor 6; TAB1, TGF-Beta Activated Kinase 1 Binding Protein 1; TNF, Tumor Necrosis Factor; BCL2L1, BCL2 Like 1 (Bcl-xL); CXCL2, C-X-C Motif Chemokine Ligand 2; MAP3K7, Mitogen-Activated Protein Kinase Kinase Kinase 7 (TAK1); BIRC2, Baculoviral IAP Repeat Containing 2 (cIAP1); BIRC3, Baculoviral IAP Repeat Containing 3 (cIAP2); TNFAIP3, Tumor Necrosis Factor Alpha-Induced Protein 3 (A20); XIAP, X-Linked Inhibitor of Apoptosis Protein.

2.3.Validation of NF-κB mRNA Expression Using RT-qPCR

To validate the microarray data, RT-qPCR was performed for seven representative NF-κB-related genes: TNFAIP3, BCL2L1, CXCL2, MAP3K7, BIRC2, BIRC3, and XIAP.

Consistent with the transcriptomic findings, LPS stimulation significantly increased the expression of all analyzed genes compared with untreated controls, confirming activation of the NF-κB pathway. Subsequent adalimumab treatment led to a pronounced and timedependent downregulation of these transcripts relative to LPS-treated cells.

The strongest inhibitory effects were observed for TNFAIP3 and BCL2L1 at 2 h and 8 h, whereas CXCL2 and MAP3K7 exhibited gradual reductions across all time points. BIRC2, BIRC3, and XIAP followed similar patterns of suppression, closely mirroring the microarray results. Although fold-change magnitudes differed between platforms, the direction of expression changes was consistent (Figure 3 ). These results confirm that adalimumab effectively reverses LPS-induced NF-κB activation at the transcriptional level. . LPS stimulation significantly increased transcript levels compared with control, whereas adalimumab treatment reduced expression relative to LPS. Data represent mean ± SEM from three independent biological replicates (n = 3). Statistical analysis: one-way ANOVA followed by Scheffe's post hoc test. Asterisks indicate differential regulation relative to the reference condition: p < 0.05 vs. control (C) for LPS, and p < 0.05 vs. LPS for H 2 , H 8 , and H 24 . Abbreviations: C, untreated control; LPS, lipopolysaccharide-stimulated cells; H 2 , H 8 , H 24 , adalimumab treatment for 2, 8, and 24 h, respectively. Gene abbreviations: BCL2L1, BCL2 Like 1; CXCL2, C-X-C Motif Chemokine Ligand 2; MAP3K7, Mitogen-Activated Protein Kinase Kinase Kinase 7; BIRC2, Baculoviral IAP Repeat Containing 2; BIRC3, Baculoviral IAP Repeat Containing 3; TNFAIP3, Tumor Necrosis Factor Alpha-Induced Protein 3; XIAP, X-Linked Inhibitor of Apoptosis Protein.

2.4.Profiling of miRNA Expression Levels

Microarray profiling identified several microRNAs predicted to target NF-κBassociated transcripts affected by adalimumab. Differential expression was defined by |fold change| ≥ 2 and p < 0.05 across all experimental groups.

LPS stimulation downregulated miRNAs predicted to inhibit inflammatory mediators, including miR-1297 and miR-30a (targeting MAP3K7), miR-95-5p (targeting CXCL2), and miR-125b (targeting TNFAIP3). Conversely, miR-4329 (targeting XIAP) and miR-20b-3p (targeting BIRC3) were upregulated, indicating enhanced pro-survival signaling.

Adalimumab treatment reversed these trends in a time-dependent manner. Antiinflammatory miRNAs (miR-1297, miR-30a, miR-95-5p, miR-125b) were significantly restored, whereas pro-survival miRNAs (miR-4329, miR-20b-3p) were downregulated compared with LPS. These reciprocal expression patterns suggest regulatory interactions consistent with the mRNA profiles and imply that adalimumab exerts post-transcriptional control over NF-κB signaling through miRNA modulation (Table 2 ). ELISA quantification confirmed that LPS stimulation significantly increased protein levels of NF-κB and MAPK pathway components, including BCL2L1/Bcl-xL, CXCL2, MAP3K7, BIRC2, BIRC3, TNFAIP3/A20, and XIAP.

Adalimumab administration led to a marked reduction in the concentration of all these proteins, consistent with transcript-level findings. For instance, BCL2L1 levels declined from 87.12 ± 19 ng/mL (LPS) to approximately 17-18 ng/mL after treatment, returning close to baseline. CXCL2 and MAP3K7 were also significantly reduced, while BIRC2 and BIRC3 decreased more than twofold compared with LPS-treated cells. TNFAIP3 and XIAP followed a similar trend, though XIAP remained slightly above control levels (Table 3 ).

Together, these data confirm that adalimumab mitigates NF-κB activation in keratinocytes by suppressing both transcriptional and translational outputs of key pathway mediators. 2 . Protein abbreviations: IKBKB, Inhibitor of Nuclear Factor Kappa B Kinase Subunit Beta; TRAF2, TNF Receptor Associated Factor 2; IRAK1, Interleukin-1 Receptor-Associated Kinase 1; SYK, Spleen Tyrosine Kinase; PLAU, Plasminogen Activator, Urokinase; TAB2, TGF-Beta Activated Kinase 1 (MAP3K7) Binding Protein 2; MAPK14, Mitogen-Activated Protein Kinase 14; PLCG1, Phospholipase C Gamma 1; PLCG2, Phospholipase C Gamma 2; BTK, Bruton's Tyrosine Kinase; TRAF6, TNF Receptor Associated Factor 6; TAB1, TGF-Beta Activated Kinase 1 (MAP3K7) Binding Protein 1; TNF, Tumor Necrosis Factor; BCL2L1, BCL2 Like 1; CXCL2, C-X-C Motif Chemokine Ligand 2; MAP3K7, Mitogen-Activated Protein Kinase Kinase Kinase 7; BIRC2, Baculoviral IAP Repeat Containing 2; BIRC3, Baculoviral IAP Repeat Containing 3; TNFAIP3, Tumor Necrosis Factor Alpha-Induced Protein 3; XIAP, X-Linked Inhibitor of Apoptosis Protein.

Gene Ontology (GO:BP) enrichment of downregulated genes revealed significant associations with cytokine-mediated signaling, regulation of apoptosis, and innate immune responses (FDR < 0.05). The top 10 enriched biological processes are shown in Figure 5 , and the full list is provided in Appendix A (Table A1 ). These findings indicate that adalimumab exerts broad anti-inflammatory effects by targeting core NF-κB nodes and functionally linked processes. 2 . Differentially expressed genes were identified in LPS vs. untreated control (C), and their downregulation following adalimumab treatment (H 2 , H 8 , H 24 vs. LPS) was analyzed using the STRING enrichment tool (FDR < 0.05). Terms were grouped by semantic similarity (threshold = 0.8) and ranked by enrichment strength. Only the top 10 processes are shown; the complete list is provided in Table A1 .

To further characterize the biological relevance of the transcriptional changes, downregulated DEGs were subjected to Gene Ontology (GO:BP) enrichment analysis in STRING. The top enriched processes, summarized in Figure 5 , included cytokine-mediated signaling, regulation of apoptosis, and innate immune responses (FDR < 0.05). A complete list of enriched processes with corresponding genes is provided in Table A1 .

3.Discussion

The present study contributes novel insights into the NF-κB signaling network in HaCaT cells by integrating time-dependent transcriptomic, miRNA, and protein-level analyses. Unlike previous reports focusing on single endpoints or isolated cytokines, we identified coordinated changes in both NF-κB target genes and regulatory microRNAs following adalimumab exposure, revealing potential feedback mechanisms that modulate inflammation resolution. This integrative approach expands the NF-κB knowledge base for keratinocytes and provides a reference for future therapeutic studies targeting chronic cutaneous inflammation. Previous reports have established the central role of TNF-α in activating NF-κB signaling and sustaining psoriatic inflammation [11,23,24]; our findings extend this knowledge by revealing how TNF-α blockade reprograms keratinocyte transcriptional and post-transcriptional networks.

Consistent with earlier studies showing that TNF-α is a potent activator of NF-κB [21,57,58], we found that LPS stimulation in HaCaT keratinocytes led to significant upregulation of IKBKB, IRAK1, TRAF2, CXCL2, MAP3K7, BCL2L1, BIRC2, BIRC3, XIAP, and TNFAIP3. These genes are known to drive cytokine production, immune cell recruitment, and resistance to apoptosis-key elements in the pathogenesis of psoriatic inflammation [21,57,58]. Importantly, our data showed that adalimumab consistently downregulated these transcripts across all time points, supporting its broad anti-inflammatory action through inhibition of TNF-α-mediated signaling [59].

A closer examination of individual gene responses in our dataset further illustrates this effect. For example, we observed that BCL2L1 was markedly upregulated after LPS stimulation and subsequently reduced by adalimumab. Since BCL2L1 promotes cell survival by inhibiting apoptosis [60], this suggests that adalimumab may restore apoptotic balance and contribute to normalization of epidermal architecture, in agreement with previous reports [61,62].

Similarly, our experiments revealed that CXCL2 was strongly upregulated by LPS and suppressed by adalimumab at both mRNA and protein levels. This indicates inhibition of acute inflammatory signaling and attenuation of neutrophil recruitment-pathways previously linked to psoriatic lesion activity [63][64][65][66][67].

We also found that MAP3K7 (TAK1), a central kinase upstream of NF-κB and MAPK pathways [68], was significantly upregulated by LPS but downregulated by adalimumab. This highlights MAP3K7 inhibition as a potential mechanism by which TNF-α blockade disrupts inflammatory cascades, consistent with earlier mechanistic insights [69][70][71].

In addition, our results showed that apoptosis regulators BIRC2 and BIRC3 were induced by LPS and suppressed by adalimumab, supporting the concept that TNF-α inhibition corrects aberrant survival signaling in keratinocytes [72,73]. Likewise, TNFAIP3 (A20) was upregulated under inflammatory stress in our model, likely reflecting a compensatory feedback mechanism [74,75]. Similarly, TNFAIP3 (A20) is a well-established negative-feedback regulator of NF-κB signaling [76,77]. In our model, LPS robustly increased TNFAIP3, consistent with compensatory feedback to excessive IKK/NF-κB activity, whereas adalimumab reduced TNFAIP3 expression across time points. This pattern suggests diminished upstream inflammatory drive under TNF-α blockade, in line with prior observations [78,79]. Thus, lower A20 after adalimumab reflects reduced pathway stimulation rather than a pro-inflammatory effect.

Interestingly, we found that XIAP remained moderately elevated after adalimumab treatment despite a partial reduction from LPS-induced levels. This persistence may reflect residual protective signaling in keratinocytes, and further studies are warranted to clarify its role in treatment response [80] [81] [82].

Taken together, our data support the concept that adalimumab exerts dual effects in keratinocytes-downregulating proinflammatory cytokine networks and aberrant survival pathways-thereby promoting resolution of inflammation and restoration of epidermal homeostasis [52,[83] [84] [85][86].

In parallel with these transcriptomic and proteomic findings, we demonstrated that adalimumab modulates miRNA expression. These changes likely contribute to fine-tuning of inflammatory and apoptotic gene networks. Previous studies have linked miRNAs to NF-κB regulation in keratinocytes [57,[87][88][89], but our study adds novel evidence for specific miRNA-mRNA pairs influenced by adalimumab. Specifically, we observed that miR-1297 and miR-30a, both suppressed by LPS, were restored by adalimumab. These miRNAs are predicted to target MAP3K7, suggesting that their re-expression may attenuate TAK1-driven NF-κB and MAPK activation, consistent with earlier functional studies [90][91][92][93]. Similarly, our data showed that miR-95-5p was downregulated by LPS but increased with adalimumab, exhibiting an inverse relationship with CXCL2 expression-strongly supporting a functional miRNA-mRNA interaction [94].

We also identified reciprocal regulation of TNFAIP3 and miR-125b: while TNFAIP3 increased under LPS and decreased with adalimumab, miR-125b displayed the opposite trend. This aligns with previous reports describing miR-125b as a regulator of immune signaling [95], but our findings demonstrate its involvement specifically in keratinocyte responses to adalimumab [96][97][98][99].

Conversely, we found that miR-4329 was induced by LPS and suppressed after adalimumab treatment, consistent with its predicted regulation of XIAP [100].

Similarly, miR-20b-3p, which targets BIRC3, was upregulated by LPS and reduced by adalimumab [101,102]. These results support a model where adalimumab resets the miRNA landscape by enhancing anti-inflammatory and pro-apoptotic miRNAs, while reducing those that sustain chronic inflammation [57,[87][88][89].

GO enrichment analysis confirmed that the downregulated DEGs were enriched in classical inflammatory pathways, including IκB kinase/NF-κB, TNF-mediated, and Toll-like receptor signaling. No significantly enriched processes were detected among upregulated DEGs, indicating that the predominant effect of adalimumab in this model is suppression of central pro-inflammatory hubs. This selective pattern suggests that adalimumab does not act as a blanket suppressor but specifically reprograms keratinocyte signaling toward resolution of inflammation.

Systems-level STRING analysis supported this interpretation: our PPI network revealed a highly interconnected NF-κB module with IKBKB as a central hub, coordinating immune and apoptotic signals [103]. Functional enrichment analysis [104] identified key processes such as immune regulation, cellular response to LPS, and regulation of apoptosishallmarks of psoriatic pathology. Our data demonstrate that adalimumab disrupts this pathological circuitry modulating both inflammatory effectors and apoptosis regulators, thereby promoting a shift toward a homeostatic keratinocyte phenotype [52,[83] [84] [85][86]. Despite these encouraging findings, several limitations must be acknowledged. Most notably, our in vitro keratinocyte model does not capture the multicellular complexity of psoriatic skin, where dynamic interactions among keratinocytes, T cells, dendritic cells, and fibroblasts critically influence disease maintenance and therapeutic response. While our results provide valuable mechanistic insight at the keratinocyte level, further validation in ex vivo skin models, three-dimensional organotypic cultures, or patient-derived organoids is warranted to confirm translational relevance.

Moreover, although we identified several miRNA-mRNA correlations supporting post-transcriptional regulation of NF-κB signaling-such as luciferase reporter assays, miRNA mimic or inhibitor experiments, and loss-or gain-of-function studies-functional validation was not performed and will be necessary to establish direct causal interactions.

Finally, the STRING database was employed as a predictive tool to explore networks among NF-κB-related differentially expressed genes. While STRING provides a useful preliminary framework for mapping potential molecular relationships, its computational predictions should be experimentally verified. Future research should therefore incorporate biochemical assays such as co-immunoprecipitation (Co-IP) or pull-down assays using tagged fusion proteins (e.g., GST-tag, His-tag) to confirm the physical binding of key NF-κB regulators, including IKBKB, TRAF2, and MAP3K7. Combining these validation approaches with proteomic or phospho-proteomic analyses would strengthen the mechanistic interpretation of adalimumab-mediated NF-κB modulation in keratinocytes. In conclusion, our findings indicate that adalimumab exerts a two-pronged effect: suppression of NF-κB-driven inflammatory circuits and reinforcement of regulatory processes that preserve keratinocyte viability. This systems-level reprogramming may explain its sustained clinical efficacy in psoriasis and supports NF-κB-associated miRNAs as potential biomarkers of therapeutic response. Future studies in ex vivo skin models and longitudinal patient cohorts will be essential to validate these mechanisms and assess their translational relevance.

4.Materials and Methods

This section builds upon findings from our previous studies [53,55,56].

4.1.Study Design

This study investigated the modulatory effects of adalimumab on NF-κB-related signaling in HaCaT human keratinocytes under inflammatory stress induced by lipopolysaccharide (LPS). A multilevel approach combining transcriptomic (mRNA microarray), posttranscriptional (miRNA microarray), and protein (ELISA) analyses was used to characterize temporal changes at 2 h, 8 h, and 24 h following LPS and adalimumab exposure. Experimental procedures are summarized in Figure 1 .

4.2.Keratinocyte Cell Culture

HaCaT cells (AddexBio, San Diego, CA, USA) were cultured in Dulbecco's Modified Eagle Medium (DMEM; Gibco, Thermo Fisher Scientific, Waltham, MA, USA) supplemented with 10% fetal bovine serum (FBS; Gibco), 100 U/mL penicillin, and 100 µg/mL streptomycin (Sigma-Aldrich, St. Louis, MO, USA). Cells were maintained at 37 • C in a humidified atmosphere with 5% CO 2 .

For experiments, cells were seeded at 1 × 10 6 per well and allowed to reach 80% confluence. The inflammatory model was established using LPS from Escherichia coli (1 µg/mL; Sigma-Aldrich). Adalimumab (Humira ® , AbbVie, Chicago, IL, USA) was added at a final concentration of 8 µg/mL, consistent with therapeutic serum levels. Experimental groups were as follows: untreated control (C), LPS-stimulated (LPS), and LPS + adalimumab-treated at 2 h (H 2 ), 8 h (H 8 ), and 24 h (H 24 ).

Cytotoxicity was assessed in a preliminary experiment using the sulforhodamine B (SRB) assay (Sigma-Aldrich, Cat. No. 3520-42-1). HaCaT cells were treated with LPS (1, 2, or 10 µg/mL) or adalimumab (0.8, 8, or 80 µg/mL) for 24 h, and absorbance was measured at 490-530 nm. Viability was expressed as a percentage relative to untreated controls [56].

4.3.Total Ribonucleic Acid (RNA) Extraction

Total ribonucleic acid (RNA) was isolated from untreated HaCaT cells (control, C), LPS-stimulated cells (LPS), and LPS-primed cells subsequently treated with adalimumab for 2, 8, or 24 h (H 2 , H 8 , H 24 ). Extraction was performed using TRIzol reagent (Invitrogen Life Technologies, Carlsbad, CA, USA; Cat. No. 15596026) in accordance with the manufacturer's protocol. To improve RNA quality and remove residual contaminants, samples were further purified using the RNeasy Mini Kit (QIAGEN, Hilden, Germany; Cat. No. 74104) combined with on-column DNase I digestion (Thermo Fisher Scientific; Cat. No. 18047019) to eliminate genomic DNA. Purified RNA was eluted in RNase-free water to a final volume of 100 µL. Concentrations ranged between 80 and 150 ng/µL, and A260/A280 absorbance ratios exceeded 1.8 in all samples as assessed by NanoDrop spectrophotometry (Thermo Fisher Scientific, Waltham, MA, USA), confirming sufficient yield and purity for downstream analyses.

4.4.NF-κB Gene Expression Profiling via Oligonucleotide Microarrays

Global mRNA expression profiling was conducted to investigate transcriptional changes in NF-κB-related genes. HG-U133_A2 oligonucleotide microarrays (Affymetrix, Santa Clara, CA, USA) and the GeneChip™ 3 ′ IVT PLUS Reagent Kit (Affymetrix; Cat. No. 902416) were used according to the manufacturer's instructions. The NF-κB pathway gene set (hsa04064) was obtained from the Kyoto Encyclopedia of Genes and Genomes (KEGG; accessed 14 April 2021), yielding 105 pathway-associated transcripts [105] [106][107]. Samples were collected from untreated control cells (C), LPS-only cells (8 h), and adalimumabtreated groups after 8 h of LPS priming followed by 2, 8, or 24 h of adalimumab exposure (H 2 , H 8 , H 24 ). Each experimental group was analyzed in three independent biological replicates. Differential expression analysis was performed between LPS and C to establish the inflammatory baseline, and between H 2 /H 8 /H 24 and LPS to determine the effects of adalimumab. Genes were defined as differentially expressed (DEGs) if they met the threshold of |fold change| ≥ 2.0 with an adjusted p-value < 0.05.

4.5.Identification of miRNAs Potentially Regulating NF-κB Gene Expression Using miRNA Microarrays

To identify microRNAs potentially regulating NF-κB-associated transcripts, miRNA expression was profiled using GeneChip™ miRNA 2.0 arrays (Affymetrix). Experimental conditions mirrored the mRNA analysis (C, LPS, H 2 , H 8 , H 24 ), with each group performed in biological triplicates. Putative regulatory interactions were evaluated using TargetScan and miRanda databases (accessed 14 April 2021) [108] Only miRNA-mRNA pairs with prediction scores ≥ 80 were retained as high-confidence interactions [108,109].

4.6.RT-qPCR

RT-qPCR was performed to validate expression changes in selected transcripts identified in the microarray screen. Seven genes were analyzed: BCL2 Like 1 (BCL2L1), C-X-C Motif Chemokine Ligand 2 (CXCL2), Mitogen-Activated Protein Kinase Kinase Kinase 7 (MAP3K7), Baculoviral IAP Repeat Containing 2 (BIRC2), Baculoviral IAP Repeat Containing 3 (BIRC3), TNF Alpha Induced Protein 3 (TNFAIP3) and X-Linked Inhibitor of Apoptosis (XIAP). ACTB (β-actin) was used as the reference gene. Reactions were carried out with the SensiFAST SYBR ® kit (Bioline, London, UK) and gene-specific primers (Table 4 ). Each sample was assayed in technical triplicates.

The qPCR protocol consisted of reverse transcription at 45 • C for 10 min, followed by 40 amplification cycles. Specificity of amplification products was confirmed by melting curve analysis and agarose gel electrophoresis. Relative expression was calculated using the 2 -∆∆Ct method [110]. All time points and experimental groups (C, LPS, H 2 , H 8 , H 24 ) were included in the analysis, each in biological triplicates.

4.7.Protein Quantification by ELISA

To examine post-transcriptional regulation, protein levels of BCL2L1, CXCL2, MAP3K7, BIRC2, BIRC3, TNFAIP3, and XIAP were quantified by ELISA. HaCaT cells from all groups (C, LPS, H 2 , H 8 , H 24 ) were harvested, washed twice with ice-cold PBS, and lysed in RIPA buffer. Lysates were centrifuged at 12,000× g for 10 min at 4 • C, and supernatants were collected for analysis.

Commercial ELISA kits (MyBioSource, San Diego, CA, USA) specific for each target protein were used according to the manufacturer's protocols: BCL2L1 (MBS9392826), CXCL2 (MBS2880010), MAP3K7 (MBS7612749), TNFAIP3 (MBS2881407), XIAP (MBS161168), BIRC2 (MBS9426546), and BIRC3 (MBS7235955). Standard curves were generated using recombinant protein standards, and absorbance was measured with a microplate reader. Protein concentrations were calculated from standard curves and normalized to total protein content. All assays were conducted in biological triplicates.

4.8.Statistical Analysis

Data analysis was performed using the Transcriptome Analysis Console (Thermo Fisher Scientific, USA) and StatPlus Pro v7.3 (AnalystSoft Inc., Brandon, FL, USA). The distribution of all variables was assessed with the Shapiro-Wilk test, and for data meeting the assumptions of normality, one-way ANOVA was applied. In the case of microarray analysis, differentially expressed genes (DEGs) were defined as those with an absolute fold change of at least 2.0 and an adjusted p-value below 0.05. Comparisons were made between LPS-stimulated cells and untreated controls (C) to establish the inflammatory baseline, as well as between adalimumab-treated groups (H 2 , H 8 , H 24 ) and the LPS group to determine drug-specific effects. Tukey's HSD post hoc test was used for multiple comparisons in the microarray dataset. For RT-qPCR and ELISA analyses, expression differences among groups were evaluated using one-way ANOVA followed by Scheffe's post hoc test, which was selected for its robustness in cases of unequal group sizes. Results are presented as mean values with standard error of the mean (SEM), and statistical significance was defined as p < 0.05.

Protein-Protein Interaction (PPI) Networks and Gene Ontology (GO) Enrichment Analyses

Functional interpretation of DEGs was performed using STRING version 12.0 (https: //string-db.org, accessed on 1 June 2025) [111]. A high-confidence interaction threshold (minimum required score 0.7) was applied. Both experimentally validated interactions and predicted associations (gene neighborhood, co-occurrence, and text mining) were included. Gene Ontology Biological Process (GO:BP) enrichment was performed on the combined set of DEGs from Table 2 (union across time points and conditions, regardless of direction of regulation). STRING output included network visualization, significantly enriched GO:BP terms, and associated false discovery rate (FDR)-corrected p-values.

5.Conclusions

This study elucidates the multifaceted molecular impact of adalimumab in LPSstimulated keratinocytes, demonstrating its ability to restore inflammatory homeostasis through coordinated suppression of NF-κB and MAPK signaling and modulation of key regulatory microRNAs, including miR-125b, miR-95-5p, and miR-30a. The reciprocal expression patterns between these miRNAs and their validated targets-TNFAIP3, CXCL2, and MAP3K7-highlight a coherent post-transcriptional regulatory network responsive to TNF-α inhibition. In parallel, the regulation of apoptosis-related genes such as BIRC3 and XIAP underscores adalimumab's dual role in modulating keratinocyte survival and dampening immune activation. Collectively, these findings advance our mechanistic understanding of biologic therapy in psoriasis and identify a panel of miRNAs as potential biomarkers for treatment monitoring and patient stratification. Future translational studies and clinical trials integrating miRNA profiling with multi-omics approaches are warranted to validate these targets and to pave the way toward more precise, individualized therapeutic strategies in inflammatory skin diseases.

Data Availability Statement:

The data presented in this study are available in this article.

Conflicts of Interest:

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:

Acknowledgements

Acknowledgments:The authors would like to thank Oskar Ogłoszka for his assistance with English language improvement of the manuscript.

Funding

Funding: This research received no external funding.
Institutional Review Board Statement: Not applicable.Informed Consent Statement: Not applicable.

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