Epidemiological studies have validated the association between hepatitis C virus (HCV) infection and hepatocellular carcinoma (HCC). An increasing number of studies show that protein-protein interactions (PPIs) between HCV proteins and host proteins play a vital role in infection and mediate HCC progression. In this work, we collected all published interaction between HCV and human proteins, which include 455 unique human proteins participating in 524 HCV-human interactions. Then, we construct the HCV-human and HCV-HCC protein interaction networks, which display the biological knowledge regarding the mechanism of HCV pathogenesis, particularly with respect to pathogenesis of HCC. Through in-depth analysis of the HCV-HCC interaction network, we found that interactors are enriched in the JAK/STAT, p53, MAPK, TNF, Wnt, and cell cycle pathways. Using a random walk with restart algorithm, we predicted the importance of each protein in the HCV-HCC network and found that AKT1 may play a key role in the HCC progression. Moreover, we found that NS5A promotes HCC cells proliferation and metastasis by activating AKT/GSK3β/β-catenin pathway. This work provides a basis for a detailed map tracking new cellular interactions of HCV and identifying potential targets for HCV-related hepatocellular carcinoma treatment.

Objective: To examine the kinetics of B cell subsets and activation markers in the early stage of belimumab treatment and their correction with treatment response.Methods: We enrolled 27 systemic lupus erythematosus (SLE) patients receiving 6 months belimumab treatment. Flow cytometry was used to test their B cell subsets and activation markers (including CD40, CD80, CD95, CD21^low, CD22, p-SYK and p-AKT).Results: During belimumab treatment, SLEDAI-2K declined, the proportions of CD19⁺ B cells and naïve B cells decreased, whereas the switched memory B cells and non-switched B cells increased. The larger variations of the B cell subsets and the activation markers were in the first 1 month than the other later time frames. The ratio of p-SYK/p-AKT on non-switched B cell at 1 month was associated with the SLEDAI-2K decline rate in the 6 months of belimumab treatment.Conclusion: B cell hyperactivity was rapidly inhibited in the early stage of belimumab treatment, and the ratio of p-SYK/p-AKT may predict SLEDAI-2K decline.Clinical Trial Registration:https://www.clinicaltrials.gov/ct2/show/NCT04893161?term=NCT04893161&draw=2&rank=1; identifier: NCT04893161.

Cell death contributes to the pathogenesis of rheumatoid arthritis (RA) through various pathways. Disulfidptosis is a recently discovered novel form of cell death characterized by the abnormal accumulation of intracellular disulfide bonds. It remains unclear for the association between RA and disulfidptosis. A comprehensive analysis of three GEO datasets was presented in this study. First, the analysis involved the use of weighted gene co-expression network analysis (WGCNA) and differential analysis and were employed to identify the key module genes related to RA and disulfidptosis-related genes. The machine learning algorithms were used to identify the hub genes. Second, a diagnostic model was constructed for RA based on the hub genes. The nomogram and receiver operating characteristic (ROC) curves were utilized to evaluate the diagnostic value of the model. Third, two RA subtypes were identified based on hub genes by using consensus clustering analysis. Then, the disease activity scores, clinical markers, and immune cells were compared between the two RA subgroups. Finally, the differential expression of hub genes was validated between healthy controls and RA patients by qPCR. Four hub genes (KLHL2, POLK, CLEC4D, NXT2) were identified. The expression of the four hub genes was verified to be significantly higher in RA patients compared with healthy controls. The superior diagnostic value of the model was validated, which demonstrated that the model outperforms each hub gene individually. Two subtypes of RA were determined. Patients in cluster A exhibited relatively lower levels of DAS28-CRP, DAS28-ESR, CDAI, SDAI, RF, CRP, and MMP3. In contrast, patients in cluster B had significantly higher levels of the above markers. Four hub genes were identified to provide unique insights into the role of disulfidptosis in RA. Additionally, a promising diagnosis model and patient stratification were established based on the hub genes to assess the risk of RA onset and RA disease activity.

Synovial fibroblasts (SFs) transform into an aggressive phenotype in rheumatoid arthritis (RA), playing a significant role in sustaining synovitis and bone erosion. Baricitinib, a JAK inhibitor, has been validated as an effective treatment for RA. However, its direct inhibitory effects on RASFs remain poorly understood. The inflammatory response and aggressive behaviors (proliferation, apoptosis, migration, and invasion) of RASFs were assessed following treatment with varying concentrations of baricitinib. RNA sequencing was performed to identify differentially expressed genes and elucidate the impact of baricitinib on RASFs. The relationship between the JAK-STAT3 signaling pathway and downstream molecules (EGR1, BCL-2, MMP-2, MMP-9) was analyzed via western blotting. Collagen-induced arthritis (CIA) mice were treated with baricitinib via oral gavage or by intra-articular injection of shEGR1 to evaluate therapeutic efficacy. Baricitinib inhibited the production of inflammatory mediators in primary RASFs and reduced the progression of synovial inflammation and hyperplasia in RA patients as assessed by ultrasound. In vitro, baricitinib promoted apoptosis and inhibited the proliferation, migration, and invasion of RASFs, effects associated with decreased expression of the transcriptional regulator EGR1. In vivo, baricitinib effectively reduced arthritis scores, paw swelling, and the expression of inflammatory cytokines in the joint tissues of CIA mice. Similar therapeutic effects were observed upon inhibition of EGR1. Baricitinib inhibits the aggressive phenotype of RASFs through the JAK-STAT3-EGR1 axis, thereby contributing to the alleviation of the inflammatory response and joint destruction in RA.

Background: Takayasu arteritis (TAK) is a chronic granulomatous vasculitis, and accurate early diagnosis and assessment of disease activity remain significant clinical challenge. Traditional biomarkers such as CRP and ESR have insufficient sensitivity and specificity. High-throughput proteomics provides a robust method for discovering new biomarkers for TAK. Methods: A comparative serum proteomic analysis of 8 TAK patients and 9 healthy controls (HCs) was conducted using mass spectrometry. Bioinformatic analyses were performed on differentially expressed proteins (DEPs). Candidate biomarkers were prioritized through machine learning and correlation analyses. An independent validation cohort with 51 TAK patients and 31 HCs was used to confirm the biomarkers using ELISA. The correlations were assessed between the new biomarkers and the clinical parameters as well as disease activity scores. Results: We identified 88 DEPs between TAK patients and HCs. Pathway analysis revealed enrichment in phagosome, platelet activation, and inflammatory response. Among these, Haptoglobin (HP) and Orosomucoid 1 (ORM1) were selected as top candidate biomarkers based on their high feature importance scores and strong correlation with inflammatory markers. ELISA validation confirmed that serum levels of HP and ORM1 were significantly elevated in TAK patients compared with HCs, and further increased in active TAK compared with stable TAK patients. Both biomarkers showed significant positive correlations with clinical inflammatory indicators (ESR, FIB, WBC) and immune cell counts, as well as disease activity scores. Conclusion: Our integrated proteomic analysis identified HP and ORM1 as 2 novel serum biomarkers significantly associated with disease activity, inflammatory and immune processes in TAK.