Proinflammatory cytokines levels in sepsis and healthy volunteers, and tumor necrosis factor-alpha associated sepsis mortality: A systematic review and meta-analysis

Gharamti, Amal; Samara, Omar; Monzon, Anthony; Montalbano, Gabrielle; Scherger, Sias; DeSanto, Kristen; Chastain, Daniel B; Sillau, Stefan; Montoya, José G.; Franco‐Paredes, Carlos; Henao-Martínez, Andrés F; Shapiro, Leland

doi:10.1016/j.cyto.2022.156006

Cited by 31 publications

(19 citation statements)

References 90 publications

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“…CytoSorb is a widely used HP device for cytokine elimination (<55 kDa) mainly through the size exclusion effect and hydrophobic interactions . However, TNF-α elimination by CytoSorb still remains below 50% because of its low concentration (mostly <1000 ng/L in sepsis) and large size (51 kDa). ,− Furthermore, the nonspecific adsorbents leading to simultaneous removal of beneficial substances (therapeutic antibiotics, clotting factors, etc.) necessitate additional monitoring of drug levels and adjustments in dosage, causing additional workload for healthcare providers. − To enhance the specific removal of TNF-α, Weber et al and Dileo et al constructed immunosorbents with antibodies as high-affinity ligands. , McAlvin et al used antibodies to modify cibdyurs for the elimination of TNF-α from the blood .…”

Section: Introductionmentioning

confidence: 99%

Biparatopic Nanobody-Based Immunosorbent for the Highly Selective Elimination of Tumor Necrosis Factor-α

Chen,

Yao,

Huang

et al. 2024

ACS Biomater. Sci. Eng.

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Removing the overexpressed TNF-α by hemoperfusion positively affects clinical treatments for diseases such as autoimmune disease and sepsis. However, clearance ratios of adsorbents targeting TNF-α were limited by the extremely low concentration of TNF-α (mostly <1000 ng/L in sepsis) and hydrophobic interactions. In this work, biparatopic nanobodies (NbC21) with a high affinity of 19.9 pM, which bind to two distinct sites of TNF-α, were constructed as high-affinity ligands for the immunosorbent. The theoretical maximum adsorption capacity estimated from the Langmuir isotherm was up to 18.22 mg/g gel. The prepared immunosorbent (NbC21-sorbent) had an outstanding TNF-α clearance ratio of approximately 96% during the dynamic adsorption test, with a sorbent-to-serum ratio of 1:1000. Additionally, it demonstrated favorable hemocompatibility and a prolonged storage capability. The results indicated that the biparatopic nanobody immunosorbent exhibited significant potential for clinical applications as it met the stringent criteria for both efficacy and safety.

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Section: Introductionmentioning

confidence: 99%

Biparatopic Nanobody-Based Immunosorbent for the Highly Selective Elimination of Tumor Necrosis Factor-α

Chen,

Yao,

Huang

et al. 2024

ACS Biomater. Sci. Eng.

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“…The damaged cells can promote the inflammatory response as endogenous inflammatory inducers. In addition, M1 macrophages also release excessive proinflammatory cytokines, such as IL-1, IL-8, TNF-α, and IFN-γ ( Gharamti et al, 2022 ). Furthermore, dendritic cells (DCs) can activate toll-like receptors (TLRs) and generate excessive pro-inflammatory factors, which augment the immune response.…”

Section: Introductionmentioning

confidence: 99%

Identification of featured necroptosis-related genes and imbalanced immune infiltration in sepsis via machine learning

et al. 2023

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Background: The precise diagnostic and prognostic biological markers were needed in immunotherapy for sepsis. Considering the role of necroptosis and immune cell infiltration in sepsis, differentially expressed necroptosis-related genes (DE-NRGs) were identified, and the relationship between DE-NRGs and the immune microenvironment in sepsis was analyzed.Methods: Machine learning algorithms were applied for screening hub genes related to necroptosis in the training cohort. CIBERSORT algorithms were employed for immune infiltration landscape analysis. Then, the diagnostic value of these hub genes was verified by the receiver operating characteristic (ROC) curve and nomogram. In addition, consensus clustering was applied to divide the septic patients into different subgroups, and quantitative real-time PCR was used to detect the mRNA levels of the hub genes between septic patients (SP) (n = 30) and healthy controls (HC) (n = 15). Finally, a multivariate prediction model based on heart rate, temperature, white blood count and 4 hub genes was established.Results: A total of 47 DE-NRGs were identified between SP and HC and 4 hub genes (BACH2, GATA3, LEF1, and BCL2) relevant to necroptosis were screened out via multiple machine learning algorithms. The high diagnostic value of these hub genes was validated by the ROC curve and Nomogram model. Besides, the immune scores, correlation analysis and immune cell infiltrations suggested an immunosuppressive microenvironment in sepsis. Septic patients were divided into 2 clusters based on the expressions of hub genes using consensus clustering, and the immune microenvironment landscapes and immune function between the 2 clusters were significantly different. The mRNA levels of the 4 hub genes significantly decreased in SP as compared with HC. The area under the curve (AUC) was better in the multivariate prediction model than in other indicators.Conclusion: This study indicated that these necroptosis hub genes might have great potential in prognosis prediction and personalized immunotherapy for sepsis.

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“…Other acute phase reactants such as interleukin-1 beta, tumor necrosis factor-alpha, procalcitonin, and interferon gamma can also act as inflammatory biomarkers. [31][32][33][34][35][36] However, CRP testing is very accessible, relatively inexpensive, and well-established in low-resource clinical settings, 19,22,23,[25][26][27]29,30 making it an ideal choice for combination with qSOFA, a rapid and simple bedside scoring system. 3,37 Current evidence evaluating the performance of a combined qSOFA and CRP score is limited.…”

Section: Introductionmentioning

confidence: 99%

“…Including CRP in qSOFA may improve qSOFA's sensitivity and ability to identify patients at high‐risk of mortality or sepsis. Other acute phase reactants such as interleukin‐1 beta, tumor necrosis factor‐alpha, procalcitonin, and interferon gamma can also act as inflammatory biomarkers 31–36 . However, CRP testing is very accessible, relatively inexpensive, and well‐established in low‐resource clinical settings, 19,22,23,25–27,29,30 making it an ideal choice for combination with qSOFA, a rapid and simple bedside scoring system 3,37 …”

Section: Introductionmentioning

confidence: 99%

Combining C‐reactive protein and quick sequential organ failure assessment (qSOFA) to improve prognostic accuracy for sepsis and mortality in adult inpatients: A systematic review

Zacharakis

Ackermann

Hughes

et al. 2023

Health Science Reports

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Proinflammatory cytokines levels in sepsis and healthy volunteers, and tumor necrosis factor-alpha associated sepsis mortality: A systematic review and meta-analysis

Cited by 31 publications

References 90 publications

Biparatopic Nanobody-Based Immunosorbent for the Highly Selective Elimination of Tumor Necrosis Factor-α

Biparatopic Nanobody-Based Immunosorbent for the Highly Selective Elimination of Tumor Necrosis Factor-α

Identification of featured necroptosis-related genes and imbalanced immune infiltration in sepsis via machine learning

Combining C‐reactive protein and quick sequential organ failure assessment (qSOFA) to improve prognostic accuracy for sepsis and mortality in adult inpatients: A systematic review

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