mProX™ Human SIGLEC9 Stable Cell Line
- Product Category:
- Membrane Protein Stable Cell Lines
- Subcategory:
- Immune Checkpoint Cell Lines
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Published Data
Fig.1 Silencing Siglec-9 in human macrophages amplifies the upregulation of CCR7 expression in response to LPS stimulation.
In the top-left panel, we observed the induction of CCR7 under different conditions: LPS stimulation, IFN-γ stimulation, or no stimulation (control), with CCR7 levels in the control set as a reference (1). Macrophages were subjected to these stimuli for 24 hours. In the top-right panel, we confirmed the knockdown of Siglec-9 through siRNA transfection in macrophages, comparing Siglec-9 expression levels with control siRNA-treated cells (set as 1) using qRT-PCR. In the lower panel, we examined the impact of Siglec-9 knockdown on CCR7 expression, with CCR7 levels normalized to control siRNA-treated cells (set as 1). Statistical significance (*p < 0.05) was observed in these experiments.
Ref: Higuchi, Hiroshi, et al. "Constitutively expressed Siglec-9 inhibits LPS-induced CCR7, but enhances IL-4-induced CD200R expression in human macrophages." Bioscience, Biotechnology, and Biochemistry 80.6 (2016): 1141-1148.
Pubmed: 26923638
DOI: 10.1080/09168451.2016.1146070
Research Highlights
Zhang, Yaqin. et al. "The change of Siglec-9 expression in peripheral blood NK cells of SFTS patients can affect the function of NK cells." Immunology letters, 2023.
The aim of this study is to examine the alterations and underlying mechanism of Siglec-9 expression on natural killer (NK) cells in the peripheral blood of individuals diagnosed with severe fever with thrombocytopenia syndrome (SFTS). This research will involve analyzing the levels of Siglec-9 and its role in modulating NK cell function in SFTS patients. The findings of this investigation could provide insights into the pathogenesis of SFTS and potentially lead to the development of new treatment strategies. This abstract aims to emphasize the significance of investigating Siglec-9 in SFTS patients and its potential implications in improving patient outcomes.
Zhang, Yaqin. et al. "The change of Siglec-9 expression in peripheral blood NK cells of SFTS patients can affect the function of NK cells." Immunology letters, 2023.
Pubmed:
37865296
DOI:
10.1016/j.imlet.2023.10.004
Xu, Sa. et al. "Construction and validation of a immune-related prognostic gene DHRS1 in hepatocellular carcinoma based on bioinformatic analysis." Medicine, 2023.
DHRS1, a member of the short-chain dehydrogenase/reductase superfamily (DHRS1, SDR19C1), has been identified as a potential predictor of hepatocellular carcinoma (HCC). However, its role in HCC immunity remains unclear. To analyze the association between DHRS1 and HCC immunity, a systematic study was conducted using transcriptional and clinical data from the Tumor Immune Estimation Resource and cBioPortal databases. Six DHRS1-associated immunomodulators were identified, strongly correlated with survival using univariate and multivariate Cox analyses. A risk score was generated for each patient, and further validation studies were conducted using an external validation set. A nomogram was constructed using the R package. Our findings suggest a correlation between levels of immune cell infiltration and DHRS1 gene copy numbers or mRNA levels in HCC. A signature based on 6 DHRS1-related immunomodulators (KDR, TNFRSF4, CD276, TNFSF4, SLAMF6, and SIGLEC9) was also generated and was found to serve as an independent indicator of HCC prognosis with an area under the receiver operating characteristic curve of 0.743. External validation sets were established to confirm the predictive validity of the risk score. Furthermore, a prognostic nomogram and calibration curve were constructed. Our results suggest that DHRS1 may play a role in HCC immunity and that the immune signature based on DHRS1-associated immunomodulators could serve as a promising prognostic biomarker for HCC.
Xu, Sa. et al. "Construction and validation of a immune-related prognostic gene DHRS1 in hepatocellular carcinoma based on bioinformatic analysis." Medicine, 2023.
Pubmed:
37861541
DOI:
10.1097/MD.0000000000035268