Studies on cell signaling pay more attention to spatial dynamics and how such diverse organization can relate to high order of cellular capabilities. To overview the specificity of cell signaling, we integrated human receptome data with proteome spatial expression profiles to systematically investigate the specificity of receptors and receptor-triggered transduction networks across 62 normal cell types and 14 cancer types. Six percent receptors showed cell-type-specific expression, and 4% signaling networks presented enriched cell-specific proteins induced by the receptors. We introduced a concept of "response context" to annotate the cell-type dependent signaling networks. We found that most cells respond similarly to the same stimulus, as the "response contexts" presented high functional similarity. Despite this, the subtle spatial diversity can be observed from the difference in network architectures. The architecture of the signaling networks in nerve cells displayed less completeness than that in glandular cells, which indicated cellular-context dependent signaling patterns are elaborately spatially organized. Likewise, in cancer cells most signaling networks were generally dysfunctional and less complete than that in normal cells. However, glioma emerged hyper-activated transduction mechanism in malignant state. Receptor ATP6AP2 and TNFRSF21 induced rennin-angiotensin and apoptosis signaling were found likely to explain the glioma-specific mechanism. This work represents an effort to decipher context-specific signaling network from spatial dimension. Our results indicated that although a majority of cells engage general signaling response with subtle differences, the spatial dynamics of cell signaling can not only deepen our insights into different signaling mechanisms, but also help understand cell signaling in disease.
Cell Line ; Databases, Protein ; Gene Expression Profiling ; Humans ; Metabolic Networks and Pathways ; Neoplasms ; metabolism ; pathology ; Proteome ; analysis ; Receptors, Cell Surface ; metabolism ; Receptors, Tumor Necrosis Factor ; metabolism ; Signal Transduction ; Vacuolar Proton-Translocating ATPases ; metabolism

Objective:To investigate the factors influencing phytohemagglutinin (PHA) response in the detection of Mycobacterium tuberculosis infection by gamma interferon release assay (IGRA). Methods:A retrospective case-control study was conducted on 360 hospitalized patients who received IGRA in West China Hospital of Sichuan University from January 2019 to December 2021. According to PHA response (IFN-γ level), they were divided into three groups: negative mitogen response group (IFN-γ<2 pg/ml), weak positive mitogen response group (IFN-γ: 2-100 pg/ml), and normal mitogen response group (IFN-γ>400 pg/ml).Results:Immune diseases were independently associated with negative (OR=0.34, 95%CI: 0.17-0.72, P=0.004) and weak positive mitogen responses (OR=0.29, 95%CI: 0.16-0.55, P<0.001). Infections caused by pathogens other than Mycobacterium tuberculosis was independently associated with negative mitogen response (OR=0.266, 95%CI: 0.09-0.83, P=0.023), while immunodeficiency was independently associated with weak positive mitogen response (OR=0.280, 95%CI: 0.12-0.63, P=0.002). Mitogen response was significantly correlated with the levels of albumin and hemoglobin in serum and the counts of neutrophils and lymphocytes ( P<0.001). Conclusions:Immune diseases and immunodeficiency can affect mitogen response. Therefore, clinicians should give attention to mitogen response in the interpretation of IGRA test results to prevent misdiagnosis and underdiagnosis. Besides, to a certain extent, mitogen response can reflect the infection status of hospitalized patients.

Background/Aims: The shortage of donor liver hinders the development of liver transplantation. This study aimed to clarify the poor outcomes of functionally marginal liver grafts (FMLs) and provide evidence for the improvement of ischemia-free liver transplantation (IFLT) after FML transplantation. Methods: Propensity score matching was used to control for confounding factors. The outcomes of the control group and FML group were compared to demonstrate the negative impact of FMLs on liver transplantation patients. We compared the clinical improvements of the different surgical types. To elucidate the underlying mechanism, we conducted bioinformatic analysis based on transcriptome and single-cell profiles. Results: FMLs had a significantly greater hazard ratio (HR: 1.969, P=0.018) than did other marginal livers. A worse 90-day survival (Mortality: 12.3% vs. 5.0%, P=0.007) was observed in patients who underwent FML transplantation. Patients who received FMLs had a significant improvement in overall survival after IFLT (Mortality: 10.4% vs 31.3%, P=0.006). Pyroptosis and inflammation were inhibited in patients who underwent IFLT. The infiltration of natural killer cells was lower in liver grafts from these patients. Bulk transcriptome profiles revealed a positive relationship between IL-32 and Caspase 1 (R=0.73, P=0.01) and between IL-32 and Gasdermin D (R=0.84, P=0.0012). Conclusions FML is a more important negative prognostic parameter than other marginal liver parameters. IFLT might ameliorate liver injury in FMLs by inhibiting the infiltration of NK cells, consequently leading to the abortion of IL-32, which drives pyroptosis in monocytes and macrophages.