Comprehensive analysis of PILRΑ’s association with the prognosis, tumor immune infiltration, and immunotherapy in pan-cancer

Li, Qiao; Yang, Zhirong; He, Xiaoyan; Yang, Xin

doi:10.1038/s41598-023-41649-6

Cited by 4 publications

References 45 publications

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Comprehensive analysis of sialylation-related genes and construct the prognostic model in sepsis

Tao,

Zhou,

et al. 2024

Sci Rep

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Sepsis, a life-threatening syndrome, continues to be a significant public health issue worldwide. Sialylation is a hot potential marker that affects the surface of a variety of cells. However, the role of genes related to sialylation and sepsis has not been fully explored. Bulk RNA-seq data sets (GSE66099 and GSE65682) were obtained from the open-access databases GEO. The classification of sepsis samples into subtypes was achieved by employing the R package “ConsensusClusterPlus” on the bulk RNA-seq data. Hub genes were discerned through the application of the R package “limma” and univariate regression analysis, with the calculation of risk scores carried out using the R package “survminer”. To identify the best learning method and construct a prognostic model, we used 21 different combinations of machine learning, and C-index ranking results of these combinations have been showed. ROC curves, time-dependent ROC curves, and Kaplan–Meier curves were utilized to evaluate the diagnostic accuracy of the model. The R packages “ESTIMATE” and “GSVA” were employed to quantify the fractions of immune cell infiltration in each sample. The bulk RNA-seq samples were categorized into two distinct sepsis subtypes utilizing 14 prognosis-related sialylation genes. A total of 20 differentially expressed genes (DEGs) were identified as being associated with the relationship between sepsis and sialylation. The RSF was used to identify key genes with importance scores higher than 0.01. The nine hub genes (SLA2A1, TMCC2, TFRC, RHAG, FKBP1B, KLF1, PILRA, ARL4A, and GYPA) with the importance values greater than 0.01 was selected for constructing the prognostic model. This research offers some understanding of the relationship between sepsis and sialylation. Besides, it contains one predictive model that might develop into diagnostic biomarkers for sepsis.

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Comprehensive analysis of sialylation-related genes and construct the prognostic model in sepsis

Tao,

Zhou,

et al. 2024

Sci Rep

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Combined PARP14 Inhibition and PD-1 Blockade Promotes Cytotoxic T Cell Quiescence and Modulates Macrophage Polarisation in Relapsed Melanoma

Leshem,

Sefton,

Wong

et al. 2024

Preprint

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Programmed Cell Death 1 (PD-1) signalling blockade is effective in restoring immune surveillance and treating melanoma. However, immune homeostatic mechanisms driven by chronic interferon-gamma (IFNγ) signalling in melanoma cells reduce efficacy, leading to persistent immune evasion and the development of acquired treatment resistance. Previously, we demonstrated that poly ADP ribosyl polymerase 14 (PARP14), encoded by an IFNγ-responsive gene, mediates IFNγ-driven resistance, as inhibition of PARP14 prolonged responsiveness to PD-1 blockade in preclinical models. Nevertheless, inhibition of PARP14 alone was insufficient to fully restore immune clearance, suggesting the presence of redundant resistance mechanisms. The findings here reveal a robust PARP14 catalytic inhibitor (PARP14i) gene signature associated with improved patient survival. We further elucidate the response and adaptation of the immune infiltrate and melanoma cells to PARP14 inhibition using preclinical models. Combining PARP14i with PD-1 blockade therapy revitalised cytotoxic T cells, driving them into a quiescent state while reducing alternatively activated macrophages and increasing pro-inflammatory memory macrophages. Despite this initial enhancement of immune responses through combination therapy, adaptive resistance mechanisms emerged within tumour cells, engaging alternative exhaustion pathways. Our findings indicate that this novel combination therapy leaves immune cells primed for further therapeutic intervention, offering a strategy to address resistance development and optimise treatment outcomes comprehensively.

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Enhancer lncRNA LOC730338 limits the innate immune response against lymphoma cells, inhibiting ADAR2-dependent alternative transcription

Cascione,

Guidetti,

Ramnarayanan

et al. 2024

Preprint

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Chronic antigenic stimulation is central to marginal zone lymphoma (MZL) development. While the pharmacological inhibition of the B-cell receptor (BCR) signaling is initially effective, secondary resistance frequently develops. We conducted a CRISPR interference (CRISPRi) screen investigating enhancer-associated long non-coding RNAs (elncRNAs) in MZL cells to identify transcripts crucial to shape their dependence on BCR pathway activation. We identified LOC730338, an elncRNA associated with A-to-I RNA editing, which we renamed ADARreg. Silencing ADARreg re-sensitized tumor cells to BCR pathway inhibition by modulating ADAR2 nuclear translocation and altering intronic RNA editing. The process preferentially affected genes that enhance immune responses, such as STING, IRF3, and p65. ADARreg knockdown also increased lymphoma cell sensitivity to NK cell-mediated cytotoxicity. Our results indicate that targeting elncRNAs like ADARreg represents a potential strategy to overcome drug resistance in lymphoma, also opening new therapeutic opportunities for immunotherapy.

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Comprehensive analysis of PILRΑ’s association with the prognosis, tumor immune infiltration, and immunotherapy in pan-cancer

Cited by 4 publications

References 45 publications

Comprehensive analysis of sialylation-related genes and construct the prognostic model in sepsis

Comprehensive analysis of sialylation-related genes and construct the prognostic model in sepsis

Combined PARP14 Inhibition and PD-1 Blockade Promotes Cytotoxic T Cell Quiescence and Modulates Macrophage Polarisation in Relapsed Melanoma

Enhancer lncRNA LOC730338 limits the innate immune response against lymphoma cells, inhibiting ADAR2-dependent alternative transcription

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