Identification of a Novel Prognostic Signature Based on N-Linked Glycosylation and Its Correlation with Immunotherapy Response in Hepatocellular Carcinoma

Application of a risk score model based on glycosylation-related genes in the prognosis and treatment of patients with low-grade glioma

Introduction

Low-grade gliomas (LGG) represent a heterogeneous and complex group of brain tumors. Despite significant progress in understanding and managing these tumors, there are still many challenges that need to be addressed. Glycosylation, a common post-translational modification of proteins, plays a significant role in tumor transformation. Numerous studies have demonstrated a close relationship between glycosylation modifications and tumor progression. However, the biological function of glycosylation-related genes in LGG remains largely unexplored. Their potential roles within the LGG microenvironment are also not well understood.

Methods

We collected RNA-seq data and scRNA-seq data from patients with LGG from TCGA and GEO databases. The glycosylation pathway activity scores of each cluster and each patient were calculated by irGSEA and GSVA algorithms, and the differential genes between the high and low glycosylation pathway activity score groups were identified. Prognostic risk profiles of glycosylation-related genes were constructed using univariate Cox and LASSO regression analyses and validated in the CGGA database.

Results

An 8 genes risk score signature including ASPM, CHI3L1, LILRA4, MSN, OCIAD2, PTGER4, SERPING1 and TNFRSF12A was constructed based on the analysis of glycosylation-related genes. Patients with LGG were divided into high risk and low risk groups according to the median risk score. Significant differences in immunological characteristics, TIDE scores, drug sensitivity, and immunotherapy response were observed between these groups. Additionally, survival analysis of clinical medication information in the TCGA cohort indicated that high risk and low risk groups have different sensitivities to drug therapy. The risk score characteristics can thus guide clinical medication decisions for LGG patients.

Conclusion

Our study established glycosylation-related gene risk score signatures, providing new perspectives and approaches for prognostic prediction and treatment of LGG.

The liquid-liquid phase separation signature predicts the prognosis and immunotherapy response in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a common and fatal malignancy characterized by poor patient prognosis and treatment outcome. The process of liquid-liquid phase separation in tumour cells alters the dysfunction of biomolecular condensation in tumour cells, which affects tumour progression and treatment. We downloaded the data of HCC samples from TCGA database and GEO database, and used a machine learning method to build a new liquid-liquid phase separation index (LLPSI) by liquid-liquid phase separation related genes. The LLPSI-related column line Figure was constructed to provide a quantitative tool for clinical practice. HCC patients were divided into high and low LLPSI groups based on LLPSI, and clinical features, tumour immune microenvironment, chemotherapeutic response, and immunotherapeutic response were systematically analysed. LLPSI, which consists of five liquid-liquid phase separation-associated genes (MAPT, WDR62, PLK1, CDCA8 and TOP2A), is a reliable predictor of survival in patients with HCC and has been validated in multiple external datasets. We found that the high LLPSI group showed higher levels of immune cell infiltration and better response to immunotherapy compared to the low LLPSI group, and LLPSI can also be used for prognostic prediction in various cancers other than HCC. In vitro experiments verified that knockdown of MAPT could inhibit the proliferation and migration of HCC. The LLPSI identified in this study can accurately assess the prognosis of patients with HCC and identify patient populations that will benefit from immunotherapy, providing valuable insights into the clinical management of HCC.

DDOST is associated with tumor immunosuppressive microenvironment in cervical cancer

Evidence has revealed that DDOST plays an important role in cancer development and progression. However, there are no reports on functions of DDOST in cervical tumorigenesis. Hence, we investigated the relationship of DDOST with prognosis, mutation, promoter methylation, immune cell infiltration, and drug sensitivity using bioinformatics techniques. Our results demonstrated that DDOST was significantly upregulated in a variety of tumor types and correlated with poor prognosis, including cervical cancer. Cox regression analysis dissected that high DDOST expression was associated with poor survival in cervical cancer patients. Immune infiltration analysis defined that DDOST was negatively correlated with CD8 T cells and NK cells. Strikingly, the sensitivity to multiple drugs was negatively correlated with the expression of DDOST. Therefore, our findings uncovered that DDOST could play an essential role in the tumor microenvironment and tumor immune regulation in cervical cancer, which indicated that DDOST could be a useful biomarker for prognosis and a potential therapeutic target for cancer treatment.