Background: Given that aberrant glycosylation acts as a catalyst for tumorigenesis, elucidating Signal Sequence Receptor 2 (SSR2)'s specific patterns is essential to unlock its potential as a prognostic biomarker and clarify its mechanistic role in cancer biology. This study aims to comprehensively characterize the expression landscape and functional significance of SSR2, a pivotal subunit of the oligosaccharyltransferase complex, across normal human tissues and diverse malignancies. Methods: In this investigation, we utilized advanced bioinformatics resources, including the Human Protein Atlas (HPA), Genotype-Tissue Expression (GTEx), The Cancer Genome Atlas (TCGA), and CPTAC databases, to analyze the expression levels of SSR2 across various human tissues and malignancies. The data were analyzed utilizing the Xiantao academic analysis tool. We performed comparative analyses of SSR2 expression in cancerous and adjacent normal tissues, assessed survival outcomes associated with SSR2 expression levels, and conducted mutation and methylation analyses using cBioPortal and other relevant platforms. Results: Our findings revealed that SSR2 was predominantly expressed in the pancreas, epididymis, and ovary. Notably, significant differences in SSR2 expression were observed between cancerous and adjacent normal tissues in bladder urothelial carcinoma, breast cancer, and colorectal cancer. High levels of SSR2 correlated with poorer overall survival in adrenocortical carcinoma, esophageal cancer, and clear cell renal carcinoma, while SSR2 expression exhibited a protective effect in ovarian serous cystadenocarcinoma. Furthermore, SSR2 mutations were frequently observed in uterine sarcoma and liver cancer. Methylation analysis identified cg24557248, a CpG site, as a promising prognostic biomarker in clear cell renal carcinoma; increased methylation at this site was linked to improved survival outcomes. Conclusions: This study emphasizes the complex role of SSR2 in cancer biology, showcasing its potential as both a biomarker and a therapeutic target. Furthermore, the link between SSR2 and tumor immune cell infiltration indicates its role in shaping tumor microenvironments. Future investigations should aim to clarify how SSR2 affects tumor growth and immune regulation, which could lead to innovative therapeutic approaches for cancer treatment.
In the cancer microenvironment, stromal and immune cells hold clinical importance. In lung squamous cell carcinoma (LSCC), the aim of this study was to find immune‐linked gene expression that has prognostic pertinence.
From the Cancer Genome Atlas, this study obtained the LSCC gene expression profile. The Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data algorithm was applied to derive stromal and immune scores for the included cases.
Stromal and immune scores were not statistically associated with sex or tumor stage, whereas a borderline significant association was observed between the immune score and smoking status (
p
= 0.0614). Interestingly, the immune score showed an independent association with overall survival in LSCC as shown by multivariate analyses. There were 517 differentially expressed genes (DEGs) linked to immune scores in total, 42 of which were upregulated. The DEGs were commonly linked to inflammatory and immune responses, extracellular exosomes, and chemokine activities. Cox analyses revealed that 21 DEGs were significantly related to overall survival (OS) in LSCC. Through validation, four genes (AP1S2, CLEC10A, FBXO2, and IQGAP2) were found to be significant OS predictors in independent Gene Expression Omnibus (GEO) datasets. However, immunohistochemistry (IHC) validation showed inconsistent prognostic trends for AP1S2 compared with bioinformatic predictions, whereas CLEC10A exhibited no differential expression between tumor and adjacent tissues. FBXO2 and IQGAP2 maintained consistent associations with OS. Multivariate Cox regression confirmed several of these genes as independent prognostic factors for LSCC.
The study refines immune score‐associated DEGs and identifies independent prognostic factors in LSCC, and it provides tissue‐level evidence that may support future prognostic evaluation.
Weijia Jiang, Jing Xu, Wenwen Ma et al.· iNew Medicine· 0 citations
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