Integrating Bioinformatic Strategies with Real-World Data to Infer Distinctive Immunocyte Infiltration Landscape and Immunologically Relevant Transcriptome Fingerprints in Ossification of Ligamentum Flavum

PURPOSE: Ossification of the ligamentum flavum (OLF) is a multifactorial disease characterized by an insidious and debilitating process of abnormal bone formation in ligamentum tissues. However, its definite pathogenesis has not been fully elucidated. Potential links between the immune system and various forms of heterotopic ossification have been discussed for many years, whereas no research investigated the immune effects on the initiation and development of OLF. Therefore, we attempt to shed light on this issue. METHODS: A series of bioinformatic algorithms were integrated to evaluate the immune score and the immunocyte infiltration patterns between OLF and normal samples, screen OLF-related and immune-related differentially expressed genes (OIDEGs), and analyze their biological functions. Correlation analysis inferred OIDEGs-related differentially expressed lncRNAs (OIDELs) and infiltrating immune cells (OIICs) to construct an immunoregulatory network. RESULTS: Differential immune score and immune cell infiltration were determined between two groups, and 10 OIDEGs with diverse biological function annotations were identified and verified. A lncRNA-gene-immunocyte regulatory network further revealed 10 OIDEGs, 41 OIDELs and 7 OIICs that were highly correlated. Among them, CD1E and STAT3 were predicted as hub genes whether at the expression level or interaction level. cDCs emerged as having the most prominent differences and the highest degree of connectivity. FO393414.3, AC096734.1, LINC01137 and DLX6-AS1 with the greatest number of OIDEGs were thought to be more likely to participate in immunoregulation of OLF. CONCLUSION: This is the first research to preliminarily elucidate OLF-related immunocyte infiltration landscape and immune-associated transcriptome signatures based on bioinformatic strategies and real-world data, which may provide compelling insights into the pathogenesis and therapeutic targets of OLF.