Identification of the novel prognostic biomarker, MLLT11, reveals its relationship with immune checkpoint markers in glioma - Chen, Long; Xiong, Zujian; Zhao, Hongyu; Teng, Chubei; Liu, Hongwei; Huang, Qi; Wanggou, Siyi; Li, Xuejun (Frontiers in Oncology, 2022)
Aim: To explore the expression pattern of MLLT11 under different pathological features and evaluate the prognostic value for glioma patients. To reveal the relationship between MLLT11 mRNA expression and immune cell infiltration in tumor microenvironment (TME) and to provide more evidence for the molecular diagnosis of glioma and immunotherapy. Methods: Using large scale bioinformatic approach and RNA-seq data from public databases (TCGA, CGGA and GEO), we investigated the relationship between MLLT11 mRNA levels and pathologic characteristics. The distribution in the different subtypes was observed based on Verhaak bulk and Neftel single-cell classification. Then, Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were used for bioinformatics analysis. Kaplan‐Meier survival analysis and Cox regression analysis were used for survival analysis. Correlation analysis were performed between MLLT11 expression and 22 immune cells and immune checkpoints in TME. Results: We found that MLLT11 expression is decreased in high grade glioma tissues; we further verified this result by RTPCR, Western Blotting and immunochemistry using our clinical samples. According to Verhaak classification, high MLLT11 expression is mostly clustered in PN and NE subtypes, while in Neftel classification, MLLT11 mainly clustered in NPC-like neoplastic cells. Survival analysis revealed that low levels of MLLT11 expression are associated with a poorer prognosis; MLLT11 was identified as an independent prognostic factor in multi-COX regression analyses. Functional enrichment analyses of MLLT11 with correlated expression indicated that low MLLT11 expression is associated with the biological process related to extracellular matrix, and the high expression group is related to synaptic structure. Correlation analyses suggest that declined MLLT11 expression is associated with increased macrophages infiltration in glioma, especially M2 macrophage, and verified by RTPCR, Western blot and immunochemistry using our clinical glioma samples. MLLT11 had high negatively correlation with immune checkpoint inhibitor (ICI) genes including PDCD1, PD-L1, TIM3(HAVCR2) and PD‐L2 (PDCD1LG2). Conclusion: MLLT11 plays a crucial role in the progression of glioma and has the potential to be a new prognostic marker for glioma.