A promising glycolysis and immune related prognostic signature for glioblastoma (GBM)

Glioblastoma glycolytic signature predicts unfavorable prognosis, immunological heterogeneity, and ENO1 promotes microglia M2 polarization and cancer cell malignancy

Glioblastomas are the most malignant brain tumors, whose progress was promoted by aberrate aerobic glycolysis. The immune environment was highly engaged in glioblastoma formation, while its interaction with aerobic glycolysis remained unclear. Herein, we build a 7-gene Glycolytic Score (GS) by Elastic Net in the training set and two independent validating sets. The GS predicted malignant features and poor survival with good performances. Immune functional analyses and Cibersort calculation identified depressed T cells, B cells, natural killer cells immunity, and high immunosuppressive cell infiltration in the high-GS group. Also, high expressions of the immune-escape genes were discovered. Subsequently, the single-cell analyses validated the glycolysis-related immunosuppression. The functional results manifested the high-GS neoplastic cells' association with T cells, NK cells, and macrophage function regulation. The intercellular cross-talk showed strong associations between high-GS neoplastic cells and M2 macrophages/microglia in several immunological pathways. We finally confirmed that ENO1, the key gene of the GS, promoted M2 microglia polarization and glioblastoma cell malignant behaviors via immunofluorescence, clone formation, CCK8, and transwell rescue experiments. These results indicated the interactions between cancerous glycolysis and immunosuppression and glycolysis' role in promoting glioblastoma progression. Conclusively, we built a robust model and discovered strong interaction between GS and immune, shedding light on prognosis management improvement and therapeutic strategies development for glioblastoma patients.

Metabolic Barriers to Glioblastoma Immunotherapy

Glioblastoma (GBM) is the most common primary brain tumor with a poor prognosis with the current standard of care treatment. To address the need for novel therapeutic options in GBM, immunotherapies which target cancer cells through stimulating an anti-tumoral immune response have been investigated in GBM. However, immunotherapies in GBM have not met with anywhere near the level of success they have encountered in other cancers. The immunosuppressive tumor microenvironment in GBM is thought to contribute significantly to resistance to immunotherapy. Metabolic alterations employed by cancer cells to promote their own growth and proliferation have been shown to impact the distribution and function of immune cells in the tumor microenvironment. More recently, the diminished function of anti-tumoral effector immune cells and promotion of immunosuppressive populations resulting from metabolic alterations have been investigated as contributory to therapeutic resistance. The GBM tumor cell metabolism of four nutrients (glucose, glutamine, tryptophan, and lipids) has recently been described as contributory to an immunosuppressive tumor microenvironment and immunotherapy resistance. Understanding metabolic mechanisms of resistance to immunotherapy in GBM can provide insight into future directions targeting the anti-tumor immune response in combination with tumor metabolism.

Bioinformatic Analyses of Broad H3K79me2 Domains in Different Leukemia Cell Line Data Sets

A subset of expressed genes is associated with a broad H3K4me3 (histone H3 trimethylated at lysine 4) domain that extends throughout the gene body. Genes marked in this way in normal cells are involved in cell-identity and tumor-suppressor activities, whereas in cancer cells, genes driving the cancer phenotype (oncogenes) have this feature. Other histone modifications associated with expressed genes that display a broad domain have been less studied. Here, we identified genes with the broadest H3K79me2 (histone H3 dimethylated at lysine 79) domain in human leukemic cell lines representing different forms of leukemia. Taking a bioinformatic approach, we provide evidence that genes with the broadest H3K79me2 domain have known roles in leukemia (e.g., JMJD1C). In the mixed-lineage leukemia cell line MOLM-13, the HOXA9 gene is in a 100 kb broad H3K79me2 domain with other HOXA protein-coding and oncogenic long non-coding RNA genes. The genes in this domain contribute to leukemia. This broad H3K79me2 domain has an unstable chromatin structure, as was evident by enhanced chromatin accessibility throughout. Together, we provide evidence that identification of genes with the broadest H3K79me2 domain will aid in generating a panel of genes in the diagnosis and therapeutic treatment of leukemia in the future.