INPP4B inhibits glioma cell proliferation and immune escape via inhibition of the PI3K/AKT signaling pathway

Amino acid metabolism in glioblastoma pathogenesis, immune evasion, and treatment resistance

Glioblastoma (GBM) ranks among the most lethal primary tumors of the central nervous system. This is partly due to its complex intracellular metabolism and interactions with the surrounding tumor microenvironment (TME). Compelling evidence represents that altered amino acids (AAs) metabolism plays a crucial role in both areas. The role of AAs and their metabolites in glioma biology is an emerging topic. Therefore, this review was conducted to summarize the current knowledge about the molecular mechanisms by which AAs participate in the GBM pathogenesis. AAs can directly influence tumor progression by affecting tumor cell metabolism or indirectly by releasing bioactive agents through particular metabolic pathways. This review begins by examining the metabolic pathways of essential AAs, such as tryptophan, tyrosine, and phenylalanine, which contribute to synthesizing critical neurotransmitters and shape tumor metabolism signatures. We explore how these pathways impact tumor growth and immune modulation, focusing on how AAs and their metabolites can promote malignant properties in GBM cells. AAs also play a pivotal role in reprogramming the TME, contributing to immune evasion and resistance to therapy. The review further discusses how tumor metabolism signatures, influenced by AA metabolism, can enhance the immunosuppressive microenvironment, providing new avenues for targeted immunotherapies. Finally, we outline potential therapeutic strategies to modulate AA metabolism and emphasize critical opportunities for future research to improve GBM management.

Seminal plasma metabolomics and sperm lipidomics profiles of bull semen with different total progressive motile sperm count

Total progressive motile sperm count (TPMSC) is a reliable index of fecundity evaluation of bull semen. It is an important determinant of frozen semen yield and conception rate of females artificially inseminated. Seminal plasma metabolites and sperm lipids are closely related to sperm survival and motility, but their relationship with TPMSC is not well known. In the present study, Simmental bulls with higher (H, n = 6) or lower (L, n = 6) TPMSC (P < 0.01) were selected from a cohort of 100 animals aged 2 to 5 yr based on semen quality. Analysis of semen quality and biochemical markers of seminal plasma revealed that H bulls had greater ejaculate volume (P < 0.05), sperm motility, plasma membrane integrity rate (P < 0.01), seminal plasma neutral α-glucosidase (P < 0.05), alkaline phosphatase, acid phosphatase, cortisol and phosphatidylcholine (P < 0.01), and lower sperm malformation rate (P < 0.05) and reactive oxygen species (P < 0.01). Semen metabolites and sperm liposome profiles of H and L groups were compared using LC-MS/MS analysis. A total of 120 differentially abundant metabolites (VIP > 1; P < 0.05) and 59 differentially abundant lipids (VIP > 1; P < 0.05) were identified between H and L groups. Oxidative stress, sperm motility, and sperm plasma membrane integrity were among the enriched biological pathways. Cyclic ADP-ribose (cADPR), up-regulated in H bulls, is associated with energy for sperm motility and maintenance of membrane stability. Thymidineglycol (Tg), levanbiose, thymidine (Thd), and CE (3M5) were down-regulated in H bulls and may have negatively affected sperm motility. Correlation analyses revealed that TPMSC and sperm motility were significantly positively correlated with cADPR, while Tg, Levanbiose, Thd, and CE (3M5) were significantly negatively correlated with TPMSC and sperm motility. Thus, we speculate that these molecules may be exploited as potential biomarkers for non-invasive evaluation of TPMSC in bull semen.

Screening of potential key pathogenic and intervention targets of low-grade glioma based on bioinformatics

Background

Sialic acid-binding immunoglobulin-like lectin 8 (SIGLEC8) is involved in the progression of numerous diseases. This study aimed to examine the relationship between SIGLEC8 and the prognosis of patients with low-grade glioma (LGG) and the related mechanisms.

Methods

First, screening of the differentially expressed genes (DEGs) SIGLEC8 in The Cancer Genome Atlas (TCGA) database was performed. The expression was then correlated with the prognosis of patients with LGG and then verified using the Tumor Immune Estimation Resource (TIMER) and TCGA databases. Cox regression was employed to conduct multifactorial analysis and was followed by the construction of an internally validated nomogram based on these results. To investigate the possible mechanisms, we used gene set enrichment analysis (GSEA). We conducted a retrospective analysis of the clinical information of patients with LGG who were treated at Longgang Central Hospital of Shenzhen from January 2018 to December 2020 and from whom tumor and peritumoral tissues were taken during surgery. Expression of essential genes was identified by employing quantitative real-time polymerase chain reaction (qRT-PCR). Multivariate analysis, via Cox regression, was employed to determine the prognostic factors for patients with LGG.

Results

The transcriptional activity of SIGLEC8 was found to be elevated in LGG neoplastic tissues compared to neighboring nonneoplastic tissues. Overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) were improved in patients with LGG with reduced expression of SIGLEC8 as compared to those with increased expression of SIGLEC8. The nomogram's C-index is 0.804 (0.781-0.827). indicating good predictive accuracy. GSEA revealed that SIGLEC8 might influence LGG biological events by participating in the PD-1, IL3, JAK/STAT, and PI3KCI signal transduction pathways, as well as cytokine and inflammatory response, cell cycle, homeostasis, and extracellular matrix. This study included 72 patients with LGG. qRT-PCR showed upregulated SIGLEC8 expression in LGG tumor tissues, which was significantly associated with tumor number and metastasis to the lymph nodes (P<0.05). Multivariate analysis using Cox regression identified the high expression of SIGLEC8 as an independent risk factor in LGG prognosis (P<0.05).

Conclusions

For the prognosis of patients with LGG, the transcriptional activity of SIGLEC8 is increased in LGG tissues and is an independent risk factor. Interference with SIGLEC8 could promote tumor progression by regulating the JAK/STAT signaling pathway, indicating that SIGLEC8 may function as a distinctive predictive biomarker for patients with LGG.

Downregulation of INPP4B is Associated with Poor Prognosis in Epithelial Ovarian Carcinoma

Background

INPP4B is a tyrosine-specific phosphatase in the human body, which plays an important role in the developing process of carcinogenesis. However, The correlation between INPP4B and epithelial ovarian cancer is rarely explored. In this study, the expression of INPP4B in human epithelial ovarian carcinoma and normal ovaries was detected, to explore the correlation between INPP4B expression and clinicopathological risk factors of epithelial ovarian carcinoma and to clarify its significance in the developing process of and prognosis of epithelial ovarian carcinoma.

Methods

The expression of INPP4B in various tumors was detected by bioinformatics method, and the expression in epithelial ovarian cancer and normal control group was detected by Elisa. The immunohistochemical method was used in this experiment to analyze the expression of INPP4B in specimens of 100 cases of epithelial ovarian carcinoma and 20 cases of normal ovaries. Analysis of clinicopathological risk factors and related survival analysis was carried out on the expression of INPP4B in 100 cases of epithelial ovarian carcinoma.

Results

The results showed that the positive expressed INPP4B protein in epithelial ovarian carcinoma was significantly less, compared with that in normal ovaries (P < 0.05). The expression of INPP4B was significantly associated with many clinicopathologic factors, such as tumor differentiation (P < 0.001), FIGO stage (P < 0.001), lymph node metastasis (P < 0.001) and distant metastasis at recurrence (P=0. 009), but not with age, pathologic type of tumor, serum CA125 at recurrence and chemotherapy sensitivity.

Conclusion

In epithelial ovarian carcinoma, there is a downregulation of INPP4B expression, which may be related to poor tumor differentiation, late FIGO stage, lymph node metastasis, distant metastasis at recurrence and insensitivity to chemotherapy. Under-expression of INPP4B, lymph node metastasis, FIGO stage, and distant metastasis at recurrence are factors of poor prognostic. The under-expression level of INPP4B may be involved in the progression of epithelial ovarian carcinoma.

A Bayesian method to infer copy number clones from single-cell RNA and ATAC sequencing

Single-cell RNA and ATAC sequencing technologies enable the examination of gene expression and chromatin accessibility in individual cells, providing insights into cellular phenotypes. In cancer research, it is important to consistently analyze these states within an evolutionary context on genetic clones. Here we present CONGAS+, a Bayesian model to map single-cell RNA and ATAC profiles onto the latent space of copy number clones. CONGAS+ clusters cells into tumour subclones with similar ploidy, rendering straightforward to compare their expression and chromatin profiles. The framework, implemented on GPU and tested on real and simulated data, scales to analyse seamlessly thousands of cells, demonstrating better performance than single-molecule models, and supporting new multi-omics assays. In prostate cancer, lymphoma and basal cell carcinoma, CONGAS+ successfully identifies complex subclonal architectures while providing a coherent mapping between ATAC and RNA, facilitating the study of genotype-phenotype maps and their connection to genomic instability.

Integrative analysis of a novel super-enhancer-associated lncRNA prognostic signature and identifying LINC00945 in aggravating glioma progression

BACKGROUND

Super-enhancers (SEs), driving high-level expression of genes with tumor-promoting functions, have been investigated recently. However, the roles of super-enhancer-associated lncRNAs (SE-lncRNAs) in tumors remain undetermined, especially in gliomas. We here established a SE-lncRNAs expression-based prognostic signature to choose the effective treatment of glioma and identify a novel therapeutic target.

METHODS

Combined analysis of RNA sequencing (RNA-seq) data and ChIP sequencing (ChIP-seq) data of glioma patient-derived glioma stem cells (GSCs) screened SE-lncRNAs. Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) datasets served to construct and validate SE-lncRNA prognostic signature. The immune profiles and potential immuno- and chemotherapies response prediction value of the signature were also explored. Moreover, we verified the epigenetic activation mechanism of LINC00945 via the ChIP assay, and its effect on glioma was determined by performing the functional assay and a mouse xenograft model.

RESULTS

6 SE-lncRNAs were obtained and identified three subgroups of glioma patients with different prognostic and clinical features. A risk signature was further constructed and demonstrated to be an independent prognostic factor. The high-risk group exhibited an immunosuppressive microenvironment and was higher enrichment of M2 macrophage, regulatory T cells (Tregs), and Cancer-associated fibroblasts (CAFs). Patients in the high-risk group were better candidates for immunotherapy and chemotherapeutics. The SE of LINC00945 was further verified via ChIP assay. Mechanistically, BRD4 may mediate epigenetic activation of LINC00945. Additionally, overexpression of LINC00945 promoted glioma cell proliferation, EMT, migration, and invasion in vitro and xenograft tumor formation in vivo.

CONCLUSION

Our study constructed the first prognostic SE-lncRNA signature with the ability to optimize the choice of patients receiving immuno- and chemotherapies and provided a potential therapeutic target for glioma.