The CEBPB+ glioblastoma subcluster specifically drives the formation of M2 tumor-associated macrophages to promote malignancy growth.

Rationale: The heterogeneity of tumor cells within the glioblastoma (GBM) microenvironment presents a complex challenge in curbing GBM progression. Understanding the specific mechanisms of interaction between different GBM cell subclusters and non-tumor cells is crucial. Methods: In this study, we utilized a comprehensive approach integrating glioma single-cell and spatial transcriptomics. This allowed us to examine the molecular interactions and spatial localization within GBM, focusing on a specific tumor cell subcluster, GBM subcluster 6, and M2-type tumor-associated macrophages (M2 TAMs). Results: Our analysis revealed a significant correlation between a specific tumor cell subcluster, GBM cluster 6, and M2-type TAMs. Further in vitro and in vivo experiments demonstrated the specific regulatory role of the CEBPB transcriptional network in GBM subcluster 6, which governs its tumorigenicity, recruitment of M2 TAMs, and polarization. This regulation involves molecules such as MCP1 for macrophage recruitment and the SPP1-Integrin αvß1-Akt signaling pathway for M2 polarization. Conclusion: Our findings not only deepen our understanding of the formation of M2 TAMs, particularly highlighting the differential roles played by heterogeneous cells within GBM in this process, but also provided new insights for effectively controlling the malignant progression of GBM.

Amplifying colorectal cancer progression: impact of a PDIA4/SP1 positive feedback loop by circPDIA4 sponging miR-9-5p.

OBJECTIVE: Colorectal cancer (CRC) is a prevalent malignant tumor with a high fatality rate. CircPDIA4 has been shown to have a vital role in cancer development by acting as a facilitator. Nevertheless, the impact of the circPDIA4/miR-9-5p/SP1 axis on development of CRC has not been studied. METHODS: Western blot, immunohistochemistry, and reverse transcription-quantitative polymerase chain reaction assays were used to analyze gene expression. The CCK-8 assay was used to assess cell growth. The Transwell assay was used to detect invasion and migration of cells. The luciferase reporter and RNA immunoprecipitation tests were used to determine if miR-9-5p and circPDIA4 (or SP1) bind to one another. An in vivo assay was used to measure tumor growth. RESULTS: It was shown that circPDIA4 expression was greater in CRC cell lines and tissues than healthy cell lines and tissues. CircPDIA4 knockdown prevented the invasion, migration, and proliferation of cells in CRC. Additionally, the combination of circPDIA4 and miR-9-5p was confirmed, as well as miR-9-5p binding to SP1. Rescue experiments also showed that the circPDIA4/miR-9-5p/SP1 axis accelerated the development of CRC. In addition, SP1 combined with the promoter region of circPDIA4 and induced circPDIA4 transcription. CircPDIA4 was shown to facilitate tumor growth in an in vivo assay. CONCLUSIONS: The circPDIA4/miR-9-5p/SP1 feedback loop was shown to aggravate CRC progression. This finding suggests that the ceRNA axis may be a promising biomarker for CRC patient treatment.

Identification of Neural Progenitor Cell-associated Chemoradiotherapy Resistance Gene Set (ARL4C, MSN, TNFAIP6) for Prognosis of Glioma.

BACKGROUND: Glioma is the most common malignant intracranial tumor with high lethality. Despite surgery combined with chemoradiotherapy, the prognosis for patients with glioma remains poor. This is primarily due to acquired chemoradiotherapy resistance. Therefore, to improve the prognosis of glioma, further study into the mechanism of chemoradiotherapy resistance is needed. OBJECTIVE: This study aimed to (1) evaluate the prognosis of patients with glioma by using a prognostic risk score model constructed by chemoradiotherapy resistance genes, (2) provide new targets and directions for precise treatment of glioma, and (3) discuss the tumor heterogeneity of tumor cells. METHODS: According to therapy class and overall survival (OS), we identified 53 genes associated with glioma chemoradiotherapy resistance in The Cancer Genome Atlas Glioblastoma (TCGA GBM) database. Considering the important role of chemoradiotherapy resistance-related genes in the prognosis of glioma, we preliminarily screened and identified vital prognostic factors among these genes by using the Cox regression model of absolute contraction and selection operators in the TCGA GBM lower-grade glioma (TCGA GBMLGG) dataset. Next, the heterogeneity of the chemoradiotherapy resistance-associated genes in different glioma cells was revealed by single-cell sequencing in the GSE117891 cohort. RESULTS: A prognostic risk score model consisting of three genes (ARL4C, MSN, TNFAIP6) was constructed. The expression of this model was high in glioma neural progenitor cells (NPCs) and low in glioma oligodendrocytes. The OS rates were significantly lower in the high- vs. low-risk group. CONCLUSION: Our 3 gene risk score complements the current glioma diagnosis and provides a novel insight into chemoradiotherapy resistance mechanisms for the prognosis of patients with glioma.