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.

Combinatorial Application of Papain and CD66B for Isolating Glioma- Associated Neutrophils.

BACKGROUND: Stromal cells in the tumor microenvironment play crucial roles in glioma development. Current methods for isolating tumor-associated stromal cells (such as neutrophils) are inefficient due to the conflict between tissue dissociation and cell surface protein protection, which hampers the research on patient-derived stromal cells. Our study aims to establish a novel method for isolating glioma-associated neutrophils (GANs). METHODS: To observe neutrophil-like polymorphonuclear cells, we performed Hematoxylin-Eosin staining on glioma tissues. For isolating single cells from glioma tissues, we evaluated the efficiency of tissue dissociation with FastPrep Grinder-mediated homogenization or proteases (trypsin or papain) digestion. To definite specific markers of GANs, fluorescence-activated cell sorting (FACS) and immunofluorescence staining were performed. FACS and Ficoll were performed for the separation of neutrophils from glioma tissue-derived single-cell or whole blood pool. To identify the isolated neutrophils, FACS and RT-PCR were carried out. RESULTS: Neutrophil-like cells were abundant in high-grade glioma tissues. Among the three tissue dissociation methods, papain digestion produced a 5.1-fold and 1.7-fold more living cells from glioma mass than physical trituration and trypsin digestion, respectively, and it preserved over 97% of neutrophil surface protein markers. CD66B could be adopted as a unique neutrophil surface protein marker for FACS sorting in glioma. Glioma-derived CD66B+ cells specifically expressed neutrophil marker genes. CONCLUSION: A combination of papain-mediated tissue dissociation and CD66B-mediated FACS sorting is an effective novel method for the isolation of GANs from glioma tissues.

LSM12 facilitates the progression of colorectal cancer by activating the WNT/CTNNB1 signaling pathway.

Aberrant activation of the WNT signaling pathway is a joint event in colorectal cancer (CRC), but the molecular mechanism is still unclear. Recently, RNA-splicing factor LSM12 (like-Sm protein 12) is highly expressed in CRC tissues. This study aimed to verify whether LSM12 is involved in regulating CRC progression via regulating the WNT signaling pathway. Here, we found that LSM12 is highly expressed in CRC patient-derived tissues and cells. LSM12 is involved in the proliferation, invasion, and apoptosis of CRC cells, similar to the function of WNT signaling in CRC. Furthermore, protein interaction simulation and biochemical experiments proved that LSM12 directly binds to CTNNB1 (also known as ß-Catenin) and regulates its protein stability to affect the CTTNB1-LEF1-TCF1 transcriptional complex formation and the associated WNT downstream signaling pathway. LSM12 depletion in CRC cells decreased the in vivo tumor growth through repression of cancer cell growth and acceleration of cancer cell apoptosis. Taken together, we suggest that the high expression of LSM12 is a novel factor leading to aberrant WNT signaling activation, and that strategies targeting this molecular mechanism may contribute to developing a new therapeutic method for CRC.

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.