S100A11 Promotes Glioma Cell Proliferation and Predicts Grade-Correlated Unfavorable Prognosis

Identification of Lower Grade Glioma Antigens Based on Ferroptosis Status for mRNA Vaccine Development

Purpose

mRNA vaccines represent a promising and innovative strategy within the realm of cancer immunotherapy. However, their efficacy in treating lower-grade glioma (LGG) requires evaluation. Ferroptosis exhibits close associations with the initiation, evolution, and suppression of cancer. In this study, we explored the landscape of the ferroptosis-associated tumor microenvironment to facilitate the development of mRNA vaccines for LGG patients.

Patients and Methods

Genomic and clinical data of the LGG patients was obtained from the Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. Ferroptosis-related tumor antigens were identified based on differential expression, mutation status, correlation with antigen-presenting cells, and prognosis, relevance to immunogenic cell death (ICD). Antigen expression levels in LGG specimens and cell lines were validated using real time-polymerase chain reaction (RT-PCR). Consensus clustering was employed for patient classification. The immune landscapes of ferroptosis subtypes were further characterized, including immune responses, prognostic ability, tumor microenvironment, and tumor-related signatures.

Results

Five tumor antigens, namely, HOTAIR, IDO1, KIF20A, NR5A2, and RRM2 were identified in LGG. RT-PCR demonstrated higher expression of these genes in LGG compared to the control. Twelve gene modules and four ferroptosis subtypes (FS1-FS4) of LGG were defined. FS2 and FS4, characterized as "cold" tumors due to their decreased tumor mutation burden (TMB) and immune checkpoint proteins (ICPs), were deemed appropriate candidates for the mRNA vaccine.

Conclusion

HOTAIR, IDO1, KIF20A, NR5A2, and RRM2 were identified as promising candidate antigens for the development of an LGG mRNA vaccine, particularly offering potential benefits to FS2 and FS4 patients.

Modeling the Annexin A1-S100A11 heterotetramer: a molecular dynamics investigation of structure and correlated motion

Annexin A1 (A1) has been shown to form a tetrameric complex (A1t) with S100A11 which is implicated in calcium homeostasis and EGFR pathways. In this work, a full-length model of the A1t was generated for the first time. Multiple molecular dynamics simulations were performed on the complete A1t model for several hundred nanoseconds each to assess the structure and dynamics of A1t. These simulations yielded three structures for the A1 N-terminus (ND) which were identified via principal component analysis. The orientations and interactions of the first 11 A1-ND residues for all three structures were conserved, and their binding modes were strikingly similar to those of the Annexin A2 N-terminus in the Annexin A2-p11 tetramer. In this study, we provided detailed atomistic information for the A1t. Strong interactions were identified within the A1t between the A1-ND and both S100A11 monomers. Residues M3, V4, S5, E6, L8, K9, W12, E15, and E18 of A1 were the strongest interactions between A1 and the S100A11 dimer. The different conformations of the A1t were attributed to the interaction between W12 of the A1-ND with M63 of S100A11 which caused a kink in the A1-ND. Cross-correlation analysis revealed strong correlated motion throughout the A1t. Strong positive correlation was observed between the ND and S100A11 in all simulations regardless of conformation. This work suggests that the stable binding of the first 11 residues of A1-ND to S100A11 is potentially a theme for Annexin-S100 complexes and that the flexibility of the A1-ND allows for multiple conformations of the A1t.Communicated by Ramaswamy H. Sarma.

Exploring the prognostic value of S100A11 and its association with immune infiltration in breast cancer

Breast cancer (BC) is a severe danger to women's lives and health globally. S100A11 is aberrantly expressed in many carcinomas and serves a crucial function in cancer development. However, the role of S100A11 in BC is unclear. In this study, we utilized multiple databases and online tools, including the TCGA database, cBioPortal, and STRING, to evaluate the significance of S100A11 in BC prognosis and immune infiltration. We found that S100A11 was considerably more abundant in BC tissues. Survival analysis indicated that individuals with S100A11 high expression of BC had shorter overall survival. Multivariate Cox regression analysis revealed that high S100A11 expression independently influenced the poor outcome of patients with BC (HR = 1.738, 95%CI 1.197-2.524). Our nomogram incorporating five factors, including S100A11, age, clinical stage, N, and M, was developed to anticipate the survival probability in BC prognosis. The model demonstrated good consistency and accuracy. Furthermore, the mutation rete of S100A11 was 14%. Survival analysis suggested that breast cancer patients with S100A11 mutation had a worse prognosis. KEGG pathway enrichment analysis revealed that S100A11 may be mainly involved in the IL-17 signaling pathway. Finally, we discovered a correlation between S100A11 expression and immune cell infiltration on BC. S100A11 expression was positively associated with 17 immune checkpoint-related genes. In conclusion, this study indicates that S100A11 may contribute to a worse prognosis for BC and potentially has a significant impact through its influence on immune cell infiltration and the IL-17 signaling pathway.

A large-scale targeted proteomics of serum and tissue shows the utility of classifying high grade and low grade meningioma tumors

BACKGROUND

Meningiomas are the most prevalent primary brain tumors. Due to their increasing burden on healthcare, meningiomas have become a pivot of translational research globally. Despite many studies in the field of discovery proteomics, the identification of grade-specific markers for meningioma is still a paradox and requires thorough investigation. The potential of the reported markers in different studies needs further verification in large and independent sample cohorts to identify the best set of markers with a better clinical perspective.

METHODS

A total of 53 fresh frozen tumor tissue and 51 serum samples were acquired from meningioma patients respectively along with healthy controls, to validate the prospect of reported differentially expressed proteins and claimed markers of Meningioma mined from numerous manuscripts and knowledgebases. A small subset of Glioma/Glioblastoma samples were also included to investigate inter-tumor segregation. Furthermore, a simple Machine Learning (ML) based analysis was performed to evaluate the classification accuracy of the list of proteins.

RESULTS

A list of 15 proteins from tissue and 12 proteins from serum were found to be the best segregator using a feature selection-based machine learning strategy with an accuracy of around 80% in predicting low grade (WHO grade I) and high grade (WHO grade II and WHO grade III) meningiomas. In addition, the discriminant analysis could also unveil the complexity of meningioma grading from a segregation pattern, which leads to the understanding of transition phases between the grades.

CONCLUSIONS

The identified list of validated markers could play an instrumental role in the classification of meningioma as well as provide novel clinical perspectives in regard to prognosis and therapeutic targets.

miR-21-5p Inhibits the Proliferation, Migration, and Invasion of Glioma by Targeting S100A10

S100A10, a member of the S100 protein family, is upregulated in multiple human malignancies and plays a key role in regulating tumor progression. This study aimed to reveal the underlying mechanism by which S100A10 in regulates the proliferation, migration, and invasion of glioma. The expression and clinical information data of S100A10 were downloaded from public databases (TCGA, CGGA, and GEPIA2). S100A10 expression levels in glioma tumor tissues and adjacent nontumor tissues were compared by immunohistochemistry (IHC). The functional roles of S100A10 in glioma were assessed by cell counting kit-8 (CCK-8) cell proliferation assay, wound healing assay, transwell assay, and flow cytometry. miRDB and double luciferase assay were used to predict and identify potential S100A10 mRNA-complementary miRNAs, and the roles of miR-21-5p in glioma cell were examined by targeted knockdown or overexpression miR-21-5p in glioma cell lines. We found that S100A10 was overexpressed in glioma tissues and predicted a worse prognosis. S100A10 knockdown significantly inhibited glioma cell proliferation, invasion, and migration. Furthermore, we demonstrated that miR-21-5p inhibits glioma proliferation, migration, and invasion by targeting S100A10. This study showed S100A10 was a new prognostic predictor among glioma patients and provided new insights into the pathogenesis of gliomas, suggesting that miR-21-5p /S100A10 axis may serve as a valuable therapeutic target for glioma.

S100A11: A Potential Carcinogen and Prognostic Marker That Correlates with the Immunosuppressive Microenvironment in Pan-Cancer

S100 calcium-binding protein A11 (S100A11) has been proved to be an oncogene of most tumors. However, its role in the tumor microenvironment (TME) in pan-cancer stills remains poorly understood. This study used public data from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) database to evaluate the expression of S100A11. The R package "GSVA" was used for Gene set variation analysis (GSVA) of S100A11. The R package "ESTIMATE" was used to further explore the relationship between S100A11 and TME. The Genomics of Drug Sensitivity in Cancer database was used to investigate the effect of S100A11 on the efficiency of anticancer drugs. We found S100A11 expression was upregulated in most tumors and predicted a poor prognosis. Furthermore, S100A11 expression was closely associated with immune regulation-related pathways. Moreover, S100A11 expression in pan-cancer was significantly related to most immunosuppressive cells, such as tumor-associated macrophages (TAM), tumor-associated fibroblasts (TAF), and Treg cells. The expression of S100A11 was significantly related to immunosuppressive genes and immune checkpoints in most tumor types. Additionally, the upregulation of S100A11 expression made patients with cancer resistant to the treatment of most anticancer drugs, such as sorafenib. In brief, our study showed that S100A11 could be used as a potential carcinogen and prognostic marker for most tumor types. The increased expression of S100A11 was closely related to tumor immunosuppressive TME. The upregulation of S100A11 expression made patients with cancer resistant to sorafenib treatment.

Analysis of Clinical Characteristics and Risk Factors of Postoperative Recurrence and Malignant Transformation of Low-Grade Glioma

This research was developed to explore the clinical characteristics and related risk factors of postoperative recurrence and malignant transformation of low-grade glioma (LGG). The subjects were rolled into observation group (19 cases) and control group (51 cases) according to recurrence and malignant transformation during the follow-up period. The clinical data of the two groups were compared, and the risk factors of recurrence and malignant transformation were analyzed with the time of recurrence and malignant transformation as independent variables. The experimental results showed that the proportion of patients aged over 45 years in the observation group (63.16%) was higher than that in the control group (50.98%). The proportion of preoperative functional status score (KPS) ≥80 in the observation group (68.42%) was lower than that in the control group (78.43%). The proportion of patients with tumor over 5 cm in the control group (27.45%) was lower than that in the observation group (52.63%), and the proportion of total resection of tumor in the control group (47.06%) was higher than that in the observation group (21.05%). Furthermore, the multivariate analysis showed that preoperative KPS score, preoperative duration of disease, resection scope, postoperative treatment, oncotesticular antigen (OY-TES-1) mRNA, P53, mouse double microbody amplification gene (MDM2), vascular endothelial growth factor (VEGF), and epidermal growth factor receptor (EGFR) were independent risk factors (all P < 0.05). In summary, patients with postoperative recurrence and malignant transformation had poorer physical condition and higher degree of malignancy before surgery. Preoperative KPS score, duration of disease, surgical resection scope, postoperative treatment, OY-TES-1 mRNA, P53, MDM2, VEGF, and EGFR were the risk factors.

DRAXIN as a Novel Diagnostic Marker to Predict the Poor Prognosis of Glioma Patients

An increasing number of evidences have shown that the carcinogenic effect of DRAXIN plays an important role in the malignant process of tumors, but the mechanism of its involvement in glioma has not yet been revealed. The main aim of this study is to explore the relationship between DRAXIN and the prognosis and pathogenesis of glioma through a large quality of data analysis. Firstly, thousands of tissue samples with clinical information were collected based on various public databases. Then, a series of bioinformatics analyses were performed to mine data from information of glioma samples extracted from several reputable databases to reveal the key role of DRAXIN in glioma development and progression, with the confirmation of basic experiments. Our results showed that high expression of the oncogene DRAXIN in tumor tissue and cells could be used as an independent risk factor for poor prognosis in glioma patients and was strongly associated with clinical risk features. The reverse transcription-quantitative PCR technique was then utilized to validate the DRAXIN expression results we obtained. In addition, co-expression analysis identified, respectively, top 10 genes that were closely associated with DRAXIN positively or negatively. Finally, in vitro experiments demonstrated that knockdown of DRAXIN significantly inhibited proliferation and invasion of glioma cell. To sum up, this is the first report of DRAXIN being highly expressed in gliomas and leading to poor prognosis of glioma patients. DRAXIN may not only benefit to explore the pathogenesis of gliomas, but also serve as a novel biological target for the treatment of glioma.