The N(6)-Methyladenosine-Modified Pseudogene HSPA7 Correlates With the Tumor Microenvironment and Predicts the Response to Immune Checkpoint Therapy in Glioblastoma.

Glioblastoma (GBM), one of the most aggressive tumors of the brain, has no effective or sufficient therapies. Identifying robust biomarkers for the response to immune checkpoint blockade (ICB) therapy, a promising treatment option for GBM patients, is urgently needed. We comprehensively evaluated lncRNA m6A modification patterns in m6A-sequencing (m6A-seq) data for GBM tissues and systematically investigated the immune and stromal regulators of these m6A-regulated lncRNAs. We used the single-sample gene-set enrichment analysis (ssGSEA) algorithm to investigate the difference in enriched tumor microenvironment (TME) infiltrating cells and the functional annotation of HSPA7 in individual GBM samples. Further, we validated that HSPA7 promoted the recruitment of macrophages into GBM TME in vitro, as well as in our GBM tissue section. We also explored its impact on the efficacy of ICB therapy using the patient-derived glioblastoma organoid (GBO) model. Here, we depicted the first transcriptome-wide m6A methylation profile of lncRNAs in GBM, revealing highly distinct lncRNA m6A modification patterns compared to those in normal brain tissues. We identified the m6A-modified pseudogene HSPA7 as a novel prognostic risk factor in GBM patients, with crucial roles in immunophenotype determination, stromal activation, and carcinogenic pathway activation. We confirmed that HSPA7 promoted macrophage infiltration and SPP1 expression via upregulating the YAP1 and LOX expression of glioblastoma stem cells (GSCs) in vitro and in our clinical GBM tumor samples. We also confirmed that knockdown of HSPA7 might increase the efficiency of anti-PD1 therapy utilizing the GBO model, highlighting its potential as a novel target for immunotherapy. Our results indicated that HSPA7 could be a novel immunotherapy target for GBM patients.

Zhao R ，Li B ，Zhang S ，He Z ，Pan Z ，Guo Q ，Qiu W ，Qi Y ，Zhao S ，Wang S ，Chen Z ，Zhang P ，Guo X ，Xue H ，Li G ... -  《Frontiers in Immunology》

TIGIT and PD-1 Immune Checkpoint Pathways Are Associated With Patient Outcome and Anti-Tumor Immunity in Glioblastoma.

Glioblastoma (GBM) remains an aggressive brain tumor with a high rate of mortality. Immune checkpoint (IC) molecules are expressed on tumor infiltrating lymphocytes (TILs) and promote T cell exhaustion upon binding to IC ligands expressed by the tumor cells. Interfering with IC pathways with immunotherapy has promoted reactivation of anti-tumor immunity and led to success in several malignancies. However, IC inhibitors have achieved limited success in GBM patients, suggesting that other checkpoint molecules may be involved with suppressing TIL responses. Numerous IC pathways have been described, with current testing of inhibitors underway in multiple clinical trials. Identification of the most promising checkpoint pathways may be useful to guide the future trials for GBM. Here, we analyzed the The Cancer Genome Atlas (TCGA) transcriptomic database and identified PD1 and TIGIT as top putative targets for GBM immunotherapy. Additionally, dual blockade of PD1 and TIGIT improved survival and augmented CD8+ TIL accumulation and functions in a murine GBM model compared with either single agent alone. Furthermore, we demonstrated that this combination immunotherapy affected granulocytic/polymorphonuclear (PMN) myeloid derived suppressor cells (MDSCs) but not monocytic (Mo) MDSCs in in our murine gliomas. Importantly, we showed that suppressive myeloid cells express PD1, PD-L1, and TIGIT-ligands in human GBM tissue, and demonstrated that antigen specific T cell proliferation that is inhibited by immunosuppressive myeloid cells can be restored by TIGIT/PD1 blockade. Our data provide new insights into mechanisms of GBM αPD1/αTIGIT immunotherapy.

Raphael I ，Kumar R ，McCarl LH ，Shoger K ，Wang L ，Sandlesh P ，Sneiderman CT ，Allen J ，Zhai S ，Campagna ML ，Foster A ，Bruno TC ，Agnihotri S ，Hu B ，Castro BA ，Lieberman FS ，Broniscer A ，Diaz AA ，Amankulor NM ，Rajasundaram D ，Pollack IF ，Kohanbash G ... -  《Frontiers in Immunology》

The Non-N(6)-Methyladenosine Epitranscriptome Patterns and Characteristics of Tumor Microenvironment Infiltration and Mesenchymal Transition in Glioblastoma.

An increasing number of RNA modification types other than N6-methyladenosine (m6A) modification have been detected. Nonetheless, the probable functions of RNA modifications beyond m6A in the tumor microenvironment (TME), mesenchymal (MES) transition, immunotherapy, and drug sensitivity remain unclear. We analyzed the characteristics of 32 non-m6A RNA modification regulators in 539 glioblastoma (GBM) patients and the TME cell infiltration and MES transition patterns. Using principal component analysis, a non-m6A epitranscriptome regulator score (RM score) model was established. We estimated the association between RM score and clinical characteristics, TME status, GBM subtypes, and drug and immunotherapy response. Three definite non-m6A RNA modification patterns associated with diverse biological pathways and clinical characteristics were identified. The high RM score group was characterized by a poor prognosis, enhanced immune infiltration, and MES subtype. Further analysis indicated that the high RM score group had a lower tumor mutation burden as well as a weaker response to immunotherapy. The higher RM score group may benefit more from drugs targeting the EGFR and WNT signaling pathways. Our study exposed the potential relationship of non-m6A RNA modification regulators with clinical features, TME status, and GBM subtype and clarified its therapeutic value.

Xu J ，Gao Z ，Liu K ，Fan Y ，Zhang Z ，Xue H ，Guo X ，Zhang P ，Deng L ，Wang S ，Wang H ，Wang Q ，Zhao R ，Li G ... -  《-》

Targeting MS4A4A: A novel pathway to improve immunotherapy responses in glioblastoma.

Glioblastoma (GBM) remains a challenging brain tumor to treat, with limited response to PD-1 immunotherapy due to tumor-associated macrophages (TAMs), specifically the M2 phenotype. This study explores the potential of MS4A4A (membrane spanning four domains, subfamily A, member 4A) inhibition in driving M2 macrophage polarization toward the M1 phenotype via the ferroptosis pathway to enhance the effectiveness of immunotherapy in GBM. Single-cell RNA sequencing and spatial transcriptomic analyses were employed to characterize M2 macrophages and MS4A4A expression in GBM. In vitro studies utilizing TAM cultures, flow cytometry, and western blot validations were conducted to assess the impact of MS4A4A on the tumor immune microenvironment and M2 macrophage polarization. In vivo models, including subcutaneous and orthotopic transplantation in mice, were utilized to evaluate the effects of MS4A4A knockout and combined immune checkpoint blockade (ICB) therapy on tumor growth and response to PD-1 immunotherapy. Distinct subsets of GBM-associated macrophages were identified, with spatial distribution in tumor tissue elucidated. In vivo experiments demonstrated that inhibiting MS4A4A and combining ICB therapy effectively inhibited tumor growth, reshaped the tumor immune microenvironment by reducing M2 TAM infiltration and enhancing CD8+ T-cell infiltration, ultimately leading to complete tumor eradication. MS4A4A inhibition shows promise in converting M2 macrophages to M1 phenotype via ferroptosis, decreasing M2-TAM infiltration, and enhancing GBM response to PD-1 immunotherapy. These findings offer a novel approach to developing more effective immunotherapeutic strategies for GBM.

Shao G ，Cui X ，Wang Y ，Luo S ，Li C ，Jiang Y ，Cai D ，Li N ，Li X ... -  《-》

Machine learning revealed stemness features and a novel stemness-based classification with appealing implications in discriminating the prognosis, immunotherapy and temozolomide responses of 906 glioblastoma patients.

Glioblastoma (GBM) is the most malignant and lethal intracranial tumor, with extremely limited treatment options. Immunotherapy has been widely studied in GBM, but none can significantly prolong the overall survival (OS) of patients without selection. Considering that GBM cancer stem cells (CSCs) play a non-negligible role in tumorigenesis and chemoradiotherapy resistance, we proposed a novel stemness-based classification of GBM and screened out certain population more responsive to immunotherapy. The one-class logistic regression algorithm was used to calculate the stemness index (mRNAsi) of 518 GBM patients from The Cancer Genome Atlas (TCGA) database based on transcriptomics of GBM and pluripotent stem cells. Based on their stemness signature, GBM patients were divided into two subtypes via consensus clustering, and patients in Stemness Subtype I presented significantly better OS but poorer progression-free survival than Stemness Subtype II. Genomic variations revealed patients in Stemness Subtype I had higher somatic mutation loads and copy number alteration burdens. Additionally, two stemness subtypes had distinct tumor immune microenvironment patterns. Tumor Immune Dysfunction and Exclusion and subclass mapping analysis further demonstrated patients in Stemness Subtype I were more likely to respond to immunotherapy, especially anti-PD1 treatment. The pRRophetic algorithm also indicated patients in Stemness Subtype I were more resistant to temozolomide therapy. Finally, multiple machine learning algorithms were used to develop a 7-gene Stemness Subtype Predictor, which were further validated in two external independent GBM cohorts. This novel stemness-based classification could provide a promising prognostic predictor for GBM and may guide physicians in selecting potential responders for preferential use of immunotherapy.

Wang Z ，Wang Y ，Yang T ，Xing H ，Wang Y ，Gao L ，Guo X ，Xing B ，Wang Y ，Ma W ... -  《-》