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Because of the complexity of cancer‐immune system interactions, combinations of biomarkers will be required for predicting individual patient responses to treatment and for monitoring combination strategies to overcome treatment resistance. To this end, the “immunogram” has been proposed as a comprehensive framework to capture all relevant immunological variables. Here, we developed a method to convert transcriptomic data into immunogram scores (IGS). This immunogram includes 10 molecular profiles, consisting of innate immunity, priming and activation, T cell response, interferon γ (IFNG) response, inhibitory molecules, regulatory T cells, myeloid‐derived suppressor cells (MDSCs), recognition of tumor cells, proliferation, and glycolysis. Using genes related to these 10 parameters, we applied single‐sample gene set enrichment analysis (ssGSEA) to 9417 bulk RNA‐Seq data from 9362 cancer patients with 29 different solid cancers in The Cancer Genome Atlas (TCGA). Enrichment scores were z‐score normalized (Z) for each cancer type or the entire TCGA cohort. The IGS was defined by the formula IGS = 3 + 1.5 × Z so that patients would be well distributed over a range of scores from 1 to 5. The immunograms constructed in this way for all individual patients in the entire TCGA cohort can be accessed at “The RNA‐Seq based Cancer Immunogram Web” (https://yamashige33.shinyapps.io/immunogram/). We propose a novel scoring and visualization method for “immunogram” to assess the cancer immunity status of individual patients using the large TCGA dataset and RNA‐Seq of each patient. Immunograms for each individual will be a useful tool for precision immuno‐oncology, although their application needs to be validated in clinical trials.

Understanding the tumor microenvironment (TME) and anti-tumor immune responses in gastric cancer are required for precision immune-oncology. Taking advantage of next-generation sequencing technology, the feasibility and reliability of transcriptome-based TME analysis were investigated. TME of 30 surgically resected gastric cancer tissues was analyzed by RNA-Seq, immunohistochemistry (IHC) and flow cytometry (FCM). RNA-Seq of bulk gastric cancer tissues was computationally analyzed to evaluate TME. Computationally analyzed immune cell composition was validated by comparison with cell densities established by IHC and FCM from the same tumor tissue. Immune cell infiltration and cellular function were also validated with IHC and FCM. Cell proliferation and cell death in the tumor as assessed by RNA-Seq and IHC were compared. Computational tools and gene set analysis for quantifying CD8 + T cells, regulatory T cells and B cells, T cell infiltration and functional status, and cell proliferation and cell death status yielded an excellent correlation with IHC and FCM data. Using these validated transcriptome-based analyses, the immunological status of gastric cancer could be classified into immune-rich and immune-poor subtypes. Transcriptome-based TME analysis is feasible and is valuable for further understanding the immunological status of gastric cancer.

The majority of low‐grade isocitrate dehydrogenase‐mutant (IDH mt ) gliomas undergo malignant progression (MP), but their underlying mechanism remains unclear. IDH mt gliomas exhibit global DNA methylation, and our previous report suggested that MP could be partly attributed to passive demethylation caused by accelerated cell cycles. However, during MP, there is also active demethylation mediated by ten‐eleven translocation, such as DNA hydroxymethylation. Hydroxymethylation is reported to potentially contribute to gene expression regulation, but its role in MP remains under investigation. Therefore, we conducted a comprehensive analysis of hydroxymethylation during MP of IDH mt astrocytoma. Five primary/malignantly progressed IDH mt astrocytoma pairs were analyzed with oxidative bisulfite and the Infinium EPIC methylation array, detecting 5‐hydroxymethyl cytosine at over 850,000 locations for region‐specific hydroxymethylation assessment. Notably, we observed significant sharing of hydroxymethylated genomic regions during MP across the samples. Hydroxymethylated CpGs were enriched in open sea and intergenic regions ( p  < 0.001), and genes undergoing hydroxymethylation were significantly associated with cancer‐related signaling pathways. RNA sequencing data integration identified 91 genes with significant positive/negative hydroxymethylation‐expression correlations. Functional analysis suggested that positively correlated genes are involved in cell‐cycle promotion, while negatively correlated ones are associated with antineoplastic functions. Analyses of The Cancer Genome Atlas clinical data on glioma were in line with these findings. Motif‐enrichment analysis suggested the potential involvement of the transcription factor KLF4 in hydroxymethylation‐based gene regulation. Our findings shed light on the significance of region‐specific DNA hydroxymethylation in glioma MP and suggest its potential role in cancer‐related gene expression and IDH mt glioma malignancy.

Glioblastoma (GBM) is a highly lethal brain tumor. The effectiveness of temozolomide (TMZ) treatment in GBM is linked to the methylation status of O6-methyl-guanine DNA methyltransferase ( ) promoter. Patients with unmethylated promoter have limited treatment options available. Consequently, there is a pressing need for alternative therapeutic strategies for such patients. Data, including transcriptomic and clinical information, as well as information on promoter methylation status in primary GBM, were obtained from The Cancer Genome Atlas (TCGA) (n=121) and Chinese Glioma Genome Atlas (CGGA) (n=83) datasets. Samples were categorized into high and low expression groups, MGMT-high (MGMT-H) and MGMT-low (MGMT-L) tumors. A comprehensive transcriptome analysis was conducted to explore the tumor-immune microenvironment. Furthermore, we integrated transcriptome data from 13 GBM patients operated at our institution with findings from tumor-infiltrating lymphocyte (TIL) cultures, specifically investigating their response to autologous tumors. Gene signatures associated with various immune cells, including CD8 T cells, helper T cells, B cells, and macrophages, were noted in MGMT-H tumors. Pathway analysis confirmed the enrichment of immune cell-related pathways. Additionally, biological processes involved in the activation of monocytes and lymphocytes were observed in MGMT-H tumors. Furthermore, TIL culture experiments showed a greater presence of tumor-reactive T cells in MGMT-H tumors compared to MGMT-L tumors. These findings suggest that MGMT-H tumors has a potential for enhanced immune response against tumors mediated by CD8 T cells. Our study provides novel insights into the immune cell composition of MGMT-H tumors, which is characterized by the infiltration of type 1 helper T cells and activated B cells, and also the presence of tumor-reactive T cells evidenced by TIL culture. These findings contribute to a better understanding of the immune response in MGMT-H tumors, emphasizing their potential for immunotherapy. Further studies are warranted to investigate on the mechanisms of expression and antitumor immunity.

Immune checkpoint inhibitors have been approved as second-line therapy for patients with advanced urothelial carcinoma (UC). However, which patients will obtain clinical benefit remains to be determined. To identify predictive biomarkers for the pembrolizumab (PEM) response early during treatment, the present study investigated 31 patients with chemotherapy-resistant recurrent or metastatic UC who received 200 mg PEM intravenously every 3 weeks. Blood was taken just before the first dose and again before the second dose, and the peripheral blood mononuclear cells of all 31 pairs of blood samples were immune phenotyped by flow cytometry. Data were assessed by principal component analysis (PCA), correlation analysis and Cox proportional hazards modeling in order to comprehensively determine the effects of PEM on peripheral mononuclear immune cells. Absolute counts of CD45RA+CD27-CCR7- terminally differentiated CD8+ T cells and KLRG1+CD57+ senescent CD8+ T cells were significantly increased after PEM administration (P=0.042 and P=0.043, respectively). Senescent and exhausted CD4+ and CD8+ T cell dynamics were strongly associated with each other. By contrast, counts of monocytic myeloid-derived suppressor cells (mMDSCs) were not associated with other immune cell phenotypes. The results of PCA and non-hierarchical clustering of patients suggested that excessive T cell senescence and differentiation early during treatment were not necessarily associated with a survival benefit. However, decreased mMDSC counts after PEM were associated with improved overall survival. In conclusion, early on-treatment peripheral T cell status was associated with response to PEM; however, it was not associated with clinical benefit. By contrast, decreased peripheral mMDSC counts did predict improved overall survival.

Ependymomas encompass multiple clinically relevant tumor types based on localization and molecular profiles. Tumors of the methylation class “spinal ependymoma” (SP-EPN) represent the most common intramedullary neoplasms in children and adults. However, their developmental origin is ill-defined, molecular data are scarce, and the potential heterogeneity within SP-EPN remains unexplored. The only known recurrent genetic events in SP-EPN are loss of chromosome 22q and NF2 mutations, but neither types and frequency of these alterations nor their clinical relevance have been described in a large, epigenetically defined series. Transcriptomic ( n  = 72), epigenetic ( n  = 225), genetic ( n  = 134), and clinical data ( n  = 112) were integrated for a detailed molecular overview on SP-EPN. Additionally, we mapped SP-EPN transcriptomes to developmental atlases of the developing and adult spinal cord to uncover potential developmental origins of these tumors. The integration of transcriptomic ependymoma data with single-cell atlases of the spinal cord revealed that SP-EPN display the highest similarities to mature adult ependymal cells. Unsupervised hierarchical clustering of transcriptomic data together with integrated analysis of methylation profiles identified two molecular SP-EPN subtypes. Subtype A tumors primarily carried previously known germline or sporadic NF2 mutations together with 22q loss (bi-allelic NF2 loss), resulting in decreased NF2 expression. Furthermore, they more often presented as multilocular disease and demonstrated a significantly reduced progression-free survival as compared to SP-EP subtype B. In contrast, subtype B predominantly contained samples without NF2 mutation detected in sequencing together with 22q loss (monoallelic NF2 loss). These tumors showed regular NF2 expression but more extensive global copy number alterations. Based on integrated molecular profiling of a large multi-center cohort, we identified two distinct SP-EPN subtypes with important implications for genetic counseling, patient surveillance, and drug development priorities.