Transcriptome analysis reveals tumor microenvironment changes in glioblastoma

Hoogstrate, Youri; Draaisma, Kaspar; Ghisai, Santoesha A.; Hijfte, Levi van; Barin, Nastaran; Heer, Iris de; Coppieters, Wouter; Bosch, Thierry P P van den; Bolleboom, Anne; Gao, Zhenyu; Vincent, Arnaud J P E; Karim, Latifa; Deckers, Manon; Taphoorn, Martin J.B.; Kerkhof, Marjon; Weyerbrock, Astrid; Sanson, Marc; Hoeben, Ann; Lukacova, Slávka; Lombardi, Giuseppe; Leenstra, Sieger; Hanse, Monique C.J.; Fleischeuer, Ruth; Watts, Colin; Angelopoulos, Nicos; Golfinopoulos, Vassilis; Bent, Martin J. van den; Robe, Pierre A.; French, Pim J.

doi:10.1016/j.ccell.2023.02.019

Cited by 102 publications

(86 citation statements)

References 50 publications

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“…9). This observation aligns with recent studies reporting frequent overexpression of these H3K9 methyltransferases in GBM, which correlates with adverse patient prognosis (39,40). Beyond its association with the G2/M checkpoint, our analysis revealed robust correlations between H3K9me3 MtSig and various immune response pathways, including the inflammatory response, interferon alpha response, and interferon gamma response.…”

Section: Discussionsupporting

confidence: 92%

Multi-omic Analysis Identifies Glioblastoma Dependency on H3K9me3 Methyltransferase Activity

Xie,

Du,

Ghosh

et al. 2024

Preprint

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Histone H3 Lysine 9 dimethylation or trimethylation (H3K9me2 or H3K9me3) marks more than half of the human genome, particularly in heterochromatin regions and specific genes within euchromatic regions. Enzymes catalyzing the methylation of H3K9 have individually been associated with the modulation of gene expression patterns involved in cancer progression, including suppressor of variegation 3-9 homologue 1 (SUV39H1), SUV39H2, SET domain bifurcated 1 (SETDB1), SETDB2, euchromatic histone-lysine N-methyltransferase 1 and 2 (EHMT1/2). However, a comprehensive comparison and understanding of the characteristics and mechanisms of these chromatin-modifying enzymes in cancers remains incompletely understood. In this study, we demonstrated that these six H3K9 methyltransferases differentially expressed in tumors and correlated expression with somatic copy number variations (CNVs) and DNA methylation patterns. Through integrative multi-omics analyses, we identified SUV39H1, SUV39H2, and SETDB1 as the key players among the six H3K9 methyltransferases that exhibited the most significant associations with cancer phenotypes. By incorporating SUV39H1, SUV39H2, and SETDB1, we developed a novel signature termed "H3K9me3 MtSig" (H3K9me3 methyltransferases signature). H3K9me3 MtSig was unique for various tumor types, had prognostic implications and was linked to significant signaling pathways, particularly in glioblastoma (GBM). Furthermore, elevated H3K9me3 MtSig was confirmed in GBM patient-derived cells and tissues. In addition, single-cell expression analysis of H3K9me3 MtSig in GBM tissues demonstrated a pattern related to the G2/M cell cycle and was negatively correlated with immune responses. H3K9me3-mediated repetitive sequence silencing by H3K9me3 MtSig, determined using ChIP-sequencing, contributed to these phenotypes, and inhibiting H3K9me3 MtSig in patient-derived GBM cells suppressed proliferation and increased immune responses. Translationally, H3K9me3 MtSig performed as an independent prognostic factor in a clinical prediction model, and drug susceptibility screening integrating H3K9me3 MtSig identified potential biomarkers and therapeutics for GBM. In summary, H3K9me3 MtSig has the potential to elucidate novel prognostic markers, therapeutic targets, and predictors of treatment response in GBM and other cancer types for clinical intervention.

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Section: Discussionsupporting

confidence: 92%

Multi-omic Analysis Identifies Glioblastoma Dependency on H3K9me3 Methyltransferase Activity

Xie,

Du,

Ghosh

et al. 2024

Preprint

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“…Additionally, ECM hi tumors upregulated numerous immune and stromal-related signatures (Figure 1F). Using data from the Ivy Glioblastoma Atlas Project (Ivy-GAP), we found that ECM low signature was preferentially expressed at the leading edge (LE) and infiltrative region (IT) of the tumor, which are known to consist largely of non-neoplastic cells (Puchalski et al 2018), whereas the ECM hi signature was upregulated in regions corresponding to microvascular proliferation (CTmvp) and hyperplastic blood vessels (CThbv), in line with a recent study by (Hoogstrate et al 2023) (Figure S1I). We also examined in situ hybridization (ISH) and adjacent hematoxylin and eosin (H&E) tissue sections annotated for the same histologic features.…”

Section: Unsupervised Analysis Of Extracellular Matrix Expression In ...supporting

confidence: 89%

Pan-cancer transcriptomic analysis of CNS tumor stroma identifies a population of perivascular fibroblasts that predict poor immunotherapy response in glioblastoma patients

Zarodniuk

Steele

Lü

et al. 2023

Preprint

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Excessive deposition of extracellular matrix (ECM) is a hallmark of solid tumors; however, it remains poorly understood which cellular and molecular components contribute to the formation of ECM stroma in central nervous system (CNS) tumors. Here, we undertook a pan-CNS analysis of retrospective gene expression datasets to characterize inter- and intra-tumoral heterogeneity of ECM remodeling signatures in both adult and pediatric CNS disease. We found that CNS lesions – glioblastoma in particular – can be divided into two ECM-based subtypes (ECMhi and ECMlo) that are influenced by the presence of perivascular cells resembling cancer-associated fibroblasts (CAFs). We show that perivascular fibroblasts activate chemoattractant signaling pathways to recruit tumor-associated macrophages, and promote an immune-evasive, stem-like cancer cell phenotype. Our analysis reveals that perivascular fibroblasts are correlated with unfavorable response to immune checkpoint blockade in glioblastoma and poor patient survival across a subset of CNS tumors. We provide insights into novel stroma-driven mechanisms underlying immune evasion and immunotherapy resistance in CNS tumors like glioblastoma, and discuss how targeting these perivascular fibroblasts may prove an effective approach to improving treatment response and patient survival in a variety of CNS tumors.

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“…In 11 tumours, we found a substantial correlation between HRD and NDE1, with 10 tumours (GBMLGG, LGG, LUAD, KIPAN, LIHC, MESO, PAAD, BLCA, ACC and KICH) showing a significant positive association and 1 tumour (TGCT) showing a significant negative association (Figure 6E). Along with tumour cells, non‐tumour cells such as immune cells, stromal cells and stromal cells in tumour tissues also play a role in the emergence and growth of tumours 25 . In 15 tumours, a strong correlation between NDE1 and tumour purity was discovered.…”

Section: Resultsmentioning

confidence: 99%

Comprehensive analysis indicated that NDE1 is a potential biomarker for pan‐cancer and promotes bladder cancer progression

Wang,

Ning,

Chen

et al. 2024

Cancer Medicine

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BackgroundThe nuclear distribution E homologue 1 (NDE1) is a crucial dynein binding partner. The NDE1 protein has the potential to disrupt the normal functioning of centrosomes, leading to a compromised ability to generate spindles and ensure precise separation of chromosomes during cell division. The potential consequences of this phenomenon include genomic instability, malignant transformation and the proliferation of neoplastic growths. However, studies examining the connection between NDE1 and cancer is still very rare.MethodsThe expression level, prognostic impact, gene change, DNA methylation, protein interaction, mRNA m6A modification, ceRNA network, associated gene and function enrichment, and immune‐related effects of NDE1 in pan‐cancer were examined using a range of online analytic tools and the R software package. The CCK‐8 test, transwell assay, scratch assay and colony formation assay were used to confirm the effects of NDE1 on the proliferation, invasion and metastasis of bladder cancer cells.ResultsNumerous tumour types have elevated NDE1, which is linked to a bad prognosis. NDE1 is an excellent diagnostic tool for many different types of cancer. Numerous malignancies have been linked to genetic changes in NDE1. NDE1 was connected to TMB, MSI, several immunological checkpoint genes and immune cell infiltration. NDE1 is linked to a number of immunological subtypes. NDE1 could affect how well immunotherapy works to treat different types of cancer. NDE1 was mostly associated with cell cycle, chromosomal segregation, DNA replication and mitotic segregation, according to GO and KEGG analyses. NDE1 physically binds to PAFAH1B1 and DCTN1, respectively. The proliferation, invasion and metastasis of bladder cancer cells may be prevented by NDE1 knockdown. Furthermore, knockdown of NDE1 promoted the apoptosis of bladder cancer cells.ConclusionHigh expression of NDE1 is present in a variety of tumours, which is linked to a bad prognosis for cancer. Knockdown of NDE1 inhibited the proliferation, invasion and metastasis of bladder cancer cells, and promoted the apoptosis. For a number of malignancies, NDE1 may be a biomarker for immunotherapy and prognosis.

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Transcriptome analysis reveals tumor microenvironment changes in glioblastoma

Cited by 102 publications

References 50 publications

Multi-omic Analysis Identifies Glioblastoma Dependency on H3K9me3 Methyltransferase Activity

Multi-omic Analysis Identifies Glioblastoma Dependency on H3K9me3 Methyltransferase Activity

Pan-cancer transcriptomic analysis of CNS tumor stroma identifies a population of perivascular fibroblasts that predict poor immunotherapy response in glioblastoma patients

Comprehensive analysis indicated that NDE1 is a potential biomarker for pan‐cancer and promotes bladder cancer progression

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