Single‐cell <scp>RNA</scp> sequencing reveals tumor heterogeneity, microenvironment, and drug‐resistance mechanisms of recurrent glioblastoma

Wu, Haibin; Guo, Chengcheng; Wang, Chaoye; Xu, Jiang; Zheng, Suyue; Duan, Jian; Li, Yiyun; Bai, Hongming; Xu, Qian; Ning, Fangling; Wang, Feng; Yang, Qiulan

doi:10.1111/cas.15773

Cited by 15 publications

(8 citation statements)

References 47 publications

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“…Conventional scRNA-seq technologies encounter limitations when attempting to utilize matched primary-recurrent samples from the same patients for longitudinal clinical study 37 . This limitation can potentially result in the omission of crucial information regarding tumor progression.…”

Section: Resultsmentioning

confidence: 99%

An automated archival single-nucleus total RNA sequencing platform mapping integrative and retrospective cell atlas of gliomas

Xu,

Chen,

Lin

et al. 2023

Preprint

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Single-cell RNA sequencing (scRNA-seq) has dramatically transformed biomedical research within laboratory settings. It has been extensively employed to investigate the heterogeneity and plasticity of glioma, the most prevalent brain tumor. However, the clinical diagnosis and treatment of glioma remain complex and challenging, highlighting the need for comprehensive cancer research. Currently available scRNA-seq platforms are insufficient to fulfill the demands posed by large-scale clinical applications. Here, we present an automated high-throughput single-nucleus total RNA sequencing platform, known as AAsnRandom-seq. This platform integrates automated single-nucleus isolation and droplet barcoding systems with the random primer-based scRNA-seq chemistry, designed to accommodate a diverse range of sample types. The performance and versatility of AAsnRandom-seq are validated using over one hundred clinical FFPE and frozen samples. AAsnRandom-seq was applied to archival FFPE samples of various glioma subtypes, including rare clinical samples, and matched primary-recurrent glioblastomas (GBMs), delving into the comprehensive molecular characteristic of glioma at single-cell level. Abundant non-coding RNAs (ncRNAs) with distinct expression profiles within different glioma clusters are detected. Promising recurrence-related targets and pathways are identified from the matched primary-recurrent GBMs. AAsnRandom-seq holds significant application value on large-scale integrative and retrospective clinical research using archived specimens.

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Section: Resultsmentioning

confidence: 99%

An automated archival single-nucleus total RNA sequencing platform mapping integrative and retrospective cell atlas of gliomas

Xu,

Chen,

Lin

et al. 2023

Preprint

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“…2 A, B) raises an intriguing question as to whether the molecular transition seen in rGBM cells is attributed to the change of the whole population of tumor cells or preferentially a subset of cells, which cannot be fully addressed by bulk sample data [ 42 ]. On the other hand, the heterogeneity of rGBM cells has just begun to be studied and how tumor cells at recurrence behave differently is incompletely understood [ 15 , 24 , 42 , 59 ]. To tackle the above question and explore the heterogeneity of rGBM, we retrieved the GBM cells across the longitudinal samples and performed clustering analysis according to their transcriptomic similarity.…”

Section: Resultsmentioning

confidence: 99%

“…Recent studies reported several cellular and molecular changes at GBM recurrence, such as mesenchymal transition with decreased proneuronal state, increased proportion of oligodendrocytes, and enriched ECM signatures, revealing a systematic context shift of the tumor and neighborhood [ 14 – 17 , 23 , 24 , 59 , 76 ]. Thus, the comprehensive characterization of rGBM tissues in comparison to pGBM is indispensable for understanding the molecular mechanism of relapse and searching specific therapeutic targets [ 41 ].…”

Section: Discussionmentioning

confidence: 99%

Decoding key cell sub-populations and molecular alterations in glioblastoma at recurrence by single-cell analysis

Wang,

Sun,

Wang

et al. 2023

acta neuropathol commun

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Glioblastoma (GBM) is the most frequent malignant brain tumor, the relapse of which is unavoidable following standard treatment. However, the effective treatment for recurrent GBM is lacking, necessitating the understanding of key mechanisms driving tumor recurrence and the identification of new targets for intervention. Here, we integrated single-cell RNA-sequencing data spanning 36 patient-matched primary and recurrent GBM (pGBM and rGBM) specimens, with 6 longitudinal GBM spatial transcriptomics to explore molecular alterations at recurrence, with each cell type characterized in parallel. Genes involved in extracellular matrix (ECM) organization are preferentially enriched in rGBM cells, and MAFK is highlighted as a potential regulator. Notably, we uncover a unique subpopulation of GBM cells that is much less detected in pGBM and highly expresses ECM and mesenchyme related genes, suggesting it may contribute to the molecular transition of rGBM. Further regulatory network analysis reveals that transcription factors, such as NFATC4 and activator protein 1 members, may function as hub regulators. All non-tumor cells alter their specific sets of genes as well and certain subgroups of myeloid cells appear to be physically associated with the mesenchyme-like GBM subpopulation. Altogether, our study provides new insights into the molecular understanding of GBM relapse and candidate targets for rGBM treatment.

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“…Based on the aforementioned evidence, EVs appear to be fundamental in understanding glioma interplay with the microenvironment. However, they appear to be heterogeneous, like the several cell populations found in tumor tissue [10,121]. Profiling the EVs based on the cells of origin would provide insights into elucidating the molecular content and the interactions occurring between human glioma, astrocytes, and myeloid cells.…”

Section: Methodsmentioning

confidence: 99%

The Interplay between Glioblastoma Cells and Tumor Microenvironment: New Perspectives for Early Diagnosis and Targeted Cancer Therapy

Virtuoso,

D’Amico,

Scalia

et al. 2024

Brain Sciences

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Glioblastoma multiforme (GBM) stands out as the most tremendous brain tumor, constituting 60% of primary brain cancers, accompanied by dismal survival rates. Despite advancements in research, therapeutic options remain limited to chemotherapy and surgery. GBM molecular heterogeneity, the intricate interaction with the tumor microenvironment (TME), and non-selective treatments contribute to the neoplastic relapse. Diagnostic challenges arise from GBM advanced-stage detection, necessitating the exploration of novel biomarkers for early diagnosis. Using data from the literature and a bioinformatic tool, the current manuscript delineates the molecular interplay between human GBM, astrocytes, and myeloid cells, underscoring selected protein pathways belonging to astroglia and myeloid lineage, which can be considered for targeted therapies. Moreover, the pivotal role of extracellular vesicles (EVs) in orchestrating a favorable microenvironment for cancer progression is highlighted, suggesting their utility in identifying biomarkers for GBM early diagnosis.

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Single‐cell RNA sequencing reveals tumor heterogeneity, microenvironment, and drug‐resistance mechanisms of recurrent glioblastoma

Cited by 15 publications

References 47 publications

An automated archival single-nucleus total RNA sequencing platform mapping integrative and retrospective cell atlas of gliomas

An automated archival single-nucleus total RNA sequencing platform mapping integrative and retrospective cell atlas of gliomas

Decoding key cell sub-populations and molecular alterations in glioblastoma at recurrence by single-cell analysis

The Interplay between Glioblastoma Cells and Tumor Microenvironment: New Perspectives for Early Diagnosis and Targeted Cancer Therapy

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