Glioma progression is shaped by genetic evolution and microenvironment interactions

Varn, Frederick S.; Johnson, Kevin C.; Martínek, Jan; Huse, Jason T.; Nasrallah, MacLean P.; Wesseling, Pieter; Cooper, Lee; Malta, Tathiane; Wade, Taylor; Sabedot, Thaís; Brat, Daniel J.; Gould, Peter; Wöehrer, Adelheid; Aldape, Kenneth; Ismail, Azzam; Sivajothi, Santhosh; Barthel, Floris P.; Kim, Hoon; Kocakavuk, Emre; Ahmed, Nazia; White, Kieron; Datta, Indrani; Moon, Hyo-Eun; Pollock, Steven; Goldfarb, Christine N; Lee, Ga-Hyun; Garofano, Luciano; Anderson, Kevin J.; Nehar-Belaid, Djamel; Barnholtz‐Sloan, Jill S.; Bakas, Spyridon; Byrne, Annette T.; D’Angelo, Fulvio; Gan, Hui; Khasraw, Mustafa; Migliozzi, Simona; Ormond, D. Ryan; Paek, Sun Ha; Meir, Erwin G. Van; Walenkamp, Annemiek; Watts, Colin; Weiss, Tobias; Weller, Michael; Palucka, Karolina; Stead, Lucy F.; Poisson, Laila; Noushmehr, Houtan; Iavarone, Antonio; Verhaak, Roel G.W.

doi:10.1016/j.cell.2022.04.038

Cited by 191 publications

(203 citation statements)

References 81 publications

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“…High infiltration of immunosuppressive myeloid and lymphoid cell populations negatively correlates with patient prognosis and therapy response in GBM (19,25,(27)(28)(29). Notably, most infiltrating immune cells in GBM are of myeloid origin (e.g., monocyte-derived macrophages, brain-resident microglia, and MDSCs) and are defined by a variety of pro-tumor phenotypes that function to suppress the anti-tumor immune response (20,24,26,(30)(31)(32). Beyond their direct immune suppressive functions, pro-tumor myeloid populations (i.e., TAMs, microglia, and MDSCs) promote GBM growth, invasion, and angiogenesis (33)(34)(35)(36)(37)(38)(39).…”

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confidence: 99%

Exploring glioblastoma stem cell heterogeneity: Immune microenvironment modulation and therapeutic opportunities

2022

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Despite its growing use in cancer treatment, immunotherapy has been virtually ineffective in clinical trials for gliomas. The inherently cold tumor immune microenvironment (TIME) in gliomas, characterized by a high ratio of pro-tumor to anti-tumor immune cell infiltrates, acts as a seemingly insurmountable barrier to immunotherapy. Glioma stem cells (GSCs) within these tumors are key contributors to this cold TIME, often functioning indirectly through activation and recruitment of pro-tumor immune cell types. Furthermore, drivers of GSC plasticity and heterogeneity (e.g., reprogramming transcription factors, epigenetic modifications) are associated with induction of immunosuppressive cell states. Recent studies have identified GSC-intrinsic mechanisms, including functional mimicry of immune suppressive cell types, as key determinants of anti-tumor immune escape. In this review, we cover recent advancements in our understanding of GSC-intrinsic mechanisms that modulate GSC-TIME interactions and discuss cutting-edge techniques and bioinformatics platforms available to study immune modulation at high cellular resolution with exploration of both malignant (i.e., GSC) and non-malignant (i.e., immune) cell fractions. Finally, we provide insight into the therapeutic opportunities for targeting immunomodulatory GSC-intrinsic mechanisms to potentiate immunotherapy response in gliomas.

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confidence: 99%

Exploring glioblastoma stem cell heterogeneity: Immune microenvironment modulation and therapeutic opportunities

2022

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“…5b), indicating that alterations of these genes may enhance aggressiveness by disturbing pan-cancer hallmarks of tumorigenesis. In fact, TP53 alterations have been extensively linked to genomic instability 32,33 , while CDK2NA and TERT are key regulators of cell proliferation, two pathways that are often perturbed in metastatic tumors 59 (see earlier). Finally, some driver genes were strongly enriched in primary tumors, such as KMT2D mutations in non-small cell lung cancer (primary 13.7%, and metastatic 2.1%) and POLE mutations in primary colorectal carcinomas (primary 13%, metastatic 0.5%).…”

Section: Resultsmentioning

confidence: 99%

Pan-cancer whole genome comparison of primary and metastatic solid tumors

Martínez-Jiménez

Movasati

Brunner

et al. 2022

Preprint

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Metastatic cancer remains almost inevitably a lethal disease. A better understanding of disease progression and response to therapies therefore remains of utmost importance. Here, we characterize the genomic differences between early-stage untreated primary tumors and late-stage treated metastatic tumors using a harmonized pan-cancer (re-)analysis of 7,152 whole-genome-sequenced tumors. In general, our analysis shows that metastatic tumors have a low intra-tumor heterogeneity, high genomic instability and increased frequency of structural variants with comparatively a modest increase in the number of small genetic variants. However, these differences are cancer type specific and are heavily impacted by the exposure to cancer therapies. Five cancer types, namely breast, prostate, thyroid, kidney clear carcinoma and pancreatic neuroendocrine, are a clear exception to the rule, displaying an extensive transformation of their genomic landscape in advanced stages. These changes were supported by increased genomic instability and involved substantial differences in tumor mutation burden, clock-based molecular signatures and the landscape of driver alterations as well as a pervasive increase in structural variant burden. The majority of cancer types had either moderate genomic differences (e.g., cervical and colorectal cancers) or highly consistent genomic portraits (e.g., ovarian cancer and skin melanoma) when comparing early- and late-stage disease. Exposure to treatment further scars the tumor genome and introduces an evolutionary bottleneck that selects for known therapy-resistant drivers in approximately half of treated patients. Our data showcases the potential of whole-genome analysis to understand tumor evolution and provides a valuable resource to further investigate the biological basis of cancer and resistance to cancer therapies.

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“…For the reference single-cell information, previously published single-cell gene expression catalogs were employed 27 . For deconvolution of cellular components using the component single-cell gene expression patterns, CIBERSORTx 25 , which is the most frequently used program for this purpose 30 – 35 , was used. The deconvolution result of mouse kidney semibulks appeared as shown in Fig.…”

Section: Resultsmentioning

confidence: 99%

Semibulk RNA-seq analysis as a convenient method for measuring gene expression statuses in a local cellular environment

Muto

Tsuchiya

Kim

et al. 2022

Sci Rep

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When biologically interpretation of the data obtained from the single-cell RNA sequencing (scRNA-seq) analysis is attempted, additional information on the location of the single cells, behavior of the surrounding cells, and the microenvironment they generate, would be very important. We developed an inexpensive, high throughput application while preserving spatial organization, named “semibulk RNA-seq” (sbRNA-seq). We utilized a microfluidic device specifically designed for the experiments to encapsulate both a barcoded bead and a cell aggregate (a semibulk) into a single droplet. Using sbRNA-seq, we firstly analyzed mouse kidney specimens. In the mouse model, we could associate the pathological information with the gene expression information. We validated the results using spatial transcriptome analysis and found them highly consistent. When we applied the sbRNA-seq analysis to the human breast cancer specimens, we identified spatial interactions between a particular population of immune cells and that of cancer-associated fibroblast cells, which were not precisely represented solely by the single-cell analysis. Semibulk analysis may provide a convenient and versatile method, compared to a standard spatial transcriptome sequencing platform, to associate spatial information with transcriptome information.

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Glioma progression is shaped by genetic evolution and microenvironment interactions

Cited by 191 publications

References 81 publications

Exploring glioblastoma stem cell heterogeneity: Immune microenvironment modulation and therapeutic opportunities

Exploring glioblastoma stem cell heterogeneity: Immune microenvironment modulation and therapeutic opportunities

Pan-cancer whole genome comparison of primary and metastatic solid tumors

Semibulk RNA-seq analysis as a convenient method for measuring gene expression statuses in a local cellular environment

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