A cellular and spatial atlas of<i>TP53</i>-associated tissue remodeling in lung adenocarcinoma

Zhao, William; Kepecs, Benjamin; Mahadevan, Navin R.; Segerstolpe, Åsa; Weirather, Jason L.; Besson, N.; Giotti, Bruno; Soong, Brian Y.; Li, Chendi; Vigneau, Sébastien; Slyper, Michal; Wakiro, Isaac; Jané‐Valbuena, Judit; Ashenberg, Orr; Rotem, Asaf; Bueno, Raphael; Rozenblatt-Rosen, Orit; Pfaff, Kathleen L.; Rodig, Scott J.; Hata, Aaron N.; Regev, Aviv; Johnson, Bruce E.; Tsankov, Alexander M.

doi:10.1101/2023.06.28.546977

Cited by 3 publications

(1 citation statement)

References 128 publications

(266 reference statements)

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“…In colorectal carcinoma (CRC) and in other epithelial cancers, transformed cells intermingle with non-cancer epithelial cells in areas known as the invasive front (IF) 3,4 . Furthermore, normal tissues adjacent to tumours are re-shaped beyond the cancer's boundary, influenced by local immune responses and inflammation 5 , paracrine signals 6 , and genetic aberrations preceding malignant transformation 7 , as has been shown by multiplexed tissue imaging 8 , single-cell 9 and bulk transcriptomics 10 . This gradual change in cell composition from normal to cancer poses challenges for single-cell transcriptomics, as it is not immediately apparent from the transcriptome whether certain cells arise from malignant or normal lineages.…”

Section: Introductionmentioning

confidence: 99%

High-confidence calling of normal epithelial cells allows identification of a novel stem-like cell state in the colorectal cancer microenvironment

Wei,

Blanc,

Peidli

et al. 2024

Preprint

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Single-cell analyses can be confounded by assigning unrelated groups of cells to common developmental trajectories. For instance, cancer cells and admixed normal epithelial cells could potentially adopt similar cell states thus complicating analyses of their developmental potential. Here, we develop and benchmark CCISM (for Cancer Cell Identification using Somatic Mutations) to exploit genomic single nucleotide variants for the disambiguation of cancer cells from genomically normal non-cancer epithelial cells in single-cell data. In colorectal cancer datasets, we find that our method and others based on gene expression or allelic imbalances identify overlapping sets of cancer versus normal epithelial cells, depending on molecular characteristics of individual cancers. Further, we define consensus cell identities of normal and cancer epithelial cells with higher transcriptome cluster homogeneity than those derived using existing tools. Using the consensus identities, we identify significant shifts of cell state distributions in genomically normal epithelial cells developing in the cancer microenvironment, with immature states increased at the expense of terminal differentiation throughout the colon, and a novel stem-like cell state arising in the left colon. Trajectory analyses show that the new cell state extends the pseudo-time range of normal colon stem-like cells in a cancer context. We identify cancer-associated fibroblasts as sources of WNT and BMP ligands potentially contributing to increased plasticity of stem cells in the cancer microenvironment. Our analyses advocate careful interpretation of cell heterogeneity and plasticity in the cancer context and the consideration of genomic information in addition to gene expression data when possible.

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Section: Introductionmentioning

confidence: 99%

High-confidence calling of normal epithelial cells allows identification of a novel stem-like cell state in the colorectal cancer microenvironment

Wei,

Blanc,

Peidli

et al. 2024

Preprint

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High‐confidence calling of normal epithelial cells allows identification of a novel stem‐like cell state in the colorectal cancer microenvironment

Wei,

Blanc,

Peidli

et al. 2024

Intl Journal of Cancer

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Single‐cell analyses can be confounded by assigning unrelated groups of cells to common developmental trajectories. For instance, cancer cells and admixed normal epithelial cells could adopt similar cell states thus complicating analyses of their developmental potential. Here, we develop and benchmark CCISM (for Cancer Cell Identification using Somatic Mutations) to exploit genomic single nucleotide variants for the disambiguation of cancer cells from genomically normal non‐cancer cells in single‐cell data. We find that our method and others based on gene expression or allelic imbalances identify overlapping sets of colorectal cancer versus normal colon epithelial cells, depending on molecular characteristics of individual cancers. Further, we define consensus cell identities of normal and cancer epithelial cells with higher transcriptome cluster homogeneity than those derived using existing tools. Using the consensus identities, we identify significant shifts of cell state distributions in genomically normal epithelial cells developing in the cancer microenvironment, with immature states increased at the expense of terminal differentiation throughout the colon, and a novel stem‐like cell state arising in the left colon. Trajectory analyses show that the new cell state extends the pseudo‐time range of normal colon stem‐like cells in a cancer context. We identify cancer‐associated fibroblasts as sources of WNT and BMP ligands potentially contributing to increased plasticity of stem cells in the cancer microenvironment. Our analyses advocate careful interpretation of cell heterogeneity and plasticity in the cancer context and the consideration of genomic information in addition to gene expression data when possible.

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Hypoxia drives shared and distinct transcriptomic changes in two invasive glioma stem cell lines

Marallano,

Ughetta,

Tejero

et al. 2024

Sci Rep

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Glioblastoma (GBM) is the most common primary malignant cancer of the central nervous system. Insufficient oxygenation (hypoxia) has been linked to GBM invasion and aggression, leading to poor patient outcomes. Hypoxia induces gene expression for cellular adaptations. However, GBM is characterized by high intertumoral (molecular subtypes) and intratumoral heterogeneity (cell states), and it is not well understood to what extent hypoxia triggers patient-specific gene responses and cellular diversity in GBM. Here, we surveyed eight patient-derived GBM stem cell lines for invasion phenotypes in 3D culture, which identified two GBM lines showing increased invasiveness in response to hypoxia. RNA-seq analysis of the two patient GBM lines revealed a set of shared hypoxia response genes concerning glucose metabolism, angiogenesis, and autophagy, but also a large set of patient-specific hypoxia-induced genes featuring cell migration and anti-inflammation, highlighting intertumoral diversity of hypoxia responses in GBM. We further applied the Shared GBM Hypoxia gene signature to single cell RNA-seq datasets of glioma patients, which showed that hypoxic cells displayed a shift towards mesenchymal-like (MES) and astrocyte-like (AC) states. Interestingly, in response to hypoxia, tumor cells in IDH-mutant gliomas displayed a strong shift to the AC state, whereas tumor cells in IDH-wildtype gliomas mainly shifted to the MES state. This distinct hypoxia response of IDH-mutant gliomas may contribute to its more favorable prognosis. Our transcriptomic studies provide a basis for future approaches to better understand the diversity of hypoxic niches in gliomas.

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A cellular and spatial atlas ofTP53-associated tissue remodeling in lung adenocarcinoma

Cited by 3 publications

References 128 publications

High-confidence calling of normal epithelial cells allows identification of a novel stem-like cell state in the colorectal cancer microenvironment

High-confidence calling of normal epithelial cells allows identification of a novel stem-like cell state in the colorectal cancer microenvironment

High‐confidence calling of normal epithelial cells allows identification of a novel stem‐like cell state in the colorectal cancer microenvironment

Hypoxia drives shared and distinct transcriptomic changes in two invasive glioma stem cell lines

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