Single-cell RNA-seq enables comprehensive tumour and immune cell profiling in primary breast cancer

Chung, Wingyan; Eum, Hye Hyeon; Lee, Hae Ock; Lee, Kyung Min; Lee, Han‐Byoel; Kim, Kyu Tae; Ryu, Han Suk; Kim, Sang-Min; Lee, Jeong Eon; Park, Yeon Hee; Kan, Zhengyan; Han, Wonshik; Park, Woong-Yang

doi:10.1038/ncomms15081

Cited by 840 publications

(827 citation statements)

References 61 publications

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“…1d). This predominant grouping of cancer cells by their tumor of origin has been reported for a number of cerebral and non-cerebral tumors [11,14,33,37,50,54,61]. For identifying traits common to all tumors, data can be analyzed tumor per tumor [62,63,69], or merged and analyzed as a whole after standardization (i.e.…”

Section: Unsupervised Clustering Analysis Highlights First Gbm Cells'mentioning

confidence: 71%

Capture at the single cell level of metabolic modules distinguishing aggressive and indolent glioblastoma cells

Saurty

Bellenger

El-Habr

et al. 2019

Preprint

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Glioblastoma cell ability to adapt their functioning to microenvironment changes is a source of the extensive intra-tumor heterogeneity characteristic of this devastating malignant brain tumor. A systemic view of the metabolic pathways underlying glioblastoma cell functioning states is lacking.We analyzed public single cell RNA-sequencing data from glioblastoma surgical resections, which offer the closest available view of tumor cell heterogeneity as encountered at the time of patients' diagnosis. Unsupervised analyses revealed that information dispersed throughout the cell transcript repertoires encoded the identity of each tumor and masked information related to cell functioning states. Data reduction based on an experimentally-defined signature of transcription factors overcame this hurdle. It allowed cell grouping according to their tumorigenic potential, regardless of their tumor of origin. The approach relevance was validated using an independent dataset of glioblastoma tissue transcriptomes, patient-derived cell lines and orthotopic xenografts.Overexpression of genes coding for amino acid and lipid metabolism enzymes involved in antioxidative, energetic and cell membrane processes characterized cells with high tumorigenic potential. Modeling of their expression network highlighted the very long chain polyunsaturated fatty acid synthesis pathway at the core of the network. Expression of its most downstream enzymatic component, ELOVL2, was associated with worsened patient survival, and required for cell tumorigenic properties in vivo. Our results demonstrate the power of signature-driven analyses of single cell transcriptomes to obtain an integrated view of metabolic pathways at play within the heterogeneous cell landscape of patient tumors.

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Section: Unsupervised Clustering Analysis Highlights First Gbm Cells'mentioning

confidence: 71%

Capture at the single cell level of metabolic modules distinguishing aggressive and indolent glioblastoma cells

Saurty

Bellenger

El-Habr

et al. 2019

Preprint

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“…Further, by identifying genes that were most often co-expressed, the authors identified several “hub” genes coordinating the most common gene expression profiles identified in the cells, including genes such as SCN2A, CENPH , TUBGCP2 , LINC00189 , and ARHGAP15 , encompassing genes both known and previously unknown to have cancer involvement. Chung and colleagues performed single cell RNA-sequencing of cells from 11 patients with various breast cancer subtypes to identify heterogeneity of subtypes even among cells from the same patient tumor and to pinpoint subtype-specific differences in gene expression [55]. Specifically, the group found that TNBC cells have increased expression of epithelial-to-mesenchymal transition (EMT) genes than luminal and HER2+ cells, and that gene expression varies widely in cells of the TNBC subtype.…”

Section: Tumor Heterogeneity Exists At Multiple -Omic Levelsmentioning

confidence: 99%

Mechanisms and clinical implications of tumor heterogeneity and convergence on recurrent phenotypes

et al. 2017

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Tumor heterogeneity has been identified at various -omic levels. The tumor genome, transcriptome, proteome, and phenome can vary widely across cells in patient tumors and are influenced by tumor cell interactions with heterogeneous physical conditions and cellular components of the tumor microenvironment. Here, we explore the concept that while variation exists at multiple -omic levels, changes at each of these levels converge on the same pathways and lead to convergent phenotypes in tumors that can provide common drug targets. These phenotypes include cellular growth and proliferation, sustained oncogenic signaling, and immune avoidance, among others. Tumor heterogeneity complicates treatment of patient cancers as it leads to varied response to therapies. Identification of convergent cellular phenotypes arising in patient cancers and targeted therapies that reverse them has the potential to transform the way clinicians treat these cancers and to improve patient outcome.

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“…Single-cell analysis is a recently developed systematic method used to evaluate the heterogeneity of a cell population. 20,21 In the present study, we used single-cell gene expression analysis on stem cell-and gastric cell lineage-markers and evaluated features of drug-tolerant persister cells in gastric cancer patient-derived cells (PDC). Through this analysis, we identified a potential therapeutic target pathway of gastric cancer persister cells.…”

Section: Introductionmentioning

confidence: 99%

ALDH1A3‐mTOR axis as a therapeutic target for anticancer drug‐tolerant persister cells in gastric cancer

et al. 2020

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Tumors consist of heterogeneous cell populations that contain cancer cell subpopulations with anticancer drug‐resistant properties called “persister” cells. While this early‐phase drug tolerance is known to be related to the stem cell‐like characteristic of persister cells, how the stem cell‐related pathways contribute to drug resistance has remained elusive. Here, we conducted a single‐cell analysis based on the stem cell lineage‐related and gastric cell lineage‐related gene expression in patient‐derived gastric cancer cell models. The analyses revealed that 5‐fluorouracil (5‐FU) induces a dynamic change in the cell heterogeneity. In particular, cells highly expressing stem cell‐related genes were enriched in the residual cancer cells after 5‐FU treatment. Subsequent functional screening identified aldehyde dehydrogenase 1A3 (ALDH1A3) as a specific marker and potential therapeutic target of persister cells. ALDH1A3 was selectively overexpressed among the ALDH isozymes after treatment with 5‐FU or SN38, a DNA topoisomerase I inhibitor. Attenuation of ALDH1A3 expression by RNA interference significantly suppressed cell proliferation, reduced the number of persister cells after anticancer drug treatment and interfered with tumor growth in a mouse xenograft model. Mechanistically, ALDH1A3 depletion affected gene expression of the mammalian target of rapamycin (mTOR) cell survival pathway, which coincided with a decrease in the activating phosphorylation of S6 kinase. Temsirolimus, an mTOR inhibitor, reduced the number of 5FU‐tolerant persister cells. High ALDH1A3 expression correlated with worse prognosis of gastric cancer patients. These observations indicate that the ALDH1A3‐mTOR axis could be a novel therapeutic target to eradicate drug‐tolerant gastric cancer cells.

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Single-cell RNA-seq enables comprehensive tumour and immune cell profiling in primary breast cancer

Cited by 840 publications

References 61 publications

Capture at the single cell level of metabolic modules distinguishing aggressive and indolent glioblastoma cells

Capture at the single cell level of metabolic modules distinguishing aggressive and indolent glioblastoma cells

Mechanisms and clinical implications of tumor heterogeneity and convergence on recurrent phenotypes

ALDH1A3‐mTOR axis as a therapeutic target for anticancer drug‐tolerant persister cells in gastric cancer

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