Single-cell transcriptome analysis demonstrates inter-patient and intra-tumor heterogeneity in primary and metastatic lung adenocarcinoma

Liu, Yafei; Ye, Guanchao; Huang, Lan; Zhang, Chunyang; Sheng, Yinliang; Wu, Bin; Han, Lu; Wu, Chunli; Dong, Bo; Qi, Yu

doi:10.18632/aging.103945

Cited by 28 publications

(19 citation statements)

References 68 publications

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“…One of the more important things is cellular annotation, which needs to be done by integrating differentially expressed genes between clusters, expression of classical marker genes and enrichment of the reference gene set of immune cells in the literature. We combined scRNAseq data from multiple datasets in LUAD [GSE97168 ( 34 ), GSE131907 ( 35 ), GSE99254 ( 36 )] to map the expression levels of 224 cytokines in different cell types in TME ( Figure 1A ), and specific expression patterns of several representative cytokines in certain cell types were highlighted ( Figure 1B ) for cell annotation. Analyzing scRNA-seq data is challenging because it requires multidisciplinary knowledge.…”

Section: A Brief Overview Of Scrna-seqmentioning

confidence: 99%

Single-Cell RNA Sequencing in Lung Cancer: Revealing Phenotype Shaping of Stromal Cells in the Microenvironment

et al. 2022

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The lung tumor microenvironment, which is composed of heterogeneous cell populations, plays an important role in the progression of lung cancer and is closely related to therapeutic efficacy. Increasing evidence has shown that stromal components play a key role in regulating tumor invasion, metastasis and drug resistance. Therefore, a better understanding of stromal components in the tumor microenvironment is helpful for the diagnosis and treatment of lung cancer. Rapid advances in technology have brought our understanding of disease into the genetic era, and single-cell RNA sequencing has enabled us to describe gene expression profiles with unprecedented resolution, enabling quantitative analysis of gene expression at the single-cell level to reveal the correlations among heterogeneity, signaling pathways, drug resistance and microenvironment molding in lung cancer, which is important for the treatment of this disease. In this paper, several common single-cell RNA sequencing methods and their advantages and disadvantages are briefly introduced to provide a reference for selection of suitable methods. Furthermore, we review the latest progress of single-cell RNA sequencing in the study of stromal cells in the lung tumor microenvironment.

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Section: A Brief Overview Of Scrna-seqmentioning

confidence: 99%

Single-Cell RNA Sequencing in Lung Cancer: Revealing Phenotype Shaping of Stromal Cells in the Microenvironment

et al. 2022

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“…Liu et al (2020) [ 58 ] performed a single-cell RNA sequencing data analysis of 50 primary lung adenocarcinomas and their corresponding BMs. They discovered a significant intratumoral heterogeneity in both the BMs and parent cancers.…”

Section: Brain Metastases Heterogeneity In Major Malignanciesmentioning

confidence: 99%

“…They discovered a significant intratumoral heterogeneity in both the BMs and parent cancers. The pathways related to translational initiation, endoplasmic reticulum stress, exosomes, and unfolded protein response were upregulated in BMs compared to the primary sites [ 58 ]. Despite the higher mutation burden in BMs than in the primary NSCLCs, the latter were reported to harbor a greater richness of T-cell clones than their paired metastases [ 59 ].…”

Section: Brain Metastases Heterogeneity In Major Malignanciesmentioning

confidence: 99%

Molecular Profiles of Brain Metastases: A Focus on Heterogeneity

Ali

Górska

Duchnowska

et al. 2021

Cancers

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Brain metastasis is a common and devastating clinical entity. Intratumor heterogeneity in brain metastases poses a crucial challenge to precision medicine. However, advances in next-generation sequencing, new insight into the pathophysiology of driver mutations, and the creation of novel tumor models have allowed us to gain better insight into the genetic landscapes of brain metastases, their temporal evolution, and their response to various treatments. A plethora of genomic studies have identified the heterogeneous clonal landscape of tumors and, at the same time, introduced potential targets for precision medicine. As an example, we present phenotypic alterations in brain metastases originating from three malignancies with the highest brain metastasis frequency: lung cancer, breast cancer, and melanoma. We discuss the barriers to precision medicine, tumor heterogeneity, the significance of blood-based biomarkers in tracking clonal evolution, the phylogenetic relationship between primary and metastatic tumors, blood–brain barrier heterogeneity, and limitations to ongoing research.

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“…ScRNA-seq is a novel hot spot to demonstrate the underlying mechanisms of LUAD, uncovering new differentially expressed genes as well as the heterogeneity of immune response-related genes [ 5 , 6 ]. Besides, scRNA-seq was applied to unravel the molecular and cellular reprogramming mechanisms in metastatic LUAD and the cell-cycle state of the circulating tumor cells of cerebrospinal fluid in LUAD patients with leptomeningeal metastases [ 7 , 8 ]. When it comes to immunotherapy, scRNA-seq technology might locate the expression of hub genes in immune cells of LUAD to improve precision of immunotherapy in the future [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

Identification of a ZC3H12D-regulated competing endogenous RNA network for prognosis of lung adenocarcinoma at single-cell level

Chen

Guo

et al. 2022

BMC Cancer

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Background To identify hub genes from the competing endogenous RNA (ceRNA) network of lung adenocarcinoma (LUAD) and to explore their potential functions on prognosis of patients from a single-cell perspective. Methods We performed RNA-sequencing of LUAD to construct ceRNA regulatory network, integrating with public databases to identify the vital pathways related to patients’ prognosis and to reveal the expression level of hub genes under different conditions, the functional enrichment of co-expressed genes and their potential immune-related mechanisms. Results ZC3H12D-hsa-miR-4443-ENST00000630242 axis was found to be related with LUAD. Lower ZC3H12D expression was significantly associated with shorter overall survival (OS) of patients (HR = 2.007, P < 0.05), and its expression was higher in early-stage patients, including T1 (P < 0.05) and N0 (P < 0.05). Additionally, ZC3H12D expression was higher in immune cells displayed by single-cell RNA-sequencing data, especially in Treg cells of lung cancer and CD8 T cells, B cells and CD4 T cells of LUAD. The functional enrichment analysis showed that the co-expressed genes mainly played a role in lymphocyte activation and cytokine-cytokine receptor interaction. In addition, ZC3H12D was associated with multiple immune cells and immune molecules, including immune checkpoints CTLA4, CD96 and TIGIT. Conclusion ZC3H12D-hsa-miR-4443-ENST00000630242 ceRNA network was identified in LUAD. ZC3H12D could affect prognosis of patients by regulating mRNA, miRNA, lncRNA, immune cells and immune molecules. Therefore, it may serve as a vital predictive marker and could be regarded as a potential therapeutic target for LUAD in the future.

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Single-cell transcriptome analysis demonstrates inter-patient and intra-tumor heterogeneity in primary and metastatic lung adenocarcinoma

Cited by 28 publications

References 68 publications

Single-Cell RNA Sequencing in Lung Cancer: Revealing Phenotype Shaping of Stromal Cells in the Microenvironment

Single-Cell RNA Sequencing in Lung Cancer: Revealing Phenotype Shaping of Stromal Cells in the Microenvironment

Molecular Profiles of Brain Metastases: A Focus on Heterogeneity

Identification of a ZC3H12D-regulated competing endogenous RNA network for prognosis of lung adenocarcinoma at single-cell level

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