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Yalan Lei

Bio: Yalan Lei is an academic researcher. The author has contributed to research in topics: Single cell sequencing & Genomics. The author has an hindex of 1, co-authored 2 publications receiving 7 citations.

Papers
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TL;DR: The use of single-cell sequencing in cancer research has revolutionized our understanding of the biological characteristics and dynamics within cancer lesions, including information related to the landscapes of malignant cells and immune cells, tumor heterogeneity, circulating tumor cells and underlying mechanisms of tumor biological behaviors as mentioned in this paper.
Abstract: Single-cell sequencing, including genomics, transcriptomics, epigenomics, proteomics and metabolomics sequencing, is a powerful tool to decipher the cellular and molecular landscape at a single-cell resolution, unlike bulk sequencing, which provides averaged data. The use of single-cell sequencing in cancer research has revolutionized our understanding of the biological characteristics and dynamics within cancer lesions. In this review, we summarize emerging single-cell sequencing technologies and recent cancer research progress obtained by single-cell sequencing, including information related to the landscapes of malignant cells and immune cells, tumor heterogeneity, circulating tumor cells and the underlying mechanisms of tumor biological behaviors. Overall, the prospects of single-cell sequencing in facilitating diagnosis, targeted therapy and prognostic prediction among a spectrum of tumors are bright. In the near future, advances in single-cell sequencing will undoubtedly improve our understanding of the biological characteristics of tumors and highlight potential precise therapeutic targets for patients.

103 citations

Journal ArticleDOI
TL;DR: Wang et al. as discussed by the authors investigated the role of immune-related long noncoding RNAs (irlncRNAs) in predicting prognosis and the immune landscape in pancreatic cancer.
Abstract: Immune-related long noncoding RNAs (irlncRNAs) are actively involved in regulating the immune status. This study aimed to establish a risk model of irlncRNAs and further investigate the roles of irlncRNAs in predicting prognosis and the immune landscape in pancreatic cancer. The transcriptome profiles and clinical information of 176 pancreatic cancer patients were retrieved from The Cancer Genome Atlas (TCGA). Immune-related genes (irgenes) downloaded from ImmPort were used to screen 1903 immune-related lncRNAs (irlncRNAs) using Pearson's correlation analysis (R > 0.5; p < 0.001). Random survival forest (RSF) and survival tree analysis showed that 9 irlncRNAs were highly correlated with overall survival (OS) according to the variable importance (VIMP) and minimal depth. Next, Cox regression analysis was used to establish a risk model with 3 irlncRNAs (LINC00462, LINC01887, RP11-706C16.8) that was evaluated by Kaplan-Meier analysis, the areas under the curve (AUCs) of the receiver operating characteristics and the C-index. Additionally, we performed Cox regression analysis to establish the clinical prognostic model, which showed that the risk score was an independent prognostic factor (p < 0.001). A nomogram and calibration plots were drawn to visualize the clinical features. The Wilcoxon signed-rank test and Pearson's correlation analysis further explored the irlncRNA signatures and immune cell infiltration, as well as the immunotherapy response.

6 citations


Cited by
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Journal ArticleDOI
Yuze Wu, Ming Yi, Mengke Niu, Qi Mei, Kongming Wu 
TL;DR: In this paper , the classification and inhibitory function of myeloid-derived suppressor cells (MDSCs) and the crosstalk between MDSCs and other myeloids are discussed.
Abstract: The clinical responses observed following treatment with immune checkpoint inhibitors (ICIs) support immunotherapy as a potential anticancer treatment. However, a large proportion of patients cannot benefit from it due to resistance or relapse, which is most likely attributable to the multiple immunosuppressive cells in the tumor microenvironment (TME). Myeloid-derived suppressor cells (MDSCs), a heterogeneous array of pathologically activated immature cells, are a chief component of immunosuppressive networks. These cells potently suppress T-cell activity and thus contribute to the immune escape of malignant tumors. New findings indicate that targeting MDSCs might be an alternative and promising target for immunotherapy, reshaping the immunosuppressive microenvironment and enhancing the efficacy of cancer immunotherapy. In this review, we focus primarily on the classification and inhibitory function of MDSCs and the crosstalk between MDSCs and other myeloid cells. We also briefly summarize the latest approaches to therapies targeting MDSCs.

32 citations

Journal ArticleDOI
TL;DR: In this paper , a review of single-cell transcriptomics and spatial transcriptomics for the studies of the systemic tumor immune microenvironment (STIE) and their interactions is presented, which may reveal heterogeneity in immunotherapy responses as well as the dynamic changes essential for the treatment effect.
Abstract: The development of combination immunotherapy based on the mediation of regulatory mechanisms of the tumor immune microenvironment (TIME) is promising. However, a deep understanding of tumor immunology must involve the systemic tumor immune environment (STIE) which was merely illustrated previously. Here, we aim to review recent advances in single-cell transcriptomics and spatial transcriptomics for the studies of STIE, TIME, and their interactions, which may reveal heterogeneity in immunotherapy responses as well as the dynamic changes essential for the treatment effect. We review the evidence from preclinical and clinical studies related to TIME, STIE, and their significance on overall survival, through different immunomodulatory pathways, such as metabolic and neuro-immunological pathways. We also evaluate the significance of the STIE, TIME, and their interactions as well as changes after local radiotherapy and systemic immunotherapy or combined immunotherapy. We focus our review on the evidence of lung cancer, hepatocellular carcinoma, and nasopharyngeal carcinoma, aiming to reshape STIE and TIME to enhance immunotherapy efficacy.

24 citations

Journal ArticleDOI
TL;DR: In this paper , a review of single cell-sequencing methodologies for cancer is presented, focusing on different aspects of epigenetics (DNA methylation, chromatin accessibility, histone modifications, DNA-protein interactions, and chromatin 3D architecture) at the single cell level.
Abstract: Bulk sequencing methodologies have allowed us to make great progress in cancer research. Unfortunately, these techniques lack the resolution to fully unravel the epigenetic mechanisms that govern tumor heterogeneity. Consequently, many novel single cell-sequencing methodologies have been developed over the past decade, allowing us to explore the epigenetic components that regulate different aspects of cancer heterogeneity, namely: clonal heterogeneity, tumor microenvironment (TME), spatial organization, intratumoral differentiation programs, metastasis, and resistance mechanisms. In this review, we explore the different sequencing techniques that enable researchers to study different aspects of epigenetics (DNA methylation, chromatin accessibility, histone modifications, DNA-protein interactions, and chromatin 3D architecture) at the single cell level, their potential applications in cancer, and their current technical limitations.

18 citations

Journal ArticleDOI
TL;DR: In this article , the authors performed scRNA-seq on 72,475 immune cells from 40 samples of tumor and matched adjacent normal tissues spanning 19 NSCLC patients, and drew a systematic immune cell transcriptome atlas.
Abstract: Abstract A thorough interrogation of the immune landscape is crucial for immunotherapy strategy selection and prediction of clinical responses in non-small-cell lung cancer (NSCLC) patients. Single-cell RNA sequencing (scRNA-seq) techniques have prompted the opportunity to dissect the distinct immune signatures between lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), the two major subtypes of NSCLC. Here, we performed scRNA-seq on 72,475 immune cells from 40 samples of tumor and matched adjacent normal tissues spanning 19 NSCLC patients, and drew a systematic immune cell transcriptome atlas. Joint analyses of the distinct cellular compositions, differentially expressed genes (DEGs), cell–cell interactions, pseudotime trajectory, transcriptomic factors and prognostic factors based on The Cancer Genome Atlas (TCGA), revealed the central roles of cytotoxic and effector T and NK cells and the distinct functional macrophages (Mφ) subtypes in the immune microenvironment heterogeneity between LUAD and LUSC. The dominant subtype of Mφ was FABP4- Mφ in LUAD and SPP1- Mφ in LUSC. Importantly, we identified a novel lymphocyte-related Mφ cluster, which we named SELENOP- Mφ, and further established its antitumor role in both types, especially in LUAD. Our comprehensive depiction of the immune heterogeneity and definition of Mφ clusters could help design personalized treatment for lung cancer patients in clinical practice.

17 citations

Journal ArticleDOI
TL;DR: In this paper , the authors combine single-nucleus RNA sequencing (snRNA-seq) with a microarray-based spatial transcriptomics (ST) to identify cell populations and their spatial distribution in breast cancer tissues, and find that these subclusters are mapped in distinct tissue regions, where discrepant enrichment of stromal cell types are observed.
Abstract: The heterogeneity and the complex cellular architecture have a crucial effect on breast cancer progression and response to treatment. However, deciphering the neoplastic subtypes and their spatial organization is still challenging. Here, we combine single-nucleus RNA sequencing (snRNA-seq) with a microarray-based spatial transcriptomics (ST) to identify cell populations and their spatial distribution in breast cancer tissues. Malignant cells are clustered into distinct subpopulations. These cell clusters not only have diverse features, origins and functions, but also emerge to the crosstalk within subtypes. Furthermore, we find that these subclusters are mapped in distinct tissue regions, where discrepant enrichment of stromal cell types are observed. We also inferred the abundance of these tumorous subpopulations by deconvolution of large breast cancer RNA-seq cohorts, revealing differential association with patient survival and therapeutic response. Our study provides a novel insight for the cellular architecture of breast cancer and potential therapeutic strategies.

16 citations