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

Zhang, Jianhong; Song, Cheng‐Yang; Tian, Ye; Yang, Xueying

doi:10.3389/fimmu.2021.802080

Cited by 25 publications

(28 citation statements)

References 138 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Cancer cells were clustered or novel cell types were identified based on expression profiles to obtain dynamic information, such as the origin, evolution, and development of tumor subclones, the presence of cancer stem cells, or quantification of tumor stemness (Zhang et al 2020 ; Baslan and Hicks 2017 ). Studies using sc-RNAseq data have made additional contributions by comparing the subtype composition of tumors with different pathological types, clinical features, and response to treatment, and identifying differentially expressed genes between different tumor groups (Zhang et al 2021 ; Chen et al 2021 ; Dai et al 2019 ). Single-cell sequencing technology has made remarkable progress in studying tumor heterogeneity and shed new light on predicting tumor prognosis and survival.…”

Section: Introductionmentioning

confidence: 99%

RETRACTED ARTICLE: Prognostic subtypes of thyroid cancer was constructed based on single cell and bulk-RNA sequencing data and verified its authenticity

Yang

Zhou

et al. 2023

Funct Integr Genomics

View full text Add to dashboard Cite

There has been an increase in the mortality rate of thyroid cancer (THCA), which is the most common endocrine malignancy. We identified six distinct cell types in the THAC microenvironment by analyzing single-cell RNA sequencing (Sc-RNAseq) data from 23 THCA tumor samples, indicating high intratumoral heterogeneity. Through re-dimensional clustering of immune subset cells, myeloid cells, cancer-associated fibroblasts, and thyroid cell subsets, we deeply reveal differences in the tumor microenvironment of thyroid cancer. Through an in-depth analysis of thyroid cell subsets, we identified the process of thyroid cell deterioration (normal, intermediate, malignant cells). Through cell-to-cell communication analysis, we found a strong link between thyroid cells and fibroblasts and B cells in the MIF signaling pathway. In addition, we found a strong correlation between thyroid cells and B cells, TampNK cells, and bone marrow cells. Finally, we developed a prognostic model based on differentially expressed genes in thyroid cells from single-cell analysis. Both in the training set and the testing set, it can effectively predict the survival of thyroid patients. In addition, we identified significant differences in the composition of immune cell subsets between high-risk and low-risk patients, which may be responsible for their different prognosis. Through in vitro experiments, we identify that knockdown of NPC2 can significantly promote thyroid cancer cell apoptosis, and NPC2 may be a potential therapeutic target for thyroid cancer. In this study, we developed a well-performing prognostic model based on Sc-RNAseq data, revealing the cellular microenvironment and tumor heterogeneity of thyroid cancer. This will help to provide more accurate personalized treatment for patients in clinical diagnosis. Supplementary Information The online version contains supplementary material available at 10.1007/s10142-023-01027-x.

show abstract

Section: Introductionmentioning

confidence: 99%

RETRACTED ARTICLE: Prognostic subtypes of thyroid cancer was constructed based on single cell and bulk-RNA sequencing data and verified its authenticity

Yang

Zhou

et al. 2023

Funct Integr Genomics

View full text Add to dashboard Cite

show abstract

“…Single-cell RNA-sequencing (scRNA-seq) method provides a potent approach for us to explore the complex biological behavior of TILs and potential mechanisms for them in shaping tumor development in various cancer types (22)(23)(24). Hence, establishing B cell-related signatures by means of scRNA-seq data could be a useful way to predict immunotherapeutic responses and prognosis in NSCLC patients.…”

Section: Introductionmentioning

confidence: 99%

Construction of a B cell-related gene pairs signature for predicting prognosis and immunotherapeutic response in non-small cell lung cancer

Wang

et al. 2022

Front. Immunol.

View full text Add to dashboard Cite

BackgroundAccumulating evidence indicates that the B cells play important roles in anti-tumor immunity and shaping tumor development. This study aimed to explore the expression profiles of B cell marker genes and construct a B cell-related gene pairs (BRGPs) signature associated with the prognosis and immunotherapeutic efficiency in non-small cell lung cancer (NSCLC) patients.MethodsB cell-related marker genes in NSCLC were identified using single-cell RNA sequencing data. TCGA and GEO datasets were utilized to identify the prognostic BRGPs based on a novel algorithm of cyclically single pairing along with a 0-or-1 matrix. BRGPs signature was then constructed using Lasso-Cox regression model. Its prognostic value, associated immunogenomic features, putative molecular mechanism and predictive ability to immunotherapy were investigated in NSCLC patients.ResultsThe BRGPs signature was composed of 23 BRGPs including 28 distinct B cell-related genes. This predictive signature demonstrated remarkable power in distinguishing good or poor prognosis and can serve as an independent prognostic factor for NSCLC patients in both training and validation cohorts. Furthermore, BRGPs signature was significantly associated with immune scores, tumor purity, clinicopathological characteristics and various tumor-infiltrating immune cells. Besides, we demonstrated that the tumor mutational burden scores and TIDE scores were positively correlated with the risk score of the model implying immune checkpoint blockade therapy may be more effective in NSCLC patients with high-risk scores.ConclusionsThis novel BRGPs signature can be used to assess the prognosis of NSCLC patients and may be useful in guiding immune checkpoint inhibitor treatment in our clinical practice.

show abstract

“…Library construction and data analysis of bulk and single-cell sequencing approaches share essentially the same principles and workflows [ 60 ].…”

Section: Tcr Repertoire Via Hts: When Details Mattermentioning

confidence: 99%

T-Cell Receptor Repertoire Sequencing and Its Applications: Focus on Infectious Diseases and Cancer

Mazzotti

Gaimari

Bravaccini

et al. 2022

IJMS

View full text Add to dashboard Cite

The immune system is a dynamic feature of each individual and a footprint of our unique internal and external exposures. Indeed, the type and level of exposure to physical and biological agents shape the development and behavior of this complex and diffuse system. Many pathological conditions depend on how our immune system responds or does not respond to a pathogen or a disease or on how the regulation of immunity is altered by the disease itself. T-cells are important players in adaptive immunity and, together with B-cells, define specificity and monitor the internal and external signals that our organism perceives through its specific receptors, TCRs and BCRs, respectively. Today, high-throughput sequencing (HTS) applied to the TCR repertoire has opened a window of opportunity to disclose T-cell repertoire development and behavior down to the clonal level. Although TCR repertoire sequencing is easily accessible today, it is important to deeply understand the available technologies for choosing the best fit for the specific experimental needs and questions. Here, we provide an updated overview of TCR repertoire sequencing strategies, providers and applications to infectious diseases and cancer to guide researchers’ choice through the multitude of available options. The possibility of extending the TCR repertoire to HLA characterization will be of pivotal importance in the near future to understand how specific HLA genes shape T-cell responses in different pathological contexts and will add a level of comprehension that was unthinkable just a few years ago.

show abstract

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

Cited by 25 publications

References 138 publications

RETRACTED ARTICLE: Prognostic subtypes of thyroid cancer was constructed based on single cell and bulk-RNA sequencing data and verified its authenticity

RETRACTED ARTICLE: Prognostic subtypes of thyroid cancer was constructed based on single cell and bulk-RNA sequencing data and verified its authenticity

Construction of a B cell-related gene pairs signature for predicting prognosis and immunotherapeutic response in non-small cell lung cancer

T-Cell Receptor Repertoire Sequencing and Its Applications: Focus on Infectious Diseases and Cancer

Contact Info

Product

Resources

About