Single-Cell Proteomic Analysis Dissects the Complexity of Tumor Microenvironment in Muscle Invasive Bladder Cancer

Feng, Chao; Wang, Xi; Tao, Yuting; Xie, Yuanliang; Lai, Zhiyong; Z, Li; Hu, Jiaxin; Tang, Shaomei; Pan, Lixin; He, Liangyu; Wang, Qiuyan; Li, Tianyu; Mo, Zengnan

doi:10.3390/cancers13215440

Cited by 7 publications

(8 citation statements)

References 78 publications

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“…The data table integrates single ion signals per pixel, after which image and single cell segmentation can be converted to single-cell data for downstream analysis. In cancer research, IMC is used to discover novel phenotypes and biomarkers, or to study TME heterogeneity [22][23][24][25][30][31][32]36,43,44,50]. IMC is also used to predict prognosis and therapy responses in humans or in mice [23,30,51,[65][66][67][68][73][74][75].…”

Section: Imaging Mass Cytometrymentioning

confidence: 99%

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Multiplex Tissue Imaging: Spatial Revelations in the Tumor Microenvironment

Dam

Baars

Vercoulen

2022

Cancers

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The tumor microenvironment is a complex ecosystem containing various cell types, such as immune cells, fibroblasts, and endothelial cells, which interact with the tumor cells. In recent decades, the cancer research field has gained insight into the cellular subtypes that are involved in tumor microenvironment heterogeneity. Moreover, it has become evident that cellular interactions in the tumor microenvironment can either promote or inhibit tumor development, progression, and drug resistance, depending on the context. Multiplex spatial analysis methods have recently been developed; these have offered insight into how cellular crosstalk dynamics and heterogeneity affect cancer prognoses and responses to treatment. Multiplex (imaging) technologies and computational analysis methods allow for the spatial visualization and quantification of cell–cell interactions and properties. These technological advances allow for the discovery of cellular interactions within the tumor microenvironment and provide detailed single-cell information on properties that define cellular behavior. Such analyses give insights into the prognosis and mechanisms of therapy resistance, which is still an urgent problem in the treatment of multiple types of cancer. Here, we provide an overview of multiplex imaging technologies and concepts of downstream analysis methods to investigate cell–cell interactions, how these studies have advanced cancer research, and their potential clinical implications.

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Section: Imaging Mass Cytometrymentioning

confidence: 99%

“…In cancer research, IMC is used to discover novel phenotypes and biomarkers, or to study TME heterogeneity [22][23][24][25][30][31][32]36,43,44,50]. IMC is also used to predict prognosis and therapy responses in humans or in mice [23,30,51,[65][66][67][68][73][74][75].…”

Section: Imaging Mass Cytometrymentioning

confidence: 99%

Multiplex Tissue Imaging: Spatial Revelations in the Tumor Microenvironment

Dam

Baars

Vercoulen

2022

Cancers

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“…Bladder tumors and normal adjacent tissue, young and aged murine bladders scRNA-seq, scTCR-seq, sc-CyTOF (Chen et al, 2020;Ligon et al, 2020;Oh et al, 2020;Wang et al, 2021b;Feng et al, 2021) The detection of urinary exfoliated tumor cells…”

Section: Human Mousementioning

confidence: 99%

Single-cell sequencing technologies in bladder cancer research: Applications and challenges

Lyu

Lin²,

Wu³

et al. 2022

Front. Genet.

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Bladder cancer is among the most common malignant tumors with highly heterogeneous molecular characteristics. Despite advancements of the available therapeutic options, several bladder cancer patients exhibit unsatisfactory clinical outcomes. The lack of specific biomarkers for effective targeted therapy or immunotherapy remains a major obstacle in treating bladder cancer. The rapid development of single-cell techniques is transforming our understanding of the intra-tumoral heterogeneity, thereby providing us with a powerful high-throughput sequencing tool that can reveal tumorigenesis, progression, and invasion in bladder tumors. In this review, we summarise and discuss how single-cell sequencing technologies have been applied in bladder cancer research, to advance our collective knowledge on the heterogeneity of bladder tumor cells, as well as to provide new insights into the complex ecosystem of the tumor microenvironment. The application of single-cell approaches also uncovers the therapeutic resistance mechanism in bladder cancer and facilitates the detection of urinary-exfoliated tumor cells. Moreover, benefiting from the powerful technical advantages of single-cell techniques, several key therapeutic targets and prognostic models of bladder cancer have been identified. It is hoped that this paper can provide novel insights into the precision medicine of bladder cancer.

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“…For example, Kubli, SP et al proposed that the complexity of immune cell-cancer cell interaction is an important reason for the failure of tumor immunotherapy [ 67 ]. Besides, Feng, C et al, Prokhnevska, N et al and Wierz, M et al described the complexity of the tumor microenvironment in bladder cancer, prostate cancer, and chronic lymphocytic leukemia, respectively [ 68 – 70 ]. Taken together, we believe that the results of the immune infiltration analysis not only showed that the main immune cells exhibited a higher degree of immune infiltration in the low-risk group, but also provide some clues about the complexity of immune cell roles in HNSCC.…”

Section: Discussionmentioning

confidence: 99%

Transcriptome analysis reveals the prognostic and immune infiltration characteristics of glycolysis and hypoxia in head and neck squamous cell carcinoma

2022

BMC Cancer

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Background This study aims to construct a new prognostic gene signature in survival prediction and risk stratification for patients with Head and neck squamous cell carcinoma (HNSCC). Method The transcriptome profiling data and hallmark gene sets in the Molecular Signatures Database was used to explore the cancer hallmarks most relevant to the prognosis of HNSCC patients. Differential gene expression analysis, weighted gene co-expression network analysis, univariate COX regression analysis, random forest algorithm and multiple combinatorial screening were used to construct the prognostic gene signature. The predictive ability of gene signature was verified in the TCGA HNSCC cohort as the training set and the GEO HNSCC cohorts (GSE41613 and GSE42743) as the validation sets, respectively. Moreover, the correlations between risk scores and immune infiltration patterns, as well as risk scores and genomic changes were explored. Results A total of 3391 differentially expressed genes in HNSCC were screened. Glycolysis and hypoxia were screened as the main risk factors for OS in HNSCC. Using univariate Cox analysis, 97 prognostic candidates were identified (P < 0.05). Top 10 important genes were then screened out by random forest. Using multiple combinatorial screening, a combination with less genes and more significant P value was used to construct the prognostic gene signature (RNF144A, STC1, P4HA1, FMNL3, ANO1, BASP1, MME, PLEKHG2 and DKK1). Kaplan–Meier analysis showed that patients with higher risk scores had worse overall survival (p < 0.001). The ROC curve showed that the risk score had a good predictive efficiency (AUC > 0.66). Subsequently, the predictive ability of the risk score was verified in the validation sets. Moreover, the two-factor survival analysis combining the cancer hallmarks and risk scores suggested that HNSCC patients with the high hypoxia or glycolysis & high risk-score showed the worst prognosis. Besides, a nomogram based on the nine-gene signature was established for clinical practice. Furthermore, the risk score was significantly related to tumor immune infiltration profiles and genome changes. Conclusion This nine-gene signature associated with glycolysis and hypoxia can not only be used for prognosis prediction and risk stratification, but also may be a potential therapeutic target for patients with HNSCC.

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Single-Cell Proteomic Analysis Dissects the Complexity of Tumor Microenvironment in Muscle Invasive Bladder Cancer

Cited by 7 publications

References 78 publications

Multiplex Tissue Imaging: Spatial Revelations in the Tumor Microenvironment

Multiplex Tissue Imaging: Spatial Revelations in the Tumor Microenvironment

Single-cell sequencing technologies in bladder cancer research: Applications and challenges

Transcriptome analysis reveals the prognostic and immune infiltration characteristics of glycolysis and hypoxia in head and neck squamous cell carcinoma

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