RGS5 plays a significant role in renal cell carcinoma

Su, Sumeyye; Shahriyari, Leili

doi:10.1098/rsos.191422

Cited by 17 publications

(10 citation statements)

References 42 publications

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“…Moreover, RGS5 is a hypoxia-inducible factor-1 dependent involved in the induction of endothelial apoptosis. In our previous study on TCGA data, we found that a high expression level of RGS5 in ccRCC primary tumors is associated with better survival months, and when the grade of ccRCC tumor increases, the RGS5 expression level significantly decreases 29 . Interestingly, cluster ( ) has the highest RGS5 expression level compared to the other clusters, and tumor free patients have a higher level of RGS5 expression than patients with tumor (Fig.…”

Section: Resultsmentioning

confidence: 84%

Immune classification of clear cell renal cell carcinoma

Akbarinejad

Shahriyari

2021

Sci Rep

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Since the outcome of treatments, particularly immunotherapeutic interventions, depends on the tumor immune micro-environment (TIM), several experimental and computational tools such as flow cytometry, immunohistochemistry, and digital cytometry have been developed and utilized to classify TIM variations. In this project, we identify immune pattern of clear cell renal cell carcinomas (ccRCC) by estimating the percentage of each immune cell type in 526 renal tumors using the new powerful technique of digital cytometry. The results, which are in agreement with the results of a large-scale mass cytometry analysis, show that the most frequent immune cell types in ccRCC tumors are CD8+ T-cells, macrophages, and CD4+ T-cells. Saliently, unsupervised clustering of ccRCC primary tumors based on their relative number of immune cells indicates the existence of four distinct groups of ccRCC tumors. Tumors in the first group consist of approximately the same numbers of macrophages and CD8+ T-cells and and a slightly smaller number of CD4+ T cells than CD8+ T cells, while tumors in the second group have a significantly high number of macrophages compared to any other immune cell type (P-value $$<0.01$$ < 0.01 ). The third group of ccRCC tumors have a significantly higher number of CD8+ T-cells than any other immune cell type (P-value $$<0.01$$ < 0.01 ), while tumors in the group 4 have approximately the same numbers of macrophages and CD4+ T-cells and a significantly smaller number of CD8+ T-cells than CD4+ T-cells (P-value $$<0.01$$ < 0.01 ). Moreover, there is a high positive correlation between the expression levels of IFNG and PDCD1 and the percentage of CD8+ T-cells, and higher stage and grade of tumors have a substantially higher percentage of CD8+ T-cells. Furthermore, the primary tumors of patients, who are tumor free at the last time of follow up, have a significantly higher percentage of mast cells (P-value $$<0.01$$ < 0.01 ) compared to the patients with tumors for all groups of tumors except group 3.

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Section: Resultsmentioning

confidence: 84%

Immune classification of clear cell renal cell carcinoma

Akbarinejad

Shahriyari

2021

Sci Rep

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“…Moreover, RGS5 is a hypoxia-inducible factor-1 dependent involved in the induction of endothelial apoptosis 25 . In our previous study on TCGA data, we found that a high expression level of RGS5 in ccRCC primary tumors is associated with better survival months, and when the grade of ccRCC tumor increases, the RGS5 expression level significantly decreases 26 . Interestingly, cluster ( CD 8 < CD 4 ≈ M Φ) has the highest RGS5 expression level compared to the other clusters, and tumor free patients have a higher level of RGS5 expression than patients with tumor (Figure 6A).…”

Section: Resultsmentioning

confidence: 84%

Immune Classification of Clear Cell Renal Cell Carcinoma

Akbarinejad

Shahriyari

2020

Preprint

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ABSTRACTSince the outcome of treatments, particularly immunotherapeutic interventions, depends on the tumor immune micro-environment (TIM), several experimental and computational tools such as flow cytometry, immunohistochemistry, and digital cytometry have been developed and utilized to classify TIM variations. In this project, we identify immune pattern of clear cell renal cell carcinomas (ccRCC) by estimating the percentage of each immune cell type in 526 renal tumors using the new powerful technique of digital cytometry. The results, which are in agreement with the results of a large-scale mass cytometry analysis, show that the most frequent immune cell types in ccRCC tumors are CD8+ T-cells, macrophages, and CD4+ T-cells. Saliently, unsupervised clustering of ccRCC primary tumors based on their relative number of immune cells indicates the existence of four distinct groups of ccRCC tumors. Tumors in the first group consist of approximately the same numbers of CD8+ T-cells, CD4+ T-cells, and macrophages, while tumors in the second group have a significantly high number of macrophages compared to any other immune cell type (P-value< 0.01). The third group of ccRCC tumors have a significantly higher number of CD8+ T-cells than any other immune cell type (P-value< 0.01), while tumors in the group 4 have approximately the same numbers of macrophages and CD4+ T-cells and a significantly smaller number of CD8+ T-cells than CD4+ T-cells (P-value< 0.01). Moreover, there is a high positive correlation between the expression levels of IFNG and PDCD1 and the percentage of CD8+ T-cells, and higher stage and grade of tumors have a substantially higher percentage of CD8+ T-cells. Furthermore, the primary tumors of patients, who are tumor free at the last time of follow up, have a significantly higher percentage of mast cells (P-value< 0.01) compared to the patients with tumors for all groups of tumors except group 3.

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“…Additionally, the landscape of local DNRS for signaling and non-signaling genes is presented in Figure 3H , from which it is seen that a significant increase in the local DNRS of signaling genes occurs in Stage II. When applied to KIRC, it is seen from Figure 3I that the peak of DNRS (

1.592 04

) appears in Stage II, after which the lipid levels around the kidney increases rapidly, and then the tumor invades the renal vein ( Su and Shahriyari, 2020 ). As presented in gray in Figure 3I , dynamic changes (

0.053

) in the mean gene expression were detected in Stage III and therefore failed to provide timely early-warning signals of the cell fate transition.…”

Section: Resultsmentioning

confidence: 99%

Identifying the critical state of complex biological systems by the directed-network rank score method

et al. 2022

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Motivation Catastrophic transitions are ubiquitous in the dynamic progression of complex biological systems; that is, a critical transition at which complex systems suddenly shift from one stable state to another occurs. Identifying such a critical point or tipping point is essential for revealing the underlying mechanism of complex biological systems. However, it is difficult to identify the tipping point since few significant differences in the critical state are detected in terms of traditional static measurements. Results In this study, by exploring the dynamic changes in gene cooperative effects between the before-transition and critical states, we presented a model-free approach, the directed-network rank score (DNRS), to detect the early-warning signal of critical transition in complex biological systems. The proposed method is applicable to both bulk and single-cell RNA-sequencing (scRNA-seq) data. This computational method was validated by the successful identification of the critical or pre-transition state for both simulated and six real datasets, including three scRNA-seq datasets of embryonic development and three tumor datasets. In addition, the functional and pathway enrichment analyses suggested that the corresponding DNRS signaling biomarkers were involved in key biological processes. Availability The source code is freely available at https://github.com/zhongjiayuan/DNRS Supplementary information Supplementary data are available at Bioinformatics online.

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RGS5 plays a significant role in renal cell carcinoma

Cited by 17 publications

References 42 publications

Immune classification of clear cell renal cell carcinoma

Immune classification of clear cell renal cell carcinoma

Immune Classification of Clear Cell Renal Cell Carcinoma

Identifying the critical state of complex biological systems by the directed-network rank score method

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