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RETRACTED ARTICLE: Renal enhanced CT images reveal the tandem mechanism between tumor cells and immunocytes based on bulk/single-cell RNA sequencing

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Abstract

Metabolic reprogramming is essential for establishing the tumor microenvironment (TME). Glutamine has been implicated in cancer metabolism, but its role in clear cell renal carcinoma (ccRCC) remains unknown. Transcriptome data of patients with ccRCC and single-cell RNA sequencing (scRNA-seq) data were obtained from The Cancer Genome Atlas (TCGA, 539 ccRCC samples and 59 normal samples) database and GSE152938 (5 ccRCC samples). Differentially expressed genes related to glutamine metabolism (GRGs) were obtained from the MSigDB database. Consensus cluster analysis distinguished metabolism-related ccRCC subtypes. LASSO-Cox regression analysis was used to construct a metabolism-related prognostic model. The ssGSEA and ESTIMATE algorithms evaluated the level of immune cell infiltration in the TME, and the immunotherapy sensitivity score was obtained from TIDE. Cell–cell communication analysis was used to observe the distribution and effects of the target genes in the cell subsets. An image genomics model was constructed using imaging feature extraction and a machine learning algorithm. Results: Fourteen GRGs were identified. Overall survival and progression-free survival rates were lower in metabolic cluster 2, compared with those in cluster 1. The matrix/ESTIMATE/immune score in C1 decreased, but tumor purity in C2 increased. Immune cells were more active in the high-risk group, in which CD8 + T cells, follicular helper T cells, Th1 cells, and Th2 cells were significantly higher than those in the low-risk group. The expression levels of immune checkpoints were also significantly different between the two groups. RIMKL mainly appeared in epithelial cells in the single-cell analysis. ARHGAP11B was sparsely distributed. The imaging genomics model proved effective in aiding with clinical decisions. Glutamine metabolism plays a crucial role in the formation of immune TMEs in ccRCC. It is effective in differentiating the risk and predicting survival in patients with ccRCC. Imaging features can be used as new biomarkers for predicting ccRCC immunotherapy.

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Data availability

Any data and R scripts in this study can be obtained from the corresponding author upon reasonable request. The final manuscript has been read and approved by all the authors. In this study, publicly available datasets were analyzed. These data are available from TCGA (https://portal.gdc.cancer.gov/) and GEO (https://www.ncbi.nlm.nih.gov/) databases (Data Release 33.0—May 03, 2022).

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Acknowledgements

The authors thank the participants and staff for their contribution.

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Authors and Affiliations

  1. Department of Urology, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, China

    Haote Liang, Keming Wu, Rongrong Wu, Zhexian Deng & Hongde Chen

  2. Department of Pathology, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, China

    KaTe Huang

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  1. Haote Liang
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  2. Keming Wu
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  3. Rongrong Wu
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  4. KaTe Huang
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  5. Zhexian Deng
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  6. Hongde Chen
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Contributions

Conceptualization: Haote Liang; data curation: Keming Wu; formal analysis: Rongrong Wu; supervision and validation: Hongde Chen; other authors contributed to the manuscript.

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Correspondence to Hongde Chen.

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This article has been retracted. Please see the retraction notice for more detail:https://doi.org/10.1007/s10142-024-01385-0

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Liang, H., Wu, K., Wu, R. et al. RETRACTED ARTICLE: Renal enhanced CT images reveal the tandem mechanism between tumor cells and immunocytes based on bulk/single-cell RNA sequencing. Funct Integr Genomics 23, 88 (2023). https://doi.org/10.1007/s10142-023-01011-5

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  • DOI: https://doi.org/10.1007/s10142-023-01011-5

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