Abstract
Purpose
Transglutaminases (TGs) are multifunctional enzymes exhibiting transglutaminase crosslinking, as well as atypical GTPase/ATPase and kinase activities. Here, we used an integrated comprehensive analysis to assess the genomic, transcriptomic and immunological landscapes of TGs across cancers.
Methods
Gene expression and immune cell infiltration patterns across cancers were obtained from The Cancer Genome Atlas (TCGA) database and Gene Set Enrichment Analysis (GSEA) datasets. Western blotting, immunofluorescence staining, enzyme-linked immunosorbent assays, and orthotopic xenograft models were used to validate our database-derived results.
Results
We found that the overall expression of TGs (designated as the TG score) is significantly upregulated in multiple cancers and related to a worse patient survival. The expression of TG family members can be regulated through multiple mechanisms at the genetic, epigenetic and transcriptional levels. The expression of transcription factors crucial for epithelial-to-mesenchymal transition (EMT) is commonly correlated with the TG score in many cancer types. Importantly, TGM2 expression displays a close connection with chemoresistance to a wide range of chemotherapeutic drugs. We found that TGM2 expression, F13A1 expression and the overall TG score were positively correlated with the infiltration of immune cells in all cancer types tested. Functional and clinical verification revealed that a higher TGM2 expression is linked with a worse patient survival, an increased IC50 value of gemcitabine, and a higher abundance of tumor-infiltrating macrophages in pancreatic cancer. Mechanistically, we found that increased C–C motif chemokine ligand 2 (CCL2) release mediated by TGM2 contributes to macrophage infiltration into the tumor microenvironment.
Conclusions
Our results reveal the relevance and molecular networks of TG genes in human cancers and highlight the importance of TGM2 in pancreatic cancer, which may provide promising directions for immunotherapy and for addressing chemoresistance.
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Data availability
All sequencing data were obtained from publicly available database (TCGA https://portal.gdc.cancer.gov and GTEx https://xenabrowser.net) and other data generated or analyzed in this study were included in the article.
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Funding
This work was supported by grants from the National Natural Science Foundation of China (No. 82173153, 81902370, 81972582 and 92168111) and the Natural Science Foundation of Shanghai (19ZR1452500).
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Conception and design: Q. Yang, XM Yang, FY Dong, ZG Zhang; Development of methodology: S. Zhang, Q. Yang; Acquisition of data: S. Zhang, H. Li, Q. Yang, HF Yao, T. Su, W. Hao, SH Jiang; Analysis and interpretation of data: S. Zhang, Q. Yang, XM Yang, T. Su, H. Li, FY Dong, SH Jiang; Writing, review and/or revision of the manuscript: S. Zhang, Q. Yang, XM Yang, FY. Dong, ZG Zhang; Administrative, technical or material support: Q. Yang, FY Dong, ZG Zhang, XM Yang. All authors read and approved the final version of the manuscript.
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Studies using human PDAC samples were approved by the Research Ethics Committee of Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University (No. RA-2019–116). The animal experiments according to the protocols were approved by the Shanghai Jiao Tong University Animal Care Commission and all mice received humane care in accordance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals.
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Shan Zhang, Hong-Fei Yao, Hui Li and Tong Su share co-first authorship.
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Supplementary Figure 1
The prognostic value of the TG score in KIRC, LUSC, PAAD, and STAD. Time-dependent receiver operating characteristic (ROC) curves of the prognostic TG score model in TGCA-KIRC (A–C), TGCA-LUSC (D–F), TGCA-PAAD (G–I), and TGCA-STAD (J–L). The X-axis shows the false-positive rates, and the Y-axis shows the true-positive rates (PNG 233 kb)
Supplementary Figure 2
Mutation and CNV of TG family genes across cancers. (A) Point mutation frequency in TG family genes across TCGA cancer types. (B) The frequencies of missense variants and loss-of-function mutations in TG family genes in 20 TCGA cancer types. The highest frequency of mutations in TG family genes was observed in UCEC. (C) The frequency of copy number variations in TG family genes in different TCGA cancers. The gradient of colors in the bubble map represents the log2-fold change between cancer and normal tissues. The purple nodes indicate high expression in cancer, while the green nodes indicate low expression in cancer. The red circles represent copy number amplification, whereas the blue circles represent deletion (PNG 197 kb)
Supplementary Figure 3
The relationships between TG expression and drug sensitivity based on the Cancer Cell Line Encyclopedia (CCLE) database. The gradient of colors in the bubble map represents the R-value. Purple indicates a positive correlation with sensitivity to the drug candidates, while green indicates a negative correlation. The size of the nodes represents the statistical significance; the larger the size is, the greater the significance (PNG 119 kb)
Supplementary Figure 4
The relationship between TG expression and drug sensitivity based on the Genomics of Drug Sensitivity in Cancer (GDSC) database. The gradient of colors in the bubble map represents the R-value. Purple indicates a positive correlation with sensitivity to the drug candidates, while green indicates a negative correlation. The size of the nodes represents the statistical significance; the larger the size is, the greater the significance (PNG 585 kb)
Supplementary Figure 5
(A) Western blotting analysis of the knockdown efficiency of TGM2 in panc1 and patu-8988 cells. (B) Western blotting analysis of the knockdown and overexpression efficiency of Tgm2 in KPC1199 cells. (C) Analysis of CCL2 expression in TGM2 overexpression and control pancreatic cancer cells (n=3 replicates per group, means ± standard deviations, one of three biological replicates). *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001 (PNG 922 kb)
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Zhang, S., Yao, HF., Li, H. et al. Transglutaminases are oncogenic biomarkers in human cancers and therapeutic targeting of TGM2 blocks chemoresistance and macrophage infiltration in pancreatic cancer. Cell Oncol. 46, 1473–1492 (2023). https://doi.org/10.1007/s13402-023-00824-7
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DOI: https://doi.org/10.1007/s13402-023-00824-7