A novel prognostic biomarker CD3G that correlates with the tumor microenvironment in cervical cancer

Wang, Jingshuai; Gu, Xuemin; Cao, Leilei; Ouyang, Yiqin; Xiao, Qi; Wang, Zhijie; Wang, Jianjun

doi:10.3389/fonc.2022.979226

Cited by 9 publications

(7 citation statements)

References 49 publications

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“…Conversely, the CD3G protein, which forms the TCR/CD3 complex and is expressed on the surface of T cells, exhibits potent antitumor activity by recognizing tumor-associated antigens and initiating intracellular signaling ( Marshall et al, 2018 ). Notably, CD3G-deficient patients display reduced T-cell diversity, diminished suppressor function, and increased autoimmune clonality, highlighting the potential of CD3G as a target for immunotherapy ( Rowe et al, 2018 ; Wang et al, 2022 ). Nonetheless, the precise role of CD3G in ovarian cancer warrants further investigation.…”

Section: Discussionmentioning

confidence: 99%

A novel T-cell exhaustion-related feature can accurately predict the prognosis of OC patients

Yuan¹,

Zhao

et al. 2023

Front. Pharmacol.

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The phenomenon of T Cell exhaustion (TEX) entails a progressive deterioration in the functionality of T cells within the immune system during prolonged conflicts with chronic infections or tumors. In the context of ovarian cancer immunotherapy, the development, and outcome of treatment are closely linked to T-cell exhaustion. Hence, gaining an in-depth understanding of the features of TEX within the immune microenvironment of ovarian cancer is of paramount importance for the management of OC patients. To this end, we leveraged single-cell RNA data from OC to perform clustering and identify T-cell marker genes utilizing the Unified Modal Approximation and Projection (UMAP) approach. Through GSVA and WGCNA in bulk RNA-seq data, we identified 185 TEX-related genes (TEXRGs). Subsequently, we transformed ten machine learning algorithms into 80 combinations and selected the most optimal one to construct TEX-related prognostic features (TEXRPS) based on the mean C-index of the three OC cohorts. In addition, we explored the disparities in clinicopathological features, mutational status, immune cell infiltration, and immunotherapy efficacy between the high-risk (HR) and low-risk (LR) groups. Upon the integration of clinicopathological features, TEXRPS displayed robust predictive power. Notably, patients in the LR group exhibited a superior prognosis, higher tumor mutational load (TMB), greater immune cell infiltration abundance, and enhanced sensitivity to immunotherapy. Lastly, we verified the differential expression of the model gene CD44 using qRT-PCR. In conclusion, our study offers a valuable tool to guide clinical management and targeted therapy of OC.

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Section: Discussionmentioning

confidence: 99%

A novel T-cell exhaustion-related feature can accurately predict the prognosis of OC patients

Yuan¹,

Zhao

et al. 2023

Front. Pharmacol.

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“…GNLY and FAM3B have been selected as hub genes in previous models for predicting prognosis and immunotherapy response in BCa [ 32 , 40 ], revealing the good performance of the two genes in prognostic and immunotherapy response prediction. CD3G is involved in T-cell development and signal transduction and has been reported to be associated with TME and prognosis in tumor patients [ 41 , 42 ]. However, no studies have investigated the role of CD3G in prognosis and TME in BCa.…”

Section: Discussionmentioning

confidence: 99%

Development of a Molecular-Subtype-Associated Immune Prognostic Signature That Can Be Recognized by MRI Radiomics Features in Bladder Cancer

et al. 2023

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Background: Bladder cancer (BLCA) is highly heterogeneous with distinct molecular subtypes. This research aimed to investigate the heterogeneity of different molecular subtypes from a tumor microenvironment perspective and develop a molecular-subtype-associated immune prognostic signature that can be recognized by MRI radiomics features. Methods: Individuals with BLCA in The Cancer Genome Atlas (TCGA) and IMvigor210 were classified into luminal and basal subtypes according to the UNC classification. The proportions of tumor-infiltrating immune cells (TIICs) were examined using The Cell Type Identification by Estimating Relative Subsets of RNA Transcripts algorithm. Immune-linked genes that were expressed differentially between luminal and basal subtypes and associated with prognosis were selected to develop the immune prognostic signature (IPS) and utilized for the classification of the selected individuals into low- and high-risk groups. Functional enrichment analysis (GSEA) was performed on the IPS. The data from RNA-sequencing and MRI images of 111 BLCA samples in our center were utilized to construct a least absolute shrinkage and selection operator (LASSO) model for the prediction of patients’ IPSs. Results: Half of the TIICs showed differential distributions between the luminal and basal subtypes. IPS was highly associated with molecular subtypes, critical immune checkpoint gene expression, prognoses, and immunotherapy response. The prognostic value of the IPS was further verified through several validation data sets (GSE32894, GSE31684, GSE13507, and GSE48277) and meta-analysis. GSEA revealed that some oncogenic pathways were co-enriched in the group at high risk. A novel performance of a LASSO model developed as per ten radiomics features was achieved in terms of IPS prediction in both the validation (area under the curve (AUC): 0.810) and the training (AUC: 0.839) sets. Conclusions: Dysregulation of TIICs contributed to the heterogeneity between the luminal and basal subtypes. The IPS can facilitate molecular subtyping, prognostic evaluation, and personalized immunotherapy. A LASSO model developed as per the MRI radiomics features can predict the IPSs of affected individuals.

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“…Based on 233 clinical samples Ting Peng et al con rmed the association between high APOBEC3G expression and poor prognosis in patients with KIRC as well as a positive correlation between APOBEC3G and PD-L1 expression [24]. According to Wang et al, CD3G is a potential prognostic and immunotherapeutic biomarker in patients with cervical cancer [25]. Juncheng Wang.…”

Section: Discussionmentioning

confidence: 99%

Identification of a seven-gene prognostic model for kidney renal cell carcinoma associated with CD8+T lymphocyte cell

Liu,

Yin

2023

Preprint

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CD8 + T lymphocytes are important elements of the tumor immune microenvironment (TIME), hence their involvement in the development and progression of tumors is complex. Data on the precise tumor-infiltrating immune cells (TIICs) gene signature in kidney cancer (KIRC) remain limited. Therefore, this study created a TIICs-related predictive model for patients with KIRC using data from The Cancer Genome Atlas (TCGA). The most important genes associated with CD8 + T lymphocytes were identified using weighted gene co-expression network analysis (WGCNA). Functional categories of important genes were revealed using gene ontology (GO) enrichment and Kyoto encyclopedia of genes and genomes (KEGG) signaling pathway analyses. A CD8 + T lymphocyte-related prognostic model with seven important genes was simultaneously created using the least absolute shrinkage and selection operator (LASSO), univariate and multivariate Cox regressions, and the hub genes EOMES, SIRPG, PTPN7, CD3G, APOBEC3G, FASLG, and TIGIT, which were expressed particularly in CD8 + T lymphocytes according to single-cell sequencing data obtained from the Gene Expression Omnibus (GEO). Finally, we used PCR to verify the expression of hub gene in KIRC.This study identified seven genes associated with CD8 + T lymphocytes that may influence risk stratification in patients with KIRC and serve as possible CD8 + T lymphocyte-related biomarkers.

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A novel prognostic biomarker CD3G that correlates with the tumor microenvironment in cervical cancer

Cited by 9 publications

References 49 publications

A novel T-cell exhaustion-related feature can accurately predict the prognosis of OC patients

A novel T-cell exhaustion-related feature can accurately predict the prognosis of OC patients

Development of a Molecular-Subtype-Associated Immune Prognostic Signature That Can Be Recognized by MRI Radiomics Features in Bladder Cancer

Identification of a seven-gene prognostic model for kidney renal cell carcinoma associated with CD8+T lymphocyte cell

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