Identification of a tumor microenvironment-related gene signature to improve the prediction of cervical cancer prognosis

Chen, Qian; Qiu, Bingqing; Zeng, Xianmin; Hu, Lang; Huang, Dongping; Chen, Kaihua; Qiu, Xiaoqiang

doi:10.1186/s12935-021-01867-2

Cited by 10 publications

(9 citation statements)

References 41 publications

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“…In this study, we attempted to establish a predictive model with four immune-related genes with an expression matrix of 1-or-2 to replace their previous specific expression values. To a certain extent, we avoided the problem caused by platform differences and detecting technique to a certain extent, so as to make up for the limitations of previous studies (20)(21)(22)(23)(24)(25).…”

Section: Discussionmentioning

confidence: 99%

“…However, the association of their model with immune infiltration was not definitely pinpointed and had nothing to do with clinicopathological characteristics. In four latest published studies, researchers have reclassified the cervical cancer cohorts and established gene signature derived from the ESTIMATE algorithm or constructed specific TMEscore based on the penetration pattern of immune cells to evaluate the relationship between immune infiltration and prognosis (20)(21)(22)(23). Considering the relatively great differences between tumor and normal tissues, we aimed at exploring the heterogeneity in immune landscape of tumors.…”

Section: Discussionmentioning

confidence: 99%

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Development of a Novel Immune Infiltration-Based Gene Signature to Predict Prognosis and Immunotherapy Response of Patients With Cervical Cancer

Zhang

et al. 2021

Front. Immunol.

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Predictive models could indicate the clinical outcome of patients with carcinoma. Cervical cancer is one of the most frequently diagnosed female malignancies. Herein, we proposed an immune infiltration-related gene signature that predicts prognosis of patients with cervical cancer and depicts the immune landscape as well. We utilized the transcriptome data of The Cancer Genome Atlas (TCGA) and estimated the infiltration level of 28 immune cell types. We screened out four immune cell types conducive to patient survival and recognized their shared differentially expressed genes (DEGs). Four core genes (CHIT1, GTSF1L, PLA2G2D, and GNG8) that composed the ultimate signature were identified via univariate and multivariate Cox regression. The optimal model we built up could distinguish patients with cervical cancer into high-score and low-score subgroups. These two subgroups showed disparity in aspects of patient survival, immune infiltration landscape, and response to immune checkpoint inhibitors. Additionally, we found that GTSF1L was decreased gradually along with the severity of cervical lesions, and its potential role in immune contexture and clinical practice were also demonstrated. Our results suggested that the Immunoscore based on four immune-related genes could serve as a supplementary criterion to effectively foresee the survival outcome, tumor infiltration status, and immunotherapy efficacy of cervical cancer patients.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Development of a Novel Immune Infiltration-Based Gene Signature to Predict Prognosis and Immunotherapy Response of Patients With Cervical Cancer

Zhang

et al. 2021

Front. Immunol.

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“…In our study, taken together, we believe that this model can be used to evaluate the prognostic risk in cervical cancer patients. And our model is better than other cervical cancer models [ 23 , 24 ].…”

Section: Discussionmentioning

confidence: 85%

Constructe a novel 5 hypoxia genes signature for cervical cancer

Yang

et al. 2021

Cancer Cell Int

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Background Hypoxia, which affects the development, metastasis and prognosis of cancer, represents a key feature of cancer. This study describe a hypoxia risk factor model, with predicting the prognosis of cervical cancer. Methods Based on hypoxia pathway related genes, we divided cervical cancer samples into high and low expression groups. A cox analysis was then performed. Genes from these cervical cancer samples showing a significant impact on OS were selected for cluster analysis to obtain two subtypes. The TPM dataset of TCGA was divided into training and validation sets. For the training set, a lasso analysis was conducted as based on cox analysis of meaningful genes and a risk factor model was constructed. The constructed model was verified in internal and external data sets. Finally, RT-PCR, immunohistochemistry were used to detect the expression of relative genes or proteins and functional assays were used to evaluate the biological function of signature genes. Results Two molecular subtypes were obtained, Cluster2 vs Cluster1.These subtypes were obtained by clustering with a total of 149 DEGs (Differential expressed genes) being in line with this standard, of which 27 were up-regulated and 122 were down-regulated. The five genes with lambda = 0.0571 were selected to construct the model, the RiskScore = AK4*0.042 + HK2*0.021 + P4HA1*0.22 + TGFBI*0.1 + VEGFA*0.077. Further, in order to verify the signature, we used TCGA-test and GSE44001 chip datasets to test, and finally got a good risk prediction effect in those datasets. Moreover, the result of RT-PCR and immunohistochemistry demonstrated that AK4, HK2, P4HA1, TGFBI and VEGFA were all highly expressed in these cervical cancer tissue samples. The functional study shown that expression of AK4, HK2, P4HA1, TGFBI and VEGFA can regulate the proliferation, migration, and invasion ability of cervical cancer cells in vitro. Conclusions In summary, we developed a 5-gene signature prognostic hierarchical system based on the hypoxic pathway of cervical cancer, which is independent of clinical characteristics. And also conducted experimental verifications on these signature gene. Therefore, we propose that use of this classifier as a molecular diagnostic test can provide an effective means for evaluating the prognostic risk of cervical cancer patients, and provide potential targets for the treatment of cervical cancer patients.

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“…SLAMF1 (CD150) and SLAMF6 belong to the signaling lymphocytic activation molecule (SLAM) family and express on several immune cells including T cells, B cells, and NK cells ( 56 ). Previous studies have shown that the expressions of SLAMF1 in cervical cancer and SLAMF6 in liver cancer were closely related to tumor infiltration of immune cells and patient prognosis ( 57 , 58 ). The SH2D1A gene encodes SH2 domain-containing protein 1A, which is often known as SLAM-associated protein.…”

Section: Discussionmentioning

confidence: 99%

Metabolic Molecule PLA2G2D Is a Potential Prognostic Biomarker Correlating With Immune Cell Infiltration and the Expression of Immune Checkpoint Genes in Cervical Squamous Cell Carcinoma

Liu

Gao

et al. 2021

Front. Oncol.

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Cervical squamous cell carcinoma (CSCC) is the major pathological type of cervical cancer (CC), the second most prevalent reproductive system malignant tumor threatening the health of women worldwide. The prognosis of CSCC patients is largely affected by the tumor immune microenvironment (TIME); however, the biomarker landscape related to the immune microenvironment of CSCC and patient prognosis is less characterized. Here, we analyzed RNA-seq data of CSCC patients from The Cancer Genome Atlas (TCGA) database by dividing it into high- and low-immune infiltration groups with the MCP-counter and ESTIMATE R packages. After combining weighted gene co-expression network analysis (WGCNA) and differentially expressed gene (DEG) analysis, we found that PLA2G2D, a metabolism-associated gene, is the top gene positively associated with immune infiltration and patient survival. This finding was validated using data from The Cancer Genome Characterization Initiative (CGCI) database and further confirmed by quantitative reverse transcription-polymerase chain reaction (qRT-PCR). Finally, multiplex immunohistochemistry (mIHC) was performed to confirm the differential infiltration of immune cells between PLA2G2D-high and PLA2G2D-low tumors at the protein level. Our results demonstrated that PLA2G2D expression was significantly correlated with the infiltration of immune cells, especially T cells and macrophages. More importantly, PLA2G2D-high tumors also exhibited higher infiltration of CD8+ T cells inside the tumor region than PLA2G2D-low tumors. In addition, PLA2G2D expression was found to be positively correlated with the expression of multiple immune checkpoint genes (ICPs). Moreover, based on other immunotherapy cohort data, PLA2G2D high expression is correlated with increased cytotoxicity and favorable response to immune checkpoint blockade (ICB) therapy. Hence, PLA2G2D could be a novel potential biomarker for immune cell infiltration, patient survival, and the response to ICB therapy in CSCC and may represent a promising target for the treatment of CSCC patients.

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Identification of a tumor microenvironment-related gene signature to improve the prediction of cervical cancer prognosis

Cited by 10 publications

References 41 publications

Development of a Novel Immune Infiltration-Based Gene Signature to Predict Prognosis and Immunotherapy Response of Patients With Cervical Cancer

Development of a Novel Immune Infiltration-Based Gene Signature to Predict Prognosis and Immunotherapy Response of Patients With Cervical Cancer

Constructe a novel 5 hypoxia genes signature for cervical cancer

Metabolic Molecule PLA2G2D Is a Potential Prognostic Biomarker Correlating With Immune Cell Infiltration and the Expression of Immune Checkpoint Genes in Cervical Squamous Cell Carcinoma

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