FPR1 mediates the tumorigenicity of human cervical cancer cells

Cao, Guangming; Zhang, Zhenyu

doi:10.2147/cmar.s182795

Cited by 16 publications

(12 citation statements)

References 37 publications

(34 reference statements)

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“…Studies have shown that DHRS9 is involved in the biosynthesis of all trans-retinoic acid and exerts an anti-tumour role by inhibiting the proliferation of tumour cells, including acute promyelocytic leukemia, squamous cell carcinoma, neurocytoma and hepatocellular carcinoma [ 63 – 65 ]. The formyl peptide receptor 1 (FPR1), a G-protein-coupled receptor expressed by bone marrow-derived cells [ 66 ], participates in activation of immune cell induced by N-formyl peptide [ 67 , 68 ]. S1PRs is the ligand of lipid second messenger S1P, exerts an important role in the physiological process of cell proliferation, differentiation, migration and immune response [ 69 ].…”

Section: Discussionmentioning

confidence: 99%

Comprehensive analysis of prognostic gene signatures based on immune infiltration of ovarian cancer

et al. 2020

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Background Ovarian cancer (OV) is one of the most common malignant tumors of gynecology oncology. The lack of effective early diagnosis methods and treatment strategies result in a low five-year survival rate. Also, immunotherapy plays an important auxiliary role in the treatment of advanced OV patient, so it is of great significance to find out effective immune-related tumor markers for the diagnosis and treatment of OV. Methods Based on the consensus clustering analysis of single-sample gene set enrichment analysis (ssGSEA) score transformed via The Cancer Genome Atlas (TCGA) mRNA profile, we obtained two groups with high and low levels of immune infiltration. Multiple machine learning methods were conducted to explore prognostic genes associated with immune infiltration. Simultaneously, the correlation between the expression of mark genes and immune cells components was explored. Results A prognostic classifier including 5 genes (CXCL11, S1PR4, TNFRSF17, FPR1 and DHRS95) was established and its robust efficacy for predicting overall survival was validated via 1129 OV samples. Some significant variations of copy number on gene loci were found between two risk groups and it showed that patients with fine chemosensitivity has lower risk score than patient with poor chemosensitivity (P = 0.013). The high and low-risk groups showed significantly different distribution (P < 0.001) of five immune cells (Monocytes, Macrophages M1, Macrophages M2, T cells CD4 menory and T cells CD8). Conclusion The present study identified five prognostic genes associated with immune infiltration of OV, which may provide some potential clinical implications for OV treatment.

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Section: Discussionmentioning

confidence: 99%

Comprehensive analysis of prognostic gene signatures based on immune infiltration of ovarian cancer

et al. 2020

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“…Jiang et al reported that overexpression of FPR1 was associated with drug-resistant BCa and may deteriorate the overall condition of drug-resistant BCa 20 . The biological behaviors of FPR1 were also explored in ovarian cancer 21 , cervical cancer 22 , and lung cancer 23 as a risk factor related to poor prognosis, advanced stage and metastasis. However, Prevete et al found that FPR1 acted as a tumor suppressor in human gastric cancer by counteract angiogenesis 24 .…”

Section: Discussionmentioning

confidence: 99%

An immune cell infiltration-related gene signature predicts prognosis for bladder cancer

Chen

Pan

Jin

et al. 2021

Sci Rep

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To explore novel therapeutic targets, develop a gene signature and construct a prognostic nomogram of bladder cancer (BCa). Transcriptome data and clinical traits of BCa were downloaded from UCSC Xena database and Gene Expression Omnibus (GEO) database. We then used the method of Single sample Gene Set Enrichment analysis (ssGSEA) to calculate the infiltration abundances of 24 immune cells in eligible BCa samples. By weighted correlation network analysis (WGCNA), we identified turquoise module with strong and significant association with the infiltration abundance of immune cells which were associated with overall survival of BCa patients. Subsequently, we developed an immune cell infiltration-related gene signature based on the module genes (MGs) and immune-related genes (IRGs) from the Immunology Database and Analysis Portal (ImmPort). Then, we tested the prognostic power and performance of the signature in both discovery and external validation datasets. A nomogram integrated with signature and clinical features were ultimately constructed and tested. Five prognostic immune cell infiltration-related module genes (PIRMGs), namely FPR1, CIITA, KLRC1, TNFRSF6B, and WFIKKN1, were identified and used for gene signature development. And the signature showed independent and stable prognosis predictive power. Ultimately, a nomogram consisting of signature, age and tumor stage was constructed, and it showed good and stable predictive ability on prognosis. Our prognostic signature and nomogram provided prognostic indicators and potential immunotherapeutic targets for BCa. Further researches are needed to verify the clinical effectiveness of this nomogram and these biomarkers.

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“…LASSO Cox regression analysis identified MSR1, FPR1, RNASE2, GBP2, CXCL9, CXCL11, C5AR1, CCL13, FGF17, CXCL14, and PI3 as hub genes. Among these, FPR1 participates in tumorigenicity of human cervical cancer cells via activation of immune cells induced by N-formyl peptide (Cao and Zhang, 2018;Minopoli et al, 2019). CXCL9 and CXCL11 have been associated with activation of Th1 immunity within TME and a favorable response to chemotherapy and immunotherapy in melanoma (Harlin et al, 2009;Hong et al, 2011).…”

Section: Discussionmentioning

confidence: 99%

Combination of Immune-Related Genomic Alterations Reveals Immune Characterization and Prediction of Different Prognostic Risks in Ovarian Cancer

Zhao

Cong

Guo

et al. 2021

Front. Cell Dev. Biol.

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With the highest case-fatality rate among women, the molecular pathological alterations of ovarian cancer (OV) are complex, depending on the diversity of genomic alterations. Increasing evidence supports that immune infiltration in tumors is associated with prognosis. Therefore, we aim to assess infiltration in OV using multiple methods to capture genomic signatures regulating immune events to identify reliable predictions of different outcomes. A dataset of 309 ovarian serous cystadenocarcinoma patients with overall survival >90 days from The Cancer Genome Atlas (TCGA) was analyzed. Multiple estimations and clustering methods identified and verified two immune clusters with component differences. Functional analyses pointed out immune-related alterations underlying internal genomic variables potentially. After extracting immune genes from a public database, the LASSO Cox regression model with 10-fold cross-validation was used for selecting genes associated with overall survival rate significantly, and a risk score model was then constructed. Kaplan–Meier survival and Cox regression analyses among cohorts were performed systematically to evaluate prognostic efficiency among the risk score model and other clinical pathological parameters, establishing a predictive ability independently. Furthermore, this risk score model was compared among identified signatures in previous studies and applied to two external cohorts, showing better prediction performance and generalization ability, and also validated as robust in association with immune cell infiltration in bulk tissues. Besides, a transcription factor regulation network suggested upper regulatory mechanisms in OV. Our immune risk score model may provide gyneco-oncologists with predictive values for the prognosis and treatment management of patients with OV.

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FPR1 mediates the tumorigenicity of human cervical cancer cells

Cited by 16 publications

References 37 publications

Comprehensive analysis of prognostic gene signatures based on immune infiltration of ovarian cancer

Comprehensive analysis of prognostic gene signatures based on immune infiltration of ovarian cancer

An immune cell infiltration-related gene signature predicts prognosis for bladder cancer

Combination of Immune-Related Genomic Alterations Reveals Immune Characterization and Prediction of Different Prognostic Risks in Ovarian Cancer

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