Comprehensive analysis of angiogenesis subtype of squamous cell carcinoma

Qin, Fanglu; Lin, Sheng-hua; Deng, Kun; Qin, Junqi; Xu, Zhanyu; Yuan, Liqiang; Wei, Jiangbo; Sun, Yu; Zheng, Tiaozhan; Li, Shikang

doi:10.1186/s12957-021-02367-3

Cited by 3 publications

(4 citation statements)

References 36 publications

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“…Strategies to improve patient prognosis and quality of life deserve further study. It is reported that abnormal expression of important genes and alterations of signaling pathways are associated with cancer pathogenesis [ 23 , 24 ]. For instance, Qin F et al revealed a novel angiogenesis subtype classification in squamous cell carcinoma [ 23 ].…”

Section: Discussionmentioning

confidence: 99%

“…For instance, Qin F et al revealed a novel angiogenesis subtype classification in squamous cell carcinoma [ 23 ]. Li S et al screened six prognostic hub genes by weighted gene co-expression network analysis (WGCNA) combined with LASSO Cox-PH analysis, which provided a new strategy for targeted therapy of cervical cancer [ 24 ]. The study aimed to explore the molecular mechanism of cervical cancer and find new tumor markers and biological methods to treat tumors .…”

Section: Discussionmentioning

confidence: 99%

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KIF14 affects cell cycle arrest and cell viability in cervical cancer by regulating the p27Kip1 pathway

et al. 2022

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Background Cervical cancer is a kind of malignant gynecological tumor. The first choice for treating cervical cancer is still a combination of surgery and chemoradiotherapy, but the 5-year survival rate remains poor. Therefore, researchers are trying to find new ways to diagnose and treat cervical cancer early. Methods The expression level of KIF14 in cells and tissues was determined via qRT–PCR. The ability of the cells to proliferate, migrate, and invade was examined using CCK-8 assay kits, colony formation assays, and Transwell chambers. The expression levels of Cyclin D1, Cyclin B1, p21, and p27 were also detected using western blot assays. Results The results suggested that p27 is a key regulatory factor in the KIF14-mediated regulation of the cell cycle. In addition, KIF14 knockdown promotes malignancy in cervical cancer cells by inhibiting p27 degradation, resulting in cell cycle arrest. Conclusions KIF14 is an oncogene in cervical cancer, and knocking down KIF14 causes cell cycle arrest by inhibiting p27 degradation, thus affecting cell viability, proliferation, and migration. These results provide a potential therapeutic target for cervical cancer.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

KIF14 affects cell cycle arrest and cell viability in cervical cancer by regulating the p27Kip1 pathway

et al. 2022

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“…Thus, we speculate that 3 IRLs (BARX1-DT, KLHL7-DT, and LINC02154) may boost the development of an immunosuppressive TME by thoroughly downregulating the expression of key immunomodulators such as CCR3, CXCL10, and CXCL9 and subsequently decreasing the recruitment of effector CD8 T cells, thereby exerting resistance to checkpoint immunotherapy. Interestingly, ssGSEA results and correlation analysis show that signaling pathways related to tumor invasion and metastasis, such as p53 signaling pathway, EMT2, EMT3, and TGF-beta signaling pathway, were mainly involved in high-risk groups, which are recognized as immunosuppressive and play a key role in tumorigenesis [ 26 ]. However, CD8 T effector was significantly involved in low-risk group, which indicates that the low-risk group was immune activation and maybe respond better to immunotherapy.…”

Section: Discussionmentioning

confidence: 99%

Construction and validation of immune-related LncRNAs classifier to predict prognosis and immunotherapy response in laryngeal squamous cell carcinoma

Pan

Duan

et al. 2022

World J Surg Onc

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Background Rapid advances in transcriptomic profiles have resulted in recognizing IRLs (immune-related long noncoding RNAs), as modulators of the expression of genes related to immune cells that mediate immune inhibition as well as immune stimulatory, indicating LncRNAs play fundamental roles in immune modulation. Hence, we establish an IRL classifier to precisely predict prognosis and immunotherapeutic efficiency in laryngeal squamous cell carcinoma (LSCC). Methods LSCC RNA-seq (RNA sequencing) datasets, somatic mutation data, and corresponding clinicopathologic information were acquired from TCGA (the Cancer Genome Atlas) and Gene Expression Omnibus (GEO) databases. Spearman correlation analysis identified LncRNAs associated with immune-related genes (IRG). Based on Lasso penalized regression and random forest (RF), we constructed an IRL classifier associated with prognosis. GEO database was utilized to validate the IRL classifier. The predictive precision and clinical application of the IRL classifier were assessed and compared to clinicopathologic features. The immune cell infiltration of LSCC was calculated via CIBERSORTx tools and ssGSEA (single-sample gene set enrichment analysis). Then, we systematically correlated the IRL classifier with immunological characteristics from multiple perspectives, such as immune-related cells infiltrating, tumor microenvironment (TME) scoring, microsatellite instability (MSI), tumor mutation burden (TMB), and chemokines. Finally, the TIDE (tumor immune dysfunction and exclusion) algorithm was used to predict response to immunotherapy. Results Based on machine learning approach, three prognosis-related IRLs (BARX1-DT, KLHL7-DT, and LINC02154) were selected to build an IRL classifier. The IRL classifier could availably classify patients into the low-risk and high-risk groups based on the different endpoints, including recurrence-free survival (RFS) and overall survival (OS). In terms of predictive ability and clinical utility, the IRL classifier was superior to other clinical characteristics. Encouragingly, similar results were observed in the GEO databases. Immune infiltration analysis displayed immune cells that are significantly richer in low-risk group, CD8 T cells and activated NK cells via CIBERSORTx algorithm as well as activated CD8 T cell via ssGSEA. Additionally, compared with the high-risk group, immune score, CD8 T effector was higher in the low-risk group, yet stromal score, score of p53 signaling pathway and TGFher in the Tx algorithm, was lower in the low-risk group. Corresponding results were confirmed in GEO dataset. Finally, TIDE analysis uncovered that the IRL classifier may be effectually predict the clinical response of immunotherapy in LSCC. Conclusion Based on BARX1-DT, KLHL7-DT, and LINC02154, the IRL classifier was established, which can be used to predict the prognosis, immune infiltration status, and immunotherapy response in LSCC patients and might facilitate personalized counseling for immunotherapy.

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“…The efficacy of anti-angiogenic drugs in combination with immune checkpoint inhibitors is also attributed to the crosstalk of immune cells in the tumor microenvironment ( Ribatti et al, 2021 ). It has been shown that angiogenesis-related gene signatures in gastric cancer ( Ren et al, 2020 ; Qing et al, 2022 ), hepatocellular carcinoma ( Lv et al, 2021 ), and squamous carcinoma of multiple tissue types ( Qin et al, 2021 )can predict patient prognosis and elucidate the characteristics of the immune microenvironment to guide immunotherapy. Therefore, studying immune infiltration based on AG genes in cervical cancer can help to provide new predictive prognostic markers and reference for comprehensive treatment.…”

Section: Introductionmentioning

confidence: 99%

Angiogenesis-related gene signatures reveal the prognosis of cervical cancer based on single cell sequencing and co-expression network analysis

Kang

Xiang

Chen

et al. 2023

Front. Cell Dev. Biol.

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Cervical cancer ranks first in female reproductive tract tumors in terms of morbidity and mortality. Yet the curative effect of patients with persistent, recurrent or metastatic cervical cancer remains unsatisfactory. Although antitumor angiogenic drugs have been recommended as the first-line treatment options for cervical cancer, there are no comprehensive prognostic indicators for cervical cancer based on angiogenic signature genes. In this study, we aimed to develop a model to assess the prognosis of cervical cancer based on angiogenesis-related (AG) signature genes, and to provide some reference for the comprehensive treatment of cervical cancer in the clinical setting. First we screened the AG gene set from GeneCard website, and then performed angiogenesis-related scores (AGS) per cell from single cell sequencing dataset GSE168652, followed by performing weighted gene co-expression network analysis (WGCNA) for cervical cancer patients according to angiogenesis phenotype. Thus, we established a prognostic model based on AGS by taking the intersection of WGCNA angiogenic module gene and differential gene (DEGs) of GSE168652. The GSE44001 was selected as an external validation set, followed by performing ROC curve analysis to assess its accuracy. The results showed that we successfully constructed a prognostic model related to the AG genes. Patients in the high-AGS group in both the train, test and the validation sets had a worse prognosis than those in the low-AGS group, had lower expression of most immune checkpoint-associated genes and lower tumor mutational burden as well. Patients in the low-AGS group were more sensitive to AMG.706, Bosutinib, and Lenalidomide while Imatinib, Pazopanib, and Sorafenib were more recommended to patients in the high-AGS group. Finally, TXNDC12 and ZC3H13, which have high hazard ratio and poor prognosis in the model, were highly expressed in cervical cancer cell lines and tissue. Meanwhile, the results showed that TXNDC12 promoted the migration of cervical cancer cells and the tubule-forming ability of endothelial cells. In conclusion, our model based on genes with AG features can effectively assess the prognosis of cervical cancer, and can also provide reference for clinicians to choose immune-related treatments.

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Comprehensive analysis of angiogenesis subtype of squamous cell carcinoma

Cited by 3 publications

References 36 publications

KIF14 affects cell cycle arrest and cell viability in cervical cancer by regulating the p27Kip1 pathway

KIF14 affects cell cycle arrest and cell viability in cervical cancer by regulating the p27Kip1 pathway

Construction and validation of immune-related LncRNAs classifier to predict prognosis and immunotherapy response in laryngeal squamous cell carcinoma

Angiogenesis-related gene signatures reveal the prognosis of cervical cancer based on single cell sequencing and co-expression network analysis

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