Exploration of the Immune-Related Long Noncoding RNA Prognostic Signature and Inflammatory Microenvironment for Cervical Cancer

Yao, Hui; Jiang, Xiya; Fu, Hengtao; Yang, Yinting; Jin, Qinqin; Zhang, Weiyu; Cao, Wujun; Gao, Wei; Zhu, Yuting; Ying, Jie; Tian, Lu; Chen, Guo; Tong, Zhuting; Qi, Jian; Zhou, Sheng

doi:10.3389/fphar.2022.870221

Cited by 9 publications

(10 citation statements)

References 54 publications

(58 reference statements)

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“…In recent years, in-depth studies have developed a mass of immune-related prognostic signatures to predict immunotherapy response and have investigated the relationship between immune landscape and prognosis in CC [46][47][48][49][50]. For instance, Yu et al [51] established an immune infiltration-based signature and demonstrated that a better prognosis in CC patients seemed to be relatively immune-inflamed with greater immune cell infiltration, which was consistent with our findings.…”

Section: Discussionsupporting

confidence: 88%

Immune and inflammation: related factor alterations as biomarkers for predicting prognosis and responsiveness to PD-1 monoclonal antibodies in cervical cancer

et al. 2022

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Purpose We aimed to elucidate the potential mechanisms of effective responsiveness to PD-1 monoclonal antibody and evaluate more reliable biomarkers to improve the ability to predict the populations of cervical cancer (CC) suitable for immunotherapy. Methods Peripheral blood samples of CC patients undergoing anti-PD-1 therapy were collected before and after treatment. Differentially expressed genes (DEGs) were analyzed between partial response (PR) and progressive disease (PD) patients. A novel prognostic inflammation and immune–related response gene (IRRG) model was constructed and its prognostic role, correlation with tumor immunity and tumor mutation were evaluated. Results DEGs in PR patient after treatment could predict the response to PD-1 monoclonal antibodies. Among PR-specific pathways, tumor immunity, leukocyte migration, and cytokine activities were prominently enriched. Additionally, an IRRG signature comprising CTLA4, AZU1, C5, LAT, CXCL2, GDF7, MPL, PPARG and CELA1 was established and validated to predict the prognosis of CC with great accuracy and specificity. This signature could reflect the tumor microenvironment (TME) and tumor mutational burden (TMB). We also found stimulated adaptive immunity and downregulated inflammation at baseline in patients with sensitive responses to PD-1 monoclonal antibody. Conclusion We developed an IRRG signature and verified that it was an independent prognostic factor for predicting survival and could reflect a sensitive response to PD-1 monoclonal antibody, which plays a nonnegligible role in the TME of CC. Further investigations are warranted to confirm that patients with stimulated adaptive immunity and downregulated inflammation at baseline could achieve a better survival benefit from PD-1 monoclonal antibody.

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Section: Discussionsupporting

confidence: 88%

Immune and inflammation: related factor alterations as biomarkers for predicting prognosis and responsiveness to PD-1 monoclonal antibodies in cervical cancer

et al. 2022

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“…Meanwhile, compared to other models with similar prediction abilities, our signature contains the least number of lncRNAs and is relatively easy to be applied in clinical practice [41][42][43] .…”

Section: Discussionmentioning

confidence: 99%

Construction of a Cuproptosis-Related lncRNA Signature for Predicting Prognosis and Immune Response in Cervical Cancer

Zhang

Chen

Kong

et al. 2023

Preprint

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Background:Cuproptosis is a novel form of cell death, which is triggered by targeted mitochondria that bind the acylated lipid components of the tricarboxylic acid (TCA) cycle. Recent studies have suggested that targeting cuproptosis may be a new treatment strategy for cancer, but its association with cervcal cancer (CC) has not been elucidated. Methods: Data were downloaded from the TCGA-CESC. The cuproptosis-related lncRNAs were identified and prognostic risk models were constructed. Kaplan-Meier survival analysis, ROC curve, PCA and stratified analysis were used to validate the predictive ability of the model. A nomogram for predicting CC prognosis was established. The biological mechanisms associated with cuproptosis were investigated by GO and KEGG enrichment analysis. The CIBERSORT algorithm, immunoassay and TIDE score were used to measure different immune responses. Finally, we screened for sensitive drugs based on cuproptosis correlation. Results: We constructed a cuproptosis-related lncRNAs signature as a risk prognostic prediction model. The risk score was proved and the risk model had higher diagnostic efficiency than other features. The Kaplan-Meier curve indicated that lower risk score was significantly associated with better OS rate in training (P<0.001), testing group (P=0.004), and all groups (P<0.001). The time-dependent ROC curves showed the AUC reached 0.738 at 1 year, 0.698 at 3 years, and 0.699 at 5 years. GO and KEGG enrichment analysis found that the DEGs of low- and high-risk groups may be related to immune regulation. Further study of immune cell infiltration demonstrated that cuproptosis-related lncRNAs signature was significantly associated with the immune response of CC. A total of 23 drugs showed significant differences in the semi-inhibitory concentration (IC50) value, suggesting the signature may participate in the influence on drug efficacy. Conclusions: Our study reveals that assessing cuproptosis patterns in individual tumors will help improve our understanding of the immune mechanisms and prognosis of cervical cancer and thus guide immunotherapy more effectively. Establishing an independent prognostic model based on cuproptosis-associated lncRNAs could serve as a predictor of overall survival and also as a predictor of immunotherapy. The model may help provide personalized medical therapy and new insights into cancer treatment.

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“…Recently, the tumor microenvironment (TME), as an intrinsic oncogenic mechanism and epigenetic modification, has become a research hotspot [ 35 ]. The TME contains a few non-cancerous cells that influence cancer cell survival and has a significant effect on tumor metastasis and drug treatment efficacy [ 36 , 37 ].…”

Section: Discussionmentioning

confidence: 99%

Identification and Validation of the Anoikis-Related Gene Signature as a Novel Prognostic Model for Cervical Squamous Cell Carcinoma, Endocervical Adenocarcinoma, and Revelation Immune Infiltration

et al. 2023

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Background and Objectives: Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) are malignant disorders with adverse prognoses for advanced patients. Anoikis, which is involved in tumor metastasis, facilitates the survival and separation of tumor cells from their initial site. Unfortunately, it is rarely studied, and in the literature, studies have only addressed the prognosis character of anoikis for patients with CESC. Materials and Methods: We utilized anoikis-related genes (ANRGs) to construct a prognostic signature in CESC patients that were selected from the Genecards and Harmonizome portals. Furthermore, we revealed the underlying clinical value of this signature for clinical maneuvers by providing clinical specialists with an innovative nomogram on the basis of ANRGs. Finally, we investigated the immune microenvironment and drug sensitivity in different risk groups. Results: We screened six genes from fifty-eight anoikis-related differentially expressed genes in the TCGA-CESC cohort, and we constructed a prognostic signature. Then, we built a nomogram combined with CESC clinicopathological traits and risk scores, which demonstrated that this model may improve the prognosis of CESC patients in clinical therapy. Next, the prognostic risk scores were confirmed to be an independent prognostic indicator. Additionally, we programmed a series of analyses, which included immune infiltration analysis, therapy-related analysis, and GSVA enrichment analysis, to identify the functions and mechanisms of the prognostic models during the progression of cancer in CESC patients. Finally, we performed quantitative reverse transcription polymerase chain reaction (qRT-PCR) to verify the six ANRGs. Conclusions: The present discovery verified that the predictive 6-anoikis-related gene (6-ANRG) signature and nomogram serve as imperative factors that might notably impact a CESC patient’s prognosis, and they may be able to provide new clinical evidence to assume the role of underlying biological biomarkers and thus become indispensable indicators for prospective diagnoses and advancing therapy.

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Exploration of the Immune-Related Long Noncoding RNA Prognostic Signature and Inflammatory Microenvironment for Cervical Cancer

Cited by 9 publications

References 54 publications

Immune and inflammation: related factor alterations as biomarkers for predicting prognosis and responsiveness to PD-1 monoclonal antibodies in cervical cancer

Immune and inflammation: related factor alterations as biomarkers for predicting prognosis and responsiveness to PD-1 monoclonal antibodies in cervical cancer

Construction of a Cuproptosis-Related lncRNA Signature for Predicting Prognosis and Immune Response in Cervical Cancer

Identification and Validation of the Anoikis-Related Gene Signature as a Novel Prognostic Model for Cervical Squamous Cell Carcinoma, Endocervical Adenocarcinoma, and Revelation Immune Infiltration

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