Development of a Prognostic Model for Ovarian Cancer Patients Based on Novel Immune Microenvironment Related Genes

Wang, Wei; Wu, Qianqian; Wang, Ziheng; Ren, Shengxiang; Shen, Hanyu; Shi, Wenyu; Xu, Yunzhao

doi:10.3389/fonc.2021.647273

Cited by 10 publications

(9 citation statements)

References 59 publications

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“…OS differences in the different clusters were explored using Kaplan-Meier (KM) analysis. Finally, the "pheatmap" and "ggpubr" R plugins were used to examine changes in the expression levels of M6A-related lncRNAs and clinical characteristics between the clusters [16,17].…”

Section: 2mentioning

confidence: 99%

Identification of Nine M6A-Related Long Noncoding RNAs as Prognostic Signatures Associated with Oxidative Stress in Oral Cancer Based on Data from The Cancer Genome Atlas

Song

et al. 2022

Oxidative Medicine and Cellular Longevity

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Objective. Although the expression of long noncoding RNAs (lncRNAs) and N6-methyladenosine (M6A) is correlated with different tumors, it remains unclear how M6A-related lncRNA functioning affects the initiation and progression of oral squamous cell carcinoma (OSCC). Materials and Methods. Gene expression and clinical data were retrieved from The Cancer Genome Atlas. The prognostic value of M6A-related lncRNAs was determined using univariate Cox regression analyses. Gene set enrichment analysis of OSCC patient clusters revealed the pathways that elucidate the mechanism. Furthermore, a risk-based model was established. The difference in the overall survival (OS) between groups, including low-/high-risk groups, was determined by Kaplan-Meier analysis. Relationships among immune cells, clusters, clinicopathological characteristics, and risk scores were explored. Results. Among 1,080 M6A-related lncRNAs, 36 were prognosis-related. Patients with OSCC were divided into two clusters. T stage and the pathological grade were noticeably lower in cluster 2 than in cluster 1. Epithelial-mesenchymal transition showed greater enrichment in cluster 1. Nine hub M6A-related lncRNAs were identified for the model of risk score for predicting OSCC prognosis. The OS was longer in patients with a low-risk score than in patients with a high-risk score. The risk score was an independent prognostic factor of OSCC and was associated with the infiltration of different immune cells. T stages and the American Joint Committee on Cancer (AJCC) stages were more advanced in the high-risk score group than in the low-risk score group. Finally, expression correlation analysis showed that the risk score is associated with the expression of oxidative stress markers. Conclusion. M6A-related lncRNAs play an important role in OSCC progression. Immune cell infiltration was related to the risk score model in OSCC and could accurately predict OSCC prognosis.

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Section: 2mentioning

confidence: 99%

Identification of Nine M6A-Related Long Noncoding RNAs as Prognostic Signatures Associated with Oxidative Stress in Oral Cancer Based on Data from The Cancer Genome Atlas

Song

et al. 2022

Oxidative Medicine and Cellular Longevity

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“…The CIBERSORT algorithm was used to examine the association between the expression of HAUS1 and the infiltration of 22 types of TILs in glioma. CIBERSORT is an online tool that uses a deconvolution algorithm to sensitively and specifically calculate the proportion of TILs [ 31 , 32 ]. We divided CGGA samples into the low- and high-expression groups according to the median expression level of HAUS1.…”

Section: Methodsmentioning

confidence: 99%

HAUS Augmin-Like Complex Subunit 1 Influences Tumour Microenvironment and Prognostic Outcomes in Glioma

Yao

et al. 2022

Journal of Oncology

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Background. The expression of HAUS Augmin-like complex subunit 1 (HAUS1), a protein-coding gene, is low in normal samples among various cancers with pan-cancer analysis. The depletion of HAUS1 in cells decreases the G2/M cell compartment and induces apoptosis. However, the detailed expression pattern of HAUS1 and its correlation with immune infiltration in glioma (LGG and GBM) (LGG: low-grade glioma; GBM: glioblastoma) remain unknown. Therefore, in this study, we examined the role and prognostic value of HAUS1 in glioma. Methods. Transcriptional expression data of HAUS1 were collected from the CGGA and TCGA databases. The Kaplan–Meier analysis, univariate and multivariate Cox analyses, and receiver operating characteristic (ROC) curves were used to analyse the clinical significance of HAUS1 in glioma. The STRING database was used to analyse protein-protein interactions (PPI), and the “ClusterProfiler” package was used for functional enrichment analysis to examine the possible biological roles of HAUS1. In addition, the HAUS1 promoter methylation modification was analysed using MEXPRESS, and the association between HAUS1 expression and tumour-infiltrating immune cells was investigated using CIBERSORT. Results. Based on the data retrieved from TCGA (703 samples) and CGGA (1018 samples), an elevated expression of HAUS1 was observed in glioma samples, which was associated with poorer survival of patients, unfavourable clinical characteristics, 1p/19q codeletion status, WHO grade, and IDH mutation status. Furthermore, multivariate and univariate Cox analyses revealed that HAUS1 was an independent predictor of glioma. HAUS1 expression level was associated with several tumour-infiltrating immune cells, such as Th2 cells, macrophages, and activated dendritic cells. The outcomes of ROC curve analysis showed that HAUS1 was good to prognosticate immune infiltrating levels in glioma with a higher area under the curve (AUC) value (AUC = 0.974). Conclusions. HAUS1 was upregulated and served as a biomarker for poor prognosis in patients with glioma. High HAUS1 expression was associated with several tumour-infiltrating immune cells such as Th2 cells, macrophages, and activated dendritic cells, which had high infiltration levels. Therefore, these findings suggest that HAUS1 is a potential biomarker for predicting the prognosis of patients with glioma and plays a pivotal role in immune infiltration in glioma.

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“…Although theoretically, the prognosis of patients at the same stage should be similar, in clinical practice, vast differences are often observed. erefore, it is necessary to identify new biological indicators to improve the accuracy of prognostic prediction [6,7].…”

Section: Introductionmentioning

confidence: 99%

Application of Prognostic Models Based on Psoas Muscle Index, Stage, Pathological Grade, and Preoperative Carcinoembryonic Antigen Level in Stage II-III Colorectal Cancer Patients Undergoing Adjuvant Chemotherapy

Tian

et al. 2022

Journal of Oncology

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Objective. To investigate the effect of sarcopenia on the prognosis of stage II-III colorectal cancer patients undergoing adjuvant chemotherapy. Methods. A total of 196 stage II-III colorectal cancer patients who received 8 cycles of postoperative chemotherapy were retrospectively analyzed. An abdominal CT acquired at 3-4 weeks after surgery was used to calculate the psoas muscle index. Subsequently, once gender-specific receiver operating characteristic curves were plotted and cut-off values of psoas muscle index were defined, the clinicopathological characteristics and the prognosis of patients with high and low values were compared. Lastly, prognostic models were established based on the independent prognostic factors of relapse-free survival and overall survival identified by COX analysis. Results. Based on the psoas muscle index, the prevalence of sarcopenia was 37.5% among 196 patients. This prevalence has significant correlation with patients’ age and gender. However, it was not related to the AJCC stage, T stage, lymph node metastasis, pathological grade, grade III-IV myelosuppression, or preoperative carcinoembryonic antigen level. In addition, both the relapse-free and the overall survival of patients with low and high psoas muscle indexes were significantly different. COX analysis indicated that the psoas muscle index was an independent prognostic factor. Both the overall survival prognostic model based on patients’ psoas muscle index, stage, pathological grade, and preoperative carcinoembryonic antigen level and the relapse-free survival prognostic model based on patients’ psoas muscle index, pathological grade, and preoperative carcinoembryonic antigen level could accurately predict the prognosis of patients. Conclusion. For stage II-III colorectal cancer patients, the presence of sarcopenia before adjuvant chemotherapy would adversely affect their recurrence-free and overall survival. Prognostic models based on psoas muscle index, stage, pathological grade, and preoperative carcinoembryonic antigen level could accurately predict the prognosis in these patients.

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Development of a Prognostic Model for Ovarian Cancer Patients Based on Novel Immune Microenvironment Related Genes

Cited by 10 publications

References 59 publications

Identification of Nine M6A-Related Long Noncoding RNAs as Prognostic Signatures Associated with Oxidative Stress in Oral Cancer Based on Data from The Cancer Genome Atlas

Identification of Nine M6A-Related Long Noncoding RNAs as Prognostic Signatures Associated with Oxidative Stress in Oral Cancer Based on Data from The Cancer Genome Atlas

HAUS Augmin-Like Complex Subunit 1 Influences Tumour Microenvironment and Prognostic Outcomes in Glioma

Application of Prognostic Models Based on Psoas Muscle Index, Stage, Pathological Grade, and Preoperative Carcinoembryonic Antigen Level in Stage II-III Colorectal Cancer Patients Undergoing Adjuvant Chemotherapy

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