Role of PVT1 Polymorphisms in the Glioma Susceptibility and Prognosis

Ding, Xiaoying; Zhao, Yaqin; Yuan, Haozheng; Zhang, Yong; Gao, Ya

doi:10.21203/rs.3.rs-18957/v1

Cited by 3 publications

(4 citation statements)

References 24 publications

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“…The T allele of rs13255292 has also been shown to reduce the risk of ovarian cancer in women taking oral contraceptive pill [32] . Further, the recessive model (TT) of rs13255292 has been shown to decrease the risk of glioma in the male [33] . A previous study investigated the association between the genetic polymorphisms of PVT1 and the risk of lung cancer [34] .…”

Section: Discussionmentioning

confidence: 99%

“…[32] Further, the recessive model (TT) of rs13255292 has been shown to decrease the risk of glioma in the male. [33] A previous study investigated the association between the genetic polymorphisms of PVT1 and the risk of lung cancer. [34] However, no statistically significant relationship was found between rs2608053 polymorphisms in PVT1 and the risk of lung cancer in the overall population.…”

Section: Discussionmentioning

confidence: 99%

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The association between polymorphism of the long noncoding RNA, Plasmacytoma variant translocation 1, and the risk of gastric cancer

et al. 2021

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Genetic polymorphisms of plasmacytoma variant translocation 1 can affect various tumors including gastro-intestinal, sexual hormone sensitive cancers and lymphoma. Accumulated evidence have shown that plasmacytoma variant translocation 1 acts as an oncogene and tumor suppressor in various cancers. In fact, the rs13255292 and rs2608053 single nucleotide polymorphisms of plasmacytoma variant translocation 1are known to affect lymphoma; however, their effects on gastric cancer are primarily unknown. In this study, we evaluated the association between these plasmacytoma variant translocation 1 polymorphisms and the risk of gastric cancer. In the present study, 462 patients diagnosed with gastric cancer and 377 cancer-free controls were enrolled. The TaqMan genotyping assay was used to analyze the association between rs13255292 and rs2608053 single nucleotide polymorphisms and the risk of gastric cancer. The rs2608053 dominant model (CT + TT) was associated with a decreased risk of gastric cancer in T3 + T4 (odds ratio [OR] = 0.61, confidence interval (CI) = 0.41 – 0.92, P = .019), and stage III Gastric cancer subgroups (OR = 0.59, 95% CI = 0.38 – 0.91, P = .017) compared to the CC genotype. When stratified analysis by sex was carried out, the rs13255292 dominant model (CT + TT) had a significant association with an increased risk of gastric cancer in the female negative lymph node metastasis gastric cancer subgroup, compared to the CC genotype (OR = 1.96, 95% CI = 1.16 – 3.30, P = .012). The recessive model (TT) of rs13255292 was associated with an increased risk of gastric cancer in the male T3 + T4 gastric cancer subgroups compared to the CC + CT genotype (OR = 3.82, 95% CI = 1.02 – 14.33, P = .047). The dominant model (CT + TT) of rs2608053 was related to a decreased risk of gastric cancer in male T3 + T4 (OR = 0.57, 95% CI = 0.33 – 0.98, P = .042) and stage III gastric cancer subgroups (OR = 0.49, 95% CI = 0.27 – 0.89, P = .020) compared to the CC genotype. The rs13255292 and rs2608053 single nucleotide polymorphisms in plasmacytoma variant translocation 1 may contribute to susceptibility of gastric cancer. Further studies with more subjects and different ethnic groups are needed to validate our results.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

The association between polymorphism of the long noncoding RNA, Plasmacytoma variant translocation 1, and the risk of gastric cancer

et al. 2021

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“…Ding et al. reported that while rs13255292 and rs4410871 increased susceptibility to glioma in the Chinese Han population, they do not have a prognostic value ( 129 ).…”

Section: Lncrnas In Gliomamentioning

confidence: 99%

Long Non-Coding RNAs in Diagnosis, Treatment, Prognosis, and Progression of Glioma: A State-of-the-Art Review

Momtazmanesh

Rezaei

2021

Front. Oncol.

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Glioma is the most common malignant central nervous system tumor with significant mortality and morbidity. Despite considerable advances, the exact molecular pathways involved in tumor progression are not fully elucidated, and patients commonly face a poor prognosis. Long non-coding RNAs (lncRNAs) have recently drawn extra attention for their potential roles in different types of cancer as well as non-malignant diseases. More than 200 lncRNAs have been reported to be associated with glioma. We aimed to assess the roles of the most investigated lncRNAs in different stages of tumor progression and the mediating molecular pathways in addition to their clinical applications. lncRNAs are involved in different stages of tumor formation, invasion, and progression, including regulating the cell cycle, apoptosis, autophagy, epithelial-to-mesenchymal transition, tumor stemness, angiogenesis, the integrity of the blood-tumor-brain barrier, tumor metabolism, and immunological responses. The well-known oncogenic lncRNAs, which are upregulated in glioma, are H19, HOTAIR, PVT1, UCA1, XIST, CRNDE, FOXD2-AS1, ANRIL, HOXA11-AS, TP73-AS1, and DANCR. On the other hand, MEG3, GAS5, CCASC2, and TUSC7 are tumor suppressor lncRNAs, which are downregulated. While most studies reported oncogenic effects for MALAT1, TUG1, and NEAT1, there are some controversies regarding these lncRNAs. Expression levels of lncRNAs can be associated with tumor grade, survival, treatment response (chemotherapy drugs or radiotherapy), and overall prognosis. Moreover, circulatory levels of lncRNAs, such as MALAT1, H19, HOTAIR, NEAT1, TUG1, GAS5, LINK-A, and TUSC7, can provide non-invasive diagnostic and prognostic tools. Modulation of expression of lncRNAs using antisense oligonucleotides can lead to novel therapeutics. Notably, a profound understanding of the underlying molecular pathways involved in the function of lncRNAs is required to develop novel therapeutic targets. More investigations with large sample sizes and increased focus on in-vivo models are required to expand our understanding of the potential roles and application of lncRNAs in glioma.

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“…While the pathogenesis remains unclear, high-dose ionizing radiation exposure is believed to be a major risk factor. Previous studies have mostly used multivariate logistic regression models or Cox proportional hazard models to analyze factors related to end-point events (7,8). These models have high requirements on the sample size and related parameters of the study, which greatly limits the development of clinical research.…”

Section: Introductionmentioning

confidence: 99%

XGBoost algorithm and logistic regression to predict the postoperative 5-year outcome in patients with glioma

Yan¹,

Wang²,

Dong³

et al. 2022

Ann Transl Med

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Background: Glioma is the most common primary intracranial tumor with poor prognosis. The prediction of glioma prognosis has not been well investigated. XGBoost algorithm has been widely used in and data analysis. The predictive value of XGBoost algorithm in glioma remains unclear. This current study used the XGBoost algorithm to construct a predictive model for postoperative outcomes of glioma patients.Methods: Patients with glioma who underwent surgery from January 2006 to April 2017 were retrospectively included in this study. Clinical and follow-up data were collected. The XGBoost model and multivariate logistic regression analysis model were used to screen the factors related to postoperative outcomes, and the results of the two models were compared. The area under the receiver operating characteristic (ROC) curve (AUC), sensitivity, specificity, and Youden index were calculated to evaluate the predictive value of the XGBoost model.Results: A total of 638 patients were included. In total, 336 (52.7%) cases died within 5 years after the operation. Multivariate logistic regression analysis showed that age, gender, World Health Organization (WHO) grade, extent of tumor resection, Karnofsy performance score (KPS), tumor diameter, and whether postoperative radiotherapy and chemotherapy were administered, were the most important risk factors for death within 5 years after surgery in glioma patients. The XGBoost model showed that the top 5 factors related to death of glioma patients within 5 years after surgery were WHO grade (30 points), extent of tumor resection (19 points), postoperative radiotherapy and chemotherapy (16 points), KPS (14 points), and age (11 points). The AUC of the XGBoost model for predicting the death of glioma patients within 5 years after surgery was 0.803 [95% confidence interval (CI): 0.718-0.832], and the sensitivity and specificity were 0.894 and 0.581, respectively. The Youden index was 0.475. The AUC of the multivariate logistic regression model was 0.738 (95% CI: 0.704-0.781), the sensitivity and specificity were 0.785 and 0.632, respectively, and the Youden index was 0.417. Conclusions:Compared with multivariate logistic regression model, XGBoost model has better performance in predicting the risk of death within 5 years after surgery in patients with glioma.

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Role of PVT1 Polymorphisms in the Glioma Susceptibility and Prognosis

Cited by 3 publications

References 24 publications

The association between polymorphism of the long noncoding RNA, Plasmacytoma variant translocation 1, and the risk of gastric cancer

The association between polymorphism of the long noncoding RNA, Plasmacytoma variant translocation 1, and the risk of gastric cancer

Long Non-Coding RNAs in Diagnosis, Treatment, Prognosis, and Progression of Glioma: A State-of-the-Art Review

XGBoost algorithm and logistic regression to predict the postoperative 5-year outcome in patients with glioma

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