The emerging role of NR2F1-AS1 in the tumorigenesis and progression of human cancer

Luo, Dong; Liu, Yunfei; Yuan, Shuai; Bi, Xianyun; Yang, Yongchao; Zhu, Hongwei; Li, Zhiqiang; Ji, Liandong; Yu, Xiao

doi:10.1016/j.prp.2022.153938

Cited by 5 publications

(3 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In NW subjects, DHA also down-regulates PSMG3-AS1, reported to be highly expressed in gastric cancer patients [ 56 ]. Likewise, AA modulates lncRNAs previously described to have an emerging role in intestinal tumorigenesis, such as NR2F1-AS1 [ 57 ], POLR2J4 [ 58 ], NOP14 [ 59 ] and MAGI2-AS3 [ 60 ]. Similarly, AA regulates the expression of SNHG17 and MIR100HG, known to be deregulated in various human cancers [ 61 , 62 , 63 , 64 ] and in obesity, while DHA specifically up-regulates LIPE-AS1, a regulator of adipogenesis in animal models [ 65 ].…”

Section: Discussionmentioning

confidence: 99%

Gene and lncRNA Profiling of ω3/ω6 Polyunsaturated Fatty Acid-Exposed Human Visceral Adipocytes Uncovers Different Responses in Healthy Lean, Obese and Colorectal Cancer-Affected Individuals

Tait,

Calura,

Baldassarre

et al. 2024

IJMS

View full text Add to dashboard Cite

Colorectal cancer (CRC) is a major life-threatening disease, being the third most common cancer and a leading cause of death worldwide. Enhanced adiposity, particularly visceral fat, is a major risk factor for CRC, and obesity-associated alterations in metabolic, inflammatory and immune profiles in visceral adipose tissue (VAT) strongly contribute to promoting or sustaining intestinal carcinogenesis. The role of diet and nutrition in obesity and CRC has been extensively demonstrated, and AT represents the main place where diet-induced signals are integrated. Among the factors introduced with diet and processed or enriched in AT, ω3/ω6 polyunsaturated fatty acids (PUFAs) are endowed with pro- or anti-inflammatory properties and have been shown to exert either promoting or protective roles in CRC. In this study, we investigated the impact of ex vivo exposure to the ω3 and ω6 PUFAs docosahexaenoic and arachidonic acids on VAT adipocyte whole transcription in healthy lean, obese and CRC-affected individuals. High-throughput sequencing of protein-coding and long non-coding RNAs allowed us to identify specific pathways and regulatory circuits controlled by PUFAs and highlighted an impaired responsiveness of obese and CRC-affected individuals as compared to the strong response observed in healthy lean subjects. This further supports the role of healthy diets and balanced ω3/ω6 PUFA intake in the primary prevention of obesity and cancer.

show abstract

Section: Discussionmentioning

confidence: 99%

Gene and lncRNA Profiling of ω3/ω6 Polyunsaturated Fatty Acid-Exposed Human Visceral Adipocytes Uncovers Different Responses in Healthy Lean, Obese and Colorectal Cancer-Affected Individuals

Tait,

Calura,

Baldassarre

et al. 2024

IJMS

View full text Add to dashboard Cite

show abstract

“…Kuang et al (46) reported that the lncRNA MAP3K14-AS1 has a prognostic marker for BLCA. Luo et al (47) showed that NR2F1-AS1 can modulate cancer cell proliferation, invasion, migration, apoptosis, cell cycle, and glycolysis via various mechanisms, and is aberrantly expressed in numerous malignancies, which suggests that NR2F1-AS1 may be a potential therapeutic target and prognostic marker for cancer. He et al (48) demonstrated that KCNQ1OT1 can recruit DNA methyltransferases to the EIF2B5 promoter to downregulate EIF2B5 expression and thereby promote ovarian cancer metastasis.…”

Section: Discussionmentioning

confidence: 99%

“…Luo et al. ( 47 ) showed that NR2F1-AS1 can modulate cancer cell proliferation, invasion, migration, apoptosis, cell cycle, and glycolysis via various mechanisms, and is aberrantly expressed in numerous malignancies, which suggests that NR2F1-AS1 may be a potential therapeutic target and prognostic marker for cancer. He et al.…”

Section: Discussionmentioning

confidence: 99%

Identification of a novel defined inflammation-related long noncoding RNA signature contributes to predicting prognosis and distinction between the cold and hot tumors in bladder cancer

Xiong

Chen

et al. 2023

Front. Oncol.

View full text Add to dashboard Cite

PurposeBladder cancer (BLCA) is one of the most frequently diagnosed urological malignancies and is the 4th most common cancer in men worldwide. Molecular targets expressed in bladder cancer (BLCA) are usually used for developing targeted drug treatments. However, poor prognosis and poor immunotherapy efficacy remain major challenges for BLCA. Numerous studies have shown that long non-coding RNAs (LncRNAs) play an important role in the development of cancer. However, the role of lncRNAs related to inflammation in BLCA and their prognostic value remain unclear. Therefore, this study is aimed to explore new potential biomarkers that can predict cancer prognosis.MethodsWe downloaded BLCA-related RNA sequencing data from The Cancer Genome Atlas (TCGA) and searched for inflammation-related prognostic long non-coding RNAs (lncRNAs) by univariate Cox (uniCox) regression and co-expression analysis. We used the least absolute shrinkage and selection operator (LASSO) analysis to construct an inflammation-related lncRNA prognosis risk model. Samples were divided into high-risk score (HRS) group and low-risk score (LRS) group based on the median value of risk scores. The independent variable factors were identified by univariate Cox (uni-Cox) and multivariate Cox (multi-Cox) regression analyses, and receiver operating characteristic (ROC) curves were used to compare the role of different factors in predicting outcomes. Nomogram and Calibration Plot were generated by the R package rms to analyze whether the prediction results are correct and show good consistency. Correlation coefficients were calculated by Pearson analysis. The Kaplan-Meier method was used to assess the prognostic value. The expression of 7 lncRNAs related with inflammation was also confirmed by qRT-PCR in BLCA cell lines. Kyoto Encyclopedia of Gene and Genome (KEGG) pathways that were significantly enriched (P < 0.05) in each risk group were identified by the GSEA software. The R package pRRophetic was used to predict the IC50 of common chemotherapeutic agents. TIMER, XCELL, QUANTISEQ, MCPCOUNTER, EPIC and CIBERSORT were applied to quantify the relative proportions of infiltrating immune cells. We also used package ggpubr to evaluate TME scores and immune checkpoint activation in LRS and HRS populations. R package GSEABase was used to analyze the activity of immune cells or immune function. Different clusters of principal component analysis (PCA), t-distribution random neighborhood embedding (t-SNE), and Kaplan-Meier survival were analyzed using R package Rtsne’s. The R package ConsensesClusterPlus was used to class the inflammation-related lncRNAs.ResultsIn this study, a model containing 7 inflammation-related lncRNAs was constructed. The calibration plot of the model was consistent with the prognosis prediction outcomes. The 1-, 3-, and 5-year ROC curve (AUC) were 0.699, 0.689, and 0.699, respectively. High-risk patients were enriched in lncRNAs related with tumor invasion and immunity, and had higher levels of immune cell infiltration and immune checkpoint activation. Hot tumors and cold tumors were effectively distinguished by clusters 2 and 3 and cluster 1, respectively, which indicated that hot tumors are more susceptible to immunotherapy.ConclusionOur study showed that inflammation-related LncRNAs are closely related with BLCA, and inflammation-related lncRNA can accurately predict patient prognosis and effectively differentiate between hot and cold tumors, thus improving individualized immunotherapy for BLCA patients. Therefore, this study provides an effective predictive model and a new therapeutic target for the prognosis and clinical treatment of BLCA, thus facilitating the development of individualized tumor therapy.

show abstract

A Symbolic Regression Approach to Hepatocellular Carcinoma Diagnosis Using Hypermethylated CpG Islands in Circulating Cell-Free DNA

Goyal¹

2023

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Hepatocellular carcinoma is the most common primary liver cancer, accounting for 90% of cases, and a major cause of death worldwide. Despite this, alpha-fetoprotein tests are the only blood-based diagnostic tools available, and their use is limited by their low sensitivity. DNA methylation changes, which have been implicated in a majority of cancers, offer an alternative method of diagnosis through measuring such changes in circulating cell-free DNA present in blood plasma.Method A genetic programming-based symbolic regression approach was applied to gain the benefits of machine learning while avoiding the opacity drawbacks of "black box" models. The data included plasma samples from 36 patients with hepatocellular carcinoma as well as a control group of 55 that contained patients with and without cirrhosis. A 75-25 train-test splitting was done before training. ResultsThe symbolic regression methodology developed an equation utilizing the methylation levels of three biomarkers, with an accuracy of 91.3%, a sensitivity of 100%, and a specificity of 87.5% on the test data. The performance matches prior research while providing the added benefits of transparency. ConclusionCirculating cell-free DNA presents opportunities for minimally invasive early diagnosis of hepatocellular carcinoma, and utilizing transparent machine learning approaches like symbolic regression can allow accurate diagnosis by combining biological and mathematical principles. Future validation of the model obtained here on a larger and more diverse dataset can reveal the potential for such approaches in cancer diagnosis and pave the way for further research.

show abstract

The emerging role of NR2F1-AS1 in the tumorigenesis and progression of human cancer

Cited by 5 publications

References 44 publications

Gene and lncRNA Profiling of ω3/ω6 Polyunsaturated Fatty Acid-Exposed Human Visceral Adipocytes Uncovers Different Responses in Healthy Lean, Obese and Colorectal Cancer-Affected Individuals

Gene and lncRNA Profiling of ω3/ω6 Polyunsaturated Fatty Acid-Exposed Human Visceral Adipocytes Uncovers Different Responses in Healthy Lean, Obese and Colorectal Cancer-Affected Individuals

Identification of a novel defined inflammation-related long noncoding RNA signature contributes to predicting prognosis and distinction between the cold and hot tumors in bladder cancer

A Symbolic Regression Approach to Hepatocellular Carcinoma Diagnosis Using Hypermethylated CpG Islands in Circulating Cell-Free DNA

Contact Info

Product

Resources

About