SUMO1-modified DNA methyltransferase 1 induces DNA hypermethylation of VWC2 in the development of colorectal cancer

Cheng, Xiaohu; Xu, Tong; Zhou, Lianbang; Li, Fang-Yuan; Wang, Song; Liang, Huan-Ru; Tang, Jing-Jing; Duan, Chang-Qin; Jiang, Heng; Zhang, Yingfeng; Liu, Zhining

doi:10.4149/neo_2022_220817n841

Cited by 7 publications

(5 citation statements)

References 19 publications

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“…Low expression of GLYATL1 can serve as a predictor of poor prognosis in patients with clear cell renal carcinoma and hepatocellular carcinoma 47 , 48 . Moreover, overexpression of VWC2 has been shown to inhibit the proliferation of HCT-116 and HT29 cells 49 . Although the roles of genes such as UCN, SYT4, CBLN1, CBLN2, and GLYATL1 in CRC remain unclear, our findings suggest that they can still serve as potential biomarkers for CRC prognosis.…”

Section: Discussionmentioning

confidence: 99%

Identification of glutamine metabolism-related gene signature to predict colorectal cancer prognosis

Xie,

Li,

Tao

et al. 2024

J. Cancer

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Backgrounds: Colorectal cancer (CRC) is a highly malignant gastrointestinal malignancy with a poor prognosis, which imposes a significant burden on patients and healthcare providers globally. Previous studies have established that genes related to glutamine metabolism play a crucial role in the development of CRC. However, no studies have yet explored the prognostic significance of these genes in CRC. Methods: CRC patient data were downloaded from The Cancer Genome Atlas (TCGA), while glutamine metabolism-related genes were obtained from the Molecular Signatures Database (MSigDB) database. Univariate COX regression analysis and LASSO Cox regression were utilized to identify 15 glutamine metabolism-related genes associated with CRC prognosis. The risk scores were calculated and stratified into high-risk and low-risk groups based on the median risk score. The model's efficacy was assessed using Kaplan-Meier survival analysis and receiver operating characteristic (ROC) curve analysis. Cox regression analysis was employed to determine the risk score as an independent prognostic factor for CRC. Differential immune cell infiltration between the high-risk and low-risk groups was assessed using the ssGSEA method. The clinical applicability of the model was validated by constructing nomograms based on age, gender, clinical staging, and risk scores. Immunohistochemistry (IHC) was used to detect the expression levels of core genes. Results: We identified 15 genes related to glutamine metabolism in CRC: NLGN1, RIMKLB, UCN, CALB1, SYT4, WNT3A, NRCAM, LRFN4, PHGDH, GRM1, CBLN1, NRG1, GLYATL1, CBLN2, and VWC2. Compared to the high-risk group, the low-risk group demonstrated longer overall survival (OS) for CRC. Clinical correlation analysis revealed a positive correlation between the risk score and the clinical stage and TNM stage of CRC. Immune correlation analysis indicated a predominance of Th2 cells in the low-risk group. The nomogram exhibited excellent discriminatory ability for OS in CRC. Immunohistochemistry revealed that the core gene CBLN1 was expressed at a lower level in CRC, while GLYATL1 was expressed at a higher level. Conclusions: In summary, we have successfully identified and comprehensively analyzed a gene signature associated with glutamine metabolism in CRC for the first time. This gene signature consistently and reliably predicts the prognosis of CRC patients, indicating its potential as a metabolic target for individuals with CRC.

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Section: Discussionmentioning

confidence: 99%

Identification of glutamine metabolism-related gene signature to predict colorectal cancer prognosis

Xie,

Li,

Tao

et al. 2024

J. Cancer

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“…For example, NEDD9, an important ubiquitination-related gene, is associated with poor prognosis and therapy resistance in breast cancer [12]. Furthermore, studies indicate that the expression levels of sumoylation-related genes, such as SUMO1, is related to prognosis and treatment response in several cancer types, including lung [13], and colorectal cancer [14]. Additionally, ubiquitination or sumoylation genes may have potential value in predicting prognosis and treatment response in cancer molecular subtyping [8,9].…”

Section: Discussionmentioning

confidence: 99%

Identification of a Novel Prognostic Signature for Breast Cancer Derived from Post-translational Ubiquitin and Ubiquitin-Like Modification-Related Genes

Zhou,

Kong,

Lin

et al. 2024

Preprint

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Background: Ubiquitin and ubiquitin-like (UUL) modifications play pleiotropic functions and are subject to fine regulatory mechanisms frequently altered in cancer. However, the comprehensive impact of UUL modification on breast cancer remains unclear. Methods: Transcriptomic and clinical data of breast cancer were downloaded from TCGA and GEO databases. Molecular subtyping of breast cancer was conducted using the NMF and CIBERSORT algorithms. Prognostic genes were identified via univariate, lasso and multivariate Cox regression analyses. Clinical pathological features, immune cell infiltration, immune therapeutic response and chemotherapy drug sensitivity were compared between groups using the Wilcoxon test. Survival analysis was performed using the Kaplan-Meier method and log-rank test. Results: In breast cancer, 63 UUL modification-related genes were differentially expressed, with 29 up-regulated and 34 down-regulated genes. These genes were used to generate two UUL modification patterns that exhibited significant differences in prognostic features and immune cell infiltration. The UUL modification patterns were associated with 2038 differentially expressed genes that were significantly enriched in nuclear division, chromosome segregation, neuroactive ligand-receptor interaction, cell cycle, and other biological processes. Of these genes, 425 were associated with breast cancer prognosis, which enabled the classification of breast cancer into two clusters with significantly distinct prognoses. We developed a prognostic model, UULscore, which comprised nine genes and showed a significant correlation with partial immune cell infiltration. Furthermore, UULscore demonstrated potential predictive value in breast cancer overall survival prediction, immune therapeutic response, and chemotherapy drug sensitivity. UULscore, stage, radiotherapy, and chemotherapy were identified as independent prognostic factors for breast cancer. Based on these factors, a nomogram model was constructed, which demonstrated exceptional prognostic predictive performance. Conclusion: In conclusion, we identified two UUL modification-derived molecular subtypes in breast cancer, and have successfully constructed a risk scoring model that holds potential value in prognosis, immune infiltration, immune therapeutic response, and chemotherapy sensitivity.

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“…Its expression is diminished in colorectal cancer and exhibits a negative correlation with tumor stage. VWC2 inhibits tumor cell growth both in vitro and in vivo [ 59 ]. Colonic adenocarcinoma displays the highest degree of DNA methylation in VWC2.…”

Section: Discussionmentioning

confidence: 99%

Systematic proteome-wide Mendelian randomization using the human plasma proteome to identify therapeutic targets for lung adenocarcinoma

Zhang,

Xiong,

Zhang

et al. 2024

J Transl Med

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Background Lung adenocarcinoma (LUAD) is the predominant histological subtype of lung cancer and the leading cause of cancer-related mortality. Identifying effective drug targets is crucial for advancing LUAD treatment strategies. Methods This study employed proteome-wide Mendelian randomization (MR) and colocalization analyses. We collected data on 1394 plasma proteins from a protein quantitative trait loci (pQTL) study involving 4907 individuals. Genetic associations with LUAD were derived from the Transdisciplinary Research in Cancer of the Lung (TRICL) study, including 11,245 cases and 54,619 controls. We integrated pQTL and LUAD genome-wide association studies (GWASs) data to identify candidate proteins. MR utilizes single nucleotide polymorphisms (SNPs) as genetic instruments to estimate the causal effect of exposure on outcome, while Bayesian colocalization analysis determines the probability of shared causal genetic variants between traits. Our study applied these methods to assess causality between plasma proteins and LUAD. Furthermore, we employed a two-step MR to quantify the proportion of risk factors mediated by proteins on LUAD. Finally, protein–protein interaction (PPI) analysis elucidated potential links between proteins and current LUAD medications. Results We identified nine plasma proteins significantly associated with LUAD. Increased levels of ALAD, FLT1, ICAM5, and VWC2 exhibited protective effects, with odds ratios of 0.79 (95% CI 0.72–0.87), 0.39 (95% CI 0.28–0.55), 0.91 (95% CI 0.72–0.87), and 0.85 (95% CI 0.79–0.92), respectively. Conversely, MDGA2 (OR, 1.13; 95% CI 1.08–1.19), NTM (OR, 1.12; 95% CI 1.09–1.16), PMM2 (OR, 1.35; 95% CI 1.18–1.53), RNASET2 (OR, 1.15; 95% CI 1.08–1.21), and TFPI (OR, 4.58; 95% CI 3.02–6.94) increased LUAD risk. Notably, none of the nine proteins showed evidence of reverse causality. Bayesian colocalization indicated that RNASET2, TFPI, and VWC2 shared the same variant with LUAD. Furthermore, NTM and FLT1 demonstrated interactions with targets of current LUAD medications. Additionally, FLT1 and TFPI are currently under evaluation as therapeutic targets, while NTM, RNASET2, and VWC2 are potentially druggable. These findings shed light on LUAD pathogenesis, highlighting the tumor-promoting effects of RNASET2, TFPI, and NTM, along with the protective effects of VWC2 and FLT1, providing a significant biological foundation for future LUAD therapeutic targets. Conclusions Our proteome-wide MR analysis highlighted RNASET2, TFPI, VWC2, NTM, and FLT1 as potential drug targets for further clinical investigation in LUAD. However, the specific mechanisms by which these proteins influence LUAD remain elusive. Targeting these proteins in drug development holds the potential for successful clinical trials, providing a pathway to prioritize and reduce costs in LUAD therapeutics.

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SUMO1-modified DNA methyltransferase 1 induces DNA hypermethylation of VWC2 in the development of colorectal cancer

Cited by 7 publications

References 19 publications

Identification of glutamine metabolism-related gene signature to predict colorectal cancer prognosis

Identification of glutamine metabolism-related gene signature to predict colorectal cancer prognosis

Identification of a Novel Prognostic Signature for Breast Cancer Derived from Post-translational Ubiquitin and Ubiquitin-Like Modification-Related Genes

Systematic proteome-wide Mendelian randomization using the human plasma proteome to identify therapeutic targets for lung adenocarcinoma

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