DNA methylation drives a new path in gastric cancer early detection: Current impact and prospects

Wang, Xinhui; Zhao, Yinghui; Zhang, Hong; Dong, Yaqi; Miao, Tianshu; Mohseni, Ghazal; Li, Du; Du, Lutao

doi:10.1016/j.gendis.2023.02.038

Cited by 11 publications

(5 citation statements)

References 137 publications

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“…DNA methylation refers to the transfer of active methyl groups to specific bases in a DNA chain. S-adenosylmethionine serves as the methyl donor, and the process is catalyzed by DNA methyltransferase [ 37 ]. Aberrant DNA methylation is closely related to the occurrence and development of tumors.…”

Section: Discussionmentioning

confidence: 99%

“…The main function of the m 6 A modification is to affect the translation and stability of the RNA. The methylation happens at the N1 site of adenosine in m 1 A, while it happens on the fifth C atom of cytosine in m 5 C [37][38][39]. RNA methylation plays an important role in regulating biological processes like tumor cell proliferation and apoptosis.…”

Section: Discussionmentioning

confidence: 99%

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Correlation between S100A7 and immune characteristics, methylation, tumor stemness and tumor heterogeneity in pan-cancer and its role in chemotherapy resistance in breast cancer

Li,

Yang,

Jin

et al. 2024

Aging

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Objective: To explore the relationships between S100A7 and the immune characteristics, tumor heterogeneity, and tumor stemness pan-cancer as well as the effect of S100A7 on chemotherapy sensitivity in breast cancer. Methods: TCGA-BRCA and TCGA-PANCANCER RNA-seq data and clinical follow-up survival data were collected from the University of California Santa Cruz database. Survival analyses were performed to explore the relationship between S100A7 expression and pan-cancer prognosis. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, and Gene Set Enrichment Analysis (GSEA) were used to identify the potential pathways related to the differentially expressed genes in breast cancer. Spearman’s and Wilcoxon’s tests were used to investigate the relationships between S100A7 expression and immune characteristics, methylation, tumor heterogeneity, and tumor stemness. The potential functions of S100A7 and its influence on chemotherapy sensitivity in breast cancer were elucidated using reverse transcription-quantitative PCR, Cell Counting Kit-8 (CCK-8) assay, Transwell assay, and wound healing assay. Results: S100A7 was highly expressed in most types of tumors and was associated with poor prognosis. S100A7 was closely associated with immunomodulators, immune checkpoint and immune cell infiltration. Further, S100A7 was related to tumor mutational burden, tumor heterogeneity, methylation and tumor stemness in breast cancer. High S100A7 expression was associated with the invasiveness, migration, proliferation and chemotherapy resistance of breast cancer cells in vitro experiments. Conclusion: High S100A7 expression was related with poor prognosis and chemotherapy resistance in breast cancer, making it a potential immune and chemotherapy resistance biomarker.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Correlation between S100A7 and immune characteristics, methylation, tumor stemness and tumor heterogeneity in pan-cancer and its role in chemotherapy resistance in breast cancer

Li,

Yang,

Jin

et al. 2024

Aging

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“…Although early screening for gastric cancer via gastroscopy may improve overall survival 12 , the availability of reliable, simple, and non-invasive screening tests is more limited than for CRC. Several studies have recently been conducted to identify DNA methylation-based biomarkers in the plasma, serum, gastric juice, and fecal samples for gastric cancer diagnosis, albeit with varying specificity and sensitivity 13 . Early detection and in vitro diagnostics for gastric cancer have yet to reach clinics en masse .…”

Section: Clinical Applications Of Dna Methylation Biomarkers For Dete...mentioning

confidence: 99%

“…Several potential blood-based diagnostic methylation biomarkers have been identified for gastric cancer detection, including C13orf18, DLEC1, FLNC, HODX10, MGMT, PCDH10, RNF180, RPRM, RPRML, RUNX3, SEPT9, SFRP2, SOX17, THBS1, UCHL1 , and ZNF569 13 , 14 ( Table 2 ). RNF180 is one of the ring finger protein genes involved in the degradation of its substrates as an E3 ubiquitin ligase.…”

Section: Clinical Applications Of Dna Methylation Biomarkers For Dete...mentioning

confidence: 99%

DNA methylation biomarkers for early detection of gastric and colorectal cancers

Gao,

Liu,

et al. 2024

Cancer Biol Med

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“…Projected estimates suggest that by 2040, the number of new cases may increase to 1.77 million, with the number of deaths potentially reaching 1.27 million ( 2 ). In recent decades, with the advancement of screening and therapeutic strategies, the incidence and mortality of GC have decreased substantially in most parts of the world, especially in some Western countries ( 2 , 3 ). However, with the aging of the population, the disease burden on middle-aged and elderly people has increased ( 4 ).…”

Section: Introductionmentioning

confidence: 99%

Comparison of the predictive performance of three lymph node staging systems for late-onset gastric cancer patients after surgery

Chen,

Ding,

Zhao

2024

Front. Surg.

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IntroductionLymph node (LN) status is a vital prognostic factor for patients. However, there has been limited focus on predicting the prognosis of patients with late-onset gastric cancer (LOGC). This study aimed to investigate the predictive potential of the log odds of positive lymph nodes (LODDS), lymph node ratio (LNR), and pN stage in assessing the prognosis of patients diagnosed with LOGC.MethodsThe LOGC data were obtained from the Surveillance, Epidemiology, and End Results database. This study evaluated and compared the predictive performance of three LN staging systems. Univariate and multivariate Cox regression analyses were carried out to identify prognostic factors for overall survival (OS). Three machine learning methods, namely, LASSO, XGBoost, and RF analyses, were subsequently used to identify the optimal LN staging system. A nomogram was built to predict the prognosis of patients with LOGC. The efficacy of the model was demonstrated through receiver operating characteristic (ROC) curve analysis and decision curve analysis.ResultsA total of 4,743 patients with >16 removed lymph nodes were ultimately included in this investigation. Three LN staging systems demonstrated significant performance in predicting survival outcomes (P < 0.001). The LNR exhibited the most important prognostic ability, as evidenced by the use of three machine learning methods. Utilizing independent factors derived from multivariate Cox regression analysis, a nomogram for OS was constructed.DiscussionThe calibration, C-index, and AUC revealed their excellent predictive performance. The LNR demonstrated a more powerful performance than other LN staging methods in LOGC patients after surgery. Our novel nomogram exhibited superior clinical feasibility and may assist in patient clinical decision-making.

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DNA methylation drives a new path in gastric cancer early detection: Current impact and prospects

Cited by 11 publications

References 137 publications

Correlation between S100A7 and immune characteristics, methylation, tumor stemness and tumor heterogeneity in pan-cancer and its role in chemotherapy resistance in breast cancer

Correlation between S100A7 and immune characteristics, methylation, tumor stemness and tumor heterogeneity in pan-cancer and its role in chemotherapy resistance in breast cancer

DNA methylation biomarkers for early detection of gastric and colorectal cancers

Comparison of the predictive performance of three lymph node staging systems for late-onset gastric cancer patients after surgery

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