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

Genome-wide DNA methylation profiling reveals a novel hypermethylated biomarker PRKCB in gastric cancer

Globally, gastric cancer (GC) ranks among the most prevalent forms of malignancy, posing a significant health burden. Epigenetic modifications, predominantly characterized by alterations in DNA methylation patterns, have been linked to a diverse array of neoplastic processes. Here, we undertake a comprehensive analysis of the DNA methylation signature in GC, with the aim to discover the potential diagnostic epigenetic biomarkers. Utilizing the Illumina 935 K BeadChip, we conducted a genome-wide exploration of DNA methylation patterns in four paired samples of GC tissues and adjacent non-cancerous counterparts. The bisulfite-pyrosequencing (n = 7) was employed to the quantification for methylated gene. The pubic databases including GWAS Catalog, TCGA and GEO were used. The immunohistochemistry and qRT-PCR analysis were performed. In contrast to adjacent tissues, GC tissues manifested pronounced hypermethylation patterns specifically within the promoter cytosine-phosphate-guanine (CpG) islands, indicating localized epigenetic alterations. DNA methylome analysis further revealed 4432 differentially-methylated probes (DMPs), with the gene PRKCB exhibited the most prominent average DNA methylation disparity (mean Δβ = 0.353). Pyrosequencing validation confirmed three DMPs within the PRKCB promoter (cg08406370, cg00735962, and cg18526361). Notably, the mean methylation levels of PRKCB were inversely correlated with mRNA expression levels in the GWAS Catalog. Furthermore, both mRNA and protein expression levels of PRKCB were significantly reduced in GCs when compared to their adjacent non-cancerous counterparts, verified by TCGA and GEO database. Our study reveals significant DNA methylation alterations in GC and emphasizes the pivotal role of PRKCB gene hypermethylation in conferring GC risk, which offers fresh perspectives for advancing diagnostic approaches and therapeutic strategies for GC.

Identification of FGG as a Biomarker in Early Gastric Cancer via Tissue Proteomics and Clinical Verification

Early and accurate diagnosis of gastric cancer (GC) is essential for reducing mortality and improving patient well-being. However, methods for the early diagnosis of GC are still lacking. In this study, by isobaric tagging for relative and absolute quantitation (iTRAQ), we identified 336 proteins that overlapped among the upregulated differentially expressed proteins (DEPs) in early gastric cancer (EGC) versus progressive gastric cancer (PGC), upregulated DEPs in EGC versus nongastric cancer (NGC), and nonsignificant proteins in EGC versus NGC. These DEPs were involved primarily in the neutrophil-related immune response. Network analysis of proteins and pathways revealed that fibrinogen α (FGA), β (FGB), and γ (FGG) are candidates for distinguishing EGC. Furthermore, parallel reaction monitoring (PRM), immunohistochemistry (IHC), and Western blot (WB) assays of clinical samples confirmed that, compared with that in PGC and NGC, only FGG was uniquely and significantly upregulated in the gastric mucosa of EGC. Our results demonstrated that FGG in the gastric mucosa could be a novel biomarker to diagnose EGC patients via endoscopy.

The role of CBL family ubiquitin ligases in cancer progression and therapeutic strategies

The CBL (Casitas B-lineage lymphoma) family, as a class of ubiquitin ligases, can regulate signal transduction and activate receptor tyrosine kinases through various tyrosine kinase-dependent pathways. There are three members of the family: c-CBL, CBL-b, and CBL-c. Numerous studies have demonstrated the important role of CBL in various cellular pathways, particularly those involved in the occurrence and progression of cancer, hematopoietic development, and regulation of T cell receptors. Therefore, the purpose of this review is to comprehensively summarize the function and regulatory role of CBL family proteins in different human tumors, as well as the progress of drug research targeting CBL family, so as to provide a broader clinical measurement strategy for the treatment of tumors.

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

Introduction

Lymph 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.

Methods

The 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.

Results

A 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.

Discussion

The 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.

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

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.

Evaluations of Biomarkers CDX1 and CDX2 in Gastric Cancer Prognosis: A Meta-analysis

CDX1 and CDX2 are homeobox-type transcription factors that are potential biomarkers and are associated with prognostic significance in intestinal-type gastric cancer early disease before lymph node metastasis is associated with better prognosis. In addition, the genes IDH 1 and IDH 2 previously known to be involved in brain cancer are implicated in cancer-related molecular signatures as a result new targeted personalized therapies may be possible. Our retrospective study determined the correlation between CDX markers and clinicopathologic data including survival in patients with gastric cancer. This study included studies from 1997 to December 2022 a meta-analysis to provide odds ratios (ORs) and relative risks (RRs). We discussed in detail the impact of IDH 1/2 on the prognosis of gastric cancer outcomes and potential therapeutic strategies. Our meta-analysis included 20 studies identifying 11,163 patients with gastric cancer. We found that CDX 1 overexpression was associated with better overall survival (pooled HR: 1.28) and CDX 2 expression and better 3-year survival (pooled HR: 1.64) and 5-year survival was the pooled HR was correlated 1 94 with both showing statistical correlation. Evidence suggests that IDH 1/2 mutations and CDX 1/2 overexpression are closely associated with metabolic abnormalities epigenetic changes and mutations evidence suggests the potential for novel targeted therapies in gastric cancer. CDX 1/2 overexpression is associated with a favorable prognosis in gastric cancer cases. Further studies are needed to explore the clinical significance of IDH 1/2 mutations and CDX 1/2 expression.

RASSF1A promotes ATM signaling and RASSF1A methylation is a synthetic lethal marker for ATR inhibitors

Aim: The mechanism of RASSF1A in DNA damage repair remains to be further clarified for applying to synthetic lethal strategy. Materials & methods: Eight esophageal cancer cell lines, 181 cases of esophageal dysplasia and 1066 cases of primary esophageal squamous cell carcinoma (ESCC) were employed. Methylation-specific PCR, the CRISPR/Cas9 technique, immunoprecipitation assay and a xenograft mouse model were used. Results: RASSF1A was methylated in 2.21% of esophageal dysplasia and 11.73% of ESCC. RASSF1A was also involved in DNA damage repair through activating Hippo signaling. Loss of RASSF1A expression sensitized esophageal cancer cell lines to ataxia telangiectasia mutated and rad3-related (ATR) inhibitor (VE-822) both in vitro and in vivo. Conclusion: RASSF1A methylation is a synthetic lethal marker for ATR inhibitors.