LncRNA LINC01537 Promotes Gastric Cancer Metastasis and Tumorigenesis by Stabilizing RIPK4 to Activate NF-κB Signaling

GSK3β and UCHL3 govern RIPK4 homeostasis via deubiquitination to enhance tumor metastasis in ovarian cancer

Receptor-interacting protein kinase 4 (RIPK4) is increasingly recognized as a pivotal player in ovarian cancer, promoting tumorigenesis and disease progression. Despite its significance, the posttranslational modifications dictating RIPK4 stability in ovarian cancer remain largely uncharted. In this study, we first established that RIPK4 levels are markedly higher in metastatic than in primary ovarian cancer tissues through single-cell sequencing. Subsequently, we identified UCHL3 as a key deubiquitinase that regulates RIPK4. We elucidate the mechanism that UCHL3 interacts with and deubiquitinates RIPK4 at the K469 site, removing the K48-linked ubiquitin chain and thus enhancing RIPK4 stabilization. Intriguingly, inhibition of UCHL3 activity using TCID leads to increased RIPK4 ubiquitination and degradation. Furthermore, we discovered that GSK3β-mediated phosphorylation of RIPK4 at Ser420 enhances its interaction with UCHL3, facilitating further deubiquitination and stabilization. Functionally, RIPK4 was found to drive the proliferation and metastasis of ovarian cancer in a UCHL3-dependent manner both in vitro and in vivo. Importantly, positive correlations between RIPK4 and UCHL3 protein expression levels were observed, with both serving as indicators of poor prognosis in ovarian cancer patients. Overall, this study uncovers a novel pathway wherein GSK3β-induced phosphorylation of RIPK4 strengthens its interaction with UCHL3, leading to increased deubiquitination and stabilization of RIPK4, thereby promoting ovarian cancer metastasis. These findings offer new insights into the molecular underpinnings of ovarian cancer and highlight potential therapeutic targets for enhancing antitumor efficacy.

N6-methyladenosine modification of OIP5-AS1 promotes glycolysis, tumorigenesis, and metastasis of gastric cancer by inhibiting Trim21-mediated hnRNPA1 ubiquitination and degradation

BACKGROUND

Opa-interacting protein 5 antisense transcript 1 (OIP5-AS1) has been demonstrated to play vital roles in development and progression of tumors such as gastric cancer (GC). However, the detailed molecular mechanism of OIP5-AS1 has not been completely elucidated. Our study aimed to investigate the role and the epigenetic regulation mechanism of OIP5-AS1 in GC.

METHODS

OIP5-AS1 expression in GC tissues was detected by RT-qPCR. Loss- and gain-of-function experiments were conducted to assess the biological function of OIP5-AS1 in vitro and in vivo. The interaction of OIP5-AS1 with insulin-like growth factor 2 mRNA-binding protein 3 (IGF2BP3) or heterogeneous nuclear nucleoprotein A1 (hnRNPA1) was verified by bioinformatics analysis, RNA pull-down assays, and RNA immunoprecipitation assays.

RESULTS

In this study, we identified that OIP5-AS1 is specifically overexpressed in GC tumor tissues and cell lines and correlated with a poor prognosis. The loss of OIP5-AS1 suppressed the proliferation, migration, invasion, epithelial-mesenchymal transition (EMT), and glycolysis of GC cells, but the ectopic expression of OIP5-AS1 had the opposite impact. Meanwhile, knockdown of OIP5-AS1 inhibited tumor growth in patient-derived xenograft models, as well as repressed tumor metastasis. Mechanistically, IGF2BP3 could bind to OIP5-AS1 by N6-methyladenosine (m6A) modification sites on OIP5-AS1, thereby stabilizing OIP5-AS1. Moreover, OIP5-AS1 prevented Trim21-mediated ubiquitination and degradation of hnRNPA1, stabilizing hnRNPA1 protein and promoting the malignant progression of GC by regulating PKM2 signaling pathway.

CONCLUSIONS

In conclusion, this study highlighted that OIP5-AS1 is an oncogenic m6A-modified long non-coding RNA (lncRNA) in GC and that IGF2BP3/OIP5-AS1/hnRNPA1 axis may provide a potential diagnostic or prognostic target for GC.

Research progress on the biological basis of Traditional Chinese Medicine syndromes of gastrointestinal cancers

Gastrointestinal cancers account for 11.6 % of all cancers, and are the second most frequently diagnosed type of cancer worldwide. Traditional Chinese medicine (TCM), together with Western medicine or alone, has unique advantages for the prevention and treatment of cancers, including gastrointestinal cancers. Syndrome differentiation and treatment are basic characteristics of the theoretical system of TCM. TCM syndromes are the result of the differentiation of the syndrome and the basis of treatment. Genomics, transcriptomics, proteomics, metabolomics, intestinal microbiota, and serology, generated around the central law, are used to study the biological basis of TCM syndromes in gastrointestinal cancers. This review summarizes current research on the biological basis of TCM syndrome in gastrointestinal cancers and provides useful references for future research on TCM syndrome in gastrointestinal cancers.

A novel copper-induced cell death-related lncRNA prognostic signature associated with immune infiltration and clinical value in gastric cancer

BACKGROUND

Gastric cancer (GC) is one of the most important malignancies and has a poor prognosis. Copper-induced cell death, recently termed cuproptosis, may directly affect the outcome of GC. Long noncoding RNAs (lncRNAs), possessing stable structures, can influence the prognosis of cancer and may serve as potential prognostic prediction factors for various cancers. However, the role of copper cell death-related lncRNAs (CRLs) in GC has not been thoroughly investigated. Here, we aim to elucidate the role of CRLs in predicting prognosis, diagnosis, and immunotherapy in GC patients.

METHODS

RNA expression data for 407 GC patients from The Cancer Genome Atlas (TCGA) were gathered, and differentially expressed CRLs were identified. Subsequently, the researchers applied univariate, LASSO, and multivariate Cox regression to construct a prognostic signature consisting of 5 lncRNAs based on the CRLs. Stratified by the median CRLSig risk score, Kaplan-Meier analysis was utilized to compare overall survival (OS) between the high- and low-risk groups. Among the two groups, gene set enrichment analysis (GSEA), tumor microenvironment (TME), drug sensitivity analysis, and immune checkpoint analysis were conducted. In addition, consensus clustering and nomogram analysis were performed to predict OS. Cell experiments and 112 human serum samples were employed to verify the effect of lncRNAs on GC. Furthermore, the diagnostic value of the CRLSig in the serum of GC patients was analyzed by the receiver operating characteristic (ROC) curve.

RESULTS

A prognostic signature for GC patients was constructed based on CRLs, composed of AC129926.1, AP002954.1, AC023511.1, LINC01537, and TMEM75. According to the K-M survival analysis, high-risk GC patients had a lower OS rate and progression-free survival rate than low-risk GC patients. Further support for the model's accuracy was provided by ROC, principal component analysis, and the validation set. The area under the curve (AUC) of 0.772 for GC patients showed a better prognostic value than any other clinicopathological variable. Furthermore, immune infiltration analysis showed that the high-risk group had greater antitumor immune responses in the tumor microenvironment. In the high-risk subgroup, 23 immune checkpoint genes had significantly higher expression levels than in the low-risk subgroup (p < 0.05). The half-maximal inhibitory concentrations (IC50) of 86 drugs were found to be significantly different in the two groups. Accordingly, the model is capable of predicting the effectiveness of immunotherapy. In addition, the five CRLs in GC serum exhibited statistically significant expression levels. The AUC of this signature in GC serum was 0.894, with a 95% CI of 0.822-0.944. Moreover, lncRNA AC129926.1 was significantly overexpressed in GC cell lines and the serum of GC patients. Importantly, colony formation, wound healing, and transwell assays further confirmed the oncogenic role of AC129926.1 in GC.

CONCLUSION

In this study, a prognostic signature model consisting of five CRLs was developed to improve OS prediction accuracy in GC patients. The model also has the potential to predict immune infiltration and immunotherapy effectiveness. Furthermore, the CRLSig might serve as a novel serum biomarker to differentiate GC patients from healthy individuals.