A germline SNP in BRMS1 predisposes patients with lung adenocarcinoma to metastasis and can be ameliorated by targeting c-fos

The emerging roles of CEACAM6 in human cancer (Review)

Carcinoembryonic antigen (CEA)‑related cell adhesion molecule 6 (CEACAM6) is a cell adhesion protein of the CEA family of glycosyl phosphatidyl inositol anchored cell surface glycoproteins. A wealth of research has demonstrated that CEACAM6 is generally upregulated in pancreatic adenocarcinoma, breast cancer, non‑small cell lung cancer, gastric cancer, colon cancer and other cancers and promotes tumor progression, invasion and metastasis. The transcriptional expression of CEACAM6 is regulated by various factors, including the CD151/TGF‑β1/Smad3 axis, microRNA (miR)‑146, miR‑26a, miR‑29a/b/c, miR‑128, miR‑1256 and DNA methylation. In addition, the N‑glycosylation of CEACAM6 protein at Asn256 is mediated by α‑1,6‑mannosylglycoptotein 6‑β‑N‑acetylglucosaminyltransferase. In terms of downstream signaling pathways, CEACAM6 promotes tumor proliferation by increasing levels of cyclin D1 and cyclin‑dependent kinase 4 proteins. CEACAM6 can activate the ERK1/2/MAPK or SRC/focal adhesion kinase/PI3K/AKT pathways directly or through EGFR, leading to stimulation of tumor proliferation, invasion, migration, resistance to anoikis and chemotherapy, as well as angiogenesis. This article provides a review of the expression pattern, biological function and relationship with prognosis of CEACAM6 in cancer. In summary, CEACAM6 may be a valuable diagnostic biomarker and potential therapeutic target for human cancers exhibiting overexpression of CEACAM6.

METTL3 drives NSCLC metastasis by enhancing CYP19A1 translation and oestrogen synthesis

BACKGROUND

METTL3 plays a significant role as a catalytic enzyme in mediating N6-methyladenosine (m6A) modification, and its importance in tumour progression has been extensively studied in recent years. However, the precise involvement of METTL3 in the regulation of translation in non-small cell lung cancer (NSCLC) remains unclear.

RESULTS

Here we discovered by clinical investigation that METTL3 expression is correlated with NSCLC metastasis. Ablation of METTL3 in NSCLC cells inhibits invasion and metastasis in vitro and in vivo. Subsequently, through translatomics data mining and experimental validation, we demonstrated that METTL3 enhances the translation of aromatase (CYP19A1), a key enzyme in oestrogen synthesis, thereby promoting oestrogen production and mediating the invasion and metastasis of NSCLC. Mechanistically, METTL3 interacts with translation initiation factors and binds to CYP19A1 mRNA, thus enhancing the translation efficiency of CYP19A1 in an m6A-dependent manner. Pharmacological inhibition of METTL3 enzymatic activity or translation initiation factor eIF4E abolishes CYP19A1 protein synthesis.

CONCLUSIONS

Our findings indicate the crucial role of METTL3-mediated translation regulation in NSCLC and reveal the significance of METTL3/eIF4E/CYP19A1 signaling as a promising therapeutic target for anti-metastatic strategies against NSCLC.

Risk scoring based on DNA methylation-driven related DEGs for colorectal cancer prognosis with systematic insights

Colorectal cancer is a common malignant tumor of the digestive tract. Despite advances in diagnostic techniques and medications. Its prognosis remains challenging. DNA methylation-driven related circulating tumor cells have attracted enormous interest in diagnosing owing to their non-invasive nature and early recognition properties. However, the mechanism through which risk biomarkers act remains elusive. Here, we designed a risk model based on differentially expressed genes, DNA methylation, robust, and survival-related factors in the framework of Cox regression. The model has satisfactory performance and is independently verified by an external and isolated dataset in terms of C-index value, ROC, and tROC. The model was applied to Colorectal cancer patients who were subsequently divided into high- and low-risk groups. Functional annotations, genomic alterations, tumor immune environment, and drug sensitivity were analyzed. We observed that up-regulated genes are associated with epithelial cell differentiation and MAPK signaling pathways. The down-regulated genes are related to IL-7 signaling and apoptosis-induced DNA fragmentation. Interestingly, the immune system was inhibited in high-risk groups. High-frequency mutation genes tend to co-occur. High-risk score patients are related to copy number amplification events. To address the challenges, we suggested eleven and twenty-one drugs that are sensitive to low- and high-risk patients. Finally, an artificial neural network was provided to evaluate the immunotherapeutic efficiency. Taken together, the findings demonstrated that our risk score model is robust and reliable for evaluating the prognosis with novel diagnostic and treatment targets. It also yields benefits for the treatment and provides unique insights into developing therapeutic strategies.