PDAC is one of the most common malignant tumors worldwide. The difficulty of early diagnosis and lack of effective treatment are the main reasons for its poor prognosis. Therefore, it is urgent to identify novel diagnostic and therapeutic targets for PDAC patients. The m⁷G methylation is a common type of RNA modification that plays a pivotal role in regulating tumor development. However, the correlation between m⁷G regulatory genes and PDAC progression remains unclear. By integrating gene expression and related clinical information of PDAC patients from TCGA and GEO cohorts, m⁷G binding protein NCBP2 was found to be highly expressed in PDAC patients. More importantly, PDAC patients with high NCBP2 expression had a worse prognosis. Stable NCBP2-knockdown and overexpression PDAC cell lines were constructed to further perform in-vitro and in-vivo experiments. NCBP2-knockdown significantly inhibited PDAC cell proliferation, while overexpression of NCBP2 dramatically promoted PDAC cell growth. Mechanistically, NCBP2 enhanced the translation of c-JUN, which in turn activated MEK/ERK signaling to promote PDAC progression. In conclusion, our study reveals that m⁷G reader NCBP2 promotes PDAC progression by activating MEK/ERK pathway, which could serve as a novel therapeutic target for PDAC patients.

Colon cancer (CC), one of the most common malignancies worldwide, lacks an effective prognostic prediction biomarker. N7-methylguanosine (m7G) methylation is a common RNA modification type and has been proven to influence tumorigenesis. However, the correlation between m7G-related genes and CC remains unclear. The gene expression levels and clinical information of CC patients were downloaded from public databases. Twenty-nine m7G-related genes were obtained from the published literature. Via unsupervised clustering based on the expression levels of m7G-related genes, CC patients were divided into three m7G clusters. Based on differentially expressed genes (DEGs) from the above three groups, CC patients were further divided into three gene clusters. The m7G score, a prognostic model, was established using principal component analysis (PCA) based on 15 prognosis-associated m7G genes. KM curve analysis demonstrated that the overall survival rate was remarkably higher in the high-m7G score group, which was much more significant in advanced CC patients as confirmed by subgroup analysis. Correlation analysis indicated that the m7G score was associated with tumor mutational burden (TMB), PD-L1 expression, immune infiltration, and drug sensitivity. The expression level of prognosis-related m7G genes was further confirmed in human CC cell lines and samples. This study established an m7G gene-based prognostic model (m7G score), which demonstrated the important roles of m7G-related genes during CC initiation and progression. The m7G score could be a practical biomarker to predict immunotherapy response and prognosis in CC patients.

Colon cancer (CC) is one of the most common (6%) malignancies and leading cause of cancer-associated death (more than 0.5 million) worldwide, which demands reliable prognostic biomarkers. Cuproptosis is a novel modality of regulated cell death triggered by the accumulation of intracellular copper. LncRNAs have been reported as prognostic signatures in different types of tumors. However, the correlation between cuproptosis-related lncRNAs (CRLs) and CC remains unclear. Data of CC patients were downloaded from public databases. The prognosis-associated CRLs were identified by co-expression analysis and univariate Cox. Least absolute shrinkage and selection operator were utilized to construct the CRLs-based prognostic signature in silico for CC patients. CRLs level was validated in human CC cell lines and patient tissues. ROC curve and Kaplan–Meier curve results revealed that high CRLs-risk score was associated with poor prognosis in CC patients. Moreover, the nomogram revealed that this model possessed a steady prognostic prediction capability with C-index as 0.68. More importantly, CC patients with high CRLs-risk score were more sensitive to eight targeted therapy drugs. The prognostic prediction power of the CRLs-risk score was further confirmed by cell lines, tissues and two independent CC cohorts. This study constructed a novel ten-CRLs-based prognosis model for CC patients. The CRLs-risk score is expected to serve as a promising prognostic biomarker and predict targeted therapy response in CC patients.