5mC-Related lncRNAs as Potential Prognostic Biomarkers in Colon Adenocarcinoma

Tracking the Early Stage of Triplet-Induced Photodamage in a DNA Dimer and Oligomer Containing 5-Methylcytosine

Methylation at the C5 position of cytosine, a naturally occurring epigenetic modification on DNA, shows a high correlation with mutational hotspots in disease such as skin cancer. Due to its essential biological relevance, numerous studies were devoted to confirming that the methylated sites favor the formation of the cyclobutane pyrimidine dimer (CPD), a well-known UV-induced lesion. However, photophysical and photochemical properties of dinucleotides and polynucleotides containing 5-methylcytosine (5mC) remain elusive. Herein, a charge transfer (CT) triplet state, generated via intersystem crossing (ISC) from a CT singlet state that enhanced after methylation on cytosine, is directly observed by using femtosecond transient absorption (TA) and time-resolved mid-infrared (TRIR) spectroscopy together with quantum chemical calculations for the first time in the T5mC dimer. Such an ISC process is quenched due to limitations of the ground-state geometries in 5mC-containing single-strand oligomer d(T5mC)9. This mechanistic information is important for understanding the early stage of triplet state-induced CPD formation in 5mC containing DNA.

Identification of an m6A-Related Long Noncoding RNA Risk Model for Predicting Prognosis and Directing Treatments in Patients With Colon Adenocarcinoma

N6-methyladenosine (m6A) and lncRNAs have been implicated in the development of colon cancer, including tumorigenesis, migration, and invasion. However, the specific effect of m6A regulators on lncRNAs is not clear, and m6A-related lncRNAs may be new prognostic biomarkers and may help direct treatment and medication. We identified 29 prognostic m6A-related lncRNAs and constructed a risk model using 12 lncRNAs. The model was an independent prognostic factor and could accurately predict the prognosis. A stable and robust nomogram that combined the model and pathologic stage was constructed. A total of 2,424 differentially expressed genes (DEGs) were identified based on the model. Functional analysis of the DEGs showed that they were associated with tumor progression, helping investigate the underlying biological functions and signaling pathways of the risk model. In addition, the low-risk group based on the risk model had more sensitivity to afatinib, metformin, and GW.441756, and patients with low risk would more likely respond to immunotherapy. Moreover, patients with higher risk were more sensitive to olaparib, bexarotene, and doxorubicin.