Key molecular DNA damage responses of human cells to radiation.

Our understanding of the DNA damage responses of human cells to radiation has increased remarkably over the recent years although some notable signaling events remain to be discovered. Here we provide a brief account of the key molecular events of the responses to reflect the current understanding of the key underlying mechanisms involved.

Analysis of O-acetylated sialic acids by 3-nitrophenylhydrazine derivatization combined with LC-MS/MS.

Sialic acids are a family of monosaccharides that share a nine-carbon backbone and a carboxyl group. A recent derivatization method based on 3-nitrophenylhydrazine (3-NPH) provides a mild chemical labeling technique for biomolecules containing carbonyl or carboxyl groups. In this study, we utilized 3-NPH to label sialic acids via a two-step derivatization process. The derivatized species can produce a common reporter ion corresponding to C1-C3 with two labels, and a fragment differentiating between Neu5Ac, Neu5Gc, and KDN. This method is compatible with O-acetylated sialic acids and provides high sensitivity to Neu5Gc and KDN, and since the utilization of dual labeling significantly enhances the hydrophobicity of derivatives, it can effectively mitigate matrix effects when combined with parallel reaction monitoring technology. Negative-ion tandem mass spectrometry (MS/MS) analysis reveals a distinctive fragmentation profile for the 4-O-acetylated species, while the other sialic acids yield similar MS/MS spectra with a high abundance of reporter ions. Using the reporter ion as a transition, this analytical strategy is effective for analyzing complex biological samples. For example, it was successfully employed to quantify sialic acids in the intestinal tissues of several carp species, demonstrating its potential in sialylation research.

Stable isotope labeling-based two-step derivatization strategy for analysis of Phosphopeptides.

Investigating site-specific protein phosphorylation remains a challenging task. The present study introduces a two-step chemical derivatization method for accurate identification of phosphopeptides. Methylamine neutralizes carboxyl groups, thus reducing the adsorption of non-phosphorylated peptides during enrichment, while dimethylamine offers a cost-effective reagent for stable isotope labeling of phosphorylation sites. The derivatization improves the mass spectra obtained through liquid chromatography-tandem mass spectrometry. The product ions at m/z 58.07 and 64.10 Da, resulting from dimethylamine-d0 and dimethylamine-d6 labeled phosphorylation sites respectively, can serve as report ions. Derivatized phosphopeptides from casein demonstrate enhanced ionization and formation of product ions, yielding a significant increase in the number of identifiable peptides. When using the parallel reaction monitoring technique, it is possible to distinguish isomeric phosphopeptides with the same amino acid sequence but different phosphorylation sites. By employing a proteomic software and screening the report ions, we identified 29 endogenous phosphopeptides in 10 µL of human saliva with high reliability. These findings indicate that the two-step derivatization strategy has great potential in site-specific phosphorylation and large-scale phosphoproteomics research. SIGNIFICANCE: There is a significant need to improve the accuracy of identifying phosphoproteins and phosphopeptides and analyzing them quantitatively. Several chemical derivatization techniques have been developed to label phosphorylation sites, thus enabling the identification and relative quantification of phosphopeptides. Nevertheless, these methods have limitations, such as incomplete conversion or the need for costly isotopic reagents. Building upon previous contributions, our study moves the field forward due to high efficiency in site-specific labeling, cost-effectiveness, improved sensitivity, and comprehensive product ion coverage. Using the two-step derivatization approach, we successfully identified 29 endogenous phosphopeptides in 10 µL of human saliva with high reliability. The outcomes underscore the possibility of the method for site-specific phosphorylation and large-scale phosphoproteomics investigations.

Developing a prognosis and chemotherapy evaluating model for colon adenocarcinoma based on mitotic catastrophe-related genes.

Mitotic catastrophe (MC) is a novel form of cell death that plays an important role in the treatment and drug resistance of colon adenocarcinoma (COAD). However, MC related genes in COAD treatment and prognosis evaluation are rarely studied. In this study, the transcriptome data, somatic mutation and copy number variation data were obtained from The Cancer Genome Atlas (TCGA) database. The mitotic catastrophe related genes (MCRGs) were obtained from GENCARDS website. Differential gene analysis was conducted with LIMMA package. Univariate Cox regression analysis was used to identify prognostic related genes. Mutation analysis was performed and displayed by maftools package. RCircos package was used for localizing the position of genes on chromosomes. "Glmnet" R package was applied for constructing a risk model via the LASSO regression method. Consensus clustering analyses was implemented for clustering different subtypes. Functional enrichment analysis through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) methods, immune infiltration analysis via single sample gene set enrichment analysis (ssGSEA), tumor mutation burden and drug sensitivity analysis by pRRophetic R package were also carried out for risk model or molecular subtype's assessment. Additionally, the connections between the expression of hub genes and overall survival (OS) were obtained from online Human Protein Atlas (HPA) website. Real-Time Quantitative Polymerase Chain Reaction (RT­qPCR) further validated the expression of hub genes. A total of 207 differentially expressed MCRGs were selected in the TCGA cohort, 23 of which were significantly associated with OS in COAD patients. Subsequently, we constructed risk score prognostic models with 5 hub MCRGs, including SYCE2, SERPINE1, TRIP6, LIMK1, and EEPD1. The high-risk patients suffered from poorer prognosis. Furthermore, we developed a nomogram that gathered age, sex, staging, and risk score to accurately forecast the clinical survival outcomes in 1, 3, and 5 years. The results of functional enrichment suggested a significant correlation between MCRGs characteristics and cancer progression, with important implications for the immune microenvironment. Moreover, patients who displayed high TMB and high risk score showed worse prognosis, and risk characteristics were associated with different chemotherapeutic agents. Finally, RT­qPCR verified the increased expression of the five MCRGs in clinical samples. The five MCRGs in the prognostic signature were associated with prognosis, and could be treated as reliable prognostic biomarkers and therapeutic targets for COAD patients with distinct clinicopathological characteristics, thereby providing a foundation for the precise application of pertinent drugs in COAD patients.

Identification of Hub Genes for Colorectal Cancer with Liver Metastasis Using miRNA-mRNA Network.

Background: Liver metastasis is an important cause of death in patients with colorectal cancer (CRC). Increasing evidence indicates that microRNAs (miRNAs) are involved in the pathogenesis of colorectal cancer liver metastasis (CRLM). This study is aimed at exploring the potential miRNA-mRNA regulatory network. Methods: From the GEO database, we downloaded the microarray datasets GSE56350 and GSE73178. GEO2R was used to conduct differentially expressed miRNAs (DEMs) between CRC and CRLM using the GEO2R tool. Then, GO and KEGG pathway analysis for differentially expressed genes (DEGs) performed via DAVID. A protein-protein interaction (PPI) network was constructed by the STRING and identified by Cytoscape. Hub genes were identified by miRNA-mRNA network. Finally, the expression of the hub gene expression was assessed in the GSE81558. Results: The four DEMs (hsa-miR-204-5p, hsa-miR-122-5p, hsa-miR-95-3p, and hsa-miR-552-3p) were identified as common DEMs in GSE56350 and GSE73178 datasets. The SP1 was likely to adjust the upregulated DEMs; however, the YY1 could regulate both the upregulated and downregulated DEMs. A total of 3925 genes (3447 upregulated DEM genes and 478 downregulated DEM genes) were screened. These predicted genes were mainly linked to Platinum drug resistance, Cellular senescence, and ErbB signaling pathway. Through the gene network construction, most of the hub genes were found to be modulated by hsa-miR-204-5p, hsa-miR-122-5p, hsa-miR-95-3p, and hsa-miR-552-3p. Among the top 20 hub genes, the expression of CREB1, RHOA, and EGFR was significantly different in the GSE81558 dataset. Conclusion: In this study, miRNA-mRNA networks in CRLM were screened between CRC patients and CRLM patients to provide a new method to predict for the pathogenesis and development of CRC.