The nuclear-cytoplasmic trafficking of a chromatin-modifying and remodelling protein (KMT2C), in osteosarcoma

Novel diagnostic biomarkers of oxidative stress, immune- infiltration characteristics and experimental validation of SERPINE1 in colon cancer

BACKGROUND

Colon cancer (CC) is a prevalent malignant tumor that affects the colon in the gastrointestinal tract. Its aggressive nature, strong invasiveness, and rapid progression make it a significant health concern. In addition, oxidative stress can lead to the production of reactive oxygen species (ROS) that surpass the body's antioxidant defense capacity, causing damage to proteins, lipids, and DNA, potentially promoting tumor development. However, the relationship between CC and oxidative stress requires further investigation.

METHODS

We collected gene expression data and clinical data from 473 CC patients from The Cancer Genome Atlas (TCGA) dataset. Additionally, we obtained 433 oxidative stress genes from Genecards ( https://www.genecards.org/ ). Using univariate, multivariate, and LASSO Cox regression analyses, we developed predictive models for oxidative stress-related genes in CC patients. To validate the models, we utilized data from the Gene Expression Omnibus (GEO) database. We assessed the accuracy of the models through various techniques, including the creation of a nomogram, receiver operating characteristic curve (ROC) analysis, and principal component analysis (PCA). The Cytoscape program was utilized to identify hub genes among differentially expressed genes (DEGs) in tumor patients using the TCGA dataset. Subsequently, we conducted survival analysis, clinical relevance analysis, and immune cell relevance analysis for the intersected genes obtained by combining the hub genes with the genes from the predictive models. Moreover, we investigated the mRNA expression and potential functions of these intersected genes using a range of experimental approaches.

RESULTS

In both the TCGA and GSE17538 datasets, patients classified as high-risk had significantly shorter overall survival compared to those in the low-risk group (TCGA: p < 0.001; GSE17538: p = 0.010). As a result, we decided to further investigate the role of SERPINE1. Our survival analysis revealed that patients with high expression of SERPINE1 had a significantly lower probability of survival compared to those with low expression (p < 0.05). Additionally, our clinical correlation analysis showed a significant relationship between SERPINE1 expression and T, N, and M stages, as well as tumor grade. Furthermore, our immune infiltration correlation analysis demonstrated notable differences in multiple immune cells between the high- and low-expression groups of SERPINE1. To validate our findings, we conducted experimental tests and observed that knocking down SERPINE1 in colon cancer cells resulted in significant reductions in cell viability and proliferation. Interestingly, we also noticed an increase in oxidative stress parameters, such as ROS and MDA levels, while the levels of reduced GSH decreased upon SERPINE1 knockdown. These findings suggest that the antineoplastic effect of silencing SERPINE1 may be associated with the induction of oxidative stress.

CONCLUSION

In conclusion, this study introduces a new approach for the early diagnosis and treatment of CC, and further exploration of SERPINE1 could potentially lead to a significant advancement.

Molecular Subtyping and Survival Analysis of Osteosarcoma Reveals Prognostic Biomarkers and Key Canonical Pathways

Osteosarcoma (OS) is a common bone malignancy in children and adolescents. Although histological subtyping followed by improved OS treatment regimens have helped achieve favorable outcomes, a lack of understanding of the molecular subtypes remains a challenge to characterize its genetic heterogeneity and subsequently to identify diagnostic and prognostic biomarkers for developing effective treatments. In the present study, global analysis of DNA methylation, and mRNA and miRNA gene expression in OS patient samples were correlated with their clinical characteristics. The mucin family of genes, MUC6, MUC12, and MUC4, were found to be highly mutated in the OS patients. Results revealed the enrichment of molecular pathways including Wnt signaling, Calcium signaling, and PI3K-Akt signaling in the OS tumors. Survival analyses showed that the expression levels of several genes such as RAMP1, CRIP1, CORT, CHST13, and DDX60L, miRNAs and lncRNAs were associated with survival of OS patients. Molecular subtyping using Cluster-Of-Clusters Analysis (COCA) for mRNA, lncRNA, and miRNA expression; DNA methylation; and mutation data from the TARGET dataset revealed two distinct molecular subtypes, each with a distinctive gene expression profile. Between the two subtypes, three upregulated genes, POP4, HEY1, CERKL, and seven downregulated genes, CEACAM1, ABLIM1, LTBP2, ISLR, LRRC32, PTPRF, and GPX3, associated with OS metastasis were found to be differentially regulated. Thus, the molecular subtyping results provide a strong basis for classification of OS patients that could be used to develop better prognostic treatment strategies.

FAT1 and MSH2 Are Predictive Prognostic Markers for Chinese Osteosarcoma Patients Following Chemotherapeutic Treatment

Osteosarcoma is characterized by diverse genetic mutations, including single-nucleotide variants (SNVs), which can complicate clinical outcomes of the treatment. This study identified key mutations or polymorphisms in genes that correlate with osteosarcoma prognoses. A total of 110 patients with osteosarcoma were assigned to "good" or "poor" cohorts depending on their 5-year disease-free survival (DFS) after surgery and chemotherapeutic treatment. We performed next-generation sequencing analysis of tumor tissues for prognosis-associated SNVs in 315 tumorigenesis-related genes, followed by modeling of clinical outcomes for these patients using random forest classification via a support vector machine (SVM). Data from the Chinese Millionome Database were used to compare SNV frequency in osteosarcoma patients and healthy people. SVM screening identified 17 nonsynonymous SNVs located in 15 genes, of which rs17224367 and rs3733406 (located in MSH2 and FAT1, respectively) were strongly correlated with osteosarcoma prognosis. These results were verified in a 26-patient validation cohort, confirming that these SNVs could be used to predict prognosis. These results demonstrated that two SNVs located in MSH2 and FAT1 are associated with prognosis of osteosarcoma patients. © 2022 American Society for Bone and Mineral Research (ASBMR).

XIST lost induces ovarian cancer stem cells to acquire taxol resistance via a KMT2C-dependent way

BACKGROUND/AIMS

The expression levels of long non-coding RNA XIST are significantly associated with paclitaxel (Pac) sensitivity in ovarian cancer, but the mechanism of action remains unclear. Therefore, this experimental design was based on lncRNA XIST analysis to regulate the effect of XIST on the tumor stem cell and paclitaxel sensitivity in ovarian cancer.

METHODS

Sphere assay and fluorescence activated cell sorting (FACS) were used to determine the expression levels of XIST and sensitivity to paclitaxel treatment. The effect of the proliferation was detected by MTT assay. Target gene prediction and screening, luciferase reporter assays were used to validate downstream target genes for lncRNA XIS and KMT2C. The expression of KMT2C was detected by RT-qPCR and Western blotting. RT-qPCR was used to detect the expression of cancer stem cell-associated genes SOX2, OCT4 and Nanog. The tumor changes in mice were detected by in vivo experiments in nude mice.

RESULTS

There was an inverse correlation between the expression of XIST and cancer stem cell (CD44 + /CD24-) population. XIST promoted methylation of histone H3 methylation at lysine 4 by enhancing the stability of lysine (K)-specific methyltransferase 2C (KMT2C) mRNA. XIST acted on the stability of KMT2C mRNA by directly targeting miR-93-5p. Overexpression of miR-93-5p can reverse the XIST overexpression-induced KMT2C decrease and sphere number increase. Overexpression of KMT2C inhibited XIST silencing-induced proliferation of cancer stem cells, and KMT2C was able to mediate paclitaxel resistance induced by XIST in ovarian cancer. The study found that XIST can affect the expression of KMT2C in the ovarian cancer via targeting miR-93-5p.

CONCLUSION

XIST promoted the sensitivity of ovarian cancer stem cells to paclitaxel in a KMT2C-dependent manner.

KMT2C modulates migration and invasion processes in osteosarcoma cell lines

In this study we investigated the role of KMT2C (a chromatin-modifying and remodelling protein) in osteosarcoma progression through cell migration and invasion assays in osteosarcoma primary and metastatic cell lines. Wound healing and transwell assays were used to detect changes of cell migration and matrigel assay was used to evaluate changes of cell invasion in primary and metastatic osteosarcoma cell lines after KMT2C siRNA transfection. We found that primary osteosarcoma cell lines showed the highest capacity of migration before mRNA KMT2C silencing and the highest capacity of invasion after mRNA KMT2C silencing; on the contrary, osteosarcoma metastatic cell line showed the highest capacity of migration after mRNA KMT2C silencing and the highest capacity of invasion before mRNA KMT2C silencing. Our study supports data in favour of selective enhancer changes, KMT2C-mediated, in metastatic osteosarcoma probably due to the different microenvironment between primary and metastatic sites.