KRAS gene polymorphisms are associated with the risk of glioma: a two-center case-control study

Identification of circulating miRNA as early diagnostic molecular markers in malignant glioblastoma base on decision tree joint scoring algorithm

PURPOSE

The lack of clinical markers prevents early diagnosis of glioblastoma (GBM). Many studies have found that circulating microRNAs (miRNAs) can be used as early diagnostic markers of malignant tumours. Therefore, the identification of novel circulating miRNA biomolecular markers could be beneficial to clinicians in the early diagnosis of GBM.

METHODS

We developed a decision tree joint scoring algorithm (DTSA), systematically integrating significance analysis of microarray (SAM), Pearson hierarchical clustering, T test, Decision tree and Entropy weight score algorithm, to screen out circulating miRNA molecular markers with high sensitivity and accuracy for early diagnosis of GBM.

RESULTS

DTSA was developed and applied for GBM datasets and three circulating miRNA molecular markers were identified, namely, hsa-miR-2278, hsa-miR-555 and hsa-miR-892b. We have found that hsa-miR-2278 and hsa-miR-892b regulate the GBM pathway through target genes, promoting the development of GBM and affecting the survival of patients. DTSA has better classification effect in all data sets than other classification algorithms, and identified miRNAs are better than existing markers of GBM.

CONCLUSION

These results suggest that DTSA can effectively identify circulating miRNA, thus contributing to the early diagnosis and personalised treatment of GBM.

Association of the rs8720 and rs12587 KRAS Gene Variants with Colorectal Cancer in a Mexican Population and Their Analysis In Silico

Colorectal cancer (CRC) is a major global health challenge and one of the top 10 cancers in Mexico. Lifestyle and genetic factors influence CRC development, prognosis, and therapeutic response; identifying risk factors, such as the genes involved, is critical to understanding its behavior, mechanisms, and prognosis. The association between KRAS gene variants (rs8720 and rs12587) and CRC in the Mexican population was analyzed. We performed in silico analysis and analyzed 310 healthy individuals and 385 CRC patients using TaqMan assays and real-time PCR. The CC and GG genotypes of rs8720 and rs12587 were identified as CRC risk factors (p < 0.05). The CC and TC genotypes of the rs8720 were associated with rectal cancer, age over 50 years, moderately differentiated histology, and advanced cancer stage. TG and GG genotypes of the rs12587 variant were a risk factor in the CRC group, in patients with stage I-II, males, and stage III-IV non-chemotherapy response. The TG haplotype is protected against CRC. The combined CCGG genotype was linked to CRC risk. In silico analysis revealed that the rs12587 and rs8720 variants could influence KRAS gene regulation via miRNAs. In conclusion, rs8720 and rs12587 variants of the KRAS gene were associated with CRC risk and could influence KRAS regulation via miRNAs.

A novel cuproptosis-related LncRNA signature: Prognostic and therapeutic value for low grade glioma

Background

As a common primary intracranial tumor, the diagnosis and therapy of low-grade glioma (LGG) remains a pivotal barrier. Cuproptosis, a new way induces cell death, has attracted worldwide attention. However, the relationship between cuproptosis and LGG remains unknown. Our study is all about finding out if there are any genes related to coproptosis that can be used to predict the outcome of LGG.

Methods

RNA data and clinical information were selected from Cancer Genome Atlas (TCGA) datasets and the Genotype-Tissue Expression (GTEx), 5 lncRNAs (GAS5.AS1, MYLK.AS1, AC142472.1, AC011346.1, AL359643.3) were identified by Cox univariate and multivariate regression, as well as LASSO Cox regression. In the training and test sets, a dual validation of the predictive signature comprised of these 5 lncRNAs was undertaken. The findings demonstrate that the risk model is able to predict the survival regression of LGG patients and has a good performance in either the KM curve approach or the ROC curve. GO, GSEA and KEGG were carried out to explore the possible molecular processes that affecting the prognosis of LGG. The characteristics of immune microenvironment were investigated by using CIBERSORT, ESTIMATE and ssGSEA.

Results

We identified five lncRNAs related with cuproptosis that were closely associated with the prognosis of LGG and used these five lncRNAs to develop a risk model. Using this risk model, LGG patients were then divided into high-risk and low-risk groups. The two patient groups had significantly distinct survival characteristics. Analyses of Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) revealed that the differential genes of the two patient groups were primarily concentrated in neural active ligand-receptor interaction and cytokine-cytokine receptor interaction. The ssGSEA score determined the information related to immune infiltration, and the two groups were differentially expressed in immune subpopulations such as T cells and B cells as well.

Conclusion

Our study discovered 5 cuproptosis-related lncRNAs which contribute to predicting patients' survival of LGG and provide ideas for the exploration of new targets for LGG in the future.

Comprehensive Characterization of a Novel E3-Related Gene Signature With Implications in Prognosis and Immunotherapy of Low-Grade Gliomas

Gliomas, a type of primary brain tumor, have emerged as a threat to global mortality due to their high heterogeneity and mortality. A low-grade glioma (LGG), although less aggressive compared with glioblastoma, still exhibits high recurrence and malignant progression. Ubiquitination is one of the most important posttranslational modifications that contribute to carcinogenesis and cancer recurrence. E3-related genes (E3RGs) play essential roles in the process of ubiquitination. Yet, the biological function and clinical significance of E3RGs in LGGs need further exploration. In this study, differentially expressed genes (DEGs) were screened by three differential expression analyses of LGG samples from The Cancer Genome Atlas (TCGA) database. DEGs with prognostic significance were selected by the univariate Cox regression analysis and log-rank statistical test. The LASSO-COX method was performed to identify an E3-related prognostic signature consisting of seven genes AURKA, PCGF2, MAP3K1, TRIM34, PRKN, TLE3, and TRIM17. The Chinese Glioma Genome Atlas (CGGA) dataset was used as the validation cohort. Kaplan–Meier survival analysis showed that LGG patients in the low-risk group had significantly higher overall survival time than those in the high-risk group in both TCGA and CGGA cohorts. Furthermore, multivariate Cox regression analysis revealed that the E3RG signature could be used as an independent prognostic factor. A nomogram based on the E3RG signature was then established and provided the prediction of the 1-, 3-, and 5-year survival probability of patients with LGGs. Moreover, DEGs were analyzed based on the risk signature, on which function analyses were performed. GO and KEGG analyses uncovered gene enrichment in extracellular matrix–related functions and immune-related biological processes in the high-risk group. GSEA revealed high enrichment in pathways that promote tumorigenesis and progression in the high-risk group. Furthermore, ESTIMATE algorithm analysis showed a significant difference in immune and stroma activity between high- and low-risk groups. Positive correlations between the risk signature and the tumor microenvironment immune cell infiltration and immune checkpoint molecules were also observed, implying that patients with the high-risk score may have better responses to immunotherapy. Overall, our findings might provide potential diagnostic and prognostic markers for LGG patients and offer meaningful insight for individualized treatment.

Midkine promotes glioblastoma progression via PI3K-Akt signaling

Background

Our previous bioinformatics-based study found that midkine (MDK) was associated with poor prognosis of glioblastoma (GBM). However, the mechanism of MDK in GBM remains elusive.

Methods

A public GBM-related dataset and GBM tissues from our center were used validate the aberrant expression of MDK in GBM at the RNA and protein levels. The relationship between MDK expression and survival of GBM patients was also explored through survival analysis. Subsequently, we identified MDK-related GBM-specific genes using differential expression analysis. Functional enrichment analyses were performed to reveal their potential biological functions. CCK-8, 5-ethynyl-2′-deoxyuridine, and Matrigel-transwell assays were performed in GBM cell lines in which MDK was knocked out or overexpressed in order assess the effects of MDK on proliferation, migration, and invasion of GBM cells. Western blotting was performed to detect candidate proteins.

Results

Our study showed MDK is a promising diagnostic and prognostic biomarker for GBM because it is highly expressed in the disease and it is associated with poor prognosis. MDK is involved in various cancer-related pathways, such as PI3K-Akt signaling, the cell cycle, and VEGF signaling. A comprehensive transcriptional regulatory network was constructed to show the potential pathways through which MDK may be involved in GBM. In vitro, Overexpression of MDK augmented proliferation, migration, and invasion of GBM cell lines, whereas suppression of MDK led to the opposite effects. Furthermore, our study confirmed that MDK promotes the progression of GBM by activating the PI3K-Akt signaling pathway.

Conclusions

Our present study proposes that MDK promotes GBM by activating the PI3K-Akt signaling pathway, and it describes a potential regulatory network involved.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02212-3.