Bioinformatics Analysis of Neuroblastoma miRNA Based on GEO Data

Construction and evaluation of a prognostic model of autophagy-related genes in hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is a globally prevalent disease. Our article evaluates risk models based on autophagy- and HCC-related genes and their prognostic value by bioinformatics analytical methods to provide a scientific basis for clinical treatment.

Methods

Prognostic genes were identified by univariate and multivariate Cox analyses, and risk scores were calculated. The value of risk models was analysed by receiver operating characteristic curve (ROC), immune microenvironment and drug sensitivity. Prognostic gene-related regulatory mechanisms based on network database.

Results

We screened four prognosis-related genes (SQSTM1, GABARAPL1, CDKN2A, HSPB8) for model construction. The AUC for 1-, 2- and 3-year survival was higher than 0.6 in both the training and validation sets. The nomogram constructed based on risk scores, pathologic_T predicted the outcome better. There were differences in the tumour microenvironment between the high and low risk groups, as evidenced by differences in the distribution of immune cells and differences in the expression of immune checkpoints.

Conclusion

Our results illustrate that models, nomograms and risk scores were valuable for tumour progression.

Clinical trial number

Not applicable.

MiR-1271-5p promotes the growth and migration of neuroblastoma cells by regulating ACY-1

Background

Aminoacylase 1 (ACY-1) has been found to be a tumor suppressor gene in neuroblastoma (NB). This study aimed to identify and verify the microRNAs (miRNAs) that may regulate ACY-1 through database prediction analysis, and verify the mutual regulatory effect of miRNA and ACY-1 in NB through cell experiments.

Methods

The miRNAs that might bind ACY-1 were predicted and selected by TargetScan, miRTarBase and four other databases, the expression of the predicted miRNAs and ACY-1 was detected by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) in four groups of clinical samples, and the differentially expressed miRNAs were screened. Then, luciferase vector was constructed according to the ACY-1 gene sequence to detect whether ACY-1 binds to the selected miRNA. Then, miR-1271-5p expression was silenced to detect miR-1271-5p function in the growth and migration of NB. Finally, ACY-1 and miR-1271-5p were silenced to change ACY-1 expression, and ACY-1 function in NB and the regulatory role of miR-1271-5p were explored.

Results

ACY-1 was downregulated in NB, miR-1271-5p was upregulated in NB, and miR-1271-5p could be targeted to ACY-1. Silencing miR-1271-5p expression can reduce cell viability and inhibit tumor progression. After interfering with ACY-1 expression in cells, cell viability was enhanced, apoptosis was significantly decreased, and migration and invasion were enhanced. After partially restoring ACY-1 expression, the effect of si-ACY-1 on cells was weakened. In SK-N-SH and SH-SY-5Y cells, the miR-1271-5p inhibitor restored ACY-1 expression and improved ACY-1 function.

Conclusions

MiR-1271-5p can promote the growth and migration of tumor cells by inhibiting ACY-1 expression in NB.

Model for predicting prognosis and immunotherapy based on CD+8 T cells infiltration in neuroblastoma

BACKGROUND

Neuroblastoma (NBL) is an extracranial malignant tumor in children deriving from the neural crest in the sympathetic nervous system. Although various immunotherapy interventions have made significant breakthroughs in many adult cancers, the efficacy of these immunotherapies was still limited in NBL. NBL has low immunogenicity which results in a lack of tumor-infiltrating T lymphocytes in the tumor microenvironment (TME). Moreover, tumor cells can wield many immune evasion strategies both in the TME and systemically to impede lymphocyte infiltration and activation. All these factors hamper the anti-tumor effects of CD8+ T cells during immunotherapy and the levels of infiltrating CD8+ T cells correlate with therapy response.

MATERIALS AND METHODS

In this study, we utilized multidimensional bioinformatic methods to establish a risk model based on CD8+ T cells -related genes (CD8+ TRGs).

RESULTS

We obtained 33 CD8+ TRGs with well-predictive ability for prognosis in both GSE49711 and E-MTAB-8248 cohorts. Then, 12 CD8+ TRGs including HK2, RP2, HPSE, ELL2, GFI1, SLC22A16, FCGR3A, CTSS, SH2D1A, RBP5, ATF5, and ADAM9 were finally identified for risk model construction and validation. This model revealed a stable performance in prognostic prediction of the overall survival (OS) and event-free survival (EFS) in patients with NBL. Additionally, our research indicated that the immune and stromal scores, immune-related pathways, immune cell infiltration, the expression of major histocompatibility complex (MHC) and immune checkpoint molecules, immunotherapy response, and drug susceptibility revealed significant differences between high and low-risk groups.

CONCLUSIONS

According to our analyses, the constructed CD8+ TRGs-based risk model may be promising for the clinical prediction of anti-tumor therapy responses and prognoses in NBL.

Molecular Biology in Treatment Decision Processes-Neuro-Oncology Edition

Computational approaches including machine learning, deep learning, and artificial intelligence are growing in importance in all medical specialties as large data repositories are increasingly being optimised. Radiation oncology as a discipline is at the forefront of large-scale data acquisition and well positioned towards both the production and analysis of large-scale oncologic data with the potential for clinically driven endpoints and advancement of patient outcomes. Neuro-oncology is comprised of malignancies that often carry poor prognosis and significant neurological sequelae. The analysis of radiation therapy mediated treatment and the potential for computationally mediated analyses may lead to more precise therapy by employing large scale data. We analysed the state of the literature pertaining to large scale data, computational analysis, and the advancement of molecular biomarkers in neuro-oncology with emphasis on radiation oncology. We aimed to connect existing and evolving approaches to realistic avenues for clinical implementation focusing on low grade gliomas (LGG), high grade gliomas (HGG), management of the elderly patient with HGG, rare central nervous system tumors, craniospinal irradiation, and re-irradiation to examine how computational analysis and molecular science may synergistically drive advances in personalised radiation therapy (RT) and optimise patient outcomes.

Transcriptome and Metabolome Analysis Revealed the Freezing Resistance Mechanism in 60-Year-Old Overwintering Camellia sinensis

Simple Summary

The freezing stress during overwintering brings great challenges to the normal growth of Camellia sinensis. The current research on C. sinensis mainly focuses on cold resistance, but less on freezing resistance. In the present study, the transcriptome and metabolome of C. sinensis under freezing stress were studied. Results showed that Pyr/PYL-PP2C-SnRK2 played a critical role in the signal transduction of freezing stress. Three metabolic pathways including phenylpropanoid biosynthesis, flavone and flavonol biosynthesis, and flavonoid biosynthesis contributed to the freezing resistance of C. sinensis. This study provides substantial insights for the breeding of C. sinensis.

Abstract

Freezing stress in winter is the biggest obstacle to the survival of C. sinensis in mid-latitude and high-latitude areas, which has a great impact on the yield, quality, and even life of C. sinensis every year. In this study, transcriptome and metabolome were used to clarify the freezing resistance mechanism of 60-year-old natural overwintering C. sinensis under freezing stress. Next, 3880 DEGs and 353 DAMs were obtained. The enrichment analysis showed that pathways of MAPK and ABA played a key role in the signal transduction of freezing stress, and Pyr/PYL-PP2C-SnRK2 in the ABA pathway promoted stomatal closure. Then, the water holding capacity and the freezing resistance of C. sinensis were improved. The pathway analysis showed that DEGs and DAMs were significantly enriched and up-regulated in the three-related pathways of phenylpropanoid biosynthesis, flavone and flavonol biosynthesis, and flavonoid biosynthesis. In addition, the carbohydrate and fatty acid synthesis pathways also had a significant enrichment, and the synthesis of these substances facilitated the freezing resistance. These results are of great significance to elucidate the freezing resistance mechanism and the freezing resistance breeding of C. sinensis.