Impact of AKAP6 polymorphisms on Glioma susceptibility and prognosis

Treatments against Polymorphosal discrepancies in Glioblastoma Multiforme

Glioblastoma (GB) are aggressive tumors that obstruct normal brain function. While the skull cannot expand in response to cancer growth, the growing pressure in the brain is generally the first sign. It can produce more frequent headaches, unexplained nausea or vomiting, blurred peripheral vision, double vision, a loss of feeling or movement in an arm or leg, and difficulty speaking and concentrating; all depend on the tumor's location. GB can also cause vascular thrombi, damaging endothelial cells and leading to red blood cell leakage. Latest studies have revealed the role of single nucleotide polymorphisms (SNPs) in developing and spreading cancers such as GB and breast cancer. Many discovered SNPs are associated with GB, particularly in great abundance in the promoter region, creating polygenetic vulnerability to glioma. This study aims to compile a list of some of the most frequent and significant SNPs implicated with GB formation and proliferation.

Patient-derived organoids for personalized gallbladder cancer modelling and drug screening

BACKGROUND

Gallbladder carcinoma (GBC) is a relatively rare but highly aggressive cancer with late clinical detection and a poor prognosis. However, the lack of models with features consistent with human gallbladder tumours has hindered progress in pathogenic mechanisms and therapies.

METHODS

We established organoid lines derived from human GBC as well as normal gallbladder and benign gallbladder adenoma (GBA) tissues. The histopathology signatures of organoid cultures were identified by H&E staining, immunohistochemistry and immunofluorescence. The genetic and transcriptional features of organoids were analysed by whole-exome sequencing and RNA sequencing. A set of compounds targeting the most active signalling pathways in GBCs were screened for their ability to suppress GBC organoids. The antitumour effects of candidate compounds, CUDC-101 and CUDC-907, were evaluated in vitro and in vivo.

RESULTS

The established organoids were cultured stably for more than 6 months and closely recapitulated the histopathology, genetic and transcriptional features, and intratumour heterogeneity of the primary tissues at the single-cell level. Notably, expression profiling analysis of the organoids revealed a set of genes that varied across the three subtypes and thus may participate in the malignant progression of gallbladder diseases. More importantly, we found that the dual PI3K/HDAC inhibitor CUDC-907 significantly restrained the growth of various GBC organoids with minimal toxicity to normal gallbladder organoids.

CONCLUSIONS

Patient-derived organoids are potentially a useful platform to explore molecular pathogenesis of gallbladder tumours and discover personalized drugs.

A meta-analysis of XRCC1 single nucleotide polymorphism and susceptibility to gynecological malignancies

BACKGROUND

Gynecological malignant tumor is a serious threat to women's health, cervical cancer, endometrial cancer and ovarian cancer are the most common. The eponymous protein encoded by the XRCC1 (X-ray repair cross complementation 1) gene is an important functional protein in the process of single-stranded DNA damage. Non-synonymous mutations of XRCC1 gene cause amino acid sequence changes that affect protein function and DNA repair ability, and may affect the interaction with other DNA repair proteins, leading to increased risk of tumor development. Many studies have assessed the association between XRCC1 gene polymorphism and the risk of cancer in the female reproductive system, but the results have been inconclusive. In this study, the relationship between XRCC1 Arg399Gln, Arg194Trp, Arg280His single nucleotide polymorphisms and susceptibility to gynecological malignancies was further explored by meta-analysis.

METHODS

English database: Pubmed, Medline, Excerpta Medica Database, Cochrance, etc; Chinese database: China national knowledge infrastructure, Wanfang Database, etc. STATA14 was used for statistical analysis, such as odd ratio (OR) value, subgroup analysis, heterogeneity test, sensitivity analysis, and publication bias.

RESULTS

In gynecologic cancers, the allele frequency difference of Arg399Gln case control group was statistically significant (GvsA: P = .007). There was no significant difference in allele frequency in the Arg194Trp and Arg280His case control groups (P = .065, 0.198). In different gene models, Arg399Gln was significantly correlated with gynecologic cancers susceptibility (GGvs AA: OR 0.91; 95% confidence interval [CI], 0.85 0.98); Arg194Trp was significantly correlated with gynecologic cancers susceptibility (CCvs TT: OR 0.94; 95% CI 0.88,1.00; CCvs CT: OR 0.97; 95% CI 0.90, 1.05); Arg280His was significantly correlated with gynecologic cancers susceptibility (GGvs AA: OR 0.98; 95% CI 0.94, 1.02; GGvs GA: OR 1.00;95% CI 0.97, 1.04). In the subgroup analysis, Arg399Gln and Arg194Trp were significantly correlated with gynecologic cancers susceptibility in the Asian race (P = .000, 0.049). In the analysis of different cancer subgroups, Arg399Gln and cervical cancer susceptibility were statistically significant (P = .039). Arg194Trp and endometrial cancer susceptibility were statistically significant (P = .033, 0.001).

CONCLUSIONS

XRCC1 Arg399Gln, Arg194Trp, Arg280His single nucleotide polymorphisms were associated with gynecologic cancer susceptibility. Arg399Gln genotype was statistically significant in relation to cervical cancer susceptibility. Arg194Trp genotype was statistically significant in relation to endometrial cancer susceptibility.

Regulatory roles of phytochemicals on circular RNAs in cancer and other chronic diseases

As novel non-coding RNAs (ncRNAs), circular RNAs (circRNAs) play an essential role in the pathogenesis of many chronic diseases, and the regulation of these functional molecules has become a research hotspot gradually. Within the past decade, phytochemicals were reported to regulate the expression of long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) in various chronic diseases, and more recently, most studies focus on the regulatory roles of phytochemicals on circRNAs. Abnormal expression of circRNAs has been identified in chronic diseases like cancer, heart failure, depression and atherosclerosis, and numerous studies have revealed the modulation of circRNAs by phytochemicals including berberine, celastrol, cinnamaldehyde, curcumin, et al. The expression of circRNAs, such as circSATB2 and circFOXM1, were modulated by phytochemicals, and these regulations further affected cell proliferation, apoptosis, migration, invasion, autophagy, chemosensitivity, radiosensitivity and other biological processes. Mechanismly, the circRNAs mainly functioned as miRNA sponge, subsequently affecting miRNA-mediated regulation of target genes and related cell signaling pathways. In this review, we summarized the impact of phytochemicals on circRNAs expression and biological function, and discussed the mechanisms underlying phytochemicals regulating circRNAs in cancer and other chronic diseases.

Making Sense of Genetic Information: The Promising Evolution of Clinical Stratification and Precision Oncology Using Machine Learning

Precision medicine is a medical approach to administer patients with a tailored dose of treatment by taking into consideration a person's variability in genes, environment, and lifestyles. The accumulation of omics big sequence data led to the development of various genetic databases on which clinical stratification of high-risk populations may be conducted. In addition, because cancers are generally caused by tumor-specific mutations, large-scale systematic identification of single nucleotide polymorphisms (SNPs) in various tumors has propelled significant progress of tailored treatments of tumors (i.e., precision oncology). Machine learning (ML), a subfield of artificial intelligence in which computers learn through experience, has a great potential to be used in precision oncology chiefly to help physicians make diagnostic decisions based on tumor images. A promising venue of ML in precision oncology is the integration of all available data from images to multi-omics big data for the holistic care of patients and high-risk healthy subjects. In this review, we provide a focused overview of precision oncology and ML with attention to breast cancer and glioma as well as the Bayesian networks that have the flexibility and the ability to work with incomplete information. We also introduce some state-of-the-art attempts to use and incorporate ML and genetic information in precision oncology.

Association of ST6GAL1 and CYP19A1 polymorphisms in the 3'-UTR with astrocytoma risk and prognosis in a Chinese Han population

Background

Astrocytoma is a common type of central nervous system tumor. In this study, we investigated the correlation between ST6GAL1 and CYP19A1 polymorphisms and the risk and prognosis of astrocytoma.

Methods

A total of 365 astrocytoma patients and 379 healthy controls were genotyped using the Agena MassARRAY system. The correlation between ST6GAL1 and CYP19A1 variants and astrocytoma risk was calculated using logistic regression. The survival rate of patients with astrocytoma was analyzed to evaluate prognosis.

Results

We found that the ST6GAL1-rs2239611 significantly decreased the risk of astrocytoma in the codominant model (p = 0.044) and dominant model (p = 0.049). In stratified analyses, CYP19A1-rs2255192 might be associated with a higher risk of astrocytoma among the low-grade subgroup under recessive (p = 0.034) and additive (p = 0.030) models. However, CYP19A1-rs4646 had a risk-decreasing effect on the high-grade subgroup in the codominant model (p = 0.044). The results of Cox regression analysis showed that the CYP19A1-rs2239611 and -rs1042757 polymorphisms were significantly correlated with the prognosis of astrocytoma.

Conclusion

Our results suggest that ST6GAL1 and CYP19A1 genes may be a potential biomarker of genetic susceptibility and prognosis to astrocytoma in the Chinese Han population.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08110-1.

The essential role of long non-coding RNA GAS5 in glioma: interaction with microRNAs, chemosensitivity and potential as a biomarker

Glioma is a malignant brain tumor with a generally poor prognosis. Dysregulation of a long non-coding RNA, GAS5, has been detected in numerous cancers, including glioma. Previous studies have suggested that GAS5 plays a significant functional role in glioma, affecting proliferation, metastasis, invasion, and apoptosis. In this review, we describe the roles and mechanisms of GAS5 in glioma. GAS5 may be a biomarker for diagnosis and prognosis, and even a potential target for glioma treatment, and therefore warrants further investigation.

Drugs That Regulate Local Cell Signaling: AKAP Targeting as a Therapeutic Option

Cells respond to environmental cues by mobilizing signal transduction cascades that engage protein kinases and phosphoprotein phosphatases. Correct organization of these enzymes in space and time enables the efficient and precise transmission of chemical signals. The cyclic AMP-dependent protein kinase A is compartmentalized through its association with A-kinase anchoring proteins (AKAPs). AKAPs are a family of multivalent scaffolds that constrain signaling enzymes and effectors at subcellular locations to drive essential physiological events. More recently, it has been recognized that defective signaling in certain endocrine disorders and cancers proceeds through pathological AKAP complexes. Consequently, pharmacologically targeting these macromolecular complexes unlocks new therapeutic opportunities for a growing number of clinical indications. This review highlights recent findings on AKAP signaling in disease, particularly in certain cancers, and offers an overview of peptides and small molecules that locally regulate AKAP-binding partners.

Computational identification and characterization of glioma candidate biomarkers through multi-omics integrative profiling

BACKGROUND

Glioma is one of the most common malignant brain tumors and exhibits low resection rate and high recurrence risk. Although a large number of glioma studies powered by high-throughput sequencing technologies have led to massive multi-omics datasets, there lacks of comprehensive integration of glioma datasets for uncovering candidate biomarker genes.

RESULTS

In this study, we collected a large-scale assemble of multi-omics multi-cohort datasets from worldwide public resources, involving a total of 16,939 samples across 19 independent studies. Through comprehensive molecular profiling across different datasets, we revealed that PRKCG (Protein Kinase C Gamma), a brain-specific gene detectable in cerebrospinal fluid, is closely associated with glioma. Specifically, it presents lower expression and higher methylation in glioma samples compared with normal samples. PRKCG expression/methylation change from high to low is indicative of glioma progression from low-grade to high-grade and high RNA expression is suggestive of good survival. Importantly, PRKCG in combination with MGMT is effective to predict survival outcomes in a more precise manner.

CONCLUSIONS

PRKCG bears the great potential for glioma diagnosis, prognosis and therapy, and PRKCG-like genes may represent a set of important genes associated with different molecular mechanisms in glioma tumorigenesis. Our study indicates the importance of computational integrative multi-omics data analysis and represents a data-driven scheme toward precision tumor subtyping and accurate personalized healthcare.