Human Gene最新文献

Despite the improvements in diagnostic and therapeutic techniques, heterogeneous constitution and non-invasive diagnosis remain major clinical challenges for brain tumors. In such a context, liquid biopsy is a noninvasive method that analyses tumor-derived biomarkers in body fluids and thus appears quite promising. This review explores the potential for circulating tumor cells, circulating tumor DNA, microRNAs, proteins, and exosomes as liquid biopsy markers in brain tumors. Although such biomarkers have potential for early detection, monitoring of disease progression, and guiding therapy, the limitations in the form of low levels of biomarkers and analytical complexities persist. Artificial intelligence integrated with liquid biopsy can therefore be expected to improve diagnostic accuracy and clinical utility. Further research, standardization, and clinical validation are needed to exploit the full potential of liquid biopsy in brain tumor management.

Colorectal cancer (CRC) is the second in mortality among cancers with high incidence worldwide. About 5 % of patients had a previous oncopathology and 20 % develop a second malignancy. CRC molecular genetic mechanisms in primary multiple cancers (MPCs) are not fully understood. This study aimed to investigate mutational characteristics of primary CRC compared to MPCs with colorectal component. 336 CRC patients and 52 MPCs patients with a colorectal component (C97CRC) (TCGA-COAD data) were included. Comparative bioinformatics analysis of genetic mutations, their interactions, effect on signaling pathways, survival rate, and druggable categories was conducted. CRC was characterized by PIK3CA and APC mutations, while 17 mutations in other genes were identified in C97CRC. In CRC group, co-occurring somatic variants in TP53/APC and KRAS/APC were the most common, while in C97CRC, KRAS/SOX9 was specifically found. TP53/SYNE1, TP53/MUC16, and TP53/TTN mutational combinations were associated with a decreased survival rate in CRC group. Collagen type VI α3-chain protease and its inhibitor were suggested as specific druggable targets in C97CRC group. The differences in mutational profiles between groups may indicate evolutionary features of CRC as a primary and secondary malignancy. Described druggable categories open up prospects for treatment development of CRC and MPCs with a colorectal component.

Single Nucleotide Polymorphisms (SNPs) are abundantly identified by next generation sequencing (NGS) technology. Glycogen synthase kinase-3 beta (GSK3B), a widely expressed protein kinase, plays pivotal roles in cellular pathways. However, study on SNPs associated with GSK3B and their functional consequences is lacking. In this study, we analysed non-synonymous SNPs of GSK3B gene and their implications using computational tools. From NCBI dbSNP, 103,087 SNPs of GSK3B were initially gathered, later narrowed down to 255 unique nsSNPs. Around one-third of the nsSNPs resulted in charge and polarity change of the amino acids of the protein. 41 nsSNPs were found to significantly alter the stability of GSK3B protein (ΔΔG ≤ -1 or ≥ 1 kcal/mol) and few of them also affected the disorderness at the mutation site. Evolutionary conservation of the nsSNPs in the protein revealed 25 nsSNP may be deleterious to GSK3B protein function. Finally, 4 critical nsSNPs (Y161C, R167G, P225L and Y234D) were identified that can significantly alter both the stability and function of GSK3B. Furthermore, this study predicted 60 post-translational modification sites in GSK3B among which 26 sites contained nsSNPs. Interestingly, 7 upstream ORFs (uORFs) with high ribosomal occupancy were also detected in GSK3B mRNA that can reduce the expression of GSK3B protein. Altogether, this study has employed various in silico methods to characterize GSK3B nsSNPs, but they have limitations. These tools often overlook the cellular context, interacting partners, PTMs and the dynamic nature of proteins, which can affect protein behaviour and function. Despite these limitations, in silico tools are valuable for initial screening and prioritizing SNPs. The prioritized SNPs obtained in this study (Y161C, R167G, P225L and Y234D) should be experimentally validated using techniques like genome editing, biochemical assays, interactome analysis in cell lines and animal models to confirm their biological relevance.

Clinical trial registration: Not Applicable.

Background

Deafness is a prevalent sensory and neurological disorder that impacts over 466 million individuals globally. Congenital deafness is the most prevalent birth defect, occurring in approximately 2–3 out of every 1000 births. It is recognized as a highly diverse condition. >50% of congenital deafness has genetic causes and the rest is due to environmental causes or both. With the development of next-generation sequencing and bioinformatics tools, whole-exome sequencing has been proposed as one of the effective methods for diagnosing genetics of hearing loss.

Method

Five Iranian Autosomal recessive non-syndromic hearing loss (ARNSHL) families negative for GJB2 (NM_004004.6) gene mutations from Sistan and Baluchestan province were selected for further study by whole-exome sequencing analysis. The analysis procedure was performed using multiple bioinformatics tools and websites after filling the consent form and extracting DNA from whole blood using the salting out method. After detecting the variants in priority and confirming them in the probands by Sanger sequencing, other family members were studied to confirm the variant within the family.

Results

After analyzing the families recruited for this study, four known genes along with known and novel variants were discovered. Mutations found in the MYO15A, SLC26A4, TRIOBP and TECTA genes among which, the variants found in TRIOBP (NM_001039141.3, p.R283X) and MYO15A (NM_016239.4, p.P2880Rfs*19) were novel. Other known variants were TECTA (NM_005422.4, p.W1534X) and SLC26A4 (NM_000441.2, p.V239D). No genes or variants that might contribute to hearing loss have been identified within one of the families.

Conclusion

Our study's findings support previous research that has identified SLC26A4, MYO15A, and TECTA genes as common genetic factors following GJB2 in our population.

Atherosclerosis is a distinct risk factor for cardiovascular and cerebrovascular disorders, which are significant contributors to global mortality. It is defined by macrophage-derived foam cell development followed by persistent inflammation, plaque formation, fibrosis and thrombosis. Studies have shown valencene, a sesquiterpene obtained from Valencia oranges, has several health-promoting properties. However, its protective effect against atherosclerosis and foam cell models remains unexplored. The present investigation revealed that valencene treatment suppresses foam cell generation and accumulation of lipids in THP-1-derived cells macrophage models activated with oxidized low-density lipoprotein (ox-LDL), maintained in vitro. The intracellular lipid content was qualitatively and semi-quantitatively analyzed by Oil Red O staining, and the compound's cytotoxicity was assessed through the MTT assay, considering both time-dependent and dose-dependent factors. The RT-qPCR results showed promising anti-inflammatory and anti-oxidant enzyme status upon valencene treatment. The H2DCFDA staining revealed valencene's ability to reduce the oxidative stress induced by ox-LDL. Further, high-throughput proteomic profiling was carried out to identify the target proteins affected by valencene treatment and thereby explore its mechanism of action on foam cell models. Proteomic studies revealed that valencene treatment regulates the expression of several proteins associated with ox-LDL-induced inflammation, defective cholesterol homeostasis and cholesterol efflux pathways.

Background

Tuberculosis (TB) and sarcoidosis are chronic granulomatous diseases sharing similar symptoms, immune responses, and radiological characteristics. Transcriptome analysis offers insights into gene expression, regulation, and cellular processes, facilitating the understanding of shared molecular mechanisms.

Methods

Microarray datasets from the NCBI Gene Expression Omnibus (NCBI-GEO) were analysed to identify differentially expressed genes (DEGs) in TB and sarcoidosis compared to controls. DEGs were identified using the GEO2R tool, and subsequent functional enrichment analysis was conducted using EnrichR. Protein-protein interaction (PPI) networks, as well as gene-miRNA and transcription factor-DEG interaction networks, were constructed. In addition, pathway analysis and molecular docking of target proteins were conducted to further elucidate the biological mechanisms involved in both diseases.

Results

Fifteen genes, including ANKRD22, BATF2, DHRS9, EPSTI1, ETV7, FCGR1A, FCGR1B, GBP1, GBP5, SERPING1, NELL2, CCR7, PASK, LRRN3, and SLC16A10, were commonly altered in TB and sarcoidosis as compared to controls. Gene network analysis revealed 48.89% co-expression and 26.10% physical interaction between these overlapping genes. PPI networks showed a total of 15 nodes and 28 edges present between the connected proteins (PPI enrichment p-value:<1.0e−16). MiRNAs and transcription factors that exhibited the highest interaction with DEGs included hsa-miR-26a-5p, hsa-miR-16-5p, hsa-miR-335-5p, and EPAS1, HIF1A, KLF2, respectively. Pathway analysis indicated enrichment of IFN gamma signaling in both diseases. Molecular docking revealed weighted scores of −884.4, −851.9, and − 637.1 between three key proteins (PASK-GBP1, PASK-GBP5, and GBP1-GBP5).

Conclusion

The shared dysregulated genes in TB and sarcoidosis demonstrate notable co-expression and physical interaction, constituting a PPI network enriched in the IFN-gamma signaling pathway.

Background

Esophageal carcinoma (ESCA) and Lung adenocarcinoma (LUAD) are the prominent causes of death worldwide. There is an urgent need to identify and characterize potential biomarkers for these malignancies to enhance early cancer prognosis. Integrating computational-based early cancer detection with wet lab-based research offers a promising approach toward early-stage cancer prognosis.

Methodology

Two ESCA datasets (GSE17351, GSE23400) with 58 cancerous and 58 normal samples, along with two LUAD datasets (GSE18842, GSE74706) totaling 64 cancer samples and 63 controls, were used to identify DEGs. Visualization of DEGs was achieved using heat-maps, volcano plots, and Venn diagrams. Hub genes were predicted via PPI analysis and the cytoHubba plugin in Cytoscape. Potential hub gene expressions were evaluated with box plots, stage plots, and survival plots for prognostic assessment via GEPIA2. AutoDockVina wizard of PyRx was utilized for molecular docking to determine optimal binding interactions between proteins and hit compounds.

Findings

Sixty common DEGs were identified, focusing on significant pathways in ESCA and LUAD. The top ten hub genes (KIF4A, HMMR, CENPF, CDK1, ASPM, CDKN3, KIF2C, TTK, UBE2C, and MELK) were found to be linked to both cancers via PPI analysis. Notably, high expression of CDK1 was significantly associated with ESCA and LUAD progression, as evidenced by box plots, stage plots, and survival analysis. Upregulated expression of the targeted genes (CDK1) promotes multi-variant cancer progression that is observed by analyzing and comparing of all findings. Molecular docking with CDK1 highlighted four top compounds: Tanshinone I, Withanolide, Artemether, and Epigallocatechin, suggesting their potential as drug candidates for ESCA and LUAD treatment.

Conclusions

In conclusion, our discoveries unveil potential biomarker candidates, offer insights into ESCA and LUAD treatment strategies, and outline directions for further investigation, enriching our understanding of the pathogenesis of ESCA and LUAD.

Background: Hepatocellular carcinoma (HCC) poses a formidable global health challenge, exhibiting significant prevalence variations across diverse regions. This study delves into the potential therapeutic implications of punicalagin, a polyphenol abundant in pomegranates, for HCC. The primary objectives encompass the identification of potent molecular targets and enriched pathways influenced by punicalagin using integrated bioinformatic analysis. Materials and methods: Employing Gene Set Enrichment Analysis (GSEA), the study discerned potential differentially expressed genes (DEGs) in liver cancer. Collating information from diverse databases, including GEO2R, CTD database, and Gene Cards, revealed a set of 20 potential targets. A pharmacological network analysis was subsequently conducted using STITCH, with Cytoscape software pinpointing five highly upregulated genes within the punicalagin network such as SRC, CASP3, AKT1, IL6, and NOS3 via the cytohubba plugin. Furthermore, Gene Ontology (GO) analysis was employed to predict functional categories, unveiling key insights into the potential biological impact of punicalagin.

Results: KEGG pathway analysis demonstrated enrichment in crucial pathways such as AMPK signaling, HIF1a, and mTOR signaling, shedding light on the molecular mechanisms influenced by punicalagin. Diagnostic assessments were performed by analyzing mRNA expression levels and overall survival for the identified targets, utilizing datasets from UALCAN and GEPIA databases. Structural confirmation of punicalagin interactions with its targets was accomplished through molecular docking studies, revealing robust binding associations with biomolecules such as SRC, CASP3, AKT1, IL6, and NOS3. Experimental validation involved RT-PCR, showcasing reduced expression levels of target biomolecules such as SRC, CASP3, AKT1, IL6, and NOS3 in HepG2 cells treated with punicalagin. Conclusion: These findings underscore the potential of punicalagin as a promising therapeutic avenue for liver cancer treatment, presenting a comprehensive approach that integrates computational insights with experimental evidence.

Autism spectrum disorder (ASD) is a multifactorial and highly heterogeneous neurodevelopmental disorder. Mitochondrial dysfunction, caused by the genetic variations in the electron transport chain (ETC) complexes and marked by higher lactic acid and ammonia levels, can play a crucial role in the development of autism. This study focused on identifying genetic variants in the mitochondrial ATP6 gene of children with ASD and their association with autism disease outcome, disease severity, lactic acid and ammonia levels. Ninety children were recruited of which 53 were with autism and the remaining 37 were healthy controls. The ATP6 gene was amplified by PCR, purified, and sequenced by Sanger sequencing. In total forty-two genetic variants were identified within the gene. Among them 8886G > A and 8911 T > C were found to be associated with higher lactic acid levels and 8748C > T, 8886G > A, and 8964C > T were associated with higher ammonia levels after the adjustment with age, gender, and disease response. Additionally, all the synonymous variants were found to alter the relative synonymous codon usage (RSCU) values, potentially affecting the protein's structure and translation rate. Although there was no significant association between any ATP6 variants and disease outcomes, the variants associated with mitochondrial dysfunction as reflected by abnormal levels of lactic acid and ammonia may provide an improved understanding of the pathophysiology of ASD. Therefore they need to be explored further along with other components of the electron transport complex.

Background

One of the most common cancers worldwide is breast cancer (BC), which is influenced by genetics and environmental factors such as mammographic density. Studies suggested INHBB genetic polymorphisms as potential risk factors for breast cancer/density. Therefore, this study was conducted to validate this correlation in a cohort of the Iranian population.

Methods

Five ml of peripheral blood was collected from 200 patients and 200 healthy women. Mammographic density was determined by mammograms. rs11902591, rs4328642, and rs10183524 of the INHBB gene were genotyped using the ARMS-PCR method. Haplotype frequencies and statistical analysis were estimated using PHASE and SPSS 16.0 software, respectively.

Results

There was no association between rs1192591 and breast density, whereas this polymorphism was associated with breast cancer risk [per allele p = 0.040; OR = 0.56, 95%CI (0.32–0.97)]. Conversely, the C/T genotype of rs4328642 was significantly higher in individuals with dense breasts [p = 0.002; OR = 2.31, 95%CI (1.37–3.89)]. Furthermore, rs10183524 was statistically associated with breast density [p = 0.009; OR = 0.55, 95%CI (0.35–0.86)] and cancer risk [p = 0.031; OR = 0.52, 95%CI (0.29–0.94)]. Also, certain haplotypes and diplotypes of these markers were associated with BC risk and/or breast density.

Conclusion

According to the findings, INHBB gene polymorphisms affect cancer risk and density of the breast, and the interaction between alleles in the form of haplotypes and diplotypes may modulate the amount of the risk conferred by these variants.