Functional and structural analysis of non-synonymous single nucleotide polymorphisms (nsSNPs) in the MYB oncoproteins associated with human cancer

Computational screening of pathogenic missense nsSNPs in heme oxygenase 1 (HMOX1) gene and their structural and functional consequences

Heme Oxygenase 1 (HMOX1) is a cytoprotective enzyme, exhibiting the highest activity in the spleen, catalyzing the heme ring breakdown into products of biological significance- biliverdin, CO, and Fe2+. In vascular cells, HMOX1 possesses strong anti-apoptotic, antioxidant, anti-proliferative, anti-inflammatory, and immunomodulatory actions. The majority of these activities are crucial for the prevention of atherogenesis. Single amino acid substitutions in proteins generated by missense non-synonymous single nucleotide polymorphism (nsSNPs) in the protein-encoding regions of genes are potent enough to cause significant medical challenges due to the alteration of protein structure and function. The current study aimed at characterizing and analyzing high-risk nsSNPs associated with the human HMOX1 gene. Preliminary screening of the total available 288 missense SNPs was performed through the lens of deleteriousness and stability prediction tools. Finally, a total of seven nsSNPs (Y58D, A131T, Y134H, F166S, F167S, R183S and M186V) were found to be most deleterious by all tools that are present at highly conserved positions. Molecular dynamics simulations (MDS) analysis explained the mutational effects on the dynamic action of the wild-type and mutant proteins. In a nutshell, R183S (rs749644285) was identified as a highly detrimental mutation that could significantly render the enzymatic activity of HMOX1. The finding of this computational analysis might help subject the experimental confirmatory analysis to characterize the role of nsSNPs in HMOX1.Communicated by Ramaswamy H. Sarma.

Preliminary insights on the mutational spectrum of BRCA1 and BRCA2 genes in Pakhtun ethnicity breast cancer patients from Khyber Pakhtunkhwa (KP), Pakistan

Gene mutations are a source of genetic instability which fuels the progression of cancer. Mutations in BRCA1 and BRCA2 are considered as major drivers in the progression of breast cancer and their detection indispensable for devising therapeutic and management approaches. The current study aims to identify novel pathogenic and recurrent mutations in BRCA1 and BRCA2 in Pakhtun population from the Khyber Pakhtunkhwa. To determine the BRCA1 and BRCA2 pathogenic mutation prevalence in Pakhtun population from KP, whole exome sequencing of 19 patients along with 6 normal FFPE embedded blocks were performed. The pathogenicity of the mutations were determined and they were further correlated with different hormonal, sociogenetic and clinicopathological features. We obtained a total of 10 mutations (5 somatic and 5 germline) in BRCA1 while 27 mutations (24 somatic and 3 germline) for BRCA2. Five and seventeen pathogenic or deleterious mutations were identified in BRCA1 and BRCA2 respectively by examining the mutational spectrum through SIFT, PolyPhen-2 and Mutation Taster. Among the SNVs, BRCA1 p.P824L, BRCA2 p. P153Q, p.I180F, p.D559Y, p.G1529R, p.L1576F, p.E2229K were identified as mutations of the interaction sites as predicted by the deep algorithm based ISPRED-SEQ prediction tool. SAAFEQ-SEQ web-based algorithm was used to calculate the changes in free energy and effect of SNVs on protein stability. All SNVs were found to have a destabilizing effect on the protein. ConSurf database was used to determine the evolutionary conservation scores and nature of the mutated residues. Gromacs 4.5 was used for the molecular simulations. Ramachandran plots were generated using procheck server. STRING and GeneMania was used for prediction of the gene interactions. The highest number of mutations (BRCA1 7/10, 70 %) were on exon 9 and (BRCA2, 11/27; 40 %) were on exon 11. 40 % and 60 % of the BRCA2 mutations were associated Grade 2 and Grade 3 tumors respectively. The present study reveals unique BRCA1 and BRCA2 mutations in Pakhtun population. We further suggest sequencing of the large cohorts for further characterizing the pathogenic mutations.

From modulation of cellular plasticity to potentiation of therapeutic resistance: new and emerging roles of MYB transcription factors in human malignancies

MYB transcription factors are encoded by a large family of highly conserved genes from plants to vertebrates. There are three members of the MYB gene family in human, namely, MYB, MYBL1, and MYBL2 that encode MYB/c-MYB, MYBL1/A-MYB, and MYBL2/B-MYB, respectively. MYB was the first member to be identified as a cellular homolog of the v-myb oncogene carried by the avian myeloblastosis virus (AMV) causing leukemia in chickens. Under the normal scenario, MYB is predominantly expressed in hematopoietic tissues, colonic crypts, and neural stem cells and plays a role in maintaining the undifferentiated state of the cells. Over the years, aberrant expression of MYB genes has been reported in several malignancies and recent years have witnessed tremendous progress in understanding of their roles in processes associated with cancer development. Here, we review various MYB alterations reported in cancer along with the roles of MYB family proteins in tumor cell plasticity, therapy resistance, and other hallmarks of cancer. We also discuss studies that provide mechanistic insights into the oncogenic functions of MYB transcription factors to identify potential therapeutic vulnerabilities.

Genome-Wide Identification and Expression Analysis of the MYB Transcription Factor Family in Salvia nemorosa

The MYB transcription factor gene family is among the most extensive superfamilies of transcription factors in plants and is involved in various essential functions, such as plant growth, defense, and pigment formation. Salvia nemorosa is a perennial herb belonging to the Lamiaceae family, and S. nemorosa has various colors and high ornamental value. However, there is little known about its genome-wide MYB gene family and response to flower color formation. In this study, 142 SnMYB genes (MYB genes of S. nemorosa) were totally identified, and phylogenetic relationships, conserved motifs, gene structures, and expression profiles during flower development stages were analyzed. A phylogenetic analysis indicated that MYB proteins in S. nemorosa could be categorized into 24 subgroups, as supported by the conserved motif compositions and gene structures. Furthermore, according to their similarity with AtMYB genes associated with the control of anthocyanin production, ten SnMYB genes related to anthocyanin biosynthesis were speculated and chosen for further qRT-PCR analyses. The results indicated that five SnMYB genes (SnMYB75, SnMYB90, SnMYB6, SnMYB82, and SnMYB12) were expressed significantly differently in flower development stages. In conclusion, our study establishes the groundwork for understanding the anthocyanin biosynthesis of the SnMYB gene family and has the potential to enhance the breeding of S. nemorosa.

An Integrated Computational Analysis of High-Risk SNPs in Angiopoietin-like Proteins (ANGPTL3 and ANGPTL8) Reveals Perturbed Protein Dynamics Associated with Cancer

Angiopoietin-like proteins (ANGPTL) constitute a family of eight proteins (1-8) which play a pivotal role in the regulation of various pathophysiological processes. The current study sought to identify high-risk, "non-synonymous, single-nucleotide polymorphisms" (nsSNPs) in both ANGPTL3 and ANGPTL8 to evaluate the role that these nsSNPs play in various types of cancer. We retrieved a total of 301 nsSNPs from various databases; 79 of these candidates constitute high-risk nsSNPs. Moreover, we identified eleven high-risk nsSNPs that cause various types of cancer: seven candidates for ANGPTL3 (L57H, F295L, L309F, K329M, R332L, S348C, and G409R) and four candidates for ANGPTL8 (P23L, R85W, R138S, and E148D). Protein-protein interaction analysis revealed a strong association of ANGPTL proteins with several tumor-suppressor proteins such as ITGB3, ITGAV, and RASSF5. 'Gene-expression profiling interactive analysis' (GEPIA) showed that expression of ANGPTL3 is significantly downregulated in five cancers: sarcoma (SARC); cholangio carcinoma (CHOL); kidney chromophobe carcinoma (KICH); kidney renal clear cell carcinoma (KIRC); and kidney renal papillary cell carcinoma (KIRP). GEPIA also showed that expression of ANGPTL8 remains downregulated in three cancers: CHOL; glioblastoma (GBM); and breast invasive carcinoma (BRCA). Survival rate analysis indicated that both upregulation and downregulation of ANGPTL3 and ANGPTL8 leads to low survival rates in various types of cancer. Overall, the current study revealed that both ANGPTL3 and ANGPTL8 constitute potential prognostic biomarkers for cancer; moreover, nsSNPs in these proteins might lead to the progression of cancer. However, further in vivo investigation will be helpful to validate the role of these proteins in the biology of cancer.

Expression pattern and clinical value of Key RNA methylation modification regulators in ischemic stroke

Ischemic stroke (IS) is one of the major causes of death and disability worldwide, and effective diagnosis and treatment methods are lacking. RNA methylation, a common epigenetic modification, plays an important role in disease progression. However, little is known about the role of RNA methylation modification in the regulation of IS. The aim of this study was to investigate RNA methylation modification patterns and immune infiltration characteristics in IS through bioinformatics analysis. We downloaded gene expression profiles of control and IS model rat brain tissues from the Gene Expression Omnibus database. IS profiles were divided into two subtypes based on RNA methylation regulators, and functional enrichment analyses were conducted to determine the differentially expressed genes (DEGs) between the subtypes. Weighted gene co-expression network analysis was used to explore co-expression modules and genes based on DEGs. The IS clinical diagnosis model was successfully constructed and four IS characteristic genes (GFAP, GPNMB, FKBP9, and CHMP5) were identified, which were significantly upregulated in IS samples. Characteristic genes were verified by receiver operating characteristic curve and real-time quantitative PCR analyses. The correlation between characteristic genes and infiltrating immune cells was determined by correlation analysis. Furthermore, GPNMB was screened using the protein-protein interaction network, and its regulatory network and the potential therapeutic drug chloroquine were predicted. Our finding describes the expression pattern and clinical value of key RNA methylation modification regulators in IS and novel diagnostic and therapeutic targets of IS from a new perspective.

In-Silico Analysis of Deleterious SNPs of FGF4 Gene and Their Impacts on Protein Structure, Function and Bladder Cancer Prognosis

Dysregulation of fibroblast growth factors is linked to the pathogenesis of bladder cancer. The role of FGF1 and FGF3 is evident in bladder cancer; however, the role of FGF4 is vague. Despite being reported that FGF4 interacts with FGF1 and FGF3 in MAPK pathways, its pathogenesis and mechanism of action are yet to be elucidated. Therefore, this study aimed to elucidate pathogenic nsSNPs and their role in the prognosis of bladder cancer by employing in-silico analysis. The nsSNPs of FGF4 were retrieved from the NCBI database. Different in silico tools, PROVEAN, SIFT, PolyPhen-2, SNPs&GO, and PhD-SNP, were used for predicting the pathogenicity of the nsSNPs. Twenty-seven nsSNPs were identified as “damaging”, and further stability analysis using I-Mutant 2.0 and MUPro indicated 22 nsSNPs to cause decreased stability (DDG scores < −0.5). Conservation analysis predicted that Q97K, G106V, N164S, and N167S were highly conserved and exposed. Biophysical characterisation indicated these nsSNPs were not tolerated, and protein-protein interaction analysis showed their involvement in the GFR-MAPK signalling pathway. Furthermore, Kaplan Meier bioinformatics analyses indicated that the FGF4 gene deregulation affected the overall survival rate of patients with bladder cancer, leading to prognostic significance. Thus, based on these analyses, our study suggests that the reported nsSNPs of FGF4 may serve as potential targets for diagnoses and therapeutic interventions focusing on bladder cancer.