Profile of gene expression related to glycolysis serves as a new prognosis risk predictor for human hepatocellular carcinoma
Metabolic pattern reconstruction is an important factor in the development of tumors. Tumor cell metabolism is characterized by an increase in abnormal in anaerobic glycolysis, regardless of high oxygen concentration, resulting in significant energy accumulation of glucose sources.
These changes promote fast cell proliferation and tumor growth, which refer more to the process known as the Warburg effect. The current study reconstructs metabolic patterns in the development of cancer to identify genetic changes specifically in cancer cells. A total of 12 types of solid tumors are commonly included in the current study.
Analysis of Enrivision Set Gene (GSEA) is carried out to analyze 9 sets of glycolysis related genes, which are involved in the glycolysis process. Univariate and multivariate analysis is used to identify independent prognostic variables for nomogram construction based on clinical characteristics and glycolysis (GRGPI) gene-related prognostic index.
The prognostic model based on glycolysis genes shows a high area under the curve (AUC) in the LIHC (liver hepatocellular carcinoma). The current research findings show that 8 genes (Aurka, CDK1, CENPA, DepdC1, HMMR, KIF20A, PFKFB4, STMN1) are correlated with the overall survival (RFS) (RFS) as a whole. Further analysis shows that the prediction model is accurately distinguished between high-risk and low-risk cancer patients among patients in different groups in the LIHC.
Nomograms with calibration curves installed properly based on gene expression profiles and clinical characteristics indicate good discrimination based on internal and external cohorts. These findings indicate that changes in the level of expression of metabolic gene involved in glycolysis can contribute to the reconstruction of micro environments related to tumors.
Human genetics and their impact on cardiovascular disease
Cardiovascular disease (CVD) is the main cause of death throughout the world. Given that CVD is a highly inherited nature, researchers have tried to fully understand the genetic basis of CVD for a long time. The human genome consists of 3,100 MBP per haploid genome and a total of 6,200 MBP (diploid genomes).
However, there is a tendency of rare genetic variations to indicate the size of the effect of large effects, while general genetic variations have a small effect on disease, because of natural selection. In this case, dividing genetic variations into two groups based on allele frequencies (and effect size in the disease) is a good idea.
We know there are some important genes (especially genes relating to lipids) where genetic variations that rarely seem to be associated with the risk of CVD, while the polygenic risk score consisting of general genetic variations seems to work quite well in the general population circles.
That information can be used not only for risk stratification but also for discoveries for new pharmacological targets. In this article article, we provide an important and simple idea that human genetics is important for CVD because it is a highly inherited nature, and we believe that it will lead to precision medicine in this field.
Clinically significant findings from high-risk mutations in human SLC29A4 genes related to type 2 diabetes mellitus in the Pakistani population
This study conducts a deep analysis that combines computing and experimental verification of adverse Missense mutations associated with SLC29A4 protein. Functional annotations of a single non-synonym nucleotide polymorphism (NSSNPS), followed by analysis of functions, reveals 13 single nucleotide polymorphism (SNP) as the most destructive.
Among these, six mutants P429T / S, L144, M108V, N86H, and V79E, are predicted structurally and functionally damage the analysis of protein stability. Also, this variant is located in the evolutionary area controlled, both buried, contributing to structural damage, or open, causing functional changes in protein. This mutant is then taken for molecular docking studies.
When verified through experimental analysis, SNP M108V (RS149798710), N86H (RS151039853), and V79E (RS17854505) shows a relationship with Type 2 diabetes mellitus (T2DM). The minor allele frequency for RS149798710 (A> G) was 0.23 in control, 0.29 in Metformin respondents, 0.37 in non-respondent metformin, for RS151039853 (A> C) was 0.21 in control, 0.28 In Metformin respondents, 0.36 in non-respondent metformin and for RS17854505 (T> A) was 0.20 in control, 0.25 in Metformin respondents, 0.37 in non-responder metformin.
Therefore, this study concluded that SLC29A4 M108V (RS149798710), N86H (RS151039853), and V79E (RS17854505) Polymorphism was associated with an increased risk of T2DM and with an increased risk of the failure of the metformin therapy response in Pakistani T2DM patients. Communicated by Ramaswamy H. Sarma.
Changes in the pattern of methylation of tumor suppressor genes during the expanded human embryonic stem cell culture
While research on embryonic stem cells has been carried out actively, a little known about the epigenetic mechanism in human embryonic stem cells (HESCS) in the expanded cultural system. Here, we investigate whether the pattern of methylation of CPG Island (CGI) of 24 tumor suppressor genes can be maintained during expanded HESC culture. In total, 10 HESC lines were analyzed. For each cell line,
DNA genomes are extracted from the beginning and late from cell culture. CGI methylation levels from 24 tumor suppressant genes are analyzed using amplification of organizers depending on methylated multiplex (MS-MLPA), pyrosequencing, and real-time polymerase chain reactions (PCR). The different CGI methylation pattern of CASP8, FHIT, and CHFR genes is identified between the initial and end part in several HESC lines. CGI CASP8 methylation levels increased significantly in the final hallway on the Cha-36 cell line,
CHA-40, and CHA-42 compared to those in the initial passage. CGI methylation The FHIT gene is higher in the final hallway than in the initial verse in the Cha-15 line, Cha-31, Cha-32, and IPS (FS) -1 lines but decreases in the final hallway in Cha-20 and H1. Cell line. Different CGI methylation patterns detected for CHFR genes only in IPS (FS) -1, and the level increases significantly on smoothly. Thus, our findings indicate that the CGI methylation pattern can be changed during prolonged ESC culture and examining these epigenetic changes is important to assess maintenance, differentiation, and clinical use of stem cells.