[Congenital ectrodactyly caused by chromosome 10q24.31 duplication and its pathogenetic analysis].

In order to investigate the genetic variations and the clinical manifestations of a range of congenital ectrodactyly family and to summarize the split hand/foot malformation (SHFM) types and their related pathogenic genes, we conducted phenotypic analyses of patient's limbs by physical and X-ray examination. The haplotypes were analyzed by using the extracted genes from peripheral blood on D10S1709, D10S192, D10S597, D10S1693 and D10S587 loci, and the mutation duplication loci were confirmed by Array-CGH detection. The pathogenic factors and inheritance pattern of SHFM were analyzed based on family investigation and gene analysis. Results demonstrate the proband's phenotype is typically of a congenital SHFM which is manifested by missing bilateral index and middle fingers, short bilateral thumbs, deformed left ring finger with webbing of the skin missing at the middle finger; bilateral big toe with the second and the third toe missing, fourth and fifth toe fusion leading to a deformed toe separated from the first toe by the middle of the foot. The haplotype analyses show that there is a repeat of at least 610 kb in chromosome 10q24.31-10q24.32 region. Array-CGH analysis shows 10q24.31 (102 832 650-103 511 083) ×3. Our results demonstrate that the pathogenic gene variation of ectrodactyly in this family is due to duplication of 10q24.31 (102 832 650~103 511 083). The haplotype 165-251-289-219-102 can be used as a disease marker for detecting 10q24.31~10q24.32 allele for SHFM.

Ahypoxia-related signature enhances the prediction of the prognosis in hepatocellular carcinoma patients and correlates with sorafenib treatment response.

Hepatocellular carcinoma (HCC) is one of the leading cancer death and is the primary malignancy of the liver. Tumor hypoxia is the stressor that is involved in tumorigenesis and significantly increased the aggressiveness of HCC. Here, we systematically analyzed the expression profiles and prognostic values of 84 hypoxia associated genes in HCC. mRNA expression of 84 hypoxia associated genes and clinical parameters of HCC patients were downloaded from TCGA, GSE14520, GSE109211 and ICGC. Consensus clustering analysis was performed for unsupervised classes on the basis of 84 hypoxia associated genes. Univariate and LASSO analysis were used to develop the risk signature. A risk signature was developed, including the expression of APEX1, ATR, CTSA, DNAJC5, ENO1, EPO, HMOX1, LDHA, NDRG1, and PER1, and found to be significantly related with OS and DFS of HCC patients. We stratified HCC patients into the high-risk group and low-risk group by means of the risk signature. Patients of high-risk group had shorter OS and DFS, while that of the low-risk group had longer OS and DFS. The risk signature showed better predictive efficiency than the TNM staging in predicting OS and DFS. Also, macrophage M0 cells, regulatory T cells, and neutrophils were found to be significantly enriched in patients of high-risk group. Next, we validated the discrimination and prognostic value of the risk signature in GSE14520 and the ICGC HCC cohort. Finally, significantly lower risk scores were found in sorafenib treatment responders of GSE109211 cohort, and the AUC for predicting sorafenib treatment response was 0.881. In conclusion, a risk signature developed with the expression of 10 hypoxia associated genes improved the prognosis prediction of HCC and correlated with sorafenib treatment response.

14-CpG-Based Signature Improves the Prognosis Prediction of Hepatocellular Carcinoma Patients.

BACKGROUND: Epigenetic dysregulation via alteration of DNA methylation often occurs during the development and progression of cancer, including hepatocellular carcinoma (HCC). In the past, many patterns of single-gene DNA methylation have been extensively explored in the context of HCC prognosis prediction. However, the combined model of a mixture of CpGs has rarely been evaluated. In the present study, we aimed to develop and validate a CpG-based signature model for HCC patient prognosis. METHODS: Data from methylation profiling of GSE73003, GSE37988, and GSE57958 from the Gene Expression Omnibus (GEO) database and 371 HCC patients from the Cancer Genome Atlas (TCGA) were downloaded. The 371 HCC patients were randomly divided into a development cohort (N = 263) and a validation cohort (N = 263) and a validation cohort (. RESULTS: Fourteen differential CpGs associated with OS were identified in HCC patients. The MSH, based on these 14 differential CpGs, could effectively divide HCC patients into two distinct subgroups with high risk or low risk of death (P < 0.0001) in the development cohort (26.35 vs 83.18 months, HR = 3.83, 95% CI: 2.56-5.90, P < 0.0001) in the development cohort (26.35 vs 83.18 months, HR = 3.83, 95% CI: 2.56-5.90, P < 0.0001) in the development cohort (26.35 vs 83.18 months, HR = 3.83, 95% CI: 2.56-5.90. CONCLUSION: The 14-CpG-based signature is significantly associated with OS and may be used as a novel prognostic biomarker for HCC patients.

Effects of interactions between environmental factors and KIF1B genetic variants on the risk of hepatocellular carcinoma in a Chinese cohort.

AIM: To examine the effect of the potential interaction between KIF1B variants (rs17401966 and rs3748578) and environmental factors on the risk of hepatocellular carcinoma (HCC) in a high-risk region in China. METHODS: Three hundred and six patients with HCC and 306 hospital-based control participants residing in the Shunde region of Guangdong Province, China were enrolled. Clinical characteristics were collected by reviewing the complete medical histories from the patient archives, and epidemiological data were collected using a questionnaire and clinical examination. Two single nucleotide polymorphisms (SNPs) of KIF1B (rs17401966 and rs3748578) were chosen for the current study. All subjects were genotyped using a TaqMan real-time polymerase chain reaction. Multiplicative and additive logistic regression models were used to evaluate various gene-environment interactions. RESULTS: Smoking, frequent consumption of raw freshwater fish, hepatitis B virus (HBV) infection, and a family history of HCC were important risk factors for HCC in this population. Chronic infection with HBV was the most important environmental risk factor for HCC [odds ratio (OR) = 12.02; 95% confidence interval (95%CI): 6.02-24.00]. No significant association was found between the KIF1B variants alone and the risk of HCC. Nevertheless, a significant additive effect modification was observed between rs17401966 and alcohol consumption (P for additive interaction = 0.0382). Compared with non-drinkers carrying either the AG or GG genotype of rs17401966, individuals classified as alcohol consumers with the AA genotype of rs17401966 had a significantly increased risk of HCC (OR = 2.36; 95%CI: 1.49-3.74). CONCLUSION: The gene-environment interaction between the KIF1B rs17401966 variant and alcohol consumption may contribute to the development of HCC in Chinese individuals.