AIM: In hepatocellular carcinoma (HCC) prevalent areas of China, the point mutation of p53 exon7 is highly correlated with Hepatitis B virus(HBV) infection and aflatoxin B intake. While in non-HCC-prevalent areas of C...AIM: In hepatocellular carcinoma (HCC) prevalent areas of China, the point mutation of p53 exon7 is highly correlated with Hepatitis B virus(HBV) infection and aflatoxin B intake. While in non-HCC-prevalent areas of China, these factors are not so important in the etiology of HCC. Therefore, the point mutation of p53 exon7 may also be different than that in HCC-prevalent areas of China. The aim of this study is to investigate the status and carcinogenic role of the point mutation of p53 gene exon7 in hepatocellular carcinoma from Anhui Province, a non-HCC-prevalent area in China. METHODS: PCR PCR-SSCP and PCR-RFLP were applied to analyze the homozygous deletion and point mutation of p53 exon7 in HCC samples from Anhui, which were confirmed by DNA sequencing and Genbank comparison. RESULTS: In the 38 samples of hepatocellular carcinoma, no homozygous deletion of p53 exon7 was detected and point mutations of p53 exon7 were found in 4 cases, which were found to be heterozygous mutation of codon 249 with a mutation rate of 10.53%(4/38). The third base mutation(G-T) of p53 codon 249 was found by DNA sequencing and Genbank comparison. CONCLUSION: The incidence of point mutation of p53 codon 249 is lower in hepatocellular carcinoma and the heterozygous mutation of p53 exon7 found in these patients only indicate that they have genetic susceptibility to HCC. p53 codon 249 is a hotspot of p53 exon7 point mutation, suggesting that the point mutation of p53 exon 7 may not play a major role in the carcinogenesis of HCC in Anhui Province, a non-HCC-prevalent area in China.展开更多
Background： Since the invention of next-generation RNA sequencing （RNA-seq） technologies, they have become a powerful tool to study the presence and quantity of RNA molecules in biological samples and have revoluti...Background： Since the invention of next-generation RNA sequencing （RNA-seq） technologies, they have become a powerful tool to study the presence and quantity of RNA molecules in biological samples and have revolutionized transcriptomic studies. The analysis of RNA-seq data at four different levels （samples, genes, transcripts, and exons） involve multiple statistical and computational questions, some of which remain challenging up to date. Results： We review RNA-seq analysis tools at the sample, gene, transcript, and exon levels from a statistical perspective. We also highlight the biological and statistical questions of most practical considerations. Conclusions： The development of statistical and computational methods for analyzing RNA-seq data has made significant advances in the past decade. However, methods developed to answer the same biological question often rely on diverse statistical models and exhibit different performance under different scenarios. This review discusses and compares multiple commonly used statistical models regarding their assumptions, in the hope of helping users select appropriate methods as needed, as well as assisting developers for future method development.展开更多
基金the Natural Science Foundation of Anhui Province,No.99044312(WY) and No.9741006(LX)Natural Science Foundation of Anhui Educational Commission,No.JL-97-077(WY).
文摘AIM: In hepatocellular carcinoma (HCC) prevalent areas of China, the point mutation of p53 exon7 is highly correlated with Hepatitis B virus(HBV) infection and aflatoxin B intake. While in non-HCC-prevalent areas of China, these factors are not so important in the etiology of HCC. Therefore, the point mutation of p53 exon7 may also be different than that in HCC-prevalent areas of China. The aim of this study is to investigate the status and carcinogenic role of the point mutation of p53 gene exon7 in hepatocellular carcinoma from Anhui Province, a non-HCC-prevalent area in China. METHODS: PCR PCR-SSCP and PCR-RFLP were applied to analyze the homozygous deletion and point mutation of p53 exon7 in HCC samples from Anhui, which were confirmed by DNA sequencing and Genbank comparison. RESULTS: In the 38 samples of hepatocellular carcinoma, no homozygous deletion of p53 exon7 was detected and point mutations of p53 exon7 were found in 4 cases, which were found to be heterozygous mutation of codon 249 with a mutation rate of 10.53%(4/38). The third base mutation(G-T) of p53 codon 249 was found by DNA sequencing and Genbank comparison. CONCLUSION: The incidence of point mutation of p53 codon 249 is lower in hepatocellular carcinoma and the heterozygous mutation of p53 exon7 found in these patients only indicate that they have genetic susceptibility to HCC. p53 codon 249 is a hotspot of p53 exon7 point mutation, suggesting that the point mutation of p53 exon 7 may not play a major role in the carcinogenesis of HCC in Anhui Province, a non-HCC-prevalent area in China.
文摘Background： Since the invention of next-generation RNA sequencing （RNA-seq） technologies, they have become a powerful tool to study the presence and quantity of RNA molecules in biological samples and have revolutionized transcriptomic studies. The analysis of RNA-seq data at four different levels （samples, genes, transcripts, and exons） involve multiple statistical and computational questions, some of which remain challenging up to date. Results： We review RNA-seq analysis tools at the sample, gene, transcript, and exon levels from a statistical perspective. We also highlight the biological and statistical questions of most practical considerations. Conclusions： The development of statistical and computational methods for analyzing RNA-seq data has made significant advances in the past decade. However, methods developed to answer the same biological question often rely on diverse statistical models and exhibit different performance under different scenarios. This review discusses and compares multiple commonly used statistical models regarding their assumptions, in the hope of helping users select appropriate methods as needed, as well as assisting developers for future method development.
