Prostate cancer （PCa） is one of the most common malignancies in the world with over 890 000 cases and over 258 000 deaths worldwide each year. Nearly all mortalities from PCa are due to metastatic disease, typically...Prostate cancer （PCa） is one of the most common malignancies in the world with over 890 000 cases and over 258 000 deaths worldwide each year. Nearly all mortalities from PCa are due to metastatic disease, typically through tumors that evolve to be hormone-refractory or castrate-resistant. Despite intensive epidemiological study, there are few known environmental risk factors, and age and family history are the major determinants. However, there is extreme heterogeneity in PCa incidence worldwide, suggesting that major determining factors have not been described. Genome-wide association studies have been performed and a considerable number of significant, but low-risk loci have been identified. In addition, several groups have analyzed PCa by determination of genomic copy number, fusion gene generation and targeted resequencing of candidate genes, as well as exome and whole genome sequencing. These initial studies have examined both primary and metastatic tumors as well as murine xenografts and identified somatic alterations in TP53and other potential driver genes, and the disturbance of androgen response and cell cycle pathways. It is hoped that continued characterization of risk factors as well as gene mutation and misregulation in tumors will aid in understanding, diagnosing and better treating PCa.展开更多
Single-cell genomics provides substantial resources for dissecting cellular heterogeneity and cancer evolution.Unfortunately,classical DNA amplification-based methods have low throughput and introduce coverage bias du...Single-cell genomics provides substantial resources for dissecting cellular heterogeneity and cancer evolution.Unfortunately,classical DNA amplification-based methods have low throughput and introduce coverage bias during sample preamplification.We developed a single-cell DNA library preparation method without preamplification in nanolitre scale(scDPN)to address these issues.The method achieved a throughput of up to 1800 cells per run for copy number variation(CNV)detection.Also,our approach demonstrated a lower level of amplification bias and noise than the multiple displacement amplification(MDA)method and showed high sensitivity and accuracy for cell line and tumor tissue evaluation.We used this approach to profile the tumor clones in paired primary and relapsed tumor samples of hepatocellular carcinoma(HCC).We identified three clonal subpopulations with a multitude of aneuploid alterations across the genome.Furthermore,we observed that a minor clone of the primary tumor containing additional alterations in chromosomes 1q,10q,and 14q developed into the dominant clone in the recurrent tumor,indicating clonal selection during recurrence in HCC.Overall,this approach provides a comprehensive and scalable solution to understand genome heterogeneity and evolution.展开更多
文摘Prostate cancer （PCa） is one of the most common malignancies in the world with over 890 000 cases and over 258 000 deaths worldwide each year. Nearly all mortalities from PCa are due to metastatic disease, typically through tumors that evolve to be hormone-refractory or castrate-resistant. Despite intensive epidemiological study, there are few known environmental risk factors, and age and family history are the major determinants. However, there is extreme heterogeneity in PCa incidence worldwide, suggesting that major determining factors have not been described. Genome-wide association studies have been performed and a considerable number of significant, but low-risk loci have been identified. In addition, several groups have analyzed PCa by determination of genomic copy number, fusion gene generation and targeted resequencing of candidate genes, as well as exome and whole genome sequencing. These initial studies have examined both primary and metastatic tumors as well as murine xenografts and identified somatic alterations in TP53and other potential driver genes, and the disturbance of androgen response and cell cycle pathways. It is hoped that continued characterization of risk factors as well as gene mutation and misregulation in tumors will aid in understanding, diagnosing and better treating PCa.
基金This work was supported by the Technology and Innovation Commission of Shenzhen Municipality,China(Grant No.GJHZ20180419190827179)the Science,Technology and Innovation Commission of Shenzhen Municipality,China(Grant No.JCYJ20170303151334808).
文摘Single-cell genomics provides substantial resources for dissecting cellular heterogeneity and cancer evolution.Unfortunately,classical DNA amplification-based methods have low throughput and introduce coverage bias during sample preamplification.We developed a single-cell DNA library preparation method without preamplification in nanolitre scale(scDPN)to address these issues.The method achieved a throughput of up to 1800 cells per run for copy number variation(CNV)detection.Also,our approach demonstrated a lower level of amplification bias and noise than the multiple displacement amplification(MDA)method and showed high sensitivity and accuracy for cell line and tumor tissue evaluation.We used this approach to profile the tumor clones in paired primary and relapsed tumor samples of hepatocellular carcinoma(HCC).We identified three clonal subpopulations with a multitude of aneuploid alterations across the genome.Furthermore,we observed that a minor clone of the primary tumor containing additional alterations in chromosomes 1q,10q,and 14q developed into the dominant clone in the recurrent tumor,indicating clonal selection during recurrence in HCC.Overall,this approach provides a comprehensive and scalable solution to understand genome heterogeneity and evolution.
