Search

Oesophageal squamous cell carcinoma (ESCC) is one of the most lethal cancers, owing to a high frequency of metastasis. However, little is known about the genomic landscape of metastatic ESCC. To identify the genetic alterations that underlie ESCC metastasis, whole-exome sequencing was performed for 41 primary tumours and 15 lymph nodes (LNs) with metastatic ESCCs. Eleven cases included matched primary tumours, synchronous LN metastases, and non-neoplastic mucosa. Approximately 50-76% of the mutations identified in primary tumours appeared in the synchronous LN metastases. Metastatic ESCCs harbour frequent mutations of TP53, KMT2D, ZNF750, and IRF5. Importantly, ZNF750 was recurrently mutated in metastatic ESCC. Combined analysis from current and previous genomic ESCC studies indicated more frequent ZNF750 mutation in diagnosed cases with LN metastasis than in those without metastasis (14% versus 3.4%, n = 629, P = 1.78 × 10-5 ). The Cancer Genome Atlas data further showed that ZNF750 genetic alterations were associated with early disease relapse. Previous ESCC studies have demonstrated that ZNF750 knockdown strongly promotes proliferation, migration, and invasion. Collectively, these results suggest a role for ZNF750 as a metastasis suppressor. TP53 is highly mutated in ESCC, and missense mutations are associated with poor overall survival, independently of pathological stage, suggesting that these missense mutations have important functional impacts on tumour progression, and are thus likely to be gain-of-function (GOF) mutations. Additionally, mutations of epigenetic regulators, including KMT2D, TET2, and KAT2A, and chromosomal 6p22 and 11q23 deletions of histone variants, which are important for nucleosome assembly, were detected in 80% of LN metastases. Our study highlights the important role of critical genetic events including ZNF750 mutations, TP53 putative GOF mutations and nucleosome disorganization caused by genetic lesions seen with ESCC metastasis. Copyright © 2017 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Oesophageal squamous cell carcinoma (ESCC) is one of the most lethal cancers, owing to a high frequency of metastasis. However, little is known about the genomic landscape of metastatic ESCC. To identify the genetic alterations that underlie ESCC metastasis, whole-exome sequencing was performed for 41 primary tumours and 15 lymph nodes (LNs) with metastatic ESCCs. Eleven cases included matched primary tumours, synchronous LN metastases, and non-neoplastic mucosa. Approximately 50-76% of the mutations identified in primary tumours appeared in the synchronous LN metastases. Metastatic ESCCs harbour frequent mutations of TP53, KMT2D, ZNF750, and IRF5. Importantly, ZNF750 was recurrently mutated in metastatic ESCC. Combined analysis from current and previous genomic ESCC studies indicated more frequent ZNF750 mutation in diagnosed cases with LN metastasis than in those without metastasis (14% versus 3.4%, n = 629, P = 1.78 × 10

We present Virtual Pharmacist, a web-based platform that takes common types of high-throughput data, namely microarray SNP genotyping data, FASTQ and Variant Call Format (VCF) files as inputs, and reports potential drug responses in terms of efficacy, dosage and toxicity at one glance. Batch submission facilitates multivariate analysis or data mining of targeted groups. Individual analysis consists of a report that is readily comprehensible to patients and practioners who have basic knowledge in pharmacology, a table that summarizes variants and potential affected drug response according to the US Food and Drug Administration pharmacogenomic biomarker labeled drug list and PharmGKB, and visualization of a gene-drug-target network. Group analysis provides the distribution of the variants and potential affected drug response of a target group, a sample-gene variant count table, and a sample-drug count table. Our analysis of genomes from the 1000 Genome Project underlines the potentially differential drug responses among different human populations. Even within the same population, the findings from Watson's genome highlight the importance of personalized medicine. Virtual Pharmacist can be accessed freely at http://www.sustc-genome.org.cn/vp or installed as a local web server. The codes and documentation are available at the GitHub repository (https://github.com/VirtualPharmacist/vp). Administrators can download the source codes to customize access settings for further development.

Single-cell genomic analysis has grown rapidly in recent years and finds widespread applications in various fields of biology, including cancer biology, development, immunology, pre-implantation genetic diagnosis and neurobiology. To date, the amplification bias, amplification uniformity and reproducibility of the three major single cell whole genome amplification methods (GenomePlex WGA4, MDA and MALBAC) have not been systematically investigated using mammalian cells. In this study, we amplified genomic DNA from individual hippocampal neurons using three single-cell DNA amplification methods and sequenced them at shallow depth. We then systematically evaluated the GC-bias, reproducibility and copy number variations among individual neurons. Our results showed that single-cell genome sequencing results obtained from the MALBAC and WGA4 methods are highly reproducible and have a high success rate. The MALBAC displays significant biases towards high GC content. We then attempted to correct the GC bias issue by developing a bioinformatics pipeline, which allows us to call CNVs in single cell sequencing data and chromosome level and sub-chromosomal level CNVs among individual neurons can be detected. We also proposed a metric to determine the CNV detection limits. Overall, MALBAC and WGA4 have better performance than MDA in detecting CNVs.

Single-cell genomic analysis has grown rapidly in recent years and will find widespread applications in various fields of biology, including cancer biology, development, immunology, pre-implantation genetic diagnosis, and neurobiology. In this study, we amplified genomic DNA from individual hippocampal neurons using one of three single-cell DNA amplification methods (multiple annealing and looping-based amplification cycles (MALBAC), multiple displacement amplification (MDA), and GenomePlex whole genome amplification (WGA4)). We then systematically evaluated the genome coverage, GC-bias, reproducibility, and copy number variations among individual neurons. Our results showed that single-cell genome sequencing results obtained from the MALBAC and WGA4 methods are highly reproducible and have a high success rate. Chromosome-level and subchromosomal-level copy number variations among individual neurons can be detected.

Single cell genomics is a rapidly growing field with many new techniques emerging in the past few years. However, few bioinformatics tools specific for single cell genomics analysis are available. Single cell DNA/RNA sequencing data usually have low genome coverage and high amplification bias, which makes bioinformatics analysis challenging. Many current bioinformatics tools developed for bulk cell sequencing do not work well with single cell sequencing data. Here, we summarize current challenges in the bioinformatics analysis of single cell genomic DNA sequencing and single cell transcriptomes. These challenges include calling copy number variations, identifying mutated genes in tumor samples, reconstructing cell lineages, recovering low abundant transcripts, and improving the accuracy of quantitative analysis of transcripts. Development in single cell genomics bioinformatics analysis will promote the application of this technology to basic biology and medical research.