Fuqiang Li

Single-Cell Exome Sequencing Reveals Single-Nucleotide Mutation Characteristics of a Kidney Tumor

Clear cell renal cell carcinoma (ccRCC) is the most common kidney cancer and has very few mutations that are shared between different patients. To better understand the intratumoral genetics underlying mutations of ccRCC, we carried out single-cell exome sequencing on a ccRCC tumor and its adjacent kidney tissue. Our data indicate that this tumor was unlikely to have resulted from mutations in VHL and PBRM1. Quantitative population genetic analysis indicates that the tumor did not contain any significant clonal subpopulations and also showed that mutations that had different allele frequencies within the population also had different mutation spectrums. Analyses of these data allowed us to delineate a detailed intratumoral genetic landscape at a single-cell level. Our pilot study demonstrates that ccRCC may be more genetically complex than previously thought and provides information that can lead to new ways to investigate individual tumors, with the aim of developing more effective cellular targeted therapies.

Single-Cell Exome Sequencing and Monoclonal Evolution of a JAK2-Negative Myeloproliferative Neoplasm

Tumor heterogeneity presents a challenge for inferring clonal evolution and driver gene identification. Here, we describe a method for analyzing the cancer genome at a single-cell nucleotide level. To perform our analyses, we first devised and validated a high-throughput whole-genome single-cell sequencing method using two lymphoblastoid cell line single cells. We then carried out whole-exome single-cell sequencing of 90 cells from a JAK2-negative myeloproliferative neoplasm patient. The sequencing data from 58 cells passed our quality control criteria, and these data indicated that this neoplasm represented a monoclonal evolution. We further identified essential thrombocythemia (ET)-related candidate mutations such as SESN2 and NTRK1, which may be involved in neoplasm progression. This pilot study allowed the initial characterization of the disease-related genetic architecture at the single-cell nucleotide level. Further, we established a single-cell sequencing method that opens the way for detailed analyses of a variety of tumor types, including those with high genetic complex between patients.

High‐Purity Prostate Circulating Tumor Cell Isolation by a Polymer Nanofiber‐Embedded Microchip for Whole Exome Sequencing

Handpick single cancer cells: a modified NanoVelcro Chip is coupled with ArcturusXT laser capture microdissection (LCM) technology to enable the detection and isolation of single circulating tumor cells (CTCs) from patients with prostate cancer (PC). This new approach paves the way for conducting next-generation sequencing (NGS) on single CTCs.

Single-cell sequencing analysis characterizes common and cell-lineage-specific mutations in a muscle-invasive bladder cancer

BackgroundCancers arise through an evolutionary process in which cell populations are subjected to selection; however, to date, the process of bladder cancer, which is one of the most common cancers in the world, remains unknown at a single-cell level.ResultsWe carried out single-cell exome sequencing of 66 individual tumor cells from a muscle-invasive bladder transitional cell carcinoma (TCC). Analyses of the somatic mutant allele frequency spectrum and clonal structure revealed that the tumor cells were derived from a single ancestral cell, but that subsequent evolution occurred, leading to two distinct tumor cell subpopulations. By analyzing recurrently mutant genes in an additional cohort of 99 TCC tumors, we identified genes that might play roles in the maintenance of the ancestral clone and in the muscle-invasive capability of subclones of this bladder cancer, respectively.ConclusionsThis work provides a new approach of investigating the genetic details of bladder tumoral changes at the single-cell level and a new method for assessing bladder cancer evolution at a cell-population level.

A comparison of isolated circulating tumor cells and tissue biopsies using whole-genome sequencing in prostate cancer

Previous studies have demonstrated focal but limited molecular similarities between circulating tumor cells (CTCs) and biopsies using isolated genetic assays. We hypothesized that molecular similarity between CTCs and tissue exists at the single cell level when characterized by whole genome sequencing (WGS). By combining the NanoVelcro CTC Chip with laser capture microdissection (LCM), we developed a platform for single-CTC WGS. We performed this procedure on CTCs and tissue samples from a patient with advanced prostate cancer who had serial biopsies over the course of his clinical history. We achieved 30X depth and ≥ 95% coverage. Twenty-nine percent of the somatic single nucleotide variations (SSNVs) identified were founder mutations that were also identified in CTCs. In addition, 86% of the clonal mutations identified in CTCs could be traced back to either the primary or metastatic tumors. In this patient, we identified structural variations (SVs) including an intrachromosomal rearrangement in chr3 and an interchromosomal rearrangement between chr13 and chr15. These rearrangements were shared between tumor tissues and CTCs. At the same time, highly heterogeneous short structural variants were discovered in PTEN, RB1, and BRCA2 in all tumor and CTC samples. Using high-quality WGS on single-CTCs, we identified the shared genomic alterations between CTCs and tumor tissues. This approach yielded insight into the heterogeneity of the mutational landscape of SSNVs and SVs. It may be possible to use this approach to study heterogeneity and characterize the biological evolution of a cancer during the course of its natural history.

MethylPurify: tumor purity deconvolution and differential methylation detection from single tumor DNA methylomes

We propose a statistical algorithm MethylPurify that uses regions with bisulfite reads showing discordant methylation levels to infer tumor purity from tumor samples alone. MethylPurify can identify differentially methylated regions (DMRs) from individual tumor methylome samples, without genomic variation information or prior knowledge from other datasets. In simulations with mixed bisulfite reads from cancer and normal cell lines, MethylPurify correctly inferred tumor purity and identified over 96% of the DMRs. From patient data, MethylPurify gave satisfactory DMR calls from tumor methylome samples alone, and revealed potential missed DMRs by tumor to normal comparison due to tumor heterogeneity.

Full-length single-cell RNA-seq applied to a viral human cancer: applications to HPV expression and splicing analysis in HeLa S3 cells

BackgroundViral infection causes multiple forms of human cancer, and HPV infection is the primary factor in cervical carcinomas. Recent single-cell RNA-seq studies highlight the tumor heterogeneity present in most cancers, but virally induced tumors have not been studied. HeLa is a well characterized HPV+ cervical cancer cell line.ResultWe developed a new high throughput platform to prepare single-cell RNA on a nanoliter scale based on a customized microwell chip. Using this method, we successfully amplified full-length transcripts of 669 single HeLa S3 cells and 40 of them were randomly selected to perform single-cell RNA sequencing. Based on these data, we obtained a comprehensive understanding of the heterogeneity of HeLa S3 cells in gene expression, alternative splicing and fusions. Furthermore, we identified a high diversity of HPV-18 expression and splicing at the single-cell level. By co-expression analysis we identified 283 E6, E7 co-regulated genes, including CDC25, PCNA, PLK4, BUB1B and IRF1 known to interact with HPV viral proteins.ConclusionOur results reveal the heterogeneity of a virus-infected cell line. It not only provides a transcriptome characterization of HeLa S3 cells at the single cell level, but is a demonstration of the power of single cell RNA-seq analysis of virally infected cells and cancers.

Frequent alterations in cytoskeleton remodelling genes in primary and metastatic lung adenocarcinomas

The landscape of genetic alterations in lung adenocarcinoma derived from Asian patients is largely uncharacterized. Here we present an integrated genomic and transcriptomic analysis of 335 primary lung adenocarcinomas and 35 corresponding lymph node metastases from Chinese patients. Altogether 13 significantly mutated genes are identified, including the most commonly mutated gene TP53 and novel mutation targets such as RHPN2, GLI3 and MRC2. TP53 mutations are furthermore significantly enriched in tumours from patients harbouring metastases. Genes regulating cytoskeleton remodelling processes are also frequently altered, especially in metastatic samples, of which the high expression level of IQGAP3 is identified as a marker for poor prognosis. Our study represents the first large-scale sequencing effort on lung adenocarcinoma in Asian patients and provides a comprehensive mutational landscape for both primary and metastatic tumours. This may thus form a basis for personalized medical care and shed light on the molecular pathogenesis of metastatic lung adenocarcinoma.

Circumventing intratumoral heterogeneity to identify potential therapeutic targets in hepatocellular carcinoma

BACKGROUND & AIMS Identifying target genetic mutations in hepatocellular carcinoma (HCC) for therapy is made challenging by intratumoral heterogeneity. Circulating cell-free DNAs (cfDNA) may contain a more complete mutational spectrum compared to a single tumor sample. This study aimed to identify the most efficient strategy to identify all the mutations within heterogeneous HCCs. METHODS Whole exome sequencing (WES) and targeted deep sequencing (TDS) were carried out in 32 multi-regional tumor samples from five patients. Matched preoperative cfDNAs were sequenced accordingly. Intratumoral heterogeneity was measured using the average percentage of non-ubiquitous mutations (present in parts of tumor regions). Profiling efficiencies of single tumor specimen and cfDNA were compared. The strategy with the highest performance was used to screen for actionable mutations. RESULTS Variable levels of heterogeneity with branched and parallel evolution patterns were observed. The heterogeneity decreased at higher sequencing depth of TDS compared to measurements by WES (28.1% vs. 34.9%, p<0.01) but remained unchanged when additional samples were analyzed. TDS of single tumor specimen identified an average of 70% of the total mutations from multi-regional tissues. Although genome profiling efficiency of cfDNA increased with sequencing depth, an average of 47.2% total mutations were identified using TDS, suggesting that tissue samples outperformed it. TDS of single tumor specimen in 66 patients and cfDNAs in four unresectable HCCs showed that 38.6% (26/66 and 1/4) of patients carried mutations that were potential therapeutic targets. CONCLUSIONS TDS of single tumor specimen could identify actionable mutations targets for therapy in HCC. cfDNA may serve as secondary alternative in profiling HCC genome. LAY SUMMARY Targeted deep sequencing of single tumor specimen is a more efficient method to identify mutations in hepatocellular carcinoma made from mixed subtypes compared to circulating cell-free DNA in blood. cfDNA may serve as secondary alternative in profiling HCC genome. Identifying mutations may help clinicians choose targeted therapy for better individual treatments.

Analysis of ultra-deep targeted sequencing reveals mutation burden is associated with gender and clinical outcome in lung adenocarcinoma

Gender-associated difference in incidence and clinical outcomes of lung cancer have been established, but the biological mechanisms underlying these gender-associated differences are less studied. Recently we have characterized the genomic landscape of lung adenocarcinoma derived from Chinese population (Reference [1]). In this study we evaluated the clinical significance of mutation burden in lung adenocarcinoma and found that the male tumors harbored statistically greater burden of genetic alterations than female counterparts (Male median 3 (range 0–34) vs female median = 2 (0–24), male to female ratio = 1.636, 95% CI = 1.343–1.992) after adjustment of age at surgery, stage, smoking status. Kaplan-Meier survival analysis revealed that greater burden of genetic alterations was associated with worse overall survival. Moreover, multivariable analysis demonstrated mutation burden was an independent prognostic factor for the patients. Taken together, our analysis demonstrated gender disparity of mutation burden and their prognostic value in lung adenocarcinoma. This gender difference in mutation burden might provide an explanation for the distinct difference in the clinical outcomes between sexes in lung adenocarcinoma.