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.

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.

The MnO 2 /carbon nanotubes (CNTs) composites were prepared through a modified one-pot reaction process, in which CNTs were coated by cross-linked MnO 2 flakes uniformly. The composition, morphology, and microstructure of the products were characterized using TG, XRD, XPS, Raman, FESEM, TEM, and STEM. It reveals that the MnO 2 layer stands on the sidewalls of the inner nanotubes uniformly about 50 nm thick, and the loading of MnO 2 on the CNTs reaches 84%. Furthermore, the supercapacitive performances were investigated by cyclic voltammogram (CV), galvanostatic charge−discharge, and electrochemical impedance spectroscopy (EIS). The experimental results indicate that the composite exhibits not only high specific capacitance of 201 F g −1 and rate capability (the specific capacitance at 20 A g −1 is 70% of that at 1 A g −1 ), but also excellent cycle stability (no obvious capacitance decay after 10 000 cycles at 1 A g −1 ). An asymmetric electrochemical capacitor was assembled by using the obtained MnO 2 /CNTs composite as positive electrode and activated carbon (AC) as negative electrode. The as-assembled AC//MnO 2 /CNTs capacitor can cycle reversibly in a voltage of 0−1.5 V and give a high energy density of 13.3 Wh kg −1 at a power density of 600 W kg −1 .

BackgroundSingle-cell resequencing (SCRS) provides many biomedical advances in variations detection at the single-cell level, but it currently relies on whole genome amplification (WGA). Three methods are commonly used for WGA: multiple displacement amplification (MDA), degenerate-oligonucleotide-primed PCR (DOP-PCR) and multiple annealing and looping-based amplification cycles (MALBAC). However, a comprehensive comparison of variations detection performance between these WGA methods has not yet been performed.ResultsWe systematically compared the advantages and disadvantages of different WGA methods, focusing particularly on variations detection. Low-coverage whole-genome sequencing revealed that DOP-PCR had the highest duplication ratio, but an even read distribution and the best reproducibility and accuracy for detection of copy-number variations (CNVs). However, MDA had significantly higher genome recovery sensitivity (~84 %) than DOP-PCR (~6 %) and MALBAC (~52 %) at high sequencing depth. MALBAC and MDA had comparable single-nucleotide variations detection efficiency, false-positive ratio, and allele drop-out ratio. We further demonstrated that SCRS data amplified by either MDA or MALBAC from a gastric cancer cell line could accurately detect gastric cancer CNVs with comparable sensitivity and specificity, including amplifications of 12p11.22 (KRAS) and 9p24.1 (JAK2, CD274, and PDCD1LG2).ConclusionsOur findings provide a comprehensive comparison of variations detection performance using SCRS amplified by different WGA methods. It will guide researchers to determine which WGA method is best suited to individual experimental needs at single-cell level.Electronic supplementary materialThe online version of this article (doi:10.1186/s13742-015-0068-3) contains supplementary material, which is available to authorized users.

Single-cell sequencing is a powerful tool for delineating clonal relationship and identifying key driver genes for personalized cancer management. Here we performed single-cell sequencing analysis of a case of colon cancer. Population genetics analyses identified two independent clones in tumor cell population. The major tumor clone harbored APC and TP53 mutations as early oncogenic events, whereas the minor clone contained preponderant CDC27 and PABPC1 mutations. The absence of APC and TP53 mutations in the minor clone supports that these two clones were derived from two cellular origins. Examination of somatic mutation allele frequency spectra of additional 21 wholetissue exome-sequenced cases revealed the heterogeneity of clonal origins in colon cancer. Next, we identified a mutated gene SLC12A5 that showed a high frequency of mutation at the single-cell level but exhibited low prevalence at the population level. Functional characterization of mutant SLC12A5 revealed its potential oncogenic effect in colon cancer. Our study provides the first exome-wide evidence at single-cell level supporting that colon cancer could be of a biclonal origin, and suggests that low-prevalence mutations in a cohort may also play important protumorigenic roles at the individual level.

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.

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.

A lack of gravity experienced during space flight has been shown to have profound effects on human physiology including muscle atrophy, reductions in bone density and immune function, and endocrine disorders. At present, these physiological changes present major obstacles to long-term space missions. What is not clear is which pathophysiological disruptions reflect changes at the cellular level versus changes that occur due to the impact of weightlessness on the entire body. This review focuses on current research investigating the impact of microgravity at the cellular level including cellular morphology, proliferation, and adhesion. As direct research in space is currently cost prohibitive, we describe here the use of microgravity simulators for studies at the cellular level. Such instruments provide valuable tools for cost-effective research to better discern the impact of weightlessness on cellular function. Despite recent advances in understanding the relationship between extracellular forces and cell behavior, very little is understood about cellular biology and mechanotransduction under microgravity conditions. This review will examine recent insights into the impact of simulated microgravity on cell biology and how this technology may provide new insight into advancing our understanding of mechanically driven biology and disease.