Nasopharyngeal carcinoma (NPC) is an aggressive malignancy with extremely skewed ethnic and geographic distributions. Increasing evidence indicates that targeting the tumor microenvironment (TME) represents a promising therapeutic approach in NPC, highlighting an urgent need to deepen the understanding of the complex NPC TME. Here, we generated single-cell transcriptome profiles for 7581 malignant cells and 40,285 immune cells from fifteen primary NPC tumors and one normal sample. We revealed malignant signatures capturing intratumoral transcriptional heterogeneity and predicting aggressiveness of malignant cells. Diverse immune cell subtypes were identified, including novel subtypes such as CLEC9A+ dendritic cells (DCs). We further revealed transcriptional regulators underlying immune cell diversity, and cell–cell interaction analyses highlighted promising immunotherapeutic targets in NPC. Moreover, we established the immune subtype-specific signatures, and demonstrated that the signatures of macrophages, plasmacytoid dendritic cells (pDCs), CLEC9A+ DCs, natural killer (NK) cells, and plasma cells were significantly associated with improved survival outcomes in NPC. Taken together, our findings represent a unique resource providing in-depth insights into the cellular heterogeneity of NPC TME and highlight potential biomarkers for anticancer treatment and risk stratification, laying a new foundation for precision therapies in NPC.

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.

Integrative analysis of multi-omics layers at single cell level is critical for accurate dissection of cell-to-cell variation within certain cell populations. Here we report scCAT-seq, a technique for simultaneously assaying chromatin accessibility and the transcriptome within the same single cell. We show that the combined single cell signatures enable accurate construction of regulatory relationships between cis-regulatory elements and the target genes at single-cell resolution, providing a new dimension of features that helps direct discovery of regulatory patterns specific to distinct cell identities. Moreover, we generate the first single cell integrated map of chromatin accessibility and transcriptome in early embryos and demonstrate the robustness of scCAT-seq in the precise dissection of master transcription factors in cells of distinct states. The ability to obtain these two layers of omics data will help provide more accurate definitions of “single cell state” and enable the deconvolution of regulatory heterogeneity from complex cell populations.

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.

Little is known about the transcriptomic plasticity and adaptive mechanisms of circulating tumor cells (CTCs) during hematogeneous dissemination. Here we interrogate the transcriptome of 113 single CTCs from 4 different vascular sites, including hepatic vein (HV), peripheral artery (PA), peripheral vein (PV) and portal vein (PoV) using single-cell full-length RNA sequencing in hepatocellular carcinoma (HCC) patients. We reveal that the transcriptional dynamics of CTCs were associated with stress response, cell cycle and immune-evasion signaling during hematogeneous transportation. Besides, we identify chemokine CCL5 as an important mediator for CTC immune evasion. Mechanistically, overexpression of CCL5 in CTCs is transcriptionally regulated by p38-MAX signaling, which recruites regulatory T cells (Tregs) to facilitate immune escape and metastatic seeding of CTCs. Collectively, our results reveal a previously unappreciated spatial heterogeneity and an immune-escape mechanism of CTC, which may aid in designing new anti-metastasis therapeutic strategies in HCC.

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.Electronic supplementary materialThe online version of this article (doi:10.1186/s13742-015-0091-4) contains supplementary material, which is available to authorized users.

Single-cell RNA sequencing examines the transcriptome of individual cells and reveals the inter-cell transcription heterogeneity, playing a critical role in both scientific research and clinical applications. Recently, droplet microfluidics-based platform for expression profiling has been shown as a powerful tool to capture of the transcriptional information on single cell level. Despite the breakthrough this platform brought about, it required the simultaneous encapsulation of single cell and single barcoded bead, the incidence of which was very low. Suboptimal capturing efficiency limited the throughput of the Drop-seq platform. In this work, we leveraged the advance in inertial microfluidics-based cell sorting and designed a microfluidic chip for high efficiency cell-bead co-encapsulation, increasing the capturing rate by more than four folds. Specifically, we adopted spiral and serpentine channels and ordered cells/beads before the encapsulation region. We characterized the effect of cell concentration on the capturing rate and achieved a cell-bead co-capturing rate up to 3%. We tested this platform by co-encapsulating barcoded beads and human-mouse cell mixtures. The sequencing data distinguished the majority of human and mice expressions, with the doublet rate being as low as 5.8%, indicating that the simultaneous capturing of two or more cells in one droplet was minimal even when using high cell concentration. This chip design showed great potential in improving the efficiency for future single cell expression profiling.