UniPath: a uniform approach for pathway and gene-set based analysis of heterogeneity in single-cell epigenome and transcriptome profiles.

Recent advances in single-cell open-chromatin and transcriptome profiling have created a challenge of exploring novel applications with a meaningful transformation of read-counts, which often have high variability in noise and drop-out among cells. Here, we introduce UniPath, for representing single-cells using pathway and gene-set enrichment scores by a transformation of their open-chromatin or gene-expression profiles. The robust statistical approach of UniPath provides high accuracy, consistency and scalability in estimating gene-set enrichment scores for every cell. Its framework provides an easy solution for handling variability in drop-out rate, which can sometimes create artefact due to systematic patterns. UniPath provides an alternative approach of dimension reduction of single-cell open-chromatin profiles. UniPath's approach of predicting temporal-order of single-cells using their pathway enrichment scores enables suppression of covariates to achieve correct order of cells. Analysis of mouse cell atlas using our approach yielded surprising, albeit biologically-meaningful co-clustering of cell-types from distant organs. By enabling an unconventional method of exploiting pathway co-occurrence to compare two groups of cells, our approach also proves to be useful in inferring context-specific regulations in cancer cells. Available at https://reggenlab.github.io/UniPathWeb/.

Concurrent Single-Cell RNA and Targeted DNA Sequencing on an Automated Platform for Comeasurement of Genomic and Transcriptomic Signatures.

BACKGROUND: The comeasurement of both genomic and transcriptomic signatures in single cells is of fundamental importance to accurately assess how the genetic information correlates with the transcriptomic phenotype. However, existing technologies have low throughput and laborious work flows. METHODS: We developed a new method for concurrent sequencing of the transcriptome and targeted genomic regions (CORTAD-seq) within the same single cell on an automated microfluidic platform. The method was compatible with the downstream library preparation, allowing easy integration into existing next-generation sequencing work flows. We incorporated a single-cell bioinformatics pipeline for transcriptome and mutation analysis. RESULTS: As proof of principle, we applied CORTAD-seq to lung cancer cell lines to dissect the cellular consequences of mutations that result in resistance to targeted therapy. We obtained a mean detection of 6000 expressed genes and an exonic rate of 50%. The targeted DNA-sequencing data achieved a 97.8% detection rate for mutations and allowed for the identification of copy number variations and haplotype construction. We detected expression signatures of tyrosine kinase inhibitor (TKI) resistance, epidermal growth factor receptor (EGFR) amplification, and expansion of the T790M mutation among resistant cells. We also identified characteristics for TKI resistance that were independent of EGFR T790M, indicating that other alterations are required for resistance in this context. CONCLUSIONS: CORTAD-seq allows assessment of the interconnection between genetic and transcriptomic changes in single cells. It is operated on an automated, commercially available single-cell isolation platform, making its implementation straightforward.

Personalized Treatment Through Detection and Monitoring of Genetic Aberrations in Single Circulating Tumor Cells.

Circulating tumor cells (CTCs) present a viable alternative to access tumor materials other than primary biopsies in cancer. This disease is among the most widespread in the world and is difficult to target because of its complex nature, challenges in getting quality samples and dynamic temporal changes in response to treatment. Conventional methods of detection and monitoring the disease profile do not suffice to be able to target the heterogeneity that exists at the cellular level. CTCs have been identified as a possible substitute for tumor tissue samples, and can be used to complement current disease management. Challenges in CTCs molecular analysis lie in the purity of the sample, which is masked by the presence of large quantities of white blood cells (WBCs) . In this chapter, we present a microfluidic biochip platform that performs secondary purification to isolate single CTCs efficiently. Studying single CTCs will allow for sensitive detection of critical mutations and addressing intercellular variances that will be otherwise missed easily due to low mutation frequencies when evaluating bulk cell retrieval. Using the biochip, we isolated single CTCs, and conducted personalized integrated EGFR mutational analysis using conventional polymerase chain reaction (PCR) and Sanger sequencing. We also demonstrated that high quality next generation sequencing (NGS) libraries can be readily generated from these samples. In our initial study, we revealed that the dominant EGFR mutations such as L858R and T790M could be detected in Non Small Cell Lung Cancer (NSCLC) patients with low CTC counts. We envision the biochip will enable efficient isolation of rare single cells from samples. This technology coupled with downstream molecular characterization of CTCs will aid in realizing the personalized medicine for cancer patients.

Patterns of transcription factor binding and epigenome at promoters allow interpretable predictability of multiple functions of non-coding and coding genes.

Understanding the biological roles of all genes only through experimental methods is challenging. A computational approach with reliable interpretability is needed to infer the function of genes, particularly for non-coding RNAs. We have analyzed genomic features that are present across both coding and non-coding genes like transcription factor (TF) and cofactor ChIP-seq (823), histone modifications ChIP-seq (n = 621), cap analysis gene expression (CAGE) tags (n = 255), and DNase hypersensitivity profiles (n = 255) to predict ontology-based functions of genes. Our approach for gene function prediction was reliable (>90% balanced accuracy) for 486 gene-sets. PubMed abstract mining and CRISPR screens supported the inferred association of genes with biological functions, for which our method had high accuracy. Further analysis revealed that TF-binding patterns at promoters have high predictive strength for multiple functions. TF-binding patterns at the promoter add an unexplored dimension of explainable regulatory aspects of genes and their functions. Therefore, we performed a comprehensive analysis for the functional-specificity of TF-binding patterns at promoters and used them for clustering functions to reveal many latent groups of gene-sets involved in common major cellular processes. We also showed how our approach could be used to infer the functions of non-coding genes using the CRISPR screens of coding genes, which were validated using a long non-coding RNA CRISPR screen. Thus our results demonstrated the generality of our approach by using gene-sets from CRISPR screens. Overall, our approach opens an avenue for predicting the involvement of non-coding genes in various functions.

Dampened Inflammation and Improved Survival After CXCL5 Administration in Murine Lupus via Myeloid and Neutrophil Pathways.

OBJECTIVE: To determine the efficacy of CXCL5 administration in lupus-prone MRL/lpr (Faslpr ) mice and elucidate its working mechanisms. METHODS: CXCL5 expression in blood (obtained from SLE patients and Faslpr mice) and major internal organs (obtained from Faslpr mice) was examined by Luminex, real-time polymerase chain reaction, and immunofluorescent staining analyses. Pharmacokinetic studies were performed in Faslpr mice and healthy Institute of Cancer Research mice. Efficacy of CXCL5 administration was demonstrated in Faslpr mice, and the working mechanism of CXCL5 treatment was elucidated by flow cytometry, Luminex, and RNA sequencing. RESULTS: In SLE patients, serum CXCL5 levels were significantly lower than in healthy individuals (P < 0.0001) and negatively correlated with disease activity (P = 0.004). In Faslpr mice, disease severity progressed with age and was negatively associated with plasma CXCL5 levels. Intravenous administration of CXCL5 to Faslpr mice restored endogenous circulatory CXCL5, improved mice survival, and reduced anti-double-stranded DNA antibodies, proteinuria, lupus nephritis activity and chronicity indices, renal complements, and neutrophil extracellular traps over short-term (10 weeks) and long-term (2 years) time periods. In vitro and in vivo assays demonstrated that CXCL5 dictated neutrophil trafficking and suppressed neutrophil activation, degranulation, proliferation, and renal infiltration. Renal and splenic RNA sequencing further showed that CXCL5-mediated immunomodulation occurred by promoting energy production in renal-infiltrated immune cells, activating certain T cells, and reducing tissue fibrosis, granulocyte extravasation, complement components, and interferons. Further factorial design results indicated that CXCL5 appears to enhance host tolerability to cyclophosphamide in vulnerable individuals. CONCLUSION: We found that serum CXCL5 levels were significantly lower in SLE patients than in healthy individuals and were negatively correlated with disease activity. By administering CXCL5 intravenously in a mouse model of lupus, mouse survival improved, and indices of disease activity reduced significantly. Taken together, these findings indicate CXCL5 administration may represent a novel myeloid/neutrophil-targeting therapy for SLE.

Cellular reprogramming by the conjoint action of ERα, FOXA1, and GATA3 to a ligand-inducible growth state.

Despite the role of the estrogen receptor α (ERα) pathway as a key growth driver for breast cells, the phenotypic consequence of exogenous introduction of ERα into ERα-negative cells paradoxically has been growth inhibition. We mapped the binding profiles of ERα and its interacting transcription factors (TFs), FOXA1 and GATA3 in MCF-7 breast carcinoma cells, and observed that these three TFs form a functional enhanceosome that regulates the genes driving core ERα function and cooperatively modulate the transcriptional networks previously ascribed to ERα alone. We demonstrate that these enhanceosome occupied sites are associated with optimal enhancer characteristics with highest p300 co-activator recruitment, RNA Pol II occupancy, and chromatin opening. Most importantly, we show that the transfection of all three TFs was necessary to reprogramme the ERα-negative MDA-MB-231 and BT-549 cells to restore the estrogen-responsive growth resembling estrogen-treated ERα-positive MCF-7 cells. Cumulatively, these results suggest that all the enhanceosome components comprising ERα, FOXA1, and GATA3 are necessary for the full repertoire of cancer-associated effects of the ERα.

Integrative model of genomic factors for determining binding site selection by estrogen receptor-α.

A major question in transcription factor (TF) biology is why a TF binds to only a small fraction of motif eligible binding sites in the genome. Using the estrogen receptor-α as a model system, we sought to explicitly define parameters that determine TF-binding site selection. By examining 12 genetic and epigenetic parameters, we find that an energetically favorable estrogen response element (ERE) motif sequence, co-occupancy by the TF FOXA1, the presence of the H3K4me1 mark and an open chromatin configuration in the pre-ligand state provide specificity for ER binding. These factors can model estrogen-induced ER binding with high accuracy (ROC-AUC=0.95 and 0.88 using different genomic backgrounds). Moreover, when assessed in another estrogen-responsive cell line, this model was highly predictive for ERα binding (ROC-AUC=0.86). Variance in binding site selection between MCF-7 and T47D resides in sites with suboptimal ERE motifs, but modulated by the chromatin configuration. These results suggest a definable interplay between sequence motifs and local chromatin in selecting TF binding.

Structure-selective differentiation of deletion mutations in circulating tumor DNA using dual probe-based isothermal amplification.

A rapid dual probe-based fluorimetric assay was developed to detect deletion mutations in circulating tumor DNA using structure-selective isothermal amplification and pattern recognition. This method could detect both homozygous and heterozygous deletion configurations in a one-set experiment and achieved picomolar detection limits with high selectivity within 2 hours. It was promising for point-of-care cancer diagnosis in hospital settings.

Experimental and bioinformatics considerations in cancer application of single cell genomics.

Single cell genomics offers an unprecedented resolution to interrogate genetic heterogeneity in a patient's tumour at the intercellular level. However, the DNA yield per cell is insufficient for today's sequencing library preparation protocols. This necessitates DNA amplification which is a key source of experimental noise. We provide an evaluation of two protocols using micro-fluidics based amplification for whole exome sequencing, which is an experimental scenario commonly used in single cell genomics. The results highlight their respective biases and relative strengths in identification of single nucleotide variations. Towards this end, we introduce a workflow SoVaTSiC, which allows for quality evaluation and somatic variant identification of single cell data. As proof of concept, the framework was applied to study a lung adenocarcinoma tumour. The analysis provides insights into tumour phylogeny by identifying key mutational events in lung adenocarcinoma evolution. The consequence of this inference is supported by the histology of the tumour and demonstrates usefulness of the approach.

Complementary Sequential Circulating Tumor Cell (CTC) and Cell-Free Tumor DNA (ctDNA) Profiling Reveals Metastatic Heterogeneity and Genomic Changes in Lung Cancer and Breast Cancer.

INTRODUCTION: Circulating tumor cells (CTCs) and cell-free tumor DNA (ctDNA) are tumor components present in circulation. Due to the limited access to both CTC enrichment platforms and ctDNA sequencing in most laboratories, they are rarely analyzed together. METHODS: Concurrent isolation of ctDNA and single CTCs were isolated from lung cancer and breast cancer patients using the combination of size-based and CD45-negative selection method via DropCell platform. We performed targeted amplicon sequencing to evaluate the genomic heterogeneity of CTCs and ctDNA in lung cancer and breast cancer patients. RESULTS: Higher degrees of genomic heterogeneity were observed in CTCs as compared to ctDNA. Several shared alterations present in CTCs and ctDNA were undetected in the primary tumor, highlighting the intra-tumoral heterogeneity of tumor components that were shed into systemic circulation. Accordingly, CTCs and ctDNA displayed higher degree of concordance with the metastatic tumor than the primary tumor. The alterations detected in circulation correlated with worse survival outcome for both lung and breast cancer patients emphasizing the impact of the metastatic phenotype. Notably, evolving genetic signatures were detected in the CTCs and ctDNA samples during the course of treatment and disease progression. CONCLUSIONS: A standardized sample processing and data analysis workflow for concurrent analysis of CTCs and ctDNA successfully dissected the heterogeneity of metastatic tumor in circulation as well as the progressive genomic changes that may potentially guide the selection of appropriate therapy against evolving tumor clonality.

Whole-genome cartography of estrogen receptor alpha binding sites.

Using a chromatin immunoprecipitation-paired end diTag cloning and sequencing strategy, we mapped estrogen receptor alpha (ERalpha) binding sites in MCF-7 breast cancer cells. We identified 1,234 high confidence binding clusters of which 94% are projected to be bona fide ERalpha binding regions. Only 5% of the mapped estrogen receptor binding sites are located within 5 kb upstream of the transcriptional start sites of adjacent genes, regions containing the proximal promoters, whereas vast majority of the sites are mapped to intronic or distal locations (>5 kb from 5' and 3' ends of adjacent transcript), suggesting transcriptional regulatory mechanisms over significant physical distances. Of all the identified sites, 71% harbored putative full estrogen response elements (EREs), 25% bore ERE half sites, and only 4% had no recognizable ERE sequences. Genes in the vicinity of ERalpha binding sites were enriched for regulation by estradiol in MCF-7 cells, and their expression profiles in patient samples segregate ERalpha-positive from ERalpha-negative breast tumors. The expression dynamics of the genes adjacent to ERalpha binding sites suggest a direct induction of gene expression through binding to ERE-like sequences, whereas transcriptional repression by ERalpha appears to be through indirect mechanisms. Our analysis also indicates a number of candidate transcription factor binding sites adjacent to occupied EREs at frequencies much greater than by chance, including the previously reported FOXA1 sites, and demonstrate the potential involvement of one such putative adjacent factor, Sp1, in the global regulation of ERalpha target genes. Unexpectedly, we found that only 22%-24% of the bona fide human ERalpha binding sites were overlapping conserved regions in whole genome vertebrate alignments, which suggest limited conservation of functional binding sites. Taken together, this genome-scale analysis suggests complex but definable rules governing ERalpha binding and gene regulation.

A centrifugation-assisted visual detection of SNP in circulating tumor DNA using gold nanoparticles coupled with isothermal amplification.

Detection of single-nucleotide polymorphism (SNP) in circulating tumor DNA (ctDNA) is challenging because of the large DNA fragmentation (∼150 nt) and the strong background of normal cell free DNA (cfDNA). Here we developed a rapid centrifugation-assisted colorimetric assay using gold nanoparticles (AuNPs) coupled with isothermal amplification to detect a SNP (G to C mutation) in KRAS, p.G13D in ctDNA. Compared to conventional AuNP aggregation assays, our assay contains four unique design concepts. Firstly, a centrifugation step is introduced at the end of the reaction that significantly enhances the colorimetric readout by providing visually distinct precipitation for the SNP ctDNA. Secondly, to achieve a fast turnover rate for clinical pM demand, a "critical linker concentration" concept is introduced to the assay. Thirdly, in order to achieve an unambiguous differentiation of the SNP ctDNA from wild type cfDNA and the control sample without DNA, a "color code conversion" strategy is employed, where a complementary sequence of the linker DNA is introduced to manipulate the AuNP aggregation. Finally, ethylenediaminetetraacetic acid is used for enzyme inactivation only at room temperature while stabilizing the AuNP solution from unwanted aggregation. Our assay coupling two amplification strategies (isothermal amplification and centrifugation-assisted assembly) is capable of both quantitative and qualitative differentiation of SNP in ctDNA of ∼150 nt at a clinically relevant concentration and 67 pM limit of detection and in the presence of 99% normal cfDNA background. This assay can be used for point-of-care colon cancer diagnosis and prognosis with a fast turnover time (<2 h).

Author Correction: Reference component analysis of single-cell transcriptomes elucidates cellular heterogeneity in human colorectal tumors.

In the version of the article published, the author list is not accurate. Igor Cima and Min-Han Tan should have been authors, appearing after Mark Wong in the author list, while Paul Jongjoon Choi should not have been listed as an author. Igor Cima and Min-Han Tan both have the affiliation Institute of Bioengineering and Nanotechnology, Singapore, Singapore, and their contributions should have been noted in the Author Contributions section as "I.C. preprocessed Primary Cell Atlas data with inputs from M.-H.T." The following description of the contribution of Paul Jongjoon Choi should not have appeared: "P.J.C. supported the smFISH experiments." In the 'RCA: global panel' section of the Online Methods, the following sentence should have appeared as the second sentence, "An expression atlas of human primary cells (the Primary Cell Atlas) was preprocessed similarly to in ref. 55," with new reference 55 (Cima, I. et al. Tumor-derived circulating endothelial cell clusters in colorectal cancer. Science Transl. Med. 8, 345ra89, 2016).

Reference component analysis of single-cell transcriptomes elucidates cellular heterogeneity in human colorectal tumors.

Intratumoral heterogeneity is a major obstacle to cancer treatment and a significant confounding factor in bulk-tumor profiling. We performed an unbiased analysis of transcriptional heterogeneity in colorectal tumors and their microenvironments using single-cell RNA-seq from 11 primary colorectal tumors and matched normal mucosa. To robustly cluster single-cell transcriptomes, we developed reference component analysis (RCA), an algorithm that substantially improves clustering accuracy. Using RCA, we identified two distinct subtypes of cancer-associated fibroblasts (CAFs). Additionally, epithelial-mesenchymal transition (EMT)-related genes were found to be upregulated only in the CAF subpopulation of tumor samples. Notably, colorectal tumors previously assigned to a single subtype on the basis of bulk transcriptomics could be divided into subgroups with divergent survival probability by using single-cell signatures, thus underscoring the prognostic value of our approach. Overall, our results demonstrate that unbiased single-cell RNA-seq profiling of tumor and matched normal samples provides a unique opportunity to characterize aberrant cell states within a tumor.

Molecular characterization of circulating colorectal tumor cells defines genetic signatures for individualized cancer care.

Studies on circulating tumor cells (CTCs) have largely focused on platform development and CTC enumeration rather than on the genomic characterization of CTCs. To address this, we performed targeted sequencing of CTCs of colorectal cancer patients and compared the mutations with the matched primary tumors. We collected preoperative blood and matched primary tumor samples from 48 colorectal cancer patients. CTCs were isolated using a label-free microfiltration device on a silicon microsieve. Upon whole genome amplification, we performed amplicon-based targeted sequencing on a panel of 39 druggable and frequently mutated genes on both CTCs and fresh-frozen tumor samples. We developed an analysis pipeline to minimize false-positive detection of somatic mutations in amplified DNA. In 60% of the CTC-enriched blood samples, we detected primary tumor matching mutations. We found a significant positive correlation between the allele frequencies of somatic mutations detected in CTCs and abnormal CEA serum level. Strikingly, we found driver mutations and amplifications in cancer and druggable genes such as APC, KRAS, TP53, ERBB3, FBXW7 and ERBB2. In addition, we found that CTCs carried mutation signatures that resembled the signatures of their primary tumors. Cumulatively, our study defined genetic signatures and somatic mutation frequency of colorectal CTCs. The identification of druggable mutations in CTCs of preoperative colorectal cancer patients could lead to more timely and focused therapeutic interventions.

Reprogramming mouse fibroblasts into engraftable myeloerythroid and lymphoid progenitors.

Recent efforts have attempted to convert non-blood cells into hematopoietic stem cells (HSCs) with the goal of generating blood lineages de novo. Here we show that hematopoietic transcription factors Scl, Lmo2, Runx1 and Bmi1 can convert a developmentally distant lineage (fibroblasts) into 'induced hematopoietic progenitors' (iHPs). Functionally, iHPs generate acetylcholinesterase+ megakaryocytes and phagocytic myeloid cells in vitro and can also engraft immunodeficient mice, generating myeloerythoid and B-lymphoid cells for up to 4 months in vivo. Molecularly, iHPs transcriptionally resemble native Kit+ hematopoietic progenitors. Mechanistically, reprogramming factor Lmo2 implements a hematopoietic programme in fibroblasts by rapidly binding to and upregulating the Hhex and Gfi1 genes within days. Moreover the reprogramming transcription factors also require extracellular BMP and MEK signalling to cooperatively effectuate reprogramming. Thus, the transcription factors that orchestrate embryonic hematopoiesis can artificially reconstitute this programme in developmentally distant fibroblasts, converting them into engraftable blood progenitors.

Tumor-derived circulating endothelial cell clusters in colorectal cancer.

Clusters of tumor cells are often observed in the blood of cancer patients. These structures have been described as malignant entities for more than 50 years, although their comprehensive characterization is lacking. Contrary to current consensus, we demonstrate that a discrete population of circulating cell clusters isolated from the blood of colorectal cancer patients are not cancerous but consist of tumor-derived endothelial cells. These clusters express both epithelial and mesenchymal markers, consistent with previous reports on circulating tumor cell (CTC) phenotyping. However, unlike CTCs, they do not mirror the genetic variations of matched tumors. Transcriptomic analysis of single clusters revealed that these structures exhibit an endothelial phenotype and can be traced back to the tumor endothelium. Further results show that tumor-derived endothelial clusters do not form by coagulation or by outgrowth of single circulating endothelial cells, supporting a direct release of clusters from the tumor vasculature. The isolation and enumeration of these benign clusters distinguished healthy volunteers from treatment-naïve as well as pathological early-stage (≤IIA) colorectal cancer patients with high accuracy, suggesting that tumor-derived circulating endothelial cell clusters could be used as a means of noninvasive screening for colorectal cancer. In contrast to CTCs, tumor-derived endothelial cell clusters may also provide important information about the underlying tumor vasculature at the time of diagnosis, during treatment, and throughout the course of the disease.

A plasmonic nanosensor with inverse sensitivity for circulating cell-free DNA quantification.

A plasmonic nanosensor (using gold nanorods) with inverse sensitivity is presented for circulating cell-free DNA quantification. The inverse sensitivity (i.e. the lower the analyte concentration, the higher the response intensity) is achieved by the unusual DNA concentration-dependent gold nanorod aggregation. This assay method can adjust the dynamic range by controlling the concentration of nanoparticles in solution.