Single-cell sequencing and tumorigenesis: improved understanding of tumor evolution and metastasis

Application of Single-Cell Sequencing Technology in Research on Colorectal Cancer

Colorectal cancer (CRC) is the third most prevalent and second most lethal cancer globally, with gene mutations and tumor metastasis contributing to its poor prognosis. Single-cell sequencing technology enables high-throughput analysis of the genome, transcriptome, and epigenetic landscapes at the single-cell level. It offers significant insights into analyzing the tumor immune microenvironment, detecting tumor heterogeneity, exploring metastasis mechanisms, and monitoring circulating tumor cells (CTCs). This article provides a brief overview of the technical procedure and data processing involved in single-cell sequencing. It also reviews the current applications of single-cell sequencing in CRC research, aiming to enhance the understanding of intratumoral heterogeneity, CRC development, CTCs, and novel drug targets. By exploring the diverse molecular and clinicopathological characteristics of tumor heterogeneity using single-cell sequencing, valuable insights can be gained into early diagnosis, therapy, and prognosis of CRC. Thus, this review serves as a valuable resource for identifying prognostic markers, discovering new therapeutic targets, and advancing personalized therapy in CRC.

Quantitative Modeling of Stemness in Single-Cell RNA Sequencing Data: A Nonlinear One-Class Support Vector Machine Method

Intratumoral heterogeneity and the presence of cancer stem cells are challenging issues in cancer therapy. An appropriate quantification of the stemness of individual cells for assessing the potential for self-renewal and differentiation from the cell of origin can define a measurement for quantifying different cell states, which is important in understanding the dynamics of cancer evolution, and might further provide possible targeted therapies aimed at tumor stem cells. Nevertheless, it is usually difficult to quantify the stemness of a cell based on molecular information associated with the cell. In this study, we proposed a stemness definition method with one-class Hadamard kernel support vector machine (OCHSVM) based on single-cell RNA sequencing (scRNA-seq) data. Applications of the proposed OCHSVM stemness are assessed by various data sets, including preimplantation embryo cells, induced pluripotent stem cells, or tumor cells. We further compared the OCHSVM model with state-of-the-art methods CytoTRACE, one-class logistic regression, or one-class SVM methods with different kernels. The computational results demonstrate that the OCHSVM method is more suitable for stemness identification using scRNA-seq data.

The Evolution of Single-Cell RNA Sequencing Technology and Application: Progress and Perspectives

As an emerging sequencing technology, single-cell RNA sequencing (scRNA-Seq) has become a powerful tool for describing cell subpopulation classification and cell heterogeneity by achieving high-throughput and multidimensional analysis of individual cells and circumventing the shortcomings of traditional sequencing for detecting the average transcript level of cell populations. It has been applied to life science and medicine research fields such as tracking dynamic cell differentiation, revealing sensitive effector cells, and key molecular events of diseases. This review focuses on the recent technological innovations in scRNA-Seq, highlighting the latest research results with scRNA-Seq as the core technology in frontier research areas such as embryology, histology, oncology, and immunology. In addition, this review outlines the prospects for its innovative application in traditional Chinese medicine (TCM) research and discusses the key issues currently being addressed by scRNA-Seq and its great potential for exploring disease diagnostic targets and uncovering drug therapeutic targets in combination with multiomics technologies.

Research progress of single-cell transcriptome sequencing in autoimmune diseases and autoinflammatory disease: A review

Autoimmunity refers to the phenomenon that the body's immune system produces antibodies or sensitized lymphocytes to its own tissues to cause an immune response. Immune disorders caused by autoimmunity can mediate autoimmune diseases. Autoimmune diseases have complicated pathogenesis due to the many types of cells involved, and the mechanism is still unclear. The emergence of single-cell research technology can solve the problem that ordinary transcriptome technology cannot be accurate to cell type. It provides unbiased results through independent analysis of cells in tissues and provides more mRNA information for identifying cell subpopulations, which provides a novel approach to study disruption of immune tolerance and disturbance of pro-inflammatory pathways on a cellular basis. It may fundamentally change the understanding of molecular pathways in the pathogenesis of autoimmune diseases and develop targeted drugs. Single-cell transcriptome sequencing (scRNA-seq) has been widely applied in autoimmune diseases, which provides a powerful tool for demonstrating the cellular heterogeneity of tissues involved in various immune inflammations, identifying pathogenic cell populations, and revealing the mechanism of disease occurrence and development. This review describes the principles of scRNA-seq, introduces common sequencing platforms and practical procedures, and focuses on the progress of scRNA-seq in 41 autoimmune diseases, which include 9 systemic autoimmune diseases and autoinflammatory diseases (rheumatoid arthritis, systemic lupus erythematosus, etc.) and 32 organ-specific autoimmune diseases (5 Skin diseases, 3 Nervous system diseases, 4 Eye diseases, 2 Respiratory system diseases, 2 Circulatory system diseases, 6 Liver, Gallbladder and Pancreas diseases, 2 Gastrointestinal system diseases, 3 Muscle, Bones and joint diseases, 3 Urinary system diseases, 2 Reproductive system diseases). This review also prospects the molecular mechanism targets of autoimmune diseases from the multi-molecular level and multi-dimensional analysis combined with single-cell multi-omics sequencing technology (such as scRNA-seq, Single cell ATAC-seq and single cell immune group library sequencing), which provides a reference for further exploring the pathogenesis and marker screening of autoimmune diseases and autoimmune inflammatory diseases in the future.

Cervical cancer heterogeneity: a constant battle against viruses and drugs

Cervical cancer is the first identified human papillomavirus (HPV) associated cancer and the most promising malignancy to be eliminated. However, the ever-changing virus subtypes and acquired multiple drug resistance continue to induce failure of tumor prevention and treatment. The exploration of cervical cancer heterogeneity is the crucial way to achieve effective prevention and precise treatment. Tumor heterogeneity exists in various aspects including the immune clearance of viruses, tumorigenesis, neoplasm recurrence, metastasis and drug resistance. Tumor development and drug resistance are often driven by potential gene amplification and deletion, not only somatic genomic alterations, but also copy number amplifications, histone modification and DNA methylation. Genomic rearrangements may occur by selection effects from chemotherapy or radiotherapy which exhibits genetic intra-tumor heterogeneity in advanced cervical cancers. The combined application of cervical cancer therapeutic vaccine and immune checkpoint inhibitors has become an effective strategy to address the heterogeneity of treatment. In this review, we will integrate classic and recently updated epidemiological data on vaccination rates, screening rates, incidence and mortality of cervical cancer patients worldwide aiming to understand the current situation of disease prevention and control and identify the direction of urgent efforts. Additionally, we will focus on the tumor environment to summarize the conditions of immune clearance and gene integration after different HPV infections and to explore the genomic factors of tumor heterogeneity. Finally, we will make a thorough inquiry into completed and ongoing phase III clinical trials in cervical cancer and summarize molecular mechanisms of drug resistance among chemotherapy, radiotherapy, biotherapy, and immunotherapy.

Forward single-cell sequencing into clinical application: Understanding of cancer microenvironment at single-cell solution

Single‐cell RNA sequencing (scRNA‐seq) is considered an important approach to understand the molecular mechanisms of cancer microenvironmental functions and has the potential for clinical and translational discovery and development. The recent concerns on the impact of scRNA‐seq for clinical practice are whether scRNA can be applied as a routine measurement of clinical biochemistry to assist in clinical decision‐making for diagnosis and therapy. Pushing single‐cell sequencing into clinical application is one of the important missions for clinical and translational medicine (CTM), although there still are a large number of challenges to be overcome. The present Editorial as one of serials aims at overviewing the history of scRNA‐seq publications in CTM, sharing the understanding and consideration of the cancer microenvironment at the single‐cell solution and emphasising the objective of translating scRNA‐seq into clinical application. The dynamic characteristics and patterns of single‐cell identity, regulatory networks, and intercellular communication play decisive roles in the properties of the microenvironment, malignancy and migrative capacity of cancer cells, and defensive capacity of immune cells. The microenvironmental single‐cell transcriptomic profiles and cell clusters defined by scRNA‐seq have great value for exploring the molecular mechanisms of diseases and predicting cell sensitivities to therapy and patient prognosis.

Identification and validation of a seven-gene prognostic marker in colon cancer based on single-cell transcriptome analysis

Colon cancer (CC) is one of the most commonly diagnosed tumours worldwide. Single‐cell RNA sequencing (scRNA‐seq) can accurately reflect the heterogeneity within and between tumour cells and identify important genes associated with cancer development and growth. In this study, scRNA‐seq was used to identify reliable prognostic biomarkers in CC. ScRNA‐seq data of CC before and after 5‐fluorouracil treatment were first downloaded from the Gene Expression Omnibus database. The data were pre‐processed, and dimensionality reduction was performed using principal component analysis and t‐distributed stochastic neighbour embedding algorithms. Additionally, the transcriptome data, somatic variant data, and clinical reports of patients with CC were obtained from The Cancer Genome Atlas database. Seven key genes were identified using Cox regression analysis and the least absolute shrinkage and selection operator method to establish signatures associated with CC prognoses. The identified signatures were validated on independent datasets, and somatic mutations and potential oncogenic pathways were further explored. Based on these features, gene signatures, and other clinical variables, a more effective predictive model nomogram for patients with CC was constructed, and a decision curve analysis was performed to assess the utility of the nomogram. A prognostic signature consisting of seven prognostic‐related genes, including CAV2, EREG, NGFRAP1, WBSCR22, SPINT2, CCDC28A, and BCL10, was constructed and validated. The proficiency and credibility of the signature were verified in both internal and external datasets, and the results showed that the seven‐gene signature could effectively predict the prognosis of patients with CC under various clinical conditions. A nomogram was then constructed based on features such as the RiskScore, patients' age, neoplasm stage, and tumor (T), nodes (N), and metastases (M) classification, and the nomogram had good clinical utility. Higher RiskScores were associated with a higher tumour mutational burden, which was confirmed to be a prognostic risk factor. Gene set enrichment analysis showed that high‐score groups were enriched in ‘cytoplasmic DNA sensing’, ‘Extracellular matrix receptor interactions’, and ‘focal adhesion’, and low‐score groups were enriched in ‘natural killer cell‐mediated cytotoxicity’, and ‘T‐cell receptor signalling pathways’, among other pathways. A robust seven‐gene marker for CC was identified based on scRNA‐seq data and was validated in multiple independent cohort studies. These findings provide a new potential marker to predict the prognosis of patients with CC.

Circulating tumour cells in the -omics era: how far are we from achieving the 'singularity'?

Over the past decade, cancer diagnosis has expanded to include liquid biopsies in addition to tissue biopsies. Liquid biopsies can result in earlier and more accurate diagnosis and more effective monitoring of disease progression than tissue biopsies as samples can be collected frequently. Because of these advantages, liquid biopsies are now used extensively in clinical care. Liquid biopsy samples are analysed for circulating tumour cells (CTCs), cell-free DNA, RNA, proteins and exosomes. CTCs originate from the tumour, play crucial roles in metastasis and carry information on tumour heterogeneity. Multiple single-cell omics approaches allow the characterisation of the molecular makeup of CTCs. It has become evident that CTCs are robust biomarkers for predicting therapy response, clinical development of metastasis and disease progression. This review describes CTC biology, molecular heterogeneity within CTCs and the involvement of EMT in CTC dynamics. In addition, we describe the single-cell multi-omics technologies that have provided insights into the molecular features within therapy-resistant and metastasis-prone CTC populations. Functional studies coupled with integrated multi-omics analyses have the potential to identify therapies that can intervene the functions of CTCs.

Genome profiles of pathologist-defined cell clusters by multiregional LCM and G&T-seq in one triple-negative breast cancer patient

Pathological examination is the gold standard for cancer diagnosis, and breast tumor cells are often found in clusters. We report a case study on one triple-negative breast cancer (TNBC) patient, analyzing tumor development, metastasis, and prognosis with simultaneous DNA and RNA sequencing of pathologist-defined cell clusters from multiregional frozen sections. The cell clusters are isolated by laser capture microdissection (LCM) from primary tumor tissue, lymphatic vessels, and axillary lymph nodes. Data are reported for a total of 97 cell clusters. A combination of tumor cell-cluster clonality and phylogeny reveals 3 evolutionarily distinct pathways for this patient, each associated with a unique mRNA signature, and each correlated with disparate survival outcomes. Hub gene analysis indicates that extensive downregulation of ribosomal protein mRNA is a potential marker of poor prognosis in breast cancer.

Pathologically diverse cell clusters share genomic and transcriptomic profiles

Transcriptome-defined clones are more complex than genome-defined clones

Three distinct pathways were inferred, each with disparate survival outcomes

Lower expression of ribosomal proteins may be an indicator of poor prognosis

Cancer Explant Models

Overcoming the challenges of understanding and treating cancer requires reliable patient-derived models of cancer (PDMCs). For decades, cancer research and therapeutic development relied primarily on cancer cell lines because of their prevalence, reproducibility, and simplicity to maintain. However, findings from research conducted in cell lines are rarely recapitulated in vivo and seldom directly translatable to patients. The tumor microenvironment (TME), tumor-stromal interactions, and associations with host immune cells produce profound changes in tumor phenotype and complexity not captured in traditional monolayer cell culture. In this chapter, we present various cancer explant models and discuss their applicability based on specific research aims. We discuss the appropriateness of these models for basic science questions, drug screening/development, and for personalized, precision medicine. We also consider logistical factors such as resource cost, technical difficulty, and accessibility. We finish this chapter with a practical guide intended to help the reader select the cancer explant model system(s) that best address their research aims.

Development of a Prognostic Signature Based on Single-Cell RNA Sequencing Data of Immune Cells in Intrahepatic Cholangiocarcinoma

Analysis of single-cell RNA sequencing (scRNA-seq) data of immune cells from the tumor microenvironment (TME) may identify tumor progression biomarkers. This study was designed to investigate the prognostic value of differentially expressed genes (DEGs) in intrahepatic cholangiocarcinoma (ICC) using scRNA-seq. We downloaded the scRNA-seq data of 33,991 cell samples, including 17,090 ICC cell samples and 16,901 ICC adjacent tissue cell samples regarded as normal cells. scRNA-seq data were processed and classified into 20 clusters. The immune cell clusters were extracted and processed again in the same way, and each type of immune cells was divided into several subclusters. In total, 337 marker genes of macrophages and 427 marker genes of B cells were identified by comparing ICC subclusters with normal subclusters. Finally, 659 DEGs were obtained by merging B cell and macrophage marker genes. ICC sample clinical information and gene expression data were downloaded. A nine-prognosis-related-gene (PRG) signature was established by analyzing the correlation between DEGs and overall survival in ICC. The robustness and validity of the signature were verified. Functional enrichment analysis revealed that the nine PRGs were mainly involved in tumor immune mechanisms. In conclusion, we established a PRG signature based on scRNA-seq data from immune cells of patients with ICC. This PRG signature not only reflects the TME immune status but also provides new biomarkers for ICC prognosis.

An ultra-sensitive T-cell receptor detection method for TCR-Seq and RNA-Seq data

MOTIVATION

T-cell receptors (TCRs) function to recognize antigens and play vital roles in T-cell immunology. Surveying TCR repertoires by characterizing complementarity-determining region 3 (CDR3) is a key issue. Due to the high diversity of CDR3 and technological limitation, accurate characterization of CDR3 repertoires remains a great challenge.

RESULTS

We propose a computational method named CATT for ultra-sensitive and precise TCR CDR3 sequences detection. CATT can be applied on TCR sequencing, RNA-Seq and single-cell TCR(RNA)-Seq data to characterize CDR3 repertoires. CATT integrated de Bruijn graph-based micro-assembly algorithm, data-driven error correction model and Bayesian inference algorithm, to self-adaptively and ultra-sensitively characterize CDR3 repertoires with high performance. Benchmark results of datasets from in silico and experimental data demonstrated that CATT showed superior recall and precision compared with existing tools, especially for data with short read length and small size and single-cell sequencing data. Thus, CATT will be a useful tool for TCR analysis in researches of cancer and immunology.

AVAILABILITY AND IMPLEMENTATION

http://bioinfo.life.hust.edu.cn/CATT or https://github.com/GuoBioinfoLab/CATT.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Detecting cancer metastasis and accompanying protein biomarkers at single cell levels using a 3D-printed microfluidic immunoarray

A low-cost microfluidic microarray capable of lysing cells and quantifying proteins released after lysis was designed and 3D-printed. The array lyses cells on-chip in lysis buffer augmented with a 2s pulse of a sonic cell disruptor. Detection of desmoglein 3 (DSG3), a metastatic biomarker for head and neck squamous cell carcinoma (HNSCC), along with two accompanying HNSCC biomarkers from a single cell lysate of oral cancer cell cultures was demonstrated. A lysis chamber and reagent compartments deliver sample and reagents into detection chambers decorated with capture antibodies immobilized onto inner walls coated with a highly swollen 3D chitosan hydrogel film. Sandwich immunoassays are achieved when captured analytes labeled with biotinylated secondary antibodies, which then capture streptavidin-poly [horse radish peroxidase] (Poly-HRP). Subsequent delivery of super-bright femto-luminol with H2O2 generates chemiluminescence captured with a CCD camera. DSG3 is membrane-bound protein in HNSCC cells of invaded lymph nodes, vascular endothelial growth factor-A (VEGF-A), vascular endothelial growth factor-C (VEGF-C) were positive controls overexpressed into the HNSCC culture medium. Beta-tubulin (β-Tub) was used as a loading control to estimate the number of cells in analyzed samples. Limits of detection (LOD) were 0.10 fg/mL for DSG3, and 0.20 fg/mL for VEGF-A, VEGF-C and β-Tub. Three orders of magnitude semilogarithmic dynamic ranges were achieved. VEGF-A showed high in-cell expression, but VEGF-C had low levels inside cells. The very low LODs enabled quantifying these proteins released from single cells. Strong correlation between results from on-chip cell lysis, conventional off-line lysis and ELISA confirmed accuracy.

Tumor heterogeneity in muscle-invasive bladder cancer

Muscle-invasive bladder cancer (MIBC), a highly heterogeneous disease, shows genomic instability and a high mutation rate. Clinical outcomes are variable and responses to conventional chemotherapy differ among patients (due to inter-patient tumor heterogeneity and inter-tumor heterogeneity) and even within each individual tumor (intra-tumor heterogeneity). Emerging evidence indicates that tumor heterogeneity may play an important role in cancer progression, resistance to therapy, and metastasis. Comprehensive molecular subtyping classifies MIBC into distinct categories that have potential to guide prognosis, patient stratification, and treatment. Genomic characterization of time-series analyses at the single cell level, and of cell-free circulating tumor DNA or circulating tumor cells, are emerging technologies that enable dissection of the complex clonal architecture of MIBC. This review provides insight into the clinical significance of the molecular mechanisms underlying heterogeneity, focusing on inter- and intra-tumor heterogeneity, with special emphasis on molecular classification and methods used to analyze the complex patterns involved.

Single-Cell Transcriptomic Analysis Identifies a Unique Pulmonary Lymphangioleiomyomatosis Cell

Rationale: Lymphangioleiomyomatosis (LAM) is a metastatic neoplasm of reproductive-age women associated with mutations in tuberous sclerosis complex genes. LAM causes cystic remodeling of the lung and progressive respiratory failure. The sources and cellular characteristics of LAM cells underlying disease pathogenesis remain elusive.Objectives: Identification and characterization of LAM cells in human lung and uterus using a single-cell approach.Methods: Single-cell and single-nuclei RNA sequencing on LAM (n = 4) and control (n = 7) lungs, immunofluorescence confocal microscopy, ELISA, and aptamer proteomics were used to identify and validate LAMCORE cells and secreted biomarkers, predict cellular origins, and define molecular and cellular networks in LAM.Measurements and Main Results: A unique cell type termed LAMCORE was identified, which was distinct from, but closely related to, lung mesenchymal cells. LAMCORE cells expressing signature genes included known LAM markers such as PMEL, FIGF, CTSK, and MLANA and novel biomarkers validated by aptamer screening, ELISA, and immunofluorescence microscopy. LAM cells in lung and uterus are morphologically indistinguishable and share similar gene expression profiles and biallelic TSC2 mutations, supporting a potential uterine origin for the LAMCORE cell. Effects of LAM on resident pulmonary cell types indicated recruitment and activation of lymphatic endothelial cells.Conclusions: A unique population of LAMCORE cells was identified in lung and uterus of patients with LAM, sharing close transcriptomic identity. LAM cell selective markers, secreted biomarkers, and the predicted cellular molecular features provide new insights into the signaling and transcriptional programs that may serve as diagnostic markers and therapeutic targets to influence the pathogenesis of LAM.

Independent evolution of cutaneous lymphoma subclones in different microenvironments of the skin

Mycosis fungoides (MF) is the most common cutaneous T-cell lymphoma. Lesions of MF are formed by hematogenous seeding the skin with polyclonal (clonotypically diverse) neoplastic T-cells which accumulate numerous mutations and display a high degree of mutational, intratumoral heterogeneity (ITH). A characteristic but poorly studied feature of MF is epidermotropism, the tendency to infiltrate skin epithelial layer (epidermis) in addition to the vascularized dermis. By sequencing the exomes of the microdissected clusters of lymphoma cells from the epidermis and the dermis, we found that those microenvironments comprised different malignant clonotypes. Subclonal structure witnessed the independent mutational evolution in the epidermis and dermis. Thus, the epidermal involvement in MF could not be explained by gradual infiltration from the dermis but was caused by a separate seeding process followed by a quasi-neutral, branched evolution. In conclusion, tissue microenvironments shape the subclonal architecture in MF leading to “ecological heterogeneity” which contributes to the total ITH. Since ITH adversely affects cancer prognosis, targeting the microenvironment may present therapeutic opportunities in MF and other cancers.

Revealing the molecular mechanism of central nervous system leukemia with single-cell technology

Central nervous system leukemia (CNSL) is a severe complication of acute leukemia, with serious consequences for life quality and expectancy. The molecular mechanism of CNSL is unclear at present. Thus, determining appropriate prevention and therapeutic strategies for CNSL remain challenging. Currently, inferences regarding gene functions are based on the measurement of average gene expression in a bulk lysate. However, leukemia cells are a heterogeneous population in which the expression of critical genes may be masked by many unrelated genes. Single-cell sequencing may therefore be the best way to explore the development of CNSL in the bone marrow and peripheral blood at diagnosis and subsequent time points, in order to detect potential targets and prevent the development of CNSL. In this review, we first discuss the possible mechanism of CNSL, then describe the heterogeneity of leukemia cells. Finally, we focus on the role of single-cell technology in preventing and treating CNSL.

Single-Cell Transcriptomic Analysis of Cardiac Progenitor Differentiation

PURPOSE OF REVIEW

Emerging single-cell RNA sequencing technologies hold great promises to boost our understanding of the heterogeneity and molecular regulation of diverse cell phenotypes during organ development. In this review, we aimed at summarizing recent advances in employing single-cell transcriptomic analysis to depict the landscape of embryonic heart development, in particular, focusing on cardiac progenitor (CP) differentiation.

RECENT FINDINGS

Recent studies unbiasedly cataloged and characterized cardiac cell types in the spatial and temporal resolution during early heart development. Pseudo-time analysis revealed a temporal continuum of the differentiation progress from embryonic day (E) 6.5 to E9.5, implicating early cardiac lineage restriction during mouse gastrulation. First and second heart field (FHF and SHF) CPs adopted different differentiation strategies and underwent distinct transcriptional regulation. Collectively, the comprehensive molecular atlases yield a rich resource for identification of the key cardiac regulators and signaling molecules within the key cardiac gene regulatory network (GRN) governing cardiac cell fate determinations. This review offers insights into the exquisite process and its regulation of CP differentiation at single-cell resolution. As single-cell technologies continuously grow and evolve, computational integration of multimodal single-cell data with well-designed experimental validation promises to further delineate molecular basis in deploying cardiac progenitors of distinct sources with anatomical information.

Non-templated addition and template switching by Moloney murine leukemia virus (MMLV)-based reverse transcriptases co-occur and compete with each other

Single-cell RNA-Seq (scRNA-Seq) has led to an unprecedented understanding of gene expression and regulation in individual cells. Many scRNA-Seq approaches rely upon the template switching property of Moloney murine leukemia virus (MMLV)-type reverse transcriptases. Template switching is believed to happen in a sequential process involving nontemplated addition of three protruding nucleotides (+CCC) to the 3′-end of the nascent cDNA, which can then anneal to the matching rGrGrG 3′-end of the template-switching oligo (TSO), allowing the reverse transcriptase (RT) to switch templates and continue copying the TSO sequence. In this study, we present a detailed analysis of template switching biases with respect to the RNA template, specifically of the role of the sequence and nature of its 5′-end (capped versus noncapped) in these biases. Our findings confirmed that the presence of a 5′-m⁷G cap enhances template switching efficiency. We also profiled the composition of the nontemplated addition in the absence of TSO and observed that the 5′-end of RNA template influences the terminal transferase activity of the RT. Furthermore, we found that designing new TSOs that pair with the most common nontemplated additions did little to improve template switching efficiency. Our results provide evidence suggesting that, in contrast to the current understanding of the template switching process, nontemplated addition and template switching are concurrent and competing processes.

Single-Cell Analysis of Circulating Tumor Cells: How Far Have We Come in the -Omics Era?

Tumor cells detach from the primary tumor or metastatic sites and enter the peripheral blood, often causing metastasis. These cells, named Circulating Tumor Cells (CTCs), display the same spatial and temporal heterogeneity as the primary tumor. Since CTCs are involved in tumor progression, they represent a privileged window to disclose mechanisms of metastases, while -omic analyses at the single-cell level allow dissection of the complex relationships between the tumor subpopulations and the surrounding normal tissue. However, in addition to reporting the proof of concept that we can query CTCs to reveal tumor evolution throughout the continuum of treatment for early detection of resistance to therapy, the scientific literature has also been highlighting the disadvantages of CTCs, which hampers a routine use of this approach in clinical practice. To date, an increasing number of CTC technologies, as well as -omics methods, have been employed, mostly lacking strong comparative analyses. The rarity of CTCs also represents a major challenge, because there is no consensus regarding the minimal criteria necessary and sufficient to define an event as CTC; moreover, we cannot often compare data from of one study with that of another. Finally, the availability of an individual tumor profile undermines the traditional histology-based treatment. Applying molecular data for patient benefit implies a collective effort by biologists, bioengineers, and clinicians, to create tools to interpret molecular data and manage precision medicine in every single patient. Herein, we focus on the most recent findings in CTC −omics to learn how far we have come.

Targeting the Versatile Wnt/β-Catenin Pathway in Cancer Biology and Therapeutics: From Concept to Actionable Strategy

This expert review offers a critical synthesis of the latest insights and approaches at targeting the Wnt/β-catenin pathway in various cancers such as colorectal cancer, melanoma, leukemia, and breast and lung cancers. Notably, from organogenesis to cancer, the Wnt/β-catenin signaling displays varied and highly versatile biological functions in animals, with virtually all tissues requiring the Wnt/β-catenin signaling in one way or the other. Aberrant expression of the members of the Wnt/β-catenin has been implicated in many pathological conditions, particularly in human cancers. Mutations in the Wnt/β-catenin pathway genes have been noted in diverse cancers. Biochemical and genetic data support the idea that inhibition of Wnt/β-catenin signaling is beneficial in cancer therapeutics. The interaction of this important pathway with other signaling systems is also noteworthy, but remains as an area for further research and discovery. In addition, formation of different complexes by components of the Wnt/β-catenin pathway and the precise roles of these complexes in the cytoplasmic milieu are yet to be fully elucidated. This article highlights the latest medical technologies in imaging, single-cell omics, use of artificial intelligence (e.g., machine learning techniques), genome sequencing, quantum computing, molecular docking, and computational softwares in modeling interactions between molecules and predicting protein-protein and compound-protein interactions pertinent to the biology and therapeutic value of the Wnt/β-catenin signaling pathway. We discuss these emerging technologies in relationship to what is currently needed to move from concept to actionable strategies in translating the Wnt/β-catenin laboratory discoveries to Wnt-targeted cancer therapies and diagnostics in the clinic.

The transcriptome difference between colorectal tumor and normal tissues revealed by single-cell sequencing

The previous cancer studies were difficult to reproduce since the tumor tissues were analyzed directly. But the tumor tissues were actually a mixture of different cancer cells. The transcriptome of single-cell was much robust than the transcriptome of a mixed tissue. The single-cell transcriptome had much smaller variance. In this study, we analyzed the single-cell transcriptome of 272 colorectal cancer (CRC) epithelial cells and 160 normal epithelial cells and identified 342 discriminative transcripts using advanced machine learning methods. The most discriminative transcripts were LGALS4, PHGR1, C15orf48, HEPACAM2, PERP, FABP1, FCGBP, MT1G, TSPAN1 and CKB. We further clustered the 342 transcripts into two categories. The upregulated transcripts in CRC epithelial cells were significantly enriched in Ribosome, Protein processing in endoplasmic reticulum, Antigen processing and presentation and p53 signaling pathway. The downregulated transcripts in CRC epithelial cells were significantly enriched in Mineral absorption, Aldosterone-regulated sodium reabsorption and Oxidative phosphorylation pathways. The biological analysis of the discriminative transcripts revealed the possible mechanism of colorectal cancer.

Cellular plasticity and metastasis in breast cancer: a pre- and post-malignant problem

As a field we have made tremendous strides in treating breast cancer, with a decline in the past 30 years of overall breast cancer mortality. However, this progress is met with little affect once the disease spreads beyond the primary site. With a 5-year survival rate of 22%, 10-year of 13%, for those patients with metastatic breast cancer (mBC), our ability to effectively treat wide spread disease is minimal. A major contributing factor to this ineffectiveness is the complex make-up, or heterogeneity, of the primary site. Within a primary tumor, secreted factors, malignant and pre-malignant epithelial cells, immune cells, stromal fibroblasts and many others all reside alongside each other creating a dynamic environment contributing to metastasis. Furthermore, heterogeneity contributes to our lack of understanding regarding the cells' remarkable ability to undergo epithelial/non-cancer stem cell (CSC) to mesenchymal/CSC (E-M/CSC) plasticity. The enhanced invasion & motility, tumor-initiating potential, and acquired therapeutic resistance which accompanies E-M/CSC plasticity implicates a significant role in metastasis. While most work trying to understand E-M/CSC plasticity has been done on malignant cells, recent evidence is emerging concerning the ability for pre-malignant cells to undergo E-M/CSC plasticity and contribute to the metastatic process. Here we will discuss the importance of E-M/CSC plasticity within malignant and pre-malignant populations of the tumor. Moreover, we will discuss how one may potentially target these populations, ultimately disrupting the metastatic cascade and increasing patient survival for those with mBC.

Leveraging Single-Cell RNA Sequencing Experiments to Model Intratumor Heterogeneity

PURPOSE

Many cancers can be treated with targeted therapy. Almost inevitably, tumors develop resistance to targeted therapy, either from pre-existence or by evolving new genotypes and traits. Intratumor heterogeneity serves as a reservoir for resistance, which often occurs as a result of the selection of minor cellular subclones. On the level of gene expression, clonal heterogeneity can only be revealed using high-dimensional single-cell methods. We propose using a general diversity index (GDI) to quantify heterogeneity on multiple scales and relate it to disease evolution.

MATERIALS AND METHODS

We focused on individual patient samples that were probed with single-cell RNA (scRNA) sequencing to describe heterogeneity. We developed a pipeline to analyze single-cell data via sample normalization, clustering, and mathematical interpretation using a generalized diversity measure, as well as to exemplify the utility of this platform using single-cell data.

RESULTS

We focused on three sources of patient scRNA sequencing data: two healthy bone marrow (BM) donors, two patients with acute myeloid leukemia-each sampled before and after BM transplantation, four samples of presorted lineages-and six patients with lung carcinoma with multiregion sampling. While healthy/normal samples scored low in diversity overall, GDI further quantified the ways in which these samples differed. Whereas a widely used Shannon diversity index sometimes reveals fewer differences, GDI exhibits differences in the number of potential key drivers or clonal richness. Comparison of pre- and post-BM transplantation acute myeloid leukemia samples did not reveal differences in heterogeneity, although biological differences can exist.

CONCLUSION

GDI can quantify cellular heterogeneity changes across a wide spectrum, even when standard measures, such as the Shannon index, do not. Our approach can be widely applied to quantify heterogeneity across samples and conditions.

Moonshot Objectives: Catalyze New Scientific Breakthroughs-Proteogenomics

Breaking down the silos between disciplines to accelerate the pace of cancer research is a key paradigm for the Cancer Moonshot. Molecular analyses of cancer biology have tended to segregate between a focus on nucleic acids-DNA, RNA, and their modifications-and a focus on proteins and protein function. Proteogenomics represents a fusion of those two approaches, leveraging the strengths of each to provide a more integrated vision of the flow of information from DNA to RNA to protein and eventually function at the molecular level. Proteogenomic studies have been incorporated into multiple activities associated with the Cancer Moonshot, demonstrating substantial added value. Innovative study designs integrating genomic, transcriptomic, and proteomic data, particularly those using clinically relevant samples and involving clinical trials, are poised to provide new insights regarding cancer risk, progression, and response to therapy.

Single-Cell Genomics

BACKGROUND

Single-cell genomics is an approach to investigate cell heterogeneity and to identify new molecular features correlated with clinical outcomes. This approach allows identification of the complexity of cell diversity in a sample without the loss of information that occurs when multicellular or bulk tissue samples are analyzed.

CONTENT

The first single-cell RNA-sequencing study was published in 2009, and since then many more studies and single-cell sequencing methods have been published. These studies have had a major impact on several fields, including microbiology, neurobiology, cancer, and developmental biology. Recently, improvements in reliability and the development of commercial single-cell isolation platforms are opening the potential of this technology to the clinical laboratory.

SUMMARY

In this review we provide an overview of the current state of single-cell genomics. We describe opportunities in clinical research and medical applications.

Barcoding reveals complex clonal behavior in patient-derived xenografts of metastatic triple negative breast cancer

Primary triple negative breast cancers (TNBC) are prone to dissemination but sub-clonal relationships between tumors and resulting metastases are poorly understood. Here we use cellular barcoding of two treatment-naïve TNBC patient-derived xenografts (PDXs) to track the spatio-temporal fate of thousands of barcoded clones in primary tumors, and their metastases. Tumor resection had a major impact on reducing clonal diversity in secondary sites, indicating that most disseminated tumor cells lacked the capacity to 'seed', hence originated from 'shedders' that did not persist. The few clones that continued to grow after resection i.e. 'seeders', did not correlate in frequency with their parental clones in primary tumors. Cisplatin treatment of one BRCA1-mutated PDX model to non-palpable levels had a surprisingly minor impact on clonal diversity in the relapsed tumor yet purged 50% of distal clones. Therefore, clonal features of shedding, seeding and drug resistance are important factors to consider for the design of therapeutic strategies.

CRX Expression in Pluripotent Stem Cell-Derived Photoreceptors Marks a Transplantable Subpopulation of Early Cones

Death of photoreceptors is a common cause of age-related and inherited retinal dystrophies, and thus their replenishment from renewable stem cell sources is a highly desirable therapeutic goal. Human pluripotent stem cells provide a useful cell source in view of their limitless self-renewal capacity and potential to not only differentiate into cells of the retina but also self-organize into tissue with structure akin to the human retina as part of three-dimensional retinal organoids. Photoreceptor precursors have been isolated from differentiating human pluripotent stem cells through application of cell surface markers or fluorescent reporter approaches and shown to have a similar transcriptome to fetal photoreceptors. In this study, we investigated the transcriptional profile of CRX-expressing photoreceptor precursors derived from human pluripotent stem cells and their engraftment capacity in an animal model of retinitis pigmentosa (Pde6brd1), which is characterized by rapid photoreceptor degeneration. Single cell RNA-Seq analysis revealed the presence of a dominant cell cluster comprising 72% of the cells, which displayed the hallmarks of early cone photoreceptor expression. When transplanted subretinally into the Pde6brd1 mice, the CRX⁺ cells settled next to the inner nuclear layer and made connections with the inner neurons of the host retina, and approximately one-third of them expressed the pan cone marker, Arrestin 3, indicating further maturation upon integration into the host retina. Together, our data provide valuable molecular insights into the transcriptional profile of human pluripotent stem cells-derived CRX⁺ photoreceptor precursors and indicate their usefulness as a source of transplantable cone photoreceptors. Stem Cells 2019;37:609-622.

Design of Peptide-Based Nanovaccines Targeting Leading Antigens From Gynecological Cancers to Induce HLA-A2.1 Restricted CD8+ T Cell Responses

Gynecological cancers are a leading cause of mortality in women. CD8⁺ T cell immunity largely correlates with enhanced survival, whereas inflammation is associated with poor prognosis. Previous studies have shown polystyrene nanoparticles (PSNPs) are biocompatible, do not induce inflammation and when used as vaccine carriers for model peptides induce CD8⁺ T cell responses. Herein we test the immunogenicity of 24 different peptides, from three leading vaccine target proteins in gynecological cancers: the E7 protein of human papilloma virus (HPV); Wilms Tumor antigen 1 (WT1) and survivin (SV), in PSNP conjugate vaccines. Of relevance to vaccine development was the finding that a minimal CD8⁺ T cell peptide epitope from HPV was not able to induce HLA-A2.1 specific CD8⁺ T cell responses in transgenic humanized mice using conventional adjuvants such as CpG, but was nevertheless able to generate strong immunity when delivered as part of a specific longer peptide conjugated to PSNPs vaccines. Conversely, in most cases, when the minimal CD8⁺ T cell epitopes were able to induce immune responses (with WT1 or SV super agonists) in CpG, they also induced responses when conjugated to PSNPs. In this case, extending the sequence around the CD8⁺ T cell epitope, using the natural protein context, or engineering linker sequences proposed to enhance antigen processing, had minimal effects in enhancing or changing the cross-reactivity pattern induced by the super agonists. Nanoparticle approaches, such as PSNPs, therefore may offer an alternative vaccination strategy when conventional adjuvants are unable to elicit the desired CD8⁺ T cell specificity. The findings herein also offer sequence specific insights into peptide vaccine design for nanoparticle-based vaccine carriers.

Single-Cell Imaging of Metastatic Potential of Cancer Cells

Molecular imaging of metastatic “potential” is an unvanquished challenge. To engineer biosensors that can detect and measure the metastatic “potential” of single living cancer cells, we carried out a comprehensive analysis of the pan-cancer phosphoproteome to search for actin remodelers required for cell migration, which are enriched in cancers but excluded in normal cells. Only one phosphoprotein emerged, tyr-phosphorylated CCDC88A (GIV/Girdin), a bona fide metastasis-related protein across a variety of solid tumors. We designed multi-modular biosensors that are partly derived from GIV, and because GIV integrates prometastatic signaling by multiple oncogenic receptors, we named them “‘integrators of metastatic potential (IMP).” IMPs captured the heterogeneity of metastatic potential within primary lung and breast tumors at steady state, detected those few cells that have acquired the highest metastatic potential, and tracked their enrichment during metastasis. These findings provide proof of concept that IMPs can measure the diversity and plasticity of metastatic potential of tumor cells in a sensitive and unbiased way.

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Phosphoproteomes of cancers predicted a putative metastasis-specific phosphoevent

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FRET-based biosensor designed to assess this phosphoevent in living cells

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Biosensor tracks the diversity and plasticity of metastatic potential of cancer cells

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These sensors could direct drug efficacy testing against the most sinister cancer cells

Centrosome aberrations and chromosome instability contribute to tumorigenesis and intra-tumor heterogeneity

Centrosomes serve as the major microtubule organizing centers in cells and thereby contribute to cell shape, polarity, and motility. Also, centrosomes ensure equal chromosome segregation during mitosis. Centrosome aberrations arise when the centrosome cycle is deregulated, or as a result of cytokinesis failure. A long-standing postulate is that centrosome aberrations are involved in the initiation and progression of cancer. However, this notion has been a subject of controversy because until recently the relationship has been correlative. Recently, it was shown that numerical or structural centrosome aberrations can initiate tumors in certain tissues in mice, as well as invasion. Particularly, we will focus on centrosome amplification and chromosome instability as drivers of intra-tumor heterogeneity and their consequences in cancer. We will also discuss briefly the controversies surrounding this theory to highlight the fact that the role of both centrosome amplification and chromosome instability in cancer is highly context-dependent. Further, we will discuss single-cell sequencing as a novel technique to understand intra-tumor heterogeneity and some therapeutic approaches to target chromosome instability.

Comprehensive Mutation and Copy Number Profiling in Archived Circulating Breast Cancer Tumor Cells Documents Heterogeneous Resistance Mechanisms

Addressing drug resistance is a core challenge in cancer research, but the degree of heterogeneity in resistance mechanisms in cancer is unclear. In this study, we conducted next-generation sequencing (NGS) of circulating tumor cells (CTC) from patients with advanced cancer to assess mechanisms of resistance to targeted therapy and reveal opportunities for precision medicine. Comparison of the genomic landscapes of CTCs and tissue metastases is complicated by challenges in comprehensive CTC genomic profiling and paired tissue acquisition, particularly in patients who progress after targeted therapy. Thus, we assessed by NGS somatic mutations and copy number alterations (CNA) in archived CTCs isolated from patients with metastatic breast cancer who were enrolled in concurrent clinical trials that collected and analyzed CTCs and metastatic tissues. In 76 individual and pooled informative CTCs from 12 patients, we observed 85% concordance in at least one or more prioritized somatic mutations and CNA between paired CTCs and tissue metastases. Potentially actionable genomic alterations were identified in tissue but not CTCs, and vice versa. CTC profiling identified diverse intra- and interpatient molecular mechanisms of endocrine therapy resistance, including loss of heterozygosity in individual CTCs. For example, in one patient, we observed CTCs that were either wild type for ESR1 (n = 5/32), harbored the known activating ESR1 p.Y537S mutation (n = 26/32), or harbored a novel ESR1 p.A569S (n = 1/32). ESR1 p.A569S was modestly activating in vitro, consistent with its presence as a minority circulating subclone. Our results demonstrate the feasibility and potential clinical utility of comprehensive profiling of archived fixed CTCs. Tissue and CTC genomic assessment are complementary, and precise combination therapies will likely be required for effective targeting in advanced breast cancer patients.Significance: These findings demonstrate the complementary nature of genomic profiling from paired tissue metastasis and circulating tumor cells from patients with metastatic breast cancer. Cancer Res; 78(4); 1110-22. ©2017 AACR.

Roles of Single Cell Systems Biomedicine in Lung Diseases

Single cell sequencing is important to detect the gene heterogeneity between cells, as the part of single-cell systems biology which combines computational science, mathematical modelling and high-throughput technologies with biological function and organization in the cell. We initially arise the question how to integrate the outcomes of single-cell systems biology with clinical phenotype, interpret alterations of single-cell gene sequencing and function in patient response to therapies, and understand the significance of single-cell systems biology in the discovery and development of new molecular diagnostics and therapeutics. The present review furthermore focuses the significance of singe cell systems biology in respiratory diseases and calls the special attention from scientists who are working on single cell systems biology to improve the diagnosis and therapy for patients with lung diseases.

Application of Single Cell Sequencing in Cancer

Cancer is a heterogenetic disease at both the level of clinical manifestation and the level of the genome. Single-cell sequencing provides an unprecedented means of characterizing the intra-tumor heterogeneity and detecting and analyzing the genomes of cancer cells. These data will help to reconstruct the understanding of the evolutionary lineage of cancer cells. In the future, single-cell technology is believed to be a useful tool in diagnostic and prognostic application in oncology. The application of single cell technology in clinics will make it possible to detect cancer non-invasively at early stages and to develop precision medicine. In this chapter, we review the research and application status of the single cell technology in cancer.

Regulatory Roles of Mitochondrial Ribosome in Lung Diseases and Single Cell Biology

The mitochondria have the most vital processes in eukaryotic cells to produce ATP composed of polypeptides that are produced via ribosomes, as oxidative phosphorylation. Initially, studies regarding human mitochondrial ribosomes were performed in the model system, bovine mitochondrial ribosome, to investigate how ribosomes are biosynthesized and evolved as well as what their structure and function are. Advances in X-ray crystallography have led to dramatic progresses in structural studies of the ribosome. In recent years, there has been a growing interest in the properties of the mitochondrial ribosome. Although one of its main functions is the production of ATP, it was also linked to multiple diseases. A key area that remains unexplored and requires investigation and exploration is how mitochondrial ribosomal RNA (mt-rRNA) variations can affect the mitochondrial ribosomes in developing disease. This review summarizes the structure, elements, functions, and regulatory roles in associated diseases. With the continuous development of technology, studies on the mechanism of mitochondrial ribosome related diseases are crucial, in order to identify methods of prevention and treatment of these disorders.

Chimeric antigen receptor-T cell therapy for solid tumors require new clinical regimens

INTRODUCTION

Chimeric antigen receptor modified T cell (CAR-T) therapy has achieved encouraging breakthroughs in the treatment of hematological malignancies. Nevertheless, this success has not yet been extrapolated to solid tumors. This review focuses on new clinical regimens that could improve the therapeutic efficacy of CAR-T in solid tumors. Areas covered: Herein, the authors reviewed recent clinical trials using CAR-T therapies for the treatment of solid tumors. Specifically, this review covered the following areas: (1) the current status of CAR-T cells in the treatment of solid tumors; (2) the major factors constraining the efficacy of CAR-T cells in solid tumors; and (3) opinions regarding the future of CAR-T as a treatment for solid tumors. Expert commentary: While some recent studies have shown promising results, the ultimate success of CAR-T therapies in solid tumor patients will require the following improvements to clinical regimens: (1) local delivery of CAR-T cells; (2) combination of CAR-T cells with chemotherapeutic drugs to treat metastatic tumors; (3) combination of CAR-T with immune checkpoint inhibitors; (4) combination therapy using CAR-T cells targeting two different antigens; and (5) the use of CAR-T as a strategy to prevent tumor recurrence and metastasis after radical resection.