Unravelling biology and shifting paradigms in cancer with single-cell sequencing

Emerging Frontiers in the Study of Molecular Evolution

A collection of the editors of Journal of Molecular Evolution have gotten together to pose a set of key challenges and future directions for the field of molecular evolution. Topics include challenges and new directions in prebiotic chemistry and the RNA world, reconstruction of early cellular genomes and proteins, macromolecular and functional evolution, evolutionary cell biology, genome evolution, molecular evolutionary ecology, viral phylodynamics, theoretical population genomics, somatic cell molecular evolution, and directed evolution. While our effort is not meant to be exhaustive, it reflects research questions and problems in the field of molecular evolution that are exciting to our editors.

Next-Generation Sequencing of Advanced GI Tumors Reveals Individual Treatment Options

PURPOSE

Precision oncology connects highly complex diagnostic procedures with patient histories to identify individualized treatment options in interdisciplinary molecular tumor boards (MTBs). Detailed data on MTB-guided treatments and outcome with a focus on advanced GI cancers have not been reported yet.

PATIENTS AND METHODS

Next-generation sequencing of tumor and normal tissue pairs was performed between April 2016 and February 2018. After identification of relevant molecular alterations, available clinical studies or in-label, off-label, or matched experimental treatment options were recommended. Follow-up data and a response assessment that was based on radiologic imaging were recorded.

RESULTS

Ninety-six patients were presented to the MTB of Tuebingen University Hospital. Sixteen (17%) showed "pathogenic" or "likely pathogenic" germline variants. Recommendations on the basis of molecular alterations or tumor mutational burden were given for 41 patients (43%). Twenty-five received the suggested drug, and 20 were evaluable for best response assessment. Three patients (15%) reached a partial response (PR), and 6 (30%), stable disease (SD), whereas 11 (55%) had tumor progression (progressive disease). Median progression-free survival (PFS) for all treated and evaluable patients was 2.8 months (range, 1.0-9.0 months), and median overall survival (OS) of all treated patients was 5.2 months (range, 0.1 months to not reached). Patients with SD for ≥ 3 months or PR compared with progressive disease showed both a statistically significant longer median PFS (7.8 months [95% CI, 4.2 to 11.4 months] v 2.2 months [95% CI, 1.5 to 2.8 months], P < .0001) and median OS (18.0 months [95% CI, 10.4 to 25.6 months] v 3.8 months [95% CI, 2.3 to 5.4 months], P < .0001).

CONCLUSION

Next-generation sequencing diagnostics of advanced GI cancers identified a substantial number of pathogenic or likely pathogenic germline variants and unique individual treatment options. Patients with PR or SD in the course of MTB-recommended treatments seemed to benefit with respect to PFS and OS.

Microfluidic Single-Cell Omics Analysis

The commonly existing cellular heterogeneity plays a critical role in biological processes such as embryonic development, cell differentiation, and disease progress. Single-cell omics-based heterogeneous studies have great significance for identifying different cell populations, discovering new cell types, revealing informative cell features, and uncovering significant interrelationships between cells. Recently, microfluidics has evolved to be a powerful technology for single-cell omics analysis due to its merits of throughput, sensitivity, and accuracy. Herein, the recent advances of microfluidic single-cell omics analysis, including different microfluidic platform designs, lysis strategies, and omics analysis techniques, are reviewed. Representative applications of microfluidic single-cell omics analysis in complex biological studies are then summarized. Finally, a few perspectives on the future challenges and development trends of microfluidic-assisted single-cell omics analysis are discussed.

Targeting peptide-decorated biomimetic lipoproteins improve deep penetration and cancer cells accessibility in solid tumor

The limited penetration of nanoparticles and their poor accessibility to cancer cell fractions in tumor remain essential challenges for effective anticancer therapy. Herein, we designed a targeting peptide-decorated biomimetic lipoprotein (termed as BL-RD) to enable their deep penetration and efficient accessibility to cancer cell fractions in a tumor, thereby improving the combinational chemo-photodynamic therapy of triple negative breast cancer. BL-RD was composed of phospholipids, apolipoprotein A1 mimetic peptide (PK22), targeting peptide-conjugated cytotoxic mertansine (RM) and photodynamic agents of DiIC18(5) (DiD). The counterpart biomimetic lipoprotein system without RM (termed as BL-D) was fabricated as control. Both BL-D and BL-RD were nanometer-sized particles with a mean diameter of less than 30 nm and could be efficiently internalized by cancer cells. After intravenous injection, they can be specifically accumulated at tumor sites. When comparing to the counterpart BL-D, BL-RD displayed superior capability to permeate across the tumor mass, extravasate from tumor vasculature to distant regions and efficiently access the cancer cell fractions in a solid tumor, thus producing noticeable depression of the tumor growth. Taken together, BL-RD can be a promising delivery nanoplatform with prominent tumor-penetrating and cancer cells-accessing capability for effective tumor therapy.

Assessing the unified airway hypothesis in children via transcriptional profiling of the airway epithelium

BACKGROUND

Emerging evidence suggests that disease vulnerability is expressed throughout the airways, the so-called unified airway hypothesis, but the evidence to support this is predominantly indirect.

OBJECTIVES

We sought to establish the transcriptomic profiles of the upper and lower airways and determine their level of similarity irrespective of airway symptoms (wheeze) and allergy.

METHODS

We performed RNA sequencing on upper and lower airway epithelial cells from 63 children with or without wheeze and accompanying atopy, using differential gene expression and gene coexpression analyses to determine transcriptional similarity.

RESULTS

We observed approximately 91% homology in the expressed genes between the 2 sites. When coexpressed genes were grouped into modules relating to biological functions, all were found to be conserved between the 2 regions, resulting in a consensus network containing 16 modules associated with ribosomal function, metabolism, gene expression, mitochondrial activity, and antiviral responses through IFN activity. Although symptom-associated gene expression changes were more prominent in the lower airway, they were reflected in nasal epithelium and included IL-1 receptor like 1, prostaglandin-endoperoxide synthase 1, CCL26, and periostin. Through network analysis we identified a cluster of coexpressed genes associated with atopic wheeze in the lower airway, which could equally distinguish atopic and nonatopic phenotypes in upper airway samples.

CONCLUSIONS

We show that the upper and lower airways are significantly conserved in their transcriptional composition, and that variations associated with disease are present in both nasal and tracheal epithelium. Findings from this study supporting a unified airway imply that clinical insight regarding the lower airway in health and disease can be gained from studying the nasal epithelium.

An evolving paradigm of cancer stem cell hierarchies: therapeutic implications

Over a decade of research has confirmed the critical role of cancer stem-like cells (CSCs) in tumor initiation, chemoresistance, and metastasis. Increasingly, CSC hierarchies have begun to be defined with some recurring themes. This includes evidence that these hierarchies are 'flexible,' with both cell state transitions and dedifferentiation events possible. These findings pose therapeutic hurdles and opportunities. Here, we review cancer stem cell hierarchies and their interactions with the tumor microenvironment. We also discuss the current therapeutic approaches designed to target CSC hierarchies and initial clinical trial results for CSC targeting agents. While cancer stem cell targeted therapies are still in their infancy, we are beginning to see encouraging results that suggest a positive outlook for CSC-targeting approaches.

An Update on Molecular Biology of Cutaneous T Cell Lymphoma

Cutaneous T cell lymphomas represent a heterogenous group of lymphoproliferative disorders defined by clonal proliferation of T cells present in the skin. The latest WHO classification in 2016 and WHO-EORTC classification in 2018 has updated the classification of these entities based on the molecular profile. Research in the field of molecular genetics of CTCL has allowed a better understanding of the biology of these tumors and has helped to identify potential targets for therapy that can be tailored to individual patients. In this review, we discuss the latest developments in the molecular profile of CTCLs including biomarkers for diagnosis, prognosis, and potential therapeutic targets. We have also touched upon the utility of various molecular diagnostic modalities. For the purpose of this review, we researched papers in PubMed indexed journals in English literature published in the past 20 years using keywords CTCL, mycosis fungoides, molecular profile, molecular diagnosis, whole genome profile, genomic landscape, TCR clonality.

Gating a Single Cell: A Label-Free and Real-Time Measurement Method for Cellular Progression

There is an ever-growing need for more advanced methods to study the response of cancer cells to new therapies. To determine cancer cells' response from a cell-mortality perspective to various cancer therapies, we report a label-free and real time method to monitor the in situ response of individual HeLa cells using a single cell gated transistor (SCGT). As a cell undergoes apoptotic cell death, it experiences changes in morphology and ion concentrations. This change is well in line with the threshold voltage of the SCGT, which has been verified by correlating the data with the cell morphologies by scanning electron microscopy and the ion-concentration analysis by inductively-coupled plasma mass spectrometry (ICPMS). This SCGT could replace patch clamps to study single cell activity via direct measurement in real time. Importantly, this SCGT can be used to study the electrical response of a single cell to stimuli that leaves the membrane intact.

Tumor Functional Heterogeneity Unraveled by scRNA-seq Technologies

Effective cancer treatment has been precluded by the presence of various forms of intratumoral complexity that drive treatment resistance and metastasis. Recent single-cell sequencing technologies are significantly facilitating the characterization of tumor internal architecture during disease progression. New applications and advances occurring at a fast pace predict an imminent broad application of these technologies in many research areas. As occurred with next-generation sequencing (NGS) technologies, once applied to clinical samples across tumor types, single-cell sequencing technologies could trigger an exponential increase in knowledge of the molecular pathways involved in cancer progression and contribute to the improvement of cancer treatment.

SiCloneFit: Bayesian inference of population structure, genotype, and phylogeny of tumor clones from single-cell genome sequencing data

Accumulation and selection of somatic mutations in a Darwinian framework result in intra-tumor heterogeneity (ITH) that poses significant challenges to the diagnosis and clinical therapy of cancer. Identification of the tumor cell populations (clones) and reconstruction of their evolutionary relationship can elucidate this heterogeneity. Recently developed single-cell DNA sequencing (SCS) technologies promise to resolve ITH to a single-cell level. However, technical errors in SCS data sets, including false-positives (FP) and false-negatives (FN) due to allelic dropout, and cell doublets, significantly complicate these tasks. Here, we propose a nonparametric Bayesian method that reconstructs the clonal populations as clusters of single cells, genotypes of each clone, and the evolutionary relationship between the clones. It employs a tree-structured Chinese restaurant process as the prior on the number and composition of clonal populations. The evolution of the clonal populations is modeled by a clonal phylogeny and a finite-site model of evolution to account for potential mutation recurrence and losses. We probabilistically account for FP and FN errors, and cell doublets are modeled by employing a Beta-binomial distribution. We develop a Gibbs sampling algorithm comprising partial reversible-jump and partial Metropolis-Hastings updates to explore the joint posterior space of all parameters. The performance of our method on synthetic and experimental data sets suggests that joint reconstruction of tumor clones and clonal phylogeny under a finite-site model of evolution leads to more accurate inferences. Our method is the first to enable this joint reconstruction in a fully Bayesian framework, thus providing measures of support of the inferences it makes.

Microfluidics-Based Biomaterials and Biodevices

The rapid development of microfluidics technology has promoted new innovations in materials science, particularly by interacting with biological systems, based on precise manipulation of fluids and cells within microscale confinements. This article reviews the latest advances in microfluidics-based biomaterials and biodevices, highlighting some burgeoning areas such as functional biomaterials, cell manipulations, and flexible biodevices. These areas are interconnected not only in their basic principles, in that they all employ microfluidics to control the makeup and morphology of materials, but also unify at the ultimate goals in human healthcare. The challenges and future development trends in biological application are also presented.

Novel and Alternative Targets Against Breast Cancer Stemness to Combat Chemoresistance

Breast cancer stem cells (BCSCs) play a vital role in tumor progression and metastasis. They are heterogeneous and inherently radio- and chemoresistant. They have the ability to self-renew and differentiate into non-BCSCs. These determinants of BCSCs including the plasticity between the mesenchymal and epithelial phenotypes often leads to minimal residual disease (MRD), tumor relapse, and therapy failure. By studying the resistance mechanisms in BCSCs, a combinatorial therapy can be formulated to co-target BCSCs and bulk tumor cells. This review addresses breast cancer stemness and molecular underpinnings of how the cancer stemness can lead to pharmacological resistance. This might occur through rewiring of signaling pathways and modulated expression of various targets that support survival and self-renewal, clonogenicity, and multi-lineage differentiation into heterogeneous bulk tumor cells following chemotherapy. We explore emerging novel and alternative molecular targets against BC stemness and chemoresistance involving survival, drug efflux, metabolism, proliferation, cell migration, invasion, and metastasis. Strategic targeting of such vulnerabilities in BCSCs may overcome the chemoresistance and increase the longevity of the metastatic breast cancer patients.

Tumor Cell Biodiversity Drives Microenvironmental Reprogramming in Liver Cancer

Cellular diversity in tumors is a key factor for therapeutic failures and lethal outcomes of solid malignancies. Here, we determined the single-cell transcriptomic landscape of liver cancer biospecimens from 19 patients. We found varying degrees of heterogeneity in malignant cells within and between tumors and diverse landscapes of tumor microenvironment (TME). Strikingly, tumors with higher transcriptomic diversity were associated with patient's worse overall survival. We found a link between hypoxia-dependent vascular endothelial growth factor expression in tumor diversity and TME polarization. Moreover, T cells from higher heterogeneous tumors showed lower cytolytic activities. Consistent results were found using bulk genomic and transcriptomic profiles of 765 liver tumors. Our results offer insight into the diverse ecosystem of liver cancer and its impact on patient prognosis.

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.

An Integrated Microfluidic Chip and Its Clinical Application for Circulating Tumor Cell Isolation and Single-Cell Analysis

Circulating tumor cells (CTCs) represent invasive tumor cell populations and provide a noninvasive solution to the clinical management and research of tumors. Characterization of CTCs at single-cell resolution enables the comprehensive understanding of tumor heterogeneity and may benefit the diagnosis and treatment of cancer patients. However, most efforts have been made on enumeration and detection of CTCs, while little focus has been directed to single-cell study. Herein, an integrated microfluidic platform for single-cell isolation and analysis was established. After validating this platform on lung cancer cell lines, we detected and isolated single CTCs from the peripheral blood samples of 20 cancer patients before and after one treatment cycle. Furthermore, we performed single-cell whole-exome DNA sequencing on a single CTC from the peripheral blood sample of a representative early stage lung cancer patient. Among the blood samples of 20 patients, 15 of them were positive for CTC detection (75.0% detectable rate). Single-cell analysis revealed detailed genetic variations of the CTC, while six new gene mutations were detected in both single CTC and surgical specimen. This study provides a useful tool for the isolation and analysis of single CTCs from peripheral blood samples, which not only facilitates the early diagnosis of cancers but also helps to unravel the genetic information of tumor at a single-cell level. © 2019 International Society for Advancement of Cytometry.

Unravelling tumour heterogeneity by single-cell profiling of circulating tumour cells

Single-cell technologies have contributed to unravelling tumour heterogeneity, now considered a hallmark of cancer and one of the main causes of tumour resistance to cancer therapies. Liquid biopsy (LB), defined as the detection and analysis of cells or cell products released by tumours into the blood, offers an appealing minimally invasive approach that allows the characterization and monitoring of tumour heterogeneity in individual patients. Here, we will review and discuss how circulating tumour cell (CTC) analysis at single-cell resolution provides unique insights into tumour heterogeneity that are not revealed by analysis of circulating tumour DNA (ctDNA) derived from LBs. The molecular analysis of CTCs provides complementary information to that of genomic aberrations determined using ctDNA to fully describe many different cellular components (for example, DNA, RNA, proteins and metabolites) that can influence tumour heterogeneity.

Single-Cell Applications of Next-Generation Sequencing

The single cell is considered the basic unit of biology, and the pursuit of understanding how heterogeneous populations of cells can functionally coexist in tissues, organisms, microbial ecosystems, and even cancer, makes them the subject of intense study. Next-generation sequencing (NGS) of RNA and DNA has opened a new frontier of (single)-cell biology. Hundreds to millions of cells now can be assayed in parallel, providing the molecular profile of each cell in its milieu inexpensively and in a manner that can be analyzed mathematically. The goal of this article is to provide a high-level overview of single-cell sequencing for the nonexpert and show how its applications are influencing both basic and applied clinical studies in embryology, developmental genetics, and cancer.

Detection of RAS mutations in circulating tumor DNA: a new weapon in an old war against colorectal cancer. A systematic review of literature and meta-analysis

Background:

Tissue evaluation for RAS (KRAS or NRAS) gene status in metastatic colorectal cancer (mCRC) patients represent the standard of care to establish the optimal therapeutic strategy. Unfortunately, tissue biopsy is hampered by several critical limitations due to its invasiveness, difficulty to access to disease site, patient’s compliance and, more recently, neoplastic tissue spatial and temporal heterogeneity.

Methods:

The authors performed a systematic literature review to identify available trials with paired matched tissue and ctDNA RAS gene status evaluation. The authors searched EMBASE, MEDLINE, Cochrane, www.ClinicalTrials.gov, and abstracts from international meetings. In total, 19 trials comparing standard tissue RAS mutational status matched paired ctDNA evaluated through polymerase chain reaction (PCR), next generation sequencing (NGS) or beads, emulsions, amplification and magnetics (BEAMing) were identified.

Results:

The pooled sensitivity and specificity of ctDNA were 0.83 (95% CI: 0.80–0.85) and 0.91 (95% CI: 0.89–0.93) respectively. The pooled positive predictive value (PPV) and negative predictive value (NPV) of the ctDNA were 0.87 (95% CI: 0.81–0.92) and 0.87 (95% CI: 0.82–0.92), respectively. Positive likelihood ratio (PLR) was 8.20 (95% CI: 5.16–13.02) and the negative likelihood ratio (NLR) was 0.22 (95% CI: 0.16–0.30). The pooled diagnostic odds ratio (DOR) was 50.86 (95% CI: 26.15–98.76), and the area under the curve (AUC) of the summary receiver operational characteristics (sROC) curve was 0.94.

Conclusion:

The authors’ meta-analysis produced a complete and updated overview of ctDNA diagnostic accuracy to test RAS mutation in mCRC. Results provide a strong rationale to include the RAS ctDNA test into randomized clinical trials to validate it prospectively.

Taking Systems Medicine to Heart

Systems medicine is a holistic approach to deciphering the complexity of human physiology in health and disease. In essence, a living body is constituted of networks of dynamically interacting units (molecules, cells, organs, etc) that underlie its collective functions. Declining resilience because of aging and other chronic environmental exposures drives the system to transition from a health state to a disease state; these transitions, triggered by acute perturbations or chronic disturbance, manifest as qualitative shifts in the interactions and dynamics of the disease-perturbed networks. Understanding health-to-disease transitions poses a high-dimensional nonlinear reconstruction problem that requires deep understanding of biology and innovation in study design, technology, and data analysis. With a focus on the principles of systems medicine, this Review discusses approaches for deciphering this biological complexity from a novel perspective, namely, understanding how disease-perturbed networks function; their study provides insights into fundamental disease mechanisms. The immediate goals for systems medicine are to identify early transitions to cardiovascular (and other chronic) diseases and to accelerate the translation of new preventive, diagnostic, or therapeutic targets into clinical practice, a critical step in the development of personalized, predictive, preventive, and participatory (P4) medicine.

Comprehensive intra-individual genomic and transcriptional heterogeneity: Evidence-based Colorectal Cancer Precision Medicine

Despite advances in translating conventional research into multi-modal treatment for colorectal cancer (CRC), therapeutic resistance and relapse remain unresolved in advanced resectable and, particularly, non-resectable disease. Genome and transcriptome sequencing and editing technologies, coupled with interaction mapping and machine learning, are transforming biomedical research, representing the most rational hope to overcome unmet research and clinical challenges. Rapid progress in both bulk and single-cell next-generation sequencing (NGS) analyses in the identification of primary and metastatic intratumor genomic and transcriptional heterogeneity (ITH) and the detection of circulating cell-free DNA (cfDNA) alterations is providing critical insight into the origins and spatiotemporal evolution of genomic clones responsible for early and late therapeutic resistance and relapse. Moreover, DNA and RNA editing pave new avenues towards the discovery of novel drug targets. Breakthrough combinations of sequencing and editing systems with technologies exploring dynamic interaction networks within pioneering studies could delineate how coding and non-coding mutations perturb regulatory networks and gene expression. This review discusses latest data on genomic and transcriptomic landscapes in time and space, as well as early-phase clinical trials on targeted drug combinations, highlighting the transition from research to clinical Colorectal Cancer Precision Medicine, through non-invasive screening, individualized drug response prediction and development of multiple novel drugs. Future studies exploring the potential to target key transcriptional drivers and regulators will contribute to the next-generation pharmaceutical controllability of multi-layered aberrant transcriptional biocircuits.

Isoform-level gene expression patterns in single-cell RNA-sequencing data

Motivation

RNA sequencing of single cells enables characterization of transcriptional heterogeneity in seemingly homogeneous cell populations. Single-cell sequencing has been applied in a wide range of researches fields. However, few studies have focus on characterization of isoform-level expression patterns at the single-cell level. In this study, we propose and apply a novel method, ISOform-Patterns (ISOP), based on mixture modeling, to characterize the expression patterns of isoform pairs from the same gene in single-cell isoform-level expression data.

Results

We define six principal patterns of isoform expression relationships and describe a method for differential-pattern analysis. We demonstrate ISOP through analysis of single-cell RNA-sequencing data from a breast cancer cell line, with replication in three independent datasets. We assigned the pattern types to each of 16 562 isoform-pairs from 4929 genes. Among those, 26% of the discovered patterns were significant (P<0.05), while remaining patterns are possibly effects of transcriptional bursting, drop-out and stochastic biological heterogeneity. Furthermore, 32% of genes discovered through differential-pattern analysis were not detected by differential-expression analysis. Finally, the effects of drop-out events and expression levels of isoforms on ISOP's performances were investigated through simulated datasets. To conclude, ISOP provides a novel approach for characterization of isoform-level preference, commitment and heterogeneity in single-cell RNA-sequencing data.

Availability and implementation

The ISOP method has been implemented as a R package and is available at https://github.com/nghiavtr/ISOP under a GPL-3 license.

Supplementary information

Supplementary data are available at Bioinformatics online.

Intrinsic resistance to EGFR-Tyrosine Kinase Inhibitors in EGFR-Mutant Non-Small Cell Lung Cancer: Differences and Similarities with Acquired Resistance

Activating mutations in the epidermal growth factor receptor gene occur as early cancer-driving clonal events in a subset of patients with non-small cell lung cancer (NSCLC) and result in increased sensitivity to EGFR-tyrosine-kinase-inhibitors (EGFR-TKIs). Despite very frequent and often prolonged clinical response to EGFR-TKIs, virtually all advanced EGFR-mutated (EGFRM+) NSCLCs inevitably acquire resistance mechanisms and progress at some point during treatment. Additionally, 20-30% of patients do not respond or respond for a very short time (<3 months) because of intrinsic resistance. While several mechanisms of acquired EGFR-TKI-resistance have been determined by analyzing tumor specimens obtained at disease progression, the factors causing intrinsic TKI-resistance are less understood. However, recent comprehensive molecular-pathological profiling of advanced EGFRM+ NSCLC at baseline has illustrated the co-existence of multiple genetic, phenotypic, and functional mechanisms that may contribute to tumor progression and cause intrinsic TKI-resistance. Several of these mechanisms have been further corroborated by preclinical experiments. Intrinsic resistance can be caused by mechanisms inherent in EGFR or by EGFR-independent processes, including genetic, phenotypic or functional tumor changes. This comprehensive review describes the identified mechanisms connected with intrinsic EGFR-TKI-resistance and differences and similarities with acquired resistance and among clinically implemented EGFR-TKIs of different generations. Additionally, the review highlights the need for extensive pre-treatment molecular profiling of advanced NSCLC for identifying inherently TKI-resistant cases and designing potential combinatorial targeted strategies to treat them.

Cancer Treatment in the Genomic Era

The complexity of human cancer underlies its devastating clinical consequences. Drugs designed to target the genetic alterations that drive cancer have improved the outcome for many patients, but not the majority of them. Here, we review the genomic landscape of cancer, how genomic data can provide much more than a sum of its parts, and the approaches developed to identify and validate genomic alterations with potential therapeutic value. We highlight notable successes and pitfalls in predicting the value of potential therapeutic targets and discuss the use of multi-omic data to better understand cancer dependencies and drug sensitivity. We discuss how integrated approaches to collecting, curating, and sharing these large data sets might improve the identification and prioritization of cancer vulnerabilities as well as patient stratification within clinical trials. Finally, we outline how future approaches might improve the efficiency and speed of translating genomic data into clinically effective therapies and how the use of unbiased genome-wide information can identify novel predictive biomarkers that can be either simple or complex.

Defining the Hallmarks of Metastasis

Metastasis is the primary cause of cancer morbidity and mortality. The process involves a complex interplay between intrinsic tumor cell properties as well as interactions between cancer cells and multiple microenvironments. The outcome is the development of a nearby or distant discontiguous secondary mass. To successfully disseminate, metastatic cells acquire properties in addition to those necessary to become neoplastic. Heterogeneity in mechanisms involved, routes of dissemination, redundancy of molecular pathways that can be utilized, and the ability to piggyback on the actions of surrounding stromal cells makes defining the hallmarks of metastasis extraordinarily challenging. Nonetheless, this review identifies four distinguishing features that are required: motility and invasion, ability to modulate the secondary site or local microenvironments, plasticity, and ability to colonize secondary tissues. By defining these first principles of metastasis, we provide the means for focusing efforts on the aspects of metastasis that will improve patient outcomes.

Therapeutic Potential and Biological Applications of Cordycepin and Metabolic Mechanisms in Cordycepin-Producing Fungi

Cordycepin (3′-deoxyadenosine), a cytotoxic nucleoside analogue found in Cordyceps militaris, has attracted much attention due to its therapeutic potential and biological value. Cordycepin interacts with multiple medicinal targets associated with cancer, tumor, inflammation, oxidant, polyadenylation of mRNA, etc. The investigation of the medicinal drug actions supports the discovery of novel targets and the development of new drugs to enhance the therapeutic potency and reduce toxicity. Cordycepin may be of great value owing to its medicinal potential as an external drug, such as in cosmeceutical, traumatic, antalgic and muscle strain applications. In addition, the biological application of cordycepin, for example, as a ligand, has been used to uncover molecular structures. Notably, studies that investigated the metabolic mechanisms of cordycepin-producing fungi have yielded significant information related to the biosynthesis of high levels of cordycepin. Here, we summarized the medicinal targets, biological applications, cytotoxicity, delivery carriers, stability, and pros/cons of cordycepin in clinical applications, as well as described the metabolic mechanisms of cordycepin in cordycepin-producing fungi. We posit that new approaches, including single-cell analysis, have the potential to enhance medicinal potency and unravel all facets of metabolic mechanisms of cordycepin in Cordyceps militaris.

Drug resistance: origins, evolution and characterization of genomic clones and the tumor ecosystem to optimize precise individualized therapy

Progress in understanding and overcoming fatal intrinsic and acquired resistance is slow, with only a few exceptions. Despite advances in modern genome and transcriptome analysis, the controversy of the three different theories on drug resistance and tumor progression, namely dynamic intratumor heterogeneity, pre-existing minor genomic clones and tumor ecosystem, is unresolved. Moreover, evidence on transcriptional heterogeneity suggests the necessity of a drug bank for individualized, precise drug-sensitivity prediction. We propose a cancer type- and stage-specific clinicogenomic and tumor ecosystemic concept toward cancer precision medicine, focusing on early therapeutic resistance and relapse.

The Pediatric Cell Atlas: Defining the Growth Phase of Human Development at Single-Cell Resolution

Single-cell gene expression analyses of mammalian tissues have uncovered profound stage-specific molecular regulatory phenomena that have changed the understanding of unique cell types and signaling pathways critical for lineage determination, morphogenesis, and growth. We discuss here the case for a Pediatric Cell Atlas as part of the Human Cell Atlas consortium to provide single-cell profiles and spatial characterization of gene expression across human tissues and organs. Such data will complement adult and developmentally focused HCA projects to provide a rich cytogenomic framework for understanding not only pediatric health and disease but also environmental and genetic impacts across the human lifespan.

Translating insights into tumor evolution to clinical practice: promises and challenges

Accelerating technological advances have allowed the widespread genomic profiling of tumors. As yet, however, the vast catalogues of mutations that have been identified have made only a modest impact on clinical medicine. Massively parallel sequencing has informed our understanding of the genetic evolution and heterogeneity of cancers, allowing us to place these mutational catalogues into a meaningful context. Here, we review the methods used to measure tumor evolution and heterogeneity, and the potential and challenges for translating the insights gained to achieve clinical impact for cancer therapy, monitoring, early detection, risk stratification, and prevention. We discuss how tumor evolution can guide cancer therapy by targeting clonal and subclonal mutations both individually and in combination. Circulating tumor DNA and circulating tumor cells can be leveraged for monitoring the efficacy of therapy and for tracking the emergence of resistant subclones. The evolutionary history of tumors can be deduced for late-stage cancers, either directly by sampling precursor lesions or by leveraging computational approaches to infer the timing of driver events. This approach can identify recurrent early driver mutations that represent promising avenues for future early detection strategies. Emerging evidence suggests that mutational processes and complex clonal dynamics are active even in normal development and aging. This will make discriminating developing malignant neoplasms from normal aging cell lineages a challenge. Furthermore, insight into signatures of mutational processes that are active early in tumor evolution may allow the development of cancer-prevention approaches. Research and clinical studies that incorporate an appreciation of the complex evolutionary patterns in tumors will not only produce more meaningful genomic data, but also better exploit the vulnerabilities of cancer, resulting in improved treatment outcomes.

Multidimensional Single-Cell Analyses in Organ Development and Maintenance

The revolution of single-cell analysis tools in epigenomics, transcriptomics, lineage tracing, and transcriptome-scale RNA imaging, has boosted our understanding of the underlying molecular mechanisms during organ development and maintenance. Application of these tools enables the multidimensional study of organs, from cell atlas profiling, spatial organization, to cell-cell interaction. Here, we discuss recent progress in employing multidimensional single-cell analyses to address fundamental questions related to the development and maintenance of hematopoietic organs, brain and lung, which will also help provide insights into a better understanding of relevant diseases.

TARGET-seq Takes Aim at Cancer Evolution through Multi-omics Single-Cell Genotyping and Transcriptomics

In this issue of Molecular Cell, Rodriguez-Meira et al. (2019) present TARGET-seq, an elegant single-cell method that genotypes somatic mutations and captures whole transcriptomes in the same tumor cells, thus paving the way to directly link somatic mutations with resulting transcriptional phenotypes in clonally diverse cancer populations.

Single-cell imaging and RNA sequencing reveal patterns of gene expression heterogeneity during fission yeast growth and adaptation

Phenotypic cell-to-cell variability is a fundamental determinant of microbial fitness that contributes to stress adaptation and drug resistance. Gene expression heterogeneity underpins this variability but is challenging to study genome-wide. Here we examine the transcriptomes of >2,000 single fission yeast cells exposed to various environmental conditions by combining imaging, single-cell RNA sequencing and Bayesian true count recovery. We identify sets of highly variable genes during rapid proliferation in constant culture conditions. By integrating single-cell RNA sequencing and cell-size data, we provide insights into genes that are regulated during cell growth and division, including genes whose expression does not scale with cell size. We further analyse the heterogeneity of gene expression during adaptive and acute responses to changing environments. Entry into the stationary phase is preceded by a gradual, synchronized adaptation in gene regulation that is followed by highly variable gene expression when growth decreases. Conversely, sudden and acute heat shock leads to a stronger, coordinated response and adaptation across cells. This analysis reveals that the magnitude of global gene expression heterogeneity is regulated in response to different physiological conditions within populations of a unicellular eukaryote.

The Impact of Heterogeneity on Single-Cell Sequencing

The importance of diversity and cellular specialization is clear for many reasons, from population-level diversification, to improved resiliency to unforeseen stresses, to unique functions within metazoan organisms during development and differentiation. However, the level of cellular heterogeneity is just now becoming clear through the integration of genome-wide analyses and more cost effective Next Generation Sequencing (NGS). With easy access to single-cell NGS (scNGS), new opportunities exist to examine different levels of gene expression and somatic mutational heterogeneity, but these assays can generate yottabyte scale data. Here, we model the importance of heterogeneity for large-scale analysis of scNGS data, with a focus on the utilization in oncology and other diseases, providing a guide to aid in sample size and experimental design.

Apigenin as an effective anticancer natural product: Spotlight on TRAIL, WNT/β-catenin, JAK-STAT pathways, and microRNAs

Wealth of information gleaned from decades of high-impact research work; scientists have disentangled the complicated web of versatile regulators that underlie cancer development and progression. Use of structural biology approaches and functional genomics have helped us to gain new insights into complex nature of cancer, and it is now clear that genetic/epigenetic mutations, overexpression of oncogenes, inactivation of tumor suppressors, loss of apoptosis, and versatility of protein binding partners have contributory roles in carcinogenesis and metastatic spread. It is becoming progressively more understandable that reprogramming of gene expression during and nontranscriptional changes during cancer development and progression are initiated and controlled by deregulated signal transduction cascades, all of which collectively create an incalculable complexity. Data obtained through preclinical and clinical trials revealed that alterations in the targeted oncogenes and other downstream, and parallel pathways played a central role in the development of resistance against different therapeutics. Phytochemicals have regained limelight, and different natural products are currently being tested for efficacy in preclinical studies. Apigenin, a plant-derived flavonoid has considerable pharmacological value and is reportedly involved in the regulation of different signaling cascades. In this review, we have attempted to summarize rapidly evolving understanding of molecular biologists and pharmacologists about the potential of apigenin in the regulation of deregulated signaling pathways in different cancers. We have emphasized on the regulation of WNT/β-catenin and janus kinase/signal transducers and activators of transcription (JAK-STAT) pathways. We also comprehensively discuss how apigenin restored apoptosis in tumor necrosis factor-related apoptosis-inducing ligand (TRAIL)-resistant cancers. The review also gives a snapshot of microRNAs (miRNAs) that regulate wide-ranging biological processes, and it is now clear that each miRNA can control hundreds of gene targets. Apigenin was noted to upregulate miR-520b and miR-101 in different cancers to inhibit tumor growth. Moreover, apigenin-induced apoptotic rate was significantly higher when used in combination with miR-423-5p inhibitors or miR-138 mimics. Better comprehension of linear and integrated signaling pathways will be helpful in effective therapeutic targeting of deregulated signaling pathways to inhibit/prevent cancer.

p62/SQSTM1 Fuels Melanoma Progression by Opposing mRNA Decay of a Selective Set of Pro-metastatic Factors

Modulators of mRNA stability are not well understood in melanoma, an aggressive tumor with complex changes in the transcriptome. Here we report the ability of p62/SQSTM1 to extend mRNA half-life of a spectrum of pro-metastatic factors. These include FERMT2 and other transcripts with no previous links to melanoma. Transcriptomic, proteomic, and interactomic analyses, combined with validation in clinical biopsies and mouse models, identified a selected set of RNA-binding proteins (RBPs) recruited by p62, with IGF2BP1 as a key partner. This p62-RBP interaction distinguishes melanoma from other tumors where p62 controls autophagy or oxidative stress. The relevance of these data is emphasized by follow-up analyses of patient prognosis revealing p62 and FERMT2 as adverse determinants of disease-free survival.

Breast tumour organoids: promising models for the genomic and functional characterisation of breast cancer

Until recently, established cancer cell lines have been used extensively in breast cancer research, due largely to the difficulties associated with the manipulation and long-term maintenance in culture of primary tumour cells from patients. The recent development of organoid cultures has provided new opportunities to model and analyse patient samples, allowing the propagation of malignant cells under conditions that resemble the three-dimensional growth of breast tumours. They have proved efficacious in preserving the heterogeneity of primary samples and are emerging as a new model to further characterise the molecular features of breast cancer. Organoids formed from patient-derived cells are now in use for the evaluation of drug sensitivity and to validate disease-causing genomic variations. Here, the advantages and limitations of organoid cultures will be discussed and compared with the parallel development of other two- and three-dimensional culture strategies and with patient-derived xenografts. In particular, we will focus on the molecular characterisation of breast cancer organoids and provide some examples of how they have been used in functional studies.

Novel and Alternative Targets Against Breast Cancer Stemness to Combat Chemoresistance

Breast cancer stem cells (BCSCs) play a vital role in tumor progression and metastasis. They are heterogeneous and inherently radio- and chemoresistant. They have the ability to self-renew and differentiate into non-BCSCs. These determinants of BCSCs including the plasticity between the mesenchymal and epithelial phenotypes often leads to minimal residual disease (MRD), tumor relapse, and therapy failure. By studying the resistance mechanisms in BCSCs, a combinatorial therapy can be formulated to co-target BCSCs and bulk tumor cells. This review addresses breast cancer stemness and molecular underpinnings of how the cancer stemness can lead to pharmacological resistance. This might occur through rewiring of signaling pathways and modulated expression of various targets that support survival and self-renewal, clonogenicity, and multi-lineage differentiation into heterogeneous bulk tumor cells following chemotherapy. We explore emerging novel and alternative molecular targets against BC stemness and chemoresistance involving survival, drug efflux, metabolism, proliferation, cell migration, invasion, and metastasis. Strategic targeting of such vulnerabilities in BCSCs may overcome the chemoresistance and increase the longevity of the metastatic breast cancer patients.

Circulating Tumor Cells: Overview and Opportunities in Cytology

Circulating tumor cells (CTCs) have long been assumed to be the substrate of cancer metastasis. However, only in recent years have we begun to leverage the potential of CTCs found in minimally invasive peripheral blood specimens to improve care for cancer patients. Currently, CTC enumeration is an accepted prognostic indicator for breast, prostate, and colorectal cancer; however, CTC enumeration remains largely a research tool. More recently, the focus has shifted to CTC characterization and isolation which holds great promise for predictive testing. This review summarizes the relevant clinical, biological, and technical background necessary for pathologists and cytopathologists to appreciate the potential of CTC techniques. A summary of relevant systematic reviews of CTCs for specific cancers is then presented, as well as potential applications to precision medicine. Finally, we suggest future applications of CTC technologies that can be easily incorporated in the pathology laboratory, with the recommendation that pathologists and particularly cytopathologists apply these technologies to small specimens in the era of "doing more with less."

Quantification of somatic mutation flow across individual cell division events by lineage sequencing

Mutation data reveal the dynamic equilibrium between DNA damage and repair processes in cells and are indispensable to the understanding of age-related diseases, tumor evolution, and the acquisition of drug resistance. However, available genome-wide methods have a limited ability to resolve rare somatic variants and the relationships between these variants. Here, we present lineage sequencing, a new genome sequencing approach that enables somatic event reconstruction by providing quality somatic mutation call sets with resolution as high as the single-cell level in subject lineages. Lineage sequencing entails sampling single cells from a population and sequencing subclonal sample sets derived from these cells such that knowledge of relationships among the cells can be used to jointly call variants across the sample set. This approach integrates data from multiple sequence libraries to support each variant and precisely assigns mutations to lineage segments. We applied lineage sequencing to a human colon cancer cell line with a DNA polymerase epsilon (POLE) proofreading deficiency (HT115) and a human retinal epithelial cell line immortalized by constitutive telomerase expression (RPE1). Cells were cultured under continuous observation to link observed single-cell phenotypes with single-cell mutation data. The high sensitivity, specificity, and resolution of the data provide a unique opportunity for quantitative analysis of variation in mutation rate, spectrum, and correlations among variants. Our data show that mutations arrive with nonuniform probability across sublineages and that DNA lesion dynamics may cause strong correlations between certain mutations.

Translocation-Related Sarcomas

Chromosomal translocations are observed in approximately 20% of soft tissue sarcomas (STS). With the advances in pathological examination technology, the identification of translocations has enabled precise diagnoses and classifications of STS, and it has been suggested that the presence of and differences in translocations could be prognostic factors in some translocation-related sarcomas. Most of the translocations in STS were not regarded as targets of molecular therapies until recently. However, trabectedin, an alkylating agent, has shown clinical benefits against translocation-related sarcoma based on a modulation of the transcription of the tumor's oncogenic fusion proteins. Many molecular-targeted drugs that are specific to translocations (e.g., anaplastic lymphoma kinase and tropomyosin kinase related fusion proteins) have emerged. The progress in gene technologies has allowed researchers to identify and even induce new translocations and fusion proteins, which might become targets of molecular-targeted therapies. In this review, we discuss the clinical significance of translocation-related sarcomas, including their diagnoses and targeted therapies.

Power in Numbers: Single-Cell RNA-Seq Strategies to Dissect Complex Tissues

The growing scale and declining cost of single-cell RNA-sequencing (RNA-seq) now permit a repetition of cell sampling that increases the power to detect rare cell states, reconstruct developmental trajectories, and measure phenotype in new terms such as cellular variance. The characterization of anatomy and developmental dynamics has not had an equivalent breakthrough since groundbreaking advances in live fluorescent microscopy. The new resolution obtained by single-cell RNA-seq is a boon to genetics because the novel description of phenotype offers the opportunity to refine gene function and dissect pleiotropy. In addition, the recent pairing of high-throughput genetic perturbation with single-cell RNA-seq has made practical a scale of genetic screening not previously possible.

[Advances on Recognizing and Managing Tumor Heterogeneity]

肿瘤异质性是恶性肿瘤的特征之一，可使肿瘤的生长速度、侵袭与转移、药物敏感性、预后等各方面产生差异。肿瘤驱动基因和靶向药物的发现发展开启了战胜肿瘤的希望之门，然而异质性的存在又让肿瘤治疗陷入了难以攻克的困境。在肿瘤复发、进展演化的过程中肿瘤异质性如影随形，纷繁复杂。凭借不断进步的检测技术认识和理解肿瘤异质性，针对肿瘤异质性的原因和表型，定制治疗方案已成为当今精准医疗领域的重点范畴。本综述对肿瘤异质性进行了分析和探讨，从而更好的帮助我们了解肿瘤异质性，有利于我们通过多种手段对抗肿瘤异质性。

Defining Cell Identity with Single-Cell Omics

Cells are a fundamental unit of life, and the ability to study the phenotypes and behaviors of individual cells is crucial to understanding the workings of complex biological systems. Cell phenotypes (epigenomic, transcriptomic, proteomic, and metabolomic) exhibit dramatic heterogeneity between and within the different cell types and states underlying cellular functional diversity. Cell genotypes can also display heterogeneity throughout an organism, in the form of somatic genetic variation-most notably in the emergence and evolution of tumors. Recent technical advances in single-cell isolation and the development of omics approaches sensitive enough to reveal these aspects of cell identity have enabled a revolution in the study of multicellular systems. In this review, we discuss the technologies available to resolve the genomes, epigenomes, transcriptomes, proteomes, and metabolomes of single cells from a wide variety of living systems.

Pancreatic cancer circulating tumor cells: applications for personalized oncology

INTRODUCTION

Pancreatic cancer (PC) is a highly lethal disease, in part because of early metastasis, late diagnosis, and limited treatment options. Circulating tumor cells (CTCs) are cancer cells that have achieved the metastatic step of intravasation, and are thus a unique source of biomarkers with potential applications in the staging, prognostication, and treatment of PC. Areas covered: This review describes the use of CTCs in PC, including isolation methods, the significance of CTC enumeration, and studies examining phenotypic and molecular characteristics of CTCs. We also speculate on future directions for PC CTC research such as single-cell analysis and CTC culture. Expert commentary: CTCs represent a potential unique serial source of cancer tissue via a convenient and minimally invasive blood draw. Recent development of isolation methods that allow for the release of viable CTCs with unaltered molecular characteristics has set the stage for single-cell analysis and ex vivo culture. Although there is significant potential for CTCs as a biomarker to impact PC from diagnosis to therapy, there still remain a number of challenges to the routine implementation of CTCs in the clinical management of PC.

Calcium signaling and the therapeutic targeting of cancer cells

The calcium signal is implicated in a variety of processes important in tumor progression (e.g. proliferation and invasiveness). The calcium signal has also been shown to be important in other processes important in cancer progression including the development of resistance to current cancer therapies. In this review, we discuss how Ca²⁺ channels, pumps and exchangers may be drug targets in some cancer types. We consider what factors should be taken into account when considering an optimal Ca²⁺ channel, pump or exchanger as a candidate for further assessment as a novel drug target in cancer. We also present and summarize how some therapies for the treatment of cancer intersect with Ca²⁺ signaling and how pharmacological manipulation of the machinery of Ca²⁺ signaling could promote the effectiveness of some therapies. We also review new therapeutic opportunities for Ca²⁺ signal modulators in the context of the tumor microenvironment.