Single-cell lineage tracing of metastatic cancer reveals selection of hybrid EMT states

Mutually exclusive teams-like patterns of gene regulation characterize phenotypic heterogeneity along the noradrenergic-mesenchymal axis in neuroblastoma

Neuroblastoma is the most frequent extracranial pediatric tumor and leads to 15% of all cancer-related deaths in children. Tumor relapse and therapy resistance in neuroblastoma are driven by phenotypic plasticity and heterogeneity between noradrenergic (NOR) and mesenchymal (MES) cell states. Despite the importance of this phenotypic plasticity, the dynamics and molecular patterns associated with these bidirectional cell-state transitions remain relatively poorly understood. Here, we analyze multiple RNA-seq datasets at both bulk and single-cell resolution, to understand the association between NOR- and MES-specific factors. We observed that NOR-specific and MES-specific expression patterns are largely mutually exclusive, exhibiting a "teams-like" behavior among the genes involved, reminiscent of our earlier observations in lung cancer and melanoma. This antagonism between NOR and MES phenotypes was also associated with metabolic reprogramming and with immunotherapy targets PD-L1 and GD2 as well as with experimental perturbations driving the NOR-MES and/or MES-NOR transition. Further, these "teams-like" patterns were seen only among the NOR- and MES-specific genes, but not in housekeeping genes, possibly highlighting a hallmark of network topology enabling cancer cell plasticity.

Cancer, metastasis, and the epigenome

Cancer is the second leading cause of death worldwide and disease burden is expected to increase globally throughout the next several decades, with the majority of cancer-related deaths occurring in metastatic disease. Cancers exhibit known hallmarks that endow them with increased survival and proliferative capacities, frequently as a result of de-stabilizing mutations. However, the genomic features that resolve metastatic clones from primary tumors are not yet well-characterized, as no mutational landscape has been identified as predictive of metastasis. Further, many cancers exhibit no known mutation signature. This suggests a larger role for non-mutational genome re-organization in promoting cancer evolution and dissemination. In this review, we highlight current critical needs for understanding cell state transitions and clonal selection advantages for metastatic cancer cells. We examine links between epigenetic states, genome structure, and misregulation of tumor suppressors and oncogenes, and discuss how recent technologies for understanding domain-scale regulation have been leveraged for a more complete picture of oncogenic and metastatic potential.

IGF1R signaling induces epithelial-mesenchymal plasticity via ITGAV in cutaneous carcinoma

BACKGROUND

Early cutaneous squamous cell carcinomas (cSCCs) generally show epithelial differentiation features and good prognosis, whereas advanced cSCCs present mesenchymal traits associated with tumor relapse, metastasis, and poor survival. Currently, the mechanisms involved in cSCC progression are unclear, and the established markers are suboptimal for accurately predicting the clinical course of the disease.

METHODS

Using a mouse model of cSCC progression, expression microarray analysis, immunofluorescence and flow cytometry assays, we have identified a prognostic biomarker of tumor relapse, which has been evaluated in a cohort of cSCC patient samples. Phosphoproteomic analysis have revealed signaling pathways induced in epithelial plastic cancer cells that promote epithelial-mesenchymal plasticity (EMP) and tumor progression. These pathways have been validated by genetic and pharmacological inhibition assays.

RESULTS

We show that the emergence of epithelial cancer cells expressing integrin αV (ITGAV) promotes cSCC progression to a mesenchymal state. Consistently, ITGAV expression allows the identification of patients at risk of cSCC relapse above the currently employed clinical histopathological parameters. We also demonstrate that activation of insulin-like growth factor-1 receptor (IGF1R) pathway in epithelial cancer cells is necessary to induce EMP and mesenchymal state acquisition in response to tumor microenvironment-derived factors, while promoting ITGAV expression. Likewise, ITGAV knockdown in epithelial plastic cancer cells also blocks EMP acquisition, generating epithelial tumors.

CONCLUSIONS

Our results demonstrate that ITGAV is a prognostic biomarker of relapse in cSCCs that would allow improved patient stratification. ITGAV also collaborates with IGF1R to induce EMP in epithelial cancer cells and promotes cSCC progression, revealing a potential therapeutic strategy to block the generation of advanced mesenchymal cSCCs.

The heterogeneity of breast cancer metastasis: a bioinformatics analysis utilizing single-cell RNA sequencing data

PURPOSE

Breast cancer is a common malignancy in women, and its metastasis is a leading cause of cancer-related deaths. Single-cell RNA sequencing (scRNA-seq) can distinguish the molecular characteristics of metastasis and identify predictor genes for patient prognosis. This article explores gene expression in primary breast cancer tumor tissue against metastatic cells in the lymph node and liver using scRNA-seq.

METHODS

Breast cancer scRNA-seq data from the Gene Expression Omnibus were used. The data were processed using R and the Seurat package. The cells were clustered and identified using Metascape. InferCNV is used to analyze the variation in copy number. Differential expression analysis was conducted for the cancer cells using Seurat and was enriched using Metascape.

RESULTS

We identified 18 distinct cell clusters, 6 of which were epithelial. CNV analysis identified significant alterations with duplication of chromosomes 1, 8, and 19. Differential gene analysis resulted in 17 upregulated and 171 downregulated genes for the primary tumor in the primary tumor vs. liver metastasis comparison and 43 upregulated and 4 downregulated genes in the primary tumor in the primary tumor vs lymph node metastasis comparison. Several enriched terms include Ribosome biogenesis, NTP synthesis, Epithelial dedifferentiation, Autophagy, and genes associated with epithelial-to-mesenchymal transitions.

CONCLUSION

No single gene or pathway can clearly explain the mechanisms behind tumor metastasis. Several mechanisms contribute to lymph node and liver metastasis, such as the loss of differentiation, epithelial-to-mesenchymal transition, and autophagy. These findings necessitate further study of metastatic tissue for effective drug development.

MAPKAP1 orchestrates macrophage polarization and lipid metabolism in fatty liver-enhanced colorectal cancer

Various factors, including fatty liver and macrophage alterations, influence colorectal cancer (CRC). This study explores the mechanistic role of fatty liver in CRC progression, focusing on macrophage polarization and lipid metabolism. A murine fatty liver model was created with a high-fat diet (HFD), and CRC was induced using AOM and DSS. Single-cell transcriptome sequencing (scRNA-seq) identified MAPKAP1 as a critical gene promoting CRC via M2 macrophage polarization and lipid metabolism reprogramming. Prognosis analysis on the TCGA-CRC dataset confirmed MAPKAP1's significance. In vitro and in vivo experiments demonstrated that EVs from fatty liver cells enhanced MAPKAP1 expression, accelerating CRC development and metastasis. HFD exacerbated CRC, but fatty acid inhibitors delayed progression. Fatty liver upregulates MAPKAP1, driving M2 macrophage polarization and lipid metabolism changes, worsening CRC. These findings suggest potential therapeutic strategies for CRC, particularly targeting lipid metabolism and macrophage-mediated tumor promotion.

Detecting branching rate heterogeneity in multifurcating trees with applications in lineage tracing data

Understanding cellular birth rate differences is crucial for predicting cancer progression and interpreting tumor-derived genetic data. Lineage tracing experiments enable detailed reconstruction of cellular genealogies, offering new opportunities to measure branching rate heterogeneity. However, the lineage tracing process can introduce complex tree features that complicate this effort. Here, we examine tree characteristics in lineage tracing-derived genealogies and find that editing window placement leads to multifurcations at a tree's root or tips. We propose several ways in which existing tree topology-based metrics can be extended to test for rate heterogeneity on trees even in the presence of lineage-tracing associated distortions. Although these methods vary in power and robustness, a test based on the J 1 statistic effectively detects branching rate heterogeneity in simulated lineage tracing data. Tests based on other common statistics ( ŝ and the Sackin index) show interior performance to J 1 . We apply our validated methods to xenograft experimental data and find widespread rate heterogeneity across multiple study systems. Our results demonstrate the potential of tree topology statistics in analyzing lineage tracing data, and highlight the challenges associated with adapting phylogenetic methods to these systems.

RNA regulatory mechanisms controlling TGF-β signaling and EMT in cancer

Epithelial-mesenchymal transition (EMT) is a major contributor to metastatic progression and is prominently regulated by TGF-β signalling. Both EMT and TGF-β pathway components are tightly controlled by non-coding RNAs - including microRNAs (miRNAs), long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) - that collectively have major impacts on gene expression and resulting cellular states. While miRNAs are the best characterised regulators of EMT and TGF-β signaling and the miR-200-ZEB1/2 feedback loop plays a central role, important functions for lncRNAs and circRNAs are also now emerging. This review will summarise our current understanding of the roles of non-coding RNAs in EMT and TGF-β signaling with a focus on their functions in cancer progression.

Reconstructing axial progenitor field dynamics in mouse stem cell-derived embryoids

Embryogenesis requires substantial coordination to translate genetic programs to the collective behavior of differentiating cells, but understanding how cellular decisions control tissue morphology remains conceptually and technically challenging. Here, we combine continuous Cas9-based molecular recording with a mouse embryonic stem cell-based model of the embryonic trunk to build single-cell phylogenies that describe the behavior of transient, multipotent neuro-mesodermal progenitors (NMPs) as they commit into neural and somitic cell types. We find that NMPs show subtle transcriptional signatures related to their recent differentiation and contribute to downstream lineages through a surprisingly broad distribution of individual fate outcomes. Although decision-making can be heavily influenced by environmental cues to induce morphological phenotypes, axial progenitors intrinsically mature over developmental time to favor the neural lineage. Using these data, we present an experimental and analytical framework for exploring the non-homeostatic dynamics of transient progenitor populations as they shape complex tissues during critical developmental windows.

Perspectives in collective cell migration - moving forward

Collective cell migration, where cells move as a cohesive unit, is a vital process underlying morphogenesis and cancer metastasis. Thanks to recent advances in imaging and modelling, we are beginning to understand the intricate relationship between a cell and its microenvironment and how this shapes cell polarity, metabolism and modes of migration. The use of biophysical and mathematical models offers a fresh perspective on how cells migrate collectively, either flowing in a fluid-like state or transitioning to more static states. Continuing to unite researchers in biology, physics and mathematics will enable us to decode more complex biological behaviours that underly collective cell migration; only then can we understand how this coordinated movement of cells influences the formation and organisation of tissues and directs the spread of metastatic cancer. In this Perspective, we highlight exciting discoveries, emerging themes and common challenges that have arisen in recent years, and possible ways forward to bridge the gaps in our current understanding of collective cell migration.

Single-cell lineage capture across genomic modalities with CellTag-multi reveals fate-specific gene regulatory changes

Complex gene regulatory mechanisms underlie differentiation and reprogramming. Contemporary single-cell lineage-tracing (scLT) methods use expressed, heritable DNA barcodes to combine cell lineage readout with single-cell transcriptomics. However, reliance on transcriptional profiling limits adaptation to other single-cell assays. With CellTag-multi, we present an approach that enables direct capture of heritable random barcodes expressed as polyadenylated transcripts, in both single-cell RNA sequencing and single-cell Assay for Transposase Accessible Chromatin using sequencing assays, allowing for independent clonal tracking of transcriptional and epigenomic cell states. We validate CellTag-multi to characterize progenitor cell lineage priming during mouse hematopoiesis. Additionally, in direct reprogramming of fibroblasts to endoderm progenitors, we identify core regulatory programs underlying on-target and off-target fates. Furthermore, we reveal the transcription factor Zfp281 as a regulator of reprogramming outcome, biasing cells toward an off-target mesenchymal fate. Our results establish CellTag-multi as a lineage-tracing method compatible with multiple single-cell modalities and demonstrate its utility in revealing fate-specifying gene regulatory changes across diverse paradigms of differentiation and reprogramming.

The glutathione S-transferase Gstt1 drives survival and dissemination in metastases

Identifying the adaptive mechanisms of metastatic cancer cells remains an elusive question in the treatment of metastatic disease, particularly in pancreatic cancer (pancreatic adenocarcinoma, PDA). A loss-of-function shRNA targeted screen in metastatic-derived cells identified Gstt1, a member of the glutathione S-transferase superfamily, as uniquely required for dissemination and metastasis, but dispensable for primary tumour growth. Gstt1 is expressed in latent disseminated tumour cells (DTCs), is retained within a subpopulation of slow-cycling cells within existing metastases, and its inhibition leads to complete regression of macrometastatic tumours. This distinct Gstt1high population is highly metastatic and retains slow-cycling phenotypes, epithelial-mesenchymal transition features and DTC characteristics compared to the Gstt1low population. Mechanistic studies indicate that in this subset of cancer cells, Gstt1 maintains metastases by binding and glutathione-modifying intracellular fibronectin, in turn promoting its secretion and deposition into the metastatic microenvironment. We identified Gstt1 as a mediator of metastasis, highlighting the importance of heterogeneity and its influence on the metastatic tumour microenvironment.

Single-cell lineage tracing approaches to track kidney cell development and maintenance

The kidney is a complex organ consisting of various cell types. Previous studies have aimed to elucidate the cellular relationships among these cell types in developing and mature kidneys using Cre-loxP-based lineage tracing. However, this methodology falls short of fully capturing the heterogeneous nature of the kidney, making it less than ideal for comprehensively tracing cellular progression during kidney development and maintenance. Recent technological advancements in single-cell genomics have revolutionized lineage tracing methods. Single-cell lineage tracing enables the simultaneous tracing of multiple cell types within complex tissues and their transcriptomic profiles, thereby allowing the reconstruction of their lineage tree with cell state information. Although single-cell lineage tracing has been successfully applied to investigate cellular hierarchies in various organs and tissues, its application in kidney research is currently lacking. This review comprehensively consolidates the single-cell lineage tracing methods, divided into 4 categories (clustered regularly interspaced short palindromic repeat [CRISPR]/CRISPR-associated protein 9 [Cas9]-based, transposon-based, Polylox-based, and native barcoding methods), and outlines their technical advantages and disadvantages. Furthermore, we propose potential future research topics in kidney research that could benefit from single-cell lineage tracing and suggest suitable technical strategies to apply to these topics.

Heterogeneity generating capacity in tumorigenesis and cancer therapeutics

Cells of multicellular organisms generate heterogeneity in a controlled and transient fashion during embryogenesis, which can be reactivated in pathologies such as cancer. Although genomic heterogeneity is an important part of tumorigenesis, continuous generation of phenotypic heterogeneity is central for the adaptation of cancer cells to the challenges of tumorigenesis and response to therapy. Here I discuss the capacity of generating heterogeneity, hereafter called cell hetness, in cancer cells both as the activation of hetness oncogenes and inactivation of hetness tumor suppressor genes, which increase the generation of heterogeneity, ultimately producing an increase in adaptability and cell fitness. Transcriptomic high hetness states in therapy-tolerant cell states denote its importance in cancer resistance to therapy. The definition of the concept of hetness will allow the understanding of its origins, its control during embryogenesis, its loss of control in tumorigenesis and cancer therapeutics and its active targeting.

Fascin-1 Promotes Cell Metastasis through Epithelial-Mesenchymal Transition in Canine Mammary Tumor Cell Lines

Canine mammary tumors (CMTs) are the most common type of tumor in female dogs. In this study, we obtained a metastatic key protein, Fascin-1, by comparing the proteomics data of in situ tumor and metastatic cell lines from the same individual. However, the role of Fascin-1 in the CMT cell line is still unclear. Firstly, proteomics was used to analyze the differential expression of Fascin-1 between the CMT cell lines CHMm and CHMp. Then, the overexpression (CHMm-OE and CHMp-OE) and knockdown (CHMm-KD and CHMp-KD) cell lines were established by lentivirus transduction. Finally, the differentially expressed proteins (DEPs) in CHMm and CHMm-OE cells were identified through proteomics. The results showed that the CHMm cells isolated from CMT abdominal metastases exhibited minimal expression of Fascin-1. The migration, adhesion, and invasion ability of CHMm-OE and CHMp-OE cells increased, while the migration, adhesion, and invasion ability of CHMm-KD and CHMp-KD cells decreased. The overexpression of Fascin-1 can upregulate the Tetraspanin 4 (TSPAN4) protein in CHMm cells and increase the number of migrations. In conclusion, re-expressed Fascin-1 could promote cell EMT and increase lamellipodia formation, resulting in the enhancement of CHMm cell migration, adhesion, and invasion in vitro. This may be beneficial to improve female dogs' prognosis of CMT.

Analysis of synthetic cellular barcodes in the genome and transcriptome with BARtab and bartools

Cellular barcoding is a lineage-tracing methodology that couples heritable synthetic barcodes to high-throughput sequencing, enabling the accurate tracing of cell lineages across a range of biological contexts. Recent studies have extended these methods by incorporating lineage information into single-cell or spatial transcriptomics readouts. Leveraging the rich biological information within these datasets requires dedicated computational tools for dataset pre-processing and analysis. Here, we present BARtab, a portable and scalable Nextflow pipeline, and bartools, an open-source R package, designed to provide an integrated end-to-end cellular barcoding analysis toolkit. BARtab and bartools contain methods to simplify the extraction, quality control, analysis, and visualization of lineage barcodes from population-level, single-cell, and spatial transcriptomics experiments. We showcase the utility of our integrated BARtab and bartools workflow via the analysis of exemplar bulk, single-cell, and spatial transcriptomics experiments containing cellular barcoding information.

Long noncoding RNA BMPR1B-AS1 stability regulated by IGF2BP2 affects the decidualization in endometriosis patients through the SMAD1/5/9 pathway

Endometriosis (EMs)-related infertility commonly has decreased endometrial receptivity and normal decidualization is the basis for establishing and maintaining endometrial receptivity. However, the potential molecular regulatory mechanisms of impaired endometrial decidualization in patients with EMs have not been fully clarified. We confirmed the existence of reduced endometrial receptivity in patients with EMs by scanning electron microscopy and quantitative real-time PCR. Here we identified an lncRNA, named BMPR1B-AS1, which is significantly downregulated in eutopic endometrium in EMs patients and plays an essential role in decidual formation. Furthermore, RNA pull-down, mass spectrometry, RNA immunoprecipitation, and rescue analyses revealed that BMPR1B-AS1 positively regulates decidual formation through interaction with the RNA-binding protein insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2). Downregulation of IGF2BP2 led to a decreased stability of BMPR1B-AS1 and inhibition of activation of the SMAD1/5/9 pathway, an inhibitory effect which diminished decidualization in human endometrial stromal cells (hESCs) decidualization. In conclusion, our identified a novel regulatory mechanism in which the IGF2BP2-BMPR1B-AS1-SMAD1/5/9 axis plays a key role in the regulation of decidualization, providing insights into the potential link between abnormal decidualization and infertility in patients with EMs, which will be of clinical significance for the management and treatment of infertility in patients with EMs.

How CRISPR Is Revolutionizing the Generation of New Models for Cancer Research

Cancers arise through acquisition of mutations in genes that regulate core biological processes like cell proliferation and cell death. Decades of cancer research have led to the identification of genes and mutations causally involved in disease development and evolution, yet defining their precise function across different cancer types and how they influence therapy responses has been challenging. Mouse models have helped define the in vivo function of cancer-associated alterations, and genome-editing approaches using CRISPR have dramatically accelerated the pace at which these models are developed and studied. Here, we highlight how CRISPR technologies have impacted the development and use of mouse models for cancer research and discuss the many ways in which these rapidly evolving platforms will continue to transform our understanding of this disease.

Lung endothelium exploits susceptible tumor cell states to instruct metastatic latency

In metastasis, cancer cells travel around the circulation to colonize distant sites. Due to the rarity of these events, the immediate fates of metastasizing tumor cells (mTCs) are poorly understood while the role of the endothelium as a dissemination interface remains elusive. Using a newly developed combinatorial mTC enrichment approach, we provide a transcriptional blueprint of the early colonization process. Following their arrest at the metastatic site, mTCs were found to either proliferate intravascularly or extravasate, thereby establishing metastatic latency. Endothelial-derived angiocrine Wnt factors drive this bifurcation, instructing mTCs to follow the extravasation-latency route. Surprisingly, mTC responsiveness towards niche-derived Wnt was established at the epigenetic level, which predetermined tumor cell behavior. Whereas hypomethylation enabled high Wnt activity leading to metastatic latency, methylated mTCs exhibited low activity and proliferated intravascularly. Collectively the data identify the predetermined methylation status of disseminated tumor cells as a key regulator of mTC behavior in the metastatic niche.

Decoding the interplay between genetic and non-genetic drivers of metastasis

Metastasis is a multistep process by which cancer cells break away from their original location and spread to distant organs, and is responsible for the vast majority of cancer-related deaths. Preventing early metastatic dissemination would revolutionize the ability to fight cancer. Unfortunately, the relatively poor understanding of the molecular underpinnings of metastasis has hampered the development of effective anti-metastatic drugs. Although it is now accepted that disseminating tumour cells need to acquire multiple competencies to face the many obstacles they encounter before reaching their metastatic site(s), whether these competencies are acquired through an accumulation of metastasis-specific genetic alterations and/or non-genetic events is often debated. Here we review a growing body of literature highlighting the importance of both genetic and non-genetic reprogramming events during the metastatic cascade, and discuss how genetic and non-genetic processes act in concert to confer metastatic competencies. We also describe how recent technological advances, and in particular the advent of single-cell multi-omics and barcoding approaches, will help to better elucidate the cross-talk between genetic and non-genetic mechanisms of metastasis and ultimately inform innovative paths for the early detection and interception of this lethal process.

Genetic Tools for Cell Lineage Tracing and Profiling Developmental Trajectories in the Skin

The epidermis is the body's first line of protection against dehydration and pathogens, continually regenerating the outermost protective skin layers throughout life. During both embryonic development and wound healing, epidermal stem and progenitor cells must respond to external stimuli and insults to build, maintain, and repair the cutaneous barrier. Recent advances in CRISPR-based methods for cell lineage tracing have remarkably expanded the potential for experiments that track stem and progenitor cell proliferation and differentiation over the course of tissue and even organismal development. Additional tools for DNA-based recording of cellular signaling cues promise to deepen our understanding of the mechanisms driving normal skin morphogenesis and response to stressors as well as the dysregulation of cell proliferation and differentiation in skin diseases and cancer. In this review, we highlight cutting-edge methods for cell lineage tracing, including in organoids and model organisms, and explore how cutaneous biology researchers might leverage these techniques to elucidate the developmental programs that support the regenerative capacity and plasticity of the skin.

PhyloVelo enhances transcriptomic velocity field mapping using monotonically expressed genes

Single-cell RNA sequencing (scRNA-seq) is a powerful approach for studying cellular differentiation, but accurately tracking cell fate transitions can be challenging, especially in disease conditions. Here we introduce PhyloVelo, a computational framework that estimates the velocity of transcriptomic dynamics by using monotonically expressed genes (MEGs) or genes with expression patterns that either increase or decrease, but do not cycle, through phylogenetic time. Through integration of scRNA-seq data with lineage information, PhyloVelo identifies MEGs and reconstructs a transcriptomic velocity field. We validate PhyloVelo using simulated data and Caenorhabditis elegans ground truth data, successfully recovering linear, bifurcated and convergent differentiations. Applying PhyloVelo to seven lineage-traced scRNA-seq datasets, generated using CRISPR-Cas9 editing, lentiviral barcoding or immune repertoire profiling, demonstrates its high accuracy and robustness in inferring complex lineage trajectories while outperforming RNA velocity. Additionally, we discovered that MEGs across tissues and organisms share similar functions in translation and ribosome biogenesis.

Nanomedomics

Nanomaterials have attractive physicochemical properties. A variety of nanomaterials such as inorganic, lipid, polymers, and protein nanoparticles have been widely developed for nanomedicine via chemical conjugation or physical encapsulation of bioactive molecules. Superior to traditional drugs, nanomedicines offer high biocompatibility, good water solubility, long blood circulation times, and tumor-targeting properties. Capitalizing on this, several nanoformulations have already been clinically approved and many others are currently being studied in clinical trials. Despite their undoubtful success, the molecular mechanism of action of the vast majority of nanomedicines remains poorly understood. To tackle this limitation, herein, this review critically discusses the strategy of applying multiomics analysis to study the mechanism of action of nanomedicines, named nanomedomics, including advantages, applications, and future directions. A comprehensive understanding of the molecular mechanism could provide valuable insight and therefore foster the development and clinical translation of nanomedicines.

Th17 Cells Secrete TWEAK to Trigger Epithelial-Mesenchymal Transition and Promote Colorectal Cancer Liver Metastasis

Liver metastasis is the leading cause of mortality in patients with colorectal cancer. Given the significance of both epithelial-mesenchymal transition (EMT) of tumor cells and the immune microenvironment in colorectal cancer liver metastasis (CRLM), the interplay between them could hold the key for developing improved treatment options. We employed multiomics analysis of 130 samples from 18 patients with synchronous CRLM integrated with external datasets to comprehensively evaluate the interaction between immune cells and EMT of tumor cells in liver metastasis. Single-cell RNA sequencing analysis revealed distinct distributions of nonmalignant cells between primary tumors from patients with metastatic colorectal cancer (mCRC) and non-metastatic colorectal cancer, showing that Th17 cells were predominantly enriched in the primary lesion of mCRC. TWEAK, a cytokine secreted by Th17 cells, promoted EMT by binding to receptor Fn14 on tumor cells, and the TWEAK-Fn14 interaction enhanced tumor migration and invasion. In mouse models, targeting Fn14 using CRISPR-induced knockout or lipid nanoparticle-encapsulated siRNA alleviated metastasis and prolonged survival. Mice lacking Il17a or Tnfsf12 (encoding TWEAK) exhibited fewer metastases compared with wild-type mice, while cotransfer of Th17 with tumor cells promoted liver metastasis. Higher TWEAK expression was associated with a worse prognosis in patients with colorectal cancer. In addition, CD163L1+ macrophages interacted with Th17 cells, recruiting Th17 via the CCL4-CCR5 axis. Collectively, this study unveils the role of immune cells in the EMT process and identifies TWEAK secreted by Th17 as a driver of CRLM.

SIGNIFICANCE

TWEAK secreted by Th17 cells promotes EMT by binding to Fn14 on colorectal cancer cells, suggesting that blocking the TWEAK-Fn14 interaction may be a promising therapeutic approach to inhibit liver metastasis.

Cancer spreading patterns based on epithelial-mesenchymal plasticity

Introduction: Metastasis is a major cause of cancer-related deaths, underscoring the necessity to discern the rules and patterns of cancer cell spreading. Epithelial-mesenchymal plasticity contributes to cancer aggressiveness and metastasis. Despite establishing key determinants of cancer aggressiveness and metastatic ability, a comprehensive understanding of the underlying mechanism is unknown. We aimed to propose a classification system for cancer cells based on epithelial-mesenchymal plasticity, focusing on hysteresis of the epithelial-mesenchymal transition and the hybrid epithelial/mesenchymal phenotype. Methods: We extensively reviewed the concept of epithelial-mesenchymal plasticity, specifically considering the hysteresis of the epithelial-mesenchymal transition and the hybrid epithelial/mesenchymal phenotype. Results: In this review and hypothesis article, based on epithelial-mesenchymal plasticity, especially the hysteresis of epithelial-mesenchymal transition and the hybrid epithelial/mesenchymal phenotype, we proposed a classification of cancer cells, indicating that cancer cells with epithelial-mesenchymal plasticity potential could be classified into four types: irreversible hysteresis, weak hysteresis, strong hysteresis, and hybrid epithelial/mesenchymal phenotype. These four types of cancer cells had varied biology, spreading features, and prognoses. Discussion: Our results highlight that the proposed classification system offers insights into the diverse behaviors of cancer cells, providing implications for cancer aggressiveness and metastasis.

Single cell lineage tracing reveals clonal dynamics of anti-EGFR therapy resistance in triple negative breast cancer

BACKGROUND

Most primary Triple Negative Breast Cancers (TNBCs) show amplification of the Epidermal Growth Factor Receptor (EGFR) gene, leading to increased protein expression. However, unlike other EGFR-driven cancers, targeting this receptor in TNBC yields inconsistent therapeutic responses.

METHODS

To elucidate the underlying mechanisms of this variability, we employ cellular barcoding and single-cell transcriptomics to reconstruct the subclonal dynamics of EGFR-amplified TNBC cells in response to afatinib, a tyrosine kinase inhibitor (TKI) that irreversibly inhibits EGFR.

RESULTS

Integrated lineage tracing analysis revealed a rare pre-existing subpopulation of cells with distinct biological signature, including elevated expression levels of Insulin-Like Growth Factor Binding Protein 2 (IGFBP2). We show that IGFBP2 overexpression is sufficient to render TNBC cells tolerant to afatinib treatment by activating the compensatory insulin-like growth factor I receptor (IGF1-R) signalling pathway. Finally, based on reconstructed mechanisms of resistance, we employ deep learning techniques to predict the afatinib sensitivity of TNBC cells.

CONCLUSIONS

Our strategy proved effective in reconstructing the complex signalling network driving EGFR-targeted therapy resistance, offering new insights for the development of individualized treatment strategies in TNBC.

Redox signalling regulates breast cancer metastasis via phenotypic and metabolic reprogramming due to p63 activation by HIF1α

BACKGROUND

Redox signaling caused by knockdown (KD) of Glutathione Peroxidase 2 (GPx2) in the PyMT mammary tumour model promotes metastasis via phenotypic and metabolic reprogramming. However, the tumour cell subpopulations and transcriptional regulators governing these processes remained unknown.

METHODS

We used single-cell transcriptomics to decipher the tumour cell subpopulations stimulated by GPx2 KD in the PyMT mammary tumour and paired pulmonary metastases. We analyzed the EMT spectrum across the various tumour cell clusters using pseudotime trajectory analysis and elucidated the transcriptional and metabolic regulation of the hybrid EMT state.

RESULTS

Integration of single-cell transcriptomics between the PyMT/GPx2 KD primary tumour and paired lung metastases unraveled a basal/mesenchymal-like cluster and several luminal-like clusters spanning an EMT spectrum. Interestingly, the luminal clusters at the primary tumour gained mesenchymal gene expression, resulting in epithelial/mesenchymal subpopulations fueled by oxidative phosphorylation (OXPHOS) and glycolysis. By contrast, at distant metastasis, the basal/mesenchymal-like cluster gained luminal and mesenchymal gene expression, resulting in a hybrid subpopulation using OXPHOS, supporting adaptive plasticity. Furthermore, p63 was dramatically upregulated in all hybrid clusters, implying a role in regulating partial EMT and MET at primary and distant sites, respectively. Importantly, these effects were reversed by HIF1α loss or GPx2 gain of function, resulting in metastasis suppression.

CONCLUSIONS

Collectively, these results underscored a dramatic effect of redox signaling on p63 activation by HIF1α, underlying phenotypic and metabolic plasticity leading to mammary tumour metastasis.

Gene-expression memory-based prediction of cell lineages from scRNA-seq datasets

Assigning single cell transcriptomes to cellular lineage trees by lineage tracing has transformed our understanding of differentiation during development, regeneration, and disease. However, lineage tracing is technically demanding, often restricted in time-resolution, and most scRNA-seq datasets are devoid of lineage information. Here we introduce Gene Expression Memory-based Lineage Inference (GEMLI), a computational tool allowing to robustly identify small to medium-sized cell lineages solely from scRNA-seq datasets. GEMLI allows to study heritable gene expression, to discriminate symmetric and asymmetric cell fate decisions and to reconstruct individual multicellular structures from pooled scRNA-seq datasets. In human breast cancer biopsies, GEMLI reveals previously unknown gene expression changes at the onset of cancer invasiveness. The universal applicability of GEMLI allows studying the role of small cell lineages in a wide range of physiological and pathological contexts, notably in vivo. GEMLI is available as an R package on GitHub ( https://github.com/UPSUTER/GEMLI ).

Hierarchal single-cell lineage tracing reveals differential fate commitment of CD8 T-cell clones in response to acute infection

Generating balanced populations of CD8 effector and memory T cells is necessary for immediate and durable immunity to infections and cancer. Yet, a definitive understanding of CD8 differentiation remains unclear. We used CARLIN, a processive lineage recording mouse model with single-cell RNA-seq and TCR-seq to track endogenous antigen-specific CD8 T cells during acute viral infection. We identified a diverse repertoire of expanded T-cell clones represented by seven transcriptional states. TCR enrichment analysis revealed differential memory- or effector-fate biases within clonal populations. Shared Vb segments and amino acid motifs were found within biased categories despite high TCR diversity. Using single-cell CARLIN barcode-seq we tracked multi-generational clones and found that unlike unbiased or memory-biased clones, which stably retain their fate profiles, effector-biased clones could adopt memory- or effector-bias within subclones. Collectively, our study demonstrates that a heterogenous T-cell repertoire specific for a shared antigen is composed of clones with distinct TCR-intrinsic fate-biases.

How much do we know about the metastatic process?

Cancer cells can leave their primary sites and travel through the circulation to distant sites, where they lodge as disseminated cancer cells (DCCs), even during the early and asymptomatic stages of tumor progression. In experimental models and clinical samples, DCCs can be detected in a non-proliferative state, defined as cellular dormancy. This state can persist for extended periods until DCCs reawaken, usually in response to niche-derived reactivation signals. Therefore, their clinical detection in sites like lymph nodes and bone marrow is linked to poor survival. Current cancer therapy designs are based on the biology of the primary tumor and do not target the biology of the dormant DCC population and thus fail to eradicate the initial or subsequent waves of metastasis. In this brief review, we discuss the current methods for detecting DCCs and highlight new strategies that aim to target DCCs that constitute minimal residual disease to reduce or prevent metastasis formation. Furthermore, we present current evidence on the relevance of DCCs derived from early stages of tumor progression in metastatic disease and describe the animal models available for their study. We also discuss our current understanding of the dissemination mechanisms utilized by genetically less- and more-advanced cancer cells, which include the functional analysis of intermediate or hybrid states of epithelial-mesenchymal transition (EMT). Finally, we raise some intriguing questions regarding the clinical impact of studying the crosstalk between evolutionary waves of DCCs and the initiation of metastatic disease.

Molecular profile of metastasis, cell plasticity and EMT in pancreatic cancer: a pre-clinical connection to aggressiveness and drug resistance

The metastasis is a multistep process in which a small proportion of cancer cells are detached from the colony to enter into blood cells for obtaining a new place for metastasis and proliferation. The metastasis and cell plasticity are considered major causes of cancer-related deaths since they improve the malignancy of cancer cells and provide poor prognosis for patients. Furthermore, enhancement in the aggressiveness of cancer cells has been related to the development of drug resistance. Metastasis of pancreatic cancer (PC) cells has been considered one of the major causes of death in patients and their undesirable prognosis. PC is among the most malignant tumors of the gastrointestinal tract and in addition to lifestyle, smoking, and other factors, genomic changes play a key role in its progression. The stimulation of EMT in PC cells occurs as a result of changes in molecular interaction, and in addition to increasing metastasis, EMT participates in the development of chemoresistance. The epithelial, mesenchymal, and acinar cell plasticity can occur and determines the progression of PC. The major molecular pathways including STAT3, PTEN, PI3K/Akt, and Wnt participate in regulating the metastasis of PC cells. The communication in tumor microenvironment can provide by exosomes in determining PC metastasis. The components of tumor microenvironment including macrophages, neutrophils, and cancer-associated fibroblasts can modulate PC progression and the response of cancer cells to chemotherapy.

Increased heterogeneity in expression of genes associated with cancer progression and drug resistance

Fluctuations in the number of regulatory molecules and differences in timings of molecular events can generate variation in gene expression among genetically identical cells in the same environmental condition. This variation, termed as expression noise, can create differences in metabolic state and cellular functions, leading to phenotypic heterogeneity. Expression noise and phenotypic heterogeneity have been recognized as important contributors to intra-tumor heterogeneity, and have been associated with cancer growth, progression, and therapy resistance. However, how expression noise changes with cancer progression in actual cancer patients has remained poorly explored. Such an analysis, through identification of genes with increasing expression noise, can provide valuable insights into generation of intra-tumor heterogeneity, and could have important implications for understanding immune-suppression, drug tolerance and therapy resistance. In this work, we performed a genome-wide identification of changes in gene expression noise with cancer progression using single-cell RNA-seq data of lung adenocarcinoma patients at different stages of cancer. We identified 37 genes in epithelial cells that showed an increasing noise trend with cancer progression, many of which were also associated with cancer growth, EMT and therapy resistance. We found that expression of several of these genes was positively associated with expression of mitochondrial genes, suggesting an important role of mitochondria in generation of heterogeneity. In addition, we uncovered substantial differences in sample-specific noise profiles which could have implications for personalized prognosis and treatment.

Exact and efficient phylodynamic simulation from arbitrarily large populations

Many biological studies involve inferring the genealogical history of a sample of individuals from a large population and interpreting the reconstructed tree. Such an ascertained tree typically represents only a small part of a comprehensive population tree and is distorted by survivorship and sampling biases. Inferring evolutionary parameters from ascertained trees requires modeling both the underlying population dynamics and the ascertainment process. A crucial component of this phylodynamic modeling involves tree simulation, which is used to benchmark probabilistic inference methods. To simulate an ascertained tree, one must first simulate the full population tree and then prune unobserved lineages. Consequently, the computational cost is determined not by the size of the final simulated tree, but by the size of the population tree in which it is embedded. In most biological scenarios, simulations of the entire population are prohibitively expensive due to computational demands placed on lineages without sampled descendants. Here, we address this challenge by proving that, for any partially ascertained process from a general multi-type birth-death-mutation-sampling (BDMS) model, there exists an equivalent pure birth process (i.e., no death) with mutation and complete sampling. The final trees generated under these processes have exactly the same distribution. Leveraging this property, we propose a highly efficient algorithm for simulating trees under a general BDMS model. Our algorithm scales linearly with the size of the final simulated tree and is independent of the population size, enabling simulations from extremely large populations beyond the reach of current methods but essential for various biological applications. We anticipate that this unprecedented speedup will significantly advance the development of novel inference methods that require extensive training data.

How studies in developmental epithelial-mesenchymal transition and mesenchymal-epithelial transition inspired new research paradigms in biomedicine

Epithelial-mesenchymal transition (EMT) and its reverse mechanism, mesenchymal-epithelial transition (MET), are evolutionarily conserved mechanisms initially identified in studies of early metazoan development. EMT may even have been established in choanoflagellates, the closest unicellular relative of Metazoa. These crucial morphological transitions operate during body plan formation and subsequently in organogenesis. These findings have prompted an increasing number of investigators in biomedicine to assess the importance of such mechanisms that drive epithelial cell plasticity in multiple diseases associated with congenital disabilities and fibrosis, and, most importantly, in the progression of carcinoma. EMT and MET also play crucial roles in regenerative medicine, notably by contributing epigenetic changes in somatic cells to initiate reprogramming into stem cells and their subsequent differentiation into distinct lineages.

Studying temporal dynamics of single cells: expression, lineage and regulatory networks

Learning how multicellular organs are developed from single cells to different cell types is a fundamental problem in biology. With the high-throughput scRNA-seq technology, computational methods have been developed to reveal the temporal dynamics of single cells from transcriptomic data, from phenomena on cell trajectories to the underlying mechanism that formed the trajectory. There are several distinct families of computational methods including Trajectory Inference (TI), Lineage Tracing (LT), and Gene Regulatory Network (GRN) Inference which are involved in such studies. This review summarizes these computational approaches which use scRNA-seq data to study cell differentiation and cell fate specification as well as the advantages and limitations of different methods. We further discuss how GRNs can potentially affect cell fate decisions and trajectory structures.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12551-023-01090-5.

How important is EMT for cancer metastasis?

Epithelial-to-mesenchymal transition (EMT), a biological phenomenon of cellular plasticity initially reported in embryonic development, has been increasingly recognized for its importance in cancer progression and metastasis. Despite tremendous progress being made in the past 2 decades in our understanding of the molecular mechanism and functional importance of EMT in cancer, there are several mysteries around EMT that remain unresolved. In this Unsolved Mystery, we focus on the variety of EMT types in metastasis, cooperative and collective EMT behaviors, spatiotemporal characterization of EMT, and strategies of therapeutically targeting EMT. We also highlight new technical advances that will facilitate the efforts to elucidate the unsolved mysteries of EMT in metastasis.

Single-cell analysis of immune and stroma cell remodeling in clear cell renal cell carcinoma primary tumors and bone metastatic lesions

BACKGROUND

Despite therapeutic advances, once a cancer has metastasized to the bone, it represents a highly morbid and lethal disease. One third of patients with advanced clear cell renal cell carcinoma (ccRCC) present with bone metastasis at the time of diagnosis. However, the bone metastatic niche in humans, including the immune and stromal microenvironments, has not been well-defined, hindering progress towards identification of therapeutic targets.

METHODS

We collected fresh patient samples and performed single-cell transcriptomic profiling of solid metastatic tissue (Bone Met), liquid bone marrow at the vertebral level of spinal cord compression (Involved), and liquid bone marrow from a different vertebral body distant from the tumor site but within the surgical field (Distal), as well as bone marrow from patients undergoing hip replacement surgery (Benign). In addition, we incorporated single-cell data from primary ccRCC tumors (ccRCC Primary) for comparative analysis.

RESULTS

The bone marrow of metastatic patients is immune-suppressive, featuring increased, exhausted CD8 + cytotoxic T cells, T regulatory cells, and tumor-associated macrophages (TAM) with distinct transcriptional states in metastatic lesions. Bone marrow stroma from tumor samples demonstrated a tumor-associated mesenchymal stromal cell population (TA-MSC) that appears to be supportive of epithelial-to mesenchymal transition (EMT), bone remodeling, and a cancer-associated fibroblast (CAFs) phenotype. This stromal subset is associated with poor progression-free and overall survival and also markedly upregulates bone remodeling through the dysregulation of RANK/RANKL/OPG signaling activity in bone cells, ultimately leading to bone resorption.

CONCLUSIONS

These results provide a comprehensive analysis of the bone marrow niche in the setting of human metastatic cancer and highlight potential therapeutic targets for both cell populations and communication channels.

Update on Epithelial-Mesenchymal Plasticity in Cancer Progression

Epithelial-mesenchymal transition (EMT) is a cellular process by which epithelial cells lose their characteristics and acquire mesenchymal traits to promote cell movement. This program is aberrantly activated in human cancers and endows tumor cells with increased abilities in tumor initiation, cell migration, invasion, metastasis, and therapy resistance. The EMT program in tumors is rarely binary and often leads to a series of gradual or intermediate epithelial-mesenchymal states. Functionally, epithelial-mesenchymal plasticity (EMP) improves the fitness of cancer cells during tumor progression and in response to therapies. Here, we discuss the most recent advances in our understanding of the diverse roles of EMP in tumor initiation, progression, metastasis, and therapy resistance and address major clinical challenges due to EMP-driven phenotypic heterogeneity in cancer. Uncovering novel molecular markers and key regulators of EMP in cancer will aid the development of new therapeutic strategies to prevent cancer recurrence and overcome therapy resistance.

Cancer as a Disease of Development Gone Awry

In the 160 years since Rudolf Virchow first postulated that neoplasia arises by the same law that regulates embryonic development, scientists have come to recognize the striking overlap between the molecular and cellular programs used by cancers and embryos. Advances in cancer biology and molecular techniques have further highlighted the similarities between carcinogenesis and embryogenesis, where cellular growth, differentiation, motility, and intercellular cross talk are mediated by common drivers and regulatory networks. This review highlights the many connections linking cancer biology and developmental biology to provide a deeper understanding of how a tissue's developmental history may both enable and constrain cancer cell evolution.

Lineage Plasticity: The New Cancer Hallmark on the Block

Plasticity refers to the ability of cells to adopt a spectrum of states or phenotypes. In cancer, it is a critical contributor to tumor initiation, progression, invasiveness, and therapy resistance, and it has recently been recognized as an emerging cancer hallmark. Plasticity can occur as a result of cell-intrinsic factors (e.g., genetic, transcriptional, or epigenetic fluctuations), or through cell-extrinsic cues (e.g., signaling from components of the tumor microenvironment or selective pressure from therapy). Over the past decade, technological advances, analysis of patient samples, and studies in mouse model systems have led to a deeper understanding of how such plastic states come about. In this review, we discuss: (i) the definition of plasticity; (ii) methods to measure and quantify plasticity; (iii) the clinical relevance of plasticity; and (iv) therapeutic hypotheses to modulate plasticity in the clinic.

Charting Single Cell Lineage Dynamics and Mutation Networks via Homing CRISPR

Single cell lineage tracing, essential for unraveling cellular dynamics in disease evolution is critical for developing targeted therapies. CRISPR-Cas9, known for inducing permanent and cumulative mutations, is a cornerstone in lineage tracing. The novel homing guide RNA (hgRNA) technology enhances this by enabling dynamic retargeting and facilitating ongoing genetic modifications. Charting these mutations, especially through successive hgRNA edits, poses a significant challenge. Our solution, LINEMAP, is a computational framework designed to trace and map these mutations with precision. LINEMAP meticulously discerns mutation alleles at single-cell resolution and maps their complex interrelationships through a mutation evolution network. By utilizing a Markov Process model, we can predict mutation transition probabilities, revealing potential mutational routes and pathways. Our reconstruction algorithm, anchored in the Markov model's attributes, reconstructs cellular lineage pathways, shedding light on the cell's evolutionary journey to the minutiae of single-cell division. Our findings reveal an intricate network of mutation evolution paired with a predictive Markov model, advancing our capability to reconstruct single-cell lineage via hgRNA. This has substantial implications for advancing our understanding of biological mechanisms and propelling medical research forward.

Reconstructing cell lineage trees with genomic barcoding: approaches and applications

In multicellular organisms, developmental history of cell divisions and functional annotation of terminal cells can be organized into a cell lineage tree (CLT). The reconstruction of the CLT has long been a major goal in developmental biology and other related fields. Recent technological advancements, especially those in editable genomic barcodes and single-cell high-throughput sequencing, have sparked a new wave of experimental methods for reconstructing CLTs. Here we review the existing experimental approaches to the reconstruction of CLT, which are broadly categorized as either image-based or DNA barcode-based methods. In addition, we present a summary of the related literature based on the biological insight provided by the obtained CLTs. Moreover, we discuss the challenges that will arise as more and better CLT data become available in the near future. Genomic barcoding-based CLT reconstructions and analyses, due to their wide applicability and high scalability, offer the potential for novel biological discoveries, especially those related to general and systemic properties of the developmental process.

SETD2 loss in renal epithelial cells drives epithelial-to-mesenchymal transition in a TGF-β-independent manner

Histone-lysine N-methyltransferase SETD2 (SETD2), the sole histone methyltransferase that catalyzes trimethylation of lysine 36 on histone H3 (H3K36me3), is often mutated in clear cell renal cell carcinoma (ccRCC). SETD2 mutation and/or loss of H3K36me3 is linked to metastasis and poor outcome in ccRCC patients. Epithelial-to-mesenchymal transition (EMT) is a major pathway that drives invasion and metastasis in various cancer types. Here, using novel kidney epithelial cell lines isogenic for SETD2, we discovered that SETD2 inactivation drives EMT and promotes migration, invasion, and stemness in a transforming growth factor-beta-independent manner. This newly identified EMT program is triggered in part through secreted factors, including cytokines and growth factors, and through transcriptional reprogramming. RNA-seq and assay for transposase-accessible chromatin sequencing uncovered key transcription factors upregulated upon SETD2 loss, including SOX2, POU2F2 (OCT2), and PRRX1, that could individually drive EMT and stemness phenotypes in SETD2 wild-type (WT) cells. Public expression data from SETD2 WT/mutant ccRCC support the EMT transcriptional signatures derived from cell line models. In summary, our studies reveal that SETD2 is a key regulator of EMT phenotypes through cell-intrinsic and cell-extrinsic mechanisms that help explain the association between SETD2 loss and ccRCC metastasis.

Cancer-Associated Fibroblast-Like Tumor Cells Remodel the Ewing Sarcoma Tumor Microenvironment

PURPOSE

Despite limited genetic and histologic heterogeneity, Ewing sarcoma (EwS) tumor cells are transcriptionally heterogeneous and display varying degrees of mesenchymal lineage specification in vitro. In this study, we investigated if and how transcriptional heterogeneity of EwS cells contributes to heterogeneity of tumor phenotypes in vivo.

EXPERIMENTAL DESIGN

Single-cell proteogenomic-sequencing of EwS cell lines was performed and integrated with patient tumor transcriptomic data. Cell subpopulations were isolated by FACS for assessment of gene expression and phenotype. Digital spatial profiling and human whole transcriptome analysis interrogated transcriptomic heterogeneity in EwS xenografts. Tumor cell subpopulations and matrix protein deposition were evaluated in xenografts and patient tumors using multiplex immunofluorescence staining.

RESULTS

We identified CD73 as a biomarker of highly mesenchymal EwS cell subpopulations in tumor models and patient biopsies. CD73+ tumor cells displayed distinct transcriptional and phenotypic properties, including selective upregulation of genes that are repressed by EWS::FLI1, and increased migratory potential. CD73+ cells were distinguished in vitro and in vivo by increased expression of matrisomal genes and abundant deposition of extracellular matrix (ECM) proteins. In epithelial-derived malignancies, ECM is largely deposited by cancer-associated fibroblasts (CAF), and we thus labeled CD73+ EwS cells, CAF-like tumor cells. Marked heterogeneity of CD73+ EwS cell frequency and distribution was detected in tumors in situ, and CAF-like tumor cells and associated ECM were observed in peri-necrotic regions and invasive foci.

CONCLUSIONS

EwS tumor cells can adopt CAF-like properties, and these distinct cell subpopulations contribute to tumor heterogeneity by remodeling the tumor microenvironment. See related commentary by Kuo and Amatruda, p. 5002.

Mesenchymal ovarian cancer cells promote CD8+ T cell exhaustion through the LGALS3-LAG3 axis

Cancer cells often metastasize by undergoing an epithelial-mesenchymal transition (EMT). Although abundance of CD8+ T-cells in the tumor microenvironment correlates with improved survival, mesenchymal cancer cells acquire greater resistance to antitumor immunity in some cancers. We hypothesized the EMT modulates the immune response to ovarian cancer. Here we show that cancer cells from infiltrated/inflamed tumors possess more mesenchymal cells, than excluded and desert tumors. We also noted high expression of LGALS3 is associated with EMT in vivo, a finding validated with in vitro EMT models. Dissecting the cellular communications among populations in the tumor revealed that mesenchymal cancer cells in infiltrated tumors communicate through LGALS3 to LAG3 receptor expressed by CD8+ T cells. We found CD8+ T cells express high levels of LAG3, a marker of T cell exhaustion. The results indicate that EMT in ovarian cancer cells promotes interactions between cancer cells and T cells through the LGALS3 - LAG3 axis, which could increase T cell exhaustion in infiltrated tumors, dampening antitumor immunity.

TGF-β, EMT, and resistance to anti-cancer treatment

Transforming growth factor-β (TGF-β) signaling regulates cell-specific programs involved in embryonic development, wound-healing, and immune homeostasis. Yet, during tumor progression, these TGF-β-mediated programs are altered, leading to epithelial cell plasticity and a reprogramming of epithelial cells into mesenchymal lineages through epithelial-to-mesenchymal transition (EMT), a critical developmental program in morphogenesis and organogenesis. These changes, in turn, lead to enhanced carcinoma cell invasion, metastasis, immune cell differentiation, immune evasion, and chemotherapy resistance. Here, we discuss EMT as one of the critical programs associated with carcinoma cell plasticity and the influence exerted by TGF-β on carcinoma status and function. We further explore the composition of carcinoma and other cell populations within the tumor microenvironment, and consider the relevant outcomes related to the programs associated with cancer treatment resistance.

Cusp bifurcation in a metastatic regulatory network

Understanding the potential for cancers to metastasize is still relatively unknown. While many predictive methods may use deep learning or stochastic processes, we highlight a long standing mathematical concept that may be useful for modeling metastatic breast cancer systems. Ordinary differential equations (ODEs) can model cell state transitions by considering the pertinent environmental variables as well as the paths systems take over time. Bifurcation theory is a branch of dynamical systems which studies changes in the behavior of an ODE system while one or more parameters are varied. Many studies have applied concepts in one-parameter bifurcation theory to model biological network dynamics, and cell division. However, studies of two-parameter bifurcations are much more rare. Two-parameter bifurcations have not been studied in metastatic systems. Here we show how a specific two-parameter bifurcation phenomenon called a cusp bifurcation separates two qualitatively different metastatic cell state transitions modalities and propose a new perspective on defining such transitions based on mathematical theory. We hope the observations and verification methods detailed here may help in the understanding of metastatic potential from a basic biological perspective and in clinical settings.

Stochastic epithelial-mesenchymal transitions diversify non-cancerous lung cell behaviours

Epithelial-mesenchymal plasticity (EMP) is a hallmark of cancer. By enabling cells to shift between different morphological and functional states, EMP promotes invasion, metastasis and therapy resistance. We report that near-diploid non-cancerous human epithelial lung cells spontaneously shift along the EMP spectrum without genetic changes. Strikingly, more than half of single cell-derived clones adopt a mesenchymal morphology. We independently characterise epithelial-like and mesenchymal-like clones. Mesenchymal clones lose epithelial markers, display larger cell aspect ratios and lower motility, with mostly unaltered proliferation rates. Stemness marker expression and metabolic rewiring diverge independently of phenotypes. In 3D culture, more epithelial clones become mesenchymal-like. Thus, non-cancerous epithelial cells may acquire cancer metastasis-associated features prior to genetic alterations and cancerous transformation.

Identification of a 24-gene panel and a novel marker of PODXL2 essential for the pathological diagnosis of early prostate cancer

Precise diagnosis of early prostate cancer (PCa) is critical for preventing tumor progression. However, the diagnostic outcomes of currently used markers are far from satisfactory due to the low sensitivity or specificity. Here, we identified a diagnostic subpopulation in PCa tissue with the integrating analysis of single-cell and bulk RNA-seq. The representative markers of this subpopulation were extracted to perform intersection analysis with early-PCa-related gene module generated from weighted correlation network analysis (WGCNA). A total of 24 overlapping genes were obtained, the diagnostic roles of which were validated by distinguishing normal and tumorous prostate samples from the public dataset. A least absolute shrinkage and selection operator (LASSO) model was constructed based on these genes and the obtained 24-gene panel showed high sensitivity and specificity for PCa diagnosis, with better identifying capability of PCa than the commercially used gene panel of Oncotype DX. The top two risk factors, TRPM4 and PODXL2, were verified to be highly expressed in early PCa tissues by multiplex immunostaining, and PODXL2 was more sensitive and specific compared to TRPM4 and the pathologically used marker AMACR for early PCa diagnosis, suggesting a novel and promising pathology marker.

HMG-CoA reductase degrader, SR-12813, counteracts statin-induced upregulation of HMG-CoA reductase and augments the anticancer effect of atorvastatin

Statins are cholesterol-lowering drugs that have exhibited potential as cancer therapeutic agents. However, as some cancer cells are resistant to statins, broadening an anticancer spectrum of statins is desirable. The upregulated expression of the statin target enzyme, 3-hydroxy-3-methyl-glutaryl-coenzyme A (HMG-CoA) reductase (HMGCR), in statin-treated cancer cells is a well-known mechanism of statin resistance, which can be counteracted by the downregulation of HMGCR gene expression, or degradation of the HMGCR protein. However, the mechanism by which HMGCR degradation influences the anticancer effects of statins remain unreported. We tested the effect of the HMGCR degrader compound SR-12813 at a concentration that did not affect the growth of eight diverse tumor cell lines. Combined treatment with atorvastatin and a low concentration of SR-12813 led to lowering of increased HMGCR expression, and augmented the cytostatic effect of atorvastatin in both statin-resistant and -sensitive cancer cells compared with that of atorvastatin treatment alone. Dual-targeting of HMGCR using statins and SR-12813 (or similar compounds) could provide an improved anticancer therapeutic approach.