Multi-color clonal tracking reveals intra-stage proliferative heterogeneity during mammary tumor progression

Population dynamics is a cancer driver

Most tissues are continuously renovated through the division of stem cells and the death of old or damaged cells, which is known as the cell turnover rate (CTOR). Despite being in a steady state, tissues have different population dynamics thus producing diverse clonality levels. Here, we propose and test that cell population dynamics can be a cancer driver. We employed the evolutionary software esiCancer to show that CTOR, within a range comparable to what is observed in human tissues, can amplify the risk of a mutation due to ancestral selection (ANSEL). In a high CTOR tissue, a mutated ancestral cell is likely to be selected and persist over generations, which leads to a scenario of elevated ANSEL profile, characterized by few niches of large clones, which does not occur in low CTOR. We found that CTOR is significantly associated with the risk of developing cancer, even when correcting for mutation load, indicating that population dynamics per se is a cancer driver. This concept is central to understanding cancer risk and for the design of new therapeutic interventions that minimizes the contribution of ANSEL in cancer growth.

Breast cancers as ecosystems: a metabolic perspective

Breast cancer (BC) is the most frequently diagnosed cancer and one of the major causes of cancer death. Despite enormous progress in its management, both from the therapeutic and early diagnosis viewpoints, still around 700,000 patients succumb to the disease each year, worldwide. Late recurrency is the major problem in BC, with many patients developing distant metastases several years after the successful eradication of the primary tumor. This is linked to the phenomenon of metastatic dormancy, a still mysterious trait of the natural history of BC, and of several other types of cancer, by which metastatic cells remain dormant for long periods of time before becoming reactivated to initiate the clinical metastatic disease. In recent years, it has become clear that cancers are best understood if studied as ecosystems in which the impact of non-cancer-cell-autonomous events-dependent on complex interaction between the cancer and its environment, both local and systemic-plays a paramount role, probably as significant as the cell-autonomous alterations occurring in the cancer cell. In adopting this perspective, a metabolic vision of the cancer ecosystem is bound to improve our understanding of the natural history of cancer, across space and time. In BC, many metabolic pathways are coopted into the cancer ecosystem, to serve the anabolic and energy demands of the cancer. Their study is shedding new light on the most critical aspect of BC management, of metastatic dissemination, and that of the related phenomenon of dormancy and fostering the application of the knowledge to the development of metabolic therapies.

Implications of tumour heterogeneity on cancer evolution and therapy resistance: lessons from breast cancer

Tumour heterogeneity is pervasive amongst many cancers and leads to disease progression, and therapy resistance. In this review, using breast cancer as an exemplar, we focus on the recent advances in understanding the interplay between tumour cells and their microenvironment using single cell sequencing and digital spatial profiling technologies. Further, we discuss the utility of lineage tracing methodologies in pre-clinical models of breast cancer, and how these are being used to unravel new therapeutic vulnerabilities and reveal biomarkers of breast cancer progression. © 2023 The Pathological Society of Great Britain and Ireland.

Cellular barcoding tracks heterogeneous clones through selective pressures and phenotypic transitions

Genomic DNA barcoding has emerged as a sensitive and flexible tool to measure the fates of clonal subpopulations within a heterogeneous cancer cell population. Coupling cellular barcoding with single-cell transcriptomics permits the longitudinal analysis of molecular mechanisms with detailed clone-level resolution. Numerous recent studies have employed these tools to track clonal cell states in cancer progression and treatment response. With these new technologies comes the opportunity to examine longstanding questions about the origins and contributions of tumor cell heterogeneity and the roles of selection and phenotypic plasticity in disease progression and treatment.

Basal-like mammary carcinomas stimulate cancer stem cell properties through AXL-signaling to induce chemotherapy resistance

Basal-like breast cancer (BLBC) is the most aggressive and heterogeneous breast cancer (BC) subtype. Conventional chemotherapies represent next to surgery the most frequently employed treatment options. Unfortunately, resistant tumor phenotypes often develop, resulting in therapeutic failure. To identify the early events occurring upon the first drug application and initiating chemotherapy resistance in BLBC, we leveraged the WAP-T syngeneic mammary carcinoma mouse model and we developed a strategy combining magnetic-activated cell sorting (MACS)-based tumor cell enrichment with high-throughput transcriptome analyses. We discovered that chemotherapy induced a massive gene expression reprogramming toward stemness acquisition to tolerate and survive the cytotoxic treatment in vitro and in vivo. Retransplantation experiments revealed that one single cycle of cytotoxic drug combination therapy (Cyclophosphamide, Adriamycin and 5-Fluorouracil) suffices to induce resistant tumor cell phenotypes in vivo. We identified Axl and its ligand Pros1 as highly induced genes driving cancer stem cell (CSC) properties upon chemotherapy in vivo and in vitro. Furthermore, from our analysis of BLBC patient datasets, we found that AXL expression is also strongly correlated with CSC-gene signatures, a poor response to conventional therapies and worse survival outcomes in those patients. Finally, we demonstrate that AXL inhibition sensitized BLBC-cells to cytotoxic treatment in vitro. Together, our data support AXL as a promising therapeutic target to optimize the efficiency of conventional cytotoxic therapies in BLBC.

Lineage plasticity enables low-ER luminal tumors to evolve and gain basal-like traits

Stratifying breast cancer into specific molecular or histologic subtypes aids in therapeutic decision-making and predicting outcomes; however, these subtypes may not be as distinct as previously thought. Patients with luminal-like, estrogen receptor (ER)-expressing tumors have better prognosis than patients with more aggressive, triple-negative or basal-like tumors. There is, however, a subset of luminal-like tumors that express lower levels of ER, which exhibit more basal-like features. We have found that breast tumors expressing lower levels of ER, traditionally considered to be luminal-like, represent a distinct subset of breast cancer characterized by the emergence of basal-like features. Lineage tracing of low-ER tumors in the MMTV-PyMT mouse mammary tumor model revealed that basal marker-expressing cells arose from normal luminal epithelial cells, suggesting that luminal-to-basal plasticity is responsible for the evolution and emergence of basal-like characteristics. This plasticity allows tumor cells to gain a new lumino-basal phenotype, thus leading to intratumoral lumino-basal heterogeneity. Single-cell RNA sequencing revealed SOX10 as a potential driver for this plasticity, which is known among breast tumors to be almost exclusively expressed in triple-negative breast cancer (TNBC) and was also found to be highly expressed in low-ER tumors. These findings suggest that basal-like tumors may result from the evolutionary progression of luminal tumors with low ER expression.

Integration of quantitative methods and mathematical approaches for the modeling of cancer cell proliferation dynamics

Physiological processes rely on the control of cell proliferation, and the dysregulation of these processes underlies various pathological conditions, including cancer. Mathematical modeling can provide new insights into the complex regulation of cell proliferation dynamics. In this review, we first examine quantitative experimental approaches for measuring cell proliferation dynamics in vitro and compare the various types of data that can be obtained in these settings. We then explore the toolbox of common mathematical modeling frameworks that can describe cell behavior, dynamics, and interactions of proliferation. We discuss how these wet-laboratory studies may be integrated with different mathematical modeling approaches to aid the interpretation of the results and to enable the prediction of cell behaviors, specifically in the context of cancer.

Orchestration of Collective Migration and Metastasis by Tumor Cell Clusters

Metastatic dissemination has lethal consequences for cancer patients. Accruing evidence supports the hypothesis that tumor cells can migrate and metastasize as clusters of cells while maintaining contacts with one another. Collective metastasis enables tumor cells to colonize secondary sites more efficiently, resist cell death, and evade the immune system. On the other hand, tumor cell clusters face unique challenges for dissemination particularly during systemic dissemination. Here, we review recent progress toward understanding how tumor cell clusters overcome these disadvantages as well as mechanisms they utilize to gain advantages throughout the metastatic process. We consider useful models for studying collective metastasis and reflect on how the study of collective metastasis suggests new opportunities for eradicating and preventing metastatic disease.

Evolvability and emergence of tumor heterogeneity as a space-time function

The loss of control of cell proliferation, apoptosis regulation and contact inhibition leads to tumor development. While benign tumors are restricted to their primary space, i.e. where these tumors first originate, the metastatic tumors not only disseminate- facilitated by hypoxia-driven neovascularization- to distant secondary sites but also show substantial changes in metabolism, tissue architectures, gene expression profiles and immune phenotypes. All these alterations result in radio-, chemo- and immune-resistance rendering these metastatic tumor cells refractory to therapy. Since the beginning of the transformation, these factors- which influence each other- are incorporated to the developing and metastasizing tumor. As a result, the complexities in the heterogeneity of tumor progressively increase. This space-time function in the heterogeneity of tumors is generated by various conditions and factors at the genetic as well as microenvironmental levels, for example, endogenous retroviruses, methylation and epigenetic dysregulation that may be etiology-specific, cancer associated inflammation, remodeling of the extracellular matrix and mesenchymal cell shifted functions. On the one hand, these factors may cause de-differentiation of the tumor cells leading to cancer stem cells that contribute to radio-, chemo- and immune-resistance and recurrence of tumors. On the other hand, they may also enhance the heterogeneity under specific microenvironment-driven proliferation. In this editorial, we intend to underline the importance of heterogeneity in cancer progress, its evaluation and its use in correlation with the tumor evolution in a specific patient as a field of research for achieving precise patient-tailored treatments and amelioration of diagnostic (monitoring) tools and prognostic capacity.

Mastering the use of cellular barcoding to explore cancer heterogeneity

Tumours are often composed of a multitude of malignant clones that are genomically unique, and only a few of them may have the ability to escape cancer therapy and grow as symptomatic lesions. As a result, tumours with a large degree of genomic diversity have a higher chance of leading to patient death. However, clonal fate can be driven by non-genomic features. In this context, new technologies are emerging not only to track the spatiotemporal fate of individual cells and their progeny but also to study their molecular features using various omics analysis. In particular, the recent development of cellular barcoding facilitates the labelling of tens to millions of cancer clones and enables the identification of the complex mechanisms associated with clonal fate in different microenvironments and in response to therapy. In this Review, we highlight the recent discoveries made using lentiviral-based cellular barcoding techniques, namely genetic and optical barcoding. We also emphasize the strengths and limitations of each of these technologies and discuss some of the key concepts that must be taken into consideration when one is designing barcoding experiments. Finally, we suggest new directions to further improve the use of these technologies in cancer research.

Beyond Genetics: Metastasis as an Adaptive Response in Breast Cancer

Metastatic disease represents the primary cause of breast cancer (BC) mortality, yet it is still one of the most enigmatic processes in the biology of this tumor. Metastatic progression includes distinct phases: invasion, intravasation, hematogenous dissemination, extravasation and seeding at distant sites, micro-metastasis formation and metastatic outgrowth. Whole-genome sequencing analyses of primary BC and metastases revealed that BC metastatization is a non-genetically selected trait, rather the result of transcriptional and metabolic adaptation to the unfavorable microenvironmental conditions which cancer cells are exposed to (e.g., hypoxia, low nutrients, endoplasmic reticulum stress and chemotherapy administration). In this regard, the latest multi-omics analyses unveiled intra-tumor phenotypic heterogeneity, which determines the polyclonal nature of breast tumors and constitutes a challenge for clinicians, correlating with patient poor prognosis. The present work reviews BC classification and epidemiology, focusing on the impact of metastatic disease on patient prognosis and survival, while describing general principles and current in vitro/in vivo models of the BC metastatic cascade. The authors address here both genetic and phenotypic intrinsic heterogeneity of breast tumors, reporting the latest studies that support the role of the latter in metastatic spreading. Finally, the review illustrates the mechanisms underlying adaptive stress responses during BC metastatic progression.

3D imaging for driving cancer discovery

Our understanding of the cellular composition and architecture of cancer has primarily advanced using 2D models and thin slice samples. This has granted spatial information on fundamental cancer biology and treatment response. However, tissues contain a variety of interconnected cells with different functional states and shapes, and this complex organization is impossible to capture in a single plane. Furthermore, tumours have been shown to be highly heterogenous, requiring large-scale spatial analysis to reliably profile their cellular and structural composition. Volumetric imaging permits the visualization of intact biological samples, thereby revealing the spatio-phenotypic and dynamic traits of cancer. This review focuses on new insights into cancer biology uniquely brought to light by 3D imaging and concomitant progress in cancer modelling and quantitative analysis. 3D imaging has the potential to generate broad knowledge advance from major mechanisms of tumour progression to new strategies for cancer treatment and patient diagnosis. We discuss the expected future contributions of the newest imaging trends towards these goals and the challenges faced for reaching their full application in cancer research.

Spatial omics and multiplexed imaging to explore cancer biology

Understanding intratumoral heterogeneity-the molecular variation among cells within a tumor-promises to address outstanding questions in cancer biology and improve the diagnosis and treatment of specific cancer subtypes. Single-cell analyses, especially RNA sequencing and other genomics modalities, have been transformative in revealing novel biomarkers and molecular regulators associated with tumor growth, metastasis and drug resistance. However, these approaches fail to provide a complete picture of tumor biology, as information on cellular location within the tumor microenvironment is lost. New technologies leveraging multiplexed fluorescence, DNA, RNA and isotope labeling enable the detection of tens to thousands of cancer subclones or molecular biomarkers within their native spatial context. The expeditious growth in these techniques, along with methods for multiomics data integration, promises to yield a more comprehensive understanding of cell-to-cell variation within and between individual tumors. Here we provide the current state and future perspectives on the spatial technologies expected to drive the next generation of research and diagnostic and therapeutic strategies for cancer.

The site of breast cancer metastases dictates their clonal composition and reversible transcriptomic profile

Intratumoral heterogeneity is a driver of breast cancer progression, but the nature of the clonal interactive network involved in this process remains unclear. Here, we optimized the use of optical barcoding to visualize and characterize 31 cancer subclones in vivo. By mapping the clonal composition of thousands of metastases in two clinically relevant sites, the lungs and liver, we found that metastases were highly polyclonal in lungs but not in the liver. Furthermore, the transcriptome of the subclones varied according to their metastatic niche. We also identified a reversible niche-driven signature that was conserved in lung and liver metastases collected during patient autopsies. Among this signature, we found that the tumor necrosis factor-α pathway was up-regulated in lung compared to liver metastases, and inhibition of this pathway affected metastasis diversity. These results highlight that the cellular and molecular heterogeneity observed in metastases is largely dictated by the tumor microenvironment.

Leveraging microenvironmental synthetic lethalities to treat cancer

Treatment resistance leads to cancer patient mortality. Therapeutic approaches that employ synthetic lethality to target mutational vulnerabilities in key tumor cell signaling pathways have proven effective in overcoming therapeutic resistance in some cancers. Yet, tumors are organs composed of malignant cells residing within a cellular and noncellular stroma. Tumor evolution and resistance to anticancer treatment are mediated through a dynamic and reciprocal dialogue with the tumor microenvironment (TME). Accordingly, expanding tumor cell synthetic lethality to encompass contextual synthetic lethality has the potential to eradicate tumors by targeting critical TME circuits that promote tumor progression and therapeutic resistance. In this Review, we summarize current knowledge about the TME and discuss its role in treatment. We outline the concept of tumor cell-specific synthetic lethality and describe therapeutic approaches to expand this paradigm to leverage TME synthetic lethality to improve cancer therapy.