Tumour Microenvironment-Immune Cell Interactions Influencing Breast Cancer Heterogeneity and Disease Progression

Canine mammary tumors as a promising adjunct preclinical model for human breast cancer research: similarities, opportunities, and challenges

Despite significant progress in the field of human breast cancer research and treatment, there is a consistent increase in the incidence rate of 0.5 percent annually, posing challenges in the development of effective novel therapeutic strategies. The failure rate of drugs in clinical trials stands at approximately 95%, primarily attributed to the limitations and lack of reliability of existing preclinical models, such as mice, which do not mimic human tumor biology. This article examines the potential utility of canine mammary tumors as an adjunct preclinical model for investigating human breast cancer. Given the numerous similarities between canine and human breast cancer, canines present a promising alternative model. The discussion delves into the intricate molecular and clinical aspects of human breast cancer and canine mammary tumors, shedding light on the tumors' molecular profiles, identifying specific molecular markers, and the application of radiological imaging modalities. Furthermore, the manuscript addresses the current constraints of preclinical cancer studies, the benefits of using canines as models, and the obstacles linked to the canine mammary tumors model. By concentrating on these elements, this review aims to highlight the viability of canine models in enhancing our understanding and management of human breast cancer.

Spatial transcriptomics in breast cancer reveals tumour microenvironment-driven drug responses and clonal therapeutic heterogeneity

Breast cancer patients are categorized into three subtypes with distinct treatment approaches. Precision oncology has increased patient outcomes by targeting the specific molecular alterations of tumours, yet challenges remain. Treatment failure persists due to the coexistence of several malignant subpopulations with different drug sensitivities within the same tumour, a phenomenon known as intratumour heterogeneity (ITH). This heterogeneity has been extensively studied from a tumour-centric view, but recent insights underscore the role of the tumour microenvironment in treatment response. Our research utilizes spatial transcriptomics data from breast cancer patients to predict drug sensitivity. We observe diverse response patterns across tumour, interphase and microenvironment regions, unveiling a sensitivity and functional gradient from the tumour core to the periphery. Moreover, we find tumour therapeutic clusters with different drug responses associated with distinct biological functions driven by unique ligand-receptor interactions. Importantly, we identify genetically identical subclones with different responses depending on their location within the tumour ducts. This research underscores the significance of considering the distance from the tumour core and microenvironment composition when identifying suitable treatments to target ITH. Our findings provide critical insights into optimizing therapeutic strategies, highlighting the necessity of a comprehensive understanding of tumour biology for effective cancer treatment.

Gynecological cancer tumor Microenvironment: Unveiling cellular complexity and therapeutic potential

Gynecological cancers, including ovarian, cervical, endometrial, and vulvar cancers, present significant challenges in diagnosis and treatment globally. The tumor microenvironment (TME) plays a pivotal role in cancer progression and therapy response, necessitating a deeper understanding of its composition and dynamics. This review offers a comprehensive overview of the gynecological cancer tumor microenvironment, emphasizing its cellular complexity and therapeutic potential. The diverse cellular components of the TME, including cancer cells, immune cells, stromal cells, and extracellular matrix elements, are explored, elucidating their interplay in shaping tumor behavior and treatment outcomes. Across various stages of cancer progression, the TME exerts profound effects on tumor heterogeneity, immune modulation, angiogenesis, and metabolic reprogramming. The urgency for novel therapeutic strategies is underscored by understanding immune evasion mechanisms within the TME. Emerging approaches such as immunotherapy, stromal-targeting therapies, anti-angiogenic agents, and metabolic inhibitors are discussed, offering promising avenues for improving patient outcomes. Interdisciplinary collaborations and translational research are emphasized, aiming to advance precision oncology and enhance therapeutic efficacy in gynecological cancers.

Collagen Mineralization Decreases NK Cell-Mediated Cytotoxicity of Breast Cancer Cells via Increased Glycocalyx Thickness

Skeletal metastasis is common in patients with advanced breast cancer and often caused by immune evasion of disseminated tumor cells (DTCs). In the skeleton, tumor cells not only disseminate to the bone marrow but also to osteogenic niches in which they interact with newly mineralizing bone extracellular matrix (ECM). However, it remains unclear how mineralization of collagen type I, the primary component of bone ECM, regulates tumor-immune cell interactions. Here, a combination of synthetic bone matrix models with controlled mineral content, nanoscale optical imaging, and flow cytometry are utilized to evaluate how collagen type I mineralization affects the biochemical and biophysical properties of the tumor cell glycocalyx, a dense layer of glycosylated proteins and lipids decorating their cell surface. These results suggest that collagen mineralization upregulates mucin-type O-glycosylation and sialylation by tumor cells, which increases their glycocalyx thickness while enhancing resistance to attack by natural killer (NK) cells. These changes are functionally linked as treatment with a sialylation inhibitor decreased mineralization-dependent glycocalyx thickness and made tumor cells more susceptible to NK cell attack. Together, these results suggest that interference with glycocalyx sialylation may represent a therapeutic strategy to enhance cancer immunotherapies targeting bone-metastatic breast cancer.

Combating anoikis resistance: bioactive compounds transforming prostate cancer therapy

The study aims to discuss the challenges associated with treating prostate cancer (PCa), which is known for its complexity and drug resistance. It attempts to find differentially expressed genes (DEGs), such as those linked to anoikis resistance and circulating tumor cells, in PCa samples. This study involves analyzing the functional roles of these DEGs using gene enrichment analysis, and then screening of 102 bioactive compounds to identify a combination that can control the expression of the identified DEGs. In this study, 53 DEGs were identified from PCa samples including anoikis-resistant PCa cells and circulating tumor cells in PCa. Gene enrichment analysis with regards to functional enrichment of DEGs was performed. An inclusive screening process was carried out among 102 bioactive compounds to identify a combination capable of affecting and regulating the expression of selected DEGs. Eventually, gastrodin, nitidine chloride, chenodeoxycholic acid, and bilobalide were selected, as their combination demonstrated ability to modulate expression of 50 out of the 53 genes targeted. The subsequent analysis focused on investigating the biological pathways and processes influenced by this combination. The findings revealed a multifaceted and multidimensional approach to tumor regression. The combination of bioactive compounds exhibited effects on various genes including those related to production of inflammatory cytokines, cell proliferation, autophagy, apoptosis, angiogenesis, and metastasis. The current study has made a valuable contribution to the development of a combination of bioactive natural compounds that can significantly impede the development of treatment resistance in prostate tumor while countering the tumors' evasion of the immune system. The implications of this study are highly significant as it suggests the creation of an enhanced immunotherapeutic, natural therapeutic concoction with combinatorial potential.

Human-derived Tumor-On-Chip model to study the heterogeneity of breast cancer tissue

One of the leading causes that complicate the treatment of some malignancies, including breast cancer, is tumor heterogeneity. In addition to inter-heterogeneity and intra-heterogeneity of tumors that reflect the differences between cancer cell characteristics, heterogeneity in the tumor microenvironment plays a critical role in tumor progression and could be considered an overlooked and a proper target for the effective selection of therapeutic approaches. Due to the difficulty of completely capturing tumor heterogeneity in conventional detection methods, Tumor-on-Chip (TOC) devices with culturing patient-derived spheroids could be an appropriate alternative. In this research, human-derived spheroids from breast cancer individuals were cultured for 6 days in microfluidic devices. To compare TOC data with conventional detection methods, immunohistochemistry (IHC) and ITRAQ data were employed, and various protein expressions were validated using the transcriptomic databases. The behavior of the spheroids in the collagen matrix and the cell viability were monitored over 6 days of culture. IHC and immunocytochemistry (ICC) results revealed that inter and intra-heterogeneity of tumor spheroids are associated with HER2/ER expression. HER2 expression levels revealed a more important biomarker associated with invasion in the 3D culturing of spheroids. The expression levels of CD163 (as a marker for Ma2 macrophages) and CD44 (a marker for cancer stem cells (CSCs)) were also evaluated. Interestingly, the levels of M2a macrophages and CSCs were higher in triple-negative specimens and samples that showed higher migration and invasion. Cell density and extracellular matrix (ECM) stiffness were also important factors affecting the migration and invasion of the spheroids through the matrix. Among these, rigid ECM revealed a more crucial role than cell density. To sum up, these research findings demonstrated that human-derived spheroids from breast cancer specimens in microfluidic devices provide a dynamic condition for predicting tumor heterogeneity in patients, which can help move the field forward for better and more accurate therapeutic strategies.

Tumor microenvironment: A playground for cells from multiple diverse origins

Tumor microenvironment is formed by various cellular and non-cellular components which interact with one another and form a complex network of interactions. Some of these cellular components also attain a secretory phenotype and release growth factors, cytokines, chemokines etc. in the surroundings which are capable of inducing even greater number of signalling networks. All these interactions play a decisive role in determining the course of tumorigenesis. The treatment strategies against cancer also exert their impact on the local microenvironment. Such interactions and anticancer therapies have been found to induce more deleterious outcomes like immunosuppression and chemoresistance in the process of tumor progression. Hence, understanding the tumor microenvironment is crucial for dealing with cancer and chemoresistance. This review is an attempt to develop some understanding about the tumor microenvironment and different factors which modulate it, thereby contributing to tumorigenesis. Along with summarising the major components of tumor microenvironment and various interactions taking place between them, it also throws some light on how the existing and potential therapies exert their impact on these dynamics.

Applications of spatial transcriptomics and artificial intelligence to develop integrated management of pancreatic cancer

Cancer is a complex disease intrinsically associated with cellular processes and gene expression. With the development of techniques such as single-cell sequencing and sequential fluorescence in situ hybridization (seqFISH), it was possible to map the location of cells based on their gene expression with more precision. Moreover, in recent years, many tools have been developed to analyze these extensive datasets by integrating machine learning and artificial intelligence in a comprehensive manner. Since these tools analyze sequencing data, they offer the chance to analyze any tissue regardless of its origin. By applying this to cancer settings, spatial transcriptomic analysis based on artificial intelligence may help us understand cell-cell communications within the tumor microenvironment. Another advantage of this analysis is the identification of new biomarkers and therapeutic targets. The integration of such analysis with other omics data and with routine exams such as magnetic resonance imaging can help physicians with the earlier diagnosis of tumors as well as establish a more personalized treatment for pancreatic cancer patients. In this review, we give an overview description of pancreatic cancer, describe how spatial transcriptomics and artificial intelligence have been used to study pancreatic cancer and provide examples of how integrating these tools may help physicians manage pancreatic cancer in a more personalized approach.

Role of cancer stem cell ecosystem on breast cancer metastasis and related mouse models

Breast cancer metastasis is responsible for most breast cancer-related deaths and is influenced by many factors within the tumor ecosystem, including tumor cells and microenvironment. Breast cancer stem cells (BCSCs) constitute a small population of cancer cells with unique characteristics, including their capacity for self-renewal and differentiation. Studies have shown that BCSCs not only drive tumorigenesis but also play a crucial role in promoting metastasis in breast cancer. The tumor microenvironment (TME), composed of stromal cells, immune cells, blood vessel cells, fibroblasts, and microbes in proximity to cancer cells, is increasingly recognized for its crosstalk with BCSCs and role in BCSC survival, growth, and dissemination, thereby influencing metastatic ability. Hence, a thorough understanding of BCSCs and the TME is critical for unraveling the mechanisms underlying breast cancer metastasis. In this review, we summarize current knowledge on the roles of BCSCs and the TME in breast cancer metastasis, as well as the underlying regulatory mechanisms. Furthermore, we provide an overview of relevant mouse models used to study breast cancer metastasis, as well as treatment strategies and clinical trials addressing BCSC-TME interactions during metastasis. Overall, this study provides valuable insights for the development of effective therapeutic strategies to reduce breast cancer metastasis.

Mapping the function of MicroRNAs as a critical regulator of tumor-immune cell communication in breast cancer and potential treatment strategies

Among women, breast cancer ranks as the most prevalent form of cancer, and the presence of metastases significantly reduces prognosis and diminishes overall survival rates. Gaining insights into the biological mechanisms governing the conversion of cancer cells, their subsequent spread to other areas of the body, and the immune system's monitoring of tumor growth will contribute to the advancement of more efficient and targeted therapies. MicroRNAs (miRNAs) play a critical role in the interaction between tumor cells and immune cells, facilitating tumor cells' evasion of the immune system and promoting cancer progression. Additionally, miRNAs also influence metastasis formation, including the establishment of metastatic sites and the transformation of tumor cells into migratory phenotypes. Specifically, dysregulated expression of these genes has been associated with abnormal expression of oncogenes and tumor suppressor genes, thereby facilitating tumor development. This study aims to provide a concise overview of the significance and function of miRNAs in breast cancer, focusing on their involvement as tumor suppressors in the antitumor immune response and as oncogenes in metastasis formation. Furthermore, miRNAs hold tremendous potential as targets for gene therapy due to their ability to modulate specific pathways that can either promote or suppress carcinogenesis. This perspective highlights the latest strategies developed for miRNA-based therapies.

Microphysiological systems as models for immunologically 'cold' tumors

The tumor microenvironment (TME) is a diverse milieu of cells including cancerous and non-cancerous cells such as fibroblasts, pericytes, endothelial cells and immune cells. The intricate cellular interactions within the TME hold a central role in shaping the dynamics of cancer progression, influencing pivotal aspects such as tumor initiation, growth, invasion, response to therapeutic interventions, and the emergence of drug resistance. In immunologically 'cold' tumors, the TME is marked by a scarcity of infiltrating immune cells, limited antigen presentation in the absence of potent immune-stimulating signals, and an abundance of immunosuppressive factors. While strategies targeting the TME as a therapeutic avenue in 'cold' tumors have emerged, there is a pressing need for novel approaches that faithfully replicate the complex cellular and non-cellular interactions in order to develop targeted therapies that can effectively stimulate immune responses and improve therapeutic outcomes in patients. Microfluidic devices offer distinct advantages over traditional in vitro 3D co-culture models and in vivo animal models, as they better recapitulate key characteristics of the TME and allow for precise, controlled insights into the dynamic interplay between various immune, stromal and cancerous cell types at any timepoint. This review aims to underscore the pivotal role of microfluidic systems in advancing our understanding of the TME and presents current microfluidic model systems that aim to dissect tumor-stromal, tumor-immune and immune-stromal cellular interactions in various 'cold' tumors. Understanding the intricacies of the TME in 'cold' tumors is crucial for devising effective targeted therapies to reinvigorate immune responses and overcome the challenges of current immunotherapy approaches.

Neighboring macrophage-induced alteration in the phenotype of colorectal cancer cells in the tumor budding area

BACKGROUND

A higher number of tumor buds in the invasive front of colorectal cancer (CRC) specimens has been shown to contribute to a poor prognosis in CRC patients. Because macrophages (Mφs) have been demonstrated to alter the phenotype of cancer cells, we hypothesized that the phenotype of CRC cells in the tumor budding (TB) area might be changed by the interaction between CRC cells and Mφs.

METHODS

We assessed the expression of topoisomerase 1 in CRC cells to estimate the acquisition of chemoresistance in CRC. To demonstrate the tumor-stromal interaction between CRC cells and Mφs, we assessed two histological findings, the number of Mφs per single CRC cell and the proximity between CRC cells and Mφs by histological spatial analysis using HALO software.

RESULTS

The expression levels of topoisomerase 1 in CRC cells were decreased in deeper areas, especially in the TB area, compared to the surface area. Our histological spatial analysis revealed that 2.6 Mφs located within 60 μm of a single CRC cell were required to alter the phenotype of the CRC cell. Double-immunofluorescence staining revealed that higher Mφs were positive for interleukin-6 (IL-6) in the TB area and that AE1/AE3-positive CRC cells were also positive for phospho-STAT3 (pSTAT3) in the TB area; thus, the IL-6 receptor (IL-6R)/STAT3 signaling pathway in CRC cells was upregulated by IL-6 derived from neighboring Mφs.

CONCLUSION

IL-6 secreted from the neighboring Mφs would alter the phenotype of CRC cells via IL-6R/STAT3 signaling pathway.

Characterizing the Inflammatory Profile of Neutrophil-Rich Triple-Negative Breast Cancer

Breast cancer (BC) is one of the most common types of cancer in women in the United Arab Emirates. Immunogenic tumours, such as triple-negative breast cancer (TNBC), show increased neutrophil infiltration, which is associated with poor prognosis and limited efficacy of immunotherapy. This study aims to investigate in vitro the bidirectional effect of neutrophils on metastatic TNBC (MDA-MB-231) compared to less-metastatic luminal breast cancer (MCF-7) cell lines. We found that BC cells or their conditioned medium (CM) reduced the viability of neutrophil-like cells (HL60). This was supported by increased cellular stress and NETosis in differentiated HL60 cells (dHL60) upon exposure to MDA-MB-231 compared to MCF-7-CM using nucleic acid staining essays. Flow cytometry showed comparable expression of inflammatory markers by polymorphonuclear cells (PMN) when treated with MDA-MB-231-CM and standard polarizing cocktails. Furthermore, MDA-MB-231-CM triggered an inflammatory pattern with evidence of stronger adhesion (CD62L) and degranulation (CD11b and CD66b) phenotypes. The proinflammatory polarization of dHL60 by MDA-MB-231-CM was additionally confirmed by the elevated CD54 expression, myeloperoxidase, and CD11b protein levels, which matched an increased transwell migratory capacity. In conclusion, BC might use neutrophils to their benefit through NETosis and complement system activation, which makes this crosstalk a potential mechanism for understanding tumour progression.

COLLAGEN MINERALIZATION DECREASES NK CELL-MEDIATED CYTOTOXICITY OF BREAST CANCER CELLS VIA INCREASED GLYCOCALYX THICKNESS

Skeletal metastasis is common in patients with advanced breast cancer, and often caused by immune evasion of disseminated tumor cells (DTCs). In the skeleton, tumor cells not only disseminate to the bone marrow, but also to osteogenic niches in which they interact with newly mineralizing bone extracellular matrix (ECM). However, it remains unclear how mineralization of collagen type I, the primary component of bone ECM, regulates tumor-immune cell interactions. Here, we have utilized a combination of synthetic bone matrix models with controlled mineral content, nanoscale optical imaging, and flow cytometry to evaluate how collagen type I mineralization affects the biochemical and biophysical properties of the tumor cell glycocalyx, a dense layer of glycosylated proteins and lipids decorating their cell surface. Our results suggest that collagen mineralization upregulates mucin-type O-glycosylation and sialylation by tumor cells, which increased their glycocalyx thickness while enhancing resistance to attack by Natural Killer (NK) cells. These changes were functionally linked as treatment with a sialylation inhibitor decreased mineralization-dependent glycocalyx thickness and made tumor cells more susceptible to NK cell attack. Together, our results suggest that interference with glycocalyx sialylation may represent a therapeutic strategy to enhance cancer immunotherapies targeting bone-metastatic breast cancer.

Prognostic value and tumour microenvironment characteristics of the Glasgow Microenvironment Score in primary triple-negative breast cancer

AIMS

The Glasgow Microenvironment Score (GMS) reflects the tumour microenvironment (TME) status by combining inflammatory cell infiltration and the tumour-stroma percentage. This study aimed to investigate the prognostic value and TME characteristics of the GMS for patients with triple-negative breast cancer (TNBC).

METHODS

A total of 123 patients with stage I-III TNBC were enrolled in this study. The association between GMS and clinicopathological characteristics was examined using the Pearson's χ2 test or Fisher's exact test. Kaplan-Meier plots were used to compare survival among the three GMS groups. Cox regression analyses were conducted to test the HR. Microenvironment Cell Populations-counter algorithm was used to estimate the TME components of each case.

RESULTS

We found that higher GMS score tended to exhibit the lower nuclear grade (p=0.016), more positive lymph nodes (p=0.014) and later tumour, node, metastases stage (p=0.012). GMS was an independent prognostic factor for disease-free survival in TNBC, and GMS 2 showed the worst prognosis (HR=6.42, p=0.028). GMS 0 was more infiltrated with cytotoxic lymphocytes, including CD8+ T cells (p=0.037) and natural killer cells (p=0.005), while GMS 2 was enriched in more endothelial cells (p=0.014) and fibroblasts (p=0.008).

CONCLUSION

Our study suggested that the GMS is a prognostic indicator for patients with TNBC. As an accessible and effective index, the GMS may be a promising tool to help clinicians assess prognostic risk and TME for patients with TNBC.

Breast tumor-on-chip: from the tumor microenvironment to medical applications

With the development of microfluidic technology, tumor-on-chip models have gradually become a new tool for the study of breast cancer because they can simulate more key factors of the tumor microenvironment compared with traditional models in vitro. Here, we review up-to-date advancements in breast tumor-on-chip models. We summarize and analyze the breast tumor microenvironment (TME), preclinical breast cancer models for TME simulation, fabrication methods of tumor-on-chip models, tumor-on-chip models for TME reconstruction, and applications of breast tumor-on-chip models and provide a perspective on breast tumor-on-chip models. This review will contribute to the construction and design of microenvironments for breast tumor-on-chip models, even the development of the pharmaceutical field, personalized/precision therapy, and clinical medicine.

Investigating Ecological Interactions in the Tumor Microenvironment using Joint Species Distribution Models for Point Patterns

The tumor microenvironment (TME) is a complex and dynamic ecosystem that involves interactions between different cell types, such as cancer cells, immune cells, and stromal cells. These interactions can promote or inhibit tumor growth and affect response to therapy. Multitype Gibbs point process (MGPP) models are statistical models used to study the spatial distribution and interaction of different types of objects, such as the distribution of cell types in a tissue sample. Such models are potentially useful for investigating the spatial relationships between different cell types in the tumor microenvironment, but so far studies of the TME using cell-resolution imaging have been largely limited to spatial descriptive statistics. However, MGPP models have many advantages over descriptive statistics, such as uncertainty quantification, incorporation of multiple covariates and the ability to make predictions. In this paper, we describe and apply a previously developed MGPP method, the saturated pairwise interaction Gibbs point process model , to a publicly available multiplexed imaging dataset obtained from colorectal cancer patients. Importantly, we show how these methods can be used as joint species distribution models (JSDMs) to precisely frame and answer many relevant questions related to the ecology of the tumor microenvironment.

Delineating intra-tumoral heterogeneity and tumor evolution in breast cancer using precision-based approaches

The burden of breast cancer continues to increase worldwide as it remains the most diagnosed tumor in females and the second leading cause of cancer-related deaths. Breast cancer is a heterogeneous disease characterized by different subtypes which are driven by aberrations in key genes such as BRCA1 and BRCA2, and hormone receptors. However, even within each subtype, heterogeneity that is driven by underlying evolutionary mechanisms is suggested to underlie poor response to therapy, variance in disease progression, recurrence, and relapse. Intratumoral heterogeneity highlights that the evolvability of tumor cells depends on interactions with cells of the tumor microenvironment. The complexity of the tumor microenvironment is being unraveled by recent advances in screening technologies such as high throughput sequencing; however, there remain challenges that impede the practical use of these approaches, considering the underlying biology of the tumor microenvironment and the impact of selective pressures on the evolvability of tumor cells. In this review, we will highlight the advances made thus far in defining the molecular heterogeneity in breast cancer and the implications thereof in diagnosis, the design and application of targeted therapies for improved clinical outcomes. We describe the different precision-based approaches to diagnosis and treatment and their prospects. We further propose that effective cancer diagnosis and treatment are dependent on unpacking the tumor microenvironment and its role in driving intratumoral heterogeneity. Underwriting such heterogeneity are Darwinian concepts of natural selection that we suggest need to be taken into account to ensure evolutionarily informed therapeutic decisions.

Single-cell pair-wise relationships untangled by composite embedding model

In multicellular organisms, cell identity and functions are primed and refined through interactions with other surrounding cells. Here, we propose a scalable machine learning method, termed SPRUCE, which is designed to systematically ascertain common cell-cell communication patterns embedded in single-cell RNA-seq data. We applied our approach to investigate tumor microenvironments consolidating multiple breast cancer datasets and found seven frequently observed interaction signatures and underlying gene-gene interaction networks. Our results implicate that a part of tumor heterogeneity, especially within the same subtype, is better understood by differential interaction patterns rather than the static expression of known marker genes.

The complex nature of heterogeneity and its roles in breast cancer biology and therapeutic responsiveness

Heterogeneity is a complex feature of cells and tissues with many interacting components. Depending on the nature of the research context, interacting features of cellular, drug response, genetic, molecular, spatial, temporal, and vascular heterogeneity may be present. We describe the various forms of heterogeneity with examples of their interactions and how they play a role in affecting cellular phenotype and drug responses in breast cancer. While cellular heterogeneity may be the most widely described and invoked, many forms of heterogeneity are evident within the tumor microenvironment and affect responses to the endocrine and cytotoxic drugs widely used in standard clinical care. Drug response heterogeneity is a critical determinant of clinical response and curative potential and also is multifaceted when encountered. The interactive nature of some forms of heterogeneity is readily apparent. For example, the process of metastasis has the properties of both temporal and spatial heterogeneity within the host, whereas each individual metastatic deposit may exhibit cellular, genetic, molecular, and vascular heterogeneity. This review describes the many forms of heterogeneity, their integrated activities, and offers some insights into how heterogeneity may be understood and studied in the future.