Evidence for the clonal origin of spontaneous metastases

Biosensors for metastatic cancer cell detection

Early detection and effective cancer treatment are critical to improving metastatic cancer cell diagnosis and management today. In particular, accurate qualitative diagnosis of metastatic cancer cell represents an important step in the diagnosis of cancer. Today, biosensors have been widely developed due to the daily need to measure different chemical and biological species. Biosensors are utilized to quantify chemical and biological phenomena by generating signals that are directly proportional to the quantity of the analyte present in the reaction. Biosensors are widely used in disease control, drug delivery, infection detection, detection of pathogenic microorganisms, and markers that indicate a specific disease in the body. These devices have been especially popular in the field of metastatic cancer cell diagnosis and treatment due to their portability, high sensitivity, high specificity, ease of use and short response time. This article examines biosensors for metastatic cancer cells. It also studies metastatic cancer cells and the mechanism of metastasis. Finally, the function of biosensors and biomarkers in metastatic cancer cells is investigated.

Insights into the metastatic cascade through research autopsies

Metastasis is a complex process and the leading cause of cancer-related death globally. Recent studies have demonstrated that genomic sequencing data from paired primary and metastatic tumours can be used to trace the evolutionary origins of cells responsible for metastasis. This approach has yielded new insights into the genomic alterations that engender metastatic potential, and the mechanisms by which cancer spreads. Given that the reliability of these approaches is contingent upon how representative the samples are of primary and metastatic tumour heterogeneity, we review insights from studies that have reconstructed the evolution of metastasis within the context of their cohorts and designs. We discuss the role of research autopsies in achieving the comprehensive sampling necessary to advance the current understanding of metastasis.

Sensitization of Resistant Cells with a BET Bromodomain Inhibitor in a Cell Culture Model of Deep Intrinsic Resistance in Breast Cancer

We treated highly metabolically adaptable (SUM149-MA) triple-negative inflammatory breast cancer cells and their control parental SUM149-Luc cell line with JQ1 for long periods to determine its efficacy at inhibiting therapy-resistant cells. After 20 days of treatment with 1-2 µM of JQ1, which killed majority of cells in the parental cell line, a large number of SUM149-MA cells survived, consistent with their pan-resistant nature. Interestingly, though, the JQ1 treatment sensitized resistant cancer cells in both the SUM149-MA and SUM149-Luc cell lines to subsequent treatment with doxorubicin and paclitaxel. To measure JQ1-mediated sensitization of resistant cancer cells, we first eradicated approximately 99% of relatively chemotherapy-sensitive cancer cells in culture dishes by long treatments with doxorubicin or paclitaxel, and then analyzed the remaining resistant cells for survival and growth into colonies. In addition, combination, rather than sequential, treatment with JQ1 and doxorubicin was also effective in overcoming resistance. Notably, Western blotting showed that JQ1-treated cancer cells had significantly lower levels of PD-L1 protein than did untreated cells, indicating that JQ1 treatment may reduce tumor-mediated immune suppression and improve the response to immunotherapy targeting PD-L1. Finally, JQ1 treatment with a low 62.5 nM dose sensitized another resistant cell line, FC-IBC02-MA, to treatment with doxorubicin and paclitaxel.

Patterns of metastases progression- The linear parallel ratio

BACKGROUND

Linear and parallel are the two leading models of metastatic progression. In this study we propose a simple way to differentiate between them. While the linear model predicts accumulation of genetic and epigenetic alterations within the primary tumor by founder cells before spreading as waves of metastases, the parallel model suggests preclinical distribution of less advanced disseminated tumor cells with independent selection and expansion at the ectopic sites. Due to identical clonal origin and time of dispatching, linear metastases are expected to have comparable diameters in any specific organ while parallel metastases are expected to appear in variable sizes.

METHODS AND FINDINGS

Retrospective revision of chest CT of oncological patients with lung metastases was performed. Metastasis number and largest diameters were recorded. The sum number of metastases with a similar diameter (c) and those without (i) was counted and the linear/parallel ratio (LPR) was calculated for each patient using the formula (∑c-∑i)/(∑c+∑i). A LPR ratio of 1 implies pure linear progression pattern and -1 pure parallel. 12,887 metastases were measured in 503 patients with nine malignancy types. The median LPR of the entire group was 0.71 (IQR 0.14-0.93). In carcinomas of the pancreas, prostate, and thyroid the median LPR was 1. Median LPRs were 0.91, 0.65, 0.60, 0.58, 0.50 and 0.43 in renal cell carcinomas, melanomas, colorectal, breast, bladder, and sarcomas, respectively.

CONCLUSIONS

Metastatic spread of thyroid, pancreas, and prostate tumors is almost exclusively by a linear route. The spread of kidney, melanoma, colorectal, breast, bladder and sarcoma is both linear and parallel with increasing dominance of the parallel route in this order. These findings can explain and predict the clinical and genomic features of these tumors and can potentially be used for evaluation of metastatic origin in the individual patient.

DNA barcoded competitive clone-initiating cell analysis reveals novel features of metastatic growth in a cancer xenograft model

A problematic feature of many human cancers is a lack of understanding of mechanisms controlling organ-specific patterns of metastasis, despite recent progress in identifying many mutations and transcriptional programs shown to confer this potential. To address this gap, we developed a methodology that enables different aspects of the metastatic process to be comprehensively characterized at a clonal resolution. Our approach exploits the application of a computational pipeline to analyze and visualize clonal data obtained from transplant experiments in which a cellular DNA barcoding strategy is used to distinguish the separate clonal contributions of two or more competing cell populations. To illustrate the power of this methodology, we demonstrate its ability to discriminate the metastatic behavior in immunodeficient mice of a well-established human metastatic cancer cell line and its co-transplanted LRRC15 knockdown derivative. We also show how the use of machine learning to quantify clone-initiating cell (CIC) numbers and their subsequent metastatic progeny generated in different sites can reveal previously unknown relationships between different cellular genotypes and their initial sites of implantation with their subsequent respective dissemination patterns. These findings underscore the potential of such combined genomic and computational methodologies to identify new clonally-relevant drivers of site-specific patterns of metastasis.

Sensitization of Resistant Breast Cancer Cells with a Jumonji Family Histone Demethylase Inhibitor

Simple Summary

Using a cell culture model of resistant breast cancer cells with the phenotype that is often responsible for the early relapse of triple-negative breast cancer, namely, the persistence of these cells in reversible quiescence under a variety of challenges, we found that reprogramming the epigenome by treatment with JIB-04, a small-molecule inhibitor of Jumonji-family histone demethylases, sensitized resistant cells. We used this model of deep intrinsic resistance featuring many molecular mechanisms of achieving this phenotype to perform lengthy evaluations of less cytotoxic doses of JIB-04. We found that resistant cells derived from triple-negative inflammatory breast cancer cell lines were either much more sensitive to JIB-04 than the parental cell line or altered by the treatment such that they became sensitive to the chemotherapeutic drugs paclitaxel and doxorubicin. Notably, JIB-04 exposure increased PD-L1 expression in cancer cells, which means that JIB-04 may have clinical applications in improving the responses of triple-negative breast cancer to anti-PD-L1 therapy.

Abstract

In the present study, we evaluated JIB-04, a small-molecule epigenetic inhibitor initially discovered to inhibit cancer growth, to determine its ability to affect deep intrinsic resistance in a breast cancer model. The model was based on a function-based approach to the selection of cancer cells in a cell culture that can survive a variety of challenges in prolonged, but reversible, quiescence. These resistant cancer cells possessed a variety of mechanisms, including modifications of the epigenome and transcriptome, for generating a high degree of cellular heterogeneity. We found that long pretreatment with JIB-04 sensitized resistant triple-negative inflammatory breast cancer cells and their parental cell line SUM149 to the chemotherapeutic drugs doxorubicin and paclitaxel. Resistant cancer cells derived from another inflammatory breast cancer cell line, FC-IBC02, were considerably more sensitive to JIB-04 than the parental cell line. Investigating a mechanism of sensitization, we found that JIB-04 exposure increased the expression of PD-L1 in resistant cells, suggesting that JIB-04 may also sensitize resistant breast cancer cells to anti-PD-L1 immune therapy. Finally, these results support the usefulness of a cell culture-based experimental strategy for evaluating anticancer agents, such as JIB-04, that may halt cancer evolution and prevent the development of cancer resistance to currently used therapies.

Quantitative analysis of metastatic breast cancer in mice using deep learning on cryo-image data

Cryo-imaging sections and images a whole mouse and provides ~ 120-GBytes of microscopic 3D color anatomy and fluorescence images, making fully manual analysis of metastases an onerous task. A convolutional neural network (CNN)-based metastases segmentation algorithm included three steps: candidate segmentation, candidate classification, and semi-automatic correction of the classification result. The candidate segmentation generated > 5000 candidates in each of the breast cancer-bearing mice. Random forest classifier with multi-scale CNN features and hand-crafted intensity and morphology features achieved 0.8645 ± 0.0858, 0.9738 ± 0.0074, and 0.9709 ± 0.0182 sensitivity, specificity, and area under the curve (AUC) of the receiver operating characteristic (ROC), with fourfold cross validation. Classification results guided manual correction by an expert with our in-house MATLAB software. Finally, 225, 148, 165, and 344 metastases were identified in the four cancer mice. With CNN-based segmentation, the human intervention time was reduced from > 12 to ~ 2 h. We demonstrated that 4T1 breast cancer metastases spread to the lung, liver, bone, and brain. Assessing the size and distribution of metastases proves the usefulness and robustness of cryo-imaging and our software for evaluating new cancer imaging and therapeutics technologies. Application of the method with only minor modification to a pancreatic metastatic cancer model demonstrated generalizability to other tumor models.

Chemokines orchestrate tumor cells and the microenvironment to achieve metastatic heterogeneity

Chemokines, a subfamily of the cell cytokines, are low molecular weight proteins known to induce chemotaxis in leukocytes in response to inflammatory and pathogenic signals. A plethora of literature demonstrates that chemokines and their receptors regulate tumor progression and metastasis. With these diverse functionalities, chemokines act as a fundamental link between the tumor cells and their microenvironment. Recent studies demonstrate that the biology of chemokines and their receptor in metastasis is complex as numerous chemokines are involved in regulating site-specific tumor growth and metastasis. Successful treatment of disseminated cancer is a significant challenge. The most crucial problem for treating metastatic cancer is developing therapy regimes capable of overcoming heterogeneity problems within primary tumors and among metastases and within metastases (intralesional). This heterogeneity of malignant tumor cells can be related to metastatic potential, response to chemotherapy or specific immunotherapy, and many other factors. In this review, we have emphasized the role of chemokines in the process of metastasis and metastatic heterogeneity. Individual chemokines may not express the full potential to address metastatic heterogeneity, but chemokine networks need exploration. Understanding the interplay between chemokine-chemokine receptor networks between the tumor cells and their microenvironment is a novel approach to overcome the problem of metastatic heterogeneity. Recent advances in the understanding of chemokine networks pave the way for developing a potential targeted therapeutic strategy to treat metastatic cancer.

3D hydrogels reveal medulloblastoma subgroup differences and identify extracellular matrix subtypes that predict patient outcome

Medulloblastoma (MB) is the most common malignant brain tumour in children and is subdivided into four subgroups: WNT, SHH, Group 3, and Group 4. These molecular subgroups differ in their metastasis patterns and related prognosis rates. Conventional 2D cell culture methods fail to recapitulate these clinical differences. Realistic 3D models of the cerebellum are therefore necessary to investigate subgroup‐specific functional differences and their role in metastasis and chemoresistance. A major component of the brain extracellular matrix (ECM) is the glycosaminoglycan hyaluronan. MB cell lines encapsulated in hyaluronan hydrogels grew as tumour nodules, with Group 3 and Group 4 cell lines displaying clinically characteristic laminar metastatic patterns and levels of chemoresistance. The glycoproteins, laminin and vitronectin, were identified as subgroup‐specific, tumour‐secreted ECM factors. Gels of higher complexity, formed by incorporation of laminin or vitronectin, revealed subgroup‐specific adhesion and growth patterns closely mimicking clinical phenotypes. ECM subtypes, defined by relative levels of laminin and vitronectin expression in patient tissue microarrays and gene expression data sets, were able to identify novel high‐risk MB patient subgroups and predict overall survival. Our hyaluronan model system has therefore allowed us to functionally characterize the interaction between different MB subtypes and their environment. It highlights the prognostic and pathological role of specific ECM factors and enables preclinical development of subgroup‐specific therapies. © 2020 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

Can stress promote the pathophysiology of brain metastases? A critical review of biobehavioral mechanisms

Chronic stress can promote tumor growth and progression through immunosuppressive effects and bi-directional interactions between tumor cells and their microenvironment. β-Adrenergic receptor signaling plays a critical role in mediating stress-related effects on tumor progression. Stress-related mechanisms that modulate the dissemination of tumor cells to the brain have received scant attention. Brain metastases are highly resistant to chemotherapy and contribute considerably to morbidity and mortality in various cancers, occurring in up to 20% of patients in some cancer types. Understanding the mechanisms promoting brain metastasis could help to identify interventions that improve disease outcomes. In this review, we discuss biobehavioral, sympathetic, neuroendocrine, and immunological mechanisms by which chronic stress can impact tumor progression and metastatic dissemination to the brain. The critical role of the inflammatory tumor microenvironment in tumor progression and metastatic dissemination to the brain, and its association with stress pathways are delineated. We also discuss translational implications for biobehavioral and pharmacological interventions.

Circulating tumour cells: a broad perspective

Circulating tumour cells (CTCs) have recently been identified as valuable biomarkers for diagnostic and prognostic evaluations, as well for monitoring therapeutic responses to treatments. CTCs are rare cells which may be present as one CTC surrounded by approximately 1 million white blood cells and 1 billion red blood cells per millilitre of peripheral blood. Despite the various challenges in CTC detection, considerable progress in detection methods have been documented in recent times, particularly for methodologies incorporating nanomaterial-based platforms and/or integrated microfluidics. Herein, we summarize the importance of CTCs as biological markers for tumour detection, highlight their mechanism of cellular invasion and discuss the various challenges associated with CTC research, including vulnerability, heterogeneity, phenotypicity and size differences. In addition, we describe nanomaterial agents used for electrochemistry and surface plasmon resonance applications, which have recently been used to selectively capture cancer cells and amplify signals for CTC detection. The intrinsic properties of nanomaterials have also recently been exploited to achieve photothermal destruction of cancer cells. This review describes recent advancements and future perspectives in the CTC field.

Multi-cancer analysis of clonality and the timing of systemic spread in paired primary tumors and metastases

Metastasis is the primary cause of cancer-related deaths, but the natural history, clonal evolution and impact of treatment are poorly understood. We analyzed whole-exome sequencing data from 457 paired primary tumor and metastatic samples from 136 breast, colorectal and lung cancer patients, including untreated (n=99) and treated (n=100) metastases. Treated metastases often harbored private ‘driver’ mutations whereas untreated metastases did not, suggesting that treatment promotes clonal evolution. Polyclonal seeding was common in untreated lymph node metastases (n=17/29, 59%) and distant metastases (n=20/70, 29%), but less frequent in treated distant metastases (n=9/94, 10%). The low number of metastasis-private clonal mutations is consistent with early metastatic seeding, which we estimated occurred 2–4 years prior to diagnosis across these cancers. Further, these data suggest that the natural course of metastasis is selectively relaxed relative to early tumorigenesis and that metastasis-private mutations are not drivers of cancer spread but instead associated with drug resistance.

Quantification of multicellular colonization in tumor metastasis using exome-sequencing data

Metastasis is a major cause of cancer-related mortality, and it is essential to understand how metastasis occurs in order to overcome it. One relevant question is the origin of a metastatic tumor cell population. Although the hypothesis of a single-cell origin for metastasis from a primary tumor has long been prevalent, several recent studies using mouse models have supported a multicellular origin of metastasis. Human bulk whole-exome sequencing (WES) studies also have demonstrated a multiple "clonal" origin of metastasis, with different mutational compositions. Specifically, there has not yet been strong research to determine how many founder cells colonize a metastatic tumor. To address this question, under the metastatic model of "single bottleneck followed by rapid growth," we developed a method to quantify the "founder cell population size" in a metastasis using paired WES data from primary and metachronous metastatic tumors. Simulation studies demonstrated the proposed method gives unbiased results with sufficient accuracy in the range of realistic settings. Applying the proposed method to real WES data from four colorectal cancer patients, all samples supported a multicellular origin of metastasis and the founder size was quantified, ranging from 3 to 17 cells. Such a wide-range of founder sizes estimated by the proposed method suggests that there are large variations in genetic similarity between primary and metastatic tumors in the same subjects, which may explain the observed (dis)similarity of drug responses between tumors.

Thyroid hormone induces progression and invasiveness of squamous cell carcinomas by promoting a ZEB-1/E-cadherin switch

Epithelial tumor progression often involves epithelial-mesenchymal transition (EMT). We report that increased intracellular levels of thyroid hormone (TH) promote the EMT and malignant evolution of squamous cell carcinoma (SCC) cells. TH induces the EMT by transcriptionally up-regulating ZEB-1, mesenchymal genes and metalloproteases and suppresses E-cadherin expression. Accordingly, in human SCC, elevated D2 (the T3-producing enzyme) correlates with tumor grade and is associated with an increased risk of postsurgical relapse and shorter disease-free survival. These data provide the first in vivo demonstration that TH and its activating enzyme, D2, play an effective role not only in the EMT but also in the entire neoplastic cascade starting from tumor formation up to metastatic transformation, and supports the concept that TH is an EMT promoter. Our studies indicate that tumor progression relies on precise T3 availability, suggesting that pharmacological inactivation of D2 and TH signaling may suppress the metastatic proclivity of SCC.

Consecutive seeding and transfer of genetic diversity in metastasis

During metastasis, only a fraction of genetic diversity in a primary tumor is passed on to metastases. We calculate this fraction of transferred diversity as a function of the seeding rate between tumors. At one extreme, if a metastasis is seeded by a single cell, then it inherits only the somatic mutations present in the founding cell, so that none of the diversity in the primary tumor is transmitted to the metastasis. In contrast, if a metastasis is seeded by multiple cells, then some genetic diversity in the primary tumor can be transmitted. We study a multitype branching process of metastasis growth that originates from a single cell but over time receives additional cells. We derive a surprisingly simple formula that relates the expected diversity of a metastasis to the diversity in the pool of seeding cells. We calculate the probability that a metastasis is polyclonal. We apply our framework to published datasets for which polyclonality has been previously reported, analyzing 68 ovarian cancer samples, 31 breast cancer samples, and 8 colorectal cancer samples from 15 patients. For these clonally diverse metastases, under typical metastasis growth conditions, we find that 10 to 150 cells seeded each metastasis and left surviving lineages between initial formation and clinical detection.

Defining the Hallmarks of Metastasis

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

Numerical optimal control of a size-structured PDE model for metastatic cancer treatment

In this paper, we propose a unified size-structured PDE model for the growth of metastatic tumors, which extends a well-known coupled ODE-PDE dynamical model developed and studied in the literature. A treatment model based on the proposed unified PDE model is investigated via optimal control theory, where its first-order necessary optimality system characterizing the optimal control is derived. We prove that the uniqueness of the optimal control depends on the chosen objective functional, and the optimal control is of bang-bang type when it is unique. For obtaining its efficient numerical solutions, a projection gradient descent algorithm based on the characteristic scheme is developed for solving the established optimal treatment model. Several numerical examples are provided to validate our mathematical analysis and numerical algorithm, and also illustrate the biologically interesting treatment outcomes of different models and control strategies. Our simple model reveals that: (i) only the total drug dosage matters if one just cares about the final treatment output; (ii) given the same total drug dosage, the optimal bang-bang treatment plan outperforms the others in the sense that it maximally reduces the total tumor sizes during the whole period of treatment, although their final tumor sizes are the same.

Adding Nanotechnology to the Metastasis Treatment Arsenal

Metastasis is a major cause of cancer-related mortality, accounting for 90% of cancer deaths. The explosive growth of cancer biology research has revealed new mechanistic network information and pathways that promote metastasis. Consequently, a large number of antitumor agents have been developed and tested for their antimetastatic efficacy. Despite their exciting cytotoxic effects on tumor cells in vitro and antitumor activities in preclinical studies in vivo, only a few have shown potent antimetastatic activities in clinical trials. In this review, we provide a brief overview of current antimetastatic strategies that show clinical efficacy and review nanotechnology-based approaches that are currently being incorporated into these therapies to mitigate challenges associated with treating cancer metastasis.

Tracing the path of cancer initiation: the AA protein-based model for cancer genesis

Background

Cancer is a defiant disease which cure is still far from being attained besides the colossal efforts and financial means deployed towards that end. The continuing setbacks encountered with today’s arsenal of anti-cancer drugs and cancer therapy modalities; show the need for a radical approach in order to get to the root of the problem. And getting to the root of cancer initiation and development leads us to challenge the present dogmas surrounding the pathogenesis of this disease.

Results

This comprehensive analysis brings to light the following points: (i) Cancer with its plethora of genetic and cellular symptoms could originate from one major event switching a cell from normalcy-to-malignancy; (ii) The switching event is postulated to involve a pathological breakup of a non-mutated protein, called here AA protein, resulting in the acquisition of new cellular functions present only in cancer cells; (iii) Following this event, DNA mutations begin to accumulate as secondary events to ensure perpetuity of cancer. Supporting arguments for this protein-based model come mainly from these observations: (i) The AA protein-based model reconciles together the clonal-and-stem cell theories into one inclusive model; (ii) The breakup of a normal protein could be behind the cancer-linked inflammation symptom; (iii) Cancer hallmarks are but adaptive traits, earned as a result of the switch from normalcy-to-malignancy.

Conclusions

Adaptation of cancer cells to their microenvironment and to different anti-cancer drugs is deemed here as the ultimate cancer hallmark, that needs to be understood and controlled. This adaptive power of cancer cells parallels that of bacteria also known with their resistance to a large range of substances in nature and in the laboratory. Consequently, cancer development could be viewed as a backward walk on the line of Evolution. Finally this unprecedented analysis demystifies cancer and puts the finger on the core problem of malignancy while offering ideas for its control with the ultimate goal of leading to its cure.

Genetic insights into the morass of metastatic heterogeneity

Tumour heterogeneity poses a substantial problem for the clinical management of cancer. Somatic evolution of the cancer genome results in genetically distinct subclones in the primary tumour with different biological properties and therapeutic sensitivities. The problem of heterogeneity is compounded in metastatic disease owing to the complexity of the metastatic process and the multiple biological hurdles that the tumour cell must overcome to establish a clinically overt metastatic lesion. New advances in sequencing technology and clinical sample acquisition are providing insights into the phylogenetic relationship of metastases and primary tumours at the level of somatic tumour genetics while also illuminating fundamental mechanisms of the metastatic process. In addition to somatically acquired genetic heterogeneity in the tumour cells, inherited population-based genetic heterogeneity can profoundly modify metastatic biology and further complicate the development of effective, broadly applicable antimetastatic therapies. Here, we examine how genetic heterogeneity impacts metastatic disease and the implications of current knowledge for future research endeavours and therapeutic interventions.

Employing an orthotopic model to study the role of epithelial-mesenchymal transition in bladder cancer metastasis

Epithelial-to-mesenchymal transition (EMT) has been implicated in the progression of bladder cancer. To study its contribution to bladder cancer metastasis, we established new xenograft models derived from human bladder cancer cell lines utilizing an orthotopic “recycling” technique that allowed us to isolate and examine the primary tumor and its corresponding circulating tumor cells (CTC’s) and metastatic lesions. Using whole genome mRNA expression profiling, we found that a reversible epithelial-to-mesenchymal transition (EMT) characterized by TGFβ pathway activation and SNAIL expression was associated with the accumulation of CTCs. Finally, we observed that conditional silencing of SNAIL completely blocked CTC production and regional/distant metastasis. Using this unique bladder cancer xenograft model, we conclude that metastasis is dependent on a reversible EMT mediated by SNAIL.

Differences in Zbtb7a expression cause heterogeneous changes in human nasopharyngeal carcinoma CNE3 sublines

The present study aimed to determine the association between changes in Zbtb7a expression levels and heterogeneity of nasopharyngeal carcinoma (NPC) CNE3 sublines. CNE3 sublines were established by screening of serial dilution and continuous passage. Proliferative ability and tumorigenicity of the sublines were analyzed separately by soft-agar colony formation and mouse studies. The NPC tissues from mice were analyzed by histological evaluation and immunohistochemistry. The expression levels of Zbtb7a mRNA and protein were analyzed separately by quantitative reverse transcription polymerase chain reaction and western blotting. According to findings from the soft-agar colony formation and mouse studies, two sublines with increased tumorigenicity compared with other sublines were transfected transiently with Zbtb7a short hairpin RNA (shRNA) recombinant plasmid. The changes in viability, migration and invasion abilities were evaluated separately by MTT, colorimetric focus-formation, Transwell migration and invasion assays. The sublines CNE3-GX6 and CNE3-GX11 were selected for subsequent study due to increased tumorigenicity and increased Zbtb7a expression levels compared with the other sublines. High metastatic potency was not observed in all of the sublines. Zbtb7a expression levels were positively associated with tumorigenic degree of the sublines. The growth, migration and invasion abilities of the sublines transfected with Zbtb7a shRNA plasmid were decreased compared with the cells transfected with empty vector in the negative control group. The findings suggest Zbtb7a expression levels may be associated with heterogeneity of CNE3 sublines. Therefore, Zbtb7a may have an important role in the regulatory mechanism of NPC heterogeneity.

Amigo2-upregulation in Tumour Cells Facilitates Their Attachment to Liver Endothelial Cells Resulting in Liver Metastases

Since liver metastasis is the main cause of death in cancer patients, we attempted to identify the driver gene involved. QRsP-11 fibrosarcoma cells were injected into the spleens of syngeneic mice to isolate tumour sub-populations that colonize the liver. Cells from liver metastatic nodules were established and subsequently injected intrasplenically for selection. After 12 cycles, the cell subline LV12 was obtained. Intravenous injection of LV12 cells produced more liver metastases than QRsP-11 cells, whereas the incidence of lung metastases was similar to that of QRsP-11 cells. LV12 cells adhered to liver-derived but not to lung-derived endothelial cells. DNA chip analysis showed that amphoterin-induced gene and open reading frame 2 (Amigo2) was overexpressed in LV12 cells. siRNA-mediated knockdown of Amigo2 expression in LV12 cells attenuated liver endothelial cell adhesion. Ex vivo imaging showed that suppression of Amigo2 in luciferase-expressing LV12 cells reduced attachment/metastasis to liver to the same level as that observed with QRsP-11 cells. Forced expression of Amigo2 in QRsP-11 cells increased liver endothelial cell adhesion and liver metastasis. Additionally, Amigo2 expression in human cancers was higher in liver metastatic lesions than in primary lesions. Thus, Amigo2 regulated tumour cell adhesion to liver endothelial cells and formation of liver metastases.

How Subclonal Modeling Is Changing the Metastatic Paradigm

A concerted effort to sequence matched primary and metastatic tumors is vastly improving our ability to understand metastasis in humans. Compelling evidence has emerged that supports the existence of diverse and surprising metastatic patterns. Enhancing these efforts is a new class of algorithms that facilitate high-resolution subclonal modeling of metastatic spread. Here we summarize how subclonal models of metastasis are influencing the metastatic paradigm. Clin Cancer Res; 23(3); 630-5. ©2016 AACR.

The challenge of targeting metastasis

Metastases that are resistant to conventional therapy are the major cause of death from cancer. In most patients, metastasis has already occurred by the time of diagnosis. Thus, the prevention of metastasis is unlikely to be of therapeutic benefit. The biological heterogeneity of metastases presents a major obstacle to treatment. However, the growth and survival of metastases depend on interactions between tumor cells and host homeostatic mechanisms. Targeting these interactions, in addition to the tumor cells, can produce synergistic therapeutic effects against existing metastases.

Defining the Influence of Germline Variation on Metastasis Using Systems Genetics Approaches

Cancer is estimated to be responsible for 8 million deaths worldwide and over half a million deaths every year in the United States. The majority of cancer-related deaths in solid tumors is directly associated with the effects of metastasis. While the influence of germline factors on cancer risk and development has long been recognized, the contribution of hereditary variation to tumor progression and metastasis has only gained acceptance more recently. A variety of approaches have been used to define how hereditary variation influences tumor progression and metastasis. One approach that garnered much early attention was epidemiological studies of cohorts of cancer patients, which demonstrated that specific loci within the human genome are associated with a differential propensity for aggressive tumor development. However, a powerful, and somewhat underutilized approach has been the use of systems genetics approaches in transgenic mouse models of human cancer. Such approaches are typically multifaceted, and involve integration of multiple lines of evidence derived, for example, from genetic and transcriptomic screens of genetically diverse mouse models of cancer, coupled with bioinformatics analysis of human cancer datasets, and functional analysis of candidate genes. These methodologies have allowed for the identification of multiple hereditary metastasis susceptibility genes, with wide-ranging cellular functions including regulation of gene transcription, cell proliferation, and cell-cell adhesion. In this chapter, we review how each of these approaches have facilitated the identification of these hereditary metastasis modifiers, the molecular functions of these metastasis-associated genes, and the implications of these findings upon patient survival.

The Biology of Pulmonary Metastasis

The process of metastasis relies on a series of stochastic and sequential steps, with selective pressure exerted on a large number of genetically volatile cancer cells to produce a very small fraction of tumor cells with the ability to navigate the transition from primary tumor cell to end-organ metastasis. This process is intricately determined by cell-microenvironment interactions, the mechanistic understanding of which is steadily increasing. The continued elucidation of pathways that govern these interactions offers potential therapeutic options to patients with advanced disease.

The Biology of Brain Metastasis: Challenges for Therapy

Many patients with lung cancer, breast cancer, and melanoma develop brain metastases that are resistant to conventional therapy. The median survival for untreated patients is 1 to 2 months, which may be extended to 6 months with surgery, radiotherapy, and chemotherapy. The outcome of metastasis depends on multiple interactions of unique metastatic cells with host homeostatic mechanisms which the tumor cells exploit for their survival and proliferation. The blood-brain barrier is leaky in metastases that are larger than 0.5-mm diameter because of production of vascular endothelial growth factor by metastatic cells. Brain metastases are surrounded and infiltrated by microglia and activated astrocytes. The interaction with astrocytes leads to up-regulation of multiple genes in the metastatic cells, including several survival genes that are responsible for the increased resistance of tumor cells to cytotoxic drugs. These findings substantiate the importance of the "seed and soil" hypothesis and that successful treatment of brain metastases must include targeting of the organ microenvironment.

Distinctive properties of metastasis-initiating cells

Primary tumors are known to constantly shed a large number of cancer cells into systemic dissemination, yet only a tiny fraction of these cells is capable of forming overt metastases. The tremendous rate of attrition during the process of metastasis implicates the existence of a rare and unique population of metastasis-initiating cells (MICs). MICs possess advantageous traits that may originate in the primary tumor but continue to evolve during dissemination and colonization, including cellular plasticity, metabolic reprogramming, the ability to enter and exit dormancy, resistance to apoptosis, immune evasion, and co-option of other tumor and stromal cells. Better understanding of the molecular and cellular hallmarks of MICs will facilitate the development and deployment of novel therapeutic strategies.

Metastatic spread in patients with non-small cell lung cancer is associated with a reduced density of tumor-infiltrating T cells

Tumor-infiltrating lymphocytes play an important role in cell-mediated immune destruction of cancer cells and tumor growth control. We investigated the heterogeneity of immune cell infiltrates between primary non-small cell lung carcinomas (NSCLC) and corresponding metastases. Formalin-fixed, paraffin-embedded primary tumors and corresponding metastases from 34 NSCLC patients were analyzed by immunohistochemistry for CD4, CD8, CD11c, CD68, CD163 and PD-L1. The percentage of positively stained cells within the stroma and tumor cell clusters was recorded and compared between primary tumors and metastases. We found significantly fewer CD4(+) and CD8(+) T cells within tumor cell clusters as compared with the stromal compartment, both in primary tumors and corresponding metastases. CD8(+) T cell counts were significantly lower in metastatic lesions than in the corresponding primary tumors, both in the stroma and the tumor cell islets. Of note, the CD8/CD4 ratio was significantly reduced in metastatic lesions compared with the corresponding primary tumors in tumor cell islets, but not in the stroma. We noted significantly fewer CD11c(+) cells and CD68(+) as well as CD163(+) macrophages in tumor cell islets compared with the tumor stroma, but no difference between primary and metastatic lesions. Furthermore, the CD8/CD68 ratio was higher in primary tumors than in the corresponding metastases. We demonstrate a differential pattern of immune cell infiltration in matched primary and metastatic NSCLC lesions, with a significantly lower density of CD8(+) T cells in metastatic lesions compared with the primary tumors. The lower CD8/CD4 and CD8/CD68 ratios observed in metastases indicate a rather tolerogenic and tumor-promoting microenvironment at the metastatic site.

Computational Modelling of Metastasis Development in Renal Cell Carcinoma

The biology of the metastatic colonization process remains a poorly understood phenomenon. To improve our knowledge of its dynamics, we conducted a modelling study based on multi-modal data from an orthotopic murine experimental system of metastatic renal cell carcinoma. The standard theory of metastatic colonization usually assumes that secondary tumours, once established at a distant site, grow independently from each other and from the primary tumour. Using a mathematical model that translates this assumption into equations, we challenged this theory against our data that included: 1) dynamics of primary tumour cells in the kidney and metastatic cells in the lungs, retrieved by green fluorescent protein tracking, and 2) magnetic resonance images (MRI) informing on the number and size of macroscopic lesions. Critically, when calibrated on the growth of the primary tumour and total metastatic burden, the predicted theoretical size distributions were not in agreement with the MRI observations. Moreover, tumour expansion only based on proliferation was not able to explain the volume increase of the metastatic lesions. These findings strongly suggested rejection of the standard theory, demonstrating that the time development of the size distribution of metastases could not be explained by independent growth of metastatic foci. This led us to investigate the effect of spatial interactions between merging metastatic tumours on the dynamics of the global metastatic burden. We derived a mathematical model of spatial tumour growth, confronted it with experimental data of single metastatic tumour growth, and used it to provide insights on the dynamics of multiple tumours growing in close vicinity. Together, our results have implications for theories of the metastatic process and suggest that global dynamics of metastasis development is dependent on spatial interactions between metastatic lesions.

We used mathematical modelling to formalize the standard theory of metastatic initiation, under which secondary tumours, after establishment in a distant organ, grow independently from each other and from the primary tumour. When calibrated on the experimental data of primary tumour and total metastatic burden in the lungs in an animal model of renal cell carcinoma, the initial model predicted a size distribution of metastatic foci that did not fit with observations obtained experimentally using magnetic resonance imaging (which provided size and number of macro-metastases). The model predicted an increase in the number of lesions, but of smaller size when compared to the data. This led us to revise the standard theory and to propose two hypotheses in order to explain the observations: 1) small metastatic foci merge into larger ones and/or 2) circulating tumour cells may join already established tumours. We then derived a spatial model of tumour growth in order to explore the quantitative implications of tumours merging on global tumour growth and estimated the numbers of required metastatic foci to obtain the observed metastatic volumes.

Pancreatic Cancer Metastases Harbor Evidence of Polyclonality

Studies of the cancer genome have demonstrated that tumors are composed of multiple subclones with varied genetic and phenotypic properties. However, little is known about how metastases arise and evolve from these subclones. To understand the cellular dynamics that drive metastasis, we used multicolor lineage-tracing technology in an autochthonous mouse model of pancreatic cancer. Here, we report that precursor lesions exhibit significant clonal heterogeneity but that this diversity decreases during premalignant progression. Furthermore, we present evidence that a significant fraction of metastases are polyclonally seeded by distinct tumor subclones. Finally, we show that clonality during metastatic growth-leading to either monoclonal or polyclonal expansion-differs based on the site of metastatic invasion. These results provide an unprecedented window into the cellular dynamics of tumor evolution and suggest that heterotypic interactions between tumor subpopulations contribute to metastatic progression in native tumors.

SIGNIFICANCE

Studies of tumor heterogeneity indicate that distinct tumor subclones interact during cancer progression. Here, we demonstrate by lineage tracing that metastases often involve seeding by more than one clone and that subsequent cellular outgrowth depends on the metastatic site. These findings provide insight into clonal diversity and evolution in metastatic disease.

The role of individual inheritance in tumor progression and metastasis

Metastasis, the dissemination and growth of tumor cells at secondary sites, is the primary cause of patient mortality from solid tumors. Metastasis is an extremely complex, inefficient process requiring contributions of not only the tumor cell but also local and distant environmental factors, at both the cellular and molecular level. Variation in the function of any of the steps in the metastatic cascade may therefore have profound implications for the ultimate course of the disease. In addition to the somatic and cellular heterogeneity that can affect cancer outcome, an individual's specific ancestry or genetic background can also significantly influence metastatic progression. These inherited variants not only encoded for metastatic susceptibility but also provided a window to study critical factors that are not easily accessible with current technologies. Furthermore, investigations into inherited metastatic susceptibility enable identification of important molecular and cellular processes that are not subject to mutation and are consequently not detectable by standard cancer genome sequencing strategies. Incorporation of inherited variation into metastasis research therefore provides methods to more comprehensively investigate the etiology of the lethal consequences of tumor progression.

Hotspot mutation panel testing reveals clonal evolution in a study of 265 paired primary and metastatic tumors

PURPOSE

We used a clinical next-generation sequencing (NGS) hotspot mutation panel to investigate clonal evolution in paired primary and metastatic tumors.

EXPERIMENTAL DESIGN

A total of 265 primary and metastatic tumor pairs were sequenced using a 46-gene cancer mutation panel capable of detecting one or more single-nucleotide variants as well as small insertions/deletions. Mutations were tabulated together with tumor type and percentage, mutational variant frequency, time interval between onset of primary tumor and metastasis, and neoadjuvant therapy status.

RESULTS

Of note, 227 of 265 (85.7%) tumor metastasis pairs showed identical mutation calls. Of the tumor pairs with identical mutation calls, 160 (60.4%) possessed defining somatic mutation signatures and 67 (25.3%) did not exhibit any somatic mutations. There were 38 (14.3%) cases that showed at least one novel mutation call between the primary and metastasis. Metastases were almost two times more likely to show novel mutations (n = 20, 7.5%) than primary tumors (n = 12, 4.5%). TP53 was the most common additionally mutated gene in metastatic lesions, followed by PIK3CA and SMAD4. PIK3CA mutations were more often associated with metastasis in colon carcinoma samples.

CONCLUSIONS

Clinical NGS hotspot panels can be useful in analyzing clonal evolution within tumors as well as in determining subclonal mutations that can expand in future metastases. PIK3CA, SMAD4, and TP53 are most often involved in clonal divergence, providing potential targets that may help guide the clinical management of tumor progression or metastases.

Radiation-induced VEGF-C expression and endothelial cell proliferation in lung cancer

BACKGROUND

The present study was undertaken to investigate whether radiation induces the expression of vascular endothelial growth factor C (VEGF-C) through activation of the PI3K/Akt/mTOR pathway,subsequently affecting endothelial cells.

MATERIALS AND METHODS

Radiotherapy-induced tumor micro-lymphatic vessel density (MLVD) was determined in a lung cancer xenograft model established in SCID mice. The protein expression and phosphorylation of members of the PI3K/Akt/mTOR pathway and VEGF-C secretion and mRNA expression in irradiated lung cancer cells were assessed by Western blot analysis, enzyme-linked immunosorbent assays (ELISAs), and reverse transcriptase-polymerase chain reaction (RT-PCR). Moreover, specific chemical inhibitors were used to evaluate the role of the PI3K/Akt/mTOR signaling pathway. Conditioned medium (CM) from irradiated control-siRNA or VEGF-C-siRNA-expressing A549 cells was used to evaluate the proliferation of endothelial cells by the MTT assay.

RESULTS

Radiation increased VEGF-C expression in a dose-dependent manner over time at the protein but not at the mRNA level. Radiation also up-regulated the phosphorylation of Akt, mTOR, 4EBP, and eIF4E, but not of p70S6K. Radiation-induced VEGF-C expression was down-regulated by LY294002 and rapamycin (both p < 0.05). Furthermore, CM from irradiated A549 cells enhanced human umbilical vein endothelial cell (HUVEC) and lymphatic endothelial cell (LEC) proliferation, which was not observed with CM from irradiated VEGF-C-siRNA-expressing A549 cells.

CONCLUSIONS

Radiation-induced activation of the PI3K/Akt/mTOR signaling pathway increases VEGF-C expression in lung cancer cells, thereby promoting endothelial cell proliferation.

Highly adaptable triple-negative breast cancer cells as a functional model for testing anticancer agents

A major obstacle in developing effective therapies against solid tumors stems from an inability to adequately model the rare subpopulation of panresistant cancer cells that may often drive the disease. We describe a strategy for optimally modeling highly abnormal and highly adaptable human triple-negative breast cancer cells, and evaluating therapies for their ability to eradicate such cells. To overcome the shortcomings often associated with cell culture models, we incorporated several features in our model including a selection of highly adaptable cancer cells based on their ability to survive a metabolic challenge. We have previously shown that metabolically adaptable cancer cells efficiently metastasize to multiple organs in nude mice. Here we show that the cancer cells modeled in our system feature an embryo-like gene expression and amplification of the fat mass and obesity associated gene FTO. We also provide evidence of upregulation of ZEB1 and downregulation of GRHL2 indicating increased epithelial to mesenchymal transition in metabolically adaptable cancer cells. Our results obtained with a variety of anticancer agents support the validity of the model of realistic panresistance and suggest that it could be used for developing anticancer agents that would overcome panresistance.

Role of the neural niche in brain metastatic cancer

Metastasis is the relentless pursuit of cancer to escape its primary site and colonize distant organs. This malignant evolutionary process is biologically heterogeneous, yet one unifying element is the critical role of the microenvironment for arriving metastatic cells. Historically, brain metastases were rarely investigated because patients with advanced cancer were considered terminal. Fortunately, advances in molecular therapies have led to patients living longer with metastatic cancer. However, one site remains recalcitrant to our treatment efforts, the brain. The central nervous system is the most complex biologic system, which poses unique obstacles but also harbors opportunities for discovery. Much of what we know about the brain microenvironment comes from neuroscience. We suggest that the interrelated cellular responses in traumatic brain injury may guide us toward new perspectives in understanding brain metastases. In this view, brain metastases may be conceptualized as progressive oncologic injury to the nervous system. This review discusses our evolving understanding of bidirectional interactions between the brain milieu and metastatic cancer.

Circulating Tumor Cells in Metastatic Breast Cancer: A Prognostic and Predictive Marker

The role of circulating tumor cells (CTCs) as a marker for disease progression in metastatic cancer is controversial. The current review will serve to summarize the evidence on CTCs as a marker of disease progression in patients with metastatic breast cancer. The immunohistochemistry(IHC)-based CellSearch^® is the only FDA-approved isolation technique for quantifying CTCs in patients with metastatic breast cancer. We searched PubMed and Web of Knowledge for clinical studies that assessed the prognostic and predictive value of CTCs using IHC-based isolation. The patient outcomes reported include median and Cox-proportional hazard ratios for overall-survival (OS) and progression-free-survival (PFS). All studies reported shorter OS for CTC-positive patients versus CTC-negative. A subset of the selected trials reported significant lower median PFS for CTC-positive patients. The reported trials support the utility of CTC enumeration for patient prognosis. But further studies are required to determine the utility of CTC enumeration for guiding patient therapy. There are three clinical trials ongoing to test this hypothesis. These studies, and others, will further establish the role of CTCs in clinical practice.

Molecular analysis of circulating tumour cells-biology and biomarkers

Growing evidence for intratumour heterogeneity informs us that single-site biopsies fall short of revealing the complete genomic landscape of a tumour. With an expanding repertoire of targeted agents entering the clinic, screening tumours for genomic aberrations is increasingly important, as is interrogating the tumours for resistance mechanisms upon disease progression. Multiple biopsies separated spatially and temporally are impractical, uncomfortable for the patient and not without risk. Here, we describe how circulating tumour cells (CTCs), captured from a minimally invasive blood test-and readily amenable to serial sampling-have the potential to inform intratumour heterogeneity and tumour evolution, although it remains to be determined how useful this will be in the clinic. Technologies for detecting and isolating CTCs include the validated CellSearch(®) system, but other technologies are gaining prominence. We also discuss how recent CTC discoveries map to mechanisms of haematological spread, previously described in preclinical models, including evidence for epithelial-mesenchymal transition, collective cell migration and cells with tumour-initiating capacity within the circulation. Advances in single-cell molecular analysis are enhancing our ability to explore mechanisms of metastasis, and the combination of CTC and cell-free DNA assays are anticipated to provide invaluable blood-borne biomarkers for real-time patient monitoring and treatment stratification.

[An experimental study on the Chinese lung adenocarcinoma cell clone CPA-Yang1-BR with brain metastasis potency in nude mice and in vivo imaging research]

背景与目的

肺癌脑转移是临床常见的严重并发症，由于脑部结构和功能的特殊性、脑转移检测方法的局限性，预后很差。本研究旨在筛选人肺腺癌脑转移细胞株CPA-Yang1-BR以及建立裸小鼠动物模型和检测方法。

方法

将人肺腺癌细胞株CPA-Yang1-GFP接种于裸小鼠左心室，约7周-8周后比较三种小动物显像方法：micro PET/CT显像，X线、放射性核素、荧光（三合一）活体成像系统和小动物线圈MRI显像，实验证明MRI显像是最准确的小鼠脑转移病灶检测方法。脑核磁共振成像（magnatic resonance imaging, MRI）显像找到脑转移灶，深麻醉处死裸小鼠取出脑转移病灶，部分病理验证，部分行原代培养后获得人肺腺癌脑转移细胞，再次接种裸小鼠，用上述方法重复以上体内外循环4次，观察脑转移形成情况。

结果

获得人肺腺癌脑转移细胞株CPA-Yang1-BR及其裸小鼠模型。

结论

CPA-Yang1细胞经反复裸小鼠脑组织内外筛选的方法可获得具有高转移潜能的裸小鼠脑转移模型，为肺癌脑转移的生物学研究提供了一个良好的技术平台。小动物线圈MRI或micro MRI活体显像是检测小鼠肺癌脑转移敏感、准确、无创伤的显像方法。

The biology of brain metastasis

BACKGROUND

It is estimated that at least 200 000 cases of brain metastases occur each year in the US, which is 10 times the number of patients diagnosed with primary brain tumors. Brain metastasis is associated with poor prognosis, neurological deterioration, diminished quality of life, and extremely short survival. Favorable interactions between tumor cells and cerebral microvascular endothelial cells encourage tumor growth in the central nervous system, while tumor cell interactions with astrocytes protect brain metastases from the cytotoxic effects of chemotherapy.

CONTENT

We review the pathogenesis of brain metastasis and emphasize the contributions of microvascular endothelial cells and astrocytes to disease progression and therapeutic resistance. Animal models used to study brain metastasis are also discussed.

SUMMARY

Brain metastasis has many unmet clinical needs. There are few clinically relevant tumor models and no targeted therapies specific for brain metastases, and the mean survival for untreated patients is 5 weeks. Improved clinical outcomes are dependent on an enhanced understanding of the metastasis-initiating population of cells and the identification of microenvironmental factors that encourage disease progression in the central nervous system.

Clinical opportunities and challenges in targeting tumour dormancy

The reactivation of cancer cells following a seemingly successful treatment of the primary tumour with initial therapies (such as tumour excision or systemic therapy) is a well-known phenomenon. This metastatic rebirth is preceded by an interlude, termed dormancy, when cancer sleeps undetected for periods that can last years or even decades. Discoveries over the past 10 years have revealed the therapeutic potential of prolonging dormancy for maintaining a clinically asymptomatic state, or the permanent clearance of dormant residual disseminated cancer cells to affect a 'cure'. Here, we provide an overview of the mechanisms of dormancy and use genitourinary cancers as models to demonstrate how dormancy principles could be exploited clinically. Data from these models have yielded promising therapeutic strategies to address dormancy as well as diagnostics that could enable clinicians to monitor the dormant state of cancer in patients. This Review also aims to convey that dormancy, as a whole, likely results from coalescing contributions made by each of the three types of dormancy discussed (cellular, angiogenic and immunological). In our opinion, dormancy-directed therapies will prove most effective when the effect of these cumulative contributions are understood and targeted.

Positive lymph nodes do not metastasize

Our understanding of the role of lymph nodes (LN) in the metastasization process (MET) is marginal. Positive LNs (pLN) are the most important prognostic factor and lymph node dissection (LND) is still standard practice in primary treatment. However, up to now, there is almost no evidence that elective LND has a survival benefit. Based on many clinical and experimental findings, we propose that tumor foci in regional LN are incapable of metastasization and can therefore not infiltrate further LN and organs. Available data demonstrate a very early infiltration of MET capable tumor cells from the primary tumor into regional LN, and thereafter an increased probability of subsequent LN infiltrations. Disparate growth rates of the first versus subsequent infiltrating tumors as well as the asymptotic growth and prognosis of large tumor foci in LN explain many clinical observations for solid tumors. The consequence of the hypothesis "pLN do not metastasize" would impact clinical treatment and research and contribute to understanding the mounting evidence against LND.