How Subclonal Modeling Is Changing the Metastatic Paradigm

Clone Phylogenetics Reveals Metastatic Tumor Migrations, Maps, and Models

Simple Summary

Metastasis is the spread of cancer cells across organs and is a major cause of cancer mortality. Analysis of tumor sequencing data provides a means toward the reconstruction of routes of metastatic cell migrations. Our reconstructions demonstrated that many metastases were likely seeded from pre-existing metastasis of primary tumors. Additionally, multiple clone exchanges between tumor sites were common. In conclusion, the pattern of cancer cell migrations is often complex and is highly variable among patients.

Abstract

Dispersal routes of metastatic cells are not medically detected or even visible. A molecular evolutionary analysis of tumor variation provides a way to retrospectively infer metastatic migration histories and answer questions such as whether the majority of metastases are seeded from clones within primary tumors or seeded from clones within pre-existing metastases, as well as whether the evolution of metastases is generally consistent with any proposed models. We seek answers to these fundamental questions through a systematic patient-centric retrospective analysis that maps the dynamic evolutionary history of tumor cell migrations in many cancers. We analyzed tumor genetic heterogeneity in 51 cancer patients and found that most metastatic migration histories were best described by a hybrid of models of metastatic tumor evolution. Synthesizing across metastatic migration histories, we found new tumor seedings arising from clones of pre-existing metastases as often as they arose from clones from primary tumors. There were also many clone exchanges between the source and recipient tumors. Therefore, a molecular phylogenetic analysis of tumor variation provides a retrospective glimpse into general patterns of metastatic migration histories in cancer patients.

Tumors Are Evolutionary Island-Like Ecosystems

Integration of ecological and evolutionary features has begun to understand the interplay of tumor heterogeneity, microenvironment, and metastatic potential. Developing a theoretical framework is intrinsic to deciphering tumors' tremendous spatial and longitudinal genetic variation patterns in patients. Here, we propose that tumors can be considered evolutionary island-like ecosystems, that is, isolated systems that undergo evolutionary and spatiotemporal dynamic processes that shape tumor microenvironments and drive the migration of cancer cells. We examine attributes of insular systems and causes of insularity, such as physical distance and connectivity. These properties modulate migration rates of cancer cells through processes causing spatial and temporal isolation of the organs and tissues functioning as a supply of cancer cells for new colonizations. We discuss hypotheses, predictions, and limitations of tumors as islands analogy. We present emerging evidence of tumor insularity in different cancer types and discuss their relevance to the islands model. We suggest that the engagement of tumor insularity into conceptual and mathematical models holds promise to illuminate cancer evolution, tumor heterogeneity, and metastatic potential of cells.

TP53 Mutation and Extraneural Metastasis of Glioblastoma: Insights From an Institutional Experience and Comprehensive Literature Review

Extraneural metastases of glioblastoma (GBM), although rare, are becoming an increasingly recognized occurrence. Currently, the biological mechanism underlying this rare occurrence is not understood. To explore the potential genomic drivers of extraneural metastasis in GBM, we present the molecular features of 4 extraneural metastatic GBMs, along with a comprehensive review and analysis of previously reported cases that had available molecular characterization. In addition to our 4 cases, 42 patients from 35 publications are reviewed. To compare the molecular profiles between GBM cases with extraneural metastasis and the general GBM population, genomic data from GBM samples in The Cancer Genome Atlas (TCGA) database were also analyzed. We found that 64.5% (20/31) of the cases with extraneural metastasis that were tested for TP53 changes had at least 1 TP53 pathogenic variant detected in either 1 or both primary and metastatic tumors. In contrast, TP53 mutation was significantly less frequent in the unselected GBM from TCGA (22.6%, 56/248) (P=0.000). In addition, O-6-methylguanine-DNA methyltransferase (MGMT) promoter methylation was more common in unselected TCGA GBM cases (48.6%, 170/350) than in cases with extraneural metastasis (31.8%, 7/22), although not statistically significant. Although isocitrate dehydrogenase (IDH) mutation is a rare occurrence in high-grade astrocytomas, IDH-mutant grade 4 astrocytomas are at least as likely to metastasize as IDH wild-type GBMs; 3 metastatic cases definitively harbored an IDH1 (p.R132H) mutation in our analysis. Our findings not only provide potential biomarkers for earlier screening of extraneural metastasis, but could also suggest clues to understanding biological mechanisms underlying GBM metastasis, and for the development of therapeutic modalities.

Genomic and phenotypic heterogeneity in prostate cancer

From a clinical, morphological and molecular perspective, prostate cancer is a heterogeneous disease. Primary prostate cancers are often multifocal, having topographically and morphologically distinct tumour foci. Sequencing studies have revealed that individual tumour foci can arise as clonally distinct lesions with no shared driver gene alterations. This finding demonstrates that multiple genomically and phenotypically distinct primary prostate cancers can be present in an individual patient. Lethal metastatic prostate cancer seems to arise from a single clone in the primary tumour but can exhibit subclonal heterogeneity at the genomic, epigenetic and phenotypic levels. Collectively, this complex heterogeneous constellation of molecular alterations poses obstacles for the diagnosis and treatment of prostate cancer. However, advances in our understanding of intra-tumoural heterogeneity and the development of novel technologies will allow us to navigate these challenges, refine approaches for translational research and ultimately improve patient care.

Clonal Evolution and Timing of Metastatic Colorectal Cancer

Colorectal cancer (CRC) is the third most frequently diagnosed cancer worldwide, where ~50% of patients develop metastasis, despite current improved management. Genomic characterisation of metastatic CRC, and elucidating the effects of therapy on the metastatic process, are essential to help guide precision medicine. Multi-region whole-exome sequencing was performed on 191 sampled tumour regions of patient-matched therapy-naïve and treated CRC primary tumours (n = 92 tumour regions) and metastases (n = 99 tumour regions), in 30 patients. Somatic variants were analysed to define the origin, composition, and timing of seeding in the metastatic progression of therapy-naïve and treated metastatic CRC. High concordance, with few genomic differences, was observed between primary CRC and metastases. Most cases supported a late dissemination model, via either monoclonal or polyclonal seeding. Polyclonal seeding appeared more common in therapy-naïve metastases than in treated metastases. Whereby, treatment prompted for the selection of distinct resistant clones, through monoclonal seeding to distant metastatic sites. Overall, this study reinforces the importance of early clinical detection and surgical excision of the CRC tumour, whilst further highlighting the clinical challenges for metastatic CRC with increased intratumour heterogeneity (either due to early dissemination or polyclonal metastatic spread) and the underlying risk of future therapeutic resistance in treated patients.

Combination of Brachytherapy with Iodine-125 Seeds and Systemic Chemotherapy versus Systemic Chemotherapy Alone for Synchronous Extracranial Oligometastatic Non-Small Cell Lung Cancer

Background

A proportion of patients with synchronous oligometastatic non-small cell lung cancer (NSCLC) have poor survival, and currently no standard treatment is available, which poses a great challenge to physicians. This study aimed to assess and compare the efficacy and safety of the combination of brachytherapy with iodine-125 seeds and systemic chemotherapy versus systemic chemotherapy alone for synchronous extracranial oligometastatic NSCLC.

Materials and Methods

After a systematic retrospective review of the case database between 1st Mar 2014 and 30th Mar 2018, data were obtained on 69 NSCLC patients with extracranial oligometastatic NSCLC. Among them, 32 patients received brachytherapy with iodine-125 seeds combined with systemic chemotherapy (group A), and the remaining 37 patients received chemotherapy alone (group B). The primary endpoint was overall survival (OS), and the secondary endpoints included progression-free survival (PFS), objective response rate (ORR), and complications.

Results

The demographic and clinical characteristics were not significantly different between the groups (all p>0.05). The overall 3-month ORR was significantly higher in group A (65.6% vs 37.8%, p=0.030) than in group B. With a median follow-up time of 23 months, the PFS and OS were 11.6 (95% CI: 7.0–16.2) months vs 6.3 (95% CI: 3.4–9.2) months (p=0.036) and 17.6 (95% CI: 13.9–21.3) months vs 11.2 (95% CI: 7.7–14.7) months (p=0.042) in groups A and B, respectively. Furthermore, in Cox regression analysis, local brachytherapy was an independent prognostic factor for both PFS (HR=0.416, 95% CI: 0.246–0.702, p=0.001) and OS (HR=0.375, 95% CI: 0.216–0.653, p=0.001). Severe complications were not observed in either of the groups.

Conclusion

The combination of brachytherapy with iodine-125 seeds and systemic chemotherapy is superior to chemotherapy alone for synchronous extracranial oligometastatic NSCLC.

Lymph node metastases develop through a wider evolutionary bottleneck than distant metastases

Genetic diversity among metastases is poorly understood but contains important information about disease evolution at secondary sites. Here we investigate inter- and intra-lesion heterogeneity for two types of metastases that associate with different clinical outcomes: lymph node and distant organ metastases in human colorectal cancer. We develop a rigorous mathematical framework for quantifying metastatic phylogenetic diversity. Distant metastases are typically monophyletic and genetically similar to each other. Lymph node metastases, in contrast, display high levels of inter-lesion diversity. We validate these findings by analyzing 317 multi-region biopsies from an independent cohort of 20 patients. We further demonstrate higher levels of intra-lesion heterogeneity in lymph node than in distant metastases. Our results show that fewer primary tumor lineages seed distant metastases than lymph node metastases, indicating that the two sites are subject to different levels of selection. Thus, lymph node and distant metastases develop through fundamentally different evolutionary mechanisms.

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.

Multi-regional sequencing reveals clonal and polyclonal seeding from primary tumor to metastases in advanced gastric cancer

BACKGROUND

Tumor metastases to lymph nodes and distant organs are associated with worse prognosis in gastric cancer. However, little is known about the genetic profiles, subclonal architecture, and evolutional processes across primary tumors and metastases.

METHODS

We analyzed the genetic alterations of 106 multiregional samples including primary tumors, lymph node metastases, and visceral metastases from 10 patients with advanced gastric cancer. Histologically different portions were obtained by laser-capture microdissection. We reconstructed the subclonal architectures and inferred the primary to lymph or visceral metastatic seeding patterns.

RESULTS

The different histological portions in primary tumors had common mutations, suggesting common ancestral tumor origins transformed into distinct histological types. In almost all cases, TP53 mutations were identified as clonal mutations across primary tumors and metastases. Subclonal reconstruction and phylogenetic analysis showed primary tumors were classified into monoclonal or polyclonal tumors. All monoclonal primary tumors disseminated as metastases with the same tumor composition (100%, 26/26 samples). In contrast, polyclonal primary tumors mainly spread as metastases by way of polyclonal seeding (84%: 37/44 samples).

CONCLUSIONS

Clonal mutations were maintained at both the primary and metastatic sites and genetic divergence of these was low. These findings shed light on the genetic basis of primary tumor dissemination and metastatic processes in advanced gastric cancer.

Clinical Relevance and Therapeutic Application of CTCs in Advanced Breast Cancer

Precision medicine through liquid biopsy represents an emerging approach in the management of cancer. The CTC count in blood samples from patients with advanced breast cancer is a powerful prognostic factor for both progression free and overall survival. Moreover, high levels of CTCs at any time during the treatment can reliably predict progression before imaging studies and/or tumor markers. Furthermore, there are works on the molecular characterization of the CTCs and their potential ability to guide the treatment in a dynamic way. However, their role remains controversial. Detection and enumeration of CTCs is variable among different tumors and is subjected to biases related mainly to their methodology, which is not completely standardized. In addition, they must demonstrate their clinical value to guide the treatment and a translation on patient's survival.

Chromosome Instability; Implications in Cancer Development, Progression, and Clinical Outcomes

Chromosome instability (CIN) refers to an ongoing rate of chromosomal changes and is a driver of genetic, cell-to-cell heterogeneity. It is an aberrant phenotype that is intimately associated with cancer development and progression. The presence, extent, and level of CIN has tremendous implications for the clinical management and outcomes of those living with cancer. Despite its relevance in cancer, there is still extensive misuse of the term CIN, and this has adversely impacted our ability to identify and characterize the molecular determinants of CIN. Though several decades of genetic research have provided insight into CIN, the molecular determinants remain largely unknown, which severely limits its clinical potential. In this review, we provide a definition of CIN, describe the two main types, and discuss how it differs from aneuploidy. We subsequently detail its impact on cancer development and progression, and describe how it influences metastatic potential with reference to cancer prognosis and outcomes. Finally, we end with a discussion of how CIN induces genetic heterogeneity to influence the use and efficacy of several precision medicine strategies, including patient and risk stratification, as well as its impact on the acquisition of drug resistance and disease recurrence.

Power and pitfalls of computational methods for inferring clone phylogenies and mutation orders from bulk sequencing data

Tumors harbor extensive genetic heterogeneity in the form of distinct clone genotypes that arise over time and across different tissues and regions in cancer. Many computational methods produce clone phylogenies from population bulk sequencing data collected from multiple tumor samples from a patient. These clone phylogenies are used to infer mutation order and clone origins during tumor progression, rendering the selection of the appropriate clonal deconvolution method critical. Surprisingly, absolute and relative accuracies of these methods in correctly inferring clone phylogenies are yet to consistently assessed. Therefore, we evaluated the performance of seven computational methods. The accuracy of the reconstructed mutation order and inferred clone groupings varied extensively among methods. All the tested methods showed limited ability to identify ancestral clone sequences present in tumor samples correctly. The presence of copy number alterations, the occurrence of multiple seeding events among tumor sites during metastatic tumor evolution, and extensive intermixture of cancer cells among tumors hindered the detection of clones and the inference of clone phylogenies for all methods tested. Overall, CloneFinder, MACHINA, and LICHeE showed the highest overall accuracy, but none of the methods performed well for all simulated datasets. So, we present guidelines for selecting methods for data analysis.

Delineation of Tumor Migration Paths by Using a Bayesian Biogeographic Approach

Understanding tumor progression and metastatic potential are important in cancer biology. Metastasis is the migration and colonization of clones in secondary tissues. Here, we posit that clone migration events between tumors resemble the dispersal of individuals between distinct geographic regions. This similarity makes Bayesian biogeographic analysis suitable for inferring cancer cell migration paths. We evaluated the accuracy of a Bayesian biogeography method (BBM) in inferring metastatic patterns and compared it with the accuracy of a parsimony-based approach (metastatic and clonal history integrative analysis, MACHINA) that has been specifically developed to infer clone migration patterns among tumors. We used computer-simulated datasets in which simple to complex migration patterns were modeled. BBM and MACHINA were effective in reliably reconstructing simple migration patterns from primary tumors to metastases. However, both of them exhibited a limited ability to accurately infer complex migration paths that involve the migration of clones from one metastatic tumor to another and from metastasis to the primary tumor. Therefore, advanced computational methods are still needed for the biologically realistic tracing of migration paths and to assess the relative preponderance of different types of seeding and reseeding events during cancer progression in patients.

Predicting clone genotypes from tumor bulk sequencing of multiple samples

Motivation

Analyses of data generated from bulk sequencing of tumors have revealed extensive genomic heterogeneity within patients. Many computational methods have been developed to enable the inference of genotypes of tumor cell populations (clones) from bulk sequencing data. However, the relative and absolute accuracy of available computational methods in estimating clone counts and clone genotypes is not yet known.

Results

We have assessed the performance of nine methods, including eight previously-published and one new method (CloneFinder), by analyzing computer simulated datasets. CloneFinder, LICHeE, CITUP and cloneHD inferred clone genotypes with low error (<5% per clone) for a majority of datasets in which the tumor samples contained evolutionarily-related clones. Computational methods did not perform well for datasets in which tumor samples contained mixtures of clones from different clonal lineages. Generally, the number of clones was underestimated by cloneHD and overestimated by PhyloWGS, and BayClone2, Canopy and Clomial required prior information regarding the number of clones. AncesTree and Canopy did not produce results for a large number of datasets. Overall, the deconvolution of clone genotypes from single nucleotide variant (SNV) frequency differences among tumor samples remains challenging, so there is a need to develop more accurate computational methods and robust software for clone genotype inference.

Availability and implementation

CloneFinder is implemented in Python and is available from https://github.com/gstecher/CloneFinderAPI.

Supplementary information

Supplementary data are available at Bioinformatics online.

Dynamic and unpredictable changes in mutant allele fractions of BRAF and NRAS during visceral progression of cutaneous malignant melanoma

Background

Data indicate that primary cutaneous melanomas are characterized by clonal heterogeneity associated with oncogenic drivers. Less data are available on the clonal changes occurring during melanoma progression. We therefore wished to analyse these changes in skin melanomas in common sites of visceral metastases as compared to the primary tumor.

Methods

An autopsy cohort of 50 patients with BRAF- and NRAS-mutant cutaneous metastatic melanomas including 139 visceral metastases was analysed for mutant allele fractions (MAF), determined by pyrosequencing and corrected for tumor/normal ratio. MAF levels were also classified as high (> 40%), medium (15–40%) or low (< 15%).

Results

Contrary to NRAS mutant cases, in BRAF-mutant melanomas MAFs were found to be significantly increased in visceral metastases compared to the primary due to the significantly higher levels in lung-, adrenal gland-, intestinal- and kidney metastases. The incidence of the three MAF variants in BRAF-mutant primaries was similar, whereas the high MAF cases were found to be increased in metastases. On the other hand, medium MAF levels were more common in case of NRAS-mutant tumors. Only 31.3% of BRAF mutant- and 50% of NRAS mutant cases maintained the MAF profile of the primary in metastasis. In the majority of multiple metastatic tumors, (BRAF:71.8%, NRAS:75%) metastases were relatively homogeneous regarding MAF. However, in 6/32(18.7%) of BRAF mutant cases low MAF primaries switched to high MAF in metastases. In heterogeneous BRAF mutant metastatic cases low to high or high to low MAF conversions occurred in a further 4/32(12.5%) cases in individual metastases as compared to the primary tumors. At lower frequency, in NRAS mutant tumor such changes also observed (2/12,16.7%).

Conclusion

We provided evidence for the selection of BRAF-mutant melanoma cells during metastatic progression to the lung, intestine, adrenal gland and kidney. Our findings suggest that in visceral metastases of malignant melanoma BRAF- or NRAS-MAFs are rather heterogeneous and cannot be predicted from data of the primary tumor. These data may have clinical significance when using targeted therapies.

Electronic supplementary material

The online version of this article (10.1186/s12885-019-5990-9) contains supplementary material, which is available to authorized users.

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.

Frequent clonal relations between metastases and non-index prostate cancer lesions

Primary prostate cancer lesions are clonally heterogeneous and often arise independently. In contrast, metastases were reported to share a monoclonal background. Because prostate cancer mortality is the consequence of distant metastases, prevention of metastatic outgrowth by primary tumor ablation is the main focus of treatment for localized disease. Focal therapy is targeted ablation of the primary index lesion, but it is unclear whether remaining primary lesions metastasize at a later stage. In this study, we compared copy number aberration profiles of primary prostate cancer lesions with matching pelvic lymph node metastases of 30 patients to establish clonality between a lymph node metastasis and multiple primary lesions within the same patient. Interestingly, in 23.3% of the cases, the regional metastasis was not clonally linked to the index primary lesion. These findings suggest that focal ablation of only the index lesion is potentially an undertreatment of a significant proportion of prostate cancer patients.

Harnessing Human Microphysiology Systems as Key Experimental Models for Quantitative Systems Pharmacology

Two technologies that have emerged in the last decade offer a new paradigm for modern pharmacology, as well as drug discovery and development. Quantitative systems pharmacology (QSP) is a complementary approach to traditional, target-centric pharmacology and drug discovery and is based on an iterative application of computational and systems biology methods with multiscale experimental methods, both of which include models of ADME-Tox and disease. QSP has emerged as a new approach due to the low efficiency of success in developing therapeutics based on the existing target-centric paradigm. Likewise, human microphysiology systems (MPS) are experimental models complementary to existing animal models and are based on the use of human primary cells, adult stem cells, and/or induced pluripotent stem cells (iPSCs) to mimic human tissues and organ functions/structures involved in disease and ADME-Tox. Human MPS experimental models have been developed to address the relatively low concordance of human disease and ADME-Tox with engineered, experimental animal models of disease. The integration of the QSP paradigm with the use of human MPS has the potential to enhance the process of drug discovery and development.

Addition of radiotherapy to the primary tumour in oligometastatic NSCLC: A systematic review and meta-analysis

Oligometastatic non-small cell lung cancer (NSCLC) has a discrete number of distant lesions (<5) that can be amenable to radical treatment. The treatment of the primary lung tumour in such stage IV cases is still debated. We conducted a systematic review and meta-analysis to evaluate the outcome of these patients and the added benefit in terms of overall survival (OS) and progression-free survival (PFS) when radical treatment of the primary tumour with radiotherapy (RT) was delivered. PubMed, EMBASE and Cochrane Library were systematically searched to identify relevant studies published up to July 2018. Prospective trials and retrospective series comparing RT vs no RT to the primary NSCLC in the presence of oligometastases were included. Hazard ratios (HRs) for OS and PFS were aggregated according to a fixed or random effect model. Twenty-one studies for a total of 924 synchronous oligometastatic NSCLC were analysed. Median OS and PFS were 20.4 and 12 months. Pooled 1-2-3 and 5-year OS were 70.3%, 43.5%, 29.3% and 20.2% respectively. Overall survival was improved with the addition of thoracic RT (HR = 0.44, 95%CI 0.32-0.6; P < 0.001). Similarly, RT added to the primary tumour increased PFS (HR = 0.42, 95%CI 0.33-0.55; P < 0.001). The only variable associated with the median OS was the year of publication with most recent series associated with a better outcome. In patients with oligometastatic NSCLC and disease controlled with ablative therapy of distant metastases, a consolidation with radical RT to the primary tumour is associated with better survival and could be considered as a treatment modality in selected cases.

Somatic Trp53 mutations differentially drive breast cancer and evolution of metastases

TP53 mutations are the most frequent genetic alterations in breast cancer and are associated with more aggressive disease and worse overall survival. We have created two conditional mutant Trp53 alleles in the mouse that allow expression of Trp53R172H or Trp53R245W missense mutations in single cells surrounded by a normal stroma and immune system. Mice with Trp53 mutations in a few breast epithelial cells develop breast cancers with high similarity to human breast cancer including triple negative. p53R245W tumors are the most aggressive and exhibit metastases to lung and liver. Development of p53R172H breast tumors with some metastases requires additional hits. Sequencing of primary tumors and metastases shows p53R245W drives a parallel evolutionary pattern of metastases. These in vivo models most closely simulate the genesis of human breast cancer and will thus be invaluable in testing novel therapeutic options.

Mutations in TP53 gene are very common in cancer development. Here the authors take advantage of murine models to show that somatic Trp53 mutations differentially drive breast cancer and evolution of metastases.

Exit Stage Left: A Tumor Cell's Journey from Lymph Node to Beyond

Even though we have known for over 250 years that cancers spread to regional lymph nodes (LNs) and distant organs, the fundamental question of which anatomical routes are taken by tumor cells has remained a mystery. Two recently published papers in Science, by Pereira et al. and Brown et al., directly address this important issue in tumor biology by assessing the capacity of tumor cells in LNs to spread to distant sites.

Inferring parsimonious migration histories for metastatic cancers

Metastasis is the migration of cancerous cells from a primary tumor to other anatomical sites. Although metastasis was long thought to result from monoclonal seeding, or single cellular migrations, recent phylogenetic analyses of metastatic cancers have reported complex patterns of cellular migrations between sites, including polyclonal migrations and reseeding. However, accurate determination of migration patterns from somatic mutation data is complicated by intratumor heterogeneity and discordance between clonal lineage and cellular migration. We introduce MACHINA, a multi-objective optimization algorithm that jointly infers clonal lineages and parsimonious migration histories of metastatic cancers from DNA sequencing data. MACHINA analysis of data from multiple cancers shows that migration patterns are often not uniquely determined from sequencing data alone and that complicated migration patterns among primary tumors and metastases may be less prevalent than previously reported. MACHINA's rigorous analysis of migration histories will aid in studies of the drivers of metastasis.

The evolving role of lymphatics in cancer metastasis

While the link between the lymphatic system and the metastatic spread of cancer is centuries old, understanding of the underlying mechanisms is still evolving. Lymphatic vessels provide a route for tumour cells to reach regional lymph nodes (LNs), which is prognostic of distant organ metastasis and poor survival. However, genomic analyses of metastatic cancer now reveal complex patterns of dissemination. The lymphatic endothelial cells lining lymphatics respond to molecular cues from the tumour microenvironment, mediating growth and remodelling of lymphatic vessels at the primary tumour, draining LNs and distant premetastatic niches. Recent studies emphasise that this not only supports metastasis but also influences antitumour immunity. Understanding the complex interactions between tumour cells, the immune system and lymphatics will be essential to inform developing therapeutic and prognostic approaches to cancer.

How to study and overcome tumor heterogeneity with circulating biomarkers: The breast cancer case

Breast cancer ranks first among female cancer-related deaths in Western countries. As the primary tumor can often be controlled by surgical resection, the survival of women with breast cancer is closely linked to the incidence of distant metastases. Molecular screening by next generation sequencing highlighted the spatial and temporal heterogeneity of solid tumors as well as the clonal evolution of cancer cells during progression and under treatment pressure. Such findings question whether an optimal assessment of disease progression and a screening for druggable mutations should be based on molecular features of primary or recurrent/metastatic lesions and therefore represent a crucial element for failure or success of personalized medicine. In fact, new targeted therapies may induce only short-term benefit annulled by the emergence of resistant clones with new driver mutations which would need to be rapidly and reliably identified. Serial tissue sampling is therefore essential but, unfortunately, also represents a problem since biopsies from solid lesions, which are invasive and potentially painful and risky, cannot be easily repeatedly sampled, are inaccessible or may not fully reflect tumor heterogeneity. The need to early detect and strike this "moving target" is now directing the scientific community toward liquid biopsy-based biomarkers, which include circulating tumor cells (CTC) and cell-free circulating tumor DNA (ctDNA), can be repeatedly assessed through non-invasive and easy-to-perform procedures and may act as reliable read-outs of functional and molecular features of recurrent/metastatic lesions. In this review we summarize the outcome of CTCs and ctDNA in breast cancer, with special reference on their role on unveiling and overcoming tumor heterogeneity, on their potential relevance for tumor surveillance and monitoring, and for the selection of therapeutic options. Finally, we propose integration between blood-based molecular and clinical approaches for monitoring disease progression according to the specific pattern of recurrence of the most aggressive breast cancer molecular subtypes.