Multiomics in primary and metastatic breast tumors from the AURORA US network finds microenvironment and epigenetic drivers of metastasis

From virtual patients to digital twins in immuno-oncology: lessons learned from mechanistic quantitative systems pharmacology modeling

Virtual patients and digital patients/twins are two similar concepts gaining increasing attention in health care with goals to accelerate drug development and improve patients' survival, but with their own limitations. Although methods have been proposed to generate virtual patient populations using mechanistic models, there are limited number of applications in immuno-oncology research. Furthermore, due to the stricter requirements of digital twins, they are often generated in a study-specific manner with models customized to particular clinical settings (e.g., treatment, cancer, and data types). Here, we discuss the challenges for virtual patient generation in immuno-oncology with our most recent experiences, initiatives to develop digital twins, and how research on these two concepts can inform each other.

Loss of tumor suppressors promotes inflammatory tumor microenvironment and enhances LAG3+T cell mediated immune suppression

Low response rate, treatment relapse, and resistance remain key challenges for cancer treatment with immune checkpoint blockade (ICB). Here we report that loss of specific tumor suppressors (TS) induces an inflammatory response and promotes an immune suppressive tumor microenvironment. Importantly, low expression of these TSs is associated with a higher expression of immune checkpoint inhibitory mediators. Here we identify, by using in vivo CRISPR/Cas9 based loss-of-function screening, that NF1, TSC1, and TGF-β RII as TSs regulating immune composition. Loss of each of these three TSs leads to alterations in chromatin accessibility and enhances IL6-JAK3-STAT3/6 inflammatory pathways. This results in an immune suppressive landscape, characterized by increased numbers of LAG3+ CD8 and CD4 T cells. ICB targeting LAG3 and PD-L1 simultaneously inhibits metastatic progression in preclinical triple negative breast cancer (TNBC) mouse models of NF1-, TSC1- or TGF-β RII- deficient tumors. Our study thus reveals a role of TSs in regulating metastasis via non-cell-autonomous modulation of the immune compartment and provides proof-of-principle for ICB targeting LAG3 for patients with NF1-, TSC1- or TGF-β RII-inactivated cancers.

Towards targeting the breast cancer immune microenvironment

The tumour immune microenvironment is shaped by the crosstalk between cancer cells, immune cells, fibroblasts, endothelial cells and other stromal components. Although the immune tumour microenvironment (TME) serves as a source of therapeutic targets, it is also considered a friend or foe to tumour-directed therapies. This is readily illustrated by the importance of T cells in triple-negative breast cancer (TNBC), culminating in the advent of immune checkpoint therapy in combination with cytotoxic chemotherapy as standard of care for both early and advanced-stage TNBC, as well as recent promising signs of efficacy in a subset of hormone receptor-positive disease. In this Review, we discuss the various components of the immune TME in breast cancer and therapies that target or impact the immune TME, as well as the complexity of host physiology.

An essential gene signature of breast cancer metastasis reveals targetable pathways

BACKGROUND

The differential gene expression profile of metastatic versus primary breast tumors represents an avenue for discovering new or underappreciated pathways underscoring processes of metastasis. However, as tumor biopsy samples are a mixture of cancer and non-cancer cells, most differentially expressed genes in metastases would represent confounders involving sample biopsy site rather than cancer cell biology.

METHODS

By paired analysis, we defined a top set of differentially expressed genes in breast cancer metastasis versus primary tumors using an RNA-sequencing dataset of 152 patients from The Breast International Group Aiming to Understand the Molecular Aberrations dataset (BIG-AURORA). To filter the genes higher in metastasis for genes essential for breast cancer proliferation, we incorporated CRISPR-based data from breast cancer cell lines.

RESULTS

A significant fraction of genes with higher expression in metastasis versus paired primary were essential by CRISPR. These 264 genes represented an essential signature of breast cancer metastasis. In contrast, nonessential metastasis genes largely involved tumor biopsy site. The essential signature predicted breast cancer patient outcome based on primary tumor expression patterns. Pathways underlying the essential signature included proteasome degradation, the electron transport chain, oxidative phosphorylation, and cancer metabolic reprogramming. Transcription factors MYC, MAX, HDAC3, and HCFC1 each bound significant fractions of essential genes.

CONCLUSIONS

Associations involving the essential gene signature of breast cancer metastasis indicate true biological changes intrinsic to cancer cells, with important implications for applying existing therapies or developing alternate therapeutic approaches.

Epigenetic regulation of breast cancer metastasis

Breast cancer is the most frequently diagnosed malignancy and the second leading cause of cancer-related mortality among women worldwide. Recurrent metastasis is associated with poor patient outcomes and poses a significant challenge in breast cancer therapies. Cancer cells adapting to a new tissue microenvironment is the key event in distant metastasis development, where the disseminating tumor cells are likely to acquire genetic and epigenetic alterations during the process of metastatic colonization. Despite several decades of research in this field, the exact mechanisms governing metastasis are not fully understood. However, emerging body of evidence indicates that in addition to genetic changes, epigenetic reprogramming of cancer cells and the metastatic niche are paramount toward successful metastasis. Here, we review and discuss the latest knowledge about the salient attributes of metastasis and epigenetic regulation in breast cancer and crucial research domains that need further investigation.

From pre-clinical to translational brain metastasis research: current challenges and emerging opportunities

Brain metastasis, characterized by poor clinical outcomes, is a devastating disease. Despite significant mechanistic and therapeutic advances in recent years, pivotal improvements in clinical interventions have remained elusive. The heterogeneous nature of the primary tumor of origin, complications in drug delivery across the blood-brain barrier, and the distinct microenvironment collectively pose formidable clinical challenges in developing new treatments for patients with brain metastasis. Although current preclinical models have deepened our basic understanding of the disease, much of the existing research on brain metastasis has employed a reductionist approach. This approach, which often relies on either in vitro systems or in vivo injection models in young and treatment-naive mouse models, does not give sufficient consideration to the clinical context. Given the translational importance of brain metastasis research, we advocate for the design of preclinical experimental models that take into account these unique clinical challenges and align more closely with current clinical practices. We anticipate that aligning and simulating real-world patient conditions will facilitate the development of more translatable treatment regimens. This brief review outlines the most pressing clinical challenges, the current state of research in addressing them, and offers perspectives on innovative metastasis models and tools aimed at identifying novel strategies for more effective management of clinical brain metastasis.

Liver tropism of ER mutant breast cancer is characterized by unique molecular changes and immune infiltration

PURPOSE

Hotspot estrogen receptor alpha (ER/ESR1) mutations are recognized as the driver for both endocrine resistance and metastasis in advanced ER-positive (ER+) breast cancer, but their contributions to metastatic organ tropism remain insufficiently understood. In this study, we aim to comprehensively profile the organotropic metastatic pattern for ESR1 mutant breast cancer.

METHODS

The organ-specific metastatic pattern of ESR1 mutant breast cancer was delineated using multi-omics data from multiple publicly available cohorts of ER+ metastatic breast cancer patients. Gene mutation/copy number variation (CNV) and differential gene expression analyses were performed to identify the genomic and transcriptomic alterations uniquely associated with ESR1 mutant liver metastasis. Upstream regulator, downstream pathway, and immune infiltration analysis were conducted for subsequent mechanistic investigations.

RESULTS

ESR1 mutation-driven liver tropism was revealed by significant differences, encompassing a higher prevalence of liver metastasis in patients with ESR1 mutant breast cancer and an enrichment of mutations in liver metastatic samples. The significant enrichment of AGO2 copy number amplifications (CNAs) and multiple gene expression changes were revealed uniquely in ESR1 mutant liver metastasis. We also unveiled alterations in downstream signaling pathways and immune infiltration, particularly an enrichment of neutrophils, suggesting potential therapeutic vulnerabilities.

CONCLUSION

Our data provide a comprehensive characterization of the behaviors and mechanisms of ESR1 mutant liver metastasis, paving the way for the development of personalized therapy to target liver metastasis for patients with ESR1 mutant breast cancer.

Construction of a prognostic score model for breast cancer based on multi-omics analysis of study on bone metastasis

Background

Breast cancer (BRCA) is the most common type of cancer and the second leading cause of cancer-related death in women all over the world. Metastasis to bone is an indicator of poor prognosis in BRCA patients. This study aimed to develop a prognostic score model for predicting bone metastasis in patients with BRCA.

Methods

BRCA-related RNA sequencing datasets and corresponding clinical information were downloaded from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). Differentially expressed genes (DEGs) were screened using Limma package of R software. A risk score based predictive model was constructed based on the key genes identified through univariate Cox regression and the least absolute shrinkage and selection operator (LASSO) Cox regression. The gene expression profiles in BRCA patients were analyzed by gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA). Random survival forest (RSF) analysis of BRCA patients with bone metastasis was conducted to identify the key DEGs.

Results

Based on DEG analysis, a total of 677 genes were identified as genes related to bone metastasis in BRCA. By univariate Cox regression and LASSO regression, 28 DEGs were identified as signature genes to develop the prognostic model. A risk score for each patient was created by incorporating the expression values of each specific gene and weighting them with the corresponding estimated regression coefficients. Patients were divided into a low-risk and a high-risk group based on the median risk score. Overall survival (OS) was significantly lower in the high-risk group. The receiver operating characteristic (ROC) curve and multi-omics analysis indicated that the model had high training/testing accuracy and a good clinical predictive value. We used extra data from GEO database to verify the robustness of the prognostic model, and the lower OS in high-risk group and area under the curve (AUC) value indicated the model had strong predictive efficacy for prognosis of BRCA.

Conclusions

A prognostic prediction model was constructed based on 28 key DEGs identified through multi-omics analysis of studies on bone metastasis. The model may provide a promising method for distinguishing the high-risk BRCA patients and help on decision making in addition to prognosis prediction for BRCA patients.

Heterogeneity of primary and metastatic CAFs: From differential treatment outcomes to treatment opportunities (Review)

Compared with primary tumor sites, metastatic sites appear more resistant to treatments and respond differently to the treatment regimen. It may be due to the heterogeneity in the microenvironment between metastatic sites and primary tumors. Cancer‑associated fibroblasts (CAFs) are widely present in the tumor stroma as key components of the tumor microenvironment. Primary tumor CAFs (pCAFs) and metastatic CAFs (mCAFs) are heterogeneous in terms of source, activation mode, markers and functional phenotypes. They can shape the tumor microenvironment according to organ, showing heterogeneity between primary tumors and metastases, which may affect the sensitivity of these sites to treatment. It was hypothesized that understanding the heterogeneity between pCAFs and mCAFs can provide a glimpse into the difference in treatment outcomes, providing new ideas for improving the rate of metastasis control in various cancers.

Rapid autopsies to enhance metastatic research: the UPTIDER post-mortem tissue donation program

Research on metastatic cancer has been hampered by limited sample availability. Here we present the breast cancer post-mortem tissue donation program UPTIDER and show how it enabled sampling of a median of 31 (range: 5-90) metastases and 5-8 liquids per patient from its first 20 patients. In a dedicated experiment, we show the mild impact of increasing time after death on RNA quality, transcriptional profiles and immunohistochemical staining in tumor tissue samples. We show that this impact can be counteracted by organ cooling. We successfully generated ex vivo models from tissue and liquid biopsies from distinct histological subtypes of breast cancer. We anticipate these and future findings of UPTIDER to elucidate mechanisms of disease progression and treatment resistance and to provide tools for the exploration of precision medicine strategies in the metastatic setting.

Perspectives for the clinical application of ctDNA analysis to breast cancer drug therapy

Circulating tumor DNA (ctDNA) consists of DNA fragments released from cancer cells into the blood circulation with quick clearance. Analysis of ctDNA can enable real-time assessment of the presence of cancer cells and their genomic characteristics. Therefore, ctDNA is expected to be one of the most useful biomarkers for cancer. In recent years, several ultra-sensitive assays for ctDNA analysis have been developed, and many clinical trials are using these assays to investigate the efficacy of ctDNA-based therapeutic strategies. In the perioperative phase, real-time identification of minimal residual disease at the molecular level with ctDNA analysis can help evaluate the risk of recurrence to inform escalation or de-escalation of perioperative drug therapy. Many trials have examined whether therapeutic strategies using ctDNA analysis to predict treatment efficacy or resistance to molecular targeted agents can improve prognosis in metastatic breast cancer. In this review, we discuss the most recent ctDNA assays, the significance of introducing ctDNA assays to clinical practice, and the research on their application in perioperative and metastatic phases.

Natural History of Germline BRCA1 Mutated and BRCA Wild-type Triple-negative Breast Cancer

We report a deep next-generation sequencing analysis of 13 sequentially obtained tumor samples, eight sequentially obtained circulating tumor DNA (ctDNA) samples and three germline DNA samples over the life history of 3 patients with triple-negative breast cancer (TNBC), 2 of whom had germline pathogenic BRCA1 mutation, to unravel tumor evolution. Tumor tissue from all timepoints and germline DNA was subjected to whole-exome sequencing (WES), custom amplicon deep sequencing (30,000X) of a WES-derived somatic mutation panel, and SNP arrays for copy-number variation (CNV), while whole transcriptome sequencing (RNA-seq) was performed only on somatic tumor.There was enrichment of homologous recombination deficiency signature in all tumors and widespread CNV, which remained largely stable over time. Somatic tumor mutation numbers varied between patients and within each patient (range: 70-216, one outlier). There was minimal mutational overlap between patients with TP53 being the sole commonly mutated gene, but there was substantial overlap in sequential samples in each patient. Each patient's tumor contained a founding ("stem") clone at diagnosis, which persisted over time, from which all other clones ("subclone") were derived ("branching evolution"), which contained mutations in well-characterized cancer-related genes like PDGFRB, ARID2, TP53 (Patient_02), TP53, BRAF, BRIP1, CSF3R (Patient_04), and TP53, APC, EZH2 (Patient_07). Including stem and subclones, tumors from all patients were polyclonal at diagnosis and during disease progression. ctDNA recapitulated most tissue-derived stem clonal and subclonal mutations while detecting some additional subclonal mutations. RNA-seq revealed a stable basal-like pattern, with most highly expressed variants belonging to stem clone.

SIGNIFICANCE

In germline BRCA1 mutated and BRCA wild-type patients, TNBC shows a branching evolutionary pattern of mutations with a single founding clone, are polyclonal throughout their disease course, and have widespread copy-number aberrations. This evolutionary pattern may be associated with treatment resistance or sensitivity and could be therapeutically exploited.

Discovery of novel DNA methylation biomarker panels for the diagnosis and differentiation between common adenocarcinomas and their liver metastases

Differentiation between adenocarcinomas is sometimes challenging. The promising avenue for discovering new biomarkers lies in bioinformatics using DNA methylation analysis. Utilizing a 2853-sample identification dataset and a 782-sample independent verification dataset, we have identified diagnostic DNA methylation biomarkers that are hypermethylated in cancer and differentiate between breast invasive carcinoma, cholangiocarcinoma, colorectal cancer, hepatocellular carcinoma, lung adenocarcinoma, pancreatic adenocarcinoma and stomach adenocarcinoma. The best panels for cancer type exhibit sensitivity of 77.8-95.9%, a specificity of 92.7-97.5% for tumors, a specificity of 91.5-97.7% for tumors and normal tissues and a diagnostic accuracy of 85.3-96.4%. We have shown that the results can be extended from the primary cancers to their liver metastases, as the best panels diagnose and differentiate between pancreatic adenocarcinoma liver metastases and breast invasive carcinoma liver metastases with a sensitivity and specificity of 83.3-100% and a diagnostic accuracy of 86.8-91.9%. Moreover, the panels could detect hypermethylation of selected regions in the cell-free DNA of patients with liver metastases. At the same time, these were unmethylated in the cell-free DNA of healthy donors, confirming their applicability for liquid biopsies.

Rare subclonal sequencing of breast cancers indicates putative metastatic driver mutations are predominately acquired after dissemination

BACKGROUND

Evolutionary models of breast cancer progression differ on the extent to which metastatic potential is pre-encoded within primary tumors. Although metastatic recurrences often harbor putative driver mutations that are not detected in their antecedent primary tumor using standard sequencing technologies, whether these mutations were acquired before or after dissemination remains unclear.

METHODS

To ascertain whether putative metastatic driver mutations initially deemed specific to the metastasis by whole exome sequencing were, in actuality, present within rare ancestral subclones of the primary tumors from which they arose, we employed error-controlled ultra-deep sequencing (UDS-UMI) coupled with FFPE artifact mitigation by uracil-DNA glycosylase (UDG) to assess the presence of 132 "metastasis-specific" mutations within antecedent primary tumors from 21 patients. Maximum mutation detection sensitivity was ~1% of primary tumor cells. A conceptual framework was developed to estimate relative likelihoods of alternative models of mutation acquisition.

RESULTS

The ancestral primary tumor subclone responsible for seeding the metastasis was identified in 29% of patients, implicating several putative drivers in metastatic seeding including LRP5 A65V and PEAK1 K140Q. Despite this, 93% of metastasis-specific mutations in putative metastatic driver genes remained undetected within primary tumors, as did 96% of metastasis-specific mutations in known breast cancer drivers, including ERRB2 V777L, ESR1 D538G, and AKT1 D323H. Strikingly, even in those cases in which the rare ancestral subclone was identified, 87% of metastasis-specific putative driver mutations remained undetected. Modeling indicated that the sequential acquisition of multiple metastasis-specific driver or passenger mutations within the same rare subclonal lineage of the primary tumor was highly improbable.

CONCLUSIONS

Our results strongly suggest that metastatic driver mutations are sequentially acquired and selected within the same clonal lineage both before, but more commonly after, dissemination from the primary tumor, and that these mutations are biologically consequential. Despite inherent limitations in sampling archival primary tumors, our findings indicate that tumor cells in most patients continue to undergo clinically relevant genomic evolution after their dissemination from the primary tumor. This provides further evidence that metastatic recurrence is a multi-step, mutation-driven process that extends beyond primary tumor dissemination and underscores the importance of longitudinal tumor assessment to help guide clinical decisions.

High B7-H3 expression with low PD-L1 expression identifies armored-cold tumors in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is generally regarded as the most aggressive subtype among breast cancers, but exhibits higher chemotherapeutic and immunotherapeutic responses due to its unique immunogenicity. Thus, appropriate discrimination of subtypes is critical for guiding therapeutic options in clinical practice. In this research, using multiple in-house and public cohorts, we investigated the expression features and immuno-correlations of B7-H3 in breast cancer and checked the anti-tumor effect of the B7-H3 monoclonal antibody in a mouse model. We also developed a novel classifier combining B7-H3 and PD-L1 expression in TNBC. B7-H3 was revealed to be related to immuno-cold features and accumulated collagen in TNBC. In addition, targeting B7-H3 using the monoclonal antibody significantly suppressed mouse TNBC growth, reversed the armored-cold phenotype, and also boosted anti-PD-1 immunotherapy. In addition, patients with B7-H3 high and PD-L1 low expression showed the lowest anti-tumor immune infiltration, the highest collagen level, and the lowest therapeutic responses to multiple therapies, which mostly belong to armored-cold tumors. Overall, this research provides a novel subtyping strategy based on the combination of B7-H3/PD-L1 expression, which leads to a novel approach for the management of TNBC.

Epigenetic modulation of antitumor immunity and immunotherapy response in breast cancer: biological mechanisms and clinical implications

Breast cancer (BC) is the most common non-skin cancer and the second leading cause of cancer death in American women. The initiation and progression of BC can proceed through the accumulation of genetic and epigenetic changes that allow transformed cells to escape the normal cell cycle checkpoint control. Unlike nucleotide mutations, epigenetic changes such as DNA methylation, histone posttranslational modifications (PTMs), nucleosome remodeling and non-coding RNAs are generally reversible and therefore potentially responsive to pharmacological intervention. Epigenetic dysregulations are critical mechanisms for impaired antitumor immunity, evasion of immune surveillance, and resistance to immunotherapy. Compared to highly immunogenic tumor types, such as melanoma or lung cancer, breast cancer has been viewed as an immunologically quiescent tumor which displays a relatively low population of tumor-infiltrating lymphocytes (TIL), low tumor mutational burden (TMB) and modest response rates to immune checkpoint inhibitors (ICI). Emerging evidence suggests that agents targeting aberrant epigenetic modifiers may augment host antitumor immunity in BC via several interrelated mechanisms such as enhancing tumor antigen presentation, activation of cytotoxic T cells, inhibition of immunosuppressive cells, boosting response to ICI, and induction of immunogenic cell death (ICD). These discoveries have established a highly promising basis for using combinatorial approaches of epigenetic drugs with immunotherapy as an innovative paradigm to improve outcomes of BC patients. In this review, we summarize the current understanding of how epigenetic processes regulate immune cell function and antitumor immunogenicity in the context of the breast tumor microenvironment. Moreover, we discuss the therapeutic potential and latest clinical trials of the combination of immune checkpoint blockers with epigenetic agents in breast cancer.

Multiomics insights on the onset, progression, and metastatic evolution of breast cancer

Breast cancer is the most common malignant neoplasm in women. Despite progress to date, 700,000 women worldwide died of this disease in 2020. Apparently, the prognostic markers currently used in the clinic are not sufficient to determine the most appropriate treatment. For this reason, great efforts have been made in recent years to identify new molecular biomarkers that will allow more precise and personalized therapeutic decisions in both primary and recurrent breast cancers. These molecular biomarkers include genetic and post-transcriptional alterations, changes in protein expression, as well as metabolic, immunological or microbial changes identified by multiple omics technologies (e.g., genomics, epigenomics, transcriptomics, proteomics, glycomics, metabolomics, lipidomics, immunomics and microbiomics). This review summarizes studies based on omics analysis that have identified new biomarkers for diagnosis, patient stratification, differentiation between stages of tumor development (initiation, progression, and metastasis/recurrence), and their relevance for treatment selection. Furthermore, this review highlights the importance of clinical trials based on multiomics studies and the need to advance in this direction in order to establish personalized therapies and prolong disease-free survival of these patients in the future.

Harnessing immunotherapy for brain metastases: insights into tumor-brain microenvironment interactions and emerging treatment modalities

Brain metastases signify a deleterious milestone in the progression of several advanced cancers, predominantly originating from lung, breast and melanoma malignancies, with a median survival timeframe nearing six months. Existing therapeutic regimens yield suboptimal outcomes; however, burgeoning insights into the tumor microenvironment, particularly the immunosuppressive milieu engendered by tumor-brain interplay, posit immunotherapy as a promising avenue for ameliorating brain metastases. In this review, we meticulously delineate the research advancements concerning the microenvironment of brain metastases, striving to elucidate the panorama of their onset and evolution. We encapsulate three emergent immunotherapeutic strategies, namely immune checkpoint inhibition, chimeric antigen receptor (CAR) T cell transplantation and glial cell-targeted immunoenhancement. We underscore the imperative of aligning immunotherapy development with in-depth understanding of the tumor microenvironment and engendering innovative delivery platforms. Moreover, the integration with established or avant-garde physical methodologies and localized applications warrants consideration in the prevailing therapeutic schema.

Immunotherapy in patients with brain metastasis: advances and challenges for the treatment and the application of circulating biomarkers

The central nervous system (CNS) is one of the most frequent metastatic sites of various cancers, including lung cancer, breast cancer and melanoma. The development of brain metastases requires a specific therapeutic approach and is associated with high mortality and morbidity in cancer patients. Advances in precision medicine and the introduction in recent years of new drugs, such as immunotherapy, have made it possible to improve the prognosis of these patients by improving survival and quality of life. New diagnostic techniques such as liquid biopsy allow real-time monitoring of tumor evolution, providing molecular information on prognostic and predictive biomarkers of response to treatment in blood or other fluids. In this review, we perform an exhaustive update of the clinical trials that demonstrate the utility of immunotherapy in patients with brain metastases and the potential of circulating biomarkers to improving the results of efficacy and toxicity in this subgroup of patients.

Associations amongst genes, molecules, cells, and organs in breast cancer metastasis

This paper is a cross fertilization of ideas about the importance of molecular aspects of breast cancer metastasis by basic scientists, a pathologist, and clinical oncologists at the Henry Ford Health symposium. We address four major topics: (i) the complex roles of lymphatic endothelial cells and the molecules that stimulate them to enhance lymph node and systemic metastasis and influence the anti-tumor immunity that might inhibit metastasis; (ii) the interaction of molecules and cells when breast cancer spreads to bone, and how bone metastases may themselves spread to internal viscera; (iii) how molecular expression and morphologic subtypes of breast cancer assist clinicians in determining which patients to treat with more or less aggressive therapies; (iv) how the outcomes of patients with oligometastases in breast cancer are different from those with multiple metastases and how that could justify the aggressive treatment of these patients with the hope of cure.

Epigenetic markers and therapeutic targets for metastasis

The last few years have seen an increasing number of discoveries which collectively demonstrate that histone and DNA modifying enzyme modulate different stages of metastasis. Moreover, epigenomic alterations can now be measured at multiple scales of analysis and are detectable in human tumors or liquid biopsies. Malignant cell clones with a proclivity for relapse in certain organs may arise in the primary tumor as a consequence of epigenomic alterations which cause a loss in lineage integrity. These alterations may occur due to genetic aberrations acquired during tumor progression or concomitant to therapeutic response. Moreover, evolution of the stroma can also alter the epigenome of cancer cells. In this review, we highlight current knowledge with a particular emphasis on leveraging chromatin and DNA modifying mechanisms as biomarkers of disseminated disease and as therapeutic targets to treat metastatic cancers.

Regulation of dormancy during tumor dissemination: the role of the ECM

The study of the metastatic cascade has revealed the complexity of the process and the multiple cellular states that disseminated cancer cells must go through. The tumor microenvironment and in particular the extracellular matrix (ECM) plays an important role in regulating the transition from invasion, dormancy to ultimately proliferation during the metastatic cascade. The time delay from primary tumor detection to metastatic growth is regulated by a molecular program that maintains disseminated tumor cells in a non-proliferative, quiescence state known as tumor cell dormancy. Identifying dormant cells and their niches in vivo and how they transition to the proliferative state is an active area of investigation, and novel approaches have been developed to track dormant cells during dissemination. In this review, we highlight the latest research on the invasive nature of disseminated tumor cells and their link to dormancy programs. We also discuss the role of the ECM in sustaining dormant niches at distant sites.