Temporally sequenced anticancer drugs overcome adaptive resistance by targeting a vulnerable chemotherapy-induced phenotypic transition

The role of memory in non-genetic inheritance and its impact on cancer treatment resistance

Intra-tumour heterogeneity is a leading cause of treatment failure and disease progression in cancer. While genetic mutations have long been accepted as a primary mechanism of generating this heterogeneity, the role of phenotypic plasticity is becoming increasingly apparent as a driver of intra-tumour heterogeneity. Consequently, understanding the role of this plasticity in treatment resistance and failure is a key component of improving cancer therapy. We develop a mathematical model of stochastic phenotype switching that tracks the evolution of drug-sensitive and drug-tolerant subpopulations to clarify the role of phenotype switching on population growth rates and tumour persistence. By including cytotoxic therapy in the model, we show that, depending on the strategy of the drug-tolerant subpopulation, stochastic phenotype switching can lead to either transient or permanent drug resistance. We study the role of phenotypic heterogeneity in a drug-resistant, genetically homogeneous population of non-small cell lung cancer cells to derive a rational treatment schedule that drives population extinction and avoids competitive release of the drug-tolerant sub-population. This model-informed therapeutic schedule results in increased treatment efficacy when compared against periodic therapy, and, most importantly, sustained tumour decay without the development of resistance.

A mechanistic model captures the emergence and implications of non-genetic heterogeneity and reversible drug resistance in ER+ breast cancer cells

Resistance to anti-estrogen therapy is an unsolved clinical challenge in successfully treating ER+ breast cancer patients. Recent studies have demonstrated the role of non-genetic (i.e. phenotypic) adaptations in tolerating drug treatments; however, the mechanisms and dynamics of such non-genetic adaptation remain elusive. Here, we investigate coupled dynamics of epithelial–mesenchymal transition (EMT) in breast cancer cells and emergence of reversible drug resistance. Our mechanism-based model for underlying regulatory network reveals that these two axes can drive one another, thus enabling non-genetic heterogeneity in a cell population by allowing for six co-existing phenotypes: epithelial-sensitive, mesenchymal-resistant, hybrid E/M-sensitive, hybrid E/M-resistant, mesenchymal-sensitive and epithelial-resistant, with the first two ones being most dominant. Next, in a population dynamics framework, we exemplify the implications of phenotypic plasticity (both drug-induced and intrinsic stochastic switching) and/or non-genetic heterogeneity in promoting population survival in a mixture of sensitive and resistant cells, even in the absence of any cell–cell cooperation. Finally, we propose the potential therapeutic use of mesenchymal–epithelial transition inducers besides canonical anti-estrogen therapy to limit the emergence of reversible drug resistance. Our results offer mechanistic insights into empirical observations on EMT and drug resistance and illustrate how such dynamical insights can be exploited for better therapeutic designs.

Vimentin Promotes the Aggressiveness of Triple Negative Breast Cancer Cells Surviving Chemotherapeutic Treatment

Tremendous data have been accumulated in the effort to understand chemoresistance of triple negative breast cancer (TNBC). However, modifications in cancer cells surviving combined and sequential treatment still remain poorly described. In order to mimic clinical neoadjuvant treatment, we first treated MDA-MB-231 and SUM159-PT TNBC cell lines with epirubicin and cyclophosphamide for 2 days, and then with paclitaxel for another 2 days. After 4 days of recovery, persistent cells surviving the treatment were characterized at both cellular and molecular level. Persistent cells exhibited increased growth and were more invasive in vitro and in zebrafish model. Persistent cells were enriched for vimentin^high sub-population, vimentin knockdown using siRNA approach decreased the invasive and sphere forming capacities as well as Akt phosphorylation in persistent cells, indicating that vimentin is involved in chemotherapeutic treatment-induced enhancement of TNBC aggressiveness. Interestingly, ectopic vimentin overexpression in native cells increased cell invasion and sphere formation as well as Akt phosphorylation. Furthermore, vimentin overexpression alone rendered the native cells resistant to the drugs, while vimentin knockdown rendered them more sensitive to the drugs. Together, our data suggest that vimentin could be considered as a new targetable player in the ever-elusive status of drug resistance and recurrence of TNBC.

Epithelial-to-Mesenchymal Transition in the Light of Plasticity and Hybrid E/M States

Epithelial-to-mesenchymal transition (EMT) is a cellular program which leads to cells losing epithelial features, including cell polarity, cell-cell adhesion and attachment to the basement membrane, while gaining mesenchymal characteristics, such as invasive properties and stemness. This program is involved in embryogenesis, wound healing and cancer progression. Over the years, the role of EMT in cancer progression has been heavily debated, and the requirement of this process in metastasis even has been disputed. In this review, we discuss previous discrepancies in the light of recent findings on EMT, plasticity and hybrid E/M states. Moreover, we highlight various tumor microenvironmental cues and cell intrinsic signaling pathways that induce and sustain EMT programs, plasticity and hybrid E/M states. Lastly, we discuss how recent findings on plasticity, especially on those that enable cells to switch between hybrid E/M states, have changed our understanding on the role of EMT in cancer metastasis, stemness and therapy resistance.

Emerging Insights into Targeted Therapy-Tolerant Persister Cells in Cancer

Drug resistance is perhaps the greatest challenge in improving outcomes for cancer patients undergoing treatment with targeted therapies. It is becoming clear that "persisters," a subpopulation of drug-tolerant cells found in cancer populations, play a critical role in the development of drug resistance. Persisters are able to maintain viability under therapy but are typically slow cycling or dormant. These cells do not harbor classic drug resistance driver alterations, and their partial resistance phenotype is transient and reversible upon removal of the drug. In the clinic, the persister state most closely corresponds to minimal residual disease from which relapse can occur if treatment is discontinued or if acquired drug resistance develops in response to continuous therapy. Thus, eliminating persister cells will be crucial to improve outcomes for cancer patients. Using lung cancer targeted therapies as a primary paradigm, this review will give an overview of the characteristics of drug-tolerant persister cells, mechanisms associated with drug tolerance, and potential therapeutic opportunities to target this persister cell population in tumors.

Detection of phenotype-specific therapeutic vulnerabilities in breast cells using a CRISPR loss-of-function screen

Cellular phenotype plasticity between the epithelial and mesenchymal states has been linked to metastasis and heterogeneous responses to cancer therapy, and remains a challenge for the treatment of triple-negative breast cancer (TNBC). Here, we used isogenic human breast epithelial cell lines, D492 and D492M, representing the epithelial and mesenchymal phenotypes, respectively. We employed a CRISPR-Cas9 loss-of-function screen targeting a 2240-gene 'druggable genome' to identify phenotype-specific vulnerabilities. Cells with the epithelial phenotype were more vulnerable to the loss of genes related to EGFR-RAS-MAPK signaling, while the mesenchymal-like cells had increased sensitivity to knockout of G₂ -M cell cycle regulators. Furthermore, we discovered knockouts that sensitize to the mTOR inhibitor everolimus and the chemotherapeutic drug fluorouracil in a phenotype-specific manner. Specifically, loss of EGFR and fatty acid synthase (FASN) increased the effectiveness of the drugs in the epithelial and mesenchymal phenotypes, respectively. These phenotype-associated genetic vulnerabilities were confirmed using targeted inhibitors of EGFR (gefitinib), G₂ -M transition (STLC), and FASN (Fasnall). In conclusion, a CRISPR-Cas9 loss-of-function screen enables the identification of phenotype-specific genetic vulnerabilities that can pinpoint actionable targets and promising therapeutic combinations.

Loss of the Metastasis Suppressor NME1, But Not of Its Highly Related Isoform NME2, Induces a Hybrid Epithelial-Mesenchymal State in Cancer Cells

Epithelial-mesenchymal transition (EMT) is important for the initial steps of metastasis. Although it is well accepted that the nucleoside diphosphate kinase NME1 is a metastasis suppressor, its effect on EMT remains poorly documented, as does that of its closely related isoform, NME2. Here, by using gene silencing, inactivation and overexpression strategies in a variety of cellular models of cancer, we show that NME1 is a powerful inhibitor of EMT. Genetic manipulation of NME2, by contrast, had no effect on the EMT phenotype of cancer cells, indicating a specific function of NME1 in EMT regulation. Loss of NME1 in epithelial cancer cells resulted in a hybrid phenotype intermediate between epithelial and mesenchymal cells, which is known to be associated with cells with a highly metastatic character. Conversely, overexpression of NME1 in mesenchymal cancer cells resulted in a more epithelial phenotype. We found that NME1 expression was negatively associated with EMT markers in many human cancers and was reduced in human breast tumor cell lines with the aggressive 'triple-negative' phenotype when compared to human breast tumor cell lines positive for estrogen receptor. We show that NME1, but not NME2, is an inhibitor of essential concerted intracellular signaling pathways involved in inducing EMT, including the AKT and MAPK (ERK, p38, and JNK) pathways. Additionally, NME1 depletion considerably altered the distribution of E-cadherin, a gatekeeper of the epithelial phenotype, shifting it from the plasma membrane to the cytosol and resulting in less E-cadherin on the cell surface than in control cells. Functional aggregation and dispersion assays demonstrated that inactivation of NME1 decreases E-cadherin-mediated cell-cell adhesion. We conclude that NME1, but not NME2, acts specifically to inhibit EMT and prevent the earliest stages of metastasis.

Group Behavior and Emergence of Cancer Drug Resistance

Drug resistance is a major impediment in cancer. Although it is generally thought that acquired drug resistance is due to genetic mutations, emerging evidence indicates that nongenetic mechanisms also play an important role. Resistance emerges through a complex interplay of clonal groups within a heterogeneous tumor and the surrounding microenvironment. Traits such as phenotypic plasticity, intercellular communication, and adaptive stress response, act in concert to ensure survival of intermediate reversible phenotypes, until permanent, resistant clones can emerge. Understanding the role of group behavior, and the underlying nongenetic mechanisms, can lead to more efficacious treatment designs and minimize or delay emergence of resistance.

Combined heterogeneity in cell size and deformability promotes cancer invasiveness

Phenotypic heterogeneity is increasingly acknowledged to confer several advantages to cancer progression and drug resistance. Here, we probe the collective importance of heterogeneity in cell size and deformability in breast cancer invasion. A computational model of invasion of a heterogeneous cell aggregate predicts that combined heterogeneity in cell size and deformability enhances invasiveness of the whole population, with maximum invasiveness at intermediate cell-cell adhesion. We then show that small cells of varying deformability, a subpopulation predicted to be enriched at the invasive front, exhibit considerable overlap with the biophysical properties of cancer stem cells (CSCs). In MDA-MB-231 cells, these include CD44 ^hi CD24^- mesenchymal CSCs, which are small and soft, and CD44 ^hi CD24⁺ hybrid CSCs, which exhibit a wide range of size and deformability. We validate our predictions by tracking the pattern of cell invasion from spheroids implanted in three-dimensional collagen gels, wherein we show temporal enrichment of CD44 ^hi cells at the invasive front. Collectively, our results illustrate the advantages imparted by biophysical heterogeneity in enhancing cancer invasiveness.This article has an associated First Person interview with the first author of the paper.

Afatinib Exerts Immunomodulatory Effects by Targeting the Pyrimidine Biosynthesis Enzyme CAD

Current clinical trials of combined EGFR-tyrosine kinase inhibitors (TKI) and immune checkpoint blockade (ICB) therapies show no additional effect. This raises questions regarding whether EGFR-TKIs attenuate ICB-enhanced CD8⁺ T lymphocyte function. Here we show that the EGFR-TKI afatinib suppresses CD8⁺ T lymphocyte proliferation, and we identify CAD, a key enzyme of de novo pyrimidine biosynthesis, to be a novel afatinib target. Afatinib reduced tumor-infiltrating lymphocyte numbers in Lewis lung carcinoma (LLC)-bearing mice. Early afatinib treatment inhibited CD8⁺ T lymphocyte proliferation in patients with non-small cell lung cancer, but their proliferation unexpectedly rebounded following long-term treatment. This suggests a transient immunomodulatory effect of afatinib on CD8⁺ T lymphocytes. Sequential treatment of afatinib with anti-PD1 immunotherapy substantially enhanced therapeutic efficacy in MC38 and LLC-bearing mice, while simultaneous combination therapy showed only marginal improvement over each single treatment. These results suggest that afatinib can suppress CD8⁺ T lymphocyte proliferation by targeting CAD, proposing a timing window for combined therapy that may prevent the dampening of ICB efficacy by EGFR-TKIs. SIGNIFICANCE: This study elucidates a mechanism of afatinib-mediated immunosuppression and provides new insights into treatment timing for combined targeted therapy and immunotherapy. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/81/12/3270/F1.large.jpg.

Immunotherapy: A Potential Approach to Targeting Cancer Stem Cells

Tumor recurrence and drug resistance are two of the key factors affecting the prognosis of cancer patients. Cancer stem cells (CSCs) are a group of cells with infinite proliferation potential which are not sensitive to traditional therapies, including radio- and chemotherapy. These CSCs are considered to be central to tumor recurrence and the development of drug resistance. In addition, CSCs are important targets in cancer immunotherapy because of their expression of novel tumorassociated antigens, which result from mutations in cancer cells over the course of treatment. Emerging immunotherapies, including cancer vaccines, checkpoint blockade therapies, and transferred immune cell therapies, have all been shown to be more effective when they selectively target CSCs. Such therapies may also provide novel additions to the current therapeutic milieu and may offer new therapeutic combinations for treatment. This review summarizes the relationships between various immunotherapies and CSCs and provides novel insights into potential therapeutic applications for these approaches in the future.

Mathermycin, an anti-cancer molecule that targets cell surface phospholipids

Mathermycin, a lantipeptide isolated from marine actinomycete Marinactinospora thermotolerans, is an antibiotic that has been shown to disrupt bacterial plasma membrane. We now provide evidences that mathermycin can also disrupt cancer, but not normal, cell plasma membranes through targeting phosphatidylethanolamine (PE), which is located only in the inner leaflet of the plasma membrane in normal cells but in both the inner and outer leaflets of the membrane in tumor cells. Our data shows that mathermycin inhibits the metabolic activity and induces mainly necrotic death of all cancer cell lines with EC₅₀ between 4.2 and 16.9 μM, while normal cell lines have EC₅₀ between 113 and 129 μM. The cytotoxicity of mathermycin could be inhibited by exogenous PE, but not phosphoserine and phosphocholine. The formation of mathermycin-PE complexes was confirmed by in silico analysis, HPLC and MS spectrometer. Furthermore, mathermycin exhibited similar cytotoxicity toward cancer and multidrug resistant cancer cells, which could be due to its ability to inhibit mitochondrial function, as shown by our data from the Seahorse™ metabolic analyzer. This study demonstrates that mathermycin is a potentially effective class of anti-tumor chemotherapeutics that do not easily develop resistance due to a mechanism of action targeting PE.

Ratiometric Delivery of Mitoxantrone and Berberine Co-encapsulated Liposomes to Improve Antitumor Efficiency and Decrease Cardiac Toxicity

Combination therapy is one of the most common clinical practices in the treatment of malignancies. Synergistic effects, however, are produced only when optimal ratios of combined drugs were delivered to tumor cells. Thus, carriers co-encapsulating of multiple drugs are widely utilized for coordinated delivery. Herein, co-encapsulated pegylated liposomal formulation of mitoxantrone (MIT) and berberine (BER) at an optimal ratio has been developed (MBL) with high encapsulation efficiency (EE) and drug loading in order to achieve the purpose of ratiometric loading and delivery. MBL can not only extend blood circulation but also enhance tumor accumulation for both MIT and BER. More importantly, MBL can maintain the originally desired drug ratio in tumors within 48 h of intravenous injection for synergistic therapy. Compared with the liposomal formulation of MIT-treated group (ML), the progression of tumor growth was inhibited significantly in murine 4T1 breast tumor model after the treatment of MBL, as well as a lower cardiac toxicity. In addition, MBL evidently prolonged the survival of mice with L1210 ascitic tumor model. In summary, such a strategy of co-encapsulated liposomes could improve the clinical applications against multiple cancers.

SRC Signaling in Cancer and Tumor Microenvironment

Pioneering experiments performed by Harold Varmus and Mike Bishop in 1976 led to one of the most influential discoveries in cancer research and identified the first cancer-causing oncogene called Src. Later experimental and clinical evidence suggested that Src kinase plays a significant role in promoting tumor growth and progression and its activity is associated with poor patient survival. Thus, several Src inhibitors were developed and approved by FDA for treatment of cancer patients. Tumor microenvironment (TME) is a highly complex and dynamic milieu where significant cross-talk occurs between cancer cells and TME components, which consist of tumor-associated macrophages, fibroblasts, and other immune and vascular cells. Growth factors and chemokines activate multiple signaling cascades in TME and induce multiple kinases and pathways, including Src, leading to tumor growth, invasion/metastasis, angiogenesis, drug resistance, and progression. Here, we will systemically evaluate recent findings regarding regulation of Src and significance of targeting Src in cancer therapy.

Hybrid E/M Phenotype(s) and Stemness: A Mechanistic Connection Embedded in Network Topology

Metastasis remains an unsolved clinical challenge. Two crucial features of metastasizing cancer cells are (a) their ability to dynamically move along the epithelial-hybrid-mesenchymal spectrum and (b) their tumor initiation potential or stemness. With increasing functional characterization of hybrid epithelial/mesenchymal (E/M) phenotypes along the spectrum, recent in vitro and in vivo studies have suggested an increasing association of hybrid E/M phenotypes with stemness. However, the mechanistic underpinnings enabling this association remain unclear. Here, we develop a mechanism-based mathematical modeling framework that interrogates the emergent nonlinear dynamics of the coupled network modules regulating E/M plasticity (miR-200/ZEB) and stemness (LIN28/let-7). Simulating the dynamics of this coupled network across a large ensemble of parameter sets, we observe that hybrid E/M phenotype(s) are more likely to acquire stemness relative to "pure" epithelial or mesenchymal states. We also integrate multiple "phenotypic stability factors" (PSFs) that have been shown to stabilize hybrid E/M phenotypes both in silico and in vitro-such as OVOL1/2, GRHL2, and NRF2-with this network, and demonstrate that the enrichment of hybrid E/M phenotype(s) with stemness is largely conserved in the presence of these PSFs. Thus, our results offer mechanistic insights into recent experimental observations of hybrid E/M phenotype(s) that are essential for tumor initiation and highlight how this feature is embedded in the underlying topology of interconnected EMT (Epithelial-Mesenchymal Transition) and stemness networks.

Modulating proteasome inhibitor tolerance in multiple myeloma: an alternative strategy to reverse inevitable resistance

Background

Resistance to proteasome inhibitors (PIs) is a major obstacle to the successful treatment of multiple myeloma (MM). Many mechanisms have been proposed for PI resistance; however, our mechanistic understanding of how PI resistance is inevitably acquired and reversed remains incomplete.

Methods

MM patients after bortezomib relapse, MM cell lines and mouse models were used to generate matched resistant and reversed cells. RNA sequencing and bioinformatics analyses were employed to assess dysregulated epigenetic regulators. In vitro and in vivo procedures were used to characterise PI-tolerant cells and therapeutic efficacy.

Results

Upon PI treatment, MM cells enter a slow-cycling and reversible drug-tolerant state. This reversible phenotype is associated with epigenetic plasticity, which involves tolerance rather than persistence in patients with relapsed MM. Combination treatment with histone deacetylase inhibitors and high-dosage intermittent therapy, as opposed to sustained PI monotherapy, can be more effective in treating MM by preventing the emergence of PI-tolerant cells. The therapeutic basis is the reversal of dysregulated epigenetic regulators in MM patients.

Conclusions

We propose an alternative non-mutational PI resistance mechanism that explains why PI relapse is inevitable and why patients regain sensitivity after a ‘drug holiday’. Our study also suggests strategies for epigenetic elimination of drug-tolerant cells.

Cyclic Multiplexed-Immunofluorescence (cmIF), a Highly Multiplexed Method for Single-Cell Analysis

Immunotherapy harnesses the power of the adaptive immune system and has revolutionized the field of oncotherapy, as novel therapeutic strategies have been introduced into clinical use. The development of immune checkpoint inhibitors has led to durable control of disease in a subset of advanced cancer patients, such as those with melanoma and non-small cell lung cancer. However, predicting patient responses to therapy remains a major challenge, due to the remarkable genomic, epigenetic, and microenvironmental heterogeneity present in each tumor. Breast cancer (BC) is the most common cancer in women, where hormone receptor-positive (HR+; estrogen receptor and/or progesterone receptor) BC comprises the majority (>50%) and has better prognosis, while a minority (<20%) are triple negative BC (TNBC), which has an aggressive phenotype. There is a clinical need to identify predictors of late recurrence in HR+ BC and predictors of immunotherapy outcomes in advanced TNBC. Tumor-infiltrating lymphocytes (TILs) have recently been shown to predict late recurrence in HR+, counter to the findings that TILs confer good prognosis in TNBC and human epidermal growth factor receptor 2 positive (HER2+) subtypes. Furthermore, the spatial arrangement of TILs also appears to have prognostic value, with dense clusters of immune cells predicting poor prognosis in HR+ and good prognosis in TNBC. Whether TIL clusters in different breast cancer subtypes represent the same or different landscapes of TILs is unknown and may have treatment implications for a significant portion of breast cancer patients. Current histopathological staining technology is not sufficient for characterizing the ensembles of TILs and their spatial patterns, in addition to tumor and microenvironmental heterogeneity. However, recent advances in cyclic immunofluorescence enable differentiation of the subsets based on TILs, tumor heterogeneity, and microenvironment composition between good and poor responders. A computational framework for understanding the importance of the spatial relationships between TILs and tumor cells in cancer tissues, which will allow for quantitative interpretation of cyclic immunostaining, is also under development. This chapter will explore the workflow for a newly developed cyclic multiplexed-immunofluorescence (cmIF) assay, which has been optimized for formalin-fixed. paraffin-embedded tissues and developed to process digital images for quantitative single-cell based spatial analysis of tumor heterogeneity and microenvironment, including immune cell composition.

Engineering in Medicine To Address the Challenge of Cancer Drug Resistance: From Micro- and Nanotechnologies to Computational and Mathematical Modeling

Drug resistance has profoundly limited the success of cancer treatment, driving relapse, metastasis, and mortality. Nearly all anticancer drugs and even novel immunotherapies, which recalibrate the immune system for tumor recognition and destruction, have succumbed to resistance development. Engineers have emerged across mechanical, physical, chemical, mathematical, and biological disciplines to address the challenge of drug resistance using a combination of interdisciplinary tools and skill sets. This review explores the developing, complex, and under-recognized role of engineering in medicine to address the multitude of challenges in cancer drug resistance. Looking through the "lens" of intrinsic, extrinsic, and drug-induced resistance (also referred to as "tolerance"), we will discuss three specific areas where active innovation is driving novel treatment paradigms: (1) nanotechnology, which has revolutionized drug delivery in desmoplastic tissues, harnessing physiochemical characteristics to destroy tumors through photothermal therapy and rationally designed nanostructures to circumvent cancer immunotherapy failures, (2) bioengineered tumor models, which have benefitted from microfluidics and mechanical engineering, creating a paradigm shift in physiologically relevant environments to predict clinical refractoriness and enabling platforms for screening drug combinations to thwart resistance at the individual patient level, and (3) computational and mathematical modeling, which blends in silico simulations with molecular and evolutionary principles to map mutational patterns and model interactions between cells that promote resistance. On the basis that engineering in medicine has resulted in discoveries in resistance biology and successfully translated to clinical strategies that improve outcomes, we suggest the proliferation of multidisciplinary science that embraces engineering.

Hypoxia, partial EMT and collective migration: Emerging culprits in metastasis

Epithelial-mesenchymal transition (EMT) is a cellular biological process involved in migration of primary cancer cells to secondary sites facilitating metastasis. Besides, EMT also confers properties such as stemness, drug resistance and immune evasion which can aid a successful colonization at the distant site. EMT is not a binary process; recent evidence suggests that cells in partial EMT or hybrid E/M phenotype(s) can have enhanced stemness and drug resistance as compared to those undergoing a complete EMT. Moreover, partial EMT enables collective migration of cells as clusters of circulating tumor cells or emboli, further endorsing that cells in hybrid E/M phenotypes may be the 'fittest' for metastasis. Here, we review mechanisms and implications of hybrid E/M phenotypes, including their reported association with hypoxia. Hypoxia-driven activation of HIF-1α can drive EMT. In addition, cyclic hypoxia, as compared to acute or chronic hypoxia, shows the highest levels of active HIF-1α and can augment cancer aggressiveness to a greater extent, including enriching for a partial EMT phenotype. We also discuss how metastasis is influenced by hypoxia, partial EMT and collective cell migration, and call for a better understanding of interconnections among these mechanisms. We discuss the known regulators of hypoxia, hybrid EMT and collective cell migration and highlight the gaps which needs to be filled for connecting these three axes which will increase our understanding of dynamics of metastasis and help control it more effectively.

Nanoengineered Disruption of Heat Shock Protein 90 Targets Drug-Induced Resistance and Relieves Natural Killer Cell Suppression in Breast Cancer

Drug-induced resistance, or tolerance, is an emerging yet poorly understood failure of anticancer therapy. The interplay between drug-tolerant cancer cells and innate immunity within the tumor, the consequence on tumor growth, and therapeutic strategies to address these challenges remain undescribed. Here, we elucidate the role of taxane-induced resistance on natural killer (NK) cell tumor immunity in triple-negative breast cancer (TNBC) and the design of spatiotemporally controlled nanomedicines, which boost therapeutic efficacy and invigorate "disabled" NK cells. Drug tolerance limited NK cell immune surveillance via drug-induced depletion of the NK-activating ligand receptor axis, NK group 2 member D, and MHC class I polypeptide-related sequence A, B. Systems biology supported by empirical evidence revealed the heat shock protein 90 (Hsp90) simultaneously controls immune surveillance and persistence of drug-treated tumor cells. On the basis of this evidence, we engineered a "chimeric" nanotherapeutic tool comprising taxanes and a cholesterol-tethered Hsp90 inhibitor, radicicol, which targets the tumor, reduces tolerance, and optimally reprimes NK cells via prolonged induction of NK-activating ligand receptors via temporal control of drug release in vitro and in vivo. A human ex vivo TNBC model confirmed the importance of NK cells in drug-induced death under pressure of clinically approved agents. These findings highlight a convergence between drug-induced resistance, the tumor immune contexture, and engineered approaches that consider the tumor and microenvironment to improve the success of combinatorial therapy. SIGNIFICANCE: This study uncovers a molecular mechanism linking drug-induced resistance and tumor immunity and provides novel engineered solutions that target these mechanisms in the tumor and improve immunity, thus mitigating off-target effects.

Realizing Cancer Precision Medicine by Integrating Systems Biology and Nanomaterial Engineering

Many clinical trials for cancer precision medicine have yielded unsatisfactory results due to challenges such as drug resistance and low efficacy. Drug resistance is often caused by the complex compensatory regulation within the biomolecular network in a cancer cell. Recently, systems biological studies have modeled and simulated such complex networks to unravel the hidden mechanisms of drug resistance and identify promising new drug targets or combinatorial or sequential treatments for overcoming resistance to anticancer drugs. However, many of the identified targets or treatments present major difficulties for drug development and clinical application. Nanocarriers represent a path forward for developing therapies with these "undruggable" targets or those that require precise combinatorial or sequential application, for which conventional drug delivery mechanisms are unsuitable. Conversely, a challenge in nanomedicine has been low efficacy due to heterogeneity of cancers in patients. This problem can also be resolved through systems biological approaches by identifying personalized targets for individual patients or promoting the drug responses. Therefore, integration of systems biology and nanomaterial engineering will enable the clinical application of cancer precision medicine to overcome both drug resistance of conventional treatments and low efficacy of nanomedicine due to patient heterogeneity.

Restoring MLL reactivates latent tumor suppression-mediated vulnerability to proteasome inhibitors

MLL undergoes multiple distinct chromosomal translocations to yield aggressive leukemia with dismal outcomes. Besides their well-established role in leukemogenesis, MLL fusions also possess latent tumor-suppressive activity, which can be exploited as effective cancer treatment strategies using pharmacological means such as proteasome inhibitors (PIs). Here, using MLL-rearranged xenografts and MLL leukemic cells as models, we show that wild-type MLL is indispensable for the latent tumor-suppressive activity of MLL fusions. MLL dysfunction, shown as loss of the chromatin accumulation and subsequent degradation of MLL, compromises the latent tumor suppression of MLL-AF4 and is instrumental for the acquired PI resistance. Mechanistically, MLL dysfunction is caused by chronic PI treatment-induced epigenetic reprogramming through the H2Bub-ASH2L-MLL axis and can be specifically restored by histone deacetylase (HDAC) inhibitors, which induce histone acetylation and recruits MLL on chromatin to promote cell cycle gene expression. Our findings not only demonstrate the mechanism underlying the inevitable acquisition of PI resistance in MLL leukemic cells, but also illustrate that preventing the emergence of PI-resistant cells constitutes a novel rationale for combination therapy with PIs and HDAC inhibitors in MLL leukemias.

Targeting of BCL-2 Family Members during Anticancer Treatment: A Necessary Compromise between Individual Cell and Ecosystemic Responses?

The imbalance between BCL-2 homologues and pro-death counterparts frequently noted in cancer cells endows them with a cell autonomous survival advantage. To eradicate ectopic cells, inhibitors of these homologues (BH3 mimetics) were developed to trigger, during anticancer treatment, full activation of the canonical mitochondrial apoptotic pathway and related caspases. Despite efficiency in some clinical settings, these compounds do not completely fulfill their initial promise. We herein put forth that a growing body of evidence indicates that mitochondrial integrity, controlled by BCL-2 family proteins, and downstream caspases regulate other cell death modes and influence extracellular signaling by committed cells. Moreover, intercellular communications play a key role in spreading therapeutic response across cancer cell populations and in engaging an immune response. We thus advocate that BH3 mimetics administration would be more efficient in the long term if it did not induce apoptosis in all sensitive cells at the same time, but if it could instead allow (or trigger) death signal production by non-terminally committed dying cell populations. The development of such a trade-off strategy requires to unravel the effects of BH3 mimetics not only on each individual cancer cell but also on homotypic and heterotypic cell interactions in dynamic tumor ecosystems.

Dual-targeted therapeutic strategy combining CSC-DC-based vaccine and cisplatin overcomes chemo-resistance in experimental mice model

BACKGROUND AND PURPOSE

Emerging evidence suggests that one of the main reasons of chemotherapy treatment failure is the development of multi-drug resistance (MDR) associated with cancer stem cells (CSCs). Our aim is to identify a therapeutic strategy based on MDR-reversing agents.

MATERIALS AND METHODS

CSC-enriched Ehrlich carcinoma (EC) cell cultures were prepared by drug-resistant selection method using different concentrations of cisplatin (CIS). Cell cultures following drug exposure were analyzed by flow cytometry for CSC surface markers CD44⁺/CD24^-. We isolated murine bone marrow-derived dendritic cells (DCs) and then used them to prepare CSC-DC vaccine by pulsation with CSC-enriched lysate. DCs were examined by flow cytometry for phenotypic markers. Solid Ehrlich carcinoma bearing mice were injected with the CSC-DC vaccine in conjunction with repeated low doses of CIS. Tumor growth inhibition was evaluated and tumor tissues were excised and analyzed by real-time PCR to determine the relative gene expression levels of MDR and Bcl-2. Histopathological features of tumor tissues excised were examined.

RESULTS AND CONCLUSION

Co-treatment with CSC-DC and CIS resulted in a significant tumor growth inhibition. Furthermore, the greatest response of downregulation of MDR and Bcl-2 relative gene expression were achieved in the same group. In parallel, the histopathological observations demonstrated enhanced apoptosis and absence of mitotic figures in tumor tissues of the co-treatment group. Dual targeting of resistant cancer cells using CSC-DC vaccine along with cisplatin represents a promising therapeutic strategy that could suppress tumor growth, circumvent MDR, and increase the efficacy of conventional chemotherapies.

Cancer Stem Cells and Epithelial-to-Mesenchymal Transition in Cancer Metastasis

The cancer stem cell (CSC) concept stands for undifferentiated tumor cells with the ability to initiate heterogeneous tumors. It is also relevant in metastasis and can explain how metastatic tumors mirror the heterogeneity of primary tumors. Cellular plasticity, including the epithelial-to-mesenchymal transition (EMT), enables the generation of CSCs at different steps of the metastatic process including metastatic colonization. In this review, we update the concept of CSCs and provide evidence of the existence of metastatic stem cells (MetSCs). In addition, we highlight the nuanced understanding of EMT that has been gained recently and the association of mesenchymal-to-epithelial transition (MET) with the acquisition of CSCs properties during metastasis. We also comment on the computational approaches that have profoundly influenced our understanding of CSCs and EMT; and how these studies and new experimental technologies can yield a deeper understanding of the biological aspects of metastasis.

Mathematical Details on a Cancer Resistance Model

One of the most important factors limiting the success of chemotherapy in cancer treatment is the phenomenon of drug resistance. We have recently introduced a framework for quantifying the effects of induced and non-induced resistance to cancer chemotherapy (Greene et al., 2018a, 2019). In this work, we expound on the details relating to an optimal control problem outlined in Greene et al. (2018a). The control structure is precisely characterized as a concatenation of bang-bang and path-constrained arcs via the Pontryagin Maximum Principle and differential Lie algebraic techniques. A structural identifiability analysis is also presented, demonstrating that patient-specific parameters may be measured and thus utilized in the design of optimal therapies prior to the commencement of therapy. For completeness, a detailed analysis of existence results is also included.

Mathematical Approach to Differentiate Spontaneous and Induced Evolution to Drug Resistance During Cancer Treatment

Purpose

Drug resistance is a major impediment to the success of cancer treatment. Resistance is typically thought to arise from random genetic mutations, after which mutated cells expand via Darwinian selection. However, recent experimental evidence suggests that progression to drug resistance need not occur randomly, but instead may be induced by the treatment itself via either genetic changes or epigenetic alterations. This relatively novel notion of resistance complicates the already challenging task of designing effective treatment protocols.

Materials and Methods

To better understand resistance, we have developed a mathematical modeling framework that incorporates both spontaneous and drug-induced resistance.

Results

Our model demonstrates that the ability of a drug to induce resistance can result in qualitatively different responses to the same drug dose and delivery schedule. We have also proven that the induction parameter in our model is theoretically identifiable and propose an in vitro protocol that could be used to determine a treatment’s propensity to induce resistance.

Multiplexed drug testing of tumor slices using a microfluidic platform

Current methods to assess the drug response of individual human cancers are often inaccurate, costly, or slow. Functional approaches that rapidly and directly assess the response of patient cancer tissue to drugs or small molecules offer a promising way to improve drug testing, and have the potential to identify the best therapy for individual patients. We developed a digitally manufactured microfluidic platform for multiplexed drug testing of intact cancer slice cultures, and demonstrate the use of this platform to evaluate drug responses in slice cultures from human glioma xenografts and patient tumor biopsies. This approach retains much of the tissue microenvironment and can provide results rapidly enough, within days of surgery, to guide the choice of effective initial therapies. Our results establish a useful preclinical platform for cancer drug testing and development with the potential to improve cancer personalized medicine.

Identifying inhibitors of epithelial-mesenchymal plasticity using a network topology-based approach

Metastasis is the cause of over 90% of cancer-related deaths. Cancer cells undergoing metastasis can switch dynamically between different phenotypes, enabling them to adapt to harsh challenges, such as overcoming anoikis and evading immune response. This ability, known as phenotypic plasticity, is crucial for the survival of cancer cells during metastasis, as well as acquiring therapy resistance. Various biochemical networks have been identified to contribute to phenotypic plasticity, but how plasticity emerges from the dynamics of these networks remains elusive. Here, we investigated the dynamics of various regulatory networks implicated in Epithelial–mesenchymal plasticity (EMP)—an important arm of phenotypic plasticity—through two different mathematical modelling frameworks: a discrete, parameter-independent framework (Boolean) and a continuous, parameter-agnostic modelling framework (RACIPE). Results from either framework in terms of phenotypic distributions obtained from a given EMP network are qualitatively similar and suggest that these networks are multi-stable and can give rise to phenotypic plasticity. Neither method requires specific kinetic parameters, thus our results emphasize that EMP can emerge through these networks over a wide range of parameter sets, elucidating the importance of network topology in enabling phenotypic plasticity. Furthermore, we show that the ability to exhibit phenotypic plasticity correlates positively with the number of positive feedback loops in a given network. These results pave a way toward an unorthodox network topology-based approach to identify crucial links in a given EMP network that can reduce phenotypic plasticity and possibly inhibit metastasis—by reducing the number of positive feedback loops.

Cancer Stem Cell Plasticity - A Deadly Deal

Intratumoral heterogeneity is a major ongoing challenge in the effective therapeutic targeting of cancer. Accumulating evidence suggests that a fraction of cells within a tumor termed Cancer Stem Cells (CSCs) are primarily responsible for this diversity resulting in therapeutic resistance and metastasis. Adding to this complexity, recent studies have shown that there can be different subpopulations of CSCs with varying biochemical and biophysical traits resulting in varied dissemination and drug-resistance potential. Moreover, cancer cells can exhibit a high level of plasticity or the ability to dynamically switch between CSC and non-CSC states or among different subsets of CSCs. In addition, CSCs also display extensive metabolic plasticity. The molecular mechanisms underlying these different interconnected axes of plasticity has been under extensive investigation and the trans-differentiation process of Epithelial to Mesenchymal transition (EMT) has been identified as a major contributing factor. Besides genetic and epigenetic factors, CSC plasticity is also shaped by non-cell-autonomous effects such as the tumor microenvironment (TME). In this review, we discuss the latest developments in decoding mechanisms and implications of CSC plasticity in tumor progression at biochemical and biophysical levels, and the latest in silico approaches being taken for characterizing cancer cell plasticity. These efforts can help improve existing therapeutic approaches by taking into consideration the contribution of cellular plasticity/heterogeneity in enabling drug resistance.

Drug-Induced Resistance in Micrometastases: Analysis of Spatio-Temporal Cell Lineages

Resistance to anti-cancer drugs is a major cause of treatment failure. While several intracellular mechanisms of resistance have been postulated, the role of extrinsic factors in the development of resistance in individual tumor cells is still not fully understood. Here we used a hybrid agent-based model to investigate how sensitive tumor cells develop drug resistance in the heterogeneous tumor microenvironment. We characterized the spatio-temporal evolution of lineages of the resistant cells and examined how resistance at the single-cell level contributes to the overall tumor resistance. We also developed new methods to track tumor cell adaptation, to trace cell viability trajectories and to examine the three-dimensional spatio-temporal lineage trees. Our findings indicate that drug-induced resistance can result from cells adaptation to the changes in drug distribution. Two modes of cell adaptation were identified that coincide with microenvironmental niches—areas sheltered by cell micro-communities (protectorates) or regions with limited drug penetration (refuga or sanctuaries). We also recognized that certain cells gave rise to lineages of resistant cells (precursors of resistance) and pinpointed three temporal periods and spatial locations at which such cells emerged. This supports the hypothesis that tumor micrometastases do not need to harbor cell populations with pre-existing resistance, but that individual tumor cells can adapt and develop resistance induced by the drug during the treatment.

Intratumor Heterogeneity: The Rosetta Stone of Therapy Resistance

Advances in our understanding of molecular mechanisms of tumorigenesis have translated into knowledge-based therapies directed against specific oncogenic signaling targets. These therapies often induce dramatic responses in susceptible tumors. Unfortunately, most advanced cancers, including those with robust initial responses, eventually acquire resistance to targeted therapies and relapse. Even though immune-based therapies are more likely to achieve complete cures, acquired resistance remains an obstacle to their success as well. Acquired resistance is the direct consequence of pre-existing intratumor heterogeneity and ongoing diversification during therapy, which enables some tumor cells to survive treatment and facilitates the development of new therapy-resistant phenotypes. In this review, we discuss the sources of intratumor heterogeneity and approaches to capture and account for it during clinical decision making. Finally, we outline potential strategies to improve therapeutic outcomes by directly targeting intratumor heterogeneity.

Combining Tumor Microenvironment Modulating Nanoparticles with Doxorubicin to Enhance Chemotherapeutic Efficacy and Boost Antitumor Immunity

BACKGROUND

Tumor microenvironment (TME) and associated multiple factors are found to contribute to the failures in cancer therapies, including chemo- and immunotherapy. Here we report a new multimodal strategy that uses a bioreactive multifunctional hybrid polymer-lipid encapsulated manganese dioxide nanoparticle (PLMD NP) system to remodel the TME, suppress drug resistance factors, reverse immunosuppressive conditions, and enhance chemotherapy efficacy.

METHODS

The influence of PLMD NPs on enhancing cellular uptake in EMT6 mouse breast cancer cells and tumor penetration of doxorubicin (DOX) in EMT6 orthotopic breast tumor mouse model was evaluated using confocal microscopy (n = 3-4). Immunohistochemistry was employed to examine the effect of PLMD NPs on downregulating hypoxia-induced drug resistance proteins and anticancer activity of DOX (n = 3-4). The efficacy of the combination therapy with PLMD NPS and DOX was assessed in murine EMT6 (n = 15-23) and 4T1 (n = 7) orthotopic breast tumor mouse models. Rechallenge and splenocyte transfer were performed to validate the stimulation of adaptive tumor immunity in the surviving mice.

RESULTS

PLMD NPs enhanced intratumoral penetration and efficacy of DOX, and reduced intratumoral expression of P-glycoprotein, p53, and carbonic anhydrase IX by 74.5%, 38.0%, and 58.8% vs saline control, respectively. Combination treatment with PLMD NPs and DOX increased the number of tumor-infiltrated CD8+ T cells and resulted in up to 60.0% complete tumor regression. Of naïve mice (n = 7) that received splenocytes from the PLMD+DOX-treated surviving mice, 57.1% completely suppressed tumor growth whereas 100% of mice that received splenocytes from DOX-treated mice (n = 3) and the control group (n = 7) showed rapid tumor growth.

CONCLUSIONS

The clinically suitable PLMD NPs can effectively downregulate TME-associated drug resistance and immunosuppression. The combination therapy with PLMD NPs and DOX is a multimodal and translational treatment approach for enhancing chemotherapeutic efficacy and boosting antitumor immunity.

Exosomes mediate intercellular transfer of non-autonomous tolerance to proteasome inhibitors in mixed-lineage leukemia

Proteasome inhibitors significantly improve cancer outcomes, but their use is eventually followed by proteasome inhibitor resistance and relapse. Current understanding of proteasome inhibitor resistance is limited to cell‐autonomous mechanisms; whether non–autonomous mechanisms can be implicated in the development of proteasome inhibitor resistance is unclear. Here, we show that proteasome inhibitor tolerance can be transmitted non–autonomously through exosome‐mediated intercellular interactions. We revealed that reversible proteasome inhibitor resistance can be transmitted from cells under therapy stress to naïve sensitive cells through exosome‐mediated cell cycle arrest and enhanced stemness in mixed‐lineage leukemia cells. Integrated multi‐omics analysis using the Tied Diffusion through Interacting Events algorithm identified several candidate exosomal proteins that may serve as predictors for proteasome inhibitor resistance and potential therapeutic targets for treating refractory mixed‐lineage leukemia. Furthermore, inhibiting the secretion of exosomes is a promising strategy for reversing proteasome inhibitor resistance in vivo, which provides a novel proof of principle for the treatment of other refractory or relapsed cancers.

Hybrid Epithelial/Mesenchymal State in Cancer Metastasis: Clinical Significance and Regulatory Mechanisms

Epithelial-mesenchymal transition (EMT) has been well recognized for its essential role in cancer progression as well as normal tissue development. In cancer cells, activation of EMT permits the cells to acquire migratory and invasive abilities and stem-like properties. However, simple categorization of cancer cells into epithelial and mesenchymal phenotypes misleads the understanding of the complicated metastatic process, and contradictory results from different studies also indicate the limitation of application of EMT theory in cancer metastasis. Nowadays, growing evidence suggests the existence of an intermediate status between epithelial and mesenchymal phenotypes, i.e., the "hybrid epithelial-mesenchymal (hybrid E/M)" state, provides a possible explanation for those conflicting results. Appearance of hybrid E/M phenotype offers a more plastic status for cancer cells to adapt the stressful environment for proceeding metastasis. In this article, we review the biological importance of the dynamic changes between the epithelial and the mesenchymal states. The regulatory mechanisms encompassing the translational, post-translational, and epigenetic control for this complex and plastic status are also discussed.

Upregulation of CD73 Confers Acquired Radioresistance and is Required for Maintaining Irradiation-selected Pancreatic Cancer Cells in a Mesenchymal State

The molecular mechanisms underlying exceptional radioresistance in pancreatic cancer remain elusive. In the present study, we established a stable radioresistant pancreatic cancer cell line MIA PaCa-2-R by exposing the parental MIA PaCa-2 cells to fractionated ionizing radiation (IR). Systematic proteomics and bioinformatics analysis of protein expression in MIA PaCa-2 and MIA PaCa-2-R cells revealed that several growth factor-/cytokine-mediated pathways, including the OSM/STAT3, PI3K/AKT, and MAPK/ERK pathways, were activated in the radioresistant cells, leading to inhibition of apoptosis and increased epithelial-mesenchymal plasticity. In addition, the radioresistant cells exhibited enhanced capabilities of DNA repair and antioxidant defense compared with the parental cells. We focused functional analysis on one of the most up-regulated proteins in the radioresistant cells, ecto-5'-nucleotidase (CD73), which is a cell surface protein that is overexpressed in different types of cancer. Ectopic overexpression of CD73 in the parental cells resulted in radioresistance and conferred resistance to IR-induced apoptosis. Knockdown of CD73 re-sensitized the radioresistant cells to IR and IR-induced apoptosis. The effect of CD73 on radioresistance and apoptosis is independent of the enzymatic activity of CD73. Further studies demonstrate that CD73 up-regulation promotes Ser-136 phosphorylation of the proapoptotic protein BAD and is required for maintaining the radioresistant cells in a mesenchymal state. Our findings suggest that expression alterations in the IR-selected pancreatic cancer cells result in hyperactivation of the growth factor/cytokine signaling that promotes epithelial-mesenchymal plasticity and enhancement of DNA repair. Our results also suggest that CD73, potentially a novel downstream factor of the enhanced growth factor/cytokine signaling, confers acquired radioresistance by inactivating proapoptotic protein BAD via phosphorylation of BAD at Ser-136 and by maintaining the radioresistant pancreatic cancer cells in a mesenchymal state.

Cancer stem-like cells with hybrid epithelial/mesenchymal phenotype leading the collective invasion

Collective invasion of cancer cells is the key process of circulating tumor cell (CTC) cluster formation, and greatly contributes to metastasis. Cancer stem-like cells (CSC) have a distinct advantage of motility for metastatic dissemination. To verify the role of CSC in the collective invasion, we performed 3D assays to investigate the collective invasion from cancer cell spheroids. The results demonstrated that CSC can significantly promote both collective and single-cell invasion. Further study showed that CSC prefer to move outside and lead the collective invasion. More interestingly, approximately 60% of the leader CSC in collective invasion co-expressed both epithelial and mesenchymal genes, while only 4% co-expressed in single invasive CSC, indicating that CSC with hybrid epithelial/mesenchymal phenotype play a key role in cancer cell collective invasion.

Towards Multidrug Adaptive Therapy

A new ecologically inspired paradigm in cancer treatment known as "adaptive therapy" capitalizes on competitive interactions between drug-sensitive and drug-resistant subclones. The goal of adaptive therapy is to maintain a controllable stable tumor burden by allowing a significant population of treatment-sensitive cells to survive. These, in turn, suppress proliferation of the less-fit resistant populations. However, there remain several open challenges in designing adaptive therapies, particularly in extending these therapeutic concepts to multiple treatments. We present a cancer treatment case study (metastatic castrate-resistant prostate cancer) as a point of departure to illustrate three novel concepts to aid the design of multidrug adaptive therapies. First, frequency-dependent "cycles" of tumor evolution can trap tumor evolution in a periodic, controllable loop. Second, the availability and selection of treatments may limit the evolutionary "absorbing region" reachable by the tumor. Third, the velocity of evolution significantly influences the optimal timing of drug sequences. These three conceptual advances provide a path forward for multidrug adaptive therapy. SIGNIFICANCE: Driving tumor evolution into periodic, repeatable treatment cycles provides a path forward for multidrug adaptive therapy.

Understanding the role of phenotypic switching in cancer drug resistance

The emergence of acquired drug resistance in cancer represents a major barrier to treatment success. While research has traditionally focused on genetic sources of resistance, recent findings suggest that cancer cells can acquire transient resistant phenotypes via epigenetic modifications and other non-genetic mechanisms. Although these resistant phenotypes are eventually relinquished by individual cells, they can temporarily 'save' the tumor from extinction and enable the emergence of more permanent resistance mechanisms. These observations have generated interest in the potential of epigenetic therapies for long-term tumor control or eradication. In this work, we develop a mathematical model to study how phenotypic switching at the single-cell level affects resistance evolution in cancer. We highlight unique features of non-genetic resistance, probe the evolutionary consequences of epigenetic drugs and explore potential therapeutic strategies. We find that even short-term epigenetic modifications and stochastic fluctuations in gene expression can drive long-term drug resistance in the absence of any bona fide resistance mechanisms. We also find that an epigenetic drug that slightly perturbs the average retention of the resistant phenotype can turn guaranteed treatment failure into guaranteed success. Lastly, we find that combining an epigenetic drug with an anti-cancer agent can significantly outperform monotherapy, and that treatment outcome is heavily affected by drug sequencing.

Patient-derived explants (PDEs) as a powerful preclinical platform for anti-cancer drug and biomarker discovery

Preclinical models that can accurately predict outcomes in the clinic are much sought after in the field of cancer drug discovery and development. Existing models such as organoids and patient-derived xenografts have many advantages, but they suffer from the drawback of not contextually preserving human tumour architecture. This is a particular problem for the preclinical testing of immunotherapies, as these agents require an intact tumour human-specific microenvironment for them to be effective. In this review, we explore the potential of patient-derived explants (PDEs) for fulfilling this need. PDEs involve the ex vivo culture of fragments of freshly resected human tumours that retain the histological features of original tumours. PDE methodology for anti-cancer drug testing has been in existence for many years, but the platform has not been widely adopted in translational research facilities, despite strong evidence for its clinical predictivity. By modifying PDE endpoint analysis to include the spatial profiling of key biomarkers by using multispectral imaging, we argue that PDEs offer many advantages, including the ability to correlate drug responses with tumour pathology, tumour heterogeneity and changes in the tumour microenvironment. As such, PDEs are a powerful model of choice for cancer drug and biomarker discovery programmes.

Exploiting Cancer Cells Metabolic Adaptability to Enhance Therapy Response in Cancer

Despite all the progresses developed in prevention and new treatment approaches, cancer is the second leading cause of death worldwide, being chemoresistance a pivotal barrier in cancer management. Cancer cells present several mechanisms of drug resistance/tolerance and recently, growing evidence have been supporting a role of metabolism reprograming per se as a driver of chemoresistance. In fact, cancer cells display several adaptive mechanisms that allow the emergency of chemoresistance, revealing cancer as a disease that adapts and evolve along with the treatment. Therefore, clinical protocols that take into account the adaptive potential of cancer cells should be more effective than the current traditional standard protocols on the fighting against cancer.In here, some of the recent findings on the role of metabolism reprograming in cancer chemoresistance emergence will be discussed, as the potential evolutionary strategies that could unable these adaptations, hence allowing to prevent the emergency of treatment resistance, changing cancer outcome.

Mapping lung cancer epithelial-mesenchymal transition states and trajectories with single-cell resolution

Elucidating the spectrum of epithelial-mesenchymal transition (EMT) and mesenchymal-epithelial transition (MET) states in clinical samples promises insights on cancer progression and drug resistance. Using mass cytometry time-course analysis, we resolve lung cancer EMT states through TGFβ-treatment and identify, through TGFβ-withdrawal, a distinct MET state. We demonstrate significant differences between EMT and MET trajectories using a computational tool (TRACER) for reconstructing trajectories between cell states. In addition, we construct a lung cancer reference map of EMT and MET states referred to as the EMT-MET PHENOtypic STAte MaP (PHENOSTAMP). Using a neural net algorithm, we project clinical samples onto the EMT-MET PHENOSTAMP to characterize their phenotypic profile with single-cell resolution in terms of our in vitro EMT-MET analysis. In summary, we provide a framework to phenotypically characterize clinical samples in the context of in vitro EMT-MET findings which could help assess clinical relevance of EMT in cancer in future studies.

Intermediate transitions between epithelial and mesenchymal states are associated with tumor progression. Here using mass cytometry, Plevritis and colleagues develop a computational framework to resolve and map these trajectories in lung cancer cells and clinical specimens.

Exposing the Underlying Relationship of Cancer Metastasis to Metabolism and Epithelial-Mesenchymal Transitions

Cancer is a disease governed by the underlying gene regulatory networks. The hallmarks of cancer have been proposed to characterize the cancerization, e.g., abnormal metabolism, epithelial to mesenchymal transition (EMT), and cancer metastasis. We constructed a metabolism-EMT-metastasis regulatory network and quantified its underlying landscape. We identified four attractors, characterizing epithelial, abnormal metabolic, mesenchymal, and metastatic cell states, respectively. Importantly, we identified an abnormal metabolic state. Based on the transition path theory, we quantified the kinetic transition paths among these different cell states. Our results for landscape and paths indicate that metastasis is a sequential process: cells tend to first change their metabolism, then activate the EMT and eventually reach the metastatic state. This demonstrates the importance of the temporal order for different gene circuits switching on or off during metastatic progression of cancer cells and underlines the cascading regulation of metastasis through an abnormal metabolic intermediate state.

Mathematical modeling reveals the factors involved in the phenomena of cancer stem cells stabilization

Cancer Stem Cells (CSC), a subset of cancer cells resembling normal stem cells with self-renewal and asymmetric division capabilities, are present at various but low proportions in many tumors and are thought to be responsible for tumor relapses following conventional cancer therapies. In vitro, most intriguingly, isolated CSCs rapidly regenerate the original population of stem and non-stem cells (non-CSCs) as shown by various investigators. This phenomenon still remains to be explained. We propose a mathematical model of cancer cell population dynamics, based on the main parameters of cell population growth, including the proliferation rates, the rates of cell death and the frequency of symmetric and asymmetric cell divisions both in CSCs and non-CSCs sub-populations, and taking into account the stabilization phenomenon. The analysis of the model allows determination of time-varying corridors of probabilities for different cell fates, given the particular dynamics of cancer cells populations; and determination of a cell-cell communication factors influencing these time-varying probabilities of cell behavior (division, transition) scenarios. Though the results of the model have to be experimentally confirmed, we can anticipate the development of several fundamental and practical applications based on the theoretical results of the model.

Balancing STAT Activity as a Therapeutic Strategy

Driven by dysregulated IL-6 family member cytokine signaling in the tumor microenvironment (TME), aberrant signal transducer and activator of transcription (STAT3) and (STAT5) activation have been identified as key contributors to tumorigenesis. Following transformation, persistent STAT3 activation drives the emergence of mesenchymal/cancer-stem cell (CSC) properties, important determinants of metastatic potential and therapy failure. Moreover, STAT3 signaling within tumor-associated macrophages and neutrophils drives secretion of factors that facilitate metastasis and suppress immune cell function. Persistent STAT5 activation is responsible for cancer cell maintenance through suppression of apoptosis and tumor suppressor signaling. Furthermore, STAT5-mediated CD4+/CD25+ regulatory T cells (T_regs) have been implicated in suppression of immunosurveillance. We discuss these roles for STAT3 and STAT5, and weigh the attractiveness of different modes of targeting each cancer therapy. Moreover, we discuss how anti-tumorigenic STATs, including STAT1 and STAT2, may be leveraged to suppress the pro-tumorigenic functions of STAT3/STAT5 signaling.

The Complexities of Metastasis

Therapies that prevent metastatic dissemination and tumor growth in secondary organs are severely lacking. A better understanding of the mechanisms that drive metastasis will lead to improved therapies that increase patient survival. Within a tumor, cancer cells are equipped with different phenotypic and functional capacities that can impact their ability to complete the metastatic cascade. That phenotypic heterogeneity can be derived from a combination of factors, in which the genetic make-up, interaction with the environment, and ability of cells to adapt to evolving microenvironments and mechanical forces play a major role. In this review, we discuss the specific properties of those cancer cell subgroups and the mechanisms that confer or restrict their capacity to metastasize.

Breast Cancer Stem Cells as Drivers of Tumor Chemoresistance, Dormancy and Relapse: New Challenges and Therapeutic Opportunities

Breast cancer is the most frequent cancer among women worldwide. Therapeutic strategies to prevent or treat metastatic disease are still inadequate although great progress has been made in treating early-stage breast cancer. Cancer stem-like cells (CSCs) that are endowed with high plasticity and self-renewal properties have been shown to play a key role in breast cancer development, progression, and metastasis. A subpopulation of CSCs that combines tumor-initiating capacity and a dormant/quiescent/slow cycling status is present throughout the clinical history of breast cancer patients. Dormant/quiescent/slow cycling CSCs are a key component of tumor heterogeneity and they are responsible for chemoresistance, tumor migration, and metastatic dormancy, defined as the ability of CSCs to survive in target organs and generate metastasis up to two decades after diagnosis. Understanding the strategies that are used by CSCs to resist conventional and targeted therapies, to interact with their niche, to escape immune surveillance, and finally to awaken from dormancy is of key importance to prevent and treat metastatic cancer. This review summarizes the current understanding of mechanisms involved in CSCs chemoresistance, dissemination, and metastasis in breast cancer, with a particular focus on dormant cells. Finally, we discuss how advancements in the detection, molecular understanding, and targeting of dormant CSCs will likely open new therapeutic avenues for breast cancer treatment.

Sacrificial Bioprinting of a Mammary Ductal Carcinoma Model

Cancer tissue engineering has remained challenging due to the limitations of the conventional biofabrication techniques to model the complex tumor microenvironment. Here, the utilization of a sacrificial bioprinting strategy is reported to generate the biomimetic mammary duct-like structure within a hydrogel matrix, which is further populated with breast cancer cells, to model the genesis of ductal carcinoma and its subsequent outward invasion. This bioprinted mammary ductal carcinoma model provides a proof-of-concept demonstration of the value of using the sacrificial bioprinting technique for engineering biologically relevant cancer models, which may be possibly extended to other cancer types where duct-like structures are involved.

Cooperative adaptation to therapy (CAT) confers resistance in heterogeneous non-small cell lung cancer

Understanding intrinsic and acquired resistance is crucial to overcoming cancer chemotherapy failure. While it is well-established that intratumor, subclonal genetic and phenotypic heterogeneity significantly contribute to resistance, it is not fully understood how tumor sub-clones interact with each other to withstand therapy pressure. Here, we report a previously unrecognized behavior in heterogeneous tumors: cooperative adaptation to therapy (CAT), in which cancer cells induce co-resistant phenotypes in neighboring cancer cells when exposed to cancer therapy. Using a CRISPR/Cas9 toolkit we engineered phenotypically diverse non-small cell lung cancer (NSCLC) cells by conferring mutations in Dicer1, a type III cytoplasmic endoribonuclease involved in small non-coding RNA genesis. We monitored three-dimensional growth dynamics of fluorescently-labeled mutant and/or wild-type cells individually or in co-culture using a substrate-free NanoCulture system under unstimulated or drug pressure conditions. By integrating mathematical modeling with flow cytometry, we characterized the growth patterns of mono- and co-cultures using a mathematical model of intra- and interspecies competition. Leveraging the flow cytometry data, we estimated the model’s parameters to reveal that the combination of WT and mutants in co-cultures allowed for beneficial growth in previously drug sensitive cells despite drug pressure via induction of cell state transitions described by a cooperative game theoretic change in the fitness values. Finally, we used an ex vivo human tumor model that predicts clinical response through drug sensitivity analyses and determined that cellular and morphologic heterogeneity correlates to prognostic failure of multiple clinically-approved and off-label drugs in individual NSCLC patient samples. Together, these findings present a new paradox in drug resistance implicating non-genetic cooperation among tumor cells to thwart drug pressure, suggesting that profiling for druggable targets (i.e. mutations) alone may be insufficient to assign effective therapy.

Here, we provide mathematical and empirical evidence to support a potentially new paradigm in drug resistance, which we have termed “cooperative adaptation to therapy” (CAT). CAT is defined by a phenomenon wherein drug-sensitive cancer cells with different genetic and phenotypic features within a 3-dimensional heterogeneous tumor induce non-mutational resistance in their neighboring cells under pressure of cancer therapy. To develop this novel conclusion we deployed an interdisciplinary effort including an ex vivo human tumor model, a CRISPR/Cas9 platform with 3-dimensional in vitro experiments, and high throughput flow cytometry. Importantly, we wove these data together using a mathematical model of intra- and interspecies competition to understand how tumor heterogeneity influenced our observations. By estimating the model’s parameters, we determined that the combination of genetic clonal variants in co-cultures allowed for previously drug-sensitive cells to continue to grow despite drug pressure. We were thus able to characterize distinct growth regimens in mono- and co-cultures without and with drug pressure.