Metronomic Chemotherapy Modulates Clonal Interactions to Prevent Drug Resistance in Non-Small Cell Lung Cancer

Optimizing cancer therapy: a review of the multifaceted effects of metronomic chemotherapy

Metronomic chemotherapy (MCT), characterized by the continuous administration of chemotherapeutics at a lower dose without prolonged drug-free periods, has garnered significant attention over the last 2 decades. Extensive evidence from both pre-clinical and clinical settings indicates that MCT induces distinct biological effects than the standard Maximum Tolerated Dose (MTD) chemotherapy. The low toxicity profile, reduced likelihood of inducing acquired therapeutic resistance, and low cost of MCT render it an attractive chemotherapeutic regimen option. One of the most prominent aspects of MCT is its anti-angiogenesis effects. It has been shown to stimulate the expression of anti-angiogenic molecules, thereby inhibiting angiogenesis. In addition, MCT has been shown to decrease the regulatory T-cell population and promote anti-tumor immune response through inducing dendritic cell maturation and increasing the number of cytotoxic T-cells. Combination therapies utilizing MCT along with oncolytic virotherapy, radiotherapy or other chemotherapeutic regimens have been studied extensively. This review provides an overview of the current status of MCT research and the established mechanisms of action of MCT treatment and also offers insights into potential avenues of development for MCT in the future.

Tumor containment: a more general mathematical analysis

Clinical and pre-clinical data suggest that treating some tumors at a mild, patient-specific dose might delay resistance to treatment and increase survival time. A recent mathematical model with sensitive and resistant tumor cells identified conditions under which a treatment aiming at tumor containment rather than eradication is indeed optimal. This model however neglected mutations from sensitive to resistant cells, and assumed that the growth-rate of sensitive cells is non-increasing in the size of the resistant population. The latter is not true in standard models of chemotherapy. This article shows how to dispense with this assumption and allow for mutations from sensitive to resistant cells. This is achieved by a novel mathematical analysis comparing tumor sizes across treatments not as a function of time, but as a function of the resistant population size.

Addressing Genetic Tumor Heterogeneity, Post-Therapy Metastatic Spread, Cancer Repopulation, and Development of Acquired Tumor Cell Resistance

The concept of post-therapy metastatic spread, cancer repopulation and acquired tumor cell resistance (M-CRAC) rationalizes tumor progression because of tumor cell heterogeneity arising from post-therapy genetic damage and subsequent tissue repair mechanisms. Therapeutic strategies designed to specifically address M-CRAC involve tissue editing approaches, such as low-dose metronomic chemotherapy and the use of transcriptional modulators with or without targeted therapies. Notably, tumor tissue editing holds the potential to treat patients, who are refractory to or relapsing (r/r) after conventional chemotherapy, which is usually based on administering a maximum tolerable dose of a cytostatic drugs. Clinical trials enrolling patients with r/r malignancies, e.g., non-small cell lung cancer, Hodgkin's lymphoma, Langerhans cell histiocytosis and acute myelocytic leukemia, indicate that tissue editing approaches could yield tangible clinical benefit. In contrast to conventional chemotherapy or state-of-the-art precision medicine, tissue editing employs a multi-pronged approach targeting important drivers of M-CRAC across various tumor entities, thereby, simultaneously engaging tumor cell differentiation, immunomodulation, and inflammation control. In this review, we highlight the M-CRAC concept as a major factor in resistance to conventional cancer therapies and discusses tissue editing as a potential treatment.

Mathematical Modeling Support for Lung Cancer Therapy-A Short Review

The paper presents a review of models that can be used to describe dynamics of lung cancer growth and its response to treatment at both cell population and intracellular processes levels. To address the latter, models of signaling pathways associated with cellular responses to treatment are overviewed. First, treatment options for lung cancer are discussed, and main signaling pathways and regulatory networks are briefly reviewed. Then, approaches used to model specific therapies are discussed. Following that, models of intracellular processes that are crucial in responses to therapies are presented. The paper is concluded with a discussion of the applicability of the presented approaches in the context of lung cancer.

Effective dose window for containing tumor burden under tolerable level

A maximum-tolerated dose (MTD) reduces the drug-sensitive cell population, though it may result in the competitive release of drug resistance. Alternative treatment strategies such as adaptive therapy (AT) or dose modulation aim to impose competitive stress on drug-resistant cell populations by maintaining a sufficient number of drug-sensitive cells. However, given the heterogeneous treatment response and tolerable tumor burden level of individual patients, determining an effective dose that can fine-tune competitive stress remains challenging. This study presents a mathematical model-driven approach that determines the plausible existence of an effective dose window (EDW) as a range of doses that conserve sufficient sensitive cells while maintaining the tumor volume below a threshold tolerable tumor volume (TTV). We use a mathematical model that explains intratumor cell competition. Analyzing the model, we derive an EDW determined by TTV and the competitive strength. By applying a fixed endpoint optimal control model, we determine the minimal dose to contain cancer at a TTV. As a proof of concept, we study the existence of EDW for a small cohort of melanoma patients by fitting the model to longitudinal tumor response data. We performed identifiability analysis, and for the patients with uniquely identifiable parameters, we deduced patient-specific EDW and minimal dose. The tumor volume for a patient could be theoretically contained at the TTV either using continuous dose or AT strategy with doses belonging to EDW. Further, we conclude that the lower bound of the EDW approximates the minimum effective dose (MED) for containing tumor volume at the TTV.

Metronomic Chemotherapy: Anti-Tumor Pathways and Combination with Immune Checkpoint Inhibitors

Increasing evidence pinpoints metronomic chemotherapy, a frequent and low dose drug administration with no prolonged drug-free intervals, as a potential tool to fight certain types of cancers. The primary identified targets of metronomic chemotherapy were the tumor endothelial cells involved in angiogenesis. After this, metronomic chemotherapy has been shown to efficiently target the heterogeneous population of tumor cells and, more importantly, elicit the innate and adaptive immune system reverting the "cold" to "hot" tumor immunologic phenotype. Although metronomic chemotherapy is primarily used in the context of a palliative setting, with the development of new immunotherapeutic drugs, a synergistic therapeutic role of the combined metronomic chemotherapy and immune checkpoint inhibitors has emerged at both the preclinical and clinical levels. However, some aspects, such as the dose and the most effective scheduling, still remain unknown and need further investigation. Here, we summarize what is currently known of the underlying anti-tumor effects of the metronomic chemotherapy, the importance of the optimal therapeutic dose and time-exposure, and the potential therapeutic effect of the combined administration of metronomic chemotherapy with checkpoint inhibitors in preclinical and clinical settings.

The pharmacological and biological importance of EZH2 signaling in lung cancer

Up to 18% of cancer-related deaths worldwide are attributed to lung tumor and global burden of this type of cancer is ascending. Different factors are responsible for development of lung cancer such as smoking, environmental factors and genetic mutations. EZH2 is a vital protein with catalytic activity and belongs to PCR2 family. EZH2 has been implicated in regulating gene expression by binding to promoter of targets. The importance of EZH2 in lung cancer is discussed in current manuscript. Activation of EZH2 significantly elevates the proliferation rate of lung cancer. Furthermore, metastasis and associated molecular mechanisms including EMT undergo activation by EZH2 in enhancing the lung cancer progression. The response of lung cancer to therapy can be significantly diminished due to EZH2 upregulation. Since EZH2 increases tumor progression, anti-cancer agents suppressing its expression reduce malignancy. In spite of significant effort in understanding modulatory function of EZH2 on other pathways, it appears that EZH2 can be also regulated and controlled by other factors that are described in current review. Therefore, translating current findings to clinic can improve treatment and management of lung cancer patients.

A survey of open questions in adaptive therapy: Bridging mathematics and clinical translation

Adaptive therapy is a dynamic cancer treatment protocol that updates (or 'adapts') treatment decisions in anticipation of evolving tumor dynamics. This broad term encompasses many possible dynamic treatment protocols of patient-specific dose modulation or dose timing. Adaptive therapy maintains high levels of tumor burden to benefit from the competitive suppression of treatment-sensitive subpopulations on treatment-resistant subpopulations. This evolution-based approach to cancer treatment has been integrated into several ongoing or planned clinical trials, including treatment of metastatic castrate resistant prostate cancer, ovarian cancer, and BRAF-mutant melanoma. In the previous few decades, experimental and clinical investigation of adaptive therapy has progressed synergistically with mathematical and computational modeling. In this work, we discuss 11 open questions in cancer adaptive therapy mathematical modeling. The questions are split into three sections: (1) integrating the appropriate components into mathematical models (2) design and validation of dosing protocols, and (3) challenges and opportunities in clinical translation.

Targeting of the ELR+CXCL/CXCR1/2 Pathway Is a Relevant Strategy for the Treatment of Paediatric Medulloblastomas

Medulloblastoma (MB) is the most common and aggressive paediatric brain tumour. Although the cure rate can be as high as 70%, current treatments (surgery, radio- and chemotherapy) excessively affect the patients' quality of life. Relapses cannot be controlled by conventional or targeted treatments and are usually fatal. The strong heterogeneity of the disease (four subgroups and several subtypes) is related to innate or acquired resistance to reference treatments. Therefore, more efficient and less-toxic therapies are needed. Here, we demonstrated the efficacy of a novel inhibitor (C29) of CXCR1/2 receptors for ELR+CXCL cytokines for the treatment of childhood MB. The correlation between ELR+CXCL/CXCR1/2 expression and patient survival was determined using the R2: Genomics Analysis and Visualization platform. In vitro efficacy of C29 was evaluated by its ability to inhibit proliferation, migration, invasion, and pseudo-vessel formation of MB cell lines sensitive or resistant to radiotherapy. The growth of experimental MB obtained by MB spheroids on organotypic mouse cerebellar slices was also assayed. ELR+CXCL/CXCR1/2 levels correlated with shorter survival. C29 inhibited proliferation, clone formation, CXCL8/CXCR1/2-dependent migration, invasion, and pseudo-vessel formation by sensitive and radioresistant MB cells. C29 reduced experimental growth of MB in the ex vivo organotypic mouse model and crossed the blood-brain barrier. Targeting CXCR1/2 represents a promising therapeutic strategy for the treatment of paediatric MB in first-line treatment or after relapse following conventional therapy.

Revisiting metronomic vinorelbine with mathematical modelling: a Phase I trial in lung cancer

BACKGROUND

A phase Ia/Ib trial of metronomic oral vinorelbine (MOV) driven by a mathematical model was performed in heavily pretreated metastatic Non-Small Cell Lung Cancer or Pleural Mesothelioma patients. Disease Control Rate, progression free survival, toxicity and PK/PD were the main endpoints.

METHODS

Best MOV scheduling was selected using a simplified phenomenological, semi-mechanistic model with a total weekly dose of 150-mg vinorelbine. Computation of individual PK parameters was performed using population approach.

RESULTS

The mathematical model proposed the following metronomic schedule for a 150-mg weekly dose of vinorelbine: 60 mg D1, 30 mg D2, 60 mg D4. A total of 37 heavily pre-treated patients (30 evaluable) were enrolled. Grade III/IV neutropenia was observed in 30% patients. Median PFS was 11 weeks. Disease Control Rate was 73% (i.e.; 13% partial response and 60% stable disease). A large variability in drug exposure (AUC_0-24 h: 53%) and PK parameters (Cl: 83%) were observed among patients. Simulated trough levels after D2 and D4 showed similarly 56-73% variability among patients. Drug exposure was not associated with efficacy, but neutropenia was more frequent in patients with AUC > 250 ng/ml.h. Tumor burden, performance status and neutrophils-to-lymphocyte ratio (NLR) were associated with PFS, suggesting that MOV would be indicated in selected patients. We built a composite score to predict efficacy, mixing baseline tumor size and NLR showing 84% selectivity and 75% specificity.

CONCLUSIONS

MOV was characterized by important variability in drug exposure among patients. However, and despite being all heavily pre-treated, 73% of disease control rate and 11 weeks PFS were achieved with manageable toxicities. PK/PD relationships yielded conflicting results depending on the initial tumor burden and BSA, suggesting that patients should be carefully selected prior to be scheduled for metronomic regimen. Possible role NLR could play as a predictive marker suggests immunomodulating features with MOV.

Metronomic Anti-Cancer Therapy: A Multimodal Therapy Governed by the Tumor Microenvironment

Simple Summary

Metronomic chemotherapy with different mechanisms of action against cancer cells and their microenvironment represents an exceptional holistic cancer treatment. Each type of tumor has its own characteristics, including each individual tumor in each patient. Understanding the complexity of the dynamic interactions that take place between tumor and stromal cells and the microenvironment in tumor progression and metastases, as well as the response of the host and the tumor itself to anticancer therapy, will allow therapeutic actions with long-lasting effects to be implemented using metronomic regimens. This study aims to highlight the complexity of cellular interactions in the tumor microenvironment and summarize some of the preclinical and clinical results that explain the multimodality of metronomic therapy, which, together with its low toxicity, supports an inhibitory effect on the primary tumor and metastases. We also highlight the possible use of nano-therapeutic agents as good partners for metronomic chemotherapy.

Abstract

The concept of cancer as a systemic disease, and the therapeutic implications of this, has gained special relevance. This concept encompasses the interactions between tumor and stromal cells and their microenvironment in the complex setting of primary tumors and metastases. These factors determine cellular co-evolution in time and space, contribute to tumor progression, and could counteract therapeutic effects. Additionally, cancer therapies can induce cellular and molecular responses in the tumor and host that allow them to escape therapy and promote tumor progression. In this study, we describe the vascular network, tumor-infiltrated immune cells, and cancer-associated fibroblasts as sources of heterogeneity and plasticity in the tumor microenvironment, and their influence on cancer progression. We also discuss tumor and host responses to the chemotherapy regimen, at the maximum tolerated dose, mainly targeting cancer cells, and a multimodal metronomic chemotherapy approach targeting both cancer cells and their microenvironment. In a combination therapy context, metronomic chemotherapy exhibits antimetastatic efficacy with low toxicity but is not exempt from resistance mechanisms. As such, a better understanding of the interactions between the components of the tumor microenvironment could improve the selection of drug combinations and schedules, as well as the use of nano-therapeutic agents against certain malignancies.