Delicate Balances in Cancer Chemotherapy: Modeling Immune Recruitment and Emergence of Systemic Drug Resistance

Optimizing chemotherapy treatment outcomes using metaheuristic optimization algorithms: A case study

BACKGROUND

This study explores the dynamics of a mathematical model, utilizing ordinary differential equations (ODE), to depict the interplay between cancer cells and effector cells under chemotherapy. The stability of the equilibrium points in the model is analysed using the Jacobian matrix and eigenvalues. Additionally, bifurcation analysis is conducted to determine the optimal values for the control parameters.

OBJECTIVE

To evaluate the performance of the model and control strategies, benchmarking simulations are performed using the PlatEMO platform.

METHODS

The Pure Multi-objective Optimal Control Problem (PMOCP) and the Hybrid Multi-objective Optimal Control Problem (HMOCP) are two different forms of optimal control problems that are solved using revolutionary metaheuristic optimisation algorithms. The utilization of the Hypervolume (HV) performance indicator allows for the comparison of various metaheuristic optimization algorithms in their efficacy for solving the PMOCP and HMOCP.

RESULTS

Results indicate that the MOPSO algorithm excels in solving the HMOCP, with M-MOPSO outperforming for PMOCP in HV analysis.

CONCLUSION

Despite not directly addressing immediate clinical concerns, these findings indicates that the stability shifts at critical thresholds may impact treatment efficacy.

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.

HOXA9 transcription factor is a double-edged sword: from development to cancer progression

The HOXA9 transcription factor serves as a molecular orchestrator in cancer stemness, epithelial-mesenchymal transition (EMT), metastasis, and generation of the tumor microenvironment in hematological and solid malignancies. However, the multiple modes of regulation, multifaceted functions, and context-dependent interactions responsible for the dual role of HOXA9 as an oncogene or tumor suppressor in cancer remain obscure. Hence, unravelling its molecular complexities, binding partners, and interacting signaling molecules enables us to comprehend HOXA9-mediated transcriptional programs and molecular crosstalk. However, it is imperative to understand its central role in fundamental biological processes such as embryogenesis, foetus implantation, hematopoiesis, endothelial cell proliferation, and tissue homeostasis before designing targeted therapies. Indeed, it presents an enormous challenge for clinicians to selectively target its oncogenic functions or restore tumor-suppressive role without altering normal cellular functions. In addition to its implications in cancer, the present review also focuses on the clinical applications of HOXA9 in recurrence and drug resistance, which may provide a broader understanding beyond oncology, open new avenues for clinicians for accurate diagnoses, and develop personalized treatment strategies. Furthermore, we have also discussed the existing therapeutic options and accompanying challenges in HOXA9-targeted therapies in different cancer types.

Graphical Abstract

Immunogenic chemotherapy: great potential for improving response rates

The activation of anti-tumor immunity is critical in treating cancers. Recent studies indicate that several chemotherapy agents can stimulate anti-tumor immunity by inducing immunogenic cell death and durably eradicate tumors. This suggests that immunogenic chemotherapy holds great potential for improving response rates. However, chemotherapy in practice has only had limited success in inducing long-term survival or cure of cancers when used either alone or in combination with immunotherapy. We think that this is because the importance of dose, schedule, and tumor model dependence of chemotherapy-activated anti-tumor immunity is under-appreciated. Here, we review immune modulation function of representative chemotherapy agents and propose a model of immunogenic chemotherapy-induced long-lasting responses that rely on synergetic interaction between killing tumor cells and inducing anti-tumor immunity. We comb through several chemotherapy treatment schedules, and identify the needs for chemotherapy dose and schedule optimization and combination therapy with immunotherapy when chemotherapy dosage or immune responsiveness is too low. We further review tumor cell intrinsic factors that affect the optimal chemotherapy dose and schedule. Lastly, we review the biomarkers indicating responsiveness to chemotherapy and/or immunotherapy treatments. A deep understanding of how chemotherapy activates anti-tumor immunity and how to monitor its responsiveness can lead to the development of more effective chemotherapy or chemo-immunotherapy, thereby improving the efficacy of cancer treatment.

Characterization of intratumoral tertiary lymphoid structures in pancreatic ductal adenocarcinoma: cellular properties and prognostic significance

BACKGROUND

Tumor-associated tertiary lymphoid structures (TLSs) are functional immune-responsive niches that are not fully understood in pancreatic ductal adenocarcinoma (PDAC).

METHODS

Fluorescent multiplex immunohistochemistry was performed on sequential sections of surgically resected tumor tissues from 380 PDAC patients without preoperative treatment (surgery alone (SA)) and 136 patients pretreated with neoadjuvant treatment (NAT). Multispectral images were processed via machine learning and image processing platforms, inForm V.2.4 and HALO V.3.2; TLS regions were segmented, and the cells were identified and quantified. The cellular composition and immunological properties of TLSs and their adjacent tissues in PDAC were scored and compared, and their association with prognosis was further examined.

RESULTS

Intratumoral TLSs were identified in 21.1% (80/380) of patients in the SA group and 15.4% (21/136) of patients in the NAT group. In the SA group, the presence of intratumoral TLSs was significantly associated with improved overall survival (OS) and progression-free survival. The existence of intratumoral TLSs was correlated with elevated levels of infiltrating CD8+T, CD4+T, B cells and activated immune cells in adjacent tissues. A nomogram model was generated with TLS presence as a variable, which successfully predicted PDAC patient OS in an external validation cohort (n=123). In the NAT group, samples exhibited a lower proportion of B cells and a higher proportion of regulatory T cells within intratumoral TLSs. Additionally, these TLSs were smaller in size, with a lower overall maturation level and reduced immune cell activation, and the prognostic value of TLS presence was insignificant in the NAT cohort.

CONCLUSION

Our study systematically revealed the cellular properties and prognostic values of intratumoral TLSs in PDAC and described the potential impact of NAT on TLS development and function.

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.

Raloxifene and bazedoxifene as selective ALDH1A1 inhibitors to ameliorate cyclophosphamide resistance: A drug repurposing approach

Cyclophosphamide (CP) is one of the most widely used anticancer drugs for various malignancies. However, its long-term use leads to ALDH1A1-mediated inactivation and subsequent resistance which necessitates the development of potential ALDH1A1 inhibitors. Currently, ALDH1A1 inhibitors from different chemical classes have been reported, but these failed to reach the market due to safety and efficacy problems. Developing a new treatment from the ground requires a huge amount of time, effort, and money, therefore it is worthwhile to improve CP efficacy by proposing better adjuvants as ALDH1A1 inhibitors. Herein, the database constituting the FDA-approved drugs with well-established safety and toxicity profiles was screened through already reported machine learning models by our research group. This model is validated for discriminating the ALDH1A1 inhibitors and non-inhibitors. Virtual screening protocol (VS) from this model identified four FDA-approved drugs, raloxifene, bazedoxifene, avanafil, and betrixaban as selective ALDH1A1 inhibitors. The molecular docking, dynamics, and water swap analysis also suggested these drugs to be promising ALDH1A1 inhibitors which were further validated for their CP resistance reversal potential by in-vitro analysis. The in-vitro enzymatic assay results indicated that raloxifene and bazedoxifene selectively inhibited the ALDH1A1 enzyme with IC₅₀ values of 2.35 and 4.41 μM respectively, whereas IC₅₀ values of both the drugs against ALDH2 and ALDH3A1 was >100 μM. Additional in-vitro stu = dies with well-reported ALDH1A1 overexpressing A549 and MIA paCa-2 cell lines suggested that mafosfamide sensitivity was further ameliorated by the combination of both raloxifene and bazedoxifene. Collectively, in-silico and in-vitro studies indicate raloxifene and bazedoxifene act as promising adjuvants with CP that may improve the quality of treatment for cancer patients with minimal toxicities.

A mathematical model of the within-host kinetics of SARS-CoV-2 neutralizing antibodies following COVID-19 vaccination

Compelling evidence continues to build to support the idea that SARS-CoV-2 Neutralizing Antibody (NAb) levels in an individual can serve as an important indicator of the strength of protective immunity against infection. It is not well understood why NAb levels in some individuals remain high over time, while in others levels decline rapidly. In this work, we present a two-state mathematical model of within-host NAb dynamics in response to vaccination. By fitting only four host-specific parameters, the model is able to capture individual-specific NAb levels over time as measured by the AditxtScore™ for NAbs. The model can serve as a foundation for predicting NAb levels in the long-term, understanding connections between NAb levels, protective immunity, and breakthrough infections, and potentially guiding decisions about whether and when a booster vaccination may be warranted.

Mathematical modeling of cancer immunotherapy for personalized clinical translation

Encouraging advances are being made in cancer immunotherapy modeling, especially in the key areas of developing personalized treatment strategies based on individual patient parameters, predicting treatment outcomes and optimizing immunotherapy synergy when used in combination with other treatment approaches. Here we present a focused review of the most recent mathematical modeling work on cancer immunotherapy with a focus on clinical translatability. It can be seen that this field is transitioning from pure basic science to applications that can make impactful differences in patients' lives. We discuss how researchers are integrating experimental and clinical data to fully inform models so that they can be applied for clinical predictions, and present the challenges that remain to be overcome if widespread clinical adaptation is to be realized. Lastly, we discuss the most promising future applications and areas that are expected to be the focus of extensive upcoming modeling studies.

Drug delivery strategies in maximizing anti-angiogenesis and anti-tumor immunity

Metronomic chemotherapy has been shown to elicit anti-tumor immune response and block tumor angiogenesis distinct from that observed with maximal tolerated dose (MTD) therapy. This review delves into the mechanisms behind anti-tumor immunity and seeks to identify the differential effect of dosing regimens, including daily low-dose and medium-dose intermittent chemotherapy (MEDIC), on both innate and adaptive immune populations involved in observed anti-tumor immune response. Given reports of VEGF/VEGFR blockade antagonizing anti-tumor immunity, drug choice, dose, and selective delivery determined by advanced formulations/vehicles are highlighted as potential sources of innovation for identifying anti-angiogenic modalities that may be combined with metronomic regimens without interrupting key immune players in the anti-tumor response. Engineered drug delivery mechanisms that exhibit extended and local release of anti-angiogenic agents both alone and in combination with chemotherapeutic treatments have also been demonstrated to elicit a potent and potentially systemic anti-tumor immune response, favoring tumor regression and stasis over progression. This review examines this interplay between various cancer models, the host immune response, and select anti-cancer agents depending on drug dosing, scheduling/regimen, and delivery modality.

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.

Hypothesis on the possible relevance of the immunogenic cell death in the treatment of gestational trophoblastic neoplasms

The genetic background and the antigenic landscape of cancer cells play a critical role in the response to immunotherapies. A high tumor antigenicity, together with an increased adjuvanticity potentially induced by a peculiar type of cell death, namely immunogenic cell death (ICD), could foster the response to immunogenic therapies. The gestational trophoblastic neoplasm (GTN) is a one-of-a-kind cancer in the oncological landscape due to its exclusive genomic makeup. The prognosis of GTN is significantly better than non-gestational trophoblastic neoplasm (nGTN). Due to its peculiar genetic inheritance, GTN potentially constitutes a singular archetype in the immuno-oncological field.

Predator-Prey in Tumor-Immune Interactions: A Wrong Model or Just an Incomplete One?

Tumor-immune interactions are often framed as predator-prey. This imperfect analogy describes how immune cells (the predators) hunt and kill immunogenic tumor cells (the prey). It allows for evaluation of tumor cell populations that change over time during immunoediting and it also considers how the immune system changes in response to these alterations. However, two aspects of predator-prey type models are not typically observed in immuno-oncology. The first concerns the conversion of prey killed into predator biomass. In standard predator-prey models, the predator relies on the prey for nutrients, while in the tumor microenvironment the predator and prey compete for resources (e.g. glucose). The second concerns oscillatory dynamics. Standard predator-prey models can show a perpetual cycling in both prey and predator population sizes, while in oncology we see increases in tumor volume and decreases in infiltrating immune cell populations. Here we discuss the applicability of predator-prey models in the context of cancer immunology and evaluate possible causes for discrepancies. Key processes include "safety in numbers", resource availability, time delays, interference competition, and immunoediting. Finally, we propose a way forward to reconcile differences between model predictions and empirical observations. The immune system is not just predator-prey. Like natural food webs, the immune-tumor community of cell types forms an immune-web of different and identifiable interactions.

How Should Cancer Models Be Constructed?

Choosing and optimizing treatment strategies for cancer requires capturing its complex dynamics sufficiently well for understanding but without being overwhelmed. Mathematical models are essential to achieve this understanding, and we discuss the challenge of choosing the right level of complexity to address the full range of tumor complexity from growth, the generation of tumor heterogeneity, and interactions within tumors and with treatments and the tumor microenvironment. We discuss the differences between conceptual and descriptive models, and compare the use of predator-prey models, evolutionary game theory, and dynamic precision medicine approaches in the face of uncertainty about mechanisms and parameter values. Although there is of course no one-size-fits-all approach, we conclude that broad and flexible thinking about cancer, based on combined modeling approaches, will play a key role in finding creative and improved treatments.

Comparative efficacy and safety of metronomic chemotherapy in breast cancer: A protocol for network meta-analysis protocol

BACKGROUND

Metronomic chemotherapy (MC) strategy has been used in breast cancer for more than a decade since it was first proposed. The purpose of this study is to systematically evaluate its efficacy and safety for breast cancer patients at various stages, as well as to clarify the most effective medication strategy when applying MC and discover its most sensitive subpopulation in breast cancer patients.

METHOD

We will systematically retrieve random controlled trials evaluating the efficacy and safety of MC in breast cancer on PubMed, Cochrane Library, Embase, and web of science to perform this network meta-analysis. Markov chain Monte Carlo method based on Bayesian Theory will be used to conduct network meta-analysis and the efficacy and safety will be ranked by combining direct and indirect evidence in mixed treatment comparisons. We will assess the quality of literatures with the Cochrane Risk Bias Assessment Tool and assess the strength of the evidence using the GRADE methodology. Data analysis will be completed with the WinBUGS, R, Stata and RevMan softwares.

RESULTS AND CONCLUSION

Through the analysis, we can obtain the ranking of efficacy and safety in different MC strategy, and reveal the specific breast cancer groups that are more sensitive to MC. We access the effectiveness by disease free survival, progress free survival, time to progress, objective response rate, and overall survival, and measure the toxicity by dose-limiting toxicity. The result of our study could provide evidence for clinicians to make a better choice when they consider MC.

INPLASY REGISTRATION NUMBER

INPLASY202140142.

Effects of Chemotherapy Agents on Circulating Leukocyte Populations: Potential Implications for the Success of CAR-T Cell Therapies

Simple Summary

CAR-T cell therapy is a new approach to cancer treatment that is based on manipulating a patient’s own T cells such that they become able to seek and destroy cancer cells in a highly specific manner. This approach is showing remarkable efficacy in treating some types of blood cancers but so far has been much less effective against solid cancers. Here, we review the diverse effects of chemotherapy agents on circulating leukocyte populations and find that, despite some negative effects over the short term, chemotherapy can favourably modulate the immune systems of cancer patients over the longer term. Since blood is the starting material for CAR-T cell production, we propose that these effects could significantly influence the success of manufacturing, and anti-cancer activity, of CAR-T cells. Thus, if timed correctly, chemotherapy-induced changes to circulating immune cells could allow CAR-T cells to unleash more effective anti-tumour responses.

Abstract

Adoptive T-cell therapy using autologous T cells genetically modified to express cancer-specific chimeric antigen receptors (CAR) has emerged as a novel approach for cancer treatment. CAR-T cell therapy has been approved in several major jurisdictions for treating refractory or relapsed cases of B-cell precursor acute lymphoblastic leukaemia and diffuse large B-cell lymphoma. However, in solid cancer patients, several clinical studies of CAR-T cell therapy have demonstrated minimal therapeutic effects, thus encouraging interest in better integrating CAR-T cells with other treatments such as conventional cytotoxic chemotherapy. Increasing evidence shows that not only do chemotherapy drugs have tumoricidal effects, but also significantly modulate the immune system. Here, we discuss immunomodulatory effects of chemotherapy drugs on circulating leukocyte populations, including their ability to enhance cytotoxic effects and preserve the frequency of CD8⁺ T cells and to deplete immunosuppressive populations including regulatory T cells and myeloid-derived suppressor cells. By modulating the abundance and phenotype of leukocytes in the blood (the ‘raw material’ for CAR-T cell manufacturing), we propose that prior chemotherapy could facilitate production of the most effective CAR-T cell products. Further research is required to directly test this concept and identify strategies for the optimal integration of CAR-T cell therapies with cytotoxic chemotherapy for solid cancers.