Modeling putative therapeutic implications of exosome exchange between tumor and immune cells

The Impact of T-cell Exhaustion Dynamics on Tumour-Immune Interactions and Tumour Growth

Tumours evade immune surveillance through a number of different immunosuppressive mechanisms. One such mechanism causes cytotoxic T-cells, a major driving force of the immune system, to differentiate to a state of 'exhaustion', rendering them less effective at killing tumour cells. We present a structured mathematical model that focuses on T-cell exhaustion and its effect on tumour growth. We compartmentalise cytotoxic T-cells into discrete subgroups based on their exhaustion level, which affects their ability to kill tumour cells. We show that the model reduces to a simpler system of ordinary differential equations (ODEs) that describes the time evolution of the total number of T-cells, their mean exhaustion level and the total number of tumour cells. Numerical simulations of the model equations reveal how the exhaustion distribution of T-cells changes over time and how it influences the tumour's growth dynamics. Complementary bifurcation analysis shows how altering key parameters significantly reduces the tumour burden, highlighting exhaustion as a promising target for immunotherapy. Finally, we derive a continuum approximation of the discrete ODE model, which admits analytical solutions that provide complementary insight into T-cell exhaustion dynamics and their effect on tumour growth.

Exosomal miRNAs as Participators of Hexavalent Chromium-Induced Genotoxicity and Immunotoxicity: A Two-Stage Population Study

Genotoxic and immunosuppressive characteristics are central to the carcinogenic profile of hexavalent chromium [Cr(VI)], with dysregulation of circulating exosomal miRNA potentially acting as oncogenes or tumor suppressors or participating in the carcinogenic landscape of heavy metals through immunomodulation. In this two-stage epidemiological investigation, we unveiled for the first time the perturbations of exosomal miRNAs among individuals exposed to Cr(VI), alongside their significant correlations with biomarkers of genetic injury (γ-H2AX positivity in circulating lymphocytes and the urinary 8-OHdG levels) and immunological indicators (immunosuppressive PD-1 expression), which was supported by validation in an external cohort. Employing a support vector machine model, we discerned that exosomal miRNAs, particularly miR-4467, miR-345-5p, miR-144-3p, and miR-206, exhibited a remarkable capacity to delineate the genetic damage stratum within the population with high precision, and the target genes predicted of these miRNAs further elucidated their intricate regulatory interplay with the effector biomarkers. Additionally, employing a Bayesian mediation framework, we observed the intermediary function of miR-4467 in the nexus between chromium exposure and the escalation of urinary 8-OHdG levels (mediation effect: 0.47, P < 0.05). Although our findings suggested a link between extracellular miRNAs and immunosuppressive biomarkers, this association did not achieve validation in the external cohort, possibly due to population heterogeneity. Collectively, this study advanced our understanding of the epigenetic orchestration of health hazards of Cr(VI) by exosomal miRNAs, shedding light on their expression signatures and their intricate interplay with Cr(VI)-induced genetic and immunological perturbations, thus providing novel perspectives on the toxic pathways of heavy metals.

Dynamical Modeling and Qualitative Analysis of a Delayed Model for CD8 T Cells in Response to Viral Antigens

Although the immune effector CD8 T cells play a crucial role in clearance of viruses, the mechanisms underlying the dynamics of how CD8 T cells respond to viral infection remain largely unexplored. Here, we develop a delayed model that incorporates CD8 T cells and infected cells to investigate the functional role of CD8 T cells in persistent virus infection. Bifurcation analysis reveals that the model has four steady states that can finely divide the progressions of viral infection into four states, and endows the model with bistability that has ability to achieve the switch from one state to another. Furthermore, analytical and numerical methods find that the time delay resulting from incubation period of virus can induce a stable low-infection steady state to be oscillatory, coexisting with a stable high-infection steady state in phase space. In particular, a novel mechanism to achieve the switch between two stable steady states, time-delay-based switch, is proposed, where the initial conditions and other parameters of the model remain unchanged. Moreover, our model predicts that, for a certain range of initial antigen load: 1) under a longer incubation period, the lower the initial antigen load, the easier the virus infection will evolve into severe state; while the higher the initial antigen load, the easier it is for the virus infection to be effectively controlled and 2) only when the incubation period is small, the lower the initial antigen load, the easier it is to effectively control the infection progression. Our results are consistent with multiple experimental observations, which may facilitate the understanding of the dynamical and physiological mechanisms of CD8 T cells in response to viral infections.

Exosomal non-coding RNAs: Blueprint in colorectal cancer metastasis and therapeutic targets

Colorectal cancer (CRC) is ranked as the world's third-most prevalent cancer, and metastatic CRC considerably increases cancer-related fatalities globally. A number of complex mechanisms that are strictly controlled at the molecular level are involved in metastasis, which is the primary reason for death in people with CRC. Recently, it has become clear that exosomes, which are small extracellular vesicles released by non-tumorous and tumorigenic cells, play a critical role as communication mediators among tumor microenvironment (TME). To facilitate communication between the TME and cancer cells, non-coding RNAs (ncRNAs) play a crucial role and are recognized as potent regulators of gene expression and cellular processes, such as metastasis and drug resistance. NcRNAs are now recognized as potent regulators of gene expression and many hallmarks of cancer, including metastasis. Exosomal ncRNAs, like miRNAs, circRNAs, and lncRNAs, have been demonstrated to influence a number of cellular mechanisms that contribute to CRC metastasis. However, the molecular mechanisms that link exosomal ncRNAs with CRC metastasis are not well understood. This review highlights the essential roles that exosomal ncRNAs play in the progression of CRC metastatic disease and explores the therapeutic choices that are open to patients who have CRC metastases. However, exosomal ncRNA treatment strategy development is still in its early phases; consequently, additional investigation is required to improve delivery methods and find novel therapeutic targets as well as confirm the effectiveness and safety of these therapies in preclinical and clinical contexts.

Extracellular Vesicles: Investigating the Pathophysiology of Diabetes-Associated Hypertension and Diabetic Nephropathy

Extracellular vesicles (EVs) include exosomes, microvesicles, and apoptotic bodies. EVs are released by all cell types and are found in biological fluids including plasma and urine. Urinary extracellular vesicles (uEVs) are a mixed population of EVs that comprise small EVs that are filtered and excreted, EVs secreted by tubular epithelial cells, and EVs released from the bladder, urethra, and prostate. The packaged cargo within uEVs includes bioactive molecules such as metabolites, lipids, proteins, mRNAs, and miRNAs. These molecules are involved in intercellular communication, elicit changes in intracellular signaling pathways, and play a role in the pathogenesis of various diseases including diabetes-associated hypertension and diabetic nephropathy. uEVs represent a rich source of biomarkers, prognosis markers, and can be loaded with small-molecule drugs as a vehicle for delivery.

Data mining and mathematical models in cancer prognosis and prediction

Cancer is a fetal and complex disease. Individual differences of the same cancer type or the same patient at different stages of cancer development may require distinct treatments. Pathological differences are reflected in tissues, cells and gene levels etc. The interactions between the cancer cells and nearby microenvironments can also influence the cancer progression and metastasis. It is a huge challenge to understand all of these mechanistically and quantitatively. Researchers applied pattern recognition algorithms such as machine learning or data mining to predict cancer types or classifications. With the rapidly growing and available computing powers, researchers begin to integrate huge data sets, multi-dimensional data types and information. The cells are controlled by the gene expressions determined by the promoter sequences and transcription regulators. For example, the changes in the gene expression through these underlying mechanisms can modify cell progressing in the cell-cycle. Such molecular activities can be governed by the gene regulations through the underlying gene regulatory networks, which are essential for cancer study when the information and gene regulations are clear and available. In this review, we briefly introduce several machine learning methods of cancer prediction and classification which include Artificial Neural Networks (ANNs), Decision Trees (DTs), Support Vector Machine (SVM) and naive Bayes. Then we describe a few typical models for building up gene regulatory networks such as Correlation, Regression and Bayes methods based on available data. These methods can help on cancer diagnosis such as susceptibility, recurrence, survival etc. At last, we summarize and compare the modeling methods to analyze the development and progression of cancer through gene regulatory networks. These models can provide possible physical strategies to analyze cancer progression in a systematic and quantitative way.

Recent Advances in Device Engineering and Computational Analysis for Characterization of Cell-Released Cancer Biomarkers

During cancer progression, tumors shed different biomarkers into the bloodstream, including circulating tumor cells (CTCs), extracellular vesicles (EVs), circulating cell-free DNA (cfDNA), and circulating tumor DNA (ctDNA). The analysis of these biomarkers in the blood, known as 'liquid biopsy' (LB), is a promising approach for early cancer detection and treatment monitoring, and more recently, as a means for cancer therapy. Previous reviews have discussed the role of CTCs and ctDNA in cancer progression; however, ctDNA and EVs are rapidly evolving with technological advancements and computational analysis and are the subject of enormous recent studies in cancer biomarkers. In this review, first, we introduce these cell-released cancer biomarkers and briefly discuss their clinical significance in cancer diagnosis and treatment monitoring. Second, we present conventional and novel approaches for the isolation, profiling, and characterization of these markers. We then investigate the mathematical and in silico models that are developed to investigate the function of ctDNA and EVs in cancer progression. We convey our views on what is needed to pave the way to translate the emerging technologies and models into the clinic and make the case that optimized next-generation techniques and models are needed to precisely evaluate the clinical relevance of these LB markers.

The potential role of exosomal circRNAs in the tumor microenvironment: insights into cancer diagnosis and therapy

Exosomes are multifunctional regulators of intercellular communication by carrying various messages under both physiological and pathological status of cancer patients. Accumulating studies have identified the presence of circular RNAs (circRNAs) in exosomes with crucial regulatory roles in diverse pathophysiological processes. Exosomal circRNAs derived from donor cells can modulate crosstalk with recipient cells locally or remotely to enhance cancer development and propagation, and play crucial roles in the tumor microenvironment (TME), leading to significant enhancement of tumor immunity, metabolism, angiogenesis, drug resistance, epithelial mesenchymal transition (EMT), invasion and metastasis. In this review, we describe the advances of exosomal circRNAs and their roles in modulating cancer hallmarks, especially those in the TME. Moreover, clinical application potential of exosomal circRNAs in cancer diagnosis and therapy are highlighted, bridging the gap between basic knowledge and clinical practice.

Towards the First Principles in Biology and Cancer: New Vistas in Computational Systems Biology of Cancer

These days many leading scientists argue for a new paradigm for cancer research and propose a complex systems-view of cancer supported by empirical evidence. As an example, Thea Newman (2021) has applied "the lessons learned from physical systems to a critique of reductionism in medical research, with an emphasis on cancer". It is the understanding of this author that the mesoscale constructs that combine the bottom-up as well as top-down approaches, are very close to the concept of emergence. The mesoscale constructs can be said to be those effective components through which the system allows itself to be understood. A short list of basic concepts related to life/biology fundamentals are first introduced to demonstrate a lack of emphasis on these matters in literature. It is imperative that physical and chemical approaches are introduced and incorporated in biology to make it more conceptually sound, quantitative, and based on the first principles. Non-equilibrium thermodynamics is the only tool currently available for making progress in this direction. A brief outline of systems biology, the discovery of emergent properties, and metabolic modeling are introduced in the second part. Then, different cancer initiation concepts are reviewed, followed by application of non-equilibrium thermodynamics in the metabolic and genomic analysis of initiation and development of cancer, stressing the endogenous network hypothesis (ENH). Finally, extension of the ENH is suggested to include a cancer niche (exogenous network hypothesis). It is expected that this will lead to a unifying systems-biology approach for a future combination of the analytical and synthetic arms of two major hypotheses of cancer models (SMT and TOFT).

A Voxel Model to Decipher the Role of Molecular Communication in the Growth of Glioblastoma Multiforme

Glioblastoma Multiforme (GBM), the most malignant human tumour, can be defined by the evolution of growing bio-nanomachine networks within an interplay between self-renewal (Grow) and invasion (Go) potential of mutually exclusive phenotypes of transmitter and receiver cells. Herein, we present a mathematical model for the growth of GBM tumour driven by molecule-mediated inter-cellular communication between two populations of evolutionary bio-nanomachines representing the Glioma Stem Cells (GSCs) and Glioma Cells (GCs). The contribution of each subpopulation to tumour growth is quantified by a voxel model representing the end to end inter-cellular communication models for GSCs and progressively evolving invasiveness levels of glioma cells within a network of diverse cell configurations. Mutual information, information propagation speed and the impact of cell numbers and phenotypes on the communication output and GBM growth are studied by using analysis from information theory. The numerical simulations show that the progression of GBM is directly related to higher mutual information and higher input information flow of molecules between the GSCs and GCs, resulting in an increased tumour growth rate. These fundamental findings contribute to deciphering the mechanisms of tumour growth and are expected to provide new knowledge towards the development of future bio-nanomachine-based therapeutic approaches for GBM.

Extracellular Vesicles and Pancreatic Cancer: Insights on the Roles of miRNA, lncRNA, and Protein Cargos in Cancer Progression

Pancreatic cancer (PC) is among the most devastating digestive tract cancers worldwide. This cancer is characterized by poor diagnostic detection, lack of therapy, and difficulty in predicting tumorigenesis progression. Although mutations of key oncogenes and oncosuppressor involved in tumor growth and in immunosurveillance escape are known, the underlying mechanisms that orchestrate PC initiation and progression are poorly understood or still under debate. In recent years, the attention of many researchers has been concentrated on the role of extracellular vesicles and of a particular subset of extracellular vesicles, known as exosomes. Literature data report that these nanovesicles are able to deliver their cargos to recipient cells playing key roles in the pathogenesis and progression of many pancreatic precancerous conditions. In this review, we have summarized and discussed principal cargos of extracellular vesicles characterized in PC, such as miRNAs, lncRNAs, and several proteins, to offer a systematic overview of their function in PC progression. The study of extracellular vesicles is allowing to understand that investigation of their secretion and analysis of their content might represent a new and potential diagnostic and prognostic tools for PC.

Extracellular Vesicles in Oncology: from Immune Suppression to Immunotherapy

Exosomes are involved in cell-to-cell communication and play a crucial role in cellular physiology. The role of exosomes in cancer has been widely explored. Tumor cells have evolved and adapted to evade the immune response. The study of the immune system's modulations in favor of rogue tumor cells led to the development of a novel immunotherapeutic strategy targeting the immune checkpoint proteins (ICPs). In clinical settings, the response to ICP therapy has been inconsistent and is difficult to predict. Quantitating the targeted ICPs through immunohistochemistry is one approach, but is not pragmatic in a clinical setting and is often not sensitive. Examining the molecules present in bodily fluids to determine ICP treatment response, "liquid biopsy" is a convenient alternative. The term "liquid biopsy" refers to circulating tumor cells (CTCs), extracellular vesicles (EVs), non-coding (nc) RNA, circulating tumor DNA (ctDNA), circulating free DNA (cfDNA), etc. EVs includes exosomes, microvesicles, and oncosomes. Herein, we focus on exosomes isolated from bodily fluids and their use in liquid biopsy. Due to their unique ability to transfer bioactive molecules and perturb the physiology of recipient cells, exosomes have garnered attention for their immune modulation role and as a resource to identify molecules associated with liquid biopsy-based diagnostic methods. In this review, we examine the putative role of exosomes and their cargo in influencing the immune system. We discuss the immune and tumor cells present in the tumor microenvironment (TME), and the exosomes derived from these cells to understand how they participate in creating the immune-suppressive TME. Additionally, use of exosomes in liquid biopsy-based methods to measure the treatment response elicited by immunotherapy is discussed. Finally, we describe how exosomes have been used to develop immune therapies, especially cell-free vaccines, for cancer treatment.

The potential roles of exosomes in pancreatic cancer initiation and metastasis

Pancreatic cancer (PaCa) is an insidious and highly metastatic malignancy, with a 5-year survival rate of less than 5%. So far, the pathogenesis and progression mechanisms of PaCa have been poorly characterized. Exosomes correspond to a class of extracellular nanovesicles, produced by a broad range of human somatic and cancerous cells. These particular nanovesicles are mainly composed by proteins, genetic substances and lipids, which mediate signal transduction and material transport. A large number of studies have indicated that exosomes may play decisive roles in the occurrence and metastatic progression of PaCa. This article summarizes the specific functions of exosomes and their underlying molecular mechanisms in mediating the initiation and metastatic capability of PaCa.

Small Extracellular Vesicles Containing miR-381-3p from Keratinocytes Promote T Helper Type 1 and T Helper Type 17 Polarization in Psoriasis

T helper cells are crucial for psoriasis pathogenesis. Communication between T cells and psoriatic keratinocytes (KCs) helps drive the Th1 and Th17 response, but the underlying mechanism is not well-understood. Small extracellular vesicles (sEVs) are emerging mediators of intercellular communication. Here, we investigated the role of KC-derived sEVs in the Th1 and Th17 response in psoriasis. We isolated and characterized sEVs from KCs under normal (untreated) and psoriatic (cytokine-treated) conditions. sEVs under both conditions exhibited a cup-shaped morphology and expressed markers CD63 and CD81. sEVs from cytokine-treated KCs can be taken up by CD4⁺T cells, leading to the induction of Th1 and Th17 polarization. Small RNA sequencing revealed that miR-381-3p was significantly increased in sEVs from cytokine-treated KCs and in CD4⁺T cells from patients with psoriasis. Moreover, sEVs-containing miR-381-3p was responsible for sEVs-induced Th1 and Th17 polarization. We further found that the miR-381-3p targeted to the 3' untranslated region of E3 ubiquitin-ligase UBR5 and stabilized RORγt protein expression. It also targeted to the 3' untranslated region of FOXO1, associated with activated T-bet and RORγt transcription. Taken together, we propose that psoriatic KCs transfer miR-381-3p to CD4⁺T cells through sEVs, inducing Th1 and Th17 polarization and promoting psoriasis development. Our findings motivate future studies of KC-derived sEVs or their specific cargoes as therapeutic candidates for psoriasis.

Modeling of Modulated Exosome Release From Differentiated Induced Neural Stem Cells for Targeted Drug Delivery

A novel implantable and externally controllable stem-cell-based platform for the treatment of Glioblastoma brain cancer has been proposed to bring hope to patients who suffer from this devastating cancer type. Induced Neural Stem Cells (iNSCs), known to have potent therapeutic effects through exosomes-based molecular communication, play a pivotal role in this platform. Transplanted iNSCs demonstrate long-term survival and differentiation into neurons and glia which then fully functionally integrate with the existing neural network. Recent studies have shown that specific types of calcium channels in differentiated neurons and astrocytes are inhibited or activated upon cell depolarization leading to the increased intracellular calcium concentration levels which, in turn, interact with mobilization of multivesicular bodies and exosomal release. In order to provide a platform towards treating brain cancer with the optimum therapy dosage, we propose mathematical models to compute the therapeutic exosomal release rate that is modulated by cell stimulation patterns applied from the external wearable device. This study serves as an initial and required step in the evaluation of controlled exosomal secretion and release via induced stimulation with electromagnetic, optical and/or ultrasonic waves.

A Novel Model of Cancer Drug Resistance: Oncosomal Release of Cytotoxic and Antibody-Based Drugs

Extracellular vesicles (EVs), such as exosomes or oncosomes, often carry oncogenic molecules derived from tumor cells. In addition, accumulating evidence indicates that tumor cells can eject anti-cancer drugs such as chemotherapeutics and targeted drugs within EVs, a novel mechanism of drug resistance. The EV-releasing drug resistance phenotype is often coupled with cellular dedifferentiation and transformation in cells undergoing epithelial-mesenchymal transition (EMT), and the adoption of a cancer stem cell phenotype. The release of EVs is also involved in immunosuppression. Herein, we address different aspects by which EVs modulate the tumor microenvironment to become resistant to anticancer and antibody-based drugs, as well as the concept of the resistance-associated secretory phenotype (RASP).

Circular RNAs in the tumour microenvironment

BACKGROUND

Circular RNAs (circRNAs) are a new class of endogenous non-coding RNAs (ncRNAs) widely expressed in eukaryotic cells. Mounting evidence has highlighted circRNAs as critical regulators of various tumours. More importantly, circRNAs have been revealed to recruit and reprogram key components involved in the tumour microenvironment (TME), and mediate various signaling pathways, thus affecting tumourigenesis, angiogenesis, immune response, and metastatic progression. In this review, we briefly introduce the biogenesis, characteristics and classification of circRNAs, and describe various mechanistic models of circRNAs. Further, we provide the first systematic overview of the interplay between circRNAs and cellular/non-cellular counterparts of the TME and highlight the potential of circRNAs as prospective biomarkers or targets in cancer clinics. Finally, we discuss the biological mechanisms through which the circRNAs drive development of resistance, revealing the mystery of circRNAs in drug resistance of tumours.

SHORT CONCLUSION

Deep understanding the emerging role of circRNAs and their involvements in the TME may provide potential biomarkers and therapeutic targets for cancer patients. The combined targeting of circRNAs and co-activated components in the TME may achieve higher therapeutic efficiency and become a new mode of tumour therapy in the future.

Exosomal lncRNAs and cancer: connecting the missing links

Motivation

Extracellular vesicles (EVs), including exosomes and microvesicles, are potent and clinically valuable tools for early diagnosis, prognosis and potentially the targeted treatment of cancer. The content of EVs is closely related to the type and status of the EV-secreting cell. Circulating exosomes are a source of stable RNAs including mRNAs, microRNAs and long non-coding RNAs (lncRNAs).

Results

This review outlines the links between EVs, lncRNAs and cancer. We highlight communication networks involving the tumor microenvironment, the immune system and metastasis. We show examples supporting the value of exosomal lncRNAs as cancer biomarkers and therapeutic targets. We demonstrate how a system biology approach can be used to model cell-cell communication via exosomal lncRNAs and to simulate effects of therapeutic interventions. In addition, we introduce algorithms and bioinformatics resources for the discovery of tumor-specific lncRNAs and tools that are applied to determine exosome content and lncRNA function. Finally, this review provides a comprehensive collection and guide to databases for exosomal lncRNAs.

Supplementary information

Supplementary data are available at Bioinformatics online.

Modeling heterogeneous tumor growth dynamics and cell-cell interactions at single-cell and cell-population resolution

Cancer is a complex, dynamic disease that despite recent advances remains mostly incurable. Inter- and intratumoral heterogeneity are generally considered major drivers of therapy resistance, metastasis, and treatment failure. Recent advances in high-throughput experimentation have produced a wealth of data on tumor heterogeneity and researchers are increasingly turning to mathematical modeling to aid in the interpretation of these complex datasets. In this mini-review, we discuss three important classes of approaches for modeling cellular dynamics within heterogeneous tumors: agent-based models, population dynamics, and multiscale models. An important new focus, for which we provide an example, is the role of intratumoral cell-cell interactions.

The emerging role of exosomes in multiple myeloma

Multiple myeloma (MM), one of the most prevalent hematological malignancies, accounts for approximately 10% of all blood cancers. In spite of the recent advancements in MM therapy, this malignancy of terminally differentiated plasma cells (PCs) continues to remain a hard-to-cure disease due to the emergence of drug resistance and frequent relapses. It is now well-established that the tumor-supportive involvement of the bone marrow microenvironment (BMM) including the cellular and non-cellular elements are the major causes behind treatment failures of MM as well as its main complications such as osteolytic bone loss. Exosomes (EXs) are membranous structures that carry signaling molecules and have recently received a great deal of attention as important mediators of inter-cellular communication in health and disease. EXs involve in the growth and drug resistance of many tumors via delivering their rich contents of bioactive molecules including miRNAs, growth factors, cytokines, signaling molecules, etc. With regard to MM, many studies have reported that EXs are among the main culprits playing key roles in the vicious network within the BMM of these patients. The main producers of EXs that largely contribute to MM pathogenesis are bone marrow stromal cells (BMSCs) as well as MM cells themselves. These cell types produce large amounts of EXs that affect a variety of target cells including natural killer (NK) cells, osteoclasts (OCs) and osteoblasts (OBs) to the advantage of tumor survival and progression. These EXs contain a different profile of proteins and miRNAs from that of EXs obtained from their counterparts in healthy individuals. MM patients exhibit distinguishable elevations in some of their contents such as miR-21, miR-146a, let-7b and miR-18a, while some molecules like miR-15a are markedly downregulated in EXs of MM patients compared to healthy individuals. These findings make EXs desirable biomarkers for early prediction of disease progression and drug resistance in the context of MM. On the other hand, due to the tumor-supportive role of EXs, targeting these structures in parallel to the conventional therapeutic regimens may be a promising approach to a successful anti-MM therapy. In the present work, an extensive review of the literature has been carried out to highlight the recent advances in the field.

Development of a human immuno-oncology therapeutic agent targeting HER2: targeted delivery of granzyme B

Background

Immunotherapeutic approaches designed to augment T and B cell mediated killing of tumor cells has met with clinical success in recent years suggesting tremendous potential for treatment in a broad spectrum of tumor types. After complex recognition of target cells by T and B cells, delivery of the serine protease granzyme B (GrB) to tumor cells comprises the cytotoxic insult resulting in a well-characterized, multimodal apoptotic cascade.

Methods

We designed a recombinant fusion construct, GrB-Fc-4D5, composed of a humanized anti-HER2 scFv fused to active GrB for recognition of tumor cells and internal delivery of GrB, simulating T and B cell therapy. We assessed the construct’s antigen-binding specificity and GrB enzymatic activity, as well as in vitro cytotoxicity and internalization into target and control cells. We also assessed pharmacokinetic and toxicology parameters in vivo.

Results

GrB-Fc-4D5 was highly cytotoxic to Her2 positive cells such as SKBR3, MCF7 and MDA-MB-231 with IC₅₀ values of 56, 99 and 27 nM, respectively, and against a panel of HER2+ cell lines regardless of endogenous expression levels of the PI-9 inhibitor. Contemporaneous studies with Kadcyla demonstrated similar levels of in vitro activity against virtually all cells tested. GrB-Fc-4D5 internalized rapidly into target SKOV3 cells within 1 h of exposure rapidly delivering GrB to the cytoplasmic compartment. In keeping with its relatively high molecular weight (160 kDa), the construct demonstrated a terminal-phase serum half-life in mice of 39.2 h. Toxicity studies conducted on BALB/c mice demonstrated no statistically significant changes in SGPT, SGOT or serum LDH. Histopathologic analysis of tissues from treated mice demonstrated no drug-related changes in any tissues examined.

Conclusion

GrB-Fc-4D5 shows excellent, specific cytotoxicity and demonstrates no significant toxicity in normal, antigen-negative murine models. This construct constitutes a novel approach against HER2-expressing tumors and is an excellent candidate for further development.

Uncovering the underlying physical mechanism for cancer-immunity of MHC class I diversity

The cancer cells are heterogeneous populated, which can be classified as MHC class I positive and MHC I class negative. They influence the immune system differently. In this work, we build a core cancer-immune circuit of MHC class I diversity including MHC class I positive cancer type, MHC I class I negative cancer type and 4 immune cell types to uncover the underlying mechanism of the cancer immunity based on the underlying landscape topography. We quantify four steady state attractors, normal state, two low cancer states and a high cancer state. The landscape topography changes upon changes in cancer self-activation and the related killing rate of the killer cells are illustrated. It demonstrates that the competition between the two cancer cell types. We simulate the tumorigenesis and development of cancer according to its biological process and classify these into 7 stages. This landscape framework provides a quantitative way to understand characteristics of these two cancer cell types under immune microenvironment and the underlying physical mechanisms of cancer cell evolution along cancer development.

Proteomic Profiling of Secreted Proteins, Exosomes, and Microvesicles in Cell Culture Conditioned Media

Secreted proteins are of tremendous biological interest since they can act as ligands for receptors to activate downstream signalling cascades or be used as biomarkers if altered abundance is correlated with a specific pathological state. Proteins can be secreted either as soluble molecules or as part of extracellular vesicles (i.e., exosomes or microvesicles). The complete proteomic profiling of secretomes requires analysis of secreted proteins and extracellular vesicles. Hence, the method described here enriches for microvesicles, exosomes, and secreted proteins from conditioned media using differential centrifugation. The three fractions are then analyzed by mass spectrometry-based proteomics for in-depth characterization and comparison of the protein secretome of cell lines.

Modifying exosome release in cancer therapy: How can it help?

The reciprocal interactions of cancer cells with their microenvironment constitute an inevitable aspect of tumor development, progression and response to treatment in all cancers. Such bilateral transactions also serve as the key scenario underlying the development of drug resistance in many cases finally determining the fate of the disease and survival. In this view, a class of extracellular vesicles (EV) known as exosomes (EX) have been shown in the past few years to be important mediators of local and remote cell-to-cell contact changing the activity of their target cells by introducing their content of proteins, non-coding RNAs, and membrane-associated small molecules. In addition to the direct targeting of cancer cells, which has been routinely undertaken by different means to date, parallel attempts to change the signaling network governed by tumor-derived exosomes (TDE) may offer a promising potential to be utilized in cancer therapy. TDE drive diverse functions in the body, most of which have been shown to act to the advantage of tumor progression; however, there are also several studies that report the good aspects of TDE the interruption of which may result in undesirable outcomes. In the present paper, we made an effort to address this important issue by reviewing the very recent literature on different aspects of EX biogenesis and regulation and the various bodily effects of TDE which have been uncovered to date. Moreover, we have reviewed the possible interventions that can be made in TDE release as an important stage of EX biogenesis. Finally, keeping a criticizing view, the advantages and disadvantages of such interventions have been discussed and the future prospect in the field has been outlined.

Uncovering the underlying mechanism of cancer tumorigenesis and development under an immune microenvironment from global quantification of the landscape

The study of the cancer-immune system is important for understanding tumorigenesis and the development of cancer and immunotherapy. In this work, we build a comprehensive cancer-immune model including both cells and cytokines to uncover the underlying mechanism of cancer immunity based on landscape topography. We quantify three steady-state attractors, normal state, low cancer state and high cancer state, for the innate immunity and adaptive immunity of cancer. We also illustrate the cardinal inhibiting cancer immunity interactions and promoting cancer immunity interactions through global sensitivity analysis. We simulate tumorigenesis and the development of cancer and classify these into six stages. The characteristics of the six stages can be classified further into three groups. These correspond to the escape, elimination and equilibrium phases in immunoediting, respectively. Under specific cell-cell interactions strength oscillations emerge. We found that tumorigenesis and cancer recovery processes may need to go through cancer-immune oscillation, which consumes more energy. Based on the cancer-immune landscape, we predict three types of cells and two types of cytokines for cancer immunotherapy as well as combination immunotherapy. This landscape framework provides a quantitative way to understand the underlying mechanisms of the interplay between cancer and the immune system for cancer tumorigenesis and development.

Dendritic cells loaded with HeLa-derived exosomes simulate an antitumor immune response

The aim of the present study was to investigate the effect of loading dendritic cells (DCs) with HeLa-derived exosomes on cytotoxic T-lymphocyte (CTL) responses, and the cytotoxic effects of CTL responses on the HeLa cell line. Ultrafiltration centrifugation combined with sucrose density gradient ultracentrifugation was applied to isolate exosomes (HeLa-exo) from the supernatant of HeLa cells. Morphological features of HeLa-exo were identified by transmission electron microscopy (TEM), and the expression of cluster of differentiation (CD)63 was detected by western blotting. Next, monocytes were isolated from peripheral blood and cultured with the removal of adherent cells to induce DC proliferation. DCs were then phenotypically characterized by flow cytometry. Finally, MTT assays were performed to analyze the effects of DCs loaded with HeLa-exo on T cell proliferation and cytotoxicity assays to evaluate the effect of CTL responses on HeLa cells. TEM revealed that HeLa-exo exhibit typical cup-shaped morphology with a diameter range of 30-100 nm. It was also identified that the CD63 surface antigen is expressed on HeLa-exo. Furthermore, monocyte-derived DCs were able to express CD1a, suggesting that DC induction was a success. DCs exhibited hair-like protrusions and other typical dendritic cell morphology. Furthermore, DCs loaded with HeLa-exo could enhance CTL proliferation and the cytotoxic activity of CTLs compared with DCs without HeLa-exo (P<0.05). In conclusion, DCs loaded with HeLa-exo may promote T cell proliferation and induce CTL responses to inhibit the growth of cervical cancer cells in vitro.

Identifying the optimal anticancer targets from the landscape of a cancer-immunity interaction network

Cancer immunotherapy, an approach of targeting immune cells to attack tumor cells, has been suggested to be a promising way for cancer treatment recently. However, the successful application of this approach warrants a deeper understanding of the intricate interplay between cancer cells and the immune system. Especially, the mechanisms of immunotherapy remain elusive. In this work, we constructed a cancer-immunity interplay network by incorporating interactions among cancer cells and some representative immune cells, and uncovered the potential landscape of the cancer-immunity network. Three attractors emerge on the landscape, representing the cancer state, the immune state, and the hybrid state, which can correspond to escape, elimination, and equilibrium phases in the immunoediting theory, respectively. We quantified the transition processes between the cancer state and the immune state by calculating transition actions and identifying the corresponding minimum action paths (MAPs) between these two attractors. The transition actions, directly calculated from the high dimensional system, are correlated with the barrier heights from the landscape, but provide a more precise description of the dynamics of a system. By optimizing the transition actions from the cancer state to the immune state, we identified some optimal combinations of anticancer targets. Our combined approach of the landscape and optimization of transition actions offers a framework to study the stochastic dynamics and identify the optimal combination of targets for the cancer-immunity interplay, and can be applied to other cell communication networks or gene regulatory networks.

Exosomes, DAMPs and miRNA: Features of Stress Physiology and Immune Homeostasis

Psychological/physical stressors and local tissue damage increase inflammatory proteins in tissues and blood in humans and animals, in the absence of pathogenic disease. Stress-evoked cytokine/chemokine responses, or sterile inflammation, can facilitate host survival and/or negatively affect health, depending on context. Recent evidence supports the hypothesis that systemic stress-evoked sterile inflammation is initiated by the sympathetic nervous system, resulting in the elevation of exosome-associated immunostimulatory endogenous danger/damage associated molecular patterns (DAMPs) and a reduction in immunoinhibitory miRNA, which are carried in the circulation to tissues throughout the body. We propose that sterile inflammation should be considered an elemental feature of the stress response and that circulating exosomes transporting immunomodulatory signals, may play a role fundamental role in immune homeostasis.

Label-free Proteomic Analysis of Exosomes Derived from Inducible Hepatitis B Virus-Replicating HepAD38 Cell Line

Hepatitis B virus (HBV) infection is a major health problem worldwide. Recent evidence suggests that some viruses can manipulate the infection process by packing specific viral and cellular components into exosomes, small nanometer-sized (30-150 nm) vesicles secreted from various cells. However, the impact of HBV replication on the content of exosomes produced by hepatocytes has not been fully delineated. In this work, an HBV-inducible cell line HepAD38 was used to directly compare changes in the protein content of exosomes secreted from HepAD38 cells with or without HBV replication. Exosomes were isolated from supernantants of HepAD38 cells cultured with or without doxycycline (dox) and their purity was confirmed by transmission electron microscopy (TEM) and Western immunoblotting assays. Ion-intensity based label-free LC-MS/MS quantitation technologies were applied to analyze protein content of exosomes from HBV replicating cells [referred as HepAD38 (dox^-)-exo] and from HBV nonreplicating cells [referred as HepAD38 (dox⁺)-exo]. A total of 1412 exosomal protein groups were identified, among which the abundance of 35 proteins was significantly changed following HBV replication. Strikingly, 5 subunit proteins from the 26S proteasome complex, including PSMC1, PSMC2, PSMD1, PSMD7 and PSMD14 were consistently enhanced in HepAD38 (dox^-)-exo. Bioinformatic analysis of differential exosomal proteins confirmed the significant enrichment of components involved in the proteasomal catabolic process. Proteasome activity assays further suggested that HepAD38 (dox^-)-exo had enhanced proteolytic activity compared with HepAD38 (dox⁺)-exo. Furthermore, human peripheral monocytes incubated with HepAD38 (dox^-)-exo induced a significantly lower level of IL-6 secretion compared with IL-6 levels from HepAD38 (dox⁺)-exo. Irreversible inhibition of proteasomal activity within exosomes restored higher production of IL-6 by monocytes, suggesting that transmission of proteasome subunit proteins by HepAD38 (dox^-)-exo might modulate the production of pro-inflammatory molecules in the recipient monocytes. These results revealed the composition and potential function of exosomes produced during HBV replication, thus providing a new perspective on the role of exosomes in HBV-host interaction.

Circulating MicroRNAs in Graves' Disease in Relation to Clinical Activity

BACKGROUND

Understanding the roles of circulating microRNAs (miRNAs) can provide important and novel information regarding disease pathogenesis and a patient's clinical condition. Circulating miRNAs, such as exosomal miRNA, may regulate various bioactivities related to intercellular communication. However, the circulation of miRNAs in Graves' disease (GD) in relation to disease activity has never been elucidated. This study aimed to identify circulating miRNAs in GD in relation to disease activity and whether their exosomes play a role in the pathogenesis of GD.

METHODS

Circulating miRNAs were measured in serum obtained from seven intractable GD patients, seven GD patients in remission, and seven healthy controls using the miScript miRNA PCR Array. Altered miRNAs selected from array data were validated in 65 subjects. To investigate exosome biology, peripheral blood mononuclear cells (PBMCs) were incubated with exosomes isolated from the subjects' sera. mRNAs were quantified for cytokines using quantitative real-time polymerase chain reaction.

RESULTS

Circulating miR-23b-5p and miR-92a-39 were increased in GD patients in remission compared with intractable GD patients (p < 0.05). On the other hand, let-7g-3p and miR-339-5p were decreased in GD patients in remission compared with intractable GD patients (p < 0.05). Exosomes from intractable GD patients stimulated mRNA expression for IL-1β and TNF-α compared with GD patients in remission or healthy controls.

CONCLUSIONS

This study demonstrates that different levels of circulating miRNAs are associated with intractable GD. Moreover, serum exosomes of patients with intractable GD may activate immune cells, which may play an important role in GD pathogenesis.

The Novel Methods for Analysis of Exosomes Released from Endothelial Cells and Endothelial Progenitor Cells

Exosomes (EXs) are cell-derived vesicles that mediate cell-cell communication and could serve as biomarkers. Here we described novel methods for purification and phenotyping of EXs released from endothelial cells (ECs) and endothelial progenitor cells (EPCs) by combining microbeads and fluorescence quantum dots (Q-dots®) techniques. EXs from the culture medium of ECs and EPCs were isolated and detected with cell-specific antibody conjugated microbeads and second antibody conjugated Q-dots by using nanoparticle tracking analysis (NTA) system. The sensitivities of the cell origin markers for ECs (CD105, CD144) and EPCs (CD34, KDR) were evaluated. The sensitivity and specificity were determined by using positive and negative markers for EXs (CD63), platelets (CD41), erythrocytes (CD235a), and microvesicles (Annexin V). Moreover, the methods were further validated in particle-free plasma and patient samples. Results showed that anti-CD105/anti-CD144 and anti-CD34/anti-KDR had the highest sensitivity and specificity for isolating and detecting EC-EXs and EPC-EXs, respectively. The methods had the overall recovery rate of over 70% and were able to detect the dynamical changes of circulating EC-EXs and EPC-EXs in acute ischemic stroke. In conclusion, we have developed sensitive and specific microbeads/Q-dots fluorescence NTA methods for EC-EX and EPC-EX isolation and detection, which will facilitate the functional study and biomarker discovery.

Periodic, Quasi-periodic and Chaotic Dynamics in Simple Gene Elements with Time Delays

Regulatory gene circuit motifs play crucial roles in performing and maintaining vital cellular functions. Frequently, theoretical studies of gene circuits focus on steady-state behaviors and do not include time delays. In this study, the inclusion of time delays is shown to entirely change the time-dependent dynamics for even the simplest possible circuits with one and two gene elements with self and cross regulations. These elements can give rise to rich behaviors including periodic, quasi-periodic, weak chaotic, strong chaotic and intermittent dynamics. We introduce a special power-spectrum-based method to characterize and discriminate these dynamical modes quantitatively. Our simulation results suggest that, while a single negative feedback loop of either one- or two-gene element can only have periodic dynamics, the elements with two positive/negative feedback loops are the minimalist elements to have chaotic dynamics. These elements typically have one negative feedback loop that generates oscillations, and another unit that allows frequent switches among multiple steady states or between oscillatory and non-oscillatory dynamics. Possible dynamical features of several simple one- and two-gene elements are presented in details. Discussion is presented for possible roles of the chaotic behavior in the robustness of cellular functions and diseases, for example, in the context of cancer.

The Dichotomy of Tumor Exosomes (TEX) in Cancer Immunity: Is It All in the ConTEXt?

Exosomes are virus-sized nanoparticles (30–130 nm) formed intracellularly as intravesicular bodies/intralumenal vesicles within maturing endosomes (“multivesicular bodies”, MVBs). If MVBs fuse with the cell’s plasma membrane, the interior vesicles may be released extracellularly, and are termed “exosomes”. The protein cargo of exosomes consists of cytosolic, membrane, and extracellular proteins, along with membrane-derived lipids, and an extraordinary variety of nucleic acids. As such, exosomes reflect the status and identity of the parent cell, and are considered as tiny cellular surrogates. Because of this closely entwined relationship between exosome content and the source/status of the parental cell, conceivably exosomes could be used as vaccines against various pathologies, as they contain antigens associated with a given disease, e.g., cancer. Tumor-derived exosomes (TEX) have been shown to be potent anticancer vaccines in animal models, driving antigen-specific T and B cell responses, but much recent literature concerning TEX strongly places the vesicles as powerfully immunosuppressive. This dichotomy suggests that the context in which the immune system encounters TEX is critical in determining immune stimulation versus immunosuppression. Here, we review literature on both sides of this immune coin, and suggest that it may be time to revisit the concept of TEX as anticancer vaccines in clinical settings.

High-efficiency Generation of Multiple Short Noncoding RNA in B-cells and B-cell-derived Extracellular Vesicles

Short noncoding (snc)RNAs are important new players in the landscape of biologics with therapeutic potential. Recently, we reported on a new method for the synthesis and delivery of snc RNA in B-cells transfected with plasmid DNA. Here using the same approach, we demonstrate that B-cells can be programmed for the enforced biogenesis and synchronous release of multiple sncRNAs. Our data show that this goal is feasible and that multiple sncRNA are released in the extracellular compartment in amounts comparable to those from B-cells programmed to express and secrete one scnRNA only. Furthermore, we found that the cargo of extracellular vescicles (EVs) isolated from programmed B-cells is remarkably enriched for multiple sncRNA. On average, we found that the content of multiple sncRNAs in EVs is 3.6 copynumber/EV. Collectively, we demonstrate that B-cells can be easily programmed toward the synthesis and release of multiple sncRNAs, including sncRNA-laden EVs, efficiently and specifically.

Hypotheses of cancer weakening and origin

Approximately 2.7 billion years ago, cyanobacteria began producing oxygen by photosynthesis. Any free oxygen they produced was chemically captured by dissolved iron or organic matter. There was no ozone layer to protect living species against the radiation from space. Eukaryotic cells lived in water, under hypoxic environments, and metabolized glucose by fermentation. The Great Oxygenation Event (GOE) describes the point when oxygen sinks became saturated. This massive oxygenation of the Earth occurred approximately half a billion years ago. Species that evolved after the GOE are characterized by aerobic metabolism. Mammals evolved approximately a few hundred million years ago, with the ancient eukaryotic genes deeply embedded in their genome.

Many genes have been exchanged by horizontal gene transfer (HGT) throughout the history of cellular evolution. Mammals have been invaded by viruses, and while viral genetic relics are embedded in mammalian junk genes, not all junk genes are genetic relics of viruses. These viral relics have been inactivated through evolution and have little impact on mammalian life. However, there is evidence to suggest that these viral genetic relics are linked to cancer.

This hypothesis states that cancer develops when cell reproduction becomes defective because of the active involvement of viral genes, in a process similar to genetic engineering. Cancer cells are amalgamations of genetically modified organisms (GMOs). There are two main groups in cancer development. One group of cells arises by genetic engineering of a viral genetic relic, such as endogenous retroviruses (ERVs), which evolved after oxygenation of the atmosphere. This group is referred to here as genetically modified organisms from viral genes (GMOV). GMOVs may be inhibited by anticancer drugs. The second group arises by engineering of the genes of ancient eukaryotes, which existed prior to the oxygenation of the Earth. This second group is referred to as genetically modified organisms from ancient eukaryotic genes (GMOE). The GMOE group lives in hypoxic environments and metabolizes glucose by fermentation. GMOEs represent advanced cancer, which proliferate aggressively and are resistant to DNA damage.

It has been demonstrated that as an ERV becomes more prevalent in a mammalian genome, the possibility that the mammal will develop cancer increases. The hypothesis also states that most cancers have their origins in GMOV by the incorporation of viral genes from junk genes. As the cancer progresses, further subgroups of cancer GMOs will develop. If the cancer advances even further, the GMOE could eventually develop prior to late-stage cancer. Because the genes of ancient eukaryotes have enhanced innate immunity, GMOE will eventually prevail over the weaker GMOV during cancer subgroup competition. Hence, cancer development is mainly determined by genes in the mammalian genome.

An inherent weakness of cancer cells is their dependence on glucose and iron. Furthermore, they cannot tolerate physical disturbance. Ancient gene GMOs can be treated with a combination of mechanical vibration using glucose-coated magnetic nanoparticles and strengthening of the immune system. Herein, I suggest trials for verifying this hypothesis.