Peptide-based materials for cancer immunotherapy

Dendrimer Conjugates with PD-L1-Binding Peptides Enhance In Vivo Antitumor Immune Response

Peptides are an emerging class of biologics for cancer immunotherapy; however, their clinical translation is hindered by poor binding kinetics, bioavailability, and short plasma half-life compared to their corresponding antibodies. Nanoparticles present potential solutions but face scale-up difficulties due to complexity. Here, a translatable, modular nanoparticle scaffold is presented for peptide-based immune checkpoint inhibitors (ICIs). This platform is based on a simple structure of generation 7 (G7) poly(amidoamine) (PAMAM) dendrimers conjugated with engineered peptides (dendrimer-peptide conjugates, DPCs). DPCs functionalized with multiple copies of a programmed death-ligand 1 (PD-L1)-binding peptide exhibited significantly enhanced avidity-based binding kinetics and in vitro specificity, in addition to the substantially prolonged plasma half-life in vivo. Notably, a series of in vivo experiments revealed that DPCs displayed selective tumor accumulation and high efficacy, without apparent toxicity, when applied to a syngeneic mouse model bearing mouse oral carcinoma (MOC1) tumors. The results indicate that the DPC platform significantly improves the antagonistic effect and in vivo behaviors of the PD-L1-binding peptides, which can be potentially applied to virtually any peptide-based ICIs. The DPC platform's simplicity and modular nature will likely increase the potential of its clinical translation and ultimately enable precision/personalized cancer immunotherapy.

Highly Efficient Bifunctional Peptides for Tumor Immunotherapy by Simultaneously Activating T Cells and Blocking PD-L1 Immune Checkpoint

Immune checkpoint inhibitors represented by PD-1/PD-L1 monoclonal antibodies have shown great success in tumor immunotherapy. However, the response rate of immune checkpoint blockade (ICB) therapy alone is far from satisfactory due to insufficient and exhausted tumor-infiltrating T cells. Meanwhile, antibody-based drugs have some drawbacks such as high cost and complicated preparation, which require further development of nonantibody immune checkpoint inhibitors and more rational strategies for improving the effectiveness of tumor treatment. Here, a highly efficient bifunctional peptide (Bi-pep) was constructed for tumor treatment by simultaneously activating T cells and blocking the PD-L1 immune checkpoint. This peptide not only can block the PD-1/PD-L1 immunosuppressive pathway but also directly and efficiently promote the activation and proliferation of T cells, thereby showing a significant effect on promoting T cell killing of tumor cells. The Bi-pep-induced antitumor effect was verified on both subcutaneous and orthotopic tumor models, which can significantly inhibit tumor growth and thus prolong the survival of tumor-bearing mice, holding great potential for biomedical applications.

Immunomodulatory Peptides for Tumor Treatment

Peptides exhibit various biological activities, including biorecognition, cell targeting, and tumor penetration, and can stimulate immune cells to elicit immune responses for tumor immunotherapy. Peptide self-assemblies and peptide-functionalized nanocarriers can reduce the effect of various biological barriers and the degradation by peptidases, enhancing the efficiency of peptide delivery and improving antitumor immune responses. To date, the design and development of peptides with various functionalities have been extensively reviewed for enhanced chemotherapy; however, peptide-mediated tumor immunotherapy using peptides acting on different immune cells, to the knowledge, has not yet been summarized. Thus, this work provides a review of this emerging subject of research, focusing on immunomodulatory anticancer peptides. This review introduces the role of peptides in the immunomodulation of innate and adaptive immune cells, followed by a link between peptides in the innate and adaptive immune systems. The peptides are discussed in detail, following a classification according to their effects on different innate and adaptive immune cells, as well as immune checkpoints. Subsequently, two delivery strategies for peptides as drugs are presented: peptide self-assemblies and peptide-functionalized nanocarriers. The concluding remarks regarding the challenges and potential solutions of peptides for tumor immunotherapy are presented.

The Potential Effect of Endogenous Antimicrobial Peptides in Cancer Immunotherapy and Prevention

Antimicrobial peptides (AMPs) are crucial constituents of inherent immunity and serve as vital components of human host defense, playing a pivotal role in combating invading microbial pathogens. Beyond their antimicrobial functions, AMPs also exhibit various other biological activities including apoptosis induction, wound healing promotion, and immune modulation. These peptides are found in various exposed tissues or surfaces throughout the body, such as eyes, skin, mouth, ears, respiratory tract, lungs, digestive, and urinary system. Additionally, certain AMPs such as LL-37, HNP, and lactoferrin have shown potential as candidates for anticancer activity. Given the limited selectivity between normal and cancer cells exhibited by many current immunotherapeutic agents, the inherent properties of AMPs make them promising candidates for cancer treatment. Their abundance, bioavailability, safety profile, efficiency, and harmony with the host immune system position them as attractive tools in the fight against cancer. This review is aimed at exploring the potential anticancer properties of AMPs and elucidating their relationship with immunology and cancer immunotherapy.

Biomimetic Nanomaterials Based on Peptide In Situ Self-Assembly for Immunotherapy Applications

Cancer remains the leading cause of patient death worldwide and its incidence continues to rise. Immunotherapy is rapidly developing due to its significant differences in the mechanism of action from conventional radiotherapy and targeted antitumor drugs. In the past decades, many biomaterials have been designed and prepared to construct therapeutic platforms that modulate the immune system against cancer. Immunotherapeutic platforms utilizing biomaterials can markedly enhance therapeutic efficacy by optimizing the delivery of therapeutic agents, minimizing drug loss during circulation, and amplifying immunomodulatory effects. The intricate physiological barriers of tumors, coupled with adverse immune environments such as inadequate infiltration, off-target effects, and immunosuppression, have emerged as significant obstacles impeding the effectiveness of oncology drug therapy. However, most of the current studies are devoted to the development of complex immunomodulators that exert immunomodulatory functions by loading drugs or adjuvants, ignoring the complex physiological barriers and adverse immune environments of tumors. Compared with conventional biomaterials, biomimetic nanomaterials based on peptide in situ self-assembly with excellent functional characteristics of biocompatibility, biodegradability, and bioactivity have emerged as a novel and effective tool for cancer immunotherapy. This article presents a comprehensive review of the latest research findings on biomimetic nanomaterials based on peptide in situ self-assembly in tumor immunotherapy. Initially, we categorize the structural types of biomimetic peptide nanomaterials and elucidate their intrinsic driving forces. Subsequently, we delve into the in situ self-assembly strategies of these peptide biomimetic nanomaterials, highlighting their advantages in immunotherapy. Furthermore, we detail the applications of these biomimetic nanomaterials in antigen presentation and modulation of the immune microenvironment. In conclusion, we encapsulate the challenges and prospective developments of biomimetic nanomaterials based on peptide in situ self-assembly for clinical translation in immunotherapy.

Peptides as Versatile Regulators in Cancer Immunotherapy: Recent Advances, Challenges, and Future Prospects

The emergence of effective immunotherapies has revolutionized therapies for many types of cancer. However, current immunotherapy has limited efficacy in certain patient populations and displays therapeutic resistance after a period of treatment. To address these challenges, a growing number of immunotherapy drugs have been investigated in clinical and preclinical applications. The diverse functionality of peptides has made them attractive as a therapeutic modality, and the global market for peptide-based therapeutics is witnessing significant growth. Peptides can act as immunotherapeutic agents for the treatment of many malignant cancers. However, a systematic understanding of the interactions between different peptides and the host's immune system remains unclear. This review describes in detail the roles of peptides in regulating the function of the immune system for cancer immunotherapy. Initially, we systematically elaborate on the relevant mechanisms of cancer immunotherapy. Subsequently, we categorize peptide-based nanomaterials into the following three categories: peptide-based vaccines, anti-cancer peptides, and peptide-based delivery systems. We carefully analyzed the roles of these peptides in overcoming the current barriers in immunotherapy, including multiple strategies to enhance the immunogenicity of peptide vaccines, the synergistic effect of anti-cancer peptides in combination with other immune agents, and peptide assemblies functioning as immune stimulators or vehicles to deliver immune agents. Furthermore, we introduce the current status of peptide-based immunotherapy in clinical applications and discuss the weaknesses and future prospects of peptide-based materials for cancer immunotherapy. Overall, this review aims to enhance comprehension of the potential applications of peptide-based materials in cancer immunotherapy and lay the groundwork for future research and clinical applications.

Immunotherapy for glioblastoma: current state, challenges, and future perspectives

Glioblastoma (GBM) is an aggressive and lethal type of brain tumor in human adults. The standard of care offers minimal clinical benefit, and most GBM patients experience tumor recurrence after treatment. In recent years, significant advancements have been made in the development of novel immunotherapies or other therapeutic strategies that can overcome immunotherapy resistance in many advanced cancers. However, the benefit of immune-based treatments in GBM is limited because of the unique brain immune profiles, GBM cell heterogeneity, and immunosuppressive tumor microenvironment. In this review, we present a detailed overview of current immunotherapeutic strategies and discuss the challenges and potential molecular mechanisms underlying immunotherapy resistance in GBM. Furthermore, we provide an in-depth discussion regarding the strategies that can overcome immunotherapy resistance in GBM, which will likely require combination therapies.

A hybrid method for discovering interferon-gamma inducing peptides in human and mouse

Interferon-gamma (IFN-γ) is a versatile pleiotropic cytokine essential for both innate and adaptive immune responses. It exhibits both pro-inflammatory and anti-inflammatory properties, making it a promising therapeutic candidate for treating various infectious diseases and cancers. We present IFNepitope2, a host-specific technique to annotate IFN-γ inducing peptides, it is an updated version of IFNepitope introduced by Dhanda et al. In this study, dataset used for developing prediction method contain experimentally validated 25,492 and 7983 IFN-γ inducing peptides in human and mouse host, respectively. In initial phase, machine learning techniques have been exploited to develop classification model using wide range of peptide features. Further, to improve machine learning based models or alignment free models, we explore potential of similarity-based technique BLAST. Finally, a hybrid model has been developed that combine best machine learning based model with BLAST. In most of the case, models based on extra tree perform better than other machine learning techniques. In case of peptide features, compositional feature particularly dipeptide composition performs better than one-hot encoding or binary profile. Our best machine learning based models achieved AUROC 0.89 and 0.83 for human and mouse host, respectively. The hybrid model achieved the AUROC 0.90 and 0.85 for human and mouse host, respectively. All models have been evaluated on an independent/validation dataset not used for training or testing these models. Newly developed method performs better than existing method on independent dataset. The major objective of this study is to predict, design and scan IFN-γ inducing peptides, thus server/software have been developed ( https://webs.iiitd.edu.in/raghava/ifnepitope2/ ). This method is also available as standalone at https://github.com/raghavagps/ifnepitope2 and python package index at https://pypi.org/project/ifnepitope2/ .

Advancements in therapeutic peptides: Shaping the future of cancer treatment

In the evolving landscape of cancer treatment, therapeutic peptides are assuming to play an increasingly vital role. Although the number of peptide drugs available for clinical cancer treatment is currently limited, extensive preclinical research is underway, presenting a promising trajectory for the future. The collaborative efforts of natural anti-cancer peptides (ACPs) and synthetic ACPs, propelled by advancements in molecular biology and peptide chemistry, are steering remarkable progress in this domain. We explores the intricate mechanisms underlying the anti-cancer effects of these peptides. The exploration of innovative strategies, including cancer immunotherapy and advanced drug delivery systems, is likely to contribute to the increasing presenceuse of peptide drugs in clinical cancer care. Furthermore, we delve into the potential implications and challenges associated with this anticipated shift, emphasizing the need for continued research and development to unlock the full therapeutic potential of peptide drugs in cancer treatment.

Insights into therapeutic peptides in the cancer-immunity cycle: Update and challenges

Immunotherapies hold immense potential for achieving durable potency and long-term survival opportunities in cancer therapy. As vital biological mediators, peptides with high tissue penetration and superior selectivity offer significant promise for enhancing cancer immunotherapies (CITs). However, physicochemical peptide features such as conformation and stability pose challenges to their on-target efficacy. This review provides a comprehensive overview of recent advancements in therapeutic peptides targeting key steps of the cancer-immunity cycle (CIC), including tumor antigen presentation, immune cell regulation, and immune checkpoint signaling. Particular attention is given to the opportunities and challenges associated with these peptides in boosting CIC within the context of clinical progress. Furthermore, possible future developments in this field are also discussed to provide insights into emerging CITs with robust efficacy and safety profiles.

SARS-CoV-2 Vaccines: The Advantage of Mucosal Vaccine Delivery and Local Immunity

Immunity against respiratory pathogens is often short-term, and, consequently, there is an unmet need for the effective prevention of such infections. One such infectious disease is coronavirus disease 19 (COVID-19), which is caused by the novel Beta coronavirus SARS-CoV-2 that emerged around the end of 2019. The World Health Organization declared the illness a pandemic on 11 March 2020, and since then it has killed or sickened millions of people globally. The development of COVID-19 systemic vaccines, which impressively led to a significant reduction in disease severity, hospitalization, and mortality, contained the pandemic's expansion. However, these vaccines have not been able to stop the virus from spreading because of the restricted development of mucosal immunity. As a result, breakthrough infections have frequently occurred, and new strains of the virus have been emerging. Furthermore, SARS-CoV-2 will likely continue to circulate and, like the influenza virus, co-exist with humans. The upper respiratory tract and nasal cavity are the primary sites of SARS-CoV-2 infection and, thus, a mucosal/nasal vaccination to induce a mucosal response and stop the virus' transmission is warranted. In this review, we present the status of the systemic vaccines, both the approved mucosal vaccines and those under evaluation in clinical trials. Furthermore, we present our approach of a B-cell peptide-based vaccination applied by a prime-boost schedule to elicit both systemic and mucosal immunity.

Peptide-functionalized, -assembled and -loaded nanoparticles in cancer therapy

The combination of peptides and nanoparticles in cancer therapy has shown synergistic results. Nanoparticle functionalization with peptides can increase their targeting ability towards tumor cells. In some cases, the peptides can develop self-assembled nanoparticles, in combination with drugs, for targeted cancer therapy. The peptides can be loaded into nanoparticles and can be delivered by other drugs for synergistic cancer removal. Multifunctional types of peptide-based nanoparticles, including pH- and redox-sensitive classes, have been introduced in cancer therapy. The tumor microenvironment remolds, and the acceleration of immunotherapy and vaccines can be provided by peptide nanoparticles. Moreover, the bioimaging and labeling of cancers can be mediated by peptide nanoparticles. Therefore, peptides can functionalize nanoparticles in targeted cancer therapy.

Peptide nanovaccine conjugated via a retro-Diels-Alder reaction linker for overcoming the obstacle in lymph node penetration and eliciting robust cellular immunity

Nanoparticles have been regarded as a promising vaccine adjuvant due to their innate immune potentiation and enhanced antigen transport. However, the inefficient infiltration into the lymph node (LN) paracortex of nanoparticles caused by subcapsular sinus (SCS) obstruction is the main challenge in further improvement of nanovaccine immune efficacy. Herein, we propose to overcome paracortex penetration by using nanovaccine to spontaneously and continuously release antigens after retention in the SCS. In detail, we utilized a spontaneous retro-Diels-Alder (r-D-A) reaction linker to connect poly{(2-methyl-2-oxazoline)80-co-[(2-butyl-2-oxazoline)15-r-(2-thioethyl-2-oxazoline)8]} (PMBOxSH) and peptides for the peptide nanovaccine construction. The r-D-A reaction linker can spontaneously break over time, allowing the nanovaccine to release free antigens and adjuvants upon reaching the LN, thereby facilitating the entry of released antigens and adjuvants into the interior of the LNs. We showed that the efficacy of the peptide nanovaccine constructed using this dynamic linker could be significantly improved, thus greatly enhancing the tumor inhibition efficacy in the B16-OVA model. This dynamic-covalent-chemistry-based vaccine strategy may inspire designing more efficient therapeutic vaccines, especially those that require eliciting high-amount T cell responses.

Metal-Organic Framework-Based Nanovaccine for Relieving Immunosuppressive Tumors via Hindering Efferocytosis of Macrophages and Promoting Pyroptosis and Cuproptosis of Cancer Cells

Current cancer vaccines face challenges due to an immunosuppressive tumor microenvironment and their limited ability to produce an effective immune response. To address the above limitations, we develop a 3-(2-spiroadamantyl)-4-methoxy-4-(3-phosphoryloxy)-phenyl-1,2-dioxetane (alkaline phosphatase substrate) and XMD8-92 (extracellular signal-regulated kinase 5 inhibitor)-codelivered copper-tetrahydroxybenzoquinone (Cu-THBQ/AX) nanosized metal-organic framework to in situ-generate therapeutic vaccination. Once inside the early endosome, the alkaline phosphatase overexpressed in the tumor cells' membrane activates the in situ type I photodynamic effect of Cu-THBQ/AX for generating •O2-, and the Cu-THBQ/AX catalyzes O2 and H2O2 to •O2- and •OH via semiquinone radical catalysis and Fenton-like reactions. This surge of ROS in early endosomes triggers caspase-3-mediated proinflammatory pyroptosis via activating phospholipase C. Meanwhile, Cu-THBQ/AX can also induce the oligomerization of dihydrolipoamide S-acetyltransferase to trigger tumor cell cuproptosis. The production of •OH could also trigger the release of XMD8-92 for effectively inhibiting the efferocytosis of macrophages to convert immunosuppressive apoptosis of cancer cells into proinflammatory secondary necrosis. The simultaneous induction of pyroptosis, cuproptosis, and secondary necrosis effectively converts the tumor microenvironment from "cold" to "hot" conditions, making it an effective antigen pool. This transformation successfully activates the antitumor immune response, inhibiting tumor growth and metastasis.

Crosstalk Between NK Cell Receptors and Tumor Membrane Hsp70-Derived Peptide: A Combined Computational and Experimental Study

Natural killer (NK) cells are central components of the innate immunity system against cancers. Since tumor cells have evolved a series of mechanisms to escape from NK cells, developing methods for increasing the NK cell antitumor activity is of utmost importance. It is previously shown that an ex vivo stimulation of patient-derived NK cells with interleukin (IL)-2 and Hsp70-derived peptide TKD (TKDNNLLGRFELSG, aa450-461) results in a significant upregulation of activating receptors including CD94 and CD69 which triggers exhausted NK cells to target and kill malignant solid tumors expressing membrane Hsp70 (mHsp70). Considering that TKD binding to an activating receptor is the initial step in the cytolytic signaling cascade of NK cells, herein this interaction is studied by molecular docking and molecular dynamics simulation computational modeling. The in silico results showed a crucial role of the heterodimeric receptor CD94/NKG2A and CD94/NKG2C in the TKD interaction with NK cells. Antibody blocking and CRISPR/Cas9-mediated knockout studies verified the key function of CD94 in the TKD stimulation and activation of NK cells which is characterized by an increased cytotoxic capacity against mHsp70 positive tumor cells via enhanced production and release of lytic granules and pro-inflammatory cytokines.

From structural design to delivery: mRNA therapeutics for cancer immunotherapy

mRNA therapeutics have emerged as powerful tools for cancer immunotherapy in accordance with their superiority in expressing all sequence-known proteins in vivo. In particular, with a small dosage of delivered mRNA, antigen-presenting cells (APCs) can synthesize mutant neo-antigens and multi-antigens and present epitopes to T lymphocytes to elicit antitumor effects. In addition, expressing receptors like chimeric antigen receptor (CAR), T-cell receptor (TCR), CD134, and immune-modulating factors including cytokines, interferons, and antibodies in specific cells can enhance immunological response against tumors. With the maturation of in vitro transcription (IVT) technology, large-scale and pure mRNA encoding specific proteins can be synthesized quickly. However, the clinical translation of mRNA-based anticancer strategies is restricted by delivering mRNA into target organs or cells and the inadequate endosomal escape efficiency of mRNA. Recently, there have been some advances in mRNA-based cancer immunotherapy, which can be roughly classified as modifications of the mRNA structure and the development of delivery systems, especially the lipid nanoparticle platforms. In this review, the latest strategies for overcoming the limitations of mRNA-based cancer immunotherapies and the recent advances in delivering mRNA into specific organs and cells are summarized. Challenges and opportunities for clinical applications of mRNA-based cancer immunotherapy are also discussed.

An integrative machine learning model for the identification of tumor T-cell antigens

The escalating global incidence of cancer poses significant health challenges, underscoring the need for innovative and more efficacious treatments. Cancer immunotherapy, a promising approach leveraging the body's immune system against cancer, emerges as a compelling solution. Consequently, the identification and characterization of tumor T-cell antigens (TTCAs) have become pivotal for exploration. In this manuscript, we introduce TTCA-IF, an integrative machine learning-based framework designed for TTCAs identification. TTCA-IF employs ten feature encoding types in conjunction with five conventional machine learning classifiers. To establish a robust foundation, these classifiers are trained, resulting in the creation of 150 baseline models. The outputs from these baseline models are then fed back into the five classifiers, generating their respective meta-models. Through an ensemble approach, the five meta-models are seamlessly integrated to yield the final predictive model, the TTCA-IF model. Our proposed model, TTCA-IF, surpasses both baseline models and existing predictors in performance. In a comparative analysis involving nine novel peptide sequences, TTCA-IF demonstrated exceptional accuracy by correctly identifying 8 out of 9 peptides as TTCAs. As a tool for screening and pinpointing potential TTCAs, we anticipate TTCA-IF to be invaluable in advancing cancer immunotherapy.

The Use of Immune Regulation in Treating Head and Neck Squamous Cell Carcinoma (HNSCC)

Immunotherapy has emerged as a promising new treatment modality for head and neck cancer, offering the potential for targeted and effective cancer management. Squamous cell carcinomas pose significant challenges due to their aggressive nature and limited treatment options. Conventional therapies such as surgery, radiation, and chemotherapy often have limited success rates and can have significant side effects. Immunotherapy harnesses the power of the immune system to recognize and eliminate cancer cells, and thus represents a novel approach with the potential to improve patient outcomes. In the management of head and neck squamous cell carcinoma (HNSCC), important contributions are made by immunotherapies, including adaptive cell therapy (ACT) and immune checkpoint inhibitor therapy. In this review, we are focusing on the latter. Immune checkpoint inhibitors target proteins such as programmed cell death protein 1 (PD-1) and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) to enhance the immune response against cancer cells. The CTLA-4 inhibitors, such as ipilimumab and tremelimumab, have been approved for early-stage clinical trials and have shown promising outcomes in terms of tumor regression and durable responses in patients with advanced HNSCC. Thus, immune checkpoint inhibitor therapy holds promise in overcoming the limitations of conventional therapies. However, further research is needed to optimize treatment regimens, identify predictive biomarkers, and overcome potential resistance mechanisms. With ongoing advancements in immunotherapy, the future holds great potential for transforming the landscape of oral tumor treatment and providing new hope for patients.

Characterizing the Inflammatory Profile of Neutrophil-Rich Triple-Negative Breast Cancer

Breast cancer (BC) is one of the most common types of cancer in women in the United Arab Emirates. Immunogenic tumours, such as triple-negative breast cancer (TNBC), show increased neutrophil infiltration, which is associated with poor prognosis and limited efficacy of immunotherapy. This study aims to investigate in vitro the bidirectional effect of neutrophils on metastatic TNBC (MDA-MB-231) compared to less-metastatic luminal breast cancer (MCF-7) cell lines. We found that BC cells or their conditioned medium (CM) reduced the viability of neutrophil-like cells (HL60). This was supported by increased cellular stress and NETosis in differentiated HL60 cells (dHL60) upon exposure to MDA-MB-231 compared to MCF-7-CM using nucleic acid staining essays. Flow cytometry showed comparable expression of inflammatory markers by polymorphonuclear cells (PMN) when treated with MDA-MB-231-CM and standard polarizing cocktails. Furthermore, MDA-MB-231-CM triggered an inflammatory pattern with evidence of stronger adhesion (CD62L) and degranulation (CD11b and CD66b) phenotypes. The proinflammatory polarization of dHL60 by MDA-MB-231-CM was additionally confirmed by the elevated CD54 expression, myeloperoxidase, and CD11b protein levels, which matched an increased transwell migratory capacity. In conclusion, BC might use neutrophils to their benefit through NETosis and complement system activation, which makes this crosstalk a potential mechanism for understanding tumour progression.

Nano-Drug Delivery Systems Based on Natural Products

Natural products have proven to have significant curative effects and are increasingly considered as potential candidates for clinical prevention, diagnosis, and treatment. Compared with synthetic drugs, natural products not only have diverse structures but also exhibit a range of biological activities against different disease states and molecular targets, making them attractive for development in the field of medicine. Despite advancements in the use of natural products for clinical purposes, there remain obstacles that hinder their full potential. These challenges include issues such as limited solubility and stability when administered orally, as well as short durations of effectiveness. To address these concerns, nano-drug delivery systems have emerged as a promising solution to overcome the barriers faced in the clinical application of natural products. These systems offer notable advantages, such as a large specific surface area, enhanced targeting capabilities, and the ability to achieve sustained and controlled release. Extensive in vitro and in vivo studies have provided further evidence supporting the efficacy and safety of nanoparticle-based systems in delivering natural products in preclinical disease models. This review describes the limitations of natural product applications and the current status of natural products combined with nanotechnology. The latest advances in nano-drug delivery systems for delivery of natural products are considered from three aspects: connecting targeting warheads, self-assembly, and co-delivery. Finally, the challenges faced in the clinical translation of nano-drugs are discussed.

Role of Functionalized Peptides in Nanomedicine for Effective Cancer Therapy

Peptide-functionalized nanomedicine, which addresses the challenges of specificity and efficacy in drug delivery, is emerging as a pivotal approach for cancer therapy. Globally, cancer remains a leading cause of mortality, and conventional treatments, such as chemotherapy, often lack precision and cause adverse effects. The integration of peptides into nanomedicine offers a promising solution for enhancing the targeting and delivery of therapeutic agents. This review focuses on the three primary applications of peptides: cancer cell-targeting ligands, building blocks for self-assembling nanostructures, and elements of stimuli-responsive systems. Nanoparticles modified with peptides improved targeting of cancer cells, minimized damage to healthy tissues, and optimized drug delivery. The versatility of self-assembled peptide structures makes them an innovative vehicle for drug delivery by leveraging their biocompatibility and diverse nanoarchitectures. In particular, the mechanism of cell death induced by self-assembled structures offers a novel approach to cancer therapy. In addition, peptides in stimuli-responsive systems enable precise drug release in response to specific conditions in the tumor microenvironment. The use of peptides in nanomedicine not only augments the efficacy and safety of cancer treatments but also suggests new research directions. In this review, we introduce systems and functionalization methods using peptides or peptide-modified nanoparticles to overcome challenges in the treatment of specific cancers, including breast cancer, lung cancer, colon cancer, prostate cancer, pancreatic cancer, liver cancer, skin cancer, glioma, osteosarcoma, and cervical cancer.

A Transformable Supramolecular Bispecific Cell Engager for Augmenting Natural Killer and T Cell-Based Cancer Immunotherapy

Immune cells are pivotal in cancer immunotherapy, yet their therapeutic effectiveness is often hampered by limited tumor infiltration and inhibitory tumor microenvironments. An alkaline phosphatase (ALP)-responsive and transformable supramolecular bis-specific cell engager (Supra-BiCE) to harness natural killer (NK)/T cells for effective cancer immunotherapy is introduced here. The Supra-BiCE, consisting of both SA-P (a phosphorylated peptide targeting and blocking programmed cell death ligand 1 (PD-L1)) and SA-T (a phosphorylated peptide targeting and blocking T cell immunoglobulin and ITIM domain (TIGIT)) is constructed by a simple co-assembling strategy. Upon intravenous administration, Supra-BiCE self-assembles into nanoribbons and interacts with NK/T cells via TIGIT. Notably, these nanoribbons undergo transformation into long nanofibrils within ALP-overexpressing tumor regions, resulting in enhanced binding affinities of Supra-BiCE to both PD-L1 and TIGIT. Consequently, this leads to the accumulation and retention of NK/T cells within tumor regions. Furthermore, the combinatorial blockade of checkpoints by Supra-BiCE activates infiltrating NK/T cells. Moreover, the adjustable peptide ratio in Supra-BiCE enables customization for optimal therapeutic effects against distinct tumor types. Particularly, Supra-BiCE (T:P = 1:3) achieved 98.27% tumor suppression rate against colon carcinoma model. Overall, this study offers a promising tool for engaging NK and T cells for cancer immunotherapy.

Breast cancer vaccines; A comprehensive and updated review

According to the International Agency for Research on Cancer, breast cancer is more common than lung cancer globally. By 2040, mortality from breast cancer will rise by 50% and 40%, respectively. Despite advances in chemotherapy, endocrine therapy, and HER2-targeted therapy, breast cancer metastases and recurrences remain challenging to treat. Cancer vaccines are an effective treatment option because they stimulate a long-lasting immune response that will eliminate tumor cells. In studies on the breast cancer vaccine, no appreciable advantages were discovered. A recent study claims that immune checkpoint inhibitors or anti-HER2 monoclonal antibodies may be used in vaccinations. This vaccination strengthens the immune system to fight off breast cancer cells. Clinical trials have been conducted on DNA, dendritic cells, and peptide-based breast cancer vaccines. Studies on the breast cancer vaccine have employed subcutaneous, intramuscular, and intradermal injections. Clinical studies have shown that these efforts have not been successful. Several factors might have slowed the development of a breast cancer vaccine. The complexity of the immune system makes it challenging to create cancer vaccines. Given the heterogeneity of breast cancer, there may be a need for different vaccination strategies. Despite these obstacles, research into breast cancer vaccines continues. Effective methods for creating vaccines include immune checkpoint inhibition and anti-HER2 monoclonal antibodies. Research is also being done on specialized tumor vaccinations.

StackTTCA: a stacking ensemble learning-based framework for accurate and high-throughput identification of tumor T cell antigens

BACKGROUND

The identification of tumor T cell antigens (TTCAs) is crucial for providing insights into their functional mechanisms and utilizing their potential in anticancer vaccines development. In this context, TTCAs are highly promising. Meanwhile, experimental technologies for discovering and characterizing new TTCAs are expensive and time-consuming. Although many machine learning (ML)-based models have been proposed for identifying new TTCAs, there is still a need to develop a robust model that can achieve higher rates of accuracy and precision.

RESULTS

In this study, we propose a new stacking ensemble learning-based framework, termed StackTTCA, for accurate and large-scale identification of TTCAs. Firstly, we constructed 156 different baseline models by using 12 different feature encoding schemes and 13 popular ML algorithms. Secondly, these baseline models were trained and employed to create a new probabilistic feature vector. Finally, the optimal probabilistic feature vector was determined based the feature selection strategy and then used for the construction of our stacked model. Comparative benchmarking experiments indicated that StackTTCA clearly outperformed several ML classifiers and the existing methods in terms of the independent test, with an accuracy of 0.932 and Matthew's correlation coefficient of 0.866.

CONCLUSIONS

In summary, the proposed stacking ensemble learning-based framework of StackTTCA could help to precisely and rapidly identify true TTCAs for follow-up experimental verification. In addition, we developed an online web server ( http://2pmlab.camt.cmu.ac.th/StackTTCA ) to maximize user convenience for high-throughput screening of novel TTCAs.

Peptide-Based Vaccine against Breast Cancer: Recent Advances and Prospects

Breast cancer is considered the second-leading cancer after lung cancer and is the most prevalent cancer among women globally. Currently, cancer immunotherapy via vaccine has gained great attention due to specific and targeted immune cell activity that creates a potent immune response, thus providing long-lasting protection against the disease. Despite peptides being very susceptible to enzymatic degradation and poor immunogenicity, they can be easily customized with selected epitopes to induce a specific immune response and particulate with carriers to improve their delivery and thus overcome their weaknesses. With advances in nanotechnology, the peptide-based vaccine could incorporate other components, thereby modulating the immune system response against breast cancer. Considering that peptide-based vaccines seem to show remarkably promising outcomes against cancer, this review focuses on and provides a specific view of peptide-based vaccines used against breast cancer. Here, we discuss the benefits associated with a peptide-based vaccine, which can be a mainstay in the prevention and recurrence of breast cancer. Additionally, we also report the results of recent trials as well as plausible prospects for nanotechnology against breast cancer.

DNA Nanomaterials-Based Platforms for Cancer Immunotherapy

The past few decades have witnessed the evolving paradigm for cancer therapy from nonspecific cytotoxic agents to selective, mechanism-based therapeutics, especially immunotherapy. In particular, the integration of nanomaterials with immunotherapy is proven to improve the therapeutic outcome and minimize off-target toxicity in the treatment. As a novel nanomaterial, DNA-based self-assemblies featuring uniform geometries, feasible modifications, programmability, surface addressability, versatility, and intrinsic biocompatibility, are extensively exploited for innovative and effective cancer immunotherapy. In this review, the successful employment of DNA nanoplatforms for cancer immunotherapy, including the delivery of immunogenic cell death inducers, adjuvants and vaccines, immune checkpoint blockers as well as the application in immune cell engineering and adoptive cell therapy is summarized. The remaining challenges and future perspectives regarding the pharmacokinetics/pharmacodynamics, in vivo fate and immunogenicity of DNA materials, and the design of intelligent DNA nanomedicine for individualized cancer immunotherapy are also discussed.

TNFepitope: A webserver for the prediction of TNF-α inducing epitopes

Tumor Necrosis Factor alpha (TNF-α) is a pleiotropic pro-inflammatory cytokine that is crucial in controlling the signaling pathways within the immune cells. Recent studies reported that higher expression levels of TNF-α are associated with the progression of several diseases, including cancers, cytokine release syndrome in COVID-19, and autoimmune disorders. Thus, it is the need of the hour to develop immunotherapies or subunit vaccines to manage TNF-α progression in various disease conditions. In the pilot study, we proposed a host-specific in-silico tool for predicting, designing, and scanning TNF-α inducing epitopes. The prediction models were trained and validated on the experimentally validated TNF-α inducing/non-inducing epitopes from human and mouse hosts. Firstly, we developed alignment-free (machine learning based models using composition-based features of peptides) methods for predicting TNF-α inducing peptides and achieved maximum AUROC of 0.79 and 0.74 for human and mouse hosts, respectively. Secondly, an alignment-based (using BLAST) method has been used for predicting TNF-α inducing epitopes. Finally, a hybrid method (combination of alignment-free and alignment-based method) has been developed for predicting epitopes. Hybrid approach achieved maximum AUROC of 0.83 and 0.77 on an independent dataset for human and mouse hosts, respectively. We have also identified potential TNF-α inducing peptides in different proteins of HIV-1, HIV-2, SARS-CoV-2, and human insulin. The best models developed in this study has been incorporated in the webserver TNFepitope (https://webs.iiitd.edu.in/raghava/tnfepitope/), standalone package and GitLab (https://gitlab.com/raghavalab/tnfepitope).

Peptide-based diagnostic and therapeutic agents: Where we are and where we are heading?

Peptides are increasingly present in all branches of medicine as innovative drugs, imaging agents, theragnostic, and constituent moieties of other sophisticated drugs such as peptide-drug conjugates. Due to new developments in chemical synthesis strategies, computational biology, recombinant technology, and chemical biology, peptide drug development has made a great progress in the last decade. Numerous natural peptides and peptide mimics have been obtained and studied, covering multiple therapeutic areas. Even though peptides have been investigated across the wide therapeutic spectrum, oncology, metabolism, and endocrinology are the most frequent medical indications of them. This review summarizes the current use of and the emerging new opportunities of peptides for diagnosis and treatment of various diseases.

Cancel cancer: The immunotherapeutic potential of CD200/CD200R blockade

Immune checkpoint molecules function to inhibit and regulate immune response pathways to prevent hyperactive immune activity from damaging healthy tissues. In cancer patients, targeting these key molecules may serve as a valuable therapeutic mechanism to bolster immune function and restore the body's natural defenses against tumors. CD200, an immune checkpoint molecule, is a surface glycoprotein that is widely but not ubiquitously expressed throughout the body. By interacting with its inhibitory receptor CD200R, CD200 suppresses immune cell activity within the tumor microenvironment, creating conditions that foster tumor growth. Targeting the CD200/CD200R pathway, either through the use of monoclonal antibodies or peptide inhibitors, has shown to be effective in boosting anti-tumor immune activity. This review will explore CD200 and the protein's expression and role within the tumor microenvironment, blood endothelial cells, and lymph nodes. This paper will also discuss the advantages and challenges of current strategies used to target CD200 and briefly summarize relevant preclinical/clinical studies investigating the immunotherapeutic efficacy of CD200/CD200R blockade.

From design to clinic: Engineered peptide nanomaterials for cancer immunotherapy

Immunotherapy has revolutionized the field of cancer therapy. Nanomaterials can further improve the efficacy and safety of immunotherapy because of their tunability and multifunctionality. Owing to their natural biocompatibility, diverse designs, and dynamic self-assembly, peptide-based nanomaterials hold great potential as immunotherapeutic agents for many malignant cancers, with good immune response and safety. Over the past several decades, peptides have been developed as tumor antigens, effective antigen delivery carriers, and self-assembling adjuvants for cancer immunotherapy. In this review, we give a brief introduction to the use of peptide-based nanomaterials for cancer immunotherapy as antigens, carriers, and adjuvants, and to their current clinical applications. Overall, this review can facilitate further understanding of peptide-based nanomaterials for cancer immunotherapy and may pave the way for designing safe and efficient methods for future vaccines or immunotherapies.

Self-Assembled Peptide-Based Nanodrugs: Molecular Design, Synthesis, Functionalization, and Targeted Tumor Bioimaging and Biotherapy

Functional nanomaterials as nanodrugs based on the self-assembly of inorganics, polymers, and biomolecules have showed wide applications in biomedicine and tissue engineering. Ascribing to the unique biological, chemical, and physical properties of peptide molecules, peptide is used as an excellent precursor material for the synthesis of functional nanodrugs for highly effective cancer therapy. Herein, recent progress on the design, synthesis, functional regulation, and cancer bioimaging and biotherapy of peptide-based nanodrugs is summarized. For this aim, first molecular design and controllable synthesis of peptide nanodrugs with 0D to 3D structures are presented, and then the functional customization strategies for peptide nanodrugs are presented. Then, the applications of peptide-based nanodrugs in bioimaging, chemotherapy, photothermal therapy (PTT), and photodynamic therapy (PDT) are demonstrated and discussed in detail. Furthermore, peptide-based drugs in preclinical, clinical trials, and approved are briefly described. Finally, the challenges and potential solutions are pointed out on addressing the questions of this promising research topic. This comprehensive review can guide the motif design and functional regulation of peptide nanomaterials for facile synthesis of nanodrugs, and further promote their practical applications for diagnostics and therapy of diseases.

PSRTTCA: A new approach for improving the prediction and characterization of tumor T cell antigens using propensity score representation learning

Despite the arsenal of existing cancer therapies, the ongoing recurrence and new cases of cancer pose a serious health concern that necessitates the development of new and effective treatments. Cancer immunotherapy, which uses the body's immune system to combat cancer, is a promising treatment option. As a result, in silico methods for identifying and characterizing tumor T cell antigens (TTCAs) would be useful for better understanding their functional mechanisms. Although few computational methods for TTCA identification have been developed, their lack of model interpretability is a major drawback. Thus, developing computational methods for the effective identification and characterization of TTCAs is a critical endeavor. PSRTTCA, a new machine learning (ML)-based approach for improving the identification and characterization of TTCAs based on their primary sequences, is proposed in this study. Specifically, we introduce a new propensity score representation learning algorithm that allows one to generate various sets of propensity scores of amino acids, dipeptides, and g-gap dipeptides to be TTCAs. To enhance the predictive performance, optimal sets of variant propensity scores were determined and fed into the final meta-predictor (PSRTTCA). Benchmarking results revealed that PSRTTCA was a more precise and promising tool for the identification and characterization of TTCAs than conventional ML classifiers and existing methods. Furthermore, PSR-derived propensities of amino acids in becoming TTCAs are used to reveal the relationship between TTCAs and their informative physicochemical properties in order to provide insights into TTCA characteristics. Finally, a user-friendly online computational platform of PSRTTCA is publicly available at http://pmlabstack.pythonanywhere.com/PSRTTCA. The PSRTTCA predictor is anticipated to facilitate community-wide efforts in accelerating the discovery of novel TTCAs for cancer immunotherapy and other clinical applications.

Peptide-Based Materials That Exploit Metal Coordination

Metal-ion coordination has been widely exploited to control the supramolecular behavior of a variety of building blocks into functional materials. In particular, peptides offer great chemical diversity for metal-binding modes, combined with inherent biocompatibility and biodegradability that make them attractive especially for medicine, sensing, and environmental remediation. The focus of this review is the last 5 years' progress in this exciting field to conclude with an overview of the future directions that this research area is currently undertaking.

Immunogenic analysis of epitope-based vaccine candidate induced by photodynamic therapy in MDA-MB-231 triple-negative breast cancer cells

BACKGROUND

Photodynamic therapy (PDT) is used to treat tumors through selective cytotoxic effects. PDT induces damage-associated molecular patterns (DAMPs) expression, which can cause an immunogenic death cell (IDC). In this study we identified potential immunogenic epitopes generated by PDT on triple-negative breast cancer cell line (MDA-MB-231).

METHODS

MDA-MB-231 cells were exposed to PDT using ALA (160 µg/mL)/630 nm at 8 J/cm². Membrane proteins were extracted and separated by 2D PAGE. Proteins overexpressed were identified by LC-MS/MS and analyzed in silico through a peptide-HLA docking in order to identify the epitopes with more immunogenicity and antigenicity properties, as well as lower allergenicity and toxicity activity. The selected peptides were evaluated in response to macrophage activation and cytokine release by flow cytometry.

RESULTS

Differential proteins were overexpressed in the cells treated with PDT. A group of 16 peptides were identified from them, established in a rigorous selection by measuring antigenicity, immunogenicity, allergenicity, and toxicity in silico. The final selection was based on molecular dynamics, where 2 peptides showed the highest stability regarding to the RMSD value. These peptides were obtained from the proteins calreticulin and HSP90. The cytokine analysis evidenced macrophage activation by the releasing of TNF.

CONCLUSION

Two peptides were identified from calreticulin and HSP90; proteins induced by PDT in MDA-MB-231 cells. Both epitopes showed immunogenic potential as a peptide-based vaccine for triple-negative breast cancer.

Combined Vaccination with B Cell Peptides Targeting Her-2/neu and Immune Checkpoints as Emerging Treatment Option in Cancer

The application of monoclonal antibodies (mAbs), targeting tumor-associated (TAAs) or tumor-specific antigens or immune checkpoints (ICs), has shown tremendous success in cancer therapy. However, the application of mAbs suffers from a series of limitations, including the necessity of frequent administration, the limited duration of clinical response and the emergence of frequently pronounced immune-related adverse events. However, the introduction of mAbs has also resulted in a multitude of novel developments for the treatment of cancers, including vaccinations against various tumor cell-associated epitopes. Here, we reviewed recent clinical trials involving combination therapies with mAbs targeting the PD-1/PD-L1 axis and Her-2/neu, which was chosen as a paradigm for a clinically highly relevant TAA. Our recent findings from murine immunizations against the PD-1 pathway and Her-2/neu with peptides representing the mimotopes/B cell peptides of therapeutic antibodies targeting these molecules are an important focus of the present review. Moreover, concerns regarding the safety of vaccination approaches targeting PD-1, in the context of the continuing immune response, as a result of induced immunological memory, are also addressed. Hence, we describe a new frontier of cancer treatment by active immunization using combined mimotopes/B cell peptides aimed at various targets relevant to cancer biology.

Functionalized Peptide-Based Nanoparticles for Targeted Cancer Nanotherapeutics: A State-of-the-Art Review

Cancer mortality is increasing at an alarming rate across the globe. Albeit, many therapeutics are available commercially, they are not effective and have no cure up to today. Moreover, the knowledge gap in cancer therapy persists, representing a potential blind spot for the innovation of effective anticancer therapeutics. This review presents an update on current advancements in nanopeptide therapeutics. Herein, a detailed exploration of peptide-functionalized nanoparticles for the development of nanotherapeutics was carried out. Different approaches that include self-assembly nanostructures, solid phase peptide synthesis, ligand exchange, chemical reduction, and conjugation methods for assembling peptides for functionalizing nanodrugs are also highlighted. An outlook on biomedical applications is also reviewed. Additionally, a comprehensive discussion on targeted cancer cell therapy and mechanism of action are provided. The present review reflects the functional novelty of nanodrugs to improve stability, accessibility, bioavailability, and specificity toward cancerous cells. Finally, it summarizes the current challenges and future perspectives on the formulation of these nanodrugs.

mRNA vaccine with unmodified uridine induces robust type I interferon-dependent anti-tumor immunity in a melanoma model

An mRNA with unmodified nucleosides induces type I interferons (IFN-I) through the stimulation of innate immune sensors. Whether IFN-I induced by mRNA vaccine is crucial for anti-tumor immune response remains to be elucidated. In this study, we investigated the immunogenicity and anti-tumor responses of mRNA encoding tumor antigens with different degrees of N1-methylpseudouridine (m1Ψ) modification in B16 melanoma model. Our results demonstrated that ovalbumin (OVA) encoding mRNA formulated in a lipid nanoparticle (OVA-LNP) induced substantial IFN-I production and the maturation of dendritic cells (DCs) with negative correlation with increasing percentages of m1Ψ modification. In B16-OVA murine melanoma model, unmodified OVA-LNP significantly reduced tumor growth and prolonged survival, compared to OVA-LNP with m1Ψ modification. This robust anti-tumor effect correlated with the increase in intratumoral CD40⁺ DCs and the frequency of granzyme B⁺/IFN-γ⁺/TNF-α⁺ polyfunctional OVA peptide-specific CD8⁺ T cells. Blocking type I IFN receptor completely reversed the anti-tumor immunity of unmodified mRNA-OVA reflected in a significant decrease in OVA-specific IFN-γ secreting T cells and enrichment of PD-1⁺ tumor-infiltrating T cells. The robust anti-tumor effect of unmodified OVA-LNP was also observed in the lung metastatic tumor model. Finally, this mRNA vaccine was tested using B16 melanoma neoantigens (Pbk-Actn4) which resulted in delayed tumor growth. Taken together, our findings demonstrated that an unmodified mRNA vaccine induces IFN-I production or the downstream signaling cascades which plays a crucial role in inducing robust anti-tumor T cell response for controlling tumor growth and metastasis.

Potential association factors for developing effective peptide-based cancer vaccines

Peptide-based cancer vaccines have been shown to boost immune systems to kill tumor cells in cancer patients. However, designing an effective T cell epitope peptide-based cancer vaccine still remains a challenge and is a major hurdle for the application of cancer vaccines. In this study, we constructed for the first time a library of peptide-based cancer vaccines and their clinical attributes, named CancerVaccine (https://peptidecancervaccine.weebly.com/). To investigate the association factors that influence the effectiveness of cancer vaccines, these peptide-based cancer vaccines were classified into high (HCR) and low (LCR) clinical responses based on their clinical efficacy. Our study highlights that modified peptides derived from artificially modified proteins are suitable as cancer vaccines, especially for melanoma. It may be possible to advance cancer vaccines by screening for HLA class II affinity peptides may be an effective therapeutic strategy. In addition, the treatment regimen has the potential to influence the clinical response of a cancer vaccine, and Montanide ISA-51 might be an effective adjuvant. Finally, we constructed a high sensitivity and specificity machine learning model to assist in designing peptide-based cancer vaccines capable of providing high clinical responses. Together, our findings illustrate that a high clinical response following peptide-based cancer vaccination is correlated with the right type of peptide, the appropriate adjuvant, and a matched HLA allele, as well as an appropriate treatment regimen. This study would allow for enhanced development of cancer vaccines.

FXYD3 Expression Predicts Poor Prognosis in Renal Cell Carcinoma with Immunosuppressive Tumor Microenvironment

Simple Summary

FXYD3 belongs to the protein-coding gene family associated with Na+/K+-ATPase enzymes and chloride ion channels. Recently, the biological role of FXYD3 has been reported in multiple cancers. Nevertheless, the prognostic value of FXYD3 expression has been undiscovered in clear renal cell carcinoma (KIRC). In this study, we assessed the datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) dataset (GSE29609). We found the FXYD3 high KIRC patients had distinct clinical characteristics, including hypoxia and poor overall survival. Furthermore, the algorithms discovered that FXYD3 mRNA levels were associated with tumor purity, multiple types of the tumor infiltrating lymphocytes (TILs) and several genes related to T cell exhaustion. In conclusion, FXYD3 predicts a poor prognosis associated with hypoxia, pro-tumor TILs, and T cell exhaustion in KIRC.

Abstract

FXYD3 is a protein-coding gene, belonging to the FXYD protein family associated with Na+/K+-ATPase enzymes and chloride ion channels. Accumulating evidence suggests the biological role of FXYD3 in multiple cancers. However, the prognostic value of FXYD3 expression in clear renal cell carcinoma (KIRC) is unclear. Therefore, we evaluated the clinical data with tumor-infiltrating lymphocytes (TILs) and immunoinhibitory gene expression data using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) dataset (GSE29609). First, the FXYD3 high KIRC patients had distinct clinical characteristics, including age, sex, disease stage, histological grade, and hypoxia-related gene expressions. Next, FXYD3 gene expression was correlated with poor overall survival in both TCGA and GSE29609 cohorts. The ESTIMATE algorithm revealed that higher FXYD3 mRNA levels were associated with increased infiltration of immune cells and tumor purity. Moreover, the FXYD3 high KIRC tissue harbored increased TILs such as B cells, CD8+ T cells, and M1 macrophage, whereas NK cells and neutrophils were decreased. In addition, we showed FXYD3 was co-expressed with several immunoinhibitory genes related to T cell exhaustion such as LGALS9, CTLA4, BTLA, PDCD1, and LAG3. In conclusion, FXYD3 is an unfavorable prognostic biomarker associated with hypoxia, pro-tumor TILs, and T cell exhaustion.

Image-guided/improved diseases management: From immune-strategies and beyond

Timely and accurate assessment and diagnosis are extremely important and beneficial for all diseases, especially for some of the major human disease, such as cancers, cardiovascular diseases, infectious diseases, and neurodegenerative diseases. Limited by the variable disease microenvironment, early imperceptible symptoms, complex immune system interactions, and delayed clinical phenotypes, disease diagnosis and treatment are difficult in most cases. Molecular imaging (MI) techniques can track therapeutic drugs and disease sites in vivo and in vitro in a non-invasive, real-time and visible strategies. Comprehensive visual imaging and quantitative analysis based on different levels can help to clarify the disease process, pathogenesis, drug pharmacokinetics, and further evaluate the therapeutic effects. This review summarizes the application of different MI techniques in the diagnosis and treatment of these major human diseases. It is hoped to shed a light on the development of related technologies and fields.

Chimeric adenoviral (Ad5.F35) and listeria vector prime-boost immunization is safe and effective for cancer immunotherapy

Strategies to augment immunity to self/neoantigens expressed by cancers are urgently needed to expand the proportion of patients benefiting from immunotherapy, particularly for GI cancers where only a fraction of patients respond to immunotherapies. However, current vaccine strategies are limited by poor immunogenicity, pre-existing vector-specific immunity, and vaccine-induced vector-specific immunity. Here, we examined a prime-boost strategy using a chimeric adenoviral vector (Ad5.F35) that resists pre-existing immunity followed by recombinant Listeria monocytogenes (Lm) to amplify immunity to the GI cancer antigen GUCY2C. This previously unexplored combination enhanced the quantity, avidity, polyfunctionality, and antitumor efficacy of GUCY2C-specific effector CD8+ T cells, without toxicity in any tissue, including GUCY2C-expressing intestines and brain. Importantly, this combination was partially resistant to pre-existing immunity to Ad5 which is endemic in human populations and vector-specific immunity did not limit the ability of multiple Lm administrations to repeatedly enhance GUCY2C-specific responses. Broadly, these findings suggest that cancer patient immunizations targeting self/neoantigens, as well as immunizations for difficult infectious diseases (HIV, malaria, etc), may be most successful using a combination of Ad5.F35-based priming, followed by Lm-based boosting. More specifically, Lm-GUCY2C may be utilized to amplify GUCY2C-specific immunity in patients receiving adenovirus-based GUCY2C vaccines currently in clinical trials to prevent or treat recurrent GI cancer.

Peptide PDHPS1 inhibits ovarian cancer growth through disrupting YAP signaling

The lives of ovarian cancer patients are threatened largely due to metastasis and drug resistance. Endogenous peptides attract increasing attention in oncologic therapeutic area, a few anti-tumor peptides have been approved by the food and drug administration (FDA) for clinical use over the past decades. However, only few peptides or peptide-derived drugs with anti-ovarian cancer effects have been identified. Here we focused on the biological roles and mechanism of a peptide named PDHPS1 in ovarian cancer development. Our results indicated that PDHPS1 reduced the proliferation ability of ovarian cancer cells in vitro and inhibited the ovarian cancer growth in vivo. Peptide pull down and following mass spectrometry, western blot and qRT-PCR revealed that PDHPS1 could bind to protein phosphatase 2 phosphatase activator (PTPA), an essential activator of protein phosphatase 2A (PP2A), which resulted in increase of phosphorylated YAP, further inactivated YAP and suppressed the expression of its downstream target genes. Flow cytometry, cell membrane permeability test and immunohistochemical staining study demonstrated that there are no observable side effects of PDHPS1 on normal ovarian epithelium and hepatorenal function. Besides, modification of membrane penetration could improve the physicochemical properties and biological activity of PDHPS1. In conclusion, our study demonstrated that the endogenous peptide PDHPS1 serves as an anti-tumor peptide to inhibit YAP signaling pathway though interacting with PTPA in ovarian cancer.

Peptides-Coated Oncolytic Vaccines for Cancer Personalized Medicine

Oncolytic Viruses (OVs) work through two main mechanisms of action: the direct lysis of the virus-infected cancer cells and the release of tumor antigens as a result of the viral burst. In this sc.enario, the OVs act as in situ cancer vaccines, since the immunogenicity of the virus is combined with tumor antigens, that direct the specificity of the anti-tumor adaptive immune response. However, this mechanism in some cases fails in eliciting a strong specific T cell response. One way to overcome this problem and enhance the priming efficiency is the production of genetically modified oncolytic viruses encoding one or more tumor antigens. To avoid the long and expensive process related to the engineering of the OVs, we have exploited an approach based on coating OVs (adenovirus and vaccinia virus) with tumor antigens. In this work, oncolytic viruses encoding tumor antigens and tumor antigen decorated adenoviral platform (PeptiCRAd) have been used as cancer vaccines and evaluated both for their prophylactic and therapeutic efficacy. We have first tested the oncolytic vaccines by exploiting the OVA model, moving then to TRP2, a more clinically relevant tumor antigen. Finally, both approaches have been investigated in tumor neo-antigens settings. Interestingly, both genetically modified oncolytic adenovirus and PeptiCRAd elicited T cells-specific anti-tumor responses. However, in vitro cross-representation experiments, showed an advantage of PeptiCRAd as regards the fast presentation of the model epitope SIINFEKL from OVA in an immunogenic rather than tolerogenic fashion. Here two approaches used as cancer oncolytic vaccines have been explored and characterized for their efficacy. Although the generation of specific anti-tumor T cells was elicited in both approaches, PeptiCRAd retains the advantage of being rapidly adaptable by coating the adenovirus with a different set of tumor antigens, which is crucial in personalized cancer vaccines clinical setting.

Recent advances in targeted drug delivery for the treatment of pancreatic ductal adenocarcinoma

INTRODUCTION

Pancreatic ductal adenocarcinoma (PDAC) has become a serious health problem with high impact worldwide. The heterogeneity of PDAC makes it difficult to apply drug delivery systems (DDS) used in other cancer models, for example, the poorly developed vascular system makes anti-angiogenic therapy ineffective. Due to its various malignant pathological changes, drug delivery against PDAC is a matter of urgent concern. Based on this situation, various drug delivery strategies specially designed for PDAC have been generated.

AREAS COVERED

This review will briefly describe how delivery systems can be designed through nanotechnology and formulation science. Most research focused on penetrating the stromal barrier, exploiting and alleviating the hypoxic microenvironment, targeting immune cells, or designing vaccines, and combination therapies. This review will summarize the ways to reverse the malignant pathological features of PDAC and hopefully provide ideas for subsequent studies.

EXPERT OPINION

Drug delivery systems designed to achieve penetrating functions or to alleviate hypoxia and activate immunity have achieved good therapeutic results in animal models in several studies. In future studies, there is a need to deliver PDAC therapeutics in a more precise manner, or the use of drug carriers for multiple functions simultaneously, are potential therapeutic strategy.

On the development of a neoantigen vaccine for the prevention of Lynch Syndrome

Lynch Syndrome (LS) is an autosomal dominant genetic condition that causes a high risk of colorectal cancer (CRC). The hallmark of LS is genetic instability as a result of mismatch repair (MMR) deficiency, particularly in repetitive low complexity regions called microsatellites (MS). MLH1^-/- mice deficient in MMR are prone to developing tumors in the colon, upon oral administration of dextran sodium sulfate (DSS), at a rate of more than 70%. Using this LS mouse model, we found a novel tumor neo-antigen from a deletion mutation of the coding MS in the SENP6 gene that prevented tumorigenesis or hindered tumor growth rate in immunized mice. This was accomplished via high throughput exome sequencing of DSS-induced colorectal tumors in the MLH1^-/- mice and predicting the most highly immunogenic mutant gene products processed and presented as antigens in C57B6 MHC-I molecules. Throughout this study, we were able to prove the validity of the vaccine by analyzing the colorectal tumors in immunized DSS-treated mice using either our epitope, called Sp6D1, or an unrelated peptide as a negative control. Tumors developed in this context were found to be antigenic and Sp6D1-specific CD8⁺ tumor infiltrating lymphocytes (TILs) were detected by flow cytometry and cytotoxic T lymphocytes (CTL) killing assays. Additionally, immunohistochemistry showed that tumor-adjacent tertiary lymphoid organs were a potentially significant source of CD8⁺ lymphocytes. Altogether, our results indicate that there may be a protective effect to patients carrying LS mutations through the induction of a peptide-specific CTL response from the use of neoepitope vaccination. This article is protected by copyright. All rights reserved.

Supramolecular cancer photoimmunotherapy based on precise peptide self-assembly design

Combinational photoimmunotherapy (PIT) is considered to be an ideal strategy for the treatment of highly recurrent and metastatic cancer, because it can ablate the primary tumor and provide in situ an autologous tumor vaccine to induce the host immune response, ultimately achieving the goal of controlling tumor growth and distal metastasis. Significant efforts have been devoted to enhancing the immune response caused by phototherapy-eliminated tumors. Recently, supramolecular PIT nanoagents based on precise peptide self-assembly design have been employed to improve the efficacy of photoimmunotherapy by utilizing the stability, targeting capability and flexibility of drugs, increasing tumor immunogenicity and realizing the synergistic amplification of immune effects through multiple pathways and collaborative strategy. This review summarizes peptide-based supramolecular PIT nanoagents for phototherapy-synergized cancer immunotherapy and its progress in enhancing the effect of photoimmunotherapy, especially focusing on the design of peptide-based PIT nanoagents, the progress of bioactive peptides combined photoimmunotherapy, and the synergistic immune-response mechanism.

Beyond Sequencing: Prioritizing and Delivering Neoantigens for Cancer Vaccines

Neoantigens are tumor-specific proteins and peptides that can be highly immunogenic. Immune-mediated tumor rejection is strongly associated with cytotoxic responses to neoantigen-derived peptides in noncovalent association with self-HLA molecules. Neoantigen-based therapies, such as adoptive T cell transfer, have shown the potential to induce remission of treatment-resistant metastatic disease in select patients. Cancer vaccines are similarly designed to elicit or amplify antigen-specific T cell populations and stimulate directed antitumor immunity, but the selection and prioritization of the neoantigens remains a challenge. Bioinformatic algorithms can predict tumor neoantigens from somatic mutations, insertion-deletions, and other aberrant peptide products, but this often leads to hundreds of potential neoepitopes, all unique for that tumor. Selecting neoantigens for cancer vaccines is complicated by the technical challenges of neoepitope discovery, the diversity of HLA molecules, and intratumoral heterogeneity of passenger mutations leading to immune escape. Despite strong preclinical evidence, few neoantigen cancer vaccines tested in vivo have generated epitope-specific T cell populations, suggesting suboptimal immune system activation. In this chapter, we review factors affecting the prioritization and delivery of candidate neoantigens in the design of therapeutic and preventive cancer vaccines and consider synergism with standard chemotherapies.