Extending traditional antibody therapies: Novel discoveries in immunotherapy and clinical applications

Monoclonal antibodies: From magic bullet to precision weapon

Monoclonal antibodies (mAbs) are used to prevent, detect, and treat a broad spectrum of non-communicable and communicable diseases. Over the past few years, the market for mAbs has grown exponentially with an expected compound annual growth rate (CAGR) of 11.07% from 2024 (237.64 billion USD estimated at the end of 2023) to 2033 (679.03 billion USD expected by the end of 2033). Ever since the advent of hybridoma technology introduced in 1975, antibody-based therapeutics were realized using murine antibodies which further progressed into humanized and fully human antibodies, reducing the risk of immunogenicity. Some benefits of using mAbs over conventional drugs include a drastic reduction in the chances of adverse reactions, interactions between drugs, and targeting specific proteins. While antibodies are very efficient, their higher production costs impede the process of commercialization. However, their cost factor has been improved by developing biosimilar antibodies as affordable versions of therapeutic antibodies. Along with the recent advancements and innovations in antibody engineering have helped and will furtherly help to design bio-better antibodies with improved efficacy than the conventional ones. These novel mAb-based therapeutics are set to revolutionize existing drug therapies targeting a wide spectrum of diseases, thereby meeting several unmet medical needs. This review provides comprehensive insights into the current fundamental landscape of mAbs development and applications and the key factors influencing the future projections, advancement, and incorporation of such promising immunotherapeutic candidates as a confrontation approach against a wide list of diseases, with a rationalistic mentioning of any limitations facing this field.

Accelerating drug discovery, development, and clinical trials by artificial intelligence

Artificial intelligence (AI) has profoundly advanced the field of biomedical research, which also demonstrates transformative capacity for innovation in drug development. This paper aims to deliver a comprehensive analysis of the progress in AI-assisted drug development, particularly focusing on small molecules, RNA, and antibodies. Moreover, this paper elucidates the current integration of AI methodologies within the industrial drug development framework. This encompasses a detailed examination of the industry-standard drug development process, supplemented by a review of medications presently undergoing clinical trials. Conclusively, the paper tackles a predominant obstacle within the AI pharmaceutical sector: the absence of AI-conceived drugs receiving approval. This paper also advocates for the adoption of large language models and diffusion models as a viable strategy to surmount this challenge. This review not only underscores the significant potential of AI in drug discovery but also deliberates on the challenges and prospects within this dynamically progressing field.

Construction of a versatile fusion protein for targeted therapy and immunotherapy

Antibody (Ab)-based drugs have been widely used in targeted therapies and immunotherapies, leading to significant improvements in tumor therapy. However, the failure of Ab therapy due to the loss of target antigens or Ab modifications that affect its function limits its application. In this study, we expanded the application of antibodies (Abs) by constructing a fusion protein as a versatile tool for Ab-based target cell detection, delivery, and therapy. We first constructed a SpaC Catcher (SpaCC for short) fusion protein that included the C domains of Staphylococcal protein A (SpaC) and the SpyCatcher. SpaCC conjugated with SpyTag-X (S-X) to form the SpaCC-S-X complex, which binds non-covalently to an Ab to form the Ab-SpaCC-S-X protein complex. The "X" can be a variety of small molecules such as fluoresceins, cell-penetrating peptide TAT, Monomethyl auristatin E (MMAE), and DNA. We found that Ab-SpaCC-S-FITC(-TAT) could be used for target cell detection and delivery. Besides, we synthesized the Ab-SpaCC-SN3-MMAE complex by linking Ab with MMAE by SpaCC, which improved the cytotoxicity of small molecule toxins. Moreover, we constructed an Ab-DNA complex by conjugating SpaCC with the aptamer (Ap) and found that Ab-SpaCC-SN3-Ap boosted the tumor-killing function of T-cells by retargeting tumor cells. Thus, we developed a multifunctional tool that could be used for targeted therapies and immunotherapies, providing a cheap and convenient novel drug development strategy.

Recent Advances in the Development of Monoclonal Antibodies and Next-Generation Antibodies

mAbs are highly indispensable tools for diagnostic, prophylactic, and therapeutic applications. The first technique, hybridoma technology, was based on fusion of B lymphocytes with myeloma cells, which resulted in generation of single mAbs against a specific Ag. Along with hybridoma technology, several novel and alternative methods have been developed to improve mAb generation, ranging from electrofusion to the discovery of completely novel technologies such as B cell immortalization; phage, yeast, bacterial, ribosome, and mammalian display systems; DNA/RNA encoded Abs; single B cell technology; transgenic animals; and artificial intelligence/machine learning. This commentary outlines the evolution, methodology, advantages, and limitations of various mAb production techniques. Furthermore, with the advent of next-generation Ab technologies such as single-chain variable fragments, nanobodies, bispecific Abs, Fc-engineered Abs, Ab biosimilars, Ab mimetics, and Ab-drug conjugates, the healthcare and pharmaceutical sectors have become resourceful to develop highly specific mAb treatments against various diseases such as cancer and autoimmune and infectious diseases.

A glycosylation-related signature predicts survival in pancreatic cancer

BACKGROUND

Tumor initiation and progression are closely associated with glycosylation. However, glycosylated molecules have not been the subject of extensive studies as prognostic markers for pancreatic cancer. The objectives of this study were to identify glycosylation-related genes in pancreatic cancer and use them to construct reliable prognostic models.

MATERIALS AND METHODS

The Cancer Genome Atlas and Gene Expression Omnibus databases were used to assess the differential expression of glycosylation-related genes; four clusters were identified based on consistent clustering analysis. Kaplan-Meier analyses identified three glycosylation-related genes associated with overall survival. LASSO analysis was then performed on The Cancer Genome Atlas and International Cancer Genome Consortium databases to identify glycosylation-related signatures. We identified 12 GRGs differently expressed in pancreatic cancer and selected three genes (SEL1L, TUBA1C, and SDC1) to build a prognostic model. Thereafter, patients were divided into high and low-risk groups. Eventually, we performed Quantitative real-time PCR (qRT-PCR) to validate the signature.

RESULTS

Clinical outcomes were significantly poorer in the high-risk group than in the low-risk group. There were also significant correlations between the high-risk group and several risk factors, including no-smoking history, drinking history, radiotherapy history, and lower tumor grade. Furthermore, the high-risk group had a higher proportion of immune cells. Eventually, three glycosylation-related genes were validated in human PC cell lines.

CONCLUSION

This study identified the glycosylation-related signature for pancreatic cancer. It is an effective predictor of survival and can guide treatment decisions.

Mucosal absorption of antibody drugs enhanced by cell-penetrating peptides anchored to a platform of polysaccharides

Our previous studies demonstrated that L-octaarginine grafted onto hyaluronic acid via a tetraglycine spacer significantly enhanced intranasal absorption of protein drugs with a molecular weight (Mw) of 22 kDa or less. The present study focused on its potential as an absorption enhancer for antibody drugs with a larger Mw and the enhancement mechanism. When ranibizumab (48 kDa) alone was intranasally administered in mice, its absolute bioavailability was 0.67% on average. The mean bioavailability elevated to 6.2% under coadministration with tetraglycine-L-octaarginine-linked hyaluronic acid. A similar result was observed under substitution of ranibizumab with certolizumab pegol (91 kDa), although bioavailability itself decreased with the Mw increase, irrespective of coadministration with the hyaluronic acid derivative. Rat experiments also revealed that coadministration with the polysaccharide derivative resulted in significant enhancement of intranasal absorption of trastuzumab (148 kDa). In vitro studies using gene-knocked down cells indicated that syndecan-4-induced macropinocytosis played a crucial role on acceleration of antibody uptake into epithelial cells on the nasal mucosa, irrespective of their Mw. It appeared that neither clathrin heavy chain nor caveolin-1 involved in cellular uptake of antibodies. Tetraglycine-L-octaarginine-linked hyaluronic acid was concluded to be a promising delivery tool that possessed universal absorption-enhancing abilities independent to Mw of biologics.

Exploiting the Features of Short Peptides to Recognize Specific Cell Surface Markers

Antibodies are the macromolecules of choice to ensure specific recognition of biomarkers in biological assays. However, they present a range of shortfalls including a relatively high production cost and limited tissue penetration. Peptides are relatively small molecules able to reproduce sequences of highly specific paratopes and, although they have less biospecificity than antibodies, they offer advantages like ease of synthesis, modifications of their amino acid sequences and tagging with fluorophores and other molecules required for detection. This work presents a strategy to design peptide sequences able to recognize the CD44 hyaluronic acid receptor present in the plasmalemma of a range of cells including human bone marrow stromal mesenchymal cells. The protocol of identification of the optimal amino acid sequence was based on the combination of rational design and in silico methodologies. This protocol led to the identification of two peptide sequences which were synthesized and tested on human bone marrow mesenchymal stromal cells (hBM-MSCs) for their ability to ensure specific binding to the CD44 receptor. Of the two peptides, one binds CD44 with sensitivity and selectivity, thus proving its potential to be used as a suitable alternative to this antibody in conventional immunostaining. In the context of regenerative medicine, the availability of this peptide could be harnessed to functionalize tissue engineering scaffolds to anchor stem cells as well as to be integrated into systems such as cell sorters to efficiently isolate MSCs from biological samples including various cell subpopulations. The data here reported can represent a model for developing peptide sequences able to recognize hBM-MSCs and other types of cells and for their integration in a range of biomedical applications.

Multivalent protein-drug conjugates - An emerging strategy for the upgraded precision and efficiency of drug delivery to cancer cells

With almost 20 million new cases per year, cancer constitutes one of the most important challenges for public health systems. Unlike traditional chemotherapy, targeted anti-cancer strategies employ sophisticated therapeutics to precisely identify and attack cancer cells, limiting the impact of drugs on healthy cells and thereby minimizing the unwanted side effects of therapy. Protein drug conjugates (PDCs) are a rapidly growing group of targeted therapeutics, composed of a cancer-recognition factor covalently coupled to a cytotoxic drug. Several PDCs, mainly in the form of antibody-drug conjugates (ADCs) that employ monoclonal antibodies as cancer-recognition molecules, are used in the clinic and many PDCs are currently in clinical trials. Highly selective, strong and stable interaction of the PDC with the tumor marker, combined with efficient, rapid endocytosis of the receptor/PDC complex and its subsequent effective delivery to lysosomes, is critical for the efficacy of targeted cancer therapy with PDCs. However, the bivalent architecture of contemporary clinical PDCs is not optimal for tumor receptor recognition or PDCs internalization. In this review, we focus on multivalent PDCs, which represent a rapidly evolving and highly promising therapeutics that overcome most of the limitations of current bivalent PDCs, enhancing the precision and efficiency of drug delivery to cancer cells. We present an expanding set of protein scaffolds used to generate multivalent PDCs that, in addition to folding into well-defined multivalent molecular structures, enable site-specific conjugation of the cytotoxic drug to ensure PDC homogeneity. We provide an overview of the architectures of multivalent PDCs developed to date, emphasizing their efficacy in the targeted treatment of various cancers.

The First-In-Class Anti-AXL×CD3ε Pronectin™-Based Bispecific T-Cell Engager Is Active in Preclinical Models of Human Soft Tissue and Bone Sarcomas

Sarcomas are heterogeneous malignancies with limited therapeutic options and a poor prognosis. We developed an innovative immunotherapeutic agent, a first-in-class Pronectin™-based Bispecific T-Cell Engager (pAXL×CD3ε), for the targeting of AXL, a TAM family tyrosine kinase receptor highly expressed in sarcomas. AXL expression was first analyzed by flow cytometry, qRT-PCR, and Western blot on a panel of sarcoma cell lines. The T-cell-mediated pAXL×CD3ε cytotoxicity against sarcoma cells was investigated by flow cytometry, luminescence assay, and fluorescent microscopy imaging. The activation and degranulation of T cells induced by pAXL×CD3ε were evaluated by flow cytometry. The antitumor activity induced by pAXL×CD3ε in combination with trabectedin was also investigated. In vivo activity studies of pAXL×CD3ε were performed in immunocompromised mice (NSG), engrafted with human sarcoma cells and reconstituted with human peripheral blood mononuclear cells from healthy donors. Most sarcoma cells showed high expression of AXL. pAXL×CD3ε triggered T-lymphocyte activation and induced dose-dependent T-cell-mediated cytotoxicity. The combination of pAXL×CD3ε with trabectedin increased cytotoxicity. pAXL×CD3ε inhibited the in vivo growth of human sarcoma xenografts, increasing the survival of treated mice. Our data demonstrate the antitumor efficacy of pAXL×CD3ε against sarcoma cells, providing a translational framework for the clinical development of pAXL×CD3ε in the treatment of human sarcomas, aggressive and still-incurable malignancies.

Development of a validated molecular analytical method to determine the viral safety of F(AB´)2 products: A novel application for a well-known technique

The immunotherapy agents derived from horses are biological products that allow the neutralization of clinically relevant immunogens, such as the SARS-CoV-2 virus that causes COVID-19, or the neutralization of toxins present in the venoms of snakes, spiders, and other poisonous animals. Due to their importance, detecting adventitious viruses in equine hyperimmune serum (raw material in industrial processes) is a critical step to support the safety of products for human use, and, in consequence, it is a requirement for commercialization and distribution. The safety of the finished product is based on three complementary approaches: (i) testing of the source material (horse serum) donations, (ii) release of the starting material (i.e., pool of horse serum) based on non-reactivity for a range of human infectious or pathogenic viruses, and (iii) validate (selected) steps of the manufacturing process for their capacity to inactivate and/or remove a wide range of viruses potentially present in the starting material. Orthogonal approaches to reduce viral contamination risk include implementing a reliable and validated system for detecting adventitious viruses. Thus, it is necessary to establish trustworthy and sufficiently sensitive analytical methods to evidence the lack of viruses to assure the safety of the therapeutic product. Therefore, in this research, an analytical method based on end-point Reverse Transcription Polymerase Chain Reaction (RT-PCR) was developed, implemented, and validated in hyperimmune equine serum samples to detect Venezuelan equine encephalitis virus, West Nile virus, and Rabies virus.

Targeted Nanoparticles for the Binding of Injured Vascular Endothelium after Percutaneous Coronary Intervention

Percutaneous coronary intervention (PCI) is a common procedure for the management of coronary artery obstruction. However, it usually causes vascular wall injury leading to restenosis that limits the long-term success of the PCI endeavor. The ultimate objective of this study was to develop the targeting nanoparticles (NPs) that were destined for the injured subendothelium and attract endothelial progenitor cells (EPCs) to the damaged location for endothelium regeneration. Biodegradable poly(lactic-co-glycolic acid) (PLGA) NPs were conjugated with double targeting moieties, which are glycoprotein Ib alpha chain (GPIbα) and human single-chain antibody variable fragment (HuscFv) specific to the cluster of differentiation 34 (CD34). GPIb is a platelet receptor that interacts with the von Willebrand factor (vWF), highly deposited on the damaged subendothelial surface, while CD34 is a surface marker of EPCs. A candidate anti-CD34 HuscFv was successfully constructed using a phage display biopanning technique. The HuscFv could be purified and showed binding affinity to the CD34-positive cells. The GPIb-conjugated NPs (GPIb-NPs) could target vWF and prevent platelet adherence to vWF in vitro. Furthermore, the HuscFv-conjugated NPs (HuscFv-NPs) could capture CD34-positive cells. The bispecific NPs have high potential to locate at the damaged subendothelial surface and capture EPCs for accelerating the vessel repair.

Identification of an Inflammatory Response-Related Gene Signature to Predict Survival and Immune Status in Glioma Patients

Background

Glioma is the most common primary brain tumor with high mortality and poor outcomes. As a hallmark of cancers, inflammatory responses are crucial for their progression. The present study is aimed at exploring the prognostic value of inflammatory response-related genes (IRRGs) and constructing a prognostic IRRG signature for gliomas.

Materials and Methods

We investigated the relationship between IRRGs and gliomas by integrating the transcriptomic data for gliomas from public databases. Differentially expressed IRRGs (DE-IRRGs) were identified in the GSE4290 cohort. Further, univariate, least absolute shrinkage and selection operator, and multivariate Cox regression analyses were conducted to construct an IRRG signature using The Cancer Genome Atlas (TCGA) cohort. Gliomas from the Chinese Glioma Genome Atlas (CGGA) cohort were employed for independent validation. The performance of gene signature was assessed by survival and receiver operating characteristic curve analyses. The differences in clinical correlations, immune infiltrate types, immunotherapeutic response predictions, and pathway enrichment among subgroups were investigated via bioinformatic algorithms.

Results

In total, 37 DE-IRRGs were determined, of which 31 were found to be associated with survival. Ultimately, eight genes were retained to construct an IRRG signature that further classified glioma patients into two groups; the high-risk group suffered a poorer outcome as compared to the low-risk group. Furthermore, the high-risk group was significantly correlated with several risk factors, including older age, higher tumor grade, IDH wild type, 1p19q noncodel, and MGMT unmethylation. The nomogram was constructed by integrating the risk scores and other independent clinical characteristics. Moreover, the high-risk group had a greater immune infiltration and was most likely to benefit from immunotherapy. Gene set enrichment analysis suggested that immune and oncogenic pathways were enriched in high-risk glioma patients.

Conclusion

We constructed a signature composed of eight IRRGs for gliomas, which could effectively predict survival and guide decision-making for treatment.

The Research Progress of Antiangiogenic Therapy, Immune Therapy and Tumor Microenvironment

Anti-angiogenesis therapy, a promising strategy against cancer progression, is limited by drug-resistance, which could be attributed to changes within the tumor microenvironment. Studies have increasingly shown that combining anti-angiogenesis drugs with immunotherapy synergistically inhibits tumor growth and progression. Combination of anti-angiogenesis therapy and immunotherapy are well-established therapeutic options among solid tumors, such as non-small cell lung cancer, hepatic cell carcinoma, and renal cell carcinoma. However, this combination has achieved an unsatisfactory effect among some tumors, such as breast cancer, glioblastoma, and pancreatic ductal adenocarcinoma. Therefore, resistance to anti-angiogenesis agents, as well as a lack of biomarkers, remains a challenge. In this review, the current anti-angiogenesis therapies and corresponding drug-resistance, the relationship between tumor microenvironment and immunotherapy, and the latest progress on the combination of both therapeutic modalities are discussed. The aim of this review is to discuss whether the combination of anti-angiogenesis therapy and immunotherapy can exert synergistic antitumor effects, which can provide a basis to exploring new targets and developing more advanced strategies.

Applying Synthetic Biology with Rational Design to Nature’s Greatest Challenges: Bioengineering Immunotherapeutics for the Treatment of Glioblastoma

Improvements in bioengineering methodology and tools have allowed for significant progress in the development of therapeutics and diagnostics in medicine, as well as progress in many other diverse industries, such as materials manufacturing, food and agriculture, and consumer goods. Glioblastomas present significant challenges to adequate treatment, in part due to their immune-evasive and manipulative nature. Rational-design bioengineering using novel scaffolds, biomaterials, and inspiration across disciplines can push the boundaries in treatment development to create effective therapeutics for glioblastomas. In this review, we will discuss bioengineering strategies currently applied across diseases and disciplines to inspire creative development for GBM immunotherapies.

A Novel Pyroptosis-Related Signature for Predicting Prognosis and Indicating Immune Microenvironment Features in Osteosarcoma

Osteosarcoma is a common malignant bone tumor with a propensity for drug resistance, recurrence, and metastasis. A growing number of studies have elucidated the dual role of pyroptosis in the development of cancer, which is a gasdermin-regulated novel inflammatory programmed cell death. However, the interaction between pyroptosis and the overall survival (OS) of osteosarcoma patients is poorly understood. This study aimed to construct a prognostic model based on pyroptosis-related genes to provide new insights into the prognosis of osteosarcoma patients. We identified 46 differentially expressed pyroptosis-associated genes between osteosarcoma tissues and normal control tissues. A total of six risk genes affecting the prognosis of osteosarcoma patients were screened to form a pyroptosis-related signature by univariate and LASSO regression analysis and verified using GSE21257 as a validation cohort. Combined with other clinical characteristics, including age, gender, and metastatic status, we found that the pyroptosis-related signature score, which we named “PRS-score,” was an independent prognostic factor for patients with osteosarcoma and that a low PRS-score indicated better OS and a lower risk of metastasis. The result of ssGSEA and ESTIMATE algorithms showed that a lower PRS-score indicated higher immune scores, higher levels of tumor infiltration by immune cells, more active immune function, and lower tumor purity. In summary, we developed and validated a pyroptosis-related signature for predicting the prognosis of osteosarcoma, which may contribute to early diagnosis and immunotherapy of osteosarcoma.