Cancer continues to be a global health concern, necessitating innovative solutions for treatment. Tri-specific killer engagers (TriKEs) have emerged as a promising class of immunotherapeutic agents, offering a multifaceted approach to cancer treatment. TriKEs simultaneously engage and activate natural killer (NK) cells while specifically targeting cancer cells, representing an outstanding advancement in immunotherapy. This review explores the generation and mechanisms of TriKEs, highlighting their advantages over other immunotherapies and discussing their potential impact on clinical trials and cancer treatment. TriKEs are composed of three distinct domains, primarily antibody-derived building blocks, linked together by short amino acid sequences. They incorporate critical elements, anti-cluster of differentiation 16 (CD16) and interleukin-15 (IL-15), which activate and enhance NK cell function, together with specific antibody to target each cancer. TriKEs exhibit remarkable potential in preclinical and early clinical studies across various cancer types, making them a versatile tool in cancer immunotherapy. Comparative analyses with other immunotherapies, such as chimeric antigen receptor-T (CAR-T) cell therapy, immune checkpoint inhibitors (ICIs), cytokine therapies, and monoclonal antibodies (mAbs), reveal the unique advantages of TriKEs. They offer a safer pathway for immunotherapy by targeting cancer cells without hyperactivating T cells, reducing off-target effects and complications. The future of TriKEs involves addressing challenges related to dosing, tumor-associated antigen (TAA) expression, and NK cell suppression. Researchers are exploring innovative dosing strategies, enhancing specificity through tumor-specific antigens (TSAs), and combining TriKEs with other therapies for increased efficacy.

Colorectal cancer (CRC) is a heterogeneous disease. Conventional two-dimensional (2D) culture employing cell lines was developed to study the molecular properties of CRC in vitro. Although these cell lines which are isolated from the tumor niche in which cancer develop, the translation to human model such as studying drug response is often hindered by the inability of cell lines to recapture original tumor features and the lack of heterogeneous clinical tumors represented by this 2D model, differed from in vivo condition. These limitations which may be overcome by utilizing three-dimensional (3D) culture consisting of spheroids and organoids. Over the past decade, great advancements have been made in optimizing culture method to establish spheroids and organoids of solid tumors including of CRC for multiple purposes including drug screening and establishing personalized medicine. These structures have been proven to be versatile and robust models to study CRC progression and deciphering its heterogeneity. This review will describe on advances in 3D culture technology and the application as well as the challenges of CRC-derived spheroids and organoids as a mode to screen for anticancer drugs.

In the 21st century, advances in basic research have provided new insights in the field of pediatric oncology. Pediatric patients tend to experience higher levels of distressing symptoms, which together form a symptom cluster. In clinical practice, these symptom clusters are reported daily by children and adolescents with cancer. Translational research has emerged as the translation of new knowledge from basic science into clinical practice. Understanding how neuroimmunoendocrine pathways regulate cancer development and the aspects underlying the specific therapies, such as chemotherapy and immunotherapy, is an important frontier for future research in pediatric oncology. The goal of translational research is to show how different variables in tumor and patient characteristics explain the differential effects of interventions, as translational research provides new insights into the management of cancer symptoms in children and adolescents with cancer. Together, this approach could lead to improvements in pediatric oncology care worldwide.

Aerobic glycolysis also known as the Warburg effect, remains a hallmark of various cancers, including ovarian cancer. Cancer cells undergo metabolic changes to sustain their tumorigenic properties and adapt to environmental conditions, such as hypoxia and nutrient starvation. Altered metabolic pathways not only facilitate ovarian cancer cells’ survival and proliferation but also endow them to metastasize, develop resistance to chemotherapy, maintain cancer stem cell phenotype, and escape anti-tumor immune responses. Glucose transporters (GLUTs), which play a pivotal role as the rate-limiting step in glycolysis, are frequently overexpressed in a variety of tumors, including ovarian cancer. Multiple oncoproteins can regulate GLUT proteins, promoting tumor proliferation, migration, and metastasis, either dependent or independent of glycolysis. This review examines the alteration of GLUT proteins, particularly GLUT1, in ovarian cancer and its impact on cancer initiation, progression, and resistance to treatment. Additionally, it highlights the role of these proteins as biomarkers for diagnosis and prognosis in ovarian cancer, and delves into novel therapeutic strategies currently under development that target GLUT isoforms.

Fluoropyrimidines, crucial in cancer treatment, often cause toxicity concerns even at standard doses. Toxic accumulation of fluoropyrimidine metabolites, culminating in adverse effects, can stem from impaired dihydropyrimidine dehydrogenase (DPYD) enzymatic function. Emerging evidence underscores the role of single nucleotide polymorphisms (SNPs) in DPYD gene, capable of inducing DPYD activity deficiency. Consequently, DPYD genotyping’s importance is on the rise in clinical practice before initiating fluoropyrimidine treatment. Although polymerase chain reaction (PCR) followed by Sanger sequencing (SS; PCR-SS) is a prevalent method for DPYD genotyping, it may encounter limitations. In this context, there is reported a case in which a routine PCR-SS approach for genotyping DPYD SNP rs55886062 failed in a proband of African descent. The Clinical Pharmacogenetics Implementation Consortium (CPIC) categorizes the guanine (G) allele of this SNP as non-functional. The enforcement of whole genome sequencing (WGS) approach led to the identification of two adenine (A) insertions near the PCR primers annealing regions in the proband, responsible for a sequence frameshift and a genotyping error for rs55886062. These SNPs (rs145228578, 1-97981199-T-TA and rs141050810, 1-97981622-G-GA) were extremely rare in non-Finnish Europeans (0.05%) but prevalent in African populations (16%). Although limited evidence was available for these SNPs, they were catalogued as benign variants in public databases. Notably, these two SNPs exhibited a high linkage disequilibrium [LD; squared correlation coefficient (R²) = 0.98]. These findings highlighted the importance to consider the prevalence of genetic variants within diverse ethnic populations when designing primers and probes for SNP genotyping in pharmacogenetic testing. This preventive measure is essential to avoid sequence frameshifts or primer misalignments arising from SNP occurrences in the genome, which can compromise PCR-SS and lead to genotyping failures. Furthermore, this case highlights the significance of exploring alternative genotyping approaches, like WGS, when confronted with challenges associated with conventional techniques.

Pheochromocytomas and paragangliomas (PPGLs) have emerged as one of the most common endocrine tumors. It epitomizes fascinating crossroads of genetic, metabolic, and endocrine oncology, providing a canvas to explore the molecular intricacies of tumor biology. Predominantly rooted in the aberration of metabolic pathways, particularly the Krebs cycle and related enzymatic functionalities, PPGLs manifest an intriguing metabolic profile, highlighting elevated levels of oncometabolites like succinate and fumarate, and furthering cellular malignancy and genomic instability. This comprehensive review aims to delineate the multifaceted aspects of tumor metabolism in PPGLs, encapsulating genetic factors, oncometabolites, and potential therapeutic avenues, thereby providing a cohesive understanding of metabolic disturbances and their ramifications in tumorigenesis and disease progression. Initial investigations into PPGLs metabolomics unveiled a stark correlation between specific genetic mutations, notably in the succinate dehydrogenase complex (SDHx) genes, and the accumulation of oncometabolites, establishing a pivotal role in epigenetic alterations and hypoxia-inducible pathways. By scrutinizing voluminous metabolic studies and exploiting technologies, novel insights into the metabolic and genetic aspects of PPGLs are perpetually being gathered elucidating complex interactions and molecular machinations. Additionally, the exploration of therapeutic strategies targeting metabolic abnormalities has burgeoned harboring potential for innovative and efficacious treatment modalities. This review encapsulates the profound metabolic complexities of PPGLs, aiming to foster an enriched understanding and pave the way for future investigations and therapeutic innovations in managing these metabolically unique tumors.

Hematologists, geneticists, and clinicians came to a multidisciplinary agreement on the classification of lymphoid neoplasms that combines clinical features, histological characteristics, immunophenotype, and molecular pathology analyses. The current classification includes the World Health Organization (WHO) Classification of tumours of haematopoietic and lymphoid tissues revised 4th edition, the International Consensus Classification (ICC) of mature lymphoid neoplasms (report from the Clinical Advisory Committee 2022), and the 5th edition of the proposed WHO Classification of haematolymphoid tumours (lymphoid neoplasms, WHO-HAEM5). This article revises the recent advances in the classification of mature lymphoid neoplasms. Artificial intelligence (AI) has advanced rapidly recently, and its role in medicine is becoming more important as AI integrates computer science and datasets to make predictions or classifications based on complex input data. Summarizing previous research, it is described how several machine learning and neural networks can predict the prognosis of the patients, and classified mature B-cell neoplasms. In addition, new analysis predicted lymphoma subtypes using cell-of-origin markers that hematopathologists use in the clinical routine, including CD3, CD5, CD19, CD79A, MS4A1 (CD20), MME (CD10), BCL6, IRF4 (MUM-1), BCL2, SOX11, MNDA, and FCRL4 (IRTA1). In conclusion, although most categories are similar in both classifications, there are also conceptual differences and differences in the diagnostic criteria for some diseases. It is expected that AI will be incorporated into the lymphoma classification as another bioinformatics tool.

Cancer immunotherapy has emerged as a groundbreaking field, offering promising and transformative tools for oncological research and treatment. However, it faces several limitations, including variations in cancer types, dependence on the tumor microenvironments (TMEs), immune cell exhaustion, and adverse reactions. Magnetic nanoparticles, particularly magnetite nanoparticles (MNPs), with established pharmacodynamics and pharmacokinetics for clinical use, hold great promise in this context and are now being explored for therapeutic aims. Numerous preclinical studies have illustrated their efficacy in enhancing immunotherapy through various strategies, such as modulating leukocyte functions, creating favorable TMEs for cytotoxic T lymphocytes, combining with monoclonal antibodies, and stimulating the immune response via magnetic hyperthermia (MHT) treatment (Front Immunol. 2021;12:701485. doi: 10.3389/fimmu.2021.701485). However, the current clinical trials of MNPs are mostly for diagnostic aims and as a tool for generating hyperthermia for tumor ablation. With concerns about the adverse effects of MNPs in the in vivo systems, clinical translation and clinical study of MNP-boosted immunotherapy remains limited. The lack of extensive clinical investigations poses a current barrier to patient application. Urgent efforts are needed to ascertain both the efficacy of MNP-enhanced immunotherapy and its safety profile in combination therapy. This article reviews the roles, potential, and challenges of using MNPs in advancing cancer immunotherapy. The application of MNPs in boosting immunotherapy, and its perspective role in research and development is also discussed.

Innate lymphoid cells (ILCs) are the most recently discovered class of innate immune cells found to have prominent roles in various human immune-related pathologies such as infection and autoimmune diseases. However, their role in cancer was largely unclear until recently, where several emerging studies over the past few years unanimously demonstrate ILCs to be critical players in tumour immunity. Being the innate counterpart of T cells, ILCs are potent cytokine producers through which they orchestrate the overall immune response upstream of adaptive immunity thereby modulating T cell function. Out of the major ILC subsets, ILC1s have gained significant traction as potential immunotherapeutic candidates due to their central involvement with the anti-tumour type 1 immune response. ILC1s are potent producers of the well-established anti-tumour cytokine interferon γ (IFNγ), and exert direct cytotoxicity against cancer cells in response to the cytokine interleukin-15 (IL-15). However, in advanced diseases, ILC1s are found to demonstrate an exhausted phenotype in the tumour microenvironment (TME) with impaired effector functions, characterised by decreased responsiveness to cytokines and reduced IFNγ production. Tumour cells produce immunomodulatory cytokines such as transforming growth factor β (TGFβ) and IL-23, and through these suppress ILC1 anti-tumour actfivities and converts ILC1s to pro-tumoural ILC3s respectively, resulting in disease progression. This review provides a comprehensive overview of ILC1s in tumour immunity, and discusses the exciting prospects of harnessing ILC1s for cancer immunotherapy, either alone or in combination with cytokine-based treatment. The exciting prospects of targeting the upstream innate immune system through ILC1s may surmount the limitations associated with adaptive immune T cell-based strategies used in the clinic currently, and overcome cancer immunotherapeutic resistance.