Search Results (36)

Chimeric Antigen Receptor (CAR)-T cell therapy has transformed the treatment landscape of cancer, yet major challenges remain in enhancing efficacy, reducing adverse effects, and expanding accessibility. Autologous CAR-T cells, derived from individual patients, have achieved remarkable clinical success in hematologic malignancies; however, their highly personalized nature limits scalability, increases costs, and delays timely treatment. Allogeneic CAR-T cells generated from healthy donors provide an “off-the-shelf” alternative but face two critical immune barriers: graft-versus-host disease (GvHD), caused by donor T-cell receptor (TCR) recognition of host tissues, and host-versus-graft rejection, mediated by recipient immune responses against donor HLA molecules. Recent advances in genome engineering, particularly Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9, allow precise modification of donor T cells to overcome these limitations. For example, TRAC gene knockout eliminates TCR expression, preventing GvHD, while disruption of HLA molecules reduces immunogenicity without impairing cytotoxicity. Beyond hematologic cancers, CRISPR-edited allogeneic CAR-T cells targeting the NKG2D receptor have shown promise in preclinical studies and early-phase trials. NKG2D CAR-T cells recognize stress ligands (MICA/B, ULBP1–6) expressed on over 80% of diverse solid tumors, including pancreatic and ovarian cancers, thereby broadening therapeutic applicability. Nevertheless, the genomic editing process carries risks of off-target effects, including potential disruption of tumor suppressor genes and oncogenes, underscoring the need for stringent safety and quality control. This review examines the distinguishing features of allogeneic versus autologous CAR-T therapy, with a particular focus on NKG2D-based allogeneic CAR-T approaches for solid tumors. We summarize current strategies to mitigate immune barriers, discuss practical manufacturing challenges, and analyze available clinical data on NKG2D CAR-T trials. Collectively, these insights underscore both the promise and the hurdles of developing safe, universal, and scalable allogeneic CAR-T therapies for solid malignancies. Full article

UL16-binding protein 2 (ULBP2), a ligand for the activating receptor NKG2D, plays a dual role in tumor immunity, promoting immune activation or suppression, depending on the context. To investigate its impact on CD4⁺CD25⁺ T cell-targeted immunotherapies, we used a syngeneic CT26 colon cancer model engineered to express ULBP2 and compared tumor growth and tumor-infiltrating lymphocyte (TIL) profiles in control and ULBP2-expressing tumors treated with anti-CD4, anti-CD25, or anti-CTLA-4 antibodies. Tumor growth was uniformly assessed on day 21 post-transplantation, and TIL analysis was performed in groups with evaluable residual tumors. Anti-CD4 antibody significantly suppressed tumor growth in mock-transfected tumors, while no significant suppression was observed in ULBP2-expressing tumors. Anti-CD25 antibody had limited efficacy in mock tumors and tended to promote tumor growth in ULBP2-expressing tumors. Following these treatments, ULBP2 expression was associated with reduced NKG2D expression in CD8⁺ effector memory T cells, particularly PD-1^high subsets. In contrast, anti-CTLA-4 antibody treatment induced marked tumor regression irrespective of ULBP2 expression. These findings suggest that ULBP2–NKG2D signaling may contribute to altered CD8⁺ T cell phenotypes under T cell-modulatory conditions, potentially impacting the outcome of CD4⁺CD25⁺ T cell-targeted therapies and providing insights for optimizing immunotherapeutic strategies. Full article

UL-16 binding protein 2 (ULBP2), a human NKG2D ligand, has been identified as a poor prognostic factor in several cancers based on recent comprehensive analyses of immune-related genes using the Cancer Genome Atlas datasets. Despite its clinical significance, the functional role of ULBP2 in vivo remains largely unknown. In this study, we investigated the role of ULBP2 in modulating anti-tumor immunity using murine melanoma cell lines engineered to stably express surface-expressed or soluble ULBP2. Subcutaneous transplantation of ULBP2-expressing melanoma cells into syngeneic mice resulted in accelerated tumor growth, mediated by surface-expressed ULBP2, through the suppression of NKG2D-dependent immune responses. In vitro experiments revealed that sustained exposure to tumor-expressed ULBP2 reduced NKG2D expression and cytotoxic activity of splenocytes. In contrast, soluble ULBP2 did not significantly affect tumor growth or immune responses. These findings suggest that surface-expressed ULBP2 plays a pivotal role in tumor immune evasion and highlight its potential as a therapeutic target to enhance anti-tumor immunity. Full article

The immune system’s ability to detect and eliminate transformed cells is a critical factor in suppressing cancer development. However, immune surveillance in tumors is often disrupted by various immune escape mechanisms, many of which remain poorly understood. The Natural Killer Group 2D (NKG2D) receptor is an activating receptor expressed on natural killer (NK) cells and cytotoxic T lymphocytes. It can recognize and bind with varying affinities to a wide range of structurally diverse ligands, including MHC class I chain-related proteins A and B (MICA and MICB) and members of the ULBP family (ULBP1-6). The expression of these ligands plays a crucial role in immune antitumor responses and cancer immunoevasion mechanisms. Some evidence suggests that functional polymorphisms in the NKG2D receptor and the genes encoding its ligands significantly influence HLA-independent cancer immunosurveillance. Consequently, the NKG2D-NKG2D ligands (NKG2DLs) axis represents a promising target for developing novel therapeutic strategies. This review aims to provide a general overview of the role of NKG2D and its ligands in various malignancies and explore their potential in advancing personalized cancer treatment protocols. Full article

The genetic improvement of beef cattle breeds is crucial for the advancement of the beef cattle industry. Whole-genome resequencing technology has been widely applied in genetic breeding as well as research on selection signatures in beef cattle. In this study, 20× whole-genome resequencing was performed on 282 Angus cattle from the Ningxia region, and a high-quality dataset encompassing extensive genomic variations across the entire genome was constructed. The iHS test identified 495 selection signal regions, which included pregnancy-associated glycoprotein (PAG) family genes and immune-related genes such as UL16-binding protein 21 (ULBP21), CD1b molecule (CD1B), and tumor necrosis factor ligand superfamily member 11 (TNFSF11). A quantitative trait locus (QTL) enrichment analysis revealed that several economic traits, including longissimus muscle area, marbling score, carcass weight, average daily gain, and milk yield, were significantly enriched in cattle with these selection signatures. Although the enrichment of QTLs for health traits was low, immune-related genes may indirectly contribute to improvements in production performance. These findings show the genetic basis of economic and adaptive traits in Ningxia Angus cattle, providing a theoretical foundation and guidance for further genetic improvement and breeding strategies. Full article

Glioblastoma (GBM) is an immunologically cold tumor, but several immunotherapy-based strategies show promise, including the administration of ex vivo expanded and activated cytotoxic gamma delta T cells. Cytotoxicity is partially mediated through interactions with natural killer group 2D ligands (NKG2DL) on tumor cells. We sought to determine whether the addition of the blood–brain barrier penetrant PARP inhibitor niraparib to the standard of care DNA alkylator temozolomide (TMZ) could upregulate NKG2DL, thereby improving immune cell recognition. Changes in viability were consistent with prior publications as there was a growth inhibitory effect of the combination of TMZ and niraparib. However, decreases in viability did not always correlate with changes in NKG2DL mRNA. ULBP1/Mult-1 mRNA was increased with the combination therapy in comparison to either drug alone in two of the three cell types tested, even though viability was consistently decreased. mRNA expression correlated with protein levels and ULBP1/MULT-1 cell surface protein was significantly increased with TMZ and niraparib treatment in four of the five cell types tested. Gamma delta T cell-mediated cytotoxicity at a 10:1 effector-to-target ratio was significantly increased upon pretreatment of cells derived from a GBM PDX with TMZ and niraparib in comparison to the control or either drug alone. Together, these data demonstrate that the combination of PARP inhibition, DNA alkylation, and gamma delta T cell therapy has the potential for the treatment of GBM. Full article

Ligands of the natural killer group 2D (NKG2DL) family are expressed on malignant cells and are usually absent from healthy tissues. Recognition of NKG2DLs such as MICA/B and ULBP1-3 by the activating immunoreceptor NKG2D, expressed by NK and cytotoxic T cells, stimulates anti-tumor immunity in breast cancer. Upregulation of membrane-bound NKG2DLs in breast cancer has been demonstrated by immunohistochemistry. Tumor cells release NKG2DLs via proteolytic cleavage as soluble (s)NKG2DLs, which allows for effective immune escape and is associated with poor prognosis. In this study, we collected serum from 140 breast cancer (BC) and 20 ductal carcinoma in situ (DCIS) patients at the time of initial diagnosis and 20 healthy volunteers (HVs). Serum levels of sNKG2DLs were quantified through the use of ELISA and correlated with clinical data. The analyzed sNKG2DLs were low to absent in HVs and significantly higher in BC patients. For some of the ligands analyzed, higher sNKG2DLs serum levels were associated with the classification of malignant tumor (TNM) stage and grading. Low sMICA serum levels were associated with significantly longer progression-free (PFS) and overall survival (OS). In conclusion, we provide the first insights into sNKG2DLs in BC patients and suggest their potential role in tumor immune escape in breast cancer. Furthermore, our observations suggest that serum sMICA levels may serve as a prognostic parameter in the patients analyzed in this study. Full article

Natural killer (NK) cells play a vital role in xenotransplantation rejection. One approach to induce NK cell immune tolerance is to prevent the NK cell-mediated direct killing of porcine cells by targeting the interaction of the activating receptor NKG2D and its ligands. However, the identity of porcine ligands for the human NKG2D receptor has remained elusive. Previous studies on porcine UL-16 binding protein 1 (pULBP-1) as a ligand for human NKG2D have yielded contradictory results. The goal of the present study was to clarify the role of pULBP-1 in the immune response and its interaction with human NKG2D receptor. To accomplish this, the CRISPR/Cas9 gene editing tool was employed to disrupt the porcine ULBP-1 gene in a 5-gene knockout porcine endothelial cell line (GGTA1, CMAH, β4galNT2, SLA-I α chain, and β-2 microglobulin, 5GKO). A colony with two allele mutations in pULBP-1 was established as a 6-gene knockout pig cell line (6GKO). We found that pULBP-1-deficient pig cells exhibited a reduced binding capacity to human NKG2D-Fc, a recombinant chimera protein. However, the removal of ULBP-1 from porcine endothelial cells did not significantly impact human NK cell degranulation or cytotoxicity upon stimulation with the pig cells. These findings conclusively demonstrate that pULBP-1 is not a crucial ligand for initiating xenogeneic human NK cell activation. Full article

Triple–negative breast cancer (TNBC) is a particularly aggressive subtype of breast cancer with a poor response rate to conventional systemic treatment and high relapse rates. Members of the natural killer group 2D ligand (NKG2DL) family are expressed on cancer cells but are typically absent from healthy tissues; thus, they are promising tumor antigens for novel immunotherapeutic approaches. We developed bispecific fusion proteins (BFPs) consisting of the NKG2D receptor domain targeting multiple NKG2DLs, fused to either anti–CD3 (NKG2D–CD3) or anti–CD16 (NKG2D–CD16) Fab fragments. First, we characterized the expression of the NKG2DLs (MICA, MICB, ULBP1–4) on TNBC cell lines and observed the highest surface expression for MICA and ULBP2. Targeting TNBC cells with NKG2D–CD3/CD16 efficiently activated both NK and T cells, leading to their degranulation and cytokine release and lysis of TNBC cells. Furthermore, PBMCs from TNBC patients currently undergoing chemotherapy showed significantly higher NK and T cell activation and tumor cell lysis when stimulated with NKG2D–CD3/CD16. In conclusions, BFPs activate and direct the NK and T cells of healthy and TNBC patients against TNBC cells, leading to efficient eradication of tumor cells. Therefore, NKG2D–based NK and T cell engagers could be a valuable addition to the treatment options for TNBC patients. Full article

The family of human NKG2D ligands (NKG2DL) consists of eight stress-induced molecules. Over 80% of human cancers express these ligands on the surface of tumour cells and/or associated stromal elements. In mice, NKG2D deficiency increases susceptibility to some types of cancer, implicating this system in immune surveillance for malignancy. However, NKG2DL can also be shed, released via exosomes and trapped intracellularly, leading to immunosuppressive effects. Moreover, NKG2D can enhance chronic inflammatory processes which themselves can increase cancer risk and progression. Indeed, tumours commonly deploy a range of countermeasures that can neutralise or even corrupt this surveillance system, tipping the balance away from immune control towards tumour progression. Consequently, the prognostic impact of NKG2DL expression in human cancer is variable. In this review, we consider the underlying biology and regulation of the NKG2D/NKG2DL system and its expression and role in a range of cancer types. We also consider the opportunities for pharmacological modulation of NKG2DL expression while cautioning that such interventions need to be carefully calibrated according to the biology of the specific cancer type. Full article

Breast cancer is a disease that affects women in different countries around the world. The real cause of breast cancer is particularly challenging to determine, and early detection of the disease is necessary for reducing the death rate, due to the high risks associated with breast cancer. Treatment in the early period can increase the life expectancy and quality of life for women. CAD (Computer Aided Diagnostic) systems can perform the diagnosis of the benign and malignant lesions of breast cancer using technologies and tools based on image processing, helping specialist doctors to obtain a more precise point of view with fewer processes when making their diagnosis by giving a second opinion. This study presents a novel CAD system for automated breast cancer diagnosis. The proposed method consists of different stages. In the preprocessing stage, an image is segmented, and a mask of a lesion is obtained; during the next stage, the extraction of the deep learning features is performed by a CNN—specifically, DenseNet 201. Additionally, handcrafted features (Histogram of Oriented Gradients (HOG)-based, ULBP-based, perimeter area, area, eccentricity, and circularity) are obtained from an image. The designed hybrid system uses CNN architecture for extracting deep learning features, along with traditional methods which perform several handcraft features, following the medical properties of the disease with the purpose of later fusion via proposed statistical criteria. During the fusion stage, where deep learning and handcrafted features are analyzed, the genetic algorithms as well as mutual information selection algorithm, followed by several classifiers (XGBoost, AdaBoost, Multilayer perceptron (MLP)) based on stochastic measures, are applied to choose the most sensible information group among the features. In the experimental validation of two modalities of the CAD design, which performed two types of medical studies—mammography (MG) and ultrasound (US)—the databases mini-DDSM (Digital Database for Screening Mammography) and BUSI (Breast Ultrasound Images Dataset) were used. Novel CAD systems were evaluated and compared with recent state-of-the-art systems, demonstrating better performance in commonly used criteria, obtaining ACC of 97.6%, PRE of 98%, Recall of 98%, F1-Score of 98%, and IBA of 95% for the abovementioned datasets. Full article

Natural Killer (NK) cells are innate cytotoxic lymphoid cells that play a crucial role in cancer immunosurveillance. NKG2D is an activating receptor that binds to MIC and ULBP molecules typically induced on damaged, transformed, or infected cells. The secretion of NKG2D ligands (NKG2DLs) through protease-mediated cleavage or in an extracellular vesicle (EV) is a mode to control their cell surface expression and a mechanism used by cancer cells to evade NKG2D-mediated immunosurveillance. EVs are emerging as important players in mediating cell-to-cell communication due to their ability to transfer biological material to acceptor cells. Herein, we investigated the spreading of NKG2DLs of both MIC and ULBP molecules through the EV-mediated cross-dressing on multiple myeloma (MM) cells. We focused our attention on two MICA allelic variants, namely MICA*008 and MICA*019, representing the prototype of short and long MICA alleles, respectively, and on ULBP-1, ULBP-2, and ULBP-3. Our findings demonstrate that both ULBP and MICA ligands can be acquired from tumor cells through EVs enhancing NK cell recognition and killing. Moreover, besides MICA, EVs expressing ULBP-1 but not ULBP-2 and 3 were detected in bone marrow aspirates derived from a cohort of MM patients. Our findings shed light on the role of EV-associated MICA allelic variants and ULBP molecules in the modulation of NKG2D-mediated NK cell immunosurveillance in the tumor microenvironment. Moreover, the EV-mediated transfer of NKG2DLs could suggest novel therapeutic approaches based on the usage of engineered nanoparticles aimed at increasing cancer cell immunogenicity. Full article

Bridges deteriorate over time, which requires the continuous monitoring of their condition. There are many digital technologies for inspecting and monitoring bridges in real-time. In this context, computer vision has extensively studied cracks to automate their identification in concrete surfaces, overcoming the conventional manual methods that rely on human judgment. The general framework of vision-based techniques consists of feature extraction using different filters and descriptors and classifier training to perform the classification task. However, training can be time-consuming and computationally expensive, depending on the dimension of the features. To address this limitation, dimensionality reduction techniques are applied to extracted features, and a new feature subspace is generated. This work used histograms of oriented gradients (HOGs) and uniform local binary patterns (ULBPs) to extract features from a dataset containing over 3000 uncracked and cracked images covering different patterns of cracks and concrete surface representations. Nonlinear dimensionality reduction was performed using kernel principal component analysis (KPCA), and three machine learning classifiers were implemented to conduct the classification. The experimental results show that the classification scheme based on the support-vector machine (SVM) model and feature-level fusion of the HOG and ULBP features after KPCA application provided the best results as an accuracy of 99.26% was achieved by the proposed classification framework. Full article

This paper aims to study the application of hyperspectral technology in the classification of deep-sea manganese nodules. Considering the spectral spatial variation of hyperspectral images, the difficulty of label acquisition, and the inability to guarantee stable illumination in deep-sea environments. This paper proposes a local binary pattern manifold superpixel-based fuzzy clustering method (LMSLIC-FCM). Firstly, we introduce a uniform local binary pattern (ULBP) to design a superpixel algorithm (LMSLIC) that is insensitive to illumination and has texture perception. Secondly, the weighted feature and the mean feature are fused as the representative features of superpixels. Finally, it is fused with fuzzy clustering method (FCM) to obtain a superpixel-based clustering algorithm LMSLIC-FCM. To verify the feasibility of LMSLIC-FCM on deep-sea manganese nodule data, the experiments were conducted on three different types of manganese nodule data. The average identification rate of LMSLIC-FCM reached 83.8%, and the average true positive rate reached 93.3%, which was preferable to the previous algorithms. Therefore, LMSLIC-FCM is effective in the classification of manganese nodules. Full article

Evolutionary mechanisms have shaped the genomic architecture of Colombian Creole cattle breeds. The mating and selection processes have impacted several traits, promoting differences within and between populations. Studies of population structure and selection signatures in Colombian Creole breeds are scarce, and need more attention to better understand genetic differentiation, gene flow, and genetic distance. This study aimed to analyze the population structure and identify selection imprints in the Criollo Caqueteño (CAQ) population. It used 127 CAQ animals genotyped with Chip HD 777,000 SNPs. The population structure analyses used discriminant principal component analysis (DAPC), integrated haplotype scoring (iHS), and index-fixing (Fst) methodologies to detect selection signals. We can highlight SNP regions on the genes TMPRSS15, PGAM2, and EGFR, identified by the Fst method. Additionally, the iHS regions for cluster 1 identified candidate genes on BTA 3 (CMPK1 and FOXD2), BTA 11 (RCAN1), and BTA 22 (ARPP21). In group 2, we can highlight the genes on BTA 4 (SLC13A4, BRAF), BTA 9 (ULBP), BTA 14 (CSMD3) and BTA 19 (KRTAP9-2). These candidate genes have been associated with fertility traits, precocity, growth, and environmental and disease resistance, indicating a genetic potential in CAQ animals. All this promotes a better understanding of the diversity and genetic structure in the CAQ population. Based on that, our study can significantly assist the sustainable development and conservation of the breed in the Colombian Amazon. Full article