Cell Recognition Research Articles

Identification of CD160-TM as a tumor target on triple negative breast cancers: possible therapeutic applications

BackgroundDespite major therapeutic advances, triple-negative breast cancer (TNBC) still presents a worth prognosis than hormone receptors-positive breast cancers. One major issue relies in the molecular and mutational heterogeneity of TNBC subtypes that is reinforced by the absence of reliable tumor-antigen that could serve as a specific target to further promote efficient tumor cell recognition and depletion. CD160 is a receptor mainly expressed by NK lymphocytes and presenting two isoforms, namely the GPI-anchored form (CD160-GPI) and the transmembrane isoform (CD160-TM). While CD160-GPI is constitutively expressed on resting cells and involved in the generation of NK cells' cytotoxic activity, CD160-TM is neo-synthesized upon activation and promotes the amplification of NK cells' killing ability.MethodsCD160 expression was assessed by immunohistochemistry (IHC) and flow cytometry on TNBC patient biopsies or cell lines, respectively. Antibody (Ab)-mediated tumor depletion was tested in vitro by performing antibody-dependent cell cytotoxicity (ADCC) and phagocytosis (ADCP) assays, and in vivo on a TNBC mouse model.ResultsPreliminary data obtained by IHC on TNBC patients' tumor biopsies revealed an unconventional expression of CD160 by TNBC tumor cells. By using a specific but conformation-dependent anti-CD160-TM Ab, we established that CD160-TM, but not CD160-GPI, was expressed by TNBC tumor cells. A conformation-independent anti-CD160-TM mAb (22B12; muIgG2a isotype) was generated and selected according to pre-defined specificity and functional criterions. In vitro functional assays demonstrated that ADCC and ADCP could be induced in the presence of 22B12, resulting in TNBC cell line apoptosis. The ability of 22B12 to exert an in vivo anti-tumor activity was also demonstrated on a TNBC murine model.ConclusionsOur data identify CD160-TM as a tumor marker for TNBC and provide a rational for the use of anti-CD160-TM antibodies as therapeutic tools in this tumor context.

Biophysical Analysis of Potential Inhibitors of SARS-CoV-2 Cell Recognition and Their Effect on Viral Dynamics in Different Cell Types: A Computational Prediction from In Vitro Experimental Data.

Recent reports have suggested that the susceptibility of cells to SARS-CoV-2 infection can be influenced by various proteins that potentially act as receptors for the virus. To investigate this further, we conducted simulations of viral dynamics using different cellular systems (Vero E6, HeLa, HEK293, and CaLu3) in the presence and absence of drugs (anthelmintic, ARBs, anticoagulant, serine protease inhibitor, antimalarials, and NSAID) that have been shown to impact cellular recognition by the spike protein based on experimental data. Our simulations revealed that the susceptibility of the simulated cell systems to SARS-CoV-2 infection was similar across all tested systems. Notably, CaLu3 cells exhibited the highest susceptibility to SARS-CoV-2 infection, potentially due to the presence of receptors other than ACE2, which may account for a significant portion of the observed susceptibility. Throughout the study, all tested compounds showed thermodynamically favorable and stable binding to the spike protein. Among the tested compounds, the anticoagulant nafamostat demonstrated the most favorable characteristics in terms of thermodynamics, kinetics, theoretical antiviral activity, and potential safety (toxicity) in relation to SARS-CoV-2 spike protein-mediated infections in the tested cell lines. This study provides mathematical and bioinformatic models that can aid in the identification of optimal cell lines for compound evaluation and detection, particularly in studies focused on repurposed drugs and their mechanisms of action. It is important to note that these observations should be experimentally validated, and this research is expected to inspire future quantitative experiments.

HVS-Unsup: Unsupervised cervical cell instance segmentation method based on human visual simulation

Instance segmentation plays an important role in the automatic diagnosis of cervical cancer. Although deep learning-based instance segmentation methods can achieve outstanding performance, they need large amounts of labeled data. This results in a huge consumption of manpower and material resources. To solve this problem, we propose an unsupervised cervical cell instance segmentation method based on human visual simulation, named HVS-Unsup. Our method simulates the process of human cell recognition and incorporates prior knowledge of cervical cells. Specifically, firstly, we utilize prior knowledge to generate three types of pseudo labels for cervical cells. In this way, the unsupervised instance segmentation is transformed to a supervised task. Secondly, we design a Nucleus Enhanced Module (NEM) and a Mask-Assisted Segmentation module (MAS) to address problems of cell overlapping, adhesion, and even scenarios involving visually indistinguishable cases. NEM can accurately locate the nuclei by the nuclei attention feature maps generated by point-level pseudo labels, and MAS can reduce the interference from impurities by updating the weight of the shallow network through the dice loss. Next, we propose a Category-Wise droploss (CW-droploss) to reduce cell omissions in lower-contrast images. Finally, we employ an iterative self-training strategy to rectify mislabeled instances. Experimental results on our dataset MS-cellSeg, the public datasets Cx22 and ISBI2015 demonstrate that HVS-Unsup outperforms existing mainstream unsupervised cervical cell segmentation methods.

A mismatch in the expression of cell surface molecules induces tissue-intrinsic defense against aberrant cells

Tissue-intrinsic error correction enables epithelial cells to detect abnormal neighboring cells and facilitate their removal from the tissue. One of these pathways, "interface surveillance," is triggered by cells with aberrant developmental and cell-fate-patterning pathways. It remains unknown which molecular mechanisms provide cells with the ability to compare fate between neighboring cells. We demonstrate that Drosophila imaginal discs express an array of cell surface molecules previously implicated in neuronal axon guidance processes. They include members of the Robo, Teneurin, Ephrin, Toll-like, or atypical cadherin families. Importantly, a mismatch in expression levels of these cell surface molecules between adjacent cells is sufficient to induce interface surveillance, indicating that differences in expression levels between neighboring cells, rather than their absolute expression levels, are crucial. Specifically, a mismatch in Robo2 and Robo3, but not Robo1, induces enrichment of actin, myosin II, and Ena/Vasp, as well as activation of JNK and apoptosis at clonal interfaces. Moreover, Robo2 can induce interface surveillance independently of its cytosolic domain and without the need for the Robo-ligand Slit. The expression of Robo2 and other cell surface molecules, such as Teneurins or the Ephrin receptor is regulated by fate-patterning pathways intrinsic and extrinsic to the wing disc, as well as by expression of oncogenic RasV12. Combined, we demonstrate that neighboring cells respond to a mismatch in surface code patterns mediated by specific transmembrane proteins and reveal a novel function for these cell surface proteins in cell fate recognition and removal of aberrant cells during development and homeostasis of epithelial tissues.

Epitope accessibility affects B cell recognition of influenza virus proteins

Epitope accessibility affects B cell recognition of influenza virus proteins

Bioinformatics analysis identifies coagulation factor II receptor as a potential biomarker in stomach adenocarcinoma

Coagulation factor 2 thrombin receptor (F2R), a member of the G protein-coupled receptor family, plays an important role in regulating blood clotting through protein hydrolytic cleavage mediated receptor activation. However, the underlying biological mechanisms by which F2R affects the development of gastric adenocarcinoma are not fully understood. This study aimed to systematically analyze the role of F2R in gastric adenocarcinoma. Stomach adenocarcinoma (STAD)-related gene microarray data and corresponding clinicopathological information were downloaded from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Differential expression genes (DEGs) associated with F2R were analyzed using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), gene set enrichment analysis (GSEA), and protein–protein interaction (PPI) networks. F2R mRNA expression data were utilized to estimate stromal cell and immune cell scores in gastric cancer tissue samples, including stromal score, immune score, and ESTIMATE score, derived from single-sample enrichment studies. Analysis of TCGA and GEO databases revealed significantly higher F2R expression in STAD tissues compared to normal tissues. Patients with high F2R expression had shorter survival times than those with low F2R expression. F2R expression was significantly correlated with tumor (T) stage, node (N) stage, histological grade and pathological stage. Enrichment analysis of F2R-related genes showed that GO terms were mainly related to circulation-mediated human immune response, immunoglobulin, cell recognition and phagocytosis. KEGG analysis indicated associations to extracellular matrix (ECM) receptor interactions, neuroactive ligand-receptor interactions, the phosphoinositide-3-kinase-protein kinase B/Akt (PI3K-AKT) signaling pathway, the Wnt signaling pathway and the transforming growth factor-beta (TGF-β) signaling pathway. GSEA revealed connections to DNA replication, the Janus kinase/signal transducers and activators of transcription (JAK-STAT) signaling pathway, the mitogen-activated protein kinase (MAPK) signaling pathway and oxidative phosphorylation. Drug sensitivity analysis demonstrated positive correlations between F2R and several drugs, including BEZ235, CGP-60474, Dasatinib, HG-6-64-1, Aazopanib, Rapamycin, Sunitinib and TGX221, while negative correlation with CP724714, FH535, GSK1904529A, JNK-9L, LY317615, pyrimidine, rTRAIL and Vinorelbine. Knocking down F2R in GC cell lines resulted in slowed proliferation, migration, and invasion. All statistical analyses were performed using R software (version 4.2.1) and GraphPad Prism 9.0. p < 0.05 was considered statistically significant. In conclusion, this study underscores the significance of F2R as a potential biomarker in gastric adenocarcinoma, shedding light on its molecular mechanisms in tumorigenesis. F2R holds promise for aiding in the diagnosis, prognosis, and targeted therapy of STAD.

T antigen-specific CD8+ T cells associate with PD-1 blockade response in virus-positive Merkel cell carcinoma.

Merkel cell carcinoma (MCC) is a highly immunogenic skin cancer primarily induced by Merkel cell polyomavirus, which is driven by the expression of the oncogenic T antigens (T-Ags). Blockade of the programmed cell death protein-1 (PD-1) pathway has shown remarkable response rates, but evidence for therapy-associated T-Ag-specific immune response and therapeutic strategies for the nonresponding fraction are both limited. We tracked T-Ag-reactive CD8+ T cells in peripheral blood of 26 MCC patients under anti-PD1 therapy, using DNA-barcoded pMHC multimers, displaying all peptides from the predicted HLA ligandome of the oncoproteins, covering 33 class I haplotypes. We observed a broad T cell recognition of T-Ags, including identification of 20 T-Ag-derived epitopes we believe to be novel. Broadening of the T-Ag recognition profile and increased T cell frequencies during therapy were strongly associated with clinical response and prolonged progression-free survival. T-Ag-specific T cells could be further boosted and expanded directly from peripheral blood using artificial antigen-presenting scaffolds, even in patients with no detectable T-Ag-specific T cells. These T cells provided strong tumor-rejection capacity while retaining a favorable phenotype for adoptive cell transfer. These findings demonstrate that T-Ag-specific T cells are associated with the clinical outcome to PD-1 blockade and that Ag-presenting scaffolds can be used to boost such responses.

HER2 aptamer-conjugated iron oxide nanoparticles with PDMAEMA-b-PMPC coating for breast cancer cell identification.

Aim: To synthesize HER2 aptamer-conjugated iron oxide nanoparticles with a coating of poly(2-(dimethylamino) ethyl methacrylate)-poly(2-methacryloyloxyethylphosphorylcholine) block copolymer (IONPPPs). Methods: Characterization covered molecular structure, chemical composition, thermal stability, magnetic characteristics, aptamer interaction, crystalline nature and microscopic features. Subsequent investigations focused on IONPPPs for in vitro cancer cell identification. Results: Results demonstrated high biocompatibility of the diblock copolymer with no significant toxicity up to 150μg/ml. The facile coating process yielded the IONPP complex, featuring a 13.27nm metal core and a 3.10nm polymer coating. Functionalized with a HER2-targeting DNA aptamer, IONPPP enhanced recognition in HER2-amplified SKBR3 cells via magnetization separation. Conclusion: These findings underscore IONPPP's potential in cancer research and clinical applications, showcasing diagnostic efficacy and HER2 protein targeting in a proof-of-concept approach.

Convolutional neural network model for automatic recognition and classification of pancreatic cancer cell based on analysis of lipid droplet on unlabeled sample by 3D optical diffraction tomography

IntroductionPancreatic cancer cells generally accumulate large numbers of lipid droplets (LDs), which regulate lipid storage. To promote rapid diagnosis, an automatic pancreatic cancer cell recognition system based on a deep convolutional neural network was proposed in this study using quantitative images of LDs from stain-free cytologic samples by optical diffraction tomography. MethodsWe retrieved 3D refractive index tomograms and reconstructed 37 optical images of one cell. From the four cell lines, the obtained fields were separated into training and test datasets with 10,397 and 3,478 images, respectively. Furthermore, we adopted several machine learning techniques based on a single image-based prediction model to improve the performance of the computer-aided diagnostic system. ResultsPancreatic cancer cells had a significantly lower total cell volume and dry mass than did normal pancreatic cells and were accompanied by greater numbers of lipid droplets (LDs). When evaluating multitask learning techniques utilizing the EfficientNet-b3 model through confusion matrices, the overall 2-category accuracy for cancer classification reached 96.7 %. Simultaneously, the overall 4-category accuracy for individual cell line classification achieved a high accuracy of 96.2 %. Furthermore, when we added the core techniques one by one, the overall performance of the proposed technique significantly improved, reaching an area under the curve (AUC) of 0.997 and an accuracy of 97.06 %. Finally, the AUC reached 0.998 through the ablation study with the score fusion technique. DiscussionOur novel training strategy has significant potential for automating and promoting rapid recognition of pancreatic cancer cells. In the near future, deep learning-embedded medical devices will substitute laborious manual cytopathologic examinations for sustainable economic potential.

AI-Enhanced Blood Cell Recognition and Analysis: Advancing Traditional Microscopy with the Web-Based Platform IKOSA

Microscopy of stained blood smears is still a ubiquitous technique in pathology. It is often used in addition to automated electronic counters or flow cytometers to evaluate leukocytes and their morphologies in a rather simple manner and has low requirements for resources and equipment. However, despite the constant advances in microscopy, computer science, and pathology, it still usually follows the traditional approach of manual assessment by humans. We aimed to extend this technique using AI-based automated cell recognition methods while maintaining its technical simplicity. Using the web platform IKOSA, we developed an AI-based workflow to segment and identify all blood cells in DAPI-Giemsa co-stained blood smears. Thereby, we could automatically detect and classify neutrophils (young and segmented), lymphocytes, eosinophils, and monocytes, in addition to erythrocytes and platelets, in contrast to previously published algorithms, which usually focus on only one type of blood cell. Furthermore, our method delivers quantitative measurements, unattainable by the classical method or formerly published AI techniques, and it provides more sophisticated analyses based on entropy or gray-level co-occurrence matrices (GLCMs), which have the potential to monitor changes in internal cellular structures associated with disease states or responses to treatment. We conclude that AI-based automated blood cell evaluation has the potential to facilitate and improve routine diagnostics by adding quantitative shape and structure parameters to simple leukocyte counts of classical analysis.

MHCpLogics: an interactive machine learning-based tool for unsupervised data visualization and cluster analysis of immunopeptidomes.

The major histocompatibility complex (MHC) encodes a range of immune response genes, including the human leukocyte antigens (HLAs) in humans. These molecules bind peptide antigens and present them on the cell surface for T cell recognition. The repertoires of peptides presented by HLA molecules are termed immunopeptidomes. The highly polymorphic nature of the genres that encode the HLA molecules confers allotype-specific differences in the sequences of bound ligands. Allotype-specific ligand preferences are often defined by peptide-binding motifs. Individuals express up to six classical class I HLA allotypes, which likely present peptides displaying different binding motifs. Such complex datasets make the deconvolution of immunopeptidomic data into allotype-specific contributions and further dissection of binding-specificities challenging. Herein, we developed MHCpLogics as an interactive machine learning-based tool for mining peptide-binding sequence motifs and visualization of immunopeptidome data across complex datasets. We showcase the functionalities of MHCpLogics by analyzing both in-house and published mono- and multi-allelic immunopeptidomics data. The visualization modalities of MHCpLogics allow users to inspect clustered sequences down to individual peptide components and to examine broader sequence patterns within multiple immunopeptidome datasets. MHCpLogics can deconvolute large immunopeptidome datasets enabling the interrogation of clusters for the segregation of allotype-specific peptide sequence motifs, identification of sub-peptidome motifs, and the exportation of clustered peptide sequence lists. The tool facilitates rapid inspection of immunopeptidomes as a resource for the immunology and vaccine communities. MHCpLogics is a standalone application available via an executable installation at: https://github.com/PurcellLab/MHCpLogics.

Tunable Multivalent Aptamer-Based DNA Nanostructures To Regulate Multiheteroreceptor-Mediated Tumor Recognition.

Precise mapping and regulation of cell surface receptors hold immense significance in disease treatment, such as cancer, infection, and neurodisorders, but also face enormous challenges. In this study, we designed a series of adjustable multivalent aptamer-based DNA nanostructures to precisely control their interaction with receptors in tumor cells. By profiling surface receptors on 12 cell lines using 10 different aptamers, we generated a heatmap that accurately distinguished between various tumor types based on multiple markers. We then incorporated these aptamers onto DNA origami structures to regulate receptor recognition, with patch-like structures demonstrating a tendency to be trapped on the cell surface and with tube-like structures showing a preference for internalization. Through precise control of aptamer species, valence, and geometric patterns, we found that multiheteroreceptor-mediated recognition not only favored the specific binding of nanostructures to tumor cells but also greatly enhanced intracellular uptake by promoting clathrin-dependent endocytosis. Specifically, we achieved over 5-fold uptake in different tumor cells versus normal cells using tube-like structures modified with different diheteroaptamer pairs, facilitating targeted drug delivery. Moreover, patch-like structures with triheteroaptamers guided specific interactions between macrophages and tumor cells, leading to effective immune clearance. This programmable multivalent system allows for the precise regulation of cell recognition using multiple parameters, demonstrating great potential for personalized tumor treatment.

First-in-human phase 1/2 trial evaluating TAC01-CLDN18.2 autologous T cells in CLDN18.2-positive solid tumors.

TPS419 Background: CLDN18.2 is a tight junction protein expressed in differentiated gastric epithelial cells and is abnormally expressed in various solid tumor types, serving as a promising target for therapy. To date, there are no approved therapies directed against this target, but compelling data exist using monoclonal antibodies and conventional CAR T therapy. The T Cell Antigen Coupler (TAC) technology is an approach to modifying T cells ex vivo, which allows recognition and cytotoxicity of tumor cells by co-opting the natural T cell receptor. The TAC technology has a safer profile than conventional CAR T therapies and is used to create an autologous TAC01-CLDN18.2 T cell product targeting CLDN18.2. Methods: This first in-human trial (NCT05862324) is designed to assess both the safety profile and preliminary antitumor activity of TAC01-CLDN18.2 in patients with CLDN18.2+/HER2- solid tumors after ≥ 2 lines of therapy. The phase 1 dose escalation segment employs a traditional 3+3 dose-escalation design to evaluate increasing doses of TAC01-CLDN18.2 with estimated enrollment numbers of 9 to 24 subjects. The subsequent phase 2 will further evaluate the efficacy, safety, and pharmacokinetics of the optimal TAC01-CLDN18.2 dose. With 3 cohorts, Group A will enroll up to 57 subjects with gastric and esophageal adenocarcinoma, Group B aims to enroll 10 subjects with pancreatic ductal adenocarcinoma (PDAC) while Group C will examine up to 22 subjects with ovarian and non-small cell lung cancer (NSCLC). Groups A and C will leverage a Simon 2-stage design to assess whether the treatment achieves efficacy, while Group B will be exploratory with an opportunity for cohort enrichment based on clinical data. Prior to TAC01-CLDN18.2 infusion, subjects will undergo leukapheresis and may receive bridging anticancer therapy as appropriate during cell manufacturing. CLDN18.2 expression levels will be determined centrally using a clinical trial assay validated across relevant indications. Subjects will then undergo low intensity lymphodepletion chemotherapy. A second dose of TAC01-CLDN18.2 may be administered based on prespecified safety and clinical criteria. Evaluation of DLTs will take place within a 28-day window following the first infusion. In both phases, CLDN18.2+/HER2- solid tumor patients must have completed at least two prior therapy lines except for PDAC patients who may qualify after one prior antineoplastic regimen. For phase 2, up to four prior treatment lines is permissible and definitions of eligible CLDN18.2 expression levels will be based on retrospective analysis of data from Phase 1 in association with clinical efficacy. The trial is currently in the open-enrollment stage, awaiting the inclusion of the inaugural patient. No data analysis is available as of the submission deadline. Clinical trial information: NCT05862324 .

A phase I/II trial investigating safety and efficacy of autologous TAC01-HER2 in relapsed or refractory solid tumors.

747 Background: Despite therapeutic developments for patients with advanced HER2+ solid tumors, significant unmet medical needs still exist. The T cell antigen coupler (TAC) technology is an approach to modifying T cells ex vivo, which allows recognition and cytotoxicity of tumor cells by co-opting the natural T cell receptor. TAC T cells demonstrate a safer profile than chimeric antigen receptor T cells. TAC01-HER2 is an autologous T-cell product comprising T cells expressing HER2 TAC. Methods: The ongoing clinical trial (NCT04727151) is evaluating the safety and preliminary anti-tumor activity of TAC01-HER2 treatment of HER2+ solid tumors. Subjects undergo leukapheresis followed by low-intensity lymphodepletion chemotherapy prior to TAC01-HER2 infusion. In phase I dose escalation, TAC01-HER2 is administered at increasing doses (Cohorts 1-4) in adult subjects after ≥2 lines of therapy. Dose limiting toxicities (DLT) are assessed up to 28 days from TAC01-HER2 infusion. In Phase II, dose expansion groups will further evaluate the efficacy, safety, and pharmacokinetics of the optimal TAC01-HER2 dose in gastric/GEJ tumors. Results: As of 31 August 2023, 20 patients with solid tumors have been treated in Cohorts 1-4. Subjects had a median of 4 prior therapies (2-12) and all had maintained HER2 expression on central review at enrollment. Three subjects were HER2 1+ or 2+/FISH-. One DLT event of grade 3 (G3) pneumonitis has been reported in 1 subject in Cohort 4. No neurotoxicity has been reported. Most subjects treated at Cohorts 3-4 experienced cytokine release syndrome (CRS) which resolved with supportive therapy. Fifteen subjects have reported a total of 31 serious adverse events, with 1 G3 pneumonitis and 5 CRS (one G1, three G2 and one G3) related to TAC01-HER2. A 68.8% disease control rate (DCR) was observed in Cohorts 2-4 at first restaging after TAC01-HER2 infusion. For gastric/GEJ subjects of the same Cohorts, DCR was 85.7%. 3 months after TAC01-HER2 infusion, DCR was 30.8% for all subjects of Cohorts 2-4 and 28.6% for gastric/GEJ subjects. Two patients had a partial response (PR). At Cohort 4, a PR was observed in a subject with GEJ (HER2 2+, FISH+) with 100% reduction of target lesion. This patient had progressed on 4 prior lines of therapy including trastuzumab and trastuzumab deruxtecan. Conclusions: Treatment with TAC01-HER2 showed manageable safety and promising clinical activity in a heavily pre-treated cancer population. The recommended phase 2 dose was identified as dose level 4 (6-8 x 106 cells/kg). Clinical trial information: NCT04727151 .

Enterovirus D68 3C protease antagonizes type I interferon signaling by cleaving signal transducer and activator of transcription 1.

Following the successful control of poliovirus, the re-emergence of respiratory enterovirus D68 (EV-D68), a prominent non-polio enterovirus, has become a serious public health concern worldwide. Host innate immune responses are the primary defense against EV-D68 invasion; however, the mechanism underlying viral evasion of the antiviral activity of interferons (IFN) remains unclear. In this study, we found that EV-D68 inhibited type I IFN signaling by cleaving signal transducer and activator of transcription 1 (STAT1), a crucial factor in cellular responses to interferons and other cytokines. We observed that the prototype and circulating EV-D68 strains conserved their ability to induce STAT1 cleavage and attenuate IFN signal transduction. Further investigation revealed that EV-D68 3C protease cleaves STAT1 at the 131Q residue. Interestingly, not all enterovirus-encoded 3C proteases exhibited this ability. EV-D68 and poliovirus 3C proteases efficiently induced STAT1 cleavage; whereas, 3C proteases from EV-A71, coxsackievirus A16, and echoviruses did not. STAT1 cleavage also abolished the nuclear translocation capacity of STAT1 in response to IFN stimulation to activate downstream signaling elements. Overall, these results suggest that STAT1, targeted by viral protease 3C, is utilized by EV-D68 to subvert the host's innate immune response.IMPORTANCEEnterovirus D68 (EV-D68) has significantly transformed over the past decade, evolving from a rare pathogen to a potential pandemic pathogen. The interferon (IFN) signaling pathway is an important defense mechanism and therapeutic target for the host to resist viral invasion. Previous studies have reported that the EV-D68 virus blocks or weakens immune recognition and IFN production in host cells through diverse strategies; however, the mechanisms of EV-D68 resistance to IFN signaling have not been fully elucidated. Our study revealed that EV-D68 relies on its own encoded protease, 3C, to directly cleave signal transducer and activator of transcription 1 (STAT1), a pivotal transduction component in the IFN signaling pathway, disrupting the IFN-mediated antiviral response. Previous studies on human enteroviruses have not documented direct cleavage of the STAT1 protein to evade cellular immune defenses. However, not all enteroviral 3C proteins can cleave STAT1. These findings highlight the diverse evolutionary strategies different human enteroviruses employ to evade host immunity.

Cancer-cell-specific Self-Reporting Photosensitizer for Precise Identification and Ablation of Cancer Cells.

Cancer-cell-specific fluorescent photosensitizers (PSs) are highly desired molecular tools for cancer ablation with minimal damage to normal cells. However, such PSs that can achieve cancer specification and ablation and a self-reporting manner concurrently are rarely reported and still an extremely challenging task. Herein, we have proposed a feasible strategy and conceived a series of fluorescent PSs based on simple chemical structures for identifying and killing cancer cells as well as monitoring the photodynamic therapy (PDT) process by visualizing the change of subcellular localization. All of the constructed cationic molecules could stain mitochondria in cancer cells, identify cancer cells specifically, and monitor cancer cell viability. Among these, IVP-Br has the strongest ability to produce ROS, which serves as a potent PS for specific recognition and killing of cancer cells. IVP-Br could translocate from mitochondria to the nucleolus during PDT, self-reporting the entire therapeutic process. Mechanism study confirms that IVP-Br with light irradiation causes cancer cell ablation via inducing cell cycle arrest, cell apoptosis, and autophagy. The efficient ablation of tumor through PDT induced by IVP-Br has been confirmed in the 3D tumor spheroid chip. Particularly, IVP-Br could discriminate cancer cells from white blood cells (WBCs), exhibiting great potential to identify circulating tumor cells (CTCs).

Abstract C019: The circadian master regulator BMAL1 blocks immune cell recognition of pancreatic ductal adenocarcinomas by reducing proteasome activity and MHC1 cell surface localization

Abstract Many tumor types, including pancreatic adenocarcinomas, have dysregulated circadian rhythms. Here we show that the master regulator of circadian control, BMAL1, is overexpressed in pancreatic ductal adenocarcinoma (PDAC) relative to normal tissue and plays a role in protecting PDAC cells from recognition by the immune system. Using CRISPR-generated knockout (KO) cell lines, we evaluated the cells ability to create liver metastasis using a splenic metastasis assay and found that loss of Bmal1 KO abrograted metastasis. We hypothesized that could be through an immune mediated mechanism and evaluated the Bmal KO cells for their expression of cell surface MHCI. Remarkably loss of Bmal1 led to a significant increase in cell surface MHCI expression. This was due to a change in localization of the MHCI molecule. Proper localization of MHC1 is known to depend upon proteasome-generated peptides, and we found that loss of Bmal1 increased proteosomal activity. We used Cut and Run to demonstrate that Bmal1 binds directly to the promoters for core components of the proteosome. Taken together these studies implicate Bmal1 in regulating anti-tumor immunity in PDAC through its regulation of protesomal activity and MHC1 surface expression. This is a novel function for a circadian rhythm gene in PDAC biology. Citation Format: Orjola Prela, Lan Wang, Ching-Hua Shih, Juliana Cazarin de Menezes, Brian Altman, Paula M. Vertino, Chris R. Harris, Darren R. Carpizo. The circadian master regulator BMAL1 blocks immune cell recognition of pancreatic ductal adenocarcinomas by reducing proteasome activity and MHC1 cell surface localization [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr C019.

Aptamer-Based Recognition of Breast Tumor Cells: A New Era for Breast Cancer Diagnosis.

Breast cancer is one of the leading causes of death among women worldwide and can be classified into four major distinct molecular subtypes based on the expression of specific receptors. Despite significant advances, the lack of biomarkers for detailed diagnosis and prognosis remains a major challenge in the field of oncology. This study aimed to identify short single-stranded oligonucleotides known as aptamers to improve breast cancer diagnosis. The Cell-SELEX technique was used to select aptamers specific to the MDA-MB-231 tumor cell line. After selection, five aptamers demonstrated specific recognition for tumor breast cell lines and no binding to non-tumor breast cells. Validation of aptamer specificity revealed recognition of primary and metastatic tumors of all subtypes. In particular, AptaB4 and AptaB5 showed greater recognition of primary tumors and metastatic tissue, respectively. Finally, a computational biology approach was used to identify potential aptamer targets, which indicated that CSKP could interact with AptaB4. These results suggest that aptamers are promising in breast cancer diagnosis and treatment due to their specificity and selectivity.

The role of secreted proteins in efferocytosis.

The clearance of apoptotic cells known as efferocytosis is the final stage of apoptosis, and includes the recognition, phagocytosis, and degradation of apoptotic cells. The maintenance of tissue homeostasis requires the daily elimination of billions of apoptotic cells from the human body via the process of efferocytosis. Accordingly, aberrations in efferocytosis underlie a growing list of diseases, including atherosclerosis, cancer, and infections. During the initial phase of apoptosis, "Eat-Me" signals are exposed and recognized by phagocytes either directly through phagocyte receptors or indirectly through secreted proteins that function as bridge molecules that cross-link dying cells to phagocytes. Here, we set out to provide a comprehensive review of the molecular mechanisms and biological significance of secreted proteins in apoptotic cell clearance. Specifically, it focuses on how these secreted proteins act as bridging molecules to facilitate the clearance process.

One CD4+TCR and One CD8+TCR Targeting Autochthonous Neoantigens Are Essential and Sufficient for Tumor Eradication.

To achieve eradication of solid tumors, we examined how many neoantigens need to be targeted with how many T-cell receptors (TCR) by which type of T cells. Unmanipulated, naturally expressed (autochthonous) neoantigens were targeted with adoptively transferred TCR-engineered autologous T cells (TCR-therapy). TCR-therapy used CD8+ T-cell subsets engineered with TCRs isolated from CD8+ T cells (CD8+TCR-therapy), CD4+ T-cell subsets engineered with TCRs isolated from CD4+ T cells (CD4+TCR-therapy), or combinations of both. The targeted tumors were established for at least 3 weeks and derived from primary autochthonous cancer cell cultures, resembling natural solid tumors and their heterogeneity as found in humans. Relapse was common with CD8+TCR-therapy even when targeting multiple different autochthonous neoantigens on heterogeneous solid tumors. CD8+TCR-therapy was only effective against homogenous tumors artificially derived from a cancer cell clone. In contrast, a combination of CD8+TCR-therapy with CD4+TCR-therapy, each targeting one neoantigen, eradicated large and established solid tumors of natural heterogeneity. CD4+TCR-therapy targeted a mutant neoantigen on tumor stroma while direct cancer cell recognition by CD8+TCR-therapy was essential for cure. In vitro data were consistent with elimination of cancer cells requiring a four-cell cluster composed of TCR-engineered CD4+ and CD8+ T cells together with antigen-presenting cells and cancer cells. Two cancer-specific TCRs can be essential and sufficient to eradicate heterogeneous solid tumors expressing unmanipulated, autochthonous targets. We demonstrate that simplifications to adoptive TCR-therapy are possible without compromising efficacy.