Target Spectrum Research Articles

Rbfox1 controls alternative splicing of focal adhesion genes in cardiac muscle cells.

Alternative splicing is one of the major cellular processes that determine the tissue-specific expression of protein variants. However, it remains challenging to identify physiologically relevant and tissue-selective proteins that are generated by alternative splicing. Hence, we investigated the target spectrum of the splicing factor Rbfox1 in the cardiac muscle context in more detail. By using a combination of in silico target prediction and in-cell validation, we identified several focal adhesion proteins as alternative splicing targets of Rbfox1. We focused on the alternative splicing patterns of vinculin (metavinculin isoform) and paxillin (extended paxillin isoform) and identified both as potential Rbfox1 targets. Minigene analyses suggested that both isoforms are promoted by Rbfox1 due to binding in the introns. Focal adhesions play an important role in the cardiac muscle context, since they mainly influence cell shape, cytoskeletal organization, and cell-matrix association. Our data confirmed that depletion of Rbfox1 changed cardiomyoblast morphology, cytoskeletal organization, and multinuclearity after differentiation, which might be due to changes in alternative splicing of focal adhesion proteins. Hence, our results indicate that Rbfox1 promotes alternative splicing of focal adhesion genes in cardiac muscle cells, which might contribute to heart disease progression, where downregulation of Rbfox1 is frequently observed.

Current status of molecular diagnostics for lung cancer.

The management of lung cancer (LC) requires the analysis of a diverse spectrum of molecular targets, including kinase activating mutations in EGFR, ERBB2 (HER2), BRAF and MET oncogenes, KRAS G12C substitutions, and ALK, ROS1, RET and NTRK1-3 gene fusions. Administration of immune checkpoint inhibitors (ICIs) is based on the immunohistochemical (IHC) analysis of PD-L1 expression and determination of tumor mutation burden (TMB). Clinical characteristics of the patients, particularly age, gender and smoking history, significantly influence the probability of finding the above targets: for example, LC in young patients is characterized by high frequency of kinase gene rearrangements, while heavy smokers often have KRAS G12C mutations and/or high TMB. Proper selection of first-line therapy influences overall treatment outcomes, therefore, the majority of these tests need to be completed within no more than 10 working days. Activating events in MAPK signaling pathway are mutually exclusive, hence, fast single-gene testing remains an option for some laboratories. RNA next-generation sequencing (NGS) is capable of detecting the entire repertoire of druggable gene alterations, therefore it is gradually becoming a dominating technology in LC molecular diagnosis.

Nanomaterials as a Service (NaaS) concept: on-demand protocols for volume synthesis of nanomaterials.

Establishing scalable nanomaterials synthesis protocols remains a bottleneck towards their commercialisation and, thus, a topic of intense research and development. Herein, we present an automated machine-learning microfluidic platform capable of synthesising optically active nanomaterials from target spectra originating from prior experience, theorised or published. Implementing unsupervised Bayesian optimisation with Gaussian processes reduces the optimisation time and the need for prior knowledge to initiate the process. Using PTFE tubing and connectors enables facile change in reactor design. Ultimately, the platform substitutes the labour-intensive trial-and-error synthesis and provides a pathway to standardisation and volume synthesis, slowing down the translation and commercialisation of high-quality nanomaterials. As a proof-of-concept, Ag nanoplates and Prussian-blue nanoparticle protocols were optimised and validated for volume production.

Calibration method of relative spectral response function of indirect imaging spectrometer

In imaging spectrometers, area array detectors are usually used as photoelectric conversion devices, but the inconsistency of the spectral response among pixels can distort the collected target spectra. To improve the spectral radiometric accuracy of imaging spectrometers, calibrating and correcting the inconsistency of the spectral response among pixels is essential. The signal received by each pixel of area array detector of the indirect imaging spectrometer is usually the superposition of the target multi-spectral radiation signals or full-spectral radiation signals. Therefore, its relative spectral radiometric calibration requires measuring the spectral response of each pixel at different wavelengths on the array detector. Under the ideal conditions, the response values of each pixel in the area array detector are different, so the indirect imaging spectrometer cannot simply calibrate the relative spectral response (RSR) function between pixels by using the method of “monochromator + integrating sphere”. In this work, taking the interferometric imaging spectrometer for example, we analyze the influence of the inconsistency of the RSR among pixels on the target spectral radiation measurement accuracy, and propose a system-level RSR function measurement method for the indirect imaging spectrometer based on the Fourier transform modulation calibration source. In addition, we establish a mathematical model for calibrating the RSR function,and provide guidelines for selecting calibration system parameters such as light source, spectral resolution, and OPD sampling interval. The simulation results show that under the ideal noise-free condition, the 1% spectral response inconsistency among pixels results in a relative error of 1.02% to the recovered spectra. After RSR correction, the relative error of the recovered spectra of different rows decreases to 0.08%. Furthermore, in this work we simulate and analyse the influence of spectral signal-to-noise ratio on the calibration accuracy of the RSR function, and point out that increasing the brightness of the calibration light source, extending exposure time, and combining multi-frame interferograms can enhance RSR function calibration accuracy in practical applications. The research result can provide a theoretical basis for realizing the relative spectral radiometric calibration of indirect imaging spectrometer, which is of great significance in promoting quantitative spectral remote sensing.

A Review Article on Migrane

Migrane are a neurological disorder characterized by recurrent, moderate to severe headache. They are often accompanied by symptoms such as nausea, vomiting, sensitivity to light and sound and in some cases, visual disturbances migraines can significantly impact a person’s quality of life and may require a combination of lifestyles changes, medication and other therapies for effective management. Migraine is the sixth most prevalent disease globally, a major cause of disability, and it imposes an enormous personal and socio-economic burden. Migraine treatment is often limited by insufficient therapy response, leading to the need for individually adjusted treatment. In this review, we analyse historical and current pharmaceutical development approaches in acute and chronic migraine based on comprehensive and systematic analysis of Food and Drug Administration (FDA)-approved drugs and those under investigation. The development of migraine therapeutics has significantly intensified during the last 3 years, as shown by our analysis of the trends of drug development between 1970 and 2020. The spectrum of drug targets has expanded considerably, which has been accompanied by an increase in the number of specialised clinical trials. This review highlights the mechanistic implications of FDA approved and currently investigated drugs and discusses current and future therapeutic options based on identified drug classes of interest.

A characteristic extraction method for VoicePrint slice statistics base on joint time-frequency processing

Mel-Frequency Cepstral Coefficients (MFCC) and its differential coefficients are widely used as a typical non-linear spectral envelope feature in passive sonar target recognition. MFCC emphasizes the frequency domain information at the low-frequency end of the target, while the differential coefficients add dynamic characteristics of MFCC in the time domain. However, the utilization of time information is not sufficient. In response to this issue, we propose two solutions: one is the characteristic fusion method of Weighted Mel-Frequency Cepstral Coefficient based on Bhattacharyya Distance (BD-WMFCC); the other is the characteristic extraction method of VoicePrint Slice Statistics (VPSS) based on time–frequency joint processing. BD-WMFCC combines weighted differential coefficients with MFCC using Bhattacharyya distance, maximizing the utilization of time information. VPSS is a linear spectral feature that utilizes the stability of the spectral intensity within a certain bandwidth over continuous time. It extracts the steady-state characteristics of the target's spectrum with respect to time changes at equidistant bandwidths. Simulation and real data analysis have shown that VPSS demonstrates outstanding separability and classification performance in both non-linear and linear spectral features, with strong stability. In practical data analysis, the accuracy of VPSS features under the AlexNet algorithm is 3.8 % and 5.7 % higher than the spectral (Fre) and Mel features, respectively.

Diverse and Synergistic Actions of Phytochemicals in a Plant-Based Multivitamin/Mineral Supplement against Oxidative Stress and Inflammation in Healthy Individuals: A Systems Biology Approach Based on a Randomized Clinical Trial.

Traditional clinical methodologies often fall short of revealing the complex interplay of multiple components and targets within the human body. This study was designed to explore the complex and synergistic effects of phytochemicals in a plant-based multivitamin/mineral supplement (PBS) on oxidative stress and inflammation in healthy individuals. Utilizing a systems biology framework, we integrated clinical with multi-omics analyses, including UPLC-Q-TOF-MS for 33 phytochemicals, qPCR for 42 differential transcripts, and GC-TOF-MS for 17 differential metabolites. A Gene Ontology analysis facilitated the identification of 367 biological processes linked to oxidative stress and inflammation. As a result, a comprehensive network was constructed consisting of 255 nodes and 1579 edges, featuring 10 phytochemicals, 26 targets, and 218 biological processes. Quercetin was identified as having the broadest target spectrum, succeeded by ellagic acid, hesperidin, chlorogenic acid, and quercitrin. Moreover, several phytochemicals were associated with key genes such as HMOX1, TNF, NFE2L2, CXCL8, and IL6, which play roles in the Toll-like receptor, NF-kappa B, adipocytokine, and C-type lectin receptor signaling pathways. This clinical data-driven network system approach has significantly advanced our comprehension of a PBS's effects by pinpointing pivotal phytochemicals and delineating their synergistic actions, thus illuminating potential molecular mechanisms.

Commensal production of a broad-spectrum and short-lived antimicrobial peptide polyene eliminates nasal Staphylococcus aureus

Antagonistic bacterial interactions often rely on antimicrobial bacteriocins, which attack only a narrow range of target bacteria. However, antimicrobials with broader activity may be advantageous. Here we identify an antimicrobial called epifadin, which is produced by nasal Staphylococcus epidermidis IVK83. It has an unprecedented architecture consisting of a non-ribosomally synthesized peptide, a polyketide component and a terminal modified amino acid moiety. Epifadin combines a wide antimicrobial target spectrum with a short life span of only a few hours. It is highly unstable under in vivo-like conditions, potentially as a means to limit collateral damage of bacterial mutualists. However, Staphylococcus aureus is eliminated by epifadin-producing S. epidermidis during co-cultivation in vitro and in vivo, indicating that epifadin-producing commensals could help prevent nasal S. aureus carriage. These insights into a microbiome-derived, previously unknown antimicrobial compound class suggest that limiting the half-life of an antimicrobial may help to balance its beneficial and detrimental activities.

Alternative therapeutic strategies to treat antibiotic-resistant pathogens.

Resistance threatens to render antibiotics - which are essential for modern medicine - ineffective, thus posing a threat to human health. The discovery of novel classes of antibiotics able to overcome resistance has been stalled for decades, with the developmental pipeline relying almost entirely on variations of existing chemical scaffolds. Unfortunately, this approach has been unable to keep pace with resistance evolution, necessitating new therapeutic strategies. In this Review, we highlight recent efforts to discover non-traditional antimicrobials, specifically describing the advantages and limitations of antimicrobial peptides and macrocycles, antibodies, bacteriophages and antisense oligonucleotides. These approaches have the potential to stem the tide of resistance by expanding the physicochemical property space and target spectrum occupied by currently approved antibiotics.

Model-informed classification of broadband acoustic backscatter from zooplankton in an in situ mesocosm

Abstract Classification of zooplankton to species with broadband echosounder data could increase the taxonomic resolution of acoustic surveys and reduce the dependence on net and trawl samples for ‘ground truthing’. Supervised classification with broadband echosounder data is limited by the acquisition of validated data required to train machine learning algorithms (‘classifiers’). We tested the hypothesis that acoustic scattering models could be used to train classifiers for remote classification of zooplankton. Three classifiers were trained with data from scattering models of four Arctic zooplankton groups (copepods, euphausiids, chaetognaths, and hydrozoans). We evaluated classifier predictions against observations of a mixed zooplankton community in a submerged purpose-built mesocosm (12 m3) insonified with broadband transmissions (185–255 kHz). The mesocosm was deployed from a wharf in Ny-Ålesund, Svalbard, during the Arctic polar night in January 2022. We detected 7722 tracked single targets, which were used to evaluate the classifier predictions of measured zooplankton targets. The classifiers could differentiate copepods from the other groups reasonably well, but they could not differentiate euphausiids, chaetognaths, and hydrozoans reliably due to the similarities in their modelled target spectra. We recommend that model-informed classification of zooplankton from broadband acoustic signals be used with caution until a better understanding of in situ target spectra variability is gained.

Influence of near-fault velocity pulse on the seismic response of subway station structure

This research aims to explore the influence of near-fault velocity pulse on the seismic response of subway station under the condition of acceleration response spectra being consistent. Two suites of seismic motions are utilized, one suite is twelve as-recorded seismic motions with velocity pulses, and the other one suite is the corresponding artificial seismic motions synthesized with the response spectra of seismic motions in the first suite as target spectra. For each seismic motion with velocity pulse, the corresponding synthetic seismic motion without velocity pulse is generated by using the method of superimposing narrow-band time histories. Numerical model of soil-subway station interaction is developed by using the commercial software ABAQUS with a practical 3-span, 3-story subway station as the prototype. Numerical results indicate that with the engineering sites change from hard to soft and the burial depths change from shallow to deep, the adverse effect of velocity pulse is more significant, and the maximum inter-story drift ratio of subway station with a burial depth of 20 m embedded in site classes I, II and III has increased by 16.5%, 20.1% and 21.7%, respectively. However, the influence of velocity pulse on the concrete compression damage of subway station is not obvious.

Gaia Focused Product Release: Spatial distribution of two diffuse interstellar bands

Diffuse interstellar bands (DIBs) are absorption features seen in optical and infrared spectra of stars and extragalactic objects that are probably caused by large and complex molecules in the galactic interstellar medium (ISM). Here we investigate the Galactic distribution and properties of two DIBs identified in almost six million stellar spectra collected by the Gaia Radial Velocity Spectrometer. These measurements constitute a part of the Gaia Focused Product Release to be made public between the Gaia DR3 and DR4 data releases. In order to isolate the DIB signal from the stellar features in each individual spectrum, we identified a set of 160 000 spectra at high Galactic latitudes (|b| ⩾ 65°) covering a range of stellar parameters which we consider to be the DIB-free reference sample. Matching each target spectrum to its closest reference spectra in stellar parameter space allowed us to remove the stellar spectrum empirically, without reference to stellar models, leaving a set of six million ISM spectra. Using the star’s parallax and sky coordinates, we then allocated each ISM spectrum to a voxel (VOlume piXEL) on a contiguous three-dimensional grid with an angular size of 1.8° (level 5 HEALPix) and 29 unequally sized distance bins. Identifying the two DIBs at 862.1 nm (λ862.1) and 864.8 nm (λ864.8) in the stacked spectra, we modelled their shapes and report the depth, central wavelength, width, and equivalent width (EW) for each, along with confidence bounds on these measurements. We then explored the properties and distributions of these quantities and compared them with similar measurements from other surveys. Our main results are as follows: (1) the strength and spatial distribution of the DIB λ862.1 are very consistent with what was found in Gaia DR3, but for this work we attained a higher signal-to-noise ratio in the stacked spectra to larger distances, which allowed us to trace DIBs in the outer spiral arm and beyond the Scutum–Centaurus spiral arm; (2) we produced an all-sky map below ±65° of Galactic latitude to ~4000 pc of both DIB features and their correlations; (3) we detected the signals of DIB λ862.1 inside the Local Bubble (≲200 pc); and (4) there is a reasonable correlation with the dust reddening found from stellar absorption and EWs of both DIBs with a correlation coefficient of 0.90 for λ862.1 and 0.77 for λ864.8.

Ice Identification with Error-Accumulation Enhanced Neural Dynamics in Optical Remote Sensing Images

Arctic sea ice plays an important role in Arctic-related research. Therefore, how to identify Arctic sea ice from remote sensing images with high quality in an unavoidable noise environment is an urgent challenge to be solved. In this paper, a constrained energy minimization (CEM) method is applied for Arctic sea ice identification, which only requires the target spectrum. Moreover, an error-accumulation enhanced neural dynamics (EAEND) model with strong noise immunity and high computing accuracy is proposed to aid with the CEM method for Arctic sea ice identification. With the theoretical analysis, the proposed EAEND model possesses a small steady-state error in noisy environments. Finally, compared with other existing models, the proposed EAEND model can not only complete sea ice identification in excellent fashion, but also has the advantages of high efficiency and noise immunity.

Genome-Wide CRISPR/Cas9 Screens Identify DDX19A/DDX19B As a Critical Regulator of Intrinsic Apoptosis By Regulating MCL1 mRNA Cellular Localization

Despite recent advancements, the prognosis of relapsed/refractory acute lymphoblastic leukemia (ALL) remains dismal, necessitating novel therapies. Selinexor, an XPO1 (Exportin-1) inhibitor, shows effectiveness in multiple myeloma (MM), diffuse large B-cell lymphoma (DLBCL), and ALL mouse models. However, its broad target spectrum could lead to off-target toxicities, limiting its clinical utility. To elucidate Selinexor's molecular mechanisms in ALL we used CRISPR-Cas9 screens in the presence of Selinexor on ALL cell lines NALM-6 and KOPN-49. Among 18 genes displaying synthetic lethality in both cell lines with Selinexor, we focused on paralogous genes DDX19A and DDX19B, critical in nucleocytoplasmic transport of mRNA and translation initiation by dissociating protein complexes bound to mRNA. Competition assays showed prominent growth inhibitions when DDX19B was knocked out prior to DDX19A depletion in both NALM-6 and KOPN-49, while single KO of either DDX19A or DDX19B did not remarkably inhibit cell growth. Additionally, in MOLT-3 with low DDX19B expression, significant growth inhibitions were observed upon single KO of DDX19A and these phenotypes were canceled by the overexpression of DDX19B, suggesting functional redundancy between DDX19A and DDX19B. Further, we generated MOLT-3 that stably express HA-FKBP12 F36V-tagged DDX19A and knocked out endogenous DDX19A. Western blot analysis showed depletion of DDX19A by dTAG V-1 led to upregulate cleaved caspase-3 expression level within 4 hours, accompanied by a significant decrease in MCL1 protein levels in a BAX/BAK dependent manner. These phenotypes were rescued by the overexpression of MCL1, suggesting that the loss of DDX19A/19B induced intrinsic apoptosis through the downregulation of MCL1 expression. Given that the depletion of DDX19A/19B led to the mislocalization of polyadenylated mRNA and that neither the stability of the MCL1 protein nor the translation of MCL1 mRNA was affected by this depletion, as confirmed by RNA-FISH, and Actinomycin-D and Cycloheximide chase assays respectively, we concluded that DDX19A/19B are crucial for the nucleocytoplasmic transport of MCL1 mRNA. Furthermore, in exploring the relationship between the loss of DDX19A/19B and sensitivity to Selinexor, we found that combined treatment with Selinexor and the depletion of either DDX19A or DDX19B leads to a reduction in MCL1 protein, which can be rescued by overexpressing MCL1. Through CRISPR-Cas9 screens, we identified DDX19A/19B, which are in a paralogous relationship, as potential therapeutic targets for ALL. Mechanistically, the loss of DDX19A/19B leads to impaired cytoplasmic mRNA transport, leading to the inhibition of novel synthesis and reduced expression of MCL1 protein, thereby inducing intrinsic apoptosis. Furthermore, we found that DDX19A/19B depletion exerts synergistic effects with Selinexor through the downregulation of MCL1 expression, suggesting that DDX19A/19B levels could serve as a biomarker for Selinexor treatment in ALL.

Effects of modeling assumptions on prediction of seismic demands of a single-story RC structure

This study investigates the seismic response of a single-story reinforced concrete (RC) structure subjected to strong ground motions. Effects of modeling assumptions used to idealize the reinforcement slip in beam-column joints and column footing are studied. For this purpose, the numerical model of a single-story, single-bay, three-dimensional asymmetric RC structure, tested on a shake table and its symmetric version, is analyzed. Two modeling approaches are considered to show the significance of rotation associated with the reinforcement slip. Bidirectional nonlinear time-history analyses are conducted using symmetric and asymmetric 3D models. In these analyses, 30 pairs of near-field ground motions, selected and scaled to match the target spectrum, are used. The findings indicate that the neglection of reinforcement slip in numerical model may result in an underestimation of almost 50% in story drift ratio demands.

Chemometric enhancement for blind signal resolution from non-invasive spatially offset Raman spectra

Spatially offset Raman spectroscopy (SORS) is a promising spectroscopic technique that enables the collection of Raman signals from deeper layers of materials compared to conventional Raman spectroscopy. SORS equipment allows acquiring Raman spectra of substances through packaging, making it a non-invasive analytical technique. Note that the acquired spectrum is always the result of mixing two contributions: (1) the spectrum of the container material, and (2) the spectrum of the substance inside the container. Nowadays, SORS equipment are supported by software capable of removing the surface contribution from the recorded spectral data. However, the optimal extraction of this contribution is not achieved in all cases. This study explored the potential of two chemometric methods, Multivariate Curve Resolution (MCR) and Independent Components Analysis (ICA), for resolving the mixed spectra acquired by Vaya Raman equipment (Agilent) of four standard substances (sucrose, anhydrous sodium sulphate, ethanol 96% and glycerol) analyzed through containers of two different plastic materials (polypropylene and polyethylene terephthalate). The two resulting resolved spectra (by MCR and by ICA) and the one resolved by the equipment software were compared by similarity analysis with the Raman spectra of the standard substances available in recognized databases intended as target spectra. Similarity analysis was performed by calculating four similarity indexes, namely: cosine, arccosine, coefficient of determination and nearness index. Both MCR and ICA methods successfully extracted pure Raman spectra of the test substances more similar to the standard substances than the spectra resolved by the equipment software. These results highlighted the potential of both methods for resolving complex mixed signals, such as those acquired through the SORS technique, thereby enhancing its utility.

Target spectrum-based risk analysis model for utility tunnel O&M in multiple scenarios and its application

Current utility tunnel operation and maintenance (O&M) risk management suffers from low quality and inefficiency and still lacks a robust analysis method to address various risks. Therefore, this study proposes a theoretical model to build an adaptive system of algorithms and models based on global data linkage and a decision-making system for the target spectrum of intelligent O&M of utility tunnels. In addition, a risk prevention and control platform for utility tunnel O&M is formed, and remote centralized data collection, monitoring, emergency decision-making and other functions are realized to improve the safety of utility tunnel O&M. Finally, the model is validated using data from three typical scenarios, and the Beijing International Horticultural Exhibition utility tunnel is chosen as an example. The findings demonstrate that the model offers effective and adaptable decision support for utility tunnel O&M risk management.

Generating synthetic ground motions reaching target spectrum with the optimization approach

Due to the scarcity of earthquake records and the necessity of the earthquakes matched with the predefined design response spectrum (DRS) for time history analysis, designers need to generate artificial earthquakes. The smoothness of the DRS prevents conformity in the majority of methods, and deviation happens, especially in the constant region. To overcome this condition, the present study intends to incorporate the optimization algorithm with the synthetic earthquake method to reach the ASCE DRS. Indeed, the statistical algorithm is utilized to explore the global optimum with more accuracy and faster convergence in comparison with other algorithms. The results demonstrate that the proposed method is ideally compatible with the DRS with trivial errors. Furthermore, the novel approach has been applied to Kobe and Tabas earthquakes in order to extract the envelope function to improve compatibility in the time domain. In essence, the proposed method is not only compatible with the DRS simply but also appropriate for simulating real earthquakes. Eventually, with regard to the recommendation of seismic regulations for applying several records in dynamic analysis, one of the robust advantages of this method is to generate various earthquakes compatible with the specific target spectrum.

A Small Molecule with Big Impact: MRTX1133 Targets the KRASG12D Mutation in Pancreatic Cancer.

KRAS mutations drive oncogenic alterations in numerous cancers, particularly in human pancreatic ductal adenocarcinoma (PDAC). About 93% of PDACs have KRAS mutations, with G12D (∼42% of cases) and G12V (∼32% of cases) being the most common. The recent approval of sotorasib (AMG510), a small-molecule, covalent, and selective KRASG12C inhibitor, for treating patients with non-small cell lung cancer represents a breakthrough in KRAS targeted therapy. However, there is a need to develop other much-needed KRAS-mutant inhibitors for PDAC therapy. Notably, Mirati Therapeutics recently developed MRTX1133, a small-molecule, noncovalent, and selective KRASG12D inhibitor through extensive structure-based drug design. MRTX1133 has demonstrated potent in vitro and in vivo antitumor efficacy against KRASG12D-mutant cancer cells, especially in PDAC, leading to its recent initiation of a phase I/II clinical trial. Here, we provide a summary of the recent advancements related to the use of MRTX1133 for treating KRASG12D-mutant PDAC, focusing on its efficacy and underlying mechanistic actions. In addition, we discuss potential challenges and future directions for MRTX1133 therapy for PDAC, including overcoming intrinsic and acquired drug resistance, developing effective combination therapies, and improving MRTX1133's oral bioavailability and target spectrum. The promising results obtained from preclinical studies suggest that MRTX1133 could revolutionize the treatment of PDAC, bringing about a paradigm shift in its management.

Exploring TCR-like CAR-Engineered Lymphocyte Cytotoxicity against MAGE-A4.

TCR-like chimeric antigen receptor (CAR-T) cell therapy has emerged as a game-changing strategy in cancer immunotherapy, offering a broad spectrum of potential antigen targets, particularly in solid tumors containing intracellular antigens. In this study, we investigated the cytotoxicity and functional attributes of in vitro-generated T-lymphocytes, engineered with a TCR-like CAR receptor precisely targeting the cancer testis antigen MAGE-A4. Through viral transduction, T-cells were genetically modified to express the TCR-like CAR receptor and co-cultured with MAGE-A4-expressing tumor cells. Flow cytometry analysis revealed a significant surge in cells expressing activation markers CD69, CD107a, and FasL upon encountering tumor cells, indicating robust T-cell activation and cytotoxicity. Moreover, immune transcriptome profiling unveiled heightened expression of pivotal T-effector genes involved in immune response and cell proliferation regulation. Additionally, multiplex assays also revealed increased cytokine production and cytotoxicity driven by granzymes and soluble Fas ligand (sFasL), suggesting enhanced anti-tumor immune responses. Preliminary in vivo investigations revealed a significant deceleration in tumor growth, highlighting the therapeutic potential of these TCR-like CAR-T cells. Further investigations are warranted to validate these revelations fully and harness the complete potential of TCR-like CAR-T cells in overcoming cancer's resilient defenses.