Advancements and challenges in developing in vivo CAR T cell therapies for cancer treatment.

The Chimeric Antigen Receptor (CAR) T cell therapy has emerged as a ground-breaking immunotherapeutic approach in cancer treatment. To overcome the complexity and high manufacturing cost associated with current ex vivo CAR T cell therapy products, alternative strategies to produce CAR T cells directly in the body have been developed in recent years. These strategies involve the direct infusion of CAR genes via engineered nanocarriers or viral vectors to generate CAR T cells in situ. This review offers a comprehensive overview of recent advancements in the development of T cell-targeted CAR generation in situ. Additionally, it identifies the challenges associated with in vivo CAR T method and potential strategies to overcome these issues.

Disentangling single-cell omics representation with a power spectral density-based feature extraction.

Emerging single-cell technologies provide high-resolution measurements of distinct cellular modalities opening new avenues for generating detailed cellular atlases of many and diverse tissues. The high dimensionality, sparsity, and inaccuracy of single cell sequencing measurements, however, can obscure discriminatory information, mask cellular subtype variations and complicate downstream analyses which can limit our understanding of cell function and tissue heterogeneity. Here, we present a novel pre-processing method (scPSD) inspired by power spectral density analysis that enhances the accuracy for cell subtype separation from large-scale single-cell omics data. We comprehensively benchmarked our method on a wide range of single-cell RNA-sequencing datasets and showed that scPSD pre-processing, while being fast and scalable, significantly reduces data complexity, enhances cell-type separation, and enables rare cell identification. Additionally, we applied scPSD to transcriptomics and chromatin accessibility cell atlases and demonstrated its capacity to discriminate over 100 cell types across the whole organism and across different modalities of single-cell omics data.

Upconversion nanoparticle-assisted single-molecule assay for detecting circulating antigens of aggressive prostate cancer.

Sensitive and quantitative detection of molecular biomarkers is crucial for the early diagnosis of diseases like metabolic syndrome and cancer. Here we present a single-molecule sandwich immunoassay by imaging the number of single nanoparticles to diagnose aggressive prostate cancer. Our assay employed the photo-stable upconversion nanoparticles (UCNPs) as labels to detect the four types of circulating antigens in blood circulation, including glypican-1 (GPC-1), leptin, osteopontin (OPN), and vascular endothelial growth factor (VEGF), as their serum concentrations indicate aggressive prostate cancer. Under a wide-field microscope, a single UCNP doped with thousands of lanthanide ions can emit sufficiently bright anti-Stokes' luminescence to become quantitatively detectable. By counting every single streptavidin-functionalized UCNP which specifically labeled on each sandwich immune complex across multiple fields of views, we achieved the Limit of Detection (LOD) of 0.0123 ng/ml, 0.2711 ng/ml, 0.1238 ng/ml, and 0.0158 ng/ml for GPC-1, leptin, OPN and VEGF, respectively. The serum circulating level of GPC-1, leptin, OPN, and VEGF in a mixture of 10 healthy normal human serum was 25.17 ng/ml, 18.04 ng/ml, 11.34 ng/ml, and 1.55 ng/ml, which was within the assay dynamic detection range for each analyte. Moreover, a 20% increase of GPC-1 and OPN was observed by spiking the normal human serum with recombinant antigens to confirm the accuracy of the assay. We observed no cross-reactivity among the four biomarker analytes, which eliminates the false positives and enhances the detection accuracy. The developed single upconversion nanoparticle-assisted single-molecule assay suggests its potential in clinical usage for prostate cancer detection by monitoring tiny concentration differences in a panel of serum biomarkers.