CD4+ T cell immunity is dependent on an intrinsic stem-like program.

CD4+ T cells are central to various immune responses, but the molecular programs that drive and maintain CD4+ T cell immunity are not entirely clear. Here we identify a stem-like program that governs the CD4+ T cell response in transplantation models. Single-cell-transcriptomic analysis revealed that naive alloantigen-specific CD4+ T cells develop into TCF1hi effector precursor (TEP) cells and TCF1-CXCR6+ effectors in transplant recipients. The TCF1-CXCR6+CD4+ effectors lose proliferation capacity and do not reject allografts upon adoptive transfer into secondary hosts. By contrast, the TCF1hiCD4+ TEP cells have dual features of self-renewal and effector differentiation potential, and allograft rejection depends on continuous replenishment of TCF1-CXCR6+ effectors from TCF1hiCD4+ TEP cells. Mechanistically, TCF1 sustains the CD4+ TEP cell population, whereas the transcription factor IRF4 and the glycolytic enzyme LDHA govern the effector differentiation potential of CD4+ TEP cells. Deletion of IRF4 or LDHA in T cells induces transplant acceptance. These findings unravel a stem-like program that controls the self-renewal capacity and effector differentiation potential of CD4+ TEP cells and have implications for T cell-related immunotherapies.

Label-free optical imaging for brain cancer assessment.

Advances in label-free optical imaging offer a promising avenue for brain cancer assessment, providing high-resolution, real-time insights without the need for radiation or exogeneous agents. These cost-effective and intricately detailed techniques overcome the limitations inherent in magnetic resonance imaging (MRI), computed tomography (CT), and positron emission tomography (PET) scans by offering superior resolution and more readily accessible imaging options. This comprehensive review explores a variety of such methods, including photoacoustic imaging (PAI), optical coherence tomography (OCT), Raman imaging, and IR microscopy. It focuses on their roles in the detection, diagnosis, and management of brain tumors. By highlighting recent advances in these imaging techniques, the review aims to underscore the importance of label-free optical imaging in enhancing early detection and refining therapeutic strategies for brain cancer.

MUSTANG: Multi-sample spatial transcriptomics data analysis with cross-sample transcriptional similarity guidance.

Spatially resolved transcriptomics has revolutionized genome-scale transcriptomic profiling by providing high-resolution characterization of transcriptional patterns. Here, we present our spatial transcriptomics analysis framework, MUSTANG (MUlti-sample Spatial Transcriptomics data ANalysis with cross-sample transcriptional similarity Guidance), which is capable of performing multi-sample spatial transcriptomics spot cellular deconvolution by allowing both cross-sample expression-based similarity information sharing as well as spatial correlation in gene expression patterns within samples. Experiments on a semi-synthetic spatial transcriptomics dataset and three real-world spatial transcriptomics datasets demonstrate the effectiveness of MUSTANG in revealing biological insights inherent in the cellular characterization of tissue samples under study.

Effect of the ROCK inhibitor fasudil on the brain proteomic profile in the tau transgenic mouse model of Alzheimer's disease.

Introduction: The goal of this study is to explore the pharmacological potential of the amyloid-reducing vasodilator fasudil, a selective Ras homolog (Rho)-associated kinases (ROCK) inhibitor, in the P301S tau transgenic mouse model (Line PS19) of neurodegenerative tauopathy and Alzheimer's disease (AD). Methods: We used LC-MS/MS, ELISA and bioinformatic approaches to investigate the effect of treatment with fasudil on the brain proteomic profile in PS19 tau transgenic mice. We also explored the efficacy of fasudil in reducing tau phosphorylation, and the potential beneficial and/or toxic effects of its administration in mice. Results: Proteomic profiling of mice brains exposed to fasudil revealed the activation of the mitochondrial tricarboxylic acid (TCA) cycle and blood-brain barrier (BBB) gap junction metabolic pathways. We also observed a significant negative correlation between the brain levels of phosphorylated tau (pTau) at residue 396 and both fasudil and its metabolite hydroxyfasudil. Conclusions: Our results provide evidence on the activation of proteins and pathways related to mitochondria and BBB functions by fasudil treatment and support its further development and therapeutic potential for AD.

Charting Single Cell Lineage Dynamics and Mutation Networks via Homing CRISPR.

Single cell lineage tracing, essential for unraveling cellular dynamics in disease evolution is critical for developing targeted therapies. CRISPR-Cas9, known for inducing permanent and cumulative mutations, is a cornerstone in lineage tracing. The novel homing guide RNA (hgRNA) technology enhances this by enabling dynamic retargeting and facilitating ongoing genetic modifications. Charting these mutations, especially through successive hgRNA edits, poses a significant challenge. Our solution, LINEMAP, is a computational framework designed to trace and map these mutations with precision. LINEMAP meticulously discerns mutation alleles at single-cell resolution and maps their complex interrelationships through a mutation evolution network. By utilizing a Markov Process model, we can predict mutation transition probabilities, revealing potential mutational routes and pathways. Our reconstruction algorithm, anchored in the Markov model's attributes, reconstructs cellular lineage pathways, shedding light on the cell's evolutionary journey to the minutiae of single-cell division. Our findings reveal an intricate network of mutation evolution paired with a predictive Markov model, advancing our capability to reconstruct single-cell lineage via hgRNA. This has substantial implications for advancing our understanding of biological mechanisms and propelling medical research forward.

Spatial analysis of NOS2 and COX2 interaction with T-effector cells reveals immunosuppressive landscapes associated with poor outcome in ER- breast cancer patients.

Multiple immunosuppressive mechanisms exist in the tumor microenvironment that drive poor outcomes and decrease treatment efficacy. The co-expression of NOS2 and COX2 is a strong predictor of poor prognosis in ER- breast cancer and other malignancies. Together, they generate pro-oncogenic signals that drive metastasis, drug resistance, cancer stemness, and immune suppression. Using an ER- breast cancer patient cohort, we found that the spatial expression patterns of NOS2 and COX2 with CD3+CD8+PD1- T effector (Teff) cells formed a tumor immune landscape that correlated with poor outcome. NOS2 was primarily associated with the tumor-immune interface, whereas COX2 was associated with immune desert regions of the tumor lacking Teff cells. A higher ratio of NOS2 or COX2 to Teff was highly correlated with poor outcomes. Spatial analysis revealed that regional clustering of NOS2 and COX2 was associated with stromal-restricted Teff, while only COX2 was predominant in immune deserts. Examination of other immunosuppressive elements, such as PDL1/PD1, Treg, B7H4, and IDO1, revealed that PDL1/PD1, Treg, and IDO1 were primarily associated with restricted Teff, whereas B7H4 and COX2 were found in tumor immune deserts. Regardless of the survival outcome, other leukocytes, such as CD4 T cells and macrophages, were primarily in stromal lymphoid aggregates. Finally, in a 4T1 model, COX2 inhibition led to a massive cell infiltration, thus validating the hypothesis that COX2 is an essential component of the Teff exclusion process and, thus, tumor evasion. Our study indicates that NOS2/COX2 expression plays a central role in tumor immunosuppression. Our findings indicate that new strategies combining clinically available NOS2/COX2 inhibitors with various forms of immune therapy may open a new avenue for the treatment of aggressive ER-breast cancers.