Engineering chimeric autoantibody receptor T cells for targeted B cell depletion in multiple sclerosis model: An in-vitro study.

Background: Recent evidence suggests that B cells and autoantibodies have a substantial role in the pathogenesis of Multiple sclerosis. T cells could be engineered to express chimeric autoantibody receptors (CAARs), which have an epitope of autoantigens in their extracellular domain acting as bait for trapping autoreactive B cells. This study aims to assess the function of designed CAAR T cells against B cell clones reactive to the myelin basic protein (MBP) autoantigen. Methods: T cells were transduced to express a CAAR consisting of MBP as the extracellular domain. experimental autoimmune encephalomyelitis (EAE) was induced by injecting MBP into mice. The cytotoxicity, proliferation, and cytokine production of the MBP-CAAR T cells were investigated in co-culture with B cells. Results: MBP-CAAR T cells showed higher cytotoxic activity against autoreactive B cells in all effector-to-target ratios compared to Mock T cell (empty vector-transduced T cell) and Un-T cells (un-transduced T cell). In co-cultures containing CAAR T cells, there was more proliferation and inflammatory cytokine release as compared to Un-T and Mock T cell groups. Conclusion: Based on these findings, CAAR T cells are promising for curing or modulating autoimmunity and can be served as a new approach for clone-specific B cell depletion therapy in multiple sclerosis.

Identifying Key Lysosome-Related Genes Associated with Drug-Resistant Breast Cancer Using Computational and Systems Biology Approach.

Background: Drug resistance in breast cancer is an unsolved problem in treating patients. It has been recently discussed that lysosomes contribute to the invasion and angiogenesis of cancer cells. There is evidence that lysosomes can also cause multi-drug resistance. We analyzed this emerging concept in breast cancer through computational and systems biology approaches. Objectives: We aimed to identify the key lysosome-related genes associated with drug-resistant breast cancer. Methods: All genes contributing to the structure and function of lysosomes were inquired through the Human Lysosome Gene Database. The prioritized top 51 genes from the provided lists of Endeavour, ToppGene, and GPSy as prioritization tools were selected. All lysosomal genes and 12 breast cancer-related genes aligned to identify the most similar genes to breast cancer-related genes. Different centralities were applied to score each human protein to calculate the most central lysosomal genes in the human protein-protein interaction (PPI) network. Common genes were extracted from the results of the mentioned methods as a selected gene set. For Gene Ontology enrichment, the selected gene set was analyzed by WebGestalt, DAVID, and KOBAS. The PPI network was constructed via the STRING database. The PPI network was analyzed utilizing Cytoscape for topology network interaction and CytoHubba to extract hub genes. Results: Based on biological studies, literature reviews, and comparing all mentioned analyzing methods, six genes were introduced as essential in breast cancer. This computational approach to all lysosome-related genes suggested that candidate genes include PRF1, TLR9, CLTC, GJA1, AP3B1, and RPTOR. The analyses of these six genes suggest that they may have a crucial role in breast cancer development, which has rarely been evaluated. These genes have a potential therapeutic implication for new drug discovery for chemo-resistant breast cancer. Conclusions: The present work focused on all the functional and structural lysosome-related genes associated with breast cancer. It revealed the top six lysosome hub genes that might serve as therapeutic targets in drug-resistant breast cancer. Since these genes play a pivotal role in the structure and function of lysosomes, targeting them can effectively overcome drug resistance.

Relationship Between Low Expressions of tRNA-Derived Fragments with Metastatic Behavior of Colorectal Cancer.

PURPOSE: Colorectal cancer (CRC) is one of the most commonly diagnosed malignant tumors and highly heterogeneous diseases. More recently, RNA expression profiles have been used as prognostic cancer markers. In this regard, the expression of small non-coding RNAs like tRNA-derived fragments (tRFs) in tumor tissue has potential diagnostic values in metastatic cancer. METHOD: Sixty postoperative CRC tissue samples, consisting of 30 cancers and 30 adjacent normal tissues, were collected from cancer patients. We evaluated MINTbase database to select tRNA-derived fragments. The expression levels of miR-1280, miR1308, tRNA-ValAAC/CAC, and tRNA-AspGTC were measured by TaqMan quantitative reverse transcription PCR technology. Also, we have evaluated the correlation between the levels of tRFs gene expression and clinicopathological of CRC disease. RESULT: The three tRFs derived from tRF/miR-1280, tRNA-ValAAC/CAC, and tRNA-AspGTC downregulated in tumor tissues (all, p < 0.0001). These tRFs have lower expression in stage IV in comparison with stage III. The tRFs derived from tRNA-ValAAC (p = 0.005) and tRNA-AspGTC (p = 0.034) showed the decreased expression in CRC patients with distant metastasis. CONCLUSION: The present study demonstrated that low expression of tRF/miR-1280, tRNA-ValAAC/CAC, and tRNA-AspGTC was significantly associated with metastatic stage and more aggressive tumor behavior of CRC disease. Our finding promising the potential of using tRFs as biomarkers for cancer diagnosis.