Afshin Derakhshani

The journal retracts the article entitled “Silencing ZEB2 induces apoptosis and reduces viability in glioblastoma cell lines”

There is a higher density of immune cells in peritoneal fluid than is found in blood. Thus, any perturbations, from sterile injury to endometriosis to ovarian cancer, require immune cells to recognize and nucleate to these sites. Using peritoneal injuries as a prototype, we saw a massive recruitment of large peritoneal macrophages (LPMs) interspersed with mast cells. The mast cells were activated by sensory neurons to mobilize their 1-μm granules to the cell surface. Lattice light sheet microscopy unveiled a new step in the mast cell degranulation. After granules fused with the plasma membrane, cytonemes (very thin long filopodia) grabbed the granules from the mast cell surface and deposited them on neighboring LPMs. The granules were membraneless biomolecular condensates and harbored more than 200 different proteins, including MARCO, which mediated rapid LPM aggregation to the injury nidus. The condensates also induced a repair-like phenotype in the macrophages that helped heal the injury site.

Nonresolving inflammation and maladaptive renal repair contribute to the pathogenesis of acute kidney injury (AKI) transition to chronic kidney disease (CKD). Few therapies have been identified that can modulate these injurious pathways following AKI. Spleen tyrosine kinase (SYK) is an immune regulator expressed in the kidney and a potential therapeutic target for AKI. The effect of the selective SYK inhibitor entospletinib was studied in AKI-to-CKD transition. Entospletinib was administered to mice undergoing unilateral renal ischemia-reperfusion injury (IRI), with kidneys analyzed over 14 days. Single-cell RNA sequencing, digital spatial profiling, intravital microscopy, and flow cytometry were employed to study renal phenotypes. Entospletinib administered before and after IRI protected ischemic kidneys and significantly attenuated the transition to CKD. Entospletinib targeted leukocyte-expressed SYK and prevented neutrophil/monocyte recruitment to the kidney. Entospletinib reduced nonresolving tubulointerstitial inflammation after AKI by blocking activation of mannose receptor-1– and C-type lectin domain family 7 member A–expressing proinflammatory macrophages. The resolution of renal inflammation mediated by entospletinib was associated with a reciprocal increase in resident macrophages, reparative gene expression, preserved tubular integrity, and reduced renal fibrosis. The SYK inhibitor entospletinib resolves renal inflammation and promotes repair following AKI.

Ulcerative colitis is characterized by impaired gut barrier function. Mast cell-derived chymase influences epithelial integrity, but its primary role remains unclear. Using the TAILS technique, we identified chymase/Mcpt4 substrates in colonic epithelial cells, revealing cytoskeletal and junction-associated proteins enrichment. Transepithelial electrical resistance assays confirmed chymase-mediated barrier disruption using T84 cells. Our data indicates that chymase/Mcpt4 plays a role in epithelial dysfunction in ulcerative colitis, suggesting it as a possible therapeutic target.

Background: Atopic dermatitis (AD) is a common allergic disorder. Detection of responsible pathogenic allergens in AD patients by reliable methods has a fundamental role in the prevention, management, and treatment of AD. This study was conducted to determine the most common allergens by the skin prick test (SPT) and immunoblotting among AD ...

Growing evidence suggests a role for peroxisome proliferator-activated receptor β/δ (PPAR β/δ) in the angiogenesis, growth, and metastasis of solid tumors, but little is known about its role in multiple myeloma (MM). Angiogenesis in the bone marrow (BM) is characteristic of disease transition from monoclonal gammopathy of undetermined significance (MGUS) to MM. We examined the expression and function of PPAR β/δ in endothelial cells (EC) from the BM of MGUS (MGEC) and MM (MMEC) patients and showed that PPAR β/δ was expressed at higher levels in MMEC than in MGEC and that the overexpression depended on myeloma plasma cells. The interaction between myeloma plasma cells and MMEC promoted the release of the PPAR β/δ ligand prostaglandin I2 (PGI2) by MMEC, leading to the activation of PPAR β/δ. We also demonstrated that PPAR β/δ was a strong stimulator of angiogenesis in vitro and that PPAR β/δ inhibition by a specific antagonist greatly impaired the angiogenic functions of MMEC. These findings define PGI2-PPAR β/δ signaling in EC as a potential target of anti-angiogenic therapy. They also sustain the use of PPAR β/δ inhibitors in association with conventional drugs as a new therapeutic approach in MM.

It is estimated that there were 18.1 million cancer cases worldwide in 2018, with about 9 million deaths. Proper diagnosis of cancer is essential for its effective treatment because each type of cancer requires a specific treatment procedure. Cancer therapy includes one or more approaches such as surgery, radiotherapy, chemotherapy, and immunotherapy. In recent years, immunotherapy has received much attention and immune checkpoint molecules have been used to treat several cancers. These molecules are involved in regulating the activity of T lymphocytes. Accumulated evidence shows that targeting immune checkpoint regulators like PD-1/PD-L1 and CTLA-4 are significantly useful in treating cancers. According to studies, these molecules also have pivotal roles in the chemoresistance of cancer cells. Considering these findings, the combination of immunotherapy and chemotherapy can help to treat cancer with a more efficient approach. Among immune checkpoint molecules, the B7 family checkpoints have been studied in various cancer types such as breast cancer, myeloma, and lymphoma. In these cancers, they cause the cells to become resistant to the chemotherapeutic agents. Discovering the exact signaling pathways and selective targeting of these checkpoint molecules may provide a promising avenue to overcome cancer development and therapy resistance. Highlights: (1) The development of resistance to cancer chemotherapy or immunotherapy is the main obstacle to improving the outcome of these anti-cancer therapies. (2) Recent investigations have described the involvement of immune checkpoint molecules in the development of cancer therapy resistance. (3) In the present study, the molecular participation of the B7 immune checkpoint family in anticancer therapies has been highlighted. (4) Targeting these immune checkpoint molecules may be considered an efficient approach to overcoming this obstacle.

Traditional bulk sequencing methods are limited to measuring the average signal in a group of cells, potentially masking heterogeneity, and rare populations. The single-cell resolution, however, enhances our understanding of complex biological systems and diseases, such as cancer, the immune system, and chronic diseases. However, the single-cell technologies generate massive amounts of data that are often high-dimensional, sparse, and complex, thus making analysis with traditional computational approaches difficult and unfeasible. To tackle these challenges, many are turning to deep learning (DL) methods as potential alternatives to the conventional machine learning (ML) algorithms for single-cell studies. DL is a branch of ML capable of extracting high-level features from raw inputs in multiple stages. Compared to traditional ML, DL models have provided significant improvements across many domains and applications. In this work, we examine DL applications in genomics, transcriptomics, spatial transcriptomics, and multi-omics integration, and address whether DL techniques will prove to be advantageous or if the single-cell omics domain poses unique challenges. Through a systematic literature review, we find that DL has not yet revolutionized or addressed the most pressing challenges of the single-cell omics field. However, using DL models for single-cell omics has shown promising results (in many cases outperforming the previous state-of-the-art models) in data preprocessing and downstream analysis, but many DL models still lack the needed biological interpretability. Although developments of DL algorithms for single-cell omics have generally been gradual, recent advances reveal that DL can offer valuable resources in fast-tracking and advancing research in single-cell.Abstract Figure:

Gastric cancer (GC), with a heterogeneous nature, is the third leading cause of death worldwide. Over the past few decades, stable reductions in the incidence of GC have been observed. However, due to the poor response to common treatments and late diagnosis, this cancer is still considered one of the lethal cancers. Emerging methods such as immunotherapy with immune checkpoint inhibitors (ICIs) have transformed the landscape of treatment for GC patients. There are presently eleven known members of the B7 family as immune checkpoint molecules: B7-1 (CD80), B7-2 (CD86), B7-H1 (PD-L1, CD274), B7-DC (PDCD1LG2, PD-L2, CD273), B7-H2 (B7RP1, ICOS-L, CD275), B7-H3 (CD276), B7-H4 (B7x, B7S1, Vtcn1), B7-H5 (VISTA, Gi24, DD1α, Dies1 SISP1), B7-H6 (NCR3LG1), B7-H7 (HHLA2), and Ig-like domain-containing receptor 2 (ILDR2). Interaction of the B7 family of immune-regulatory ligands with the corresponding receptors resulted in the induction and inhibition of T cell responses by sending co-stimulatory and co-inhibitory signals, respectively. Manipulation of the signals provided by the B7 family has significant potential in the management of GC.