Mohamed El-Agamy Farh

Background/Objectives: Radiation-induced lung injury (RILI) involves inflammatory responses followed by fibrotic remodeling. We evaluated CYNC-1, a synthetic compound designed as a lipoxin A4 (LXA4) mimetic, for chemical stability, cellular activity, and attenuation of lung injury after irradiation. Methods: HeLa-derived L132 epithelial-like cells and THP1-Lucia NF-κB reporter monocytes were used for cell-based assays. Male C57BL/6 mice received a single 75-Gy focal lung irradiation. CYNC-1 administration began immediately after irradiation and continued every other day for 2 or 6 weeks. Lung injury was assessed using bronchoalveolar lavage fluid cellularity, micro-computed tomography, histopathology, and lung mechanics. Prednisolone and nintedanib served as reference treatments in the 2- and 6-week cohorts, respectively. Results: CYNC-1 maintained high HPLC area purity during light-protected ethanol storage for 48 h at −78, −20, and 4 °C. It increased survival of irradiated L132 cells and reduced LPS-induced NF-κB reporter activity. In L132 cells, treatment was associated with reduced NF-κB/MAPK and Smad2 phosphorylation and lower profibrotic marker expression. In mice, CYNC-1 reduced inflammatory cell accumulation and collagen deposition and improved lung structure and mechanics. Conclusions: Early and continued CYNC-1 administration attenuated lung inflammation and subsequent fibrotic remodeling in this focal irradiation model. The signaling findings are associative, and FPR2 dependence and efficacy against established fibrosis remain to be established. Validation in primary human lung cells, clinically relevant fractionated irradiation models, animals of both sexes, and tumor models is needed to determine suitability as a normal-tissue protectant, including preservation of antitumor efficacy.

Triple-negative breast cancer (TNBC) poses a significant therapeutic challenge owing to its aggressiveness and limited treatment options. Here, we integrated genome-scale metabolic modeling with machine learning to improve gene essentiality prediction and identify candidate therapeutic targets for TNBC. Cell-line-specific genome-scale metabolic models were reconstructed for 50 breast cancer cell lines using RNA-sequencing from Cancer Dependency Map (DepMap). Metabolic reaction flux distributions derived from minimization of metabolic adjustment (MOMA) were used as features to train a random forest classifier, with DepMap gene dependency scores as ground truth labels. This integrative approach outperformed the MOMA alone for gene essentiality prediction, increasing sensitivity from 0.37 to 0.55. The model identified 57 TNBC-specific essential genes, including Enolase 1 (ENO1), that were missed by MOMA-based prediction. Furthermore, 30 synthetic lethal partners of succinate dehydrogenase subunit A (SDHA) were predicted in TNBC cell lines. This framework demonstrates the utility of combining metabolic modeling with machine learning for identifying context-specific cancer vulnerabilities.

Background: The optimal timing of adjuvant chemotherapy after cytoreductive surgery in epithelial ovarian cancer remains uncertain, and perioperative wound-healing responses may transiently create a pro-tumorigenic and drug-resistant microenvironment. This study aimed to characterize time-dependent wound-induced transcriptomic alterations and to identify pharmacologic agents capable of reversing these responses. Methods: An ID8 murine ovarian cancer model was used to compare no treatment, anesthesia alone, and anesthesia plus surgical wounding mimicking futile laparotomy. Tumors were collected at baseline, 1 day (T1), 1 week (T2), and 2 weeks (T3) after intervention. RNA sequencing was performed, and wound-specific differentially expressed genes (WsDEGs) were defined by excluding anesthesia- and progression-related signatures. Functional enrichment analyses were conducted, followed by transcriptome-based drug repurposing using the REMEDY platform to identify compounds predicted to reverse wound-induced gene expression profiles. Results: Surgical wounding significantly increased tumor burden at T1. Transcriptomic analyses revealed distinct, time-dependent wound-associated programs. At T1, WsDEGs were enriched in inflammatory signaling, coagulation, angiogenesis, and immune cell migration, with Vorinostat and Homoharringtonine identified as top candidates to counteract these signatures. At T2, pathways related to cell survival, adhesion, and morphogenesis predominated, with LY-2090314, Artesunate, and Birinapant emerging as potential modulators. At T3, cell-cycle regulation and lipid metabolic pathways were dominant, and Fulvestrant, Atorvastatin, Imatinib, and ABT-737 were predicted to inhibit these processes. Conclusions: Perioperative surgical wounding induces dynamic, stage-specific transcriptomic programs that may promote ovarian cancer progression and alter drug responsiveness. These findings support time-adapted perioperative pharmacologic strategies to optimize postoperative cancer therapy.

Intestinal glucose excretion, defined as increased intestinal serum glucose uptake and secretion into the lumen, influences bariatric surgery-associated glycaemic control. Here, we investigate molecular mechanisms that activate intestinal glucose excretion. We evaluate altered transcriptomes in variable intestinal glucose excretion models and big data-based drug discovery systems. We show that protein kinase C (PKC) activation mimics transcriptome alterations observed during intestinal glucose excretion. Among PKC subfamilies, atypical PKC (aPKC) facilitates glucose transporter 1 (GLUT1)-mediated intestinal glucose excretion without inducing oncogenic proliferation. Intestinal aPKC activation via transposon expression vector induces serum glucose uptake into intestinal tissues and excretion into the lumen. Prostratin, a non-tumorigenic phorbol ester, activates aPKC and induces a similar effect on intestinal glucose excretion. We identify the prostratin and aPKC/GLUT1 signalling pathways as putative targets for treating diabetes, providing insights into the future development of antidiabetic and weight-loss drugs.

Background: Radiation-induced pulmonary fibrosis (RPF) remains a major burden of successful lung cancer radiotherapy. Clinically validated drugs targeting RPF remains scarce. Methods: We employed a transcriptome-based drug repurposing approach using REMEDY, a computational platform built on the Library of Integrated Network-Based Cellular Signatures (LINCS). Differentially expressed genes (DEGs) derived from radiation-induced lung injury (RILI) models were used as a query to identify compounds capable of reversing pro-fibrotic expression profile. Among top-ranked candidates, homoharringtonine (HHT), an FDA-approved protein synthesis inhibitor, was selected for experimental validation. Anti-fibrotic effects of HHT were assessed using an optimized in vitro fibrotic model based on activation of MRC-5 human lung fibroblasts. Complementary in silico molecular docking analyses were also conducted to explore the mechanistic basis of HHT’s actions. This represents the first transcriptome-guided, LINCS-based drug repurposing study applied specifically to radiation-induced pulmonary fibrosis, utilizing RPF-derived molecular signatures rather than general fibrosis-related datasets. Results: HHT significantly attenuated key fibrotic phenotypes, including fibroblast proliferation, myofibroblast differentiation, and extracellular matrix (ECM) production. Notably, HHT suppressed expression of cyclin D1 and α-smooth muscle actin (α-SMA), and reduced collagen deposition. Mechanistic investigations revealed that HHT modulates two pro-fibrotic pathways: RhoA/ROCK and Wnt/β-catenin signaling. Molecular docking further suggested that HHT may directly interact with fibrosis-related receptors such as integrins and Frizzled, providing structural insight into its anti-fibrotic potential. These findings underscore the novelty of reassigning HHT to a radiation-specific fibrotic context using a signature-reversal strategy uniquely tailored to RPF biology. Conclusions: Our findings identify HHT as a promising treatment of RPF, offering a dual mechanism of action—interruption of protein synthesis and targeted inhibition of fibrotic signaling pathways. This study highlights the value of computational drug repurposing platforms for accelerating therapeutic discovery. Further preclinical investigations are warranted to evaluate HHT’s in vivo efficacy and clinical applicability in RPF.

Root rot caused by Ilyonectria mors-panacis is a devastating fungal disease leading to defect in root quality and causes reduced yield during the perennial life cycle of Panax ginseng Meyer. This indicates the imperative need to understand the molecular basis of disease development and also to enhance tolerance against the fungus. With this idea, the protective effect of silicon (supplied as silica nanoparticles) in P. ginseng root rot pathosystem and its molecular mechanism was investigated in the current study. We have tested different concentrations of silicon (Si) to disease-infected ginseng and found that long term analysis (30 dpi) displayed a striking 50% reduction in disease severity index upon the treatment of Si. Expectedly, Si had no direct degradative effect against the pathogen. Instead, in infected roots it resulted in reduced expression of PgSWEET leading to regulated sugar efflux into apoplast and enhanced tolerance against I. mors-panacis. In addition, under diseased condition, both protopanaxadiol (PPD) and protopanaxatriol (PPT) type ginsenoside profile in roots were higher in Si treated plants. This is the first report indicating the protective role of Si in ginseng-root rot pathosystem, thereby uncovering novel features of ginseng mineral physiology and at the same time, enabling its usage to overcome root rot.

Recently, green metal nanoparticles have received global attention owing to their economical synthesis, biocompatible nature, widespread biomedical and environmental applications. Current study demonstrates a sustainable approach for the green synthesis of silver nanoparticles (P-AgNPs) and gold nanoparticles (P-AuNPs) from P. serrulata fresh fruit extract. The silver and gold nanoparticles were synthesized in a very rapid, efficient and facile manner, within 50 min and 30 s at 80 °C, respectively. The nanoparticles were characterized by using visual observation, UV–Vis, FE-TEM, EDX, elemental mapping, FT-IR, XRD and DLS, which confirmed the formation of monodispersed, crystalline and stable nanoparticles. Further, we explored these nanoparticles for anti-inflammatory activity through inhibition of downstream NF-κB activation in macrophages (RAW264.7). We demonstrated that the nanoparticles reduced expression of inflammatory mediators such as nitric oxide (NO), prostaglandin E2 (PEG₂), inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) was attenuated in lipopolysaccharide (LPS)-induced RAW264.7 cells. Furthermore, nanoparticles significantly suppressed LPS-induced activation of NF-κB signalling pathway via p38 MAPK in RAW 264.7 cells. To the best of our knowledge, this is the first report on the efficient green synthesis of P-AgNPs and P-AuNPs using P. serrulata fresh fruit extract and its in vitro anti-inflammatory effects. Collectively, our results suggest that P. serrulata fresh fruit extract is a green resource for the eco-friendly synthesis of P-AgNPs and P-AuNPs, which further can be utilized as a novel therapeutic agent for prevention and cure of inflammation due to their biocompatible nature.