Bruton's tyrosine kinase (BTK) is a central mediator of B-cell receptor signaling and a validated therapeutic target in chronic lymphocytic leukemia (CLL). However, the clinical efficacy of both covalent and non-covalent BTK inhibitors is increasingly undermined by resistance-conferring mutations, particularly at residues C481 and T474. These mutations, alone or in combination, pose a significant challenge to sustained therapeutic response. In this study, integrative quantum mechanical and molecular modeling approaches were employed to investigate the effects of clinically relevant BTK mutations on inhibitor binding. Ten FDA-approved covalent and non-covalent inhibitors were evaluated against four single mutants (C481S, A428D, V416L, and D539G) and four compound mutants (T474A/C481S, T474I/C481S, T474M/C481S, and T474S/C481S). Density functional theory-based local and global reactivity descriptors identified nucleophilic and electrophilic hotspots within the inhibitors, with nitrogen atoms in pirtobrutinib, zanubrutinib, and spebrutinib displaying pronounced nucleophilic potential, suggesting a key role in stabilizing interactions within the BTK active site. Molecular docking analyses revealed that these inhibitors maintained strong binding affinities across multiple BTK mutants, frequently exceeding that of ibrutinib. Molecular dynamics simulations confirmed the structural stability and compactness of selected inhibitor-BTK complexes. Binding free-energy calculations further supported these observations, with several mutant complexes demonstrating enhanced affinities relative to the wild type. Collectively, these findings highlight structurally resilient inhibitors capable of overcoming compound mutation-driven resistance and underscore the importance of BTK mutational profiling in guiding precision therapeutic strategies for BTK-driven malignancies.

Abstract Glioblastoma is the most aggressive tumor arising from astrocytic cells and is resistant to standard therapies due to its extreme tumor heterogeneity, diverse genetic mutations, and supportive tumor microenvironment. Recent investigations from our laboratory and from other researchers have identified the atypical cadherin FAT1 as one of the oncogenic molecules regulating diverse signaling complexes that facilitate tumor progression in glioblastoma. On the basis of our published and ongoing work, the emerging patterns highlight FAT1 as a central regulator of various downstream signaling pathways that promote the oncogenic features of glioblastoma by upregulating inflammation, HIF-1α, and epithelial-to-mesenchymal transition/stemness under severe hypoxia, mediating immune evasion, and regulating autophagy. Glioblastoma patients with high-FAT1-expressing tumors showed poor overall survival. A preclinical study in nude mice using FAT1-knockout U87MG cells showed delayed tumor growth and reduced tumor volume, reflecting FAT1’s role as a tumor promoter. Overall, FAT1 represents a promising target for combination therapy with immunotherapy and autophagy modulators in glioblastoma. This review covers the role of FAT1 in regulating the downstream oncogenic molecules and pathways, current progress in understanding FAT1 function, and its potential use as a marker for patient stratification and FAT1-targeted interventions in glioblastoma.

Among various types of cancers, lung cancer causes the highest mortality globally, necessitating prompt diagnosis for effective treatment. Traditionally, histopathological analysis of Hematoxylin and Eosin (H&E)-stained slides serves as the principal method for definitive diagnosis. However, manual interpretation is often hindered by staining variability. This research focuses on designing a Convolutional Neural Network (CNN) model tailored to classify various subtypes of lung carcinoma. It aims to overcome key diagnostic challenges, including variability in staining techniques. The publicly available LC25000 dataset comprising lung histopathological images was utilized. To mitigate staining variability and reduce noise, Reinhard color normalization and Gaussian filtering were applied during pre-processing. Particle Swarm Optimization (PSO) was employed for hyperparameter tuning, which helped in the development of a multi-scale CNN architecture tailored for robust classification. The optimized CNN model achieved a classification accuracy of 98.59% across three categories: two non-small cell lung malignant classes and one benign class. Comparative evaluations revealed that pre-processed images significantly improved classification consistency and accuracy, highlighting the benefits of color normalization techniques. The developed model exhibits strong diagnostic performance and improved resilience to staining variability. To support real-time clinical use, the model was successfully deployed as an Android-based mobile application. This application is publicly available and can be accessed at: https://github.com/jar3e1/AndroidApp.

Background Glioblastoma (GBM) is the most aggressive primary brain malignancy, characterised by hypoxia-driven proliferation, therapeutic resistance and poor prognosis. While hypoxia-induced transcriptional changes are well documented, the temporal regulation of cell cycle genes under sustained hypoxia remains unclear. Purpose This study aimed to profile transcriptomic alterations induced by graded hypoxia and identify key hypoxia-responsive regulatory genes in GBM. Methods U87MG cells were cultured under normoxia and graded hypoxia (1-3 days), and experimental data of U87MG and LN229 GBM cells were utilised for validation and addressing heterogeneity. Differentially expressed genes (DEGs) were identified and analysed using STRING, Cytoscape, MCODE and CytoHubba to construct protein-protein interaction networks and extract hub genes. Functional enrichment was assessed through DAVID, ClueGO and KEGG, while prognostic relevance was evaluated using GlioVis and ONCOMINE data sets. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) validated hub gene expression dynamics. Results A total of 275 DEGs formed two main functional modules enriched in cell cycle regulation and chemokine signalling. Eighteen hub genes (KIF20A, KIFC1, CCNB1, AURKA, EGR1, CDCA3, CENPF, CDCA2, ASPM, KIF11, CCL2, CXCL8, CCNA2, DLGAP5, RACGAP1, TPX2, PTGS2 and CTGF) were significantly associated with mitotic processes and GBM progression. Survival analysis demonstrated that 17 hub genes correlated with poor overall survival (p < .05). qRT-PCR confirmed that hub gene expression peaked during early hypoxia and declined with prolonged exposure, indicating dynamic regulatory adaptation. Conclusion These findings identify key hypoxia-responsive genes governing cell cycle progression and immunomodulation in GBM, highlighting their prognostic value and therapeutic potential in GBM.

Accurate classification of lung carcinoma subtypes in histopathological images is critical for early diagnosis and timely initiation of appropriate lung carcinoma treatment. Traditional diagnostic methods, though effective, often rely on manual interpretation, which can be time-consuming and subject to inter-observer variability. In contrast, deep learning enables automated and consistent analysis of complex tissue structures, improving diagnostic accuracy in clinical workflows. This study presents a hybrid framework that combines classical edge detection techniques with a lightweight attention-based convolutional neural network (CNN) to enhance diagnostic performance on Whole Slide Image (WSI) patches. A total of 11,580 image patches—classified into Lung Adenocarcinoma (LUAD), Lung Squamous Cell Carcinoma (LSCC), and Non-Malignant (NM)—were preprocessed using four classical edge detection methods: Canny, Prewitt, Roberts, and Laplacian of Gaussian (LoG). These edge-enhanced images were then used to train a custom CNN architecture equipped with attention mechanisms to capture critical morphological patterns. Finally, a comprehensive evaluation was conducted using both edge quality metrics (EPI, edge density, and entropy) and classification metrics (accuracy, precision, sensitivity, specificity, F1-score, and AUC-ROC). The results indicate that Prewitt-based preprocessing delivered the most balanced and reliable performance, achieving AUC values as high as 0.94 and a peak classification accuracy of 89.57%. These findings highlight the effectiveness of integrating classical image processing techniques with deep learning to develop interpretable, efficient, and clinically applicable diagnostic systems.

Autophagy, a conserved intracellular degradation process, plays dual roles in cancer, promoting survival under stress or mediating cell death through deregulated autophagy. Atypical cadherin FAT1 functions as an oncogene or tumor suppressor in a context-dependent manner. Our previous work identifies the oncogenic role of FAT1 in glioblastoma. Deregulated autophagy has been documented in glioma. Here, we investigated the role of FAT1 in regulating autophagy and its implications for glioblastoma growth and progression. CRISPR-Cas9 mediated FAT1 knockout was generated in glioblastoma (U87MG and LN229) and other cancers such as hepatocellular carcinoma (HepG2 and HUH7) and pancreatic adenocarcinoma (MIAPaca-2 and Panc-1) cells. The cell viability and growth under hypoxia ± serum deprivation were analyzed by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), colony formation, and Annexin V–FITC assays. Autophagy markers were assessed by quantitative polymerase chain reaction (qPCR), Western blot, immunocytochemistry (ICC), and immunohistochemistry (IHC). Autophagosomes were visualized by transmission electron microscopy (TEM), and puncta formation was analyzed by transfecting the cells with pEGFP-LC3. Autophagy flux was evaluated by analyzing p62/SQSTM1 levels, and the GFP/RFP ratio using pMRX-IP-GFP-LC3-RFP-LC3ΔG. In vivo, FAT1-knockout U87MG xenografts in nude mice were analyzed for tumor growth and autophagy marker expression. Surgically resected glioblastoma tumors from our hospital and The Cancer Genome Atlas (TCGA) dataset were analyzed for autophagy marker expression and patient survival correlations. FAT1-knockout glioblastoma (U87MG and LN229) cells demonstrated reduced survival and colony numbers under normoxia and hypoxia with serum deprivation, facilitated by autophagy-dependent cell death. These cells exhibited upregulated autophagy markers, increased LC3 puncta, autophagosomes, and autophagy flux. FAT1-knockout glioblastoma cells showed decreased total and phospho-mTOR levels. FAT1-knockout xenografts showed reduced tumor progression with increased LC3II, Beclin1, and autophagosomes. Human glioblastoma tumors and TCGA glioblastoma data revealed an inverse expression correlation of FAT1 with LC3B/Beclin1, tumors with high-FAT1/low-LC3B expression were associated with poor patient survival. FAT1 also regulated autophagy in hepatocellular and pancreatic cancers. Our findings indicate that FAT1 mediates pro-tumorigenic function by suppressing autophagic cell death in glioblastoma and other cancers. FAT1 may serve as a potential therapeutic adjuvant along with standard therapeutic regimens for treating cancers with high FAT1 expression having an oncogenic role.

The Central nervous system (CNS) is the prime regulator of signaling pathways whose function includes regulation of food intake (consumption), energy expenditure, and other metabolic responses like glycolysis, gluconeogenesis, fatty acid oxidation, and thermogenesis that have been implicated in chronic inflammatory disorders. Type 2 diabetes mellitus (T2DM) and obesity are two metabolic disorders that are linked together and have become an epidemic worldwide, thus raising significant public health concerns. Fibroblast growth factor 21 (FGF21) is an endocrine hormone with pleiotropic metabolic effects that increase insulin sensitivity and energy expenditure by elevating thermogenesis in brown or beige adipocytes, thus reducing body weight and sugar intake. In contrast, during starvation conditions, FGF21 induces its expression in the liver to initiate glucose homeostasis. Insulin resistance is one of the main anomalies caused by impaired FGF21 signaling, which also causes abnormal regulation of other signaling pathways. Tumor necrosis factor alpha (TNF-α), the cytokine released by adipocytes and inflammatory cells in response to chronic inflammation, is regarded major factor that reduces the expression of FGF21 and modulates underlying insulin resistance that causes imbalanced glucose homeostasis. This review aims to shed light on the mechanisms underlying the development of insulin resistance in obese individuals as well as the fundamental flaw in type 2 diabetes, which is malfunctioning obese adipose tissue.

Conventional antibodies are among the most frequently used and effective biological tools explored for therapeutic and diagnostic applications. However, they face significant limitations when it comes to challenges that demand specialized attributes such as rapid tissue penetration, the ability to bind to concealed epitopes, and stability in nonphysiological environments. In recent years, shark-derived immunoglobulin variable new antigen receptor (vNAR) has emerged as a promising alternative to overcome these limitations. In this study, we constructed a naïve vNAR phage display library from a white-spotted bamboo shark (Chiloscyllium plagiosum), with a library diversity size of ∼3 × 1011 clones. Next generation sequencing analysis revealed the high diversity of the library, allowing it to encompass a broad range of classical functional vNAR types. To confirm the usability of the library for the successful isolation of positive clones, we screened the library against wide range of antigens (n = 9;) from different origin that includes viral, cancer, autoimmune, toxins, parasite, algae, and plant antigens. We achieved a hit rate of ∼100%, of potent binders with micro to nanomolar range affinity. The total number of unique binder's clones varied from 30%-100%, depending on the antigens and screening strategy. Furthermore, we provide an in-depth structural analysis by using X-ray crystallography of class IV vNARs from bamboo sharks, which remain underexplored. Our study represents a significant step forward in the field of single-domain antibody research and development.

Post-translational modifications fine-tune protein function and regulate key signalling pathways in eukaryotic cells. ADP-ribosylation, which is catalyzed by the poly(ADP‒ribose) polymerase (PARP) family of enzymes, governs processes such as transcription, DNA repair, and inflammation. PARP14, a mono-ADP-ribosyltransferase, has emerged as a key player in cancer, with its overexpression linked to aggressive B-cell lymphomas and metastatic prostate cancer, positioning it as a promising therapeutic target. This study aimed to identify novel PARP14 inhibitors by repurposing existing compounds for anticancer applications via a ligand-based computational strategy. Using advanced techniques for 3D quantitative structure-activity relationship and pharmacophore modeling, we created a reliable pharmacophore model (Hypo1) via a varied dataset of 60 confirmed PARP14 inhibitors for accuracy. The evaluation of more than 71,540 compounds from the DrugBank and IBScreen libraries through virtual screening, followed by molecular docking studies, resulted in the assessment of these compounds against Veber's and Lipinski's drug-like criteria and optimal ADMET properties. This process identified four promising candidates: Furosemide, Vilazodone, STOCK1N-42868, and STOCK1N-92908. Molecular dynamics simulations and MM-PBSA analysis provided additional evidence of the stability and positive interactions of these ligands with PARP14. Furosemide and Vilazodone exhibited significant binding affinity and anticancer properties, whereas STOCK1N-42868 emerged as a novel candidate with promising in silico results. These findings suggest that Furosemide and Vilazodone could be effectively repurposed as PARP14 inhibitors, offering a strategic approach to enhance the efficacy of cancer treatment, whereas STOCK1N-42868 represents an exciting avenue for further research. This study emphasizes the possible applications of computational methods for finding new drugs and stresses the importance of pre-clinical research to examine how these inhibitors work in cancer treatment.

BACKGROUND:Early detection of HIV-1 infection is essential for initiating antiretroviral therapy (ART) to suppress viremia and prevent disease progression. Timely diagnosis, especially in infants, is critical as rapid antibody-based serology tests are ineffective due to the presence of maternal antibodies. METHODS:We developed a CRISPR/Cas12a-based HIV-1 detection assay by optimizing components for coupled isothermal preamplification using recombinase polymerase amplification (RPA). The assay targeted the conserved region in the pol gene specific to HIV-1 with the designed CRISPR RNA (crRNA). CRISPR/Cas12a-mediated cleavage of viral cDNA was visualized through the collateral cleavage of a single-stranded DNA-FAM-BQ reporter, enabling rapid and visually detectable outcomes. The performance of the assay was evaluated using plasma from 41 HIV-1 Clade C (HIV-1C) seropositive individuals, including 28 HIV-1C infected infant samples, HIV-1 Indian Clade C and Clade B genome plasmids, viral disease control DNA/RNA samples (Influenza, RSV, Parvovirus, HPIV, CMV, and HBV), and 31 healthy donor plasma samples. Sensitivity and specificity were assessed, and detection was performed using fluorescence, visual readout, and lateral flow dipsticks. RESULTS:The CRISPR/Cas12a-based HIV-1 Clade C detection assay achieved a sensitivity of 96 % and a specificity of 92.65 %. The assay successfully provided results through both fluorescence and visual readouts and was compatible with lateral flow dipstick formats, facilitating easy and rapid detection. CONCLUSIONS:The developed CRISPR/Cas12a-based HIV-1C detection assay demonstrates high sensitivity and specificity for Clade C, indicating its potential as a robust point-of-care molecular diagnostic tool for HIV-1C. Additionally, it may serve as a rapid nucleic acid test alternative for detecting mother-to-child transmission of HIV-1C in infants under two years of age, where traditional antibody-based tests are ineffective. This assay holds promise for improving early HIV-1 diagnosis and timely initiation of ART, ultimately contributing to better disease management and outcomes.

Background Transmission of the delta variant resulted in a surge of SARS-CoV-2 cases in New Delhi, India, during the early half of the year 2021. Healthcare workers (HCWs) received vaccines on priority for the prevention of infection. We estimated the effectiveness of the BBV152 vaccine among HCWs against SARS-CoV-2 infection, hospitalization, or death. Methods This retrospective cohort study was done at a multi-speciality tertiary care public-funded hospital in New Delhi, India. 12 237 HCWs participated in the study. The intervention was the BBV152 whole virion inactivated vaccine (Covaxin, Bharat Biotech Limited, Hyderabad, administered two doses four weeks apart). The outcome measures were vaccine effectiveness against any SARS-CoV-2 infection, symptomatic infection, or hospitalization or death. Results The mean (SD) age of HCWs was 36 (11) years, 66% were men, and 16% had comorbid conditions. After adjusting for potential covariates—age, sex, health worker type category, body mass index, and comorbid conditions, the vaccine effectiveness (95% confidence interval) in fully vaccinated HCWs and >14 days after receipt of the second dose was 44% (37 to 51, p<0.001) against sympto-matic infection, hospitalization or death due to SARS-CoV-2, and 61% (37 to 76, p<0.001) against hospitalization or death, respectively. The partial dose was not effective. Conclusion The BBV152 vaccine, with complete two doses, offered a modest response to SARS-CoV-2 infection in real-life situations against a backdrop of high delta variant community transmission.

Immune evasion is one of the hallmarks of cancers, including glioblastoma, the most aggressive form of primary brain tumors. Multiple mechanisms are employed by tumor cells and its microenvironment to evade immune detection and foster tumor growth and progression. The secretion of immunosuppressive molecules such as transforming growth factor-β (TGF-β) and interleukin-10 (IL-10), the expression of checkpoint proteins such programmed death-ligand 1 (PD-L1), and the recruitment of T-regulatory cells (Tregs) and myeloid-derived suppressor cells (MDSCs) in the tumor microenvironment (TME) leads to suppressed immune cell activity, favoring unchecked tumor growth. The FAT atypical cadherin 1 (FAT1) has shown context/tissue-dependent effects in cancers of different tissue origins, with either oncogenic or tumor suppressor roles. Our laboratory has reported FAT1 to have an oncogenic function in glioblastoma. In addition, FAT1 promotes an immunosuppressive microenvironment in glioblastoma, reducing T-cell and monocyte infiltration while increasing immunosuppressive cells such as MDSCs. It also upregulates pro-inflammatory mediators [cyclooxygenase-2 (COX-2), interleukin-1β (IL-1β), and interleukin-6 (IL-6)], fostering tumor-promoting signaling. This dual role in immune evasion and pro-tumorigenic inflammatory processes makes FAT1 a key driver of glioblastoma progression. This highlights the potential of FAT1 as a compelling therapeutic target. This article provides a concise overview of immune tolerance mechanisms in glioblastoma, and the crucial role of FAT1 in promoting immune tolerance and tumor advancement. In addition, this review highlights currently available immunotherapies in clinical use or undergoing trials, and the potential of FAT1 as a promising target for combinatorial therapeutic interventions.

The rise of drug resistance in Plasmodium falciparum, rendering current treatments ineffective, has hindered efforts to eliminate malaria. To address this issue, the study employed a combination of Systems Biology approach and a structure-based pharmacophore method to identify a target against P. falciparum. Through text mining, 448 genes were extracted, and it was discovered that plasmepsins, found in the Plasmodium genus, play a crucial role in the parasite's survival. The metabolic pathways of these proteins were determined using the PlasmoDB genomic database and recreated using CellDesigner 4.4.2. To identify a potent target, Plasmepsin V (PF13_0133) was selected and examined for protein-protein interactions (PPIs) using the STRING Database. Topological analysis and global-based methods identified PF13_0133 as having the highest centrality. Moreover, the static protein knockout PPIs demonstrated the essentiality of PF13_0133 in the modeled network. Due to the unavailability of the protein’s crystal structure, it was modeled and subjected to a molecular dynamics simulation study. The structure-based pharmacophore modeling utilized the modeled PF13_0133 (PfPMV), generating 10 pharmacophore hypotheses with a library of active and inactive compounds against PfPMV. Through virtual screening, two potential candidates, hesperidin and rutin, were identified as potential drugs which may be repurposed as potential anti-malarial agents.

Neuroblastoma is the most common extra-cranial solid tumor diagnosed mostly in children below the age of five years and comprises of about 15% of all paediatric cancer deaths. Tumor initiating cancer stem cells (CSCs) can be targeted for better treatment approaches. BASP1-AS1 is a long non coding (Lnc) RNA that is a divergent LncRNA for its coding gene brain abundant membrane attached signal protein 1 (BASP1). We had earlier demonstrated it to be expressed in foetus derived human neural progenitor cells (hNPCs), where it was a positive regulator of BASP1 and was critical for neural differentiation. In this study, we have investigated the role of BASP1-AS1 in CSCs derived from the human neuroblastoma cell line SH-SY5Y. We cultured SH-SY5Y cells on Poly-D-Lysine coated flasks in serum free media supplemented with growth factors, which led to the enrichment of CSCs as determined by marker expression. When grown on ultra-low attachment flasks, these cells formed CSCs enriched neurospheres. We examined the effects of BASP1-AS1 siRNA mediated knockdown on CSCs enriched SH-SY5Y cells and SH-SY5Y derived neurospheres. BASP1-AS1 knockdown decreased the levels of the corresponding gene BASP1 and the rate of cell proliferation of CSCs enriched cells along with low expression of Ki67. It also reduced the mRNA levels of stem cell and pluripotency gene markers (CD133, CD44, c-KIT, SOX2, OCT4 and NANOG), as also Wnt 2 and the Wnt pathway effector β catenin. It also abrogated the formation of neurospheres in ultra-low attachment flasks. A similar effect on proliferation and stemness related properties was seen on BASP1 knockdown. BASP1-AS1 and its related pathways may provide a point of intervention for the CSCs population in neuroblastoma.

Oligodendrocytes (OL) are the myelinating cells of the central nervous system that mediate nerve conduction. Loss of oligodendrocytes results in demyelination, triggering neurological deficits. Developing a better understanding of the cell signaling pathways influencing OL development may aid in the development of therapeutic strategies. The primary focus of this study was to investigate and elucidate the cell signaling pathways implicated in the developmental maturation of oligodendrocytes using human fetal neural stem cells (hFNSCs)–derived primary OL and MO3.13 cell line. Successful differentiation into OL was established by examining morphological changes, increased expression of mature OL markers MBP, MOG and decreased expression of pre-OL markers CSPG4 and O4. Analyzing transcriptional datasets (using RNA sequencing) in pre-OL and mature OL derived from hFNSCs revealed the novel and critical involvement of the JAK-STAT cell signaling pathway in terminal OL maturation. The finding was validated in MO3.13 cell line whose differentiation was accompanied by upregulation of IL-6 and the transcription factor STAT3. Increased phosphorylated STAT3 (pY705) levels were demonstrated by western blotting in hFNSCs-derived primary OL as well as terminal maturation in MO3.13 cells, thus validating the involvement of the JAK-STAT pathway in OL maturation. Pharmacological suppression of STAT3 phosphorylation (confirmed by western blotting) was able to prevent the increase of MBP-positive cells as demonstrated by flow cytometry. These novel findings highlight the involvement of the JAK-STAT pathway in OL maturation and raise the possibility of using this as a therapeutic strategy in demyelinating diseases.

STAT1 (Signal Transducer and Activator of Transcription 1), belongs to the STAT protein family, essential for cytokine signaling. Ithas been reported to have either context dependent oncogenic or tumor suppressor roles in different tumors. Earlier, we demonstrated that Glioblastoma multiforme (GBMs) overexpressing FAT1, an atypical cadherin, had poorer outcomes. Overexpressed FAT1 promotes pro-tumorigenic inflammation, migration/invasion by downregulating tumor suppressor gene, PDCD4. Here, we demonstrate that STAT1 is a novel mediator downstream to FAT1, in downregulating PDCD4 in GBMs. In-silico analysis of GBM databases as well as q-PCR analysis in resected GBM tumors showed positive correlation between STAT1 and FAT1 mRNA levels. Kaplan-Meier analysis showed poorer survival of GBM patients having high FAT1 and STAT1 expression. SiRNA-mediated knockdown of FAT1 decreased STAT1 and increased PDCD4 expression in glioblastoma cells (LN229 and U87MG). Knockdown of STAT1 alone resulted in increased PDCD4 expression. In silico analysis of the PDCD4 promoter revealed four putative STAT1 binding sites (Site1-Site4). ChIP assay confirmed the binding of STAT1 to site1. ChIP-PCR revealed decrease in the binding of STAT1 on the PDCD4 promoter after FAT1 knockdown. Site directed mutagenesis of Site1 resulted in increased PDCD4 luciferase activity, substantiating STAT1 mediated PDCD4 inhibition. EMSA confirmed STAT1 binding to the Site 1 sequence. STAT1 knockdown led to decreased expression of pro-inflammatory cytokines and EMT markers, and reduced migration/invasion of GBM cells. This study therefore identifies STAT1 as a novel downstream mediator of FAT1, promoting pro-tumorigenic activity in GBM, by suppressing PDCD4 expression.