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Ayesha Akter

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Open access Sep 2026

Comprehensive Pan-Cancer Analysis Reveals the Prognostic, Molecular, and Immunological Significance of EPS8

Background Epidermal Growth Factor Receptor Pathway Substrate 8 (EPS8) is believed to function as a tumor driver; however, to understand its molecular characteristics across tumors, a comprehensive pan-cancer analysis of EPS8 is lacking. Objective This study aimed to investigate the prognostic, molecular, and immunological significance of EPS8 across multiple human cancers. Methods Comprehensive analyses were conducted using GEPIA2, UALCAN, TIMER2.0, cBioPortal, SMART, GSCA, Enrichr, and the TCGAplot R package to evaluate survival prognosis, gene expression, DNA methylation, immune infiltration, proteomic expression, tumor mutational burden (TMB), microsatellite instability (MSI), genetic alterations, drug sensitivity, and enriched pathways. Results EPS8 overexpression in LGG (p = 7.2 × 10−5) and PAAD (p = 9.4 × 10−6) was significantly associated with poor overall survival and disease-free survival. Amplification was the most common genetic alteration, with alteration frequencies approaching 6% in TGCT and UCEC. In KIRC and PAAD, EPS8 expression correlated with tumor stage. Immune infiltration analysis revealed significant associations between EPS8 expression and immune cells. EPS8 expression also showed significant correlations with both TMB and MSI in STAD and ESCA. Enrichment analysis indicated an association between EPS8 and regulation of the actin cytoskeleton and similar pathways. Conclusion These findings suggest that EPS8 has prognostic and immunological significance across multiple cancer types and may serve as a potential biomarker. The observed associations with immune-related features and drug response provide a basis for future experimental studies to evaluate its role in cancer biology and its potential relevance to immunotherapy.

Adiba Juoairia, Ayesha Akter, Rawaz Jahan Nima et al. · 0 citations
Open access Jul 2026

RNAi-based therapeutics targeting the F gene in human metapneumovirus: An in-silico approach

Background: Human metapneumovirus (HMPV) is a major cause of acute respiratory tract infections, particularly in young children, older adults, and immunocompromised individuals. Despite its significant clinical burden, no approved antiviral therapies or vaccines are currently available. This study aimed to identify potential RNA interference (RNAi)-based therapeutic candidates targeting the highly conserved fusion (F) gene of HMPV. Methods: An in silico pipeline was employed to design and evaluate small interfering RNA (siRNA) candidates targeting the HMPV F gene. A total of 869 siRNA sequences were initially generated using siDirect 2.1 software, which were sequentially filtered to 34 and then to 10 candidates based on sequence characteristics and predicted silencing efficiency. Molecular docking was performed to assess interactions between selected siRNAs and the human Argonaute-2 (AGO2) protein, followed by 100-ns molecular dynamics simulations to evaluate structural stability. Principal component analysis and free-energy landscape analyses were also performed. Results: Three siRNA candidates (F11, F19, and F26) demonstrated favorable RNAi characteristics, including high predicted silencing efficiency and strong target binding. Among them, F11 exhibited the highest sequence conservation across global HMPV strains, the highest melting temperature, favorable AGO2 interaction, and stable dynamic behavior. Principal component analysis indicated that F11 sampled the most constrained conformational subspace, which had a well-defined low-energy basin, thereby identifying it as the most promising candidate. Conclusions: This study identified F11 as the most promising siRNA candidate targeting the highly conserved HMPV fusion (F) gene, demonstrating strong potential as an RNAi-based therapeutic agent according to computational analyses. However, further in vitro and in vivo validation is required to confirm its efficacy and safety.

Proshanto Ghosh, Md. Nur Islam, Shahriar Hossain et al. · 0 citations

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