Comprehensive multiomics and in silico approach uncovers prognostic, immunological, and therapeutic roles of ANLN in lung adenocarcinoma.

The anillin actin-binding protein (ANLN) is immensely overexpressed in cancers, including lung cancer (LC). Phytocompounds have gained interest due to their broader potential and reduced unwanted effects. Screening numerous compounds presents a challenge, but in silico molecular docking is pragmatic. The present study aims to identify the role of ANLN in lung adenocarcinoma (LUAD), along with identification and interaction analysis of anticancer and ANLN inhibitory phytocompounds followed by molecular dynamics (MD) simulation. Using a systematic approach, we found that ANLN is significantly overexpressed in LUAD and mutated with a frequency of 3.73%. It is linked with advanced stages, clinicopathological parameters, worsening of relapse-free survival (RFS), and overall survival (OS), pinpointing its oncogenic and prognostic potential. High-throughput screening and molecular docking of phytocompounds revealed that kaempferol (flavonoid aglycone) interacts strongly with the active site of ANLN protein via hydrogen bonds, Vander Waals interactions, and acts as a potent inhibitor. Furthermore, we discovered that ANLN expression was found to be significantly higher (p) in LC cells compared to normal cells. This is a propitious and first study to demonstrate ANLN and kaempferol interactions, which might eventually lead to removal of rout from cell cycle regulation posed by ANLN overexpression and allow it to resume normal processes of proliferation. Overall, this approach suggested a plausible biomarker role of ANLN and the combination of molecular docking subsequently led to the identification of contemporary phytocompounds, bearing symbolic anticancer effects. The findings would be advantageous for pharmaceutics but require validation using in vitro and in vivo methods. HIGHLIGHTS: • ANLN is significantly overexpressed in LUAD. • ANLN is implicated in the infiltration of TAMs and altering plasticity of TME. • Kaempferol (potential ANLN inhibitor) shows important interactions with ANLN which could remove the alterations in cell cycle regulation, imposed by ANLN overexpression eventually leading to normal process of cell proliferation.

Potential plasma microRNAs signature miR-190b-5p, miR-215-5p and miR-527 as non-invasive biomarkers for prostate cancer.

BackgroundProstate cancer (PCa) is the most prevalent (20%) pathological cancer among males globally. MicroRNAs (miRNAs) are short (19-22 nucleotide), conserved, noncoding molecules that regulate post-transcriptional processes either by repressing or degrading mRNA or by translation inhibition binding to complementary sites on mRNA. The goal of this study was to find out whether differentially expressed microRNA (DEM) could be used as a potential marker in the prognosis and diagnosis of PCa.MethodologyThe miRNAs profiling was done both from plasma and tissue samples of the same PCa patient (n = 3) by real-time quantitative PCR (qRT-PCR) and compared with BPH (benign prostatic hyperplasia) patients (n = 3) as controls and further validation of selected miRNAs.ResultsWe found 55 significant overexpressed DEMs, 44 significant underexpressed DEMs in plasma and 6 significant overexpressed DEMs, 27 significant underexpressed DEMs in tissue compared between PCa and BPH. Furthermore, there were eight miRNAs namely miR-190b, miR-215, miR-300, miR-329, miR-504, miR-525-3p, miR-527, miR-548a-3p found to be significantly differentially expressed in plasma and tissue samples via profiling, however only three showed concordant expression. After validation, miR-190b-5p were shown to be significantly downexpressed with fold changes of 0.4177 (p value - 0.0072) and 0.7264 (p value - 0.0143) in plasma and tissue samples, respectively. The expression of miR-215-5p was shown to be significantly overexpressed with fold change of 1.820 (p - 0.0016) and 1.476 (p - 0.0407) in plasma and tissue samples, respectively. Furthermore, miR-527 was shown to be significantly downexpressed with fold changes of 0.6018 (p - 0.0095) and 0.6917 (p - 0.0155) in plasma and tissue samples, respectively.ConclusionAccording to our findings, plasma miR-190b-5p, miR-215-5p, miR-527 levels alteration is consistently linked with PCa tissue. For establishing significant miRNAs as biomarkers, additional research of a larger population is needed.

MicroRNA-183-5p: A New Potential Marker for Prostate Cancer.

The microRNA (miR)-183-5p is expressed at high level in the majority of cancer. The purpose of present study was to investigate the role of oncogenic miR-183-5p in prostate cancer (PCa) as biomarker. We carried out our experiment in 50 prostate cancer patients and 40 patients of benign prostatic hyperplasia (BPH) and 40 adjacent controls tissue. The expression of miR-183-5p was evaluated through reverse transcription qualitative polymerase chain reaction. We found that the expression of miR-183-5p in PCa tissue was significantly up regulated as compared to BPH patients and adjacent normal tissues as control. Additionally, miR-183 expression was correlated with higher prostate-specific antigen, higher Gleason Score and metastatic condition. A receiver operating characteristic curve analysis revealed that miR-183-5p distinguished PCa patients from BPH patients and also from control. In conclusion, our data suggest that oncogenic miR-183-5p may be useful as a new tissue specific diagnostic biomarker in prostate cancer.

Integrated grade-wise profiling analysis reveals potential plasma miR-373-3p as prognostic indicator in Prostate Cancer & its target KPNA2.

Background: Plasma microRNAs (miRNAs) have recently garnered attention for their potential as stable biomarkers in the context of Prostate Cancer (PCa), demonstrating established associations with tumor grade, biochemical recurrence (BCR), and metastasis. This study seeks to assess the utility of plasma miRNAs as prognostic indicators for distinguishing between high-grade and low-grade PCa, and to explore their involvement in PCa pathogenesis. Methodology: We conducted miRNA profiling in both plasma and tissue specimens from patients with varying PCa grades. Subsequently, the identified miRNAs were validated in a substantial independent PCa cohort. Furthermore, we identified and confirmed the gene targets of these selected miRNAs through Western blot analysis. Results: In our plasma profiling investigation, we identified 98, 132, and 154 differentially expressed miRNAs (DEMs) in high-grade PCa vs. benign prostatic hyperplasia (BPH), low-grade PCa vs. BPH, and high-grade PCa vs. low-grade PCa, respectively. Our tissue profiling study revealed 111, 132, and 257 statistically significant DEMs for the same comparisons. Notably, miR-373-3p emerged as the sole consistently dysregulated miRNA in both plasma and tissue samples of PCa. This miRNA displayed significant overexpression in plasma and tissue samples, with fold changes of 3.584 ± 0.5638 and 8.796 ± 1.245, respectively. Furthermore, we observed a significant reduction in KPNA2 protein expression in PCa. Conclusion: Our findings lend support to the potential of plasma miR-373-3p as a valuable biomarker for predicting and diagnosing PCa. Additionally, this miRNA may contribute to the progression of PCa by inhibiting KPNA2 expression, shedding light on its role in the disease.

Incorporating Technology Adoption in Medical Education: A Qualitative Study of Medical Students' Perspectives.

Introduction: The integration of technology into medical education has witnessed significant growth in recent years, with tools such as virtual reality, artificial intelligence, and telemedicine gaining prominence. These tool in medical education, offering immersive, experiential learning experiences. Methods: We approached medical students currently enrolled in medical education programs and who are familiar with and actively use AI in medical education. Initially, we invited 21 random students to participate in the study; however, only 13 agreed to interviews. Some students cited their busy exam schedules as the reason for not participating. The participants were informed of the objective of the study before the commencement of the recorded interviews. Semi-structured interviews were used to guide the record interviews. Audio recordings were transcribed and analyzed using Atlas.ti, a qualitative data analysis software. Results: Participants exhibited a diverse range of perceptions and levels of awareness regarding VR, AI, and telemedicine technologies. Learning with virtual reality was considered to be fun, memorable, inclusive, and engaging by participants. The use of virtual reality technology is seen as complementing current teaching and learning approaches, helping to build learners' confidence, as well as providing medical students with a safe environment for problem-solving and trial-and-error learning. The students reported that AI was seen as a potential game-changer in the healthcare sector. Participants hoped that telemedicine would provide healthcare services to remote and underserved populations. Conclusion: The study conducted focus group discussions with medical students and residents in Saudi Arabia to explore their views on integrating VR, AI, and telemedicine in medical education and practice. Their insights highlight the need for informed decision-making and strategic development to optimize the benefits and address challenges like initial investments, technical issues, ethics, and regulations. These considerations are crucial for fully realizing the potential benefits of technology in medical education globally.

Emerging role of miRNA in prostate cancer: A future era of diagnostic and therapeutics.

Prostate cancer (PCa) is the most common cancer in men (20%) and is responsible for 6.8% (1/5) of all cancer-related deaths in men around the world. The development and spread of prostate cancer are driven by a wide variety of genomic changes and extensive epigenetic events. Because of this, the MicroRNA (miRNA) and associated molecular mechanisms involved in PCa genesis and aggressive were only partially identified until today. The miRNAs are a newly discovered category of regulatorsthat have recently been recognized to have a significant role in regulating numerous elements of cancer mechanisms, such as proliferation, differentiation, metabolism, and apoptosis. The miRNAs are a type of small (22-24 nucleotides), non-coding, endogenous, single-stranded RNA and work as potent gene regulators. Various types of cancer, including PCa, have found evidence that miRNA genes, which are often located in cancer-related genetic regions or fragile locations, have a role in the primary steps of tumorigenesis, either as oncogenes or tumorsuppressors. To explain the link between miRNAs and their function in the initiation and advancement of PCa, we conducted a preliminary assessment. The purpose of this research was to enhance our understanding of the connection between miRNA expression profiles and PCa by elucidating the fundamental processes of miRNA expression and the target genes.

Combined Multiomics and In Silico Approach Uncovers PRKAR1A as a Putative Therapeutic Target in Multi-Organ Dysfunction Syndrome.

Despite all epidemiological, clinical, and experimental research efforts, therapeutic concepts in sepsis and sepsis-induced multi-organ dysfunction syndrome (MODS) remain limited and unsatisfactory. Currently, gene expression data sets are widely utilized to discover new biomarkers and therapeutic targets in diseases. In the present study, we analyzed MODS expression profiles (comprising 13 sepsis and 8 control samples) retrieved from NCBI-GEO and found 359 differentially expressed genes (DEGs), among which 170 were downregulated and 189 were upregulated. Next, we employed the weighted gene co-expression network analysis (WGCNA) to establish a MODS-associated gene co-expression network (weighted) and identified representative module genes having an elevated correlation with age. Based on the results, a turquoise module was picked as our hub module. Further, we constructed the PPI network comprising 35 hub module DEGs. The DEGs involved in the highest-confidence PPI network were utilized for collecting pathway and gene ontology (GO) terms using various libraries. Nucleotide di- and triphosphate biosynthesis and interconversion was the most significant pathway. Also, 3 DEGs within our PPI network were involved in the top 5 significantly enriched ontology terms, with hypercortisolism being the most significant term. PRKAR1A was the overlapping gene between top 5 significant pathways and GO terms, respectively. PRKAR1A was considered as a therapeutic target in MODS, and 2992 ligands were screened for binding with PRKAR1A. Among these ligands, 3 molecules based on CDOCKER score (molecular dynamics simulated-based score, which allows us to rank the binding poses according to their quality and to identify the best pose for each system) and crucial interaction with human PRKAR1A coding protein and protein kinase-cyclic nucleotide binding domains (PKA RI alpha CNB-B domain) via active site binding residues, viz. Val283, Val302, Gln304, Val315, Ile327, Ala336, Ala337, Val339, Tyr373, and Asn374, were considered as lead molecules.

Identification of Potential Key Genes in Prostate Cancer with Gene Expression, Pivotal Pathways and Regulatory Networks Analysis Using Integrated Bioinformatics Methods.

Prostate cancer (PCa) is the most prevalent cancer (20%) in males and is accountable for a fifth (6.8%) cancer-related deaths in males globally. Smoking, obesity, race/ethnicity, diet, age, chemicals and radiation exposure, sexually transmitted diseases, etc. are among the most common risk factors for PCa. However, the basic change at the molecular level is the manifested confirmation of PCa. Thus, this study aims to evaluate the molecular signature for PCa in comparison to benign prostatic hyperplasia (BPH). Additionally, representation of differentially expressed genes (DEGs) are conducted with the help of some bioinformatics tools like DAVID, STRING, GEPIA, Cytoscape. The gene expression profile for the four data sets GSE55945, GSE104749, GSE46602, and GSE32571 was downloaded from NCBI, Gene Expression Omnibus (GEO). For the extracted DEGs, different types of analysis including functional and pathway enrichment analysis, protein-protein interaction (PPI) network construction, survival analysis and transcription factor (TF) prediction were conducted. We obtained 633 most significant upregulated genes and 1219 downregulated genes, and a sum total of 1852 DEGs were found from all four datasets after assessment. The key genes, including EGFR, MYC, VEGFA, and PTEN, are targeted by TF such as AR, Sp1, TP53, NF-KB1, STAT3, RELA. Moreover, miR-21-5p also found significantly associated with all the four key genes. Further, The Cancer Genome Atlas data (TCGA) independent database was used for validation of key genes EGFR, MYC, VEGFA, PTEN expression in prostate adenocarcinoma. All four key genes were found to be significantly correlated with overall survival in PCa. Therefore, the therapeutic target may be determined by the information of these key gene's findings for the diagnosis, prognosis and treatment of PCa.

Evaluation of miR-711 as Novel Biomarker in Prostate Cancer Progression

Objective: MicroRNAs (miRs) are class of small non-coding regulatory RNA aberrantly expressed in various types of malignancies including prostate cancer and serves as potential targets to develop new diagnostic and therapeutic strategies. In this quiet we investigated miRNAs expression profile in benign prostatic hyperplasia (BPH) and prostate cancer (PCa) tissue samples and correlated their expression with clinicopathological parameters. Methodology: The miRNAs expression profile as well as their validation has been done by using Microarray and RT-PCR, respectively. Additionally, we also tried to speculate microRNA-mRNA regulatory module through computational target predictions by using Targetscan, Miranda and MirWalk and obtained results were analysed through DAVID software. Result: We observed that miR-711 is significantly deregulated in BPH and PCa, compared to controls. The lower expression of miR-711 was found to be significantly associated with high Gleason score and metastatic disease. Furthermore, the computational target prediction analysis explored miR-711 association to various cancer cells signalling cascade key molecules associated with cancer cell survival.Conclusion: From our observations we suggest that miR-711 may play a critical role in PCa progression, regulation of various cancer cell survival signalling cascades and that it may be a valuable biomarker for prediction of metastatic disease and poor prognosis in PCa.

Association of MTHFR (C677T) Gene Polymorphism With Breast Cancer in North India.

BACKGROUND: Breast cancer is one of the most common malignancies in women and is associated with a variety of risk factors. The functional single-nucleotide polymorphism (SNP) C677T in the gene encoding 5,10-methylenetetrahydrofolate reductase (MTHFR) may lead to decreased enzyme activity and affect the chemosensitivity of tumor cells. This study was designed to investigate the association of MTHFR gene polymorphism (SNP) in the pathogenesis of breast cancer among the North Indian women population. MATERIALS AND METHODS: Genotyping was performed by polymerase chain reaction (PCR) using genomic DNA, extracted from the peripheral blood of subjects with (275 cases) or without (275 controls) breast cancer. Restriction fragment length polymorphism was used to study C677T polymorphism in the study groups. RESULTS: The distribution of MTHFR (C677T) genotype frequencies, ie, CC, TT, and CT, among the patients was 64.7%, 2.18%, and 33.09%, respectively. In the healthy control group, the CC, TT, and CT frequencies were 78.91%, 1.09%, and 20.1%, respectively. The frequencies of C and T alleles were 81.2% and 18.7%, respectively, in the patient subjects, while they were 88.9% and 11.09%, respectively, among the healthy control group. Frequencies of the CT genotype and the T allele were significantly different (P = 0.007 and P = 0.005, respectively) between the control and the case subjects. CONCLUSION: This study shows an association of the CT genotype and the T allele of the MTHFR (C667T) gene with increased genetic risk for breast cancer among Indian women.