Personalized and Precision Medicine Journal

Abstract Background: Breast cancer is the most common malignancy among women in Iran, characterized by a relatively early age of onset and a rising incidence rate. The single-nucleotide polymorphisms rs2981582 and rs1219648, located in intron 2 of the FGFR2 gene, have been linked to breast cancer susceptibility in genome-wide association studies (GWAS). Nevertheless, their significance in the Iranian population has not been extensively investigated.
This study investigates the association of FGFR2 polymorphisms (rs2981582 and rs1219648) with breast cancer risk in Iranian women, alongside haplotype interactions and gene expression profiling.
Methods: A case-control study was conducted with 160 participants (80 cases and 80 age-matched controls). FGFR2 SNPs were genotyped with PCR-RFLP. Chi-square tests were used to analyze associations of haplotypes. FGFR2 expression was evaluated in breast cancer subtypes using GEO (GDS2635, GDS3853) and Expression Atlas datasets. Statistical analyses were carried out using SPSS version 22.0 (IBM Corp., Armonk, NY, USA), with statistical significance defined as P<0.05. Hardy–Weinberg equilibrium (HWE) was verified for both SNPs in the control group (P>0.05).
Results: The TT genotype of rs2981582 was significantly associated with increased breast cancer risk (P=0.00; OR=3.566). No independent association was found for rs1219648 (P>0.05). Haplotypes AC and AT were significantly associated with elevated risk (P=0.004 and P=0.001, respectively). FGFR2 expression was upregulated in lobular carcinoma and downregulated in ductal carcinoma compared to healthy controls (P<0.05).
Conclusion: The rs2981582 TT genotype and specific haplotypes (AC, AT) are associated with increased breast cancer risk in Iranian women, supporting FGFR2 as a potential biomarker for early detection and personalized risk assessment in this population.

Abstract Objective: To investigate the relationship between changes in the level of Pituitary hormones, cholesterol levels, and the expression of genes involved in the biosynthesis of androgens, this study was designed.
Methods: In this study, the amount of changes in the levels of LH, FSH, and PRL hormones, as well as the level of cholesterol as a precursor of androgens, LDL and HDL lipoproteins, and the expression level of two genes, CYP17A1 and CYP11A1, in 120 people with prostate cancer as a case group and 120 people with BPH as a control group by RT-qPCR.
Results: The statistical analysis demonstrated that serum levels of testosterone, LH, and TSH were significantly higher in the malignant group compared to the benign group. PRL levels were also elevated in the Prostate cancer (PCa) group; however, this difference did not reach statistical significance. No significant difference was observed in serum PSA levels between the two groups. Prostate volume was significantly greater in the benign group than in the malignant group. Serum cholesterol levels were significantly higher in the PCa group compared to the Benign prostatic hyperplasia (BPH) group. In contrast, serum levels of LDL and HDL lipoproteins showed no significant differences between the groups. Additionally, the expression levels of CYP11A1 and CYP17A1 genes were significantly increased in the PCa group relative to the BPH group.
Conclusion: The results of this study showed that monitoring the hormonal profile and cholesterol level can play an important role in predicting the course of the disease.

Abstract Rheumatoid arthritis (RA) is an irreversible systemic autoimmune disorder. The advancement of the illness results in joint deformity and associated functional impairment, which profoundly impacts the standard of life of those affected. This review offers an overview of rheumatoid arthritis (RA), including a broad introduction to the illness, its epidemiology, associated risks, and pathogenesis. It also emphasizes advancements in fundamental research and the many mechanisms of signaling and molecular processes, including genetic variables. Summary of previous studies: In recent decades, researchers have garnered more interest in rheumatoid arthritis. Aberrant signaling pathways in rheumatoid arthritis (RA) constitute a significant area of study for identifying and treating the condition, offering crucial insights for comprehending this complex illness and formulating relevant therapies. The etiology of rheumatoid arthritis is associated with several signaling pathways. Research has repeatedly examined the etiology of rheumatoid arthritis (RA), revealing that both environmental and genetic variables play significant roles in its onset. Additionally, several research indicates that the susceptibility and severity of rheumatoid arthritis (RA) may correlate with the HLA-DRB1 variant, which exhibits the most significant genetic relationship with RA.

Abstract The human gut microbiome constitutes a highly diverse and unique ecosystem that plays a critical role in shaping host metabolism, immune function, and vulnerability to numerous diseases. Thanks to recent breakthroughs in high-throughput sequencing, shotgun metagenomics, and integrative multi-omics strategies, researchers can now achieve comprehensive profiling of microbial communities with strain-level precision and detailed functional insights. Specific microbial patterns have emerged as reliable predictive biomarkers for assessing disease risk, tracking progression, and determining treatment outcomes in various conditions, including metabolic syndrome, inflammatory bowel disease, autoimmune disorders, and cancer. By combining microbiome data with host genomics, metabolomics, and clinical metrics, precision medicine is enhanced, facilitating tailored interventions such as dietary changes, probiotics, prebiotics, and fecal microbiota transplantation. Sophisticated bioinformatics tools, alongside machine learning and artificial intelligence, streamline the analysis of complex, high-dimensional multi-omics data, helping to pinpoint crucial microbial taxa, functional pathways, and predictive markers. Nevertheless, significant hurdles persist regarding the standardization of sample collection, sequencing protocols, bioinformatic workflows, and reproducibility across different study cohorts. Additionally, ethical issues such as data privacy, informed consent, and fair access require careful attention. Future studies that integrate longitudinal multi-omics profiling, mechanistic investigations of host microbe interactions, and robust clinical validation of microbial biomarkers are expected to propel microbiome-driven personalized medicine forward. Ultimately, a thorough characterization of the gut microbiome offers a revolutionary approach to proactive, patient-centric healthcare, shifting focus from general population-based models to precise, individualized strategies for prevention, diagnosis, and therapy.

Abstract Gestational diabetes mellitus (GDM) is a prevalent complication of pregnancy associated with adverse outcomes for both mother and fetus. Epigenetic modifications, particularly DNA methylation, may play a significant role in its pathogenesis. This study aimed to evaluate the expression and methylation status of IGF2, PPARγ, LEP, and CDKN1C in women with GDM. In this case control study, 50 women with GDM and 50 healthy pregnant women were included. Gene expression levels and DNA methylation patterns were analyzed, and clinical risk factors were assessed. Significant differences were identified in both expression and methylation profiles of the studied genes between GDM patients and controls. Pre-pregnancy BMI, high-fat diet, and family history of diabetes were significantly associated with GDM. These results indicate that GDM is influenced by metabolic, environmental, and epigenetic factors, and that altered expression and methylation of IGF2, PPARγ, LEP, and CDKN1C may contribute to its development.

Abstract Background: Glioblastoma multiforme (GBM) is the most lethal primary brain tumor. GBM exhibits rapid growth and invasiveness along with a nadir prognosis. Epithelial–mesenchymal transition (EMT), combined with activated Wnt/β-catenin signaling, contributes to GBM progression and associated therapy resistance. Pentagalloylglucose (PGG), a polyphenolic compound from nature, has been shown to be anticancer in multiple cancers by inhibiting proliferation, migration, and EMT. The objectives are to demonstrate the effects of PGG on GBM cells and examine the modulation of EMT and the Wnt/β-catenin pathway.
Methods: U87-MG cells were treated with PGG (0.5–40 µM) for 24, 48, and 72 hours. Cell viability was assessed using the MTT assay. The expression levels of epithelial–mesenchymal transition (EMT) markers, including E-cadherin, N-cadherin, Vimentin, Snail, Slug, as well as β-catenin, were quantified by qRT-PCR. Cell migration was evaluated using a wound healing assay. Statistical analysis was performed using one-way ANOVA followed by Tukey’s post hoc test.
Results: PGG demonstrated a marked reduction in cell viability in a dose- and duration-dependent manner with IC₅₀ values at 18.4, 12.7, and 8.9 µM at 24, 48, and 72 hours, respectively. The upregulation of E-cadherin and downregulation of N-cadherin, Vimentin, and the Snail protein show that mesenchymal markers are being transcriptionally silenced. It was also a striking loss of β-catenin expression, which suggests Wnt/β-catenin suppression. Wound healing assay showed that PGG treatment resulted in a marked reduction of cell migration.
Conclusion: PGG significantly inhibits the progression of GBM by inhibiting EMT and downregulating the Wnt/β-catenin signaling pathways. Overall, PGG has potential as a natural, low-toxicity therapeutic or combinatory drug for glioblastoma, and future studies in vivo and in human trials will be needed to reaffirm this conclusion.