Enigma protein, encoded by the PDLIM7 gene, is overexpressed in thyroid cancer in a stage-dependent manner, suggesting a potential involvement in the initiation and progression of thyroid cancer. The Enigma interacts with several cellular pathways, including PI3K/AKT, MDM2, and BMP-1. The Enigma is regulated by microRNAs. Specifically, we showed that the Enigma protein upregulation corresponds to the downregulation of Let-7 family genes. There is limited research on the interactions and regulation of the Enigma with other proteins/genes in thyroid cancer tissues, indicating a gap in current knowledge. Our aim is to establish the Enigma as a biomarker. We also aim to study the interacting partners of the Enigma signaling pathways and their probable miRNA regulation in thyroid cancer progression. Using Western blotting, densitometric analysis, immunoprecipitation (IP), and reverse IP, we detected the protein expression and protein–protein interactions in the corresponding papillary thyroid carcinomas (PTCs). Utilizing real-time qPCR assay and Pearson’s correlation test, we highlighted the correlation between PDLIM7 and Let-7g gene expression in the same tissues. The results showed the differential upregulations of the Enigma protein in different stages of PTCs compared to benign tissues along with AKT, VDR, BMP-1, and MDM2 proteins. Loss of DBP was observed in a subset of PTCs. Strong interactions of the Enigma with PI3K/AKT and MDM2 were noted, along with a weaker BMP-1 interaction. Pearson’s correlation coefficient analysis between PDLIM7 and let-7g gene expression was significant (p < 0.05); however, there was a weak inverse correlation (r = −0.27). The study suggests the potential utility of the PDLIM7-qPCR assay as a biomarker for thyroid cancer. The Enigma’s interactions with key signaling pathways may provide valuable insights into the development of thyroid cancer. The study contributes to understanding the molecular mechanisms involving the Enigma protein in thyroid cancer and highlights its potential as a biomarker.

Background: Ovarian cancer (OC) is the second most common gynecologic malignancy in the United States and remains the leading cause of death among cancers of the female reproductive system. Alarmingly, mortality rates have risen disproportionately among women of African ancestry compared to those of European or Asian descent. Identifying microRNA (miRNA) signatures that contribute to these disparities may enhance prognostic accuracy and inform personalized therapeutic strategies. Methods: In this study, we identified prognostic markers of overall survival in serous ovarian cancer (SOC) using data from The Cancer Genome Atlas (TCGA) and the Human Protein Atlas. Integrative bioinformatic analyses revealed three key prognostic genes—TIMP3 (Tissue Inhibitor of Metalloproteinases-3), BRAF (v-raf murine sarcoma viral oncogene homolog B), and ITGB1 (Integrin Beta-1)—as critical molecular determinants associated with survival in patients with SOC. Candidate miRNAs regulating these genes were predicted using TargetScanHuman v8.0, identifying a core regulatory set comprising miR-192, miR-30d, miR-16-5p, miR-143-3p, and miR-20a-5p. To validate their clinical relevance, formalin-fixed, paraffin-embedded (FFPE) and fresh SOC tumor samples were obtained from African American and Caucasian patients who underwent surgery at Loma Linda University (LLU) between 2010 and 2023. Results and Discussion: Among all these, ITGB1 (p = 0.00033), TIMP3 (p = 0.0035), and BRAF (p = 0.026) emerged as statistically significant predictors. Following total RNA extraction, cDNA synthesis, and quantitative reverse transcription PCR (qRT-PCR), the expression levels of these miRNAs and their target genes were quantified. In the LLU cohort, ITGB1 and TIMP3 were significantly upregulated in African American patients compared to Caucasian patients (p < 0.01 and p < 0.02, respectively). Among the miRNAs, miR-192-5p was particularly noteworthy, showing marginally differential expression in LLU samples (p = 0.0712) but strong statistical significance in the TCGA cohort (p = 0.00013), where elevated expression correlated with poorer overall survival (p = 0.021). Pathway enrichment and gene ontology analyses (miRTargetLink2.0, Enrichr) revealed interconnected regulatory networks linking miR-192, miR-16-5p, miR-143-3p, and miR-20a-5p to ITGB1; miR-143-3p/miR-145-5p to BRAF; and miR-16-5p and miR-30c/d to TIMP3. Conclusions: Collectively, these findings identify distinct miRNA–mRNA regulatory signatures—particularly the miR-192-5p–ITGB1/TIMP3 axis—as potential clinically relevant biomarkers that may contribute to racial disparities and disease progression in ovarian cancer.

Ovarian cancer (OC) is the second most common gynecologic malignancy in the U.S. and the leading cause of death among cancers of the female reproductive system. Notably, mortality rates have disproportionately increased among women of African ancestry compared to those of Asian or European descent. Identifying microRNA (miRNA) signatures linked to these racial disparities may improve prognostic tools and guide personalized treatment. In this study, we first identified key prognostic markers for overall survival in serous ovarian cancer (SOC) from TCGA via the Human Protein Atlas, including ITGB1 (p=0.00033), TIMP3 (p=0.0035), and BRAF (p=0.026). Using TargetScanHuman v8.0, we predicted miRNAs targeting these genes and selected those commonly associated: miR-192, miR-30d, hsa-miR-16-5p, miR-143-3p, and miR-20a-5p. Formalin-fixed, paraffin-embedded (FFPE), and fresh SOC tissue samples from African American and Caucasian patients were collected post-surgery at Loma Linda University (2010–2023). Total RNA was extracted, followed by cDNA synthesis and qRT-PCR to assess miRNA expression. Expression data from LLU were then correlated with clinicopathologic data from TCGA (n=445). miR-192-5p emerged as the most significant, showing marginal differential expression in LLU samples (p=0.0712) and a significant correlation with survival in TCGA (p=0.021). Further pathway enrichment and gene ontology analyses using miRTargetLink2.0 and Enrichr linked miR-192, miR-16-5p, miR-143-3p, and miR-20a-5p to ITGB1; miR-143-3p/miR-145-5p to BRAF; and miR-16-5p and miR-30c/d to TIMP3. These findings suggest miRNA signatures, particularly miR-192-5p, may have clinical relevance in addressing racial disparities in OC prognosis and therapy.