Anaplastic thyroid carcinoma (ATC) is the rarest and most aggressive form of thyroid cancer, marked by a poor prognosis and resistance to conventional treatments. Like many malignancies, ATC has a complex genetic landscape, with numerous mutations driving tumor initiation, progression, and therapeutic resistance. However, recent advances in molecular research have expanded our understanding of these genetic alterations, paving the way for new targeted treatment strategies. Currently, therapies targeting specific genetic mutations, such as BRAF and MEK, show promise, but their effectiveness is limited to patients harboring these mutations. To explore broader therapeutic possibilities, we conducted a comprehensive literature review using the PubMed database and Google to identify studies on key genetic mutations in ATC. By leveraging these molecular insights, we aim to highlight potential therapeutic avenues that could enhance treatment options and improve patient outcomes.

Ovarian cancer is the deadliest gynecologic cancer, mainly because it is often diagnosed late and resists standard treatments. The tumor microenvironment (TME) plays a major role in disease progression and therapy failure. Two key components of the TME, cancer-associated fibroblasts (CAFs) and tumor-associated macrophages (TAMs), create conditions that facilitate tumor growth and immune evasion. CAFs are highly diverse and originate from sources like fibroblasts and stem cells. They support cancer by remodeling the extracellular matrix, promoting angiogenesis, and releasing cytokines and growth factors that aid tumor survival. TAMs, which are usually in an M2 state, also promote metastasis and suppress immune responses by secreting immunosuppressive molecules. Together, CAFs and TAMs interact with cancer cells to activate pathways such as the TGF-β, IL-6, and PI3K/AKT pathways, which drive resistance to therapy. New treatments aim to block these interactions by targeting CAFs and TAMs through depletion, reprogramming, or pathway inhibition, often combined with immunotherapy. Advances such as single-cell sequencing and spatial transcriptomics now enable more precise identification of CAF and TAM subtypes, enabling more targeted therapies. This review summarizes their roles in epithelial ovarian cancer and explores how targeting these cells could improve outcomes.

Papillary thyroid cancer (PTC) is the most common thyroid malignancy, with significant racial/ethnic disparities in incidence and survival. Asians have the highest incidence, and recurrence, while African Americans experience the lowest survival rates, suggesting contributions from genetic, environmental, and healthcare-related factors. While socioeconomic disparities play a role, emerging evidence highlights genetic and molecular mechanisms underlying these differences. This study examines differentially expressed genes (DEGs) to identify potential molecular drivers of PTC disparities. Bulk RNA-sequencing (RNA-seq) data from 20 PTC tumors (5 White, 5 African American, 5 Hispanic, and 5 Asian) were analyzed using the UseGalaxy platform. Preprocessing included quality control, adapter trimming, and genome alignment. Differential expression analysis identified genes with p < 0.01 and fold change ≥ 2.5. Volcano plots visualized significant DEGs. Gene Set Enrichment Analysis (GSEA) via eVITTA identified enriched pathways. TCGA data analysis validated racial/ethnic differences in gene expression. Ethnic groups exhibited distinct gene expression profiles. GSEA revealed differences in cell proliferation, immune regulation, and thyroid hormone metabolism. African Americans showed immune suppression and reduced tumor suppressor activity, while Asians exhibited enriched cell cycle and DNA repair pathways. Significant differences were confirmed in some of the genes in TCGA data analysis. This study identifies genetic factors contributing to racial disparities in PTC, emphasizing the need for further validation in larger cohorts and functional studies. Understanding these molecular differences may inform personalized treatment strategies and improve PTC outcomes across diverse populations.

Anaplastic thyroid carcinoma (ATC) is the rarest and most aggressive form of thyroid cancer, marked by a poor prognosis and resistance to conventional treatments. Like many malignancies, ATC has a complex genetic landscape, with numerous mutations driving tumor initiation, progression, and therapeutic resistance. However, recent advances in molecular research have expanded our understanding of these genetic alterations, paving the way for new targeted treatment strategies. Currently, therapies targeting specific genetic mutations, such as BRAF and MEK, show promise, but their effectiveness is limited to patients harboring these mutations. To explore broader therapeutic possibilities, we conducted a comprehensive literature review using the PubMed database and Google to identify studies on key genetic mutations in ATC. By leveraging these molecular insights, we aim to highlight potential therapeutic avenues that could enhance treatment options and improve patient outcomes.

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.