Background: Metastatic melanoma is an extremely aggressive malignancy with limited therapeutic options, despite advances in targeted and immunotherapy. MicroRNAs are key post-transcriptional regulators of gene expression and play a critical role in tumor adaptation, invasion, and metastasis. The aim of our study was to identify dysregulated miRNAs which may serve as novel biomarkers and therapeutic targets. Materials and Methods: The study was conducted on FFPE samples from metastatic melanoma (n = 15), compared to healthy skin tissue (n = 6). BRAF V600E/Ec mutation status was established by Real-Time qPCR. Expression miRNA analysis was performed, using digital counting of 827 miRNAs on the NanoString platform, with data normalization and fold change calculations. Results: Following normalization and quality control metrics, 58 differentially expressed miRNAs were identified in BRAFwt melanoma samples: 6 overexpressed and 52 inderexpressed miRNAs. In BRAFmut melanoma, 37 microRNAs were differentially expressed: 11 overexpressed and 26 underexpressed. Four miRNAs showed elevated expression in both melanoma groups. Among them, miR-146a-5p and miR-4286 demonstrated the highest elevation, especially in BRAFmut tumors. We focused further on their targeted genes. Conclusion: This study demonstrates significant alterations in the miRNA expression profile in metastatic melanoma and highlights the potential of miR-146a-5p and miR-4286 as key regulators of tumor biology.

Background : Recurrence after curative-intent surgery remains a major clinical challenge in non-small cell lung cancer (NSCLC). Conventional radiologic follow-up detects relapse only once macroscopic disease becomes evident, missing the minimal residual disease (MRD) window. Circulating tumor DNA (ctDNA), a tumor-derived fraction of total circulating cell-free DNA (cfDNA), has emerged as a sensitive biomarker for early MRD detection. This pilot study evaluates postoperative cfDNA dynamics as an accessible surrogate for MRD monitoring. Methods : Twelve patients with histologically confirmed NSCLC undergoing curative-intent resection were prospectively monitored at four time points: preoperatively ( T 0), postoperative day 10 ( T 1), 1 month ( T 2), and 3 months ( T 3). Blood samples were collected in Streck Cell-Free DNA BCT® tubes and processed using a double-centrifugation protocol. cfDNA was extracted using the Maelstrom Switch 8 automated system and quantified fluorometrically. Longitudinal cfDNA trends were correlated with TNM stage, adjuvant therapy, and survival outcome. Welch’s t -tests, ANOVA, and simple linear regression assessed associations between cfDNA levels and mortality. Results : Most patients (10/12; 83.3%) demonstrated a steady postoperative decline in cfDNA, consistent with molecular clearance. Two patients (16.7%) exhibited persistent or rising cfDNA and were the only patients who died during follow-up. At T 3, cfDNA levels were significantly higher in deceased vs. surviving patients (0.2821 vs. 0.2325 ng/µL, p = 0.029). Linear regression revealed a negative association between cfDNA at T 3 and survival probability ( β = –3.62, R ² = 0.18). Early postoperative cfDNA ( T 1– T 2) lacked prognostic value. Conclusion : Persistently elevated cfDNA levels at 3 months post-surgery were observed in patients with unfavorable outcomes; however, variability between individual trajectories was also present. These findings suggest that postoperative cfDNA dynamics may reflect underlying biological processes related to minimal residual disease, but given the small cohort size, they should be interpreted as hypothesis-generating. Larger prospective studies integrating mutation-specific ctDNA assays and time-to-event analyses are required to validate the potential clinical utility of cfDNA-based postoperative monitoring.

Background : KRAS (Kirsten rat sarcoma viral oncogene homolog) mutation testing is essential for therapeutic decision-making in colorectal cancer (CRC), as the presence of any activating KRAS variant predicts resistance to anti-epidermal growth factor receptor (anti-EGFR) therapy. Routine real-time PCR (qPCR) assays widely used in diagnostic laboratories typically exhibit limits of detection (LOD) around 1–5% variant allele frequency (VAF), making them prone to missing low-frequency or subclonal mutations. Droplet digital PCR (ddPCR) offers absolute quantification and significantly higher analytical sensitivity, enabling detection of variants below 1% VAF. Aim : To compare the analytical performance of ddPCR with qPCR for detecting KRAS hotspot mutations in FFPECRC tissue and determine whether ddPCR identifies additional clinically relevant low-frequency variants missed by qPCR. Methods : Fifty FFPECRC samples were genotyped using routine qPCR (easyPGX KRAS ) and subsequently re-tested using ddPCR (Droplex KRAS Mutation Detection Kit, Gencurix) on the Bio-Rad QX200 platform. Hotspot mutations across exons 2, 3, and 4 were assessed. ddPCR outputs (mutant/wild-type droplet counts and VAF) were analyzed using QuantaSoft Analysis Pro. Concordance, sensitivity, specificity, predictive values, Cohen’s κ, VAF distributions, and ROC/AUC analyses were performed. Discordant cases were evaluated for VAF relative to qPCRLOD. Results : qPCR detected KRAS mutations in 25/50 samples (50.0%), whereas ddPCR detected mutations in 31/50 samples (62.0%). ddPCR confirmed all 25 qPCR-positive cases and identified six additional mutations in qPCR wild-type samples. These ddPCR-only events exhibited VAF values between 0.9 and 2.3% (median 1.55%), consistently below the empirical qPCR detection threshold. Concordant qPCR+/ddPCR+ cases showed substantially higher VAF (18–55%, median 41.5%). ddPCR demonstrated 100% sensitivity, 76% specificity, 80.6% PPV, 100% NPV, and 88% overall accuracy versus qPCR, with Cohen’s κ = 0.76, indicating substantial agreement. ROC analysis based on ddPCR-derived VAF yielded AUC = 1.00, with an optimal discriminative threshold of ~18% VAF for qPCR positivity. Detected mutations reflected typical CRC epidemiology, with a predominance of exon 2 variants (G12x, G13D) and occasional exon 4 mutations (A146x). ddPCR also identified multiple subclonal co-existing mutations in several cases, not detectable by qPCR. Conclusion : ddPCR demonstrates superior analytical sensitivity for KRAS mutation detection in FFPECRC tissue and reliably identifies clinically meaningful low-frequency mutations missed by qPCR. Because any detectable KRAS mutation predicts lack of response to anti-EGFR therapy, failure to detect low-VAF subclones may adversely impact therapeutic selection. These results support incorporating ddPCR as a complementary reflex assay within RAS testing workflows, particularly for samples with low tumor purity, borderline amplification, or suspected intratumoral heterogeneity.