Potential of miR-181a-5p and miR-630 as clinical biomarkers in NSCLC.

BACKGROUND: The development of drug resistance and high mortality rates are the major problems observed in non-small cell lung cancer (NSCLC). Biomarkers indicating and predicting disease development towards these unfavorable directions are therefore on high demand. Many studies have demonstrated that changes in miRNAs expression may be associated with a response to treatment and disease prognosis, thus suggesting its potential biomarker value for a broad spectrum of clinical applications. The aim of the present study was to investigate the expression level of miR-181a-5p, miR-630, and its targets in NSCLC tumor tissue and plasma samples; and to analyze its association with NSCLC patient's response to treatment and disease prognosis. METHODS: The study was performed in 89 paired tissue specimens and plasma samples obtained from NSCLC patients who underwent surgical treatment at the Department of Thoracic Surgery and Oncology of the National Cancer Institute. Analysis of miR-181a-5p and miR-630 expression was performed by qRT-PCR using TaqMan miRNA specific primers. Whereas BCL2, LMO3, PTEN, SNAI2, WIF1 expression levels were identified with KAPA SYBR FAST qPCR Kit. Each sample was examined in triplicate and calculated following the 2-ΔΔCt method. When the p-value was less than 0.05, the differences were considered statistically significant. RESULTS: It was found that miR-181a-5p and miR-630 expression levels in NSCLC tissue and plasma samples were significantly decreased compared with control samples. Moreover, patients with low miR-181a-5p expression in tumor tissue and plasma had longer PFS rates than those with high miRNA expression. Decreased miR-630 expression in tumor was statistically significantly associated with better NSCLC patients' OS. In addition, the expression of miR-181a-5p, as well as miR-630 in tumor tissue, are the statistically significant variables for NSCLC patients' OS. Moreover, in NSCLC patient plasma samples circulating miR-181a-5p can be evaluated as significant independent prognostic factors for OS and PFS. CONCLUSIONS: Our findings indicate the miR-181a-5p and miR-630 expression levels have the potential to prognose and predict and therefore improve the treatment individualization and the outcome of NSCLC patients. Circulating miR-181a-5p has the potential clinical value as a non-invasive biomarker for NSCLC.

Detection of Oncogene Hotspot Mutations in Female NSCLC Tumor DNA and Cell-Free DNA.

Non-small-cell lung cancer (NSCLC) is the most prevalent type of lung cancer, with extensively characterized mutational spectra. Several biomarkers (such as EGFR, BRAF, KRAS gene mutations, etc.) have emerged as predictive and prognostic markers for NSCLC. Unfortunately, the quality of the available tumor biopsy and/or cytology material is not always adequate to perform the necessary molecular testing, prompting the search for alternatives. Cell-free DNA (cfDNA) found in plasma is emerging as a highly promising avenue or a supplementary method for assessing the efficacy of cancer treatments. This is especially valuable in instances where conventional biopsy specimens, like formalin-fixed, paraffin-embedded (FFPE), or freshly frozen tumor tissues prove inadequate for conducting molecular pathology analyses subsequent to the initial diagnostic procedures. By leveraging cfDNA from plasma, clinicians gain an additional tool to gauge the effectiveness of cancer therapies, thereby enhancing their ability to optimize tailored treatment strategies. In this study, 51 Lithuanian females with NSCLC were analyzed, with adenocarcinoma being the predominant pathology diagnosis in 40 cases (78%). Target mutations were identified in 38 out of 51 patients (74.5%) in tumor tissue samples, while in plasma samples, they were identified in only 10 patients' samples (19.6%). Even though we did not have enough voluminous plasma samples in our study, gene mutations were detected in plasma from ten women, three of whom were diagnosed with early stages of lung cancer (stages I and II). For these patients, the following mutations were detected: deletion in exon 19 of the EGFR gene and single nucleotide polymorphisms in the TP53 and MET genes. All other women were diagnosed with stages III or IV of lung cancer. This indicates that the later stages of cancer contribute more cfDNA in plasma, making extraction less complicated.

Prostate Health Index and Prostate Health Index Density as Diagnostic Tools for Improved Prostate Cancer Detection.

BACKGROUND: To evaluate the diagnostic potential of [-2] proPSA (p2PSA), %p2PSA, Prostate Health Index (phi), and phi density (PHID) as independent biomarkers and in composition of multivariable models in predicting high-grade prostatic intraepithelial neoplasia (HGPIN) and overall and clinically significant prostate cancer (PCa). METHODS: 210 males scheduled for prostate biopsy with total PSA (tPSA) range 2-10 ng/mL and normal digital rectal examination were enrolled in the prospective study. Blood samples to measure tPSA, free PSA (fPSA), and p2PSA were collected immediately before 12-core prostate biopsy. Clinically significant PCa definition was based on Epstein's criteria or ISUP grade ≥ 2 at biopsy. RESULTS: PCa has been diagnosed in 112 (53.3%) patients. Epstein significant and ISUP grade ≥ 2 PCa have been identified in 81 (72.3%) and 40 (35.7%) patients, respectively. Isolated HGPIN at biopsy have been identified in 24 (11.4%) patients. Higher p2PSA and its derivative mean values were associated with PCa. At 90% sensitivity, PHID with cut-off value of 0.54 have demonstrated the highest sensitivity of 35.7% for overall PCa detection, so PHID and phi with cut-off values of 33.2 and 0.63 have demonstrated the specificity of 34.7% and 34.1% for ISUP grade ≥ 2 PCa detection at biopsy, respectively. In univariate ROC analysis, PHID with AUC of 0.77 and 0.80 was the most accurate predictor of overall and Epstein significant PCa, respectively, so phi with AUC of 0.77 was the most accurate predictor of ISUP grade ≥ 2 PCa at biopsy. In multivariate logistic regression analysis, phi improved diagnostic accuracy of multivariable models by 5% in predicting ISUP grade ≥ 2 PCa. CONCLUSIONS: PHID and phi have shown the greatest specificity at 90% sensitivity in predicting overall and clinically significant PCa and would lead to significantly avoid unnecessary biopsies. PHID is the most accurate predictor of overall and Epstein significant PCa, so phi is the most accurate predictor of ISUP grade ≥ 2 PCa. phi significantly improves the diagnostic accuracy of multivariable models in predicting ISUP grade ≥ 2 PCa.

[Expression of matrix metalloproteinases in patients with malignant tumors]. / Matrikso metaloproteinazes sergant piktybiniais navikais.

The cancer cells secrete proteolytic enzymes, which are important in the tumor spreading. The cells must cross basement membrane and extracellular matrix barriers in order to spread. The matrix metalloproteinases are a family of endopeptidases, which enzymatic activity depends on the presence of zinc ion in the catalytic domain. Matrix metalloproteinases hydrolyze extracellular matrix components such as collagen, laminin, fibronectin, proteoglycans and contribute to the spreading of tumor cells by eliminating the surrounding extracellular matrix and basement membrane barriers. This review describes matrix metalloproteinases family classification and structure, their role under physiological conditions and induced proteolysis during pathological processes. There is a balance between proteolytic extracellular matrix degradation and proteolysis inhibition, but under pathological state (e. g. tumor development) the proteolysis becomes uncontrolled. We review tissue inhibitors of matrix metalloproteinases and synthetic matrix metalloproteinase inhibitors, their perspective in cancer treatment; as well as different matrix metalloproteinases expression in patients with tumors and its prognostic significance during cancer progression.