Study of microRNAs-21/221 as potential breast cancer biomarkers in Egyptian women

microRNAs (miRNAs) play an important role in cancer prognosis. They are small molecules, approximately 17–25 nucleotides in length, and their high stability in human serum supports their use as novel diagnostic biomarkers of cancer and other pathological conditions. In this study, we analyzed the expression patterns of miR-21 and miR-221 in the serum from a total of 100 Egyptian female subjects with breast cancer, fibroadenoma, and healthy control subjects. Using microarray-based expression profiling followed by real-time polymerase chain reaction validation, we compared the levels of the two circulating miRNAs in the serum of patients with breast cancer (n = 50), fibroadenoma (n = 25), and healthy controls (n = 25). The miRNA SNORD68 was chosen as the housekeeping endogenous control. We found that the serum levels of miR-21 and miR-221 were significantly overexpressed in breast cancer patients compared to normal controls and fibroadenoma patients. Receiver Operating Characteristic (ROC) curve analysis revealed that miR-21 has greater potential in discriminating between breast cancer patients and the control group, while miR-221 has greater potential in discriminating between breast cancer and fibroadenoma patients. Classification models using k-Nearest Neighbor (kNN), Naïve Bayes (NB), and Random Forests (RF) were developed using expression levels of both miR-21 and miR-221. Best classification performance was achieved by NB Classification models, reaching 91% of correct classification. Furthermore, relative miR-221 expression was associated with histological tumor grades. Therefore, it may be concluded that both miR-21 and miR-221 can be used to differentiate between breast cancer patients and healthy controls, but that the diagnostic accuracy of serum miR-21 is superior to miR-221 for breast cancer prediction. miR-221 has more diagnostic power in discriminating between breast cancer and fibroadenoma patients. The overexpression of miR-221 has been associated with the breast cancer grade. We also demonstrated that the combined expression of miR-21 and miR-221can be successfully applied as breast cancer biomarkers

Single Nucleotide Polymorphism in SMAD7 and CHI3L1 and Colorectal Cancer Risk

Colorectal cancer (CRC) is one of the leading cancers throughout the world. It represents the third most common cancer and the fourth in mortality. Most of CRC are sporadic, arise with no known high-penetrant genetic variation and with no previous family history. The etiology of sporadic CRC is considered to be multifactorial and arises from the interaction of genetic variants of low-penetrant genes and environmental risk factors. The most common well-studied genetic variation is single nucleotide polymorphisms (SNPs). SNP arises as a point mutation. If the frequency of the sequence variation reaches 1% or more in the population, it is referred to as polymorphism, but if it is lower than 1%, the allele is typically considered as a mutation. Lots of SNPs have been associated with CRC development and progression, for example, genes of TGF-β1 and CHI3L1 pathways. TGF-β1 is a pleiotropic cytokine with a dual role in cancer development and progression. TGF-β1 mediates its actions through canonical and noncanonical pathways. The most important negative regulatory protein for TGF-β1 activity is termed SMAD7. The production of TGF-β can be controlled by another protein called YKL-40. YKL-40 is a glycoprotein with an important role in cancer initiation and metastasis. YKL-40 is encoded by the CHI3L1 gene. The aim of the present review is to give a brief introduction of CRC, SNP, and examples of some SNPs that have been documented to be associated with CRC. We also discuss two important signaling pathways TGF-β1 and CHI3L1 that influence the incidence and progression of CRC

Serum Long Non-Coding RNAs PVT1, HOTAIR, and NEAT1 as Potential Biomarkers in Egyptian Women with Breast Cancer

Long non-coding RNAs play an important role in tumor growth, angiogenesis, and metastasis in several types of cancer. However, the clinical significance of using lncRNAs as biomarkers for breast cancer diagnosis and prognosis is still poorly investigated. In this study, we analyzed the serum expression levels of lncRNAs PVT1, HOTAIR, NEAT1, and MALAT1, and their associated proteins, PAI-1, and OPN, in breast cancer patients compared to fibroadenoma patients and healthy subjects. Using quantitative real-time PCR (qRT-PCR), we compared the serum expression levels of the four circulating lncRNAs in patients with breast cancer (n = 50), fibroadenoma (n = 25), and healthy controls (n = 25). The serum levels of PAI-1 and OPN were measured using ELISA. Receiveroperating-characteristic (ROC) analysis and multivariate logistic regression were used to evaluate the diagnostic value of the selected parameters. The serum levels of HOTAIR, PAI-1, and OPN were significantly higher in breast cancer patients compared to controls and fibroadenoma patients. The serum level of PVT1 was significantly higher in breast cancer patients than in the controls, while that of NEAT1 was significantly lower in breast cancer patients compared to controls and fibroadenoma patients. Both ROC and multivariate logistic regression analyses revealed that PAI-1 has the greatest power in discriminating breast cancer from the control, whereas HOTAIR, PAI-1, and OPN have the greatest power in discriminating breast cancer from fibroadenoma patients. In conclusion, our data suggest that the serum levels of PVT1, HOTAIR, NEAT1, PAI-1, and OPN could serve as promising diagnostic biomarkers for breast cancer