Ribonucleotide reductase regulatory subunit M2 (RRM2) as a potential sero-diagnostic biomarker in non-small cell lung cancer.

ObjectivesNon-small cell lung cancer (NSCLC) is a major cause of cancer-related death worldwide. Most cases are diagnosed at an advanced stage using current tumor markers. Here, we aimed to identify potential novel potential biomarkers for NSCLC.Material/methodsFour independent datasets from the Gene Expression Omnibus database were analyzed. The relative expression of ribonucleotide reductase regulatory subunit M2 (RRM2) mRNA in 30 paired of NSCLC paired tissues was measured by reverse transcription quantitative PCR. Serum levels of cytokeratin fragment 21-1 (CYFRA21-1), pro-gastrin-releasing peptide (ProGRP), carcinoembryonic antigen (CEA), and neuron-specific enolase (NSE) were measured using electrochemiluminescence immunoassays, and serum RRM2 levels were evaluated by an enzyme-linked immunosorbent assay.ResultsThe mRNA expression level of RRM2 was significantly increased in most NSCLC lesions compared to para-adjacent tissues. Serum RRM2 levels in NSCLC patients were significantly elevated compared to healthy controls and were also associated with distant metastasis and histological type, but not with tumor size or lymph node metastasis. Receiver operating characteristic curve analysis showed a higher diagnostic ratio for NSCLC using RRM2 alone compared to other traditional tumor markers.ConclusionsRRM2 is a potential sero-diagnostic biomarker for NSCLC

Identification of NUF2 and FAM83D as potential biomarkers in triple-negative breast cancer

Background Breast cancer is a heterogeneous disease. Compared with other subtypes of breast cancer, triple-negative breast cancer (TNBC) is easy to metastasize and has a short survival time, less choice of treatment options. Here, we aimed to identify the potential biomarkers to TNBC diagnosis and prognosis. Material/Methods Three independent data sets (GSE45827, GSE38959, GSE65194) were downloaded from the Gene Expression Omnibus (GEO). The R software packages were used to integrate the gene profiles and identify differentially expressed genes (DEGs). A variety of bioinformatics tools were used to explore the hub genes, including the DAVID database, STRING database and Cytoscape software. Reverse transcription quantitative PCR (RT-qPCR) was used to verify the hub genes in 14 pairs of TNBC paired tissues. Results In this study, we screened out 161 DEGs between 222 non-TNBC and 126 TNBC samples, of which 105 genes were up-regulated and 56 were down-regulated. These DEGs were enriched for 27 GO terms and two pathways. GO analysis enriched mainly in “cell division”, “chromosome, centromeric region” and “microtubule motor activity”. KEGG pathway analysis enriched mostly in “Cell cycle” and “Oocyte meiosis”. PPI network was constructed and then 10 top hub genes were screened. According to the analysis results of the Kaplan-Meier survival curve, the expression levels of only NUF2, FAM83D and CENPH were associated with the recurrence-free survival in TNBC samples (P < 0.05). RT-qPCR confirmed that the expression levels of NUF2 and FAM83D in TNBC tissues were indeed up-regulated significantly. Conclusions The comprehensive analysis showed that NUF2 and FAM83D could be used as potential biomarkers for diagnosis and prognosis of TNBC