Prognosis of patients with colorectal cancer (CRC) is generally poor because of the lack of simple, convenient, and noninvasive tools for CRC detection at the early stage. The discovery of microRNAs (miRNAs) and their different expression profiles among different kinds of diseases has opened a new avenue for tumor diagnosis. We built a serum microRNA expression profile signature and tested its specificity and sensitivity as a biomarker in the diagnosis of CRC. We also studied its possible role in monitoring the progression of CRC. We conducted a two phase case-control test to identify serum miRNAs as biomarkers for CRC diagnosis. Using quantitative reverse transcription polymerase chain reactions, we tested ten candidate miRNAs in a training set (30 CRCs vs 30 controls). Risk score analysis was used to evaluate the diagnostic value of the serum miRNA profiling system. Other independent samples, including 83 CRCs and 59 controls, were used to validate the diagnostic model. In the training set, six serum miRNAs (miR-21, let-7g, miR-31, miR-92a, miR-181b, and miR-203) had significantly different expression levels between the CRCs and healthy controls. Risk score analysis demonstrated that the six-miRNA-based biomarker signature had high sensitivity and specificity for distinguishing the CRC samples from cancer-free controls. The areas under the receiver operating characteristic (ROC) curve of the six-miRNA signature profiles were 0.900 and 0.923 for the two sets of serum samples, respectively. However, for the same serum samples, the areas under the ROC curve used by the tumor markers carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9) were only 0.649 and 0.598, respectively. The expression levels of the six serum miRNAs were also correlated with CRC progression. Thus, the identified six-miRNA signature can be used as a noninvasive biomarker for the diagnosis of CRC, with relatively high sensitivity and specificity.

Purpose: With the advancement of minimally invasive surgery and catheters for hepatocellular carcinoma (HCC), it is becoming more and more inconvenient to get tissues or the tissues gained are insufficient for testing. Screening of blood-derived markers is of great significance for prognosis assessment. Patients and Methods: Data-independent acquisition (DIA) and parallel reaction monitoring (PRM) were implemented to identify valuable prognostic HCC biomarkers in 48 patients with different prognosis. The potential candidate biomarkers were examined in 205 HCC patients using enzyme-linked immunosorbent assay (ELISA) and then validated in The Cancer Genome Atlas (TCGA) HCC cohort. Results: DIA screened 86 significantly differentially regulated proteins between patients with poor prognosis and those with good prognosis. Eight proteins from the DIA proteomic analyses were quantified by PRM, and six of them (KLKB1, IGFBP3, SHBG, SAA1, C7, and CD44) presented consistent expression trends between DIA and PRM. Then, the results of ELISA indicated that KLKB1 was abnormally expressed in HCC patients, and the serum level of KLKB1 also exhibited significant changes before and after treatment (P = 0.016). Patients with higher KLKB1 serum levels had significantly superior overall survival (P = 0.035) and progression-free survival (P = 0.027) than those with lower KLKB1 expression. In the TCGA-HCC cohort, Cox regression analysis suggested that KLKB1 was an independent prognostic factor for overall survival (P = 0.032) of HCC patients. Conclusion: Aberrant expression of KLKB1 was strongly associated with the prognosis of HCC patients. KLKB1 may be used to evaluate the prognosis and guide the treatment for HCC.

Background: Anthracycline-induced liver injury (AILI) is one of the serious complications of anthracycline-based adjuvant chemotherapy for postoperative breast cancer patients. Exosomal miRNAs, as signaling molecules in intercellular communication, play the essential roles in drug-induced liver injury (DILI). However, the expression profiles of them in patients with AILI remains unknown. Methods: Seven post-chemotherapy patients were recruited in this study. After isolated plasma-derived exosomes, small RNA sequencing revealed exosomal miRNA profiles and differentially expressed miRNAs (DE-miRNAs) were identified between the liver injury group and non-liver injury group. miRTarBase and miRDB were used to predict the potential target genes of DE-miRNAs. DILI-related genes were downloaded from the CTD Database. The intersection of predicted genes and DILI-related genes were identified as the AILI-related target genes of the DE-miRNAs. GO annotation and KEGG pathway enrichment analysis were performed by the DAVID database. Furthermore, the protein-protein interaction (PPI) network was established by the STRING database and essential exosomal miRNAs were identified via Cytoscape software. Results: A total of 30 DE-miRNAs and 79 AILI-related target genes were identified. AILI-related target genes of the DE-miRNAs are significantly enriched in NOD-like receptor signaling pathway, the HIF-1 signaling pathway, and the FoxO signaling pathway. Then, the hub genes were screened and we discovered that IL-6 and SOD2 are the most critical genes that may be involved in the development of AILI through the activation of immune response and the occurrence of oxidative stress, respectively. In addition, we found that miR-1-3p could potentially regulate most of the hub genes in the miRNA-hub gene network. Conclusion: We explored the potential functions of DE-miRNAs and suggested exosomal miR-1-3p might be the essential exosomal miRNA in the pathogenesis of AILI. Moreover, our study provided an experimental basis for experimental verification to reveal the actual function and mechanism of miRNAs in AILI.

Background: S100A14 is a member of the S100 calcium‐binding protein family that exerts important phenotypic effects on cell proliferation, apoptosis, differentiation, and motility. However, the functional role and potential clinical significance of S100A14 in lung adenocarcinoma has not yet been clarified.Methods: We analyzed genomic alterations of S100A14 using The Cancer Genome Atlas lung adenocarcinoma genomic dataset. S100A14 displayed significant copy number amplification in lung adenocarcinoma. We detected S100A14 expression in lung adenocarcinoma and analyzed the correlation between S100A14 expression and clinicopathological characteristics.Results: Immunohistochemical analysis showed that S100A14 expression was obviously upregulated in lung adenocarcinoma tissues compared to matched normal counterparts. Statistical analysis revealed that S100A14 expression strongly correlated with poor differentiation, metastasis, stage, smoking, and EGFR mutation. Furthermore, our data indicated that S100A14 serum levels were higher in lung adenocarcinoma patients than healthy controls. Intriguingly, S100A14 serum levels were related to distant metastasis (P = 0.028). High S100A14 expression was significantly associated with overall (P = 0.0016) and post progression (P = 0.039) survival. In addition, we investigated the biological functions of S100A14 in lung adenocarcinoma cell lines. The results demonstrated that S100A14 promoted cell migration and invasion of SPCA1 and Glc‐82 cells.Conclusions: S100A14 increases the motility of lung adenocarcinoma cells, and might be a diagnostic and prognostic serum biomarker and potential therapeutic target for lung adenocarcinoma.

Background: We screened long non-coding RNAs (lncRNAs) specifically expressed in the serum of cervical squamous carcinoma (CESC) patient samples and investigated the role of these specific lncRNAs in the diagnosis of CESC and cervical intraepithelial neoplasia (CIN). Methods: The expression levels of the lncRNAs CCAT2, LINC01133, and LINC00511 in the serum of normal controls and patient with CESC and CIN were measured using reverse transcription–quantitative polymerase chain reaction (RT-qPCR). Next, we analyzed the correlation between the serum lncRNAs levels and the clinical characteristics of CESC. Thereafter, we estimated their combined diagnostic value by receiver operating characteristic (ROC) curve analysis. Results: The results showed that CCAT2, LINC01133, and LINC00511 were highly expressed in the serum of patients with CESC. When these lncRNAs and squamous cell carcinoma (SCC) antigen were combined, the area under the ROC curve (AUC) value reached 0.94. We also found that the AUC value of the diagnostic model combining CCAT2 and LINC01133 reached 0.894. Conclusion: The serum lncRNAs (CCAT2, LINC01133, and LINC00511) and SCC may be new non-invasive biomarkers for the diagnosis of CESC.