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Accumulating evidence supports a role for exosomal protein in diagnosis. The purpose of this study was to identify the tumor‐derived exosomal biomarkers in the serum that improve the diagnostic value in Chinese non‐small cell lung cancer (NSCLC) patients. Serum exosomes were isolated from healthy donors (n = 46) and NSCLC patients (n = 125) by ultracentrifugation and were characterized using transmission electron microscopy, qNano, and immunoblotting. Proteomic profiles (by mass spectrometry) revealed multiple differentially expressed proteins in the healthy and NSCLC groups. The exosomal expression levels of alpha‐2‐HS‐glycoprotein (AHSG) and extracellular matrix protein 1 (ECM1) increased significantly in the NSCLC patients compared to the healthy group. Alpha‐2‐HS‐glycoprotein showed diagnostic values with a maximum area under the receiver operating characteristic curve (AUC) as 0.736 for NSCLC vs healthy individuals (P < .0001) and 0.682 for early stage NSCLC vs healthy individuals (P < .01). Extracellular matrix protein 1 showed the diagnostic capacity with AUC values of 0.683 (P < .001) and 0.656 (P < .05) in cancer and early stage NSCLC compared to healthy individuals. When AHSG was combined with ECM1, the AUCs were 0.795 and 0.739 in NSCLC and early stage patients, respectively. Taken together, the combination of AHSG, ECM1, and carcinoembryonic antigen improved the diagnostic potential of NSCLC. The diagnosis values were AUC of 0.938 for NSCLC and 0.911 for early stage NSCLC vs healthy individuals. Our results suggest that novel proteomic signatures found in serum exosomes of NSCLC patients show potential usefulness as diagnostic tools. The combination of alpha‐2‐HS‐glycoprotein, extracellular matrix protein 1, and carcinoembryonic antigen improved the diagnostic potential of non‐small cell lung carcinoma (NSCLC). The diagnostic values were areas under the receiver operating characteristic curves of 0.938 for NSCLC and 0.911 for early stage NSCLC vs healthy individuals.

The present study aimed to investigate the overall changes in exosomal proteomes in metastatic and non‐metastatic non‐small‐cell lung cancers (NSCLC) and healthy human serum samples, and evaluate the potential of serum exosomal biomarkers to predict NSCLC metastasis. Tandem mass tags combined with multidimensional liquid chromatography and mass spectrometry analysis were used for screening the proteomic profiles of serum samples. Quantitative proteome, significant pathway, and functional categories of patients with metastatic and non‐metastatic NSCLC and healthy donors were investigated. In total, 552 proteins of the 628 protein groups identified were quantified. Bioinformatics analysis indicated that quantifiable proteins were mainly involved in multiple biological functions, metastasis‐related pathways. Moreover, lipopolysaccharide‐binding proteins (LBP) in the exosomes were found to be well distinguished between patients with metastatic and patients with non‐metastatic NSCLC. Area under the curve (AUC) was 0.803 with a sensitivity of 83.1% and a specificity of 67% (P < .0001). Circulating LBP were also well distinguishable between metastatic and non‐metastatic NSCLC, the AUC was 0.683 with a sensitivity of 79.5% and a specificity of 47.2% (P = .005). This novel study provided a reference proteome map for metastatic NSCLC. Patients with metastatic and non‐metastatic NSCLC differed in exosome‐related proteins in the serum. LBP might be promising and effective candidates of metastatic NSCLC. This is the first study using the proteomics technique to find a diagnostic marker for metastatic NSCLC. It provides an objective basis for the early diagnosis, early treatment and prognosis of metastatic NSCLC, and provides a key point for the diagnosis of other cancerous solid tumors. It also provides a new idea for non‐invasive biomarkers for other metastatic cancers, and the clinical application of exosomes will have better prospects.

Background To identify specific exosomal microRNAs (miRNAs) as serum biomarkers for prediction of metastasis in patients with colorectal cancer (CRC). Materials and Methods Serum exosomes were isolated from patients with metastatic CRC (n = 34) and non‐metastatic CRC (n = 108) by ultracentrifugation and characterized using transmission electron microscopy, qNano, and Western blot. Differential exosomal miRNAs were screened by sequencing and validated by qPCR in metastatic and non‐metastatic CRC patients. Results After sequence analysis, KEGG analysis showed that differential genes were associated with Rap1 signaling pathway and pathways in cancer, 6 upregulated exosomal miRNAs (miR‐224‐5p, miR‐548d‐5p, miR‐200a‐3p, miR‐320d, miR‐200b‐3p, and miR‐1246), and 3 downregulated exosomal miRNAs (novel_246, novel_301, and miR‐27a‐5p) were screened with fold change >1.5, among which miR‐320d was selected as the best candidate involved in CRC metastasis. Validation analysis revealed exosomal miR‐320d could significantly distinguish metastatic from non‐metastatic CRC patients (P = .019), with AUC of 0.633 for the diagnosis of patients with metastatic CRC. Besides, the combination of miR‐320d and CEA had an area under curve (AUC) of 0.804 for the diagnosis of patients with metastatic CRC. Conclusion Serum exosomal miR‐320d is a promising non‐invasive diagnostic biomarker for distinguishing metastatic from non‐metastatic CRC.

Background Emerging data point to the critical role of snoRNA in the emergence of different types of cancer, but scarcely in breast cancer (BC). This study aimed to clarify the differential expressions and potential diagnostic value of SNORD16, SNORA73B, SCARNA4, and SNORD49B in BC. Methods We screened differential snoRNAs in BC tissues and adjacent tissues through SNORic datasets, and then we further verified them in the plasma of BC patients and healthy volunteers by quantitative polymerase chain reaction (qPCR). Results These four snoRNAs: SNORD16, SNORA73B, SCARNA4, and SNORD49B were considerably more abundant in cancerous tissues than in neighboring tissues in the TCGA database. Their plasma levels were also higher in BC and early-stage BC patients when compared to healthy controls. Furthermore, the ROC curve demonstrated that BC (AUC = 0.7521) and early-stage BC (AUC = 0.7305) might be successfully distinguished from healthy people by SNORD16, SNORA73B, SCARNA4, and SNORD49B. Conclusion Plasma snoRNAs: SNORD16, SNORA73B, SCARNA4, and SNORD49B were upregulated in BC and early-stage BC and can be used as potential diagnostic markers for BC and early-stage BC.

Background: Colorectal cancer (CRC) is currently the fourth most common cancer worldwide. The roles of exosomal competing endogenous RNAs (ceRNAs) in CRC remain unclear. In this study, we constructed an exosomal ceRNA network to identify the core ceRNAs and investigate the diagnostic biomarkers in CRC. Methods and Patients: Serum exosomes were isolated from four CRC patients and two healthy donors by ultracentrifugation, and then subjected to RNA isolation, sequencing and microarray. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) analyses were performed to identify functional enrichment implications of differentially expressed exosomal mRNAs. TargetScan and miRanda were used for identifying the miRNA-mRNA and miRNA-LncRNA interactions. The predicted lncRNAs and mRNAs were intersected with the differentially expressed genes, for which the screening criterion was fold change >1.5 in the microarray. Differentially expressed exosomal miRNAs were identified in the GSE71008 dataset, and differentially expressed mRNAs (DEmRNAs) were further summarized from The Cancer Genome Atlas (TCGA) database. Results: A total of 1186 exosomal DEmRNAs, 2088 exosomal DElncRNAs and 29 exosomal miRNAs were detected in CRC patients compared to the healthy donors. Functional enrichment analysis suggested that exosomal DEmRNAs might participate in pathways related to carcinogenesis and development of cancer. An exosomal ceRNA regulatory network of CRC was constructed based on 40 lncRNAs, two miRNAs, and five mRNAs. Exosomal miR-150-5p and miR-10b-5p expression levels were increased in healthy donors compared with CRC patients in the GSE71008 dataset, and five DEmRNAs ( TOMM70A , RBM48 , BEND3 , RHOBTB1 , and ADAMTS2 ) were significantly upregulated in TCGA database. Two potential exosomal regulatory axes of lncRNA G016261-miR-150-5p- RBM48 and lncRNA XLOC_011677-miR-10b-5p- BEND3 were identified from the network. Conclusion: The current study revealed potential molecular biological regulation pathways and diagnostic biomarkers through the exosomal ceRNA regulatory network.

Background Colon cancer with liver metastases (CCLM) characterized by genetic heterogeneity is an evolutionary process leading to variations in response to selective pressure, but the underlying evolutionary models still remains unclear.Methods Total of 30 samples, including primary tumor and two to four matched liver metastases from 8 treatment-naïve patients with CCLM were collected, and subjected to whole-exome DNA sequencing. PyClone was used to calculate intra and inter-tumor heterogeneity, LICHeE was used to reconstruct the cancer phylogeny trees and investigate the subclonal composition.ResultsThe genetic differences were observed between primary and metastatic lesions, as well as among multiple metastases in all patients. The natural history models of colorectal cancer in each case were identified, including parallel, linear, and branching evolution. Liver metastases could originate from primary lesions or other metastases. Pathway and process enrichment analysis also showed obvious heterogeneity and enhancement of several molecular functions.ConclusionsOur data reveal the genetic and heterogeneity between primary and metastatic lesions, as well as among multiple metastases and provide genomic evidence for clonal heterogeneity for CCLM.

Identifying the primary site of metastatic cancer is critical to guiding the subsequent treatment. Approximately 3–9% of metastatic patients are diagnosed with cancer of unknown primary sites (CUP) even after a comprehensive diagnostic workup. However, a widely accepted molecular test is still not available. Here, we report a method that applies formalin-fixed, paraffin-embedded tissues to construct reduced representation bisulfite sequencing libraries (FFPE-RRBS). We then generate and systematically evaluate 28 molecular classifiers, built on four DNA methylation scoring methods and seven machine learning approaches, using the RRBS library dataset of 498 fresh-frozen tumor tissues from primary cancer patients. Among these classifiers, the be ta value-based li near support ve ctor (BELIVE) performs the best, achieving overall accuracies of 81-93% for identifying the primary sites in 215 metastatic patients using top-k predictions (k = 1, 2, 3). Coincidentally, BELIVE also successfully predicts the tissue of origin in 81-93% of CUP patients (n = 68). Molecular tests that can determine the tissue of origin of cancers of unknown primary (CUP) are still needed. Here, the authors develop a DNA methylation profiling assay and a machine learning classifier to predict the origin of metastatic tumours in CUP patients using formalin-fixed, paraffin embedded samples.

Background MicroRNAs are non-coding RNA molecules that posttranscriptionally regulate expression of target genes and have been implicated in the progress of cancer proliferation, differentiation and apoptosis. The aim of this study was to determine whether microRNA-21 (miR-21), a specific microRNA implicated in multiple aspects of carcinogenesis, impacts breast cancer invasion by regulating the tissue inhibitor of metalloproteinase 3 (TIMP3) gene. Methods miR-21 expression was investigated in 32 matched breast cancer and normal breast tissues, and in four human breast cancer cell lines, by Taqman quantitative real-time PCR. Cell invasive ability was determined by matrigel invasion assay in vitro, in cells transfected with miR-21 or anti-miR-21 oligonucleotides. In addition, the regulation of tissue inhibitor of metalloproteinase 3 (TIMP3) by miR-21 was evaluated by western blotting and luciferase assays. Results Of the 32 paired samples analyzed, 25 breast cancer tissues displayed overexpression of miR-21 in comparison with matched normal breast epithelium. Additionally, incidence of lymph node metastasis closely correlated with miR-21 expression, suggesting a role for miR-21 in metastasis. Similarly, each of the four breast cancer cell lines analyzed overexpressed miR-21, to varied levels. Further, cells transfected with miR-21 showed significantly increased matrigel invasion compared with control cells, whereas transfection with anti-miR-21 significantly decreased cell invasion. Evaluation of TIMP3 protein levels, a peptidase involved in extarcellular matrix degredation, inversely correlated with miR-21 expression. Conclusion As knockdown of miR-21 increased TIMP3 protein expression and luciferase reporter activity, our data suggests that miR-21 could promote invasion in breast cancer cells via its regulation of TIMP3.

Background Telomerase reverse transcriptase (TERT) is a catalytic subunit of telomerase and required for cancer development. This study aims to reveal its clinical utility for diagnosis and prognosis of resectable NSCLC. Methods TERT was quantitatively evaluated by the enzyme-linked immunosorbent assay (ELISA) from 69 patients before and after the surgery. The prognostic value was evaluated by disease-free survival (DFS) and overall survival (OS). Results Circulating TERT in NSCLC patients were significantly higher than that in the healthy group, possessing the AUC of 0.90. Importantly, TERT change between pre- and post- operation was significantly correlated with OS and DFS ( p  = 0.022, p  = 0.046 respectively), acted as the independent prognostic factors for DFS and OS, indicating it can serve as the promising diagnostic and prognostic biomarker for resectable non-small cell lung cancer (NSCLC). Conclusions TERT change between pre- and post- resection can serve as the promising biomarker for prognosis of resectable NSCLC.

Background Accumulating evidence has confirmed the role of snoRNAs in a variety of cancer, but rare in renal cell carcinoma (RCC). This study aims to clarify the role of snoRNAs in RCC tumorigenesis and their potential as novel tumor biomarkers. Materials and methods The snoRNA expression matrix was obtained from the public TCGA and SNORic databases. SNORD15A, SNORD35B and SNORD60 were selected and validated by qPCR, then analyzed combined with related clinical factors using T-test and ROC curve. Results All three snoRNAs: SNORD15A, SNORD35B and SNORD60 were significantly upregulated in cancer tissues compared to adjacent tissues from TCGA or FFPE detection. These three snoRNAs were also increased in urinary sediment (US) of RCC as well as the early-stage RCC patients compared with the healthy controls. In addition, RNase stability experiments confirmed their stable existence in US. Meanwhile, the ROC curve shows that SNORD15A, SNORD35B and SNORD60 could effectively distinguish RCC (AUC = 0.7421) and early-stage RCC (AUC = 0.7465) from healthy individuals. Conclusion SNORD15A, SNORD35B and SNORD60 were upregulated in tissues and US of RCC, serving as novel potential biomarkers for RCC diagnosis.