Long non-coding RNAs (lncRNAs) have recently emerged as vital players in tumor biology with potential value in cancer diagnosis, prognosis, and therapeutics. The lncRNA HULC (highly up-regulated in liver cancer) is increased in many malignancies, yet its serum expression profile and clinical value in gastric cancer (GC) patients remain unclear. Quantitative real-time polymerase chain reaction (RT-qPCR) for large-scale analysis of the serum expression of HULC in GC patients reliably detected circulating HULC and revealed that it is upregulated in GC patients. A high serum HULC level correlated with tumor size, lymph node metastasis, distant metastasis, tumor-node-metastasis stage, and H. pylori infection. The area under the ROC curve for HULC was up to 0.888, which was higher than that for CEA (0.694) and CA72-4 (0.514). Follow-up detection and Kaplan-Meier curve analysis revealed HULC is a good predictor of GC prognosis. Our present study indicates that circulating HULC may represent a novel serum tumor marker for early diagnosis and monitoring progression and prognosis of GC.

The expression levels of serum PCAT-1 in MM patients were significantly higher than that in healthy controls, suggesting that it may be useful in the auxiliary diagnosis of MM.

BackgroundIntracavitary electrocardiogram (IC ECG) guidance emerges as a new technique for peripherally inserted central catheters (PICCs) placement and demonstrates many potential advantages in recent observational studies.AimsTo determine whether IC ECG-guided PICCs provide more accurate positioning of catheter tips compared to conventional anatomical landmarks in patients with cancer undergoing chemotherapy.MethodsIn this multicenter, open-label, randomized controlled study (ClinicalTrials.gov number, NCT02409589), a total of 1,007 adult patients were assigned to receive either IC ECG guidance (n = 500) or anatomical landmark guidance (n = 507) for PICC positioning. The confirmative catheter tip positioning x-ray data were centrally interpreted by independent radiologists. All reported analyses in the overall population were performed on an intention-to-treat basis. Analyses of pre-specified subgroups and a selected large subpopulation were conducted to explore consistency and accuracy.ResultsIn the IC ECG-guided group, the first-attempt success rate was 89.2% (95% confidence interval [CI], 86.5% to 91.9%), which was significantly higher than 77.4% (95% CI, 73.7% to 81.0%) in the anatomical landmark group (P < 0.0001). This trend of superiority of IC ECG guidance was consistently noted in almost all prespecified patient subgroups and two selected large subpopulations, even when using optimal target rates for measurement. In contrast, the superiority nearly disappeared when PICCs were used via the left instead of right arms (interaction P-value = 0.021). No catheter-related adverse events were reported during the PICC intra-procedures in either group.ConclusionsOur findings indicated that the IC ECG-guided method had a more favorable positioning accuracy versus traditional anatomical landmarks for PICC placement in adult patients with cancer undergoing chemotherapy. Furthermore, there were no significant safety concerns reported for catheterization using the two techniques.

Background Accurate and robust pathological image analysis for colorectal cancer (CRC) diagnosis is time-consuming and knowledge-intensive, but is essential for CRC patients’ treatment. The current heavy workload of pathologists in clinics/hospitals may easily lead to unconscious misdiagnosis of CRC based on daily image analyses. Methods Based on a state-of-the-art transfer-learned deep convolutional neural network in artificial intelligence (AI), we proposed a novel patch aggregation strategy for clinic CRC diagnosis using weakly labeled pathological whole-slide image (WSI) patches. This approach was trained and validated using an unprecedented and enormously large number of 170,099 patches, > 14,680 WSIs, from > 9631 subjects that covered diverse and representative clinical cases from multi-independent-sources across China, the USA, and Germany. Results Our innovative AI tool consistently and nearly perfectly agreed with (average Kappa statistic 0.896) and even often better than most of the experienced expert pathologists when tested in diagnosing CRC WSIs from multicenters. The average area under the receiver operating characteristics curve (AUC) of AI was greater than that of the pathologists (0.988 vs 0.970) and achieved the best performance among the application of other AI methods to CRC diagnosis. Our AI-generated heatmap highlights the image regions of cancer tissue/cells. Conclusions This first-ever generalizable AI system can handle large amounts of WSIs consistently and robustly without potential bias due to fatigue commonly experienced by clinical pathologists. It will drastically alleviate the heavy clinical burden of daily pathology diagnosis and improve the treatment for CRC patients. This tool is generalizable to other cancer diagnosis based on image recognition.

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Current techniques for diagnosing glioma are invasive and do not accurately predict prognosis. We developed a novel, non-invasive liquid chip assay to diagnose glioma and predict prognosis. Using this method, we determined the methylation state of the Alu element in cell-free DNA extracted from the serum of 109 glioma patients. Controls included 56 patients with benign intracranial tumors and 50 healthy subjects. Matched tumor tissues were processed for 36 patients. The cfDNA from glioma patients showed lower levels of Alu methylation than the controls (P<0.01). Alu methylation was also lower in high-grade than low-grade gliomas (P<0.01), indicating that Alu methylation correlates negatively with disease severity. Moreover, Alu methylation correlated positively with survival (P<0.01). These findings suggest high-throughput liquid chip could serve as a non-invasive diagnostic assay for glioma.

The aim of the present study was to investigate the association between cell-free DNA (cf-DNA) levels and clinicopathological characteristics of patients with ovarian cancer using a branched DNA (bDNA) technique, and to determine the value of quantitative cf-DNA detection in assisting with the diagnosis of ovarian cancer. Serum specimens were collected from 36 patients with ovarian cancer on days 1, 3 and 7 following surgery, and additional serum samples were also collected from 22 benign ovarian tumor cases, and 19 healthy, non-cancerous ovaries. bDNA techniques were used to detect serum cf-DNA concentrations. All data were analyzed using SPSS version 18.0. The cf-DNA levels were significantly increased in the ovarian cancer group compared with those of the benign ovarian tumor group and healthy ovarian group (P<0.01). Furthermore, cf-DNA levels were significantly increased in stage III and IV ovarian cancer compared with those of stages I and II (P<0.01). In addition, cf-DNA levels were significantly increased on the first day post-surgery (P<0.01), and subsequently demonstrated a gradual decrease. In the ovarian cancer group, the area under the receiver operating characteristic curve of cf-DNA and the sensitivity were 0.917 and 88.9%, respectively, which was higher than those of cancer antigen 125 (0.724, 75%) and human epididymis protein 4 (0.743, 80.6%). There was a correlation between the levels of serum cf-DNA and the occurrence and development of ovarian cancer in the patients evaluated. bDNA techniques possessed higher sensitivity and specificity than other methods for the detection of serum cf-DNA in patients exhibiting ovarian cancer, and bDNA techniques are more useful for detecting cf-DNA than other factors. Thus, the present study demonstrated the potential value for the use of bDNA as an adjuvant diagnostic method for ovarian cancer.

Bone marrow stromal cells (BMSCs) up-regulate B cell-activating factor (BAFF) in multiple myeloma. Increasing experimental evidence has shown that microRNAs play a causal role in hematology tumorigenesis. In this study, we characterized the role of miR-202 in regulating the expression of BAFF in BMSCs. It was found that expressions of BAFF mRNA and protein were increased in BMSCs treated with miR-202 inhibitor. The growth rate of miR-202 mimics transfection cells was significantly lower than that of non-transfected cells. The expression of Bcl-2 protein was down-regulated, and Bax protein was up-regulated after miR-202 mimics transfection. Over-expression of miR-202 in BMSCs rendered MM cells more sensitive to bortezomib. More significantly, the regulatory effect of miR-202 could inhibit the activation of NF-κB pathway in BMSCs. These results suggest that miR-202 functions as a modulator that can negatively regulate BAFF by inhibiting MM cell survival, growth, and adhesion in the bone marrow microenvironment.