Plasma H19 may serve as a potential biomarker for BC early screening and prognosis monitor.

BackgroundIt is well known that HOX transcript antisense intergenic ribonucleic acid (HOTAIR) plays an important role in breast cancer (BC). However, whether circulating HOTAIR in plasma could be used for BC diagnosis and dynamic monitoring are unclear.MethodsWe tested the expression levels of HOTAIR in 30 pairs of tissue samples and 148 plasma samples from BC patients by quantitative real time‐polymerase chain reaction, and the correlation between plasma HOTAIR levels and clinical features were analyzed. Receiver operating characteristic curve (ROC) was used to assess the diagnostic power of plasma HOTAIR for BC. Furthermore, we explored the monitoring values of plasma HOTAIR for BC and analyzed the correlation of HOTAIR levels between plasma and corresponding tissues of the same patients.ResultsThe expression levels of HOTAIR were significantly higher in BC tissues and plasma than in the control (P < 0.05). The expression levels of plasma HOTAIR were correlated with lymph node metastasis (P = 0.018), estrogen receptor (ER) (P = 0.012), c‐erbB‐2 (P = 0.006) and triple positive (P = 0.015). The area under the ROC curve of plasma HOTAIR was 0.80 (sensitivity 69.2%; specificity 93.3%), which was higher than the carcinoembryonic antigen and carbohydrate antigen 15‐3 values obtained. Moreover, plasma HOTAIR expression levels in postoperative patients were lower than those in preoperative patients (P = 0.029) and were moderately correlated with the corresponding tissue levels of the same patients (r = 0.68, P < 0.0001).ConclusionThese results indicated that HOTAIR may be a potential biomarker for the diagnosis of BC.

Abstract. Breast cancer (BC) is now the most common malignancy worldwide, with high prevalence and lethality among women. Invasion and metastasis are the major reasons for breast cancer-associated mortality. However, the underlying mechanism of invasion and metastasis has not been entirely elucidated. Long non-coding RNAs (lncRNAs) are a large class of non-coding transcripts that are >200 bases in length and cannot encode proteins. Evidence has indicated that lncRNAs regulate gene expression at the levels of epigenetic modification, transcription and post-transcription. In addition, they are involved in diverse tumor biological processes, including cell proliferation, apoptosis, invasion, metastasis and angiogenesis. The present review focuses on the recent progress of lncRNAs in breast cancer invasion and metastasis, aiming to provide novel strategies for the clinical prevention, diagnosis and treatment of breast cancer.

BackgroundPrevious studies have indicated that large intergenic non‐coding RNA regulator of reprogramming (lincRNA‐ROR) plays an important role in regulating tumor carcinogenesis and metastasis; however, whether circulating lincRNA‐ROR could function as a potential biomarker for breast cancer (BC) diagnosis and monitoring is unknown. This study was conducted to investigate circulating lincRNA‐ROR in plasma as a potential biomarker for BC diagnosis and monitoring.MethodsWe performed reverse transcription‐quantitative‐PCR to examine lincRNA‐ROR expression levels in cell lines, 24 pairs of BC tissue samples, and 94 plasma samples from BC patients. Potential correlations between plasma lincRNA‐ROR levels and clinicopathological characteristics were analyzed. A receiver operating characteristic curve was calculated to evaluate the diagnostic values for BC. Pearson correlation analysis of lincRNA‐ROR in plasma samples and the corresponding tissues of the same patients was performed to explore tumor monitoring values.ResultsLincRNA‐ROR expression was significantly increased in BC cell lines, tissues, and plasma (all P < 0.01). Plasma lincRNA‐ROR levels were associated with estrogen receptors (P = 0.042) and lymph node metastasis (P = 0.046). The area under the receiver operating characteristic curve of plasma lincRNA‐ROR was 0.844 (sensitivity 80.0%, specificity 56.7%), which was higher than carcinoembryonic and carbohydrate antigen 15‐3 values. Moreover, plasma lincRNA‐ROR levels were decreased in postoperative compared to preoperative samples (P < 0.0001). Plasma lincRNA‐ROR levels moderately correlated with the corresponding tissue level in the same patients (r2 = 0.638, P < 0.0001).ConclusionPlasma lincRNA‐ROR may be a potential biomarker for BC diagnosis and a dynamic monitor.

Background Patients who receive extracorporeal membrane oxygenation (ECMO) support require substantial transfusions. Red blood cell (RBC) and platelet (PLT) transfusions have been reported to be associated with adverse outcomes in ECMO patients. However, little is known about whether the transfusion of fresh frozen plasma (FFP) is associated with mortality and morbidity among patients receiving ECMO. The aim of this study was to examine the relationship between FFP transfusion and mortality in ECMO patients and assess risk factors for the transfusion of FFP. Methods The clinical parameters of 116 ECMO patients were collected. The machine learning approach of the Boruta algorithm was employed to select the variables associated with ECMO patients' in-hospital mortality. Univariate and multivariate logistic regression analyses were applied to identify the association between the selected variables and in-hospital mortality. Spearman correlation and backwards stepwise multiple linear regression analyses were used to examine parameters contributing to FFP transfusion. Results Among the 116 patients who received ECMO support, the in-hospital mortality was 32.8%. The median FFP (mL/kg/d) transfusion was higher in dead patients (5.07, IQR 1.78–8.90) when compared to alive patients (2.16, IQR 0.79–4.66) ( p = 0.007). After adjustment for confounders, FFP transfusion (mL/kg/d) was associated with in-hospital mortality (OR 1.09, 95% CI, 1.01–1.18; p = 0.035). Further analysis found that higher activated partial thromboplastin time (APTT), higher levels of uric acid (UA) and lower PLT counts were significant risk factors for FFP transfusion, with estimated values of 0.06 (95% CI, 0.02–0.11; p = 0.009), 0.01 (95% CI, 0.00–0.02; p = 0.003) and −0.03 (95% CI, −0.05--0.01; p = 0.007), respectively. Conclusion FFP transfusion is markedly associated with in-hospital mortality among patients receiving ECMO, and higher APTT, higher levels of UA and lower PLT counts are risk factors for FFP transfusion. This suggests that better management of patients' coagulation system and kidney function may reduce the utilization of FFP, thus improving ECMO patient outcomes.