BackgroundMany long non-coding RNAs(lncRNAs) have been found to be a good marker for several tumors. Using lncRNA-mining approach, we aimed to identify lncRNA expression signature that can predict breast cancer patient survival.MethodsWe performed LncRNA expression profiling in 887 breast cancer patients from Gene Expression Omnibus (GEO) datasets. The association between lncRNA signature and clinical survival was analyzed using the training set(n = 327, from GSE 20685). The validation for the association was performed in another three independent testing sets(252 from GSE21653, 204 from GSE12276, and 104 from GSE42568).ResultsA set of four lncRNA genes (U79277, AK024118, BC040204, AK000974) have been identified by the random survival forest algorithm. Using a risk score based on the expression signature of these lncRNAs, we separated the patients into low-risk and high-risk groups with significantly different survival times in the training set. This signature was validated in the other three cohorts. Further study revealed that the four-lncRNA expression signature was independent of age and subtype. Gene Set Enrichment Analysis (GSEA) suggested that gene sets were involved in several cancer metastasis related pathways.ConclusionsThese findings indicate that lncRNAs may be implicated in breast cancer pathogenesis. The four-lncRNA signature may have clinical implications in the selection of high-risk patients for adjuvant therapy.Electronic supplementary materialThe online version of this article (doi:10.1186/s13046-014-0084-7) contains supplementary material, which is available to authorized users.

Summary Soybean (Glycine max) production is severely affected in unfavorable environments. Identification of the regulatory factors conferring stress tolerance would facilitate soybean breeding. In this study, through coexpression network analysis of salt‐tolerant wild soybeans, together with molecular and genetic approaches, we revealed a previously unidentified function of a class B heat shock factor, HSFB2b, in soybean salt stress response. We showed that HSFB2b improves salt tolerance through the promotion of flavonoid accumulation by activating one subset of flavonoid biosynthesis‐related genes and by inhibiting the repressor gene GmNAC2 to release another subset of genes in the flavonoid biosynthesis pathway. Moreover, four promoter haplotypes of HSFB2b were identified from wild and cultivated soybeans. Promoter haplotype II from salt‐tolerant wild soybean Y20, with high promoter activity under salt stress, is probably selected for during domestication. Another promoter haplotype, III, from salt‐tolerant wild soybean Y55, had the highest promoter activity under salt stress, had a low distribution frequency and may be subjected to the next wave of selection. Together, our results revealed the mechanism of HSFB2b in soybean salt stress tolerance. Its promoter variations were identified, and the haplotype with high activity may be adopted for breeding better soybean cultivars that are adapted to stress conditions.

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The proteins of the Inhibitor of Growth (ING) candidate tumor suppressor family are involved in multiple cellular functions such as cell cycle regulation, apoptosis, and chromatin remodeling. ING5 is the new member of the family whose actual role in tumor suppression is not known. Here we show that ING5 overexpression in lung cancer A549 cells inhibited cell proliferation and invasiveness, while ING5 knockdown in lung cancer H1299 cells promoted cell aggressiveness. ING5 overexpression also abrogated tumor growth and invasive abilities of lung cancer cells in mouse xenograft models. Further study showed that ING5 overexpression inhibited EMT indicated by increase of E-cadherin and decrease of N-cadherin, Snail and slug at mRNA and protein levels, which was accompanied with morphological changes. cDNA microarray and subsequent qRT-PCR validation revealed that ING5 significantly downregulated expression of EMT (epithelial to mesenchymal transition)-inducing genes including CEACAM6, BMP2 and CDH11. Clinical study by tissue microarray showed that nuclear ING5 negatively correlated with clinical stages and lymph node metastasis of lung cancer. Furthermore, high level of nuclear ING5 was associated with a better prognosis. Taken together, these findings uncover an important role for ING5 as a potent tumor suppressor in lung cancer growth and metastasis.

Purpose Reliable and accurate predictive models are necessary to drive the success of radiomics. Our aim was to identify the optimal radiomics-based machine learning method for isocitrate dehydrogenase (IDH) genotype prediction in diffuse gliomas. Methods Eight classical machine learning methods were evaluated in terms of their stability and performance for pre-operative IDH genotype prediction. A total of 126 patients were enrolled for analysis. Overall, 704 radiomic features extracted from the pre-operative MRI images were analyzed. The patients were randomly assigned to either the training set or the validation set at a ratio of 2:1. Feature selection and classification model training were done using the training set, whereas the predictive performance and stability of the model were independently assessed using the validation set. Results Random Forest (RF) showed high predictive performance (accuracy 0.885 ± 0.041, AUC 0.931 ± 0.036), whereas neural network (NN) (accuracy 0.829 ± 0.064, AUC 0.878 ± 0.052) and flexible discriminant analysis (FDA) (accuracy 0.851 ± 0.049, AUC 0.875 ± 0.057) displayed low predictive performance. With regard to stability, RF also showed high robustness against data perturbation (relative standard deviations, RSD 3.87%). Conclusions RF is a promising machine learning method in predicting IDH genotype. Development of an accurate and reliable model can assist in the initial diagnostic evaluation and treatment planning for diffuse glioma patients. Electronic supplementary material The online version of this article (10.1007/s00432-018-2787-1) contains supplementary material, which is available to authorized users.

◥Purpose: Tumor heterogeneity and burden, which impact treatment outcome in prostate cancer, are rarely evaluated using nextgeneration imaging.Experimental Design: The trial prospectively included 37 patients who had an early PSA progression (≤2 ng/mL) during castration and high-risk (PSA doubling time ≤10 months) nonmetastatic disease by conventional imaging. All patients underwent both 68 Ga-PSMA and 18 F-FDG PET/CT. Lesions were classified into PSMAþFDGAE lesions and PSMA-FDGþ lesions. The primary endpoint was the prevalence of PSMA-FDGþ disease. Tumor burden, predictors for positive imaging, and suitability for oligometastases-directed therapy (OMDT) were also evaluated.Results: All patients were treated with RP and the median duration of castration was 23 months. The median PSA at imaging was 0.57 ng/mL. Overall, 114 lesions were detected in 29 of the 37 patients. A high prevalence (73%) of Nþ/Mþ disease was observed. Of the 114 lesions, 81 were PSMAþFDGAE and 33 were PSMA-FDGþ. Per patient level, 9 men (24%; 95% confidence interval: 10%-39%) showed at least one new PSMA-FDGþ lesions. A short PSA doubling time (P ¼ 0.009, OR ¼ 8.000) was associated with PSMAþFDGAE disease, while a high Gleason grade group (P ¼ 0.022, OR ¼ 13.091) with PSMA-FDGþ disease. Nineteen patients (51%) with 51 lesions, including 10 PSMA-FDGþ lesions, could be enrolled for OMDT. Among different disease stages, PSMA-FDGþ disease was rarely detected in the hormone-sensitive cohort, but frequently found in the castration-resistant cohort.Conclusions: Using 68 Ga-PSMA and 18 F-FDG PET, we observed a high prevalence of Nþ/Mþ disease and a significant proportion of PSMA-FDGþ disease in patients with an early PSA progression during castration (ChiCTR1900022634).

A 31-gene signature derived by integrating four different microarray experiments, has been found to have a potential for predicting radiosensitivity of cancer cells, but it was seldom validated in clinical cancer samples. We proposed that the gene signature may serve as a predictive biomarker for estimating the overall survival of radiation-treated patients. The significance of gene signature was tested in two previously published datasets from Gene Expression Omnibus (GEO) and The Cancer Genome Altas (TCGA), respectively. In GEO data set, patients predicted to be radiosensitive(RS) had an improved overall survival when compared with radioresistant(RR) patients in either radiotherapy(RT)-treated or non radiotherapy(RT)-treated subgroups(p<0.0001 in the RT-treated group). Multivariate Cox regression analysis showed that the gene signature is the strongest predictor(p=0.0093) in the RT-treated subgroup of patients. However, it does not remain significant (p=0.7668) in non radiotherapy-treated group when adjusting for age and Karnofsky performance score (KPS) as covariates. Similarly, in the TCGA data set, radiotherapy-treated glioblastoma multiforme(GBM) patients assigned to RS group had an improved overall survival compared with RR group(p<0.0001). Geneset enrichment analysis(GSEA) analysis revealed that enrichment of epithelial mesenchymal transition(EMT) pathway was observed with radioresistant phenotype. These results suggest that the signature is a predictive biomarker for radiation-treated glioma patients' prognostic.

Abstract Emerging studies have shown that the aberrant expression and function of long non-coding RNAs (lncRNAs) are involved in carcinogenesis and the development of various cancers. The long noncoding RNA JPX (lncRNA JPX) on the X chromosome is an activator of X-inactive-specific transcript (XIST) and is a molecular switch for X-chromosome inactivation. However, the exact mechanism by which JPX acts in non-small-cell lung cancer (NSCLC) is not well studied. Here, through integrating clinical data and a series of functional experiments, we found that lncRNA JPX expression is significantly upregulated in NSCLC tissues compared with that in paired adjacent normal tissues from two independent datasets and significantly associated with a poor survival and other malignant phenotypes (tumor stage, tumor volume) of NSCLC. Furthermore, we elucidated that JPX functions as an oncogene in NSCLC-promoting cell proliferation and cell migration by affecting cell-cycle progression. Mechanistically, JPX upregulates cyclin D2 (CCND2) expression in a competing endogenous RNA mechanism by interacting with miR-145-5p, thus provoking the development and progression of NSCLC. These findings reveal the mechanism of X-chromosome lncRNA JPX and its core regulatory circuitry JPX/miR-145-5p/CCND2 in the development and progression of NSCLC, which bring us closer to an understanding of the molecular drivers of NSCLC.