Rationale : Tumor metastasis is the main cause for cancer-related death. However, the driving molecules of metastasis remain largely unknown. Here, we aim to identify long non-coding RNAs (lncRNAs) critical for human hepatocellular carcinoma (HCC) metastasis. Methods : Microarrays were used to screen a comprehensive set of lncRNAs with differential expression profiles in sulfatide-treated cells. Mass spectrometry, protein arrays, and RNA pull-down experiments were used to identify proteins that interacted with lncRNA. Epigenetic analysis was used to study lncRNA-mediated regulation mechanisms. Results : We identified lncRNA AY927503 (AY) as a metastasis-associated molecule that was highly expressed in human hepatocellular carcinoma (HCC) and correlated with metastatic events and poor prognosis in patients with HCC. AY promoted HCC cell migration, stemness, 5-fluorouracil resistance, and metastasis in mice. However, knockdown of integrin αV (ITGAV) abolished AY-stimulated migration, cell viability in HCC cells or tube formation. AY strongly promoted ITGAV transcription and αVβ3 expression by interacting with the ITGAV promoter specifically and stimulating its activity. AY was identified to interact with histone 1FX (H1FX), but deletion of the central domain of AY (AY∆371-522) abolished H1FX binding and ITGAV promoter stimulation. AY significantly enriched H3K4Me3 and acH3K9/14 but reduced H3K27Me3 and H1FX occupancy on the ITGAV promoter, which remodeled chromatin structures for RNA polymerase II recruitment. Knockdown of H1FX abrogated ITGAV transcription stimulated by AY. Conclusions : Our findings suggested that lncRNA AY promoted HCC metastasis via induction of chromatin modification for ITGAV transcription as a pioneer factor and was a potential molecular signature for metastasis or poor prognosis in patients with HCC.

TACE combined with RFA was more effective than RFA alone, especially for treatment for intermediate and large-size hepatic tumours or younger patients with HCC.

This study aimed to develop and validate an effective prognostic nomogram for advanced PDAC patients. We conducted a prospective multicenter cohort study involving 1,526 advanced PDAC patients from three participating hospitals in China between January 1, 2004 and December 31, 2013. Two thirds of the patients were randomly assigned to the training set (n = 1,017), and one third were assigned to the validation set (n = 509). Multivariate cox regression analysis was performed to identify significant prognostic factors for overall survival to develop the nomogram. Internal and external validation using C-index and calibration curve were conducted in the training set and validation set respectively. As results, seven independent prognostic factors were identified: age, tumor stage, tumor size, ALT (alanine aminotransferase), ALB (albumin), CA 19-9, HBV infection status, and these factors were entered into the nomogram. The proposed nomogram showed favorable discrimination and calibration both in the training set and validation set. The C-indexes of the training set and validation set were 0.720 and 0.696 respectively, which were both significantly higher than that of the staging system (C-index = 0.613, P < 0.001). In conclusion, the proposed nomogram may be served as an effective tool for prognostic evaluation of advanced PDAC.