Esophageal squamous cell carcinoma (ESCC) is one of the deadliest cancers. We performed exome sequencing on 113 tumor-normal pairs, yielding a mean of 82 non-silent mutations per tumor, and 8 cell lines. The mutational profile of ESCC closely resembles those of squamous cell carcinomas of other tissues but differs from that of esophageal adenocarcinoma. Genes involved in cell cycle and apoptosis regulation were mutated in 99% of cases by somatic alterations of TP53 (93%), CCND1 (33%), CDKN2A (20%), NFE2L2 (10%) and RB1 (9%). Histone modifier genes were frequently mutated, including KMT2D (also called MLL2; 19%), KMT2C (MLL3; 6%), KDM6A (7%), EP300 (10%) and CREBBP (6%). EP300 mutations were associated with poor survival. The Hippo and Notch pathways were dysregulated by mutations in FAT1, FAT2, FAT3 or FAT4 (27%) or AJUBA (JUB; 7%) and NOTCH1, NOTCH2 or NOTCH3 (22%) or FBXW7 (5%), respectively. These results define the mutational landscape of ESCC and highlight mutations in epigenetic modulators with prognostic and potentially therapeutic implications.

BackgroundOesophageal cancer is one of the most deadly forms of cancer worldwide. Long non-coding RNAs (lncRNAs) are often found to have important regulatory roles.ObjectiveTo assess the lncRNA expression profile of oesophageal squamous cell carcinoma (OSCC) and identify prognosis-related lncRNAs.MethodLncRNA expression profiles were studied by microarray in paired tumour and normal tissues from 119 patients with OSCC and validated by qRT-PCR. The 119 patients were divided randomly into training (n=60) and test (n=59) groups. A prognostic signature was developed from the training group using a random Forest supervised classification algorithm and a nearest shrunken centroid algorithm, then validated in a test group and further, in an independent cohort (n=60). The independence of the signature in survival prediction was evaluated by multivariable Cox regression analysis.ResultsLncRNAs showed significantly altered expression in OSCC tissues. From the training group, we identified a three-lncRNA signature (including the lncRNAs ENST00000435885.1, XLOC_013014 and ENST00000547963.1) which classified the patients into two groups with significantly different overall survival (median survival 19.2 months vs >60 months, p<0.0001). The signature was applied to the test group (median survival 21.5 months vs >60 months, p=0.0030) and independent cohort (median survival 25.8 months vs >48 months, p=0.0187) and showed similar prognostic values in both. Multivariable Cox regression analysis showed that the signature was an independent prognostic factor for patients with OSCC. Stratified analysis suggested that the signature was prognostic within clinical stages.ConclusionsOur results suggest that the three-lncRNA signature is a new biomarker for the prognosis of patients with OSCC, enabling more accurate prediction of survival.

Introduction: Programmed death receptor-1 (PD-1) inhibitors have shown efficacy in first-line treatment of NSCLC; however, evidence of PD-1 inhibitor as neoadjuvant treatment is limited. This is a phase 1b study to evaluate the safety and outcome of PD-1 inhibitor in neoadjuvant setting. Methods: Treatment-naive patients with resectable NSCLC (stage IA-IIIB) received two cycles of sintilimab (200 mg, intravenously, day 1 out of 22). Operation was performed between day 29 and 43. Positron emission tomographycomputed tomography scans were obtained at baseline and before the operation. The primary end point was safety. Efficacy end points included rate of major pathologic response (MPR) and objective response rate. Expression of programmed cell death ligand 1 was also evaluated (registration number: ChiCTR-OIC-17013726). Results: A total of 40 patients enrolled, all of whom received two doses of sintilimab and 37 underwent radical resection. A total of 21 patients (52.5%) experienced neoadjuvant treatment-related adverse events (TRAEs). Four patients (10.0%) experienced grade 3 or higher neoadjuvant TRAEs, and one patient had grade 5 TRAE. Eight patients achieved radiological partial response, resulting in an objective response rate of 20.0%. Among 37 patients, 15 (40.5%) achieved MPR, including six (16.2%) with a pathologic complete response in primary tumor and three (8.1%) in lymph nodes as well. Squamous cell NSCLC exhibited superior response compared with adenocarcinoma (MPR: 48.4% versus 0%). Decrease of maximum standardized uptake values after sintilimab treatment correlated with pathologic remission (p < 0.00001). Baseline programmed cell death ligand 1 expression of stromal cells instead of tumor cells was correlated with pathologic regression (p ¼ 0.0471).

Esophageal cancer is the sixth leading cause of death from cancer and one of the least studied cancers worldwide. The global microRNA expression profile of esophageal cancer has not been reported previously. Here, for the first time, we have investigated expressed microRNAs in cryopreserved esophageal cancer tissues using advanced microRNA microarray techniques. Our microarray analyses identified seven microRNAs that could distinguish malignant esophageal cancer lesions from adjacent normal tissues. Some microRNAs could be correlated with the different clinicopathologic classifications. High expression of hsa-miR-103/107 correlated with poor survival by univariate analysis as well as by multivariate analysis. These results indicate that microRNA expression profiles are important diagnostic and prognostic markers of esophageal cancer, which might be analyzed simply using economical approaches such as reverse transcription-PCR.

MotivationThe BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community‐led open‐source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene.Main types of variables includedThe database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record.Spatial location and grainBioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km2 (158 cm2) to 100 km2 (1,000,000,000,000 cm2).Time period and grainBioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year.Major taxa and level of measurementBioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.Software format.csv and .SQL.