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).
Background: BGISEQ-500 is a new desktop sequencer developed by BGI. Using DNA nanoball and combinational probe anchor synthesis developed from Complete Genomics™ sequencing technologies, it generates short reads at a large scale. Findings: Here, we present the first human whole-genome sequencing dataset of BGISEQ-500. The dataset was generated by sequencing the widely used cell line HG001 (NA12878) in two sequencing runs of paired-end 50 bp (PE50) and two sequencing runs of paired-end 100 bp (PE100). We also include examples of the raw images from the sequencer for reference. Finally, we identified variations using this dataset, estimated the accuracy of the variations, and compared to that of the variations identified from similar amounts of publicly available HiSeq2500 data. Conclusions: We found similar single nucleotide polymorphism (SNP) detection accuracy for the BGISEQ-500 PE100 data (false positive rate [FPR] = 0.00020%, sensitivity = 96.20%) compared to the PE150 HiSeq2500 data (FPR = 0.00017%, sensitivity = 96.60%) better SNP detection accuracy than the PE50 data (FPR = 0.0006%, sensitivity = 94.15%). But for insertions and deletions (indels), we found lower accuracy for BGISEQ-500 data (FPR = 0.00069% and 0.00067% for PE100 and PE50 respectively, sensitivity = 88.52% and 70.93%) than the HiSeq2500 data (FPR = 0.00032%, sensitivity = 96.28%). Our dataset can serve as the reference dataset, providing basic information not just for future development, but also for all research and applications based on the new sequencing platform.
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