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.

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.

Accurately evaluating minimal residual disease (MRD) could facilitate early intervention and personalized adjuvant therapies. Here, using ultradeep targeted next-generation sequencing (NGS), we evaluate the clinical utility of circulating tumor DNA (ctDNA) for dynamic recurrence risk and adjuvant chemotherapy (ACT) benefit prediction in resected non-small cell lung cancer (NSCLC). Both postsurgical and post-ACT ctDNA positivity are significantly associated with worse recurrence-free survival. In stage II-III patients, the postsurgical ctDNA positive group benefit from ACT, while ctDNA negative patients have a low risk of relapse regardless of whether or not ACT is administered. During disease surveillance, ctDNA positivity precedes radiological recurrence by a median of 88 days. Using joint modeling of longitudinal ctDNA analysis and time-to-recurrence, we accurately predict patients’ postsurgical 12-month and 15-month recurrence status. Our findings reveal longitudinal ctDNA analysis as a promising tool to detect MRD in NSCLC, and we show pioneering work of using postsurgical ctDNA status to guide ACT and applying joint modeling to dynamically predict recurrence risk, although the results need to be further confirmed in future studies.

Purpose: Recent studies have suggested that microRNA biomarkers could be useful for stratifying lung cancer subtypes, but microRNA signatures varied between different populations. Squamous cell carcinoma (SCC) is one major subtype of lung cancer that urgently needs biomarkers to aid patient management. Here, we undertook the first comprehensive investigation on microRNA in Chinese SCC patients.Experimental Design: MicroRNA expression was measured in cancerous and noncancerous tissue pairs strictly collected from Chinese SCC patients (stages I-III), who had not been treated with chemotherapy or radiotherapy prior to surgery. The molecular targets of proposed microRNA were further examined.Results: We identified a 5-microRNA classifier (hsa-miR-210, hsa-miR-182, hsa-miR-486-5p, hsamiR-30a, and hsa-miR-140-3p) that could distinguish SCC from normal lung tissues. The classifier had an accuracy of 94.1% in a training cohort (34 patients) and 96.2% in a test cohort (26 patients). We also showed that high expression of hsa-miR-31 was associated with poor survival in these 60 SCC patients by Kaplan-Meier analysis (P ¼ 0.007), by univariate Cox analysis (P ¼ 0.011), and by multivariate Cox analysis (P ¼ 0.011). This association was independently validated in a separate cohort of 88 SCC patients (P ¼ 0.008, 0.011, and 0.003 in Kaplan-Meier analysis, univariate Cox analysis, and multivariate Cox analysis, respectively). We then determined that the tumor suppressor DICER1 is a target of hsa-miR-31. Expression of hsa-miR-31 in a human lung cancer cell line repressed DICER1 activity but not PPP2R2A or LATS2.Conclusions: Our results identified a new diagnostic microRNA classifier for SCC among Chinese patients and a new prognostic biomarker, hsa-miR-31. Clin Cancer Res; 17(21); 6802-11. Ó2011 AACR.

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Background Lung adenocarcinomas (LUAD) is the most common histological subtype of lung cancers. Tumor immune microenvironment (TIME) is involved in tumorigeneses, progressions, and metastases. This study is aimed to develop a robust immune‐related signature of LUAD. Methods A total of 1774 LUAD cases sourced from public databases were included in this study. Immune scores were calculated through ESTIMATE algorithm and weighted gene co‐expression network analysis (WGCNA) was applied to identify immune‐related genes. Stability selections and Lasso COX regressions were implemented to construct prognostic signatures. Validations and comparisons with other immune‐related signatures were conducted in independent Gene Expression Omnibus (GEO) cohorts. Abundant infiltrated immune cells and pathway enrichment analyses were carried out, respectively, through ImmuCellAI and gene set enrichment analysis (GSEA). Results In Cancer Genome Atlas (TCGA) LUAD cohorts, immune scores of higher levels were significantly associated with better prognoses ( P < .05). Yellow (n = 270) and Blue (n = 764) colored genes were selected as immune‐related genes, and after univariate Cox regression analysis ( P < .005), a total of 133 genes were screened out for subsequent model constructions. A four‐gene signature (ARNTL2, ECT2, PPIA, and TUBA4A) named IPSLUAD was developed through stability selection and Lasso COX regression. It was suggested by multivariate and subgroup analyses that IPSLUAD was an independent prognostic factor. It was suggested by Kaplan‐Meier survival analysis that eight out of nine patients in high‐risk groups had significantly worse prognoses in validation data sets ( P < .05). IPSLUAD outperformed other signatures in two independent cohorts. Conclusions A robust immune‐related prognostic signature with great performances in multiple LUAD cohorts was developed in this study.

Cyclin E is reported to be an important cell cycle regulator, and its dysregulation is implicated in tumorigenesis including esophageal squamous cell carcinoma (ESCC). MicroRNAs (miRNAs) regulate gene expression at the posttranscriptional level and play important roles in tumor initiation and progression. However, the regulation of cyclin E by miRNAs is still unclear in ESCC. In the present study, we found that overexpression of miR-29c inhibited cyclin E expression by targeting 3' untranslated region of cyclin E messenger RNA in ESCC cells. Moreover, overexpression of miR-29c induced cell cycle G(1)/G(0) arrest through suppression of cyclin E expression, without affecting other G(1) phase-related proteins level, such as cyclin D1, cyclin D2, cyclin dependent kinase (CDK) 2 and CDK6. Furthermore, we demonstrated that overexpression of miR-29c inhibited proliferation of ESCC cells in vitro and in vivo. In addition, we detected miR-29c expression in 26 pairs of esophageal tumor-in-site-tissues and 60 pairs of ESCC tissues. The result showed that miR-29c level significantly decreased in ESCC tumor tissues and cell lines compared with normal esophageal epithelia. Taken together, our findings indicated that miR-29c was frequently downregulated in ESCC tissues and cells and suppressed tumor growth by inducing cell cycle G(1)/G(0) arrest mainly through modulating cyclin E expression.