Dataset Information

Development and Validation of a Serum Biomarker Panel for the Detection of Esophageal Squamous Cell Carcinoma through RNA Transcriptome Sequencing.

ABSTRACT: Serum tumor markers for the diagnosis of esophageal squamous cell carcinoma (ESCC) have low sensitivity. This study aims to identify new serum markers for ESCC diagnosis from RNA sequencing (RNA-seq) data. RNA-seq was performed using six pairs of ESCC and matched normal tissues. The candidates for ESCC were screened from the differentially expressed genes. The candidates were analyzed by ELISA from the serum of a test group and a validation group. Real-time PCR, Western blotting and immunohistochemistry were used to detect the expression of the candidates in tumor cell lines and tumor tissues. Ten genes were selected from the RNA-seq data. Serum levels of ADAM12, CHI3L1, MMP13 and SPP1 were significantly higher in the ESCC patients than in the healthy controls. A diagnostic model combining CHI3L1, MMP13, and SPP1 was established. The area under the curve (AUC) values for serum CHI3L1, MMP13, and SPP1 and the diagnostic model for discriminating ESCC patients from controls were 0.732, 0.881, 0.661 and 0.928, respectively. In the validation cohort, the AUC values were 0.753, 0.789, 0.696 and 0.843, respectively. Moreover, the AUC of the model for classifying patients with early ESCC was 0.918 in the test group and 0.857 in the validation group. Overexpression of CHI3L1, MMP13 and SPP1 was observed in the tumor cell lines and tissues. The diagnostic model composed of CHI3L1, MMP13 and SPP1 discriminates ESCC patients with high sensitivity. Our data highlight the potential of this diagnostic model for the noninvasive diagnosis of ESCC.

SUBMITTER: Xing S

PROVIDER: S-EPMC5560154 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Development and Validation of a Serum Biomarker Panel for the Detection of Esophageal Squamous Cell Carcinoma through RNA Transcriptome Sequencing.

Xing Shan S Zheng Xin X Wei Li-Qiang LQ Song Shi-Jian SJ Liu Dan D Xue Ning N Liu Xiao-Min XM Wu Mian-Tao MT Zhong Qian Q Huang Chu-Mei CM Zeng Mu-Sheng MS Liu Wan-Li WL

Journal of Cancer 20170721 12

Serum tumor markers for the diagnosis of esophageal squamous cell carcinoma (ESCC) have low sensitivity. This study aims to identify new serum markers for ESCC diagnosis from RNA sequencing (RNA-seq) data. RNA-seq was performed using six pairs of ESCC and matched normal tissues. The candidates for ESCC were screened from the differentially expressed genes. The candidates were analyzed by ELISA from the serum of a test group and a validation group. Real-time PCR, Western blotting and immunohistoc ...[more]

PMID: 28819439

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Project description:BackgroundThe identification of effective tumor markers is of paramount importance for the early diagnosis, treatment, and prognosis of esophageal squamous cell carcinoma (ESCC). The present study endeavors to identify efficacious serological markers that can differentiate patients with early-stage ESCC from those with benign esophageal lesions and healthy controls (HC). Cystatin-SN (CST1), an active cysteine protease inhibitor belonging to the Cystatin (CST) superfamily, is implicated in the pathogenesis of inflammation and tumorigenesis. The objective of this investigation is to assess the diagnostic, therapeutic, and prognostic potential of serum CST1 in ESCC.MethodsIn our prior RNA sequencing and screening endeavors, we have identified ten genes that are up-regulated in relation to esophageal cancer. Subsequently, we have verified the gene CST1 from the transcriptome data of the The Cancer Genome Atlas Program (TCGA) and Gene Expression Profiling Interactive Analysis (GEPIA) database. Following this, we conducted an enzyme-linked immunosorbent assay (ELISA) to ascertain the expression levels of CST1 in serum samples from clinical cohorts.ResultsThe study revealed a significant elevation in serum CST1 levels among patients with early-stage esophageal squamous cell carcinoma (ESCC) (7.41 ± 4.32 ng/ml) compared to those with esophageal benign lesions (4.67 ± 2.43 ng/ml) (p < 0.0001) and healthy controls (4.87 ± 2.77 ng/ml) (p < 0.0001). The diagnostic sensitivity of CST1 for ESCC was 75.68% (specificity 70.83%, AUC 0.775). Combination of CST1 and SCC-Ag exhibited the AUC up to 0.819. Additionally, serum CST1 levels exhibited a significant decrease at 1-2 weeks post-surgery (4.49 ± 3.31 ng/ml) compared to pre-surgery levels (7.68 ± 3.71 ng/ml) (p<0.0001). Survival analysis demonstrated a strong association between high (844/415-1543 d) or low (1490/645-1710 d) serum CST1 levels at diagnosis and overall survival time (p < 0.001). Furthermore, multivariate regression analysis confirmed CST1 (p=0.024, HR=2.023, 95%CI 1.099-3.725) as an independent prognostic factor.ConclusionSerum CST1 has the potential to function as a diagnostic indicator for distinguishing early-stage esophageal squamous cell carcinoma (ESCC) from individuals with benign esophageal lesions and healthy individuals. Additionally, it could serve as a prognostic predictor and therapeutic efficacy indicator for patients with ESCC.

Project description:BackgroundEsophageal squamous cell carcinoma (ESCC) is one of the most common malignancies with poor diagnosis. Esophageal squamous dysplasia (ESD) is considered as an immediate precancerous lesion of ESCC. Lack of biomarkers for discriminating ESCC and ESD from healthy subjects limits the early diagnosis and treatment of ESCC. Therefore, a serum metabolomic strategy was conducted to identify and validate potential metabolic markers for the screening of ESCC and ESD subjects.MethodsA total of 74 patients with ESCC, 72 patients with ESD, and 75 normal control (NC) subjects were enrolled in this study. Gas chromatography-mass spectrometry was used to acquire serum metabolic profiles. Pathway analysis was conducted to uncover the fluctuated metabolic pathways during ESCC. Multivariate analyses were used to screen and validate the biomarkers.ResultsESCC, ESD, and NC subjects revealed progressively altered metabolic profiles, in which amino acids globally increased, while fatty acids decreased in ESCCs compared with the control groups. Pathway analysis demonstrated the activated biosynthesis of amino acids and inhibited desaturation of saturated fatty acids. The panel constructed with propanoic acid, linoleic acid, glycerol-3-phosphate, and l-glutamine showed the area under the curve (AUC), sensitivity, and specificity of 0.817, 0.75, and 0.74, respectively, in the discrimination of ESCC/ESD patients from NC subjects. The panel constructed by propanoic acid, l-leucine, and hydroxyproline revealed the AUC, sensitivity, and specificity of 0.819, 0.76, and 0.72, respectively, in the discrimination of ESD from NC subjects. The combination of hypoxanthine, 2-ketoisocaproic acid, l-glutamate, and l-aspartate showed the AUC, sensitivity, and specificity of 0.818, 0.83, and 0.74, respectively, in the discrimination of ESCC patients from ESD subjects.ConclusionsOur study revealed the systematic landscape for metabolic alterations in sera of ESD and ESCC patients. The defined metabolite markers showed reasonable performance in the discrimination of ESCC and ESD patients, and may provide helpful reference for clinicians and biologists.

Project description:Background:DNA methylation has been implicated as a promising biomarker for precise cancer diagnosis. However, limited DNA methylation-based biomarkers have been described in esophageal squamous cell carcinoma (ESCC). Methods:A high-throughput DNA methylation dataset (100 samples) of ESCC from The Cancer Genome Atlas (TCGA) project was analyzed and validated along with another independent dataset (12 samples) from the Gene Expression Omnibus (GEO) database. The methylation status of peripheral blood mononuclear cells and peripheral blood leukocytes from healthy controls was also utilized for biomarker selection. The candidate CpG sites as well as their adjacent regions were further validated in 94 pairs of ESCC tumor and adjacent normal tissues from the Chinese Han population using the targeted bisulfite sequencing method. Logistic regression and several machine learning methods were applied for evaluation of the diagnostic ability of our panel. Results:In the discovery stage, five hyper-methylated CpG sites were selected as candidate biomarkers for further analysis as shown below: cg15830431, P?=?2.20?×?10-4; cg19396867, P?=?3.60?×?10-4; cg20655070, P?=?3.60?×?10-4; cg26671652, P?=?5.77?×?10-4; and cg27062795, P?=?3.60?×?10-4. In the validation stage, the methylation status of both the five CpG sites and their adjacent genomic regions were tested. The diagnostic model based on the combination of these five genomic regions yielded a robust performance (sensitivity?=?0.75, specificity?=?0.88, AUC?=?0.85). Eight statistical models along with five-fold cross-validation were further applied, in which the SVM model reached the best accuracy in both training and test dataset (accuracy?=?0.82 and 0.80, respectively). In addition, subgroup analyses revealed a significant difference in diagnostic performance between the alcohol use and non-alcohol use subgroups. Conclusions:Methylation profiles of the five genomic regions covering cg15830431 (STK3), cg19396867, cg20655070, cg26671652 (ZNF418), and cg27062795 (ZNF542) can be used for effective methylation-based testing for ESCC diagnosis.

Project description:ImportancePatients with late-stage esophageal squamous cell carcinoma (ESCC) have a poor prognosis. Noninvasive screening tests using serum microRNAs (miRNAs) to accurately detect early-stage ESCC are needed to improve mortality.ObjectiveTo establish a model using serum miRNAs to distinguish patients with ESCC from noncancer controls.Design, setting, and participantsIn this case-control study, serum miRNA expression profiles of patients with ESCC (n = 566) and control patients without cancer (n = 4965) were retrospectively analyzed to establish a diagnostic model, which was tested in a training set and confirmed in a validation set. Patients histologically diagnosed as having ESCC who did not receive prior therapy or have a past or concurrent cancer other than ESCC were enrolled from the National Cancer Center Hospital in Tokyo, Japan. Between October 2010 and November 2015, control samples were collected from the National Cancer Center Biobank, the Biobank of the National Center for Geriatrics and Gerontology, and the general population undergoing routine health examination. Data analysis was performed between August 2015 and October 2018. Serum samples were randomly divided into discovery and validation sets.Main outcomes and measuresThe expression of 2565 miRNAs was assessed in each sample. The discriminant model (named the EC index) was evaluated in the training set using Fisher linear discriminant analysis with a greedy algorithm. Receiver operating characteristic curve analysis evaluated the diagnostic ability of the model in the validation set.ResultsIn the training set, 283 patients with esophageal cancer (median age, 67 years [range, 37-90 years]; 83.4% male) were compared with 283 control patients (median age, 54 years [range, 22-100 years]; 43.1% male), and the EC index was constructed using 6 miRNAs (miR-8073, miR-6820-5p, miR-6794-5p, miR-3196, miR-744-5p, and miR-6799-5p). The area under the receiver operating characteristic curve was 1.00, with sensitivity of 1.00 and specificity of 0.98. The validation set included 283 patients (median age, 66 years [range, 42-87 years]; 83.0% male) and 4682 control patients (median age, 68 years [range, 20-98 years]; 44.7% male), and the area under the receiver operating characteristic curve for the EC index was 1.00, with sensitivity of 0.96 and specificity of 0.98.Conclusions and relevanceWhat appears to be novel serum miRNA discriminant model was developed for the diagnosis of ESCC. A multicenter prospective study is ongoing to confirm the present observations.

Dataset Information

Development and Validation of a Serum Biomarker Panel for the Detection of Esophageal Squamous Cell Carcinoma through RNA Transcriptome Sequencing.

Publications

Development and Validation of a Serum Biomarker Panel for the Detection of Esophageal Squamous Cell Carcinoma through RNA Transcriptome Sequencing.

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