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Integrated analysis of genomic and transcriptomic profiles identified a prognostic immunohistochemistry panel for esophageal squamous cell cancer.

ABSTRACT: BACKGROUND:The poor outcome of patients with esophageal squamous cell carcinoma (ESCC) highlights the importance of the identification of novel effective prognostic biomarkers. We aimed to identify a clinically applicable prognostic immunohistochemistry (IHC) panel for ESCC. METHODS:An integrated analysis was performed to screen and establish a prognostic panel using exome sequencing profile from 81 pairs of ESCC samples and RNA expression microarray data from 119 ESCC subjects. Two independent ESCC cohorts were recruited as training and validation groups to test the prognostic value. RESULTS:Three genes were selected, namely, ANO1, GAL, and MMP3, which were aberrantly expressed in ESCC tumor tissues (P < .001). Among them, ANO1 and MMP3 were reserved for the construction of the prognostic panel due to their significant association with the prognosis of ESCC patients (P = .015 and P < .001). Patients with both ANO1+ and MMP3+ had a poorer prognosis than that with ANO1-/MMP3+, ANO1+/MMP3-, or ANO1-/MMP3 - in both the training set and validation set (P < .001). Receiver operating characteristic analysis showed that the combination of IHC panel and eighth American Joint Commission on Cancer staging yielded a better prognostic predictive efficacy compared with the two indexes alone (P < .001, area under curve: 0.752). Finally, a nomogram was created by integrating the IHC markers and clinicopathological risk factors to predict prognosis with a C-index of 0.695 (95% confidence interval: 0.657-0.734). CONCLUSION:Using an integrated multistage screening strategy, we identified and validated a valuable prognostic IHC panel for ESCC.

SUBMITTER: Yu Y

PROVIDER: S-EPMC6970036 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Integrated analysis of genomic and transcriptomic profiles identified a prognostic immunohistochemistry panel for esophageal squamous cell cancer.

Yu Yue Y Li Zhihua Z Huang Chenjun C Fang Haisheng H Zhao Fei F Zhou Yue Y Pan Xianglong X Li Qifan Q Zhuang Yu Y Chen Liang L Xu Jing J Wang Wei W

Cancer medicine 20191202 2

<h4>Background</h4>The poor outcome of patients with esophageal squamous cell carcinoma (ESCC) highlights the importance of the identification of novel effective prognostic biomarkers. We aimed to identify a clinically applicable prognostic immunohistochemistry (IHC) panel for ESCC.<h4>Methods</h4>An integrated analysis was performed to screen and establish a prognostic panel using exome sequencing profile from 81 pairs of ESCC samples and RNA expression microarray data from 119 ESCC subjects. T ...[more]

PMID: 31793228

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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.

Dataset Information

Integrated analysis of genomic and transcriptomic profiles identified a prognostic immunohistochemistry panel for esophageal squamous cell cancer.

Publications

Integrated analysis of genomic and transcriptomic profiles identified a prognostic immunohistochemistry panel for esophageal squamous cell cancer.

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