Dataset Information

Personalized four-category staging for predicting prognosis in patients with small bowel Adenocarcinoma: an international development and validation study.

ABSTRACT: BACKGROUND:Log odds of positive lymph nodes (LODDS) classification showed superiority over 8th edition N staging in predicting survival of small bowel adenocarcinoma (SBA) patients. The aim of this study was to develop and validate the Tumor, LODDS, and Metastasis (TLM) staging of SBA. METHODS:Totally 1789 SBA patients from the Surveillance, Epidemiology, and End Results (SEER) database between 1988-2010, 437 patients from SEER database between 2011-2013 and 166 patients from multicenters were categorized into development, validation and test cohort, respectively. The TLM staging was developed in the development cohort using Ensemble Algorithm for Clustering Cancer Data (EACCD) method. C-index was used to assess the performance of the TLM staging in predicting cancer-specific survival (CSS) and was compared with the traditional 8th edition TNM staging. FINDINGS:Four-category TLM staging designed for the development cohort showed higher discriminatory power than TNM staging in predicting CSS in the development cohort (0.682 vs. 0.650, P < 0.001), validation cohort (0.682 vs. 0.654, P = 0.022), and test cohort (0.659 vs. 0.611, P = 0.023), respectively. TLM staging continued to show its higher predictive efficacy than the 8th TNM in TNM stage II/III patients or in patients with lymph node yield less than 8. INTERPRETATION:TLM staging showed a better prognostic performance than the 8th TNM staging especially TNM stage II/III or patients with lymph node yield less than 8 and therefore, could serve to complement the TNM staging in patients with SBA. FUNDING:A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.

SUBMITTER: Dai ZH

PROVIDER: S-EPMC7519244 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Personalized four-category staging for predicting prognosis in patients with small bowel Adenocarcinoma: an international development and validation study.

Dai Zi-Hao ZH Wang Qi-Wen QW Zhang Qing-Wei QW Yan Xia-Lin XL Aparicio Thomas T Zhou Yang-Yang YY Wang Huan H Zhang Chi-Hao CH Zaanan Aziz A Afchain Pauline P Zhang Yan Y Chen Hui-Min HM Gao Yun-Jie YJ Ge Zhi-Zheng ZZ

EBioMedicine 20200924

<h4>Background</h4>Log odds of positive lymph nodes (LODDS) classification showed superiority over 8<sup>th</sup> edition N staging in predicting survival of small bowel adenocarcinoma (SBA) patients. The aim of this study was to develop and validate the Tumor, LODDS, and Metastasis (TLM) staging of SBA.<h4>Methods</h4>Totally 1789 SBA patients from the Surveillance, Epidemiology, and End Results (SEER) database between 1988-2010, 437 patients from SEER database between 2011-2013 and 166 patient ...[more]

PMID: 32980692

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Project description:Lung adenocarcinoma (LAD) is difficult to diagnose as it tends to be small in size and metastasize early. The aim of the present study was to investigate prognostic factors for patients with LAD and establish a prognosis risk model. A training set consisting of clinical and RNA sequencing data from 503 patients with LAD, as well as expression data from a further 59 LAD and adjacent tissues, was obtained from The Cancer Genome Atlas. Additionally, a validation dataset was acquired from the Gene Expression Omnibus database (GSE26939), which included clinical and gene expression data from 115 patients. Using the DESeq2 package to compare expression between LAD and adjacent tissues, differentially expressed genes (DEGs) were identified. On the basis of survival and the random forests for survival, regression and classification package, genes for constructing the prognosis risk model were selected. The prognosis risk model was constructed and validated using the survival package. Subsequently, high- and low-risk groups were compared using the Limma package to identify DEGs, and enrichment analysis was performed using the web-based gene set analysis toolkit. A protein-protein interaction network was visualized using Cytoscape software. There were 18,567 DEGs between the LAD samples and the adjacent tissues, and 363 DEGs between the high- and low-risk groups. Of these, four genes were selected for constructing the prognosis risk model, myosin IE (MYO1E), endoplasmic reticulum oxidoreductase 1α (ERO1L), C1q and tumor necrosis factor-related protein 6 (C1QTNF6) and family with sequence similarity 83, member A (FAM83A). The survival time of high- and low-risk groups in the validation set were significantly different. Functional enrichment revealed that the genes that interacted with MYO1E, ERO1L, C1QTNF6 and FAM83A separately were enriched in 'cell cycle regulation', 'synthesis and assembly of nucleic acids', 'histone modification and cell cycle progression' and 'cell secretion process'. The four-gene prognosis risk model could potentially be used for predicting the survival of patients with LAD.

Project description:Background: Lung adenocarcinoma (LUAD) is one of the main types of lung cancer. Because of its low early diagnosis rate, poor late prognosis, and high mortality, it is of great significance to find biomarkers for diagnosis and prognosis. Methods: Five hundred and twelve LUADs from The Cancer Genome Atlas were used for differential expression analysis and short time-series expression miner (STEM) analysis to identify the LUAD-development characteristic genes. Survival analysis was used to identify the LUAD-unfavorable genes and LUAD-favorable genes. Gene set variation analysis (GSVA) was used to score individual samples against the two gene sets. Receiver operating characteristic (ROC) curve analysis and univariate and multivariate Cox regression analysis were used to explore the diagnostic and prognostic ability of the two GSVA score systems. Two independent data sets from Gene Expression Omnibus (GEO) were used for verifying the results. Functional enrichment analysis was used to explore the potential biological functions of LUAD-unfavorable genes. Results: With the development of LUAD, 185 differentially expressed genes (DEGs) were gradually upregulated, of which 84 genes were associated with LUAD survival and named as LUAD-unfavorable gene set. While 237 DEGs were gradually downregulated, of which 39 genes were associated with LUAD survival and named as LUAD-favorable gene set. ROC curve analysis and univariate/multivariate Cox proportional hazards analyses indicated both of LUAD-unfavorable GSVA score and LUAD-favorable GSVA score were a biomarker of LUAD. Moreover, both of these two GSVA score systems were an independent factor for LUAD prognosis. The LUAD-unfavorable genes were significantly involved in p53 signaling pathway, Oocyte meiosis, and Cell cycle. Conclusion: We identified and validated two LUAD-development characteristic gene sets that not only have diagnostic value but also prognostic value. It may provide new insight for further research on LUAD.

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Dataset Information

Personalized four-category staging for predicting prognosis in patients with small bowel Adenocarcinoma: an international development and validation study.

Publications

Personalized four-category staging for predicting prognosis in patients with small bowel Adenocarcinoma: an international development and validation study.

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