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  • br Fig Genome wide discovery of a gene

    2019-10-07


    Fig. 1. Genome-wide discovery of a gene Cucurbitacin I signature for the identification of lymph node metastasis status in early gastric cancers (GC). (A) Heatmap illustrating the expression levels of the genes expressed between patients with lymph node-positive (LNP) and lymph node-negative (LNN) gastric cancers. Of these, 84 genes were differentially expressed between LNP and LNN patients in the training dataset of 18 TCGA T1 patients. (B) ROC curve shows the diagnostic performance of the 15-gene signature for discriminating LNP from LNN TCGA T1 patients. (C) Waterfall plot shows the LN risk scores by LN status in the TCGA T1 and T2 cohort, and the ROC curve demonstrates the diagnostic performance in the expanded set of TCGA T1 and T2 patients. (D) Waterfall plot illustrates the risk scores by LN status and the its diagnostic potential in an independent set of ACRG T2 patients.
    Tumor markers
    TruePositive 75%
    False Positive
    Tumor markers
    Positive 75%
    False Positive
    Comparison with CT
    Positive 75%
    False Positive
    Combination with clinical factors
    Positive 75%
    False Positive
    Fig. 2. Clinical validations of the 15-gene signature in identification of lymph node metastasis status in early GC. ROC curves show that our novel 15-gene signature had a higher diagnostic value for identification of LN metastasis over CEA and CA19_9 in (A) clinical cohort-1 (testing) and (B) clinical cohort-2 (validation), respectively. (C) ROC curves illustrate that the 15-gene signature had a higher performance compared to the clinical LN status determined by CT in clinical cohort-2. Comparison of AUC values were conducted by DeLong test (D) ROC curves illustrate that the combinatorial model integrating the 15-gene signature and clinical N stage further improved the predictive accuracy in clinical cohort 2.
    In the past, a few studies have attempted to identify gene-expression-based biomarkers that may facilitate identification of LN metastasis in GC patients using cDNA microarrays [23–25]. However, to the best of our knowledge, ours is the first study to perform a system-atic and comprehensive biomarker discovery from multiple RNA-Seq based datasets. Second, we performed validation of our discovered bio-markers in multiple, independent, datasets from publicly available re-sources, followed by confirmation of our results in in-house, clinical patient cohorts. Third, we focused our biomarker discovery and valida-tion effort specifically in early-stage cancers, because excessive surgical treatment in these individuals have long-term consequences with ad-verse quality of life. Fourth, we compared the performance of our bio-markers with various tumor markers and CT imaging results, and successfully demonstrated the superiority of our signature over these with currently used modalities in the clinical settings.
    One of the potential limitations of our study is that retrospective clin-ical cohorts were used for the development of the gene panel. In addi-tion, one of the limitations of the present study is that we used frozen tissue and FFPE-derived RNA from resected tissues. Considering that MTOC gene-signature will be examined in pre-surgical biopsy specimens in a clinical setting, further prospective trials are required to examine the robustness and performance of our 15-gene signature in fresh biopsy tissues. Furthermore, another limitation was that the sample size for bio-marker discovery was limited. Since one of the primary objectives of our study was to identify biomarkers for early-stage gastric cancers, we fo-cused on patients with T1 cases with LN metastasis, which further 
    reduced the total number of patients during the discovery phase. Conse-quently, we were limited to deriving our gene-signature with the lim-ited sample size, and could not fully utilize appropriate power calculations for biomarker discovery. Therefore, we would like to ac-knowledge this potential limitation of our study, that our effort would have been more comprehensive, if we had an access to larger cohorts of patients with T1 LN metastasis, which will likely require a multi-institutional effort given the rarity of this disease. Nevertheless, the reassuring aspect of our study is that regardless of this concern, 15-gene signature was successfully able to identify LN in GC patients, and was superior to both currently used tumor markers (CEA and CA-19-9) as well as CT imaging. Although the further clinical validation is required using a large prospective cohort, our gene signature was able to discrim-inate LNP patients from LNN patients using surgically resected sample.