Analysis of lncRNA-Associated ceRNA Network Reveals Potential lncRNA Biomarkers in Human Colon Adenocarcinoma

Zhang, Zhiyuan; Qian, Wenwei; Wang, Sen; Ji, Dongjian; Wang, Qingyuan; Li, Jie; Peng, Wen; Gu, Jiou; Hu, Tao; Ji, Bing; Zhang, Yue; Wang, Shijia; Sun, Yueming

doi:10.1159/000493623

Cited by 79 publications

(83 citation statements)

References 26 publications

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“…KCNQ1OT1 also reached statistical significance in the validation set after multivariate analysis. Higher expression levels of KCNQ1OT1 have been shown in tissues from solid tumors including colorectal cancer, and lung adenocarcinoma compared to normal mucosa. Interestingly, high mRNA expression levels of KCNQ1OT1 were correlated with paclitaxel resistance in lung cancer patients.…”

Section: Discussionmentioning

confidence: 99%

“…This epigenetic deregulation impacts the β‐catenin signaling and may contribute to the CRC development . Very recently, KCNQ1OT1 was shown to be negatively associated with OS in stages I–IV CRC patients . Our finding is the first that suggests a relationship between KCNQ1OT1 expression levels and DFS of stage III CRC patients treated with fluoropyrimidine‐based chemotherapy.…”

Section: Discussionmentioning

confidence: 99%

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RNA sequencing reveals PNN and KCNQ1OT1 as predictive biomarkers of clinical outcome in stage III colorectal cancer patients treated with adjuvant chemotherapy

Mini

Lapucci

Perrone

et al. 2019

Intl Journal of Cancer

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Five‐year overall survival of stage III colorectal cancer (CRC) patients treated with standard adjuvant chemotherapy (ACHT) is highly variable. Genomic biomarkers and/or transcriptomic profiles identified lack of adequate validation. Aim of our study was to identify and validate molecular biomarkers predictive of ACHT response in stage III CRC patients by a transcriptomic approach. From a series of CRC patients who received ACHT, two stage III extreme cohorts (unfavorable vs. favorable prognosis) were selected. RNA‐sequencing was performed from fresh frozen explants. Tumors were characterized for somatic mutations. Validation was performed in stage III CRC patients extracted from two GEO datasets. According to disease‐free survival (DFS), 108 differentially expressed genes (104/4 up/downregulated in the unfavorable prognosis group) were identified. Among 104 upregulated genes, 42 belonged to olfactory signaling pathways, 62 were classified as pseudogenes (n = 17), uncharacterized noncoding RNA (n = 10), immune response genes (n = 4), microRNA (n = 1), cancer‐related genes (n = 14) and cancer‐unrelated genes (n = 16). Three out of four down‐regulated genes were cancer‐related. Mutational status (i.e., RAS, BRAF, PIK3CA) did not differ among the cohorts. In the validation cohort, multivariate analysis showed high PNN and KCNQ1OT1 expression predictive of shorter DFS in ACHT treated patients (p = 0.018 and p = 0.014, respectively); no difference was observed in untreated patients. This is the first study that identifies by a transcriptomic approach and validates PNN and KCNQ1OT1 as molecular biomarkers predictive of chemotherapy response in stage III CRC patients. After a further validation in an independent cohort, PNN and KCNQ1OT1 evaluation could be proposed to prospectively identify stage III CRC patients benefiting from ACHT.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

RNA sequencing reveals PNN and KCNQ1OT1 as predictive biomarkers of clinical outcome in stage III colorectal cancer patients treated with adjuvant chemotherapy

Mini

Lapucci

Perrone

et al. 2019

Intl Journal of Cancer

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“…In China, the incidence and mortality of CRC rank fifth and fourth, respectively [3]. Colon adenocarcinoma is one of the most common types of CRC [4] and has become more prevalent in recent years [5]. Comprehensive treatment based on multidisciplinary discussion has become the trend of CRC treatment.…”

Section: Introductionmentioning

confidence: 99%

INHBA is a prognostic predictor for patients with colon adenocarcinoma

Liang

et al. 2020

BMC Cancer

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Background: Colon adenocarcinoma (COAD) is one of the most lethal cancers. It is particularly important to accurately predict prognosis and to provide individualized treatment. Several lines of evidence suggest that genetic factors and clinicopathological characteristics are related to cancer onset and progression. The aim of this study was to identify potential prognostic genes and to develop a nomogram to predict survival and recurrence of COAD. Methods: To identify potential prognostic genes in COAD, microarray datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were obtained from GEO2R. Venn diagram was drawn to select those genes that were overexpressed in all datasets, and survival analyses were performed to determine the prognostic values of the selected genes. New nomograms were developed based on the genes that were significantly associated with prognosis. Clinicopathological data were obtained from The Cancer Genome Atlas (TCGA). Finally, the new nomograms were compared head-to-head comparison with the TNM nomogram.Results: From GSE21510, GSE110223, GSE113513 and GSE110224, a total of 834, 218, 236 and 613 overexpressed DEGs were screened out, respectively. The Venn diagram revealed that 12 genes appeared in all four profiles. After survival analyses, only INHBA expression was associated with both overall survival (OS) and disease-free survival (DFS). Multivariate analyses revealed that age, pathological N and pathological M were significant independent risk factors for OS. Age, pathological N, pathological M and INHBA were significant independent risk factors for DFS. Two prediction models predicted the probability of 3-year survival and 5-year survival for OS and DFS, respectively. The concordance indexes were 0.785 for 3-year overall survival, 0.759 for 5-year overall survival, 0.789 for 3-year disease-free survival and 0.757 for 5-year disease-free survival. The head-to-head comparison according to timedependent ROC curves indicated that the new models had higher predictive accuracy. Decision curve analyses (DCA) indicated that the clinical value of the new models were higher than TNM models for predicting disease-free survival.Conclusion: The combination of INHBA expression with a clinical nomogram improves prognostic power in colon adenocarcinoma, especially for predicting recurrence.

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“…Numerous studies on the role of lncRNAs in various types of cancers have been performed, and several lncRNA biomarkers have been identified to be related to the development, diagnosis and overall survival of various cancers [7][8][9][10][11]. Recently, lncRNA HOTAIR has been identified to be related to the overall survival in CA [12]. LncRNA ATB is associated with poor prognosis of CRC [13].…”

Section: Introductionmentioning

confidence: 99%

Integration analysis for novel lncRNA markers predicting tumor recurrence in human colon adenocarcinoma

Chen

Deng

et al. 2019

J Transl Med

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Background Numerous evidence has suggested that long non-coding RNA (lncRNA) acts an important role in tumor biology. This study focuses on the identification of novel prognostic lncRNA biomarkers predicting tumor recurrence in human colon adenocarcinoma. Methods We obtained the research data from The Cancer Genome Atlas (TCGA) database. The interaction among different expressed lncRNA, miRNA and mRNA markers between colon adenocarcinoma patients with and without tumor recurrence were verified with miRcode, starBase and miRTarBase databases. We established the lncRNA–miRNA–mRNA competing endogenous RNA (ceRNA) network based on the verified association between the selected markers. We performed the functional enrichment analysis to obtain better understanding of the selected lncRNAs. Then we use multivariate logistic regression to identify the prognostic lncRNA markers with covariates. We also generated a nomogram predicting tumor recurrence risk based on the identified lncRNA biomarkers and clinical covariates. Results We included 12,727 lncRNA, 1881 miRNA and 47,761 mRNA profiling and clinical features for 113 colon adenocarcinoma patients obtained from the TCGA database. After filtration, we used 37 specific lncRNAs, 60 miRNAs and 148 mRNAs in the ceRNA network analysis. We identified five lncRNAs as prognostic lncRNA markers predicting tumor recurrence in colon adenocarcinoma, in which four of them were identified for the first time. Finally, we generated a nomogram illustrating the association between the identified lncRNAs and the tumor recurrence risk in colon adenocarcinoma. Conclusions The four newly identified lncRNA biomarkers might be potential prognostic biomarkers predicting tumor recurrence in colon adenocarcinoma. We recommend that further clinical and fundamental researches be conducted on the identified lncRNA markers.

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Analysis of lncRNA-Associated ceRNA Network Reveals Potential lncRNA Biomarkers in Human Colon Adenocarcinoma

Cited by 79 publications

References 26 publications

RNA sequencing reveals PNN and KCNQ1OT1 as predictive biomarkers of clinical outcome in stage III colorectal cancer patients treated with adjuvant chemotherapy

RNA sequencing reveals PNN and KCNQ1OT1 as predictive biomarkers of clinical outcome in stage III colorectal cancer patients treated with adjuvant chemotherapy

INHBA is a prognostic predictor for patients with colon adenocarcinoma

Integration analysis for novel lncRNA markers predicting tumor recurrence in human colon adenocarcinoma

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