Cancer RNA-Seq Nexus: a database of phenotype-specific transcriptome profiling in cancer cells

Li, Jian Rong; Sun, Chuan; Li, Wenyuan; Chao, Rou Fang; Huang, Chieh-Chen; Zhou, Xianghong Jasmine; Liu, Chun Chi

doi:10.1093/nar/gkv1282

Cited by 104 publications

(91 citation statements)

References 36 publications

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“…We further combined the results of differentially expressed genes of gastric cancer from the Cancer RNA‐seq Nexus database, which includes information on differentially expressed lncRNAs and protein‐coding genes in multiple cancer types (Li, Sun, et al., ), and recovered the same differentially expressed lncRNAs and protein‐coding genes in the same direction as the metabolism‐associated genes in gastric cancer. In total, we found eight upregulated lncRNAs and 25 upregulated protein‐coding genes, one downregulated lncRNA and 20 downregulated protein‐coding genes that may be involved in metabolism in gastric cancer (Figure c).…”

Section: Resultsmentioning

confidence: 99%

Identification and functional annotation of metabolism‐associated lncRNAs and their related protein‐coding genes in gastric cancer

Xie

et al. 2018

Molec Gen & Gen Med

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BackgroundLong noncoding RNAs (lncRNAs) play important roles in carcinogenesis. However, the roles of metabolism‐associated lncRNAs in cancers are still unclear.MethodsA microarray of metabolism‐associated lncRNAs was used to detect their expression patterns between gastric cancer and paired nontumorous tissues. Its results and gastric cancer differential gene expression data from public databases were used to screen the metabolic pathway‐associated lncRNAs. A metabolic network with microRNAs (miRNAs), lncRNAs, and protein‐coding genes was further constructed. Finally, the expression of TOPORS antisense RNA 1 (TOPORS‐AS1), a screened highly expressed lncRNA and its associated protein‐coding gene, NADH: ubiquinone oxidoreductase subunit B6 (NDUFB6), were verified by reverse transcription polymerase chain reaction.ResultsA total of eight upregulated and one downregulated lncRNAs and 25 upregulated and 20 downregulated protein‐coding genes were found to be involved in metabolism in gastric cancer. Within the lncRNAs–miRNAs–mRNAs metabolic network, 78 miRNA‐target links, 546 positive coexpression relationships, and 191 protein–protein interactions were found. The expression of TOPORS‐AS1 and its associated gene, NDUFB6 in gastric cancer tissues was significantly lower than that in adjacent nontumor tissues. Moreover, NDUFB6 expression was associated with the invasion and distal metastasis of gastric cancer.ConclusionsThe metabolism‐associated lncRNAs play important roles in the occurrence of gastric cancer.

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Section: Resultsmentioning

confidence: 99%

Identification and functional annotation of metabolism‐associated lncRNAs and their related protein‐coding genes in gastric cancer

Xie

et al. 2018

Molec Gen & Gen Med

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“…Data analyses using 2 −ΔΔCt method showed that the relative mRNA expression of lipin‐1 was upregulated in 38 of 55 BC samples (69.1%) at more than three‐fold change, in tumor tissues in comparison with adjacent normal tissues ( p < .05; Figure 2c). The expression profile of lipin‐1 in BC tumor and normal tissue was also explored in GEO data sets, GSE58135 and GSE52194 from the in silico analysis tool, Cancer RNA‐seq Nexus, indicating overexpression of various lipin‐1 isoforms in BC as depicted in Figure 2d; http://syslab4.nchu.edu.tw/; Li et al, 2015).…”

Section: Resultsmentioning

confidence: 99%

Expression and clinicopathological significance of lipin‐1 in human breast cancer and its association with p53 tumor suppressor gene

Dinarvand

Khanahmad

Hakimian

et al. 2020

Journal Cellular Physiology

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Breast cancer (BC) is an important cause of female cancer‐related death. It has recently been demonstrated that metabolic disorders including lipid metabolism are a hallmark of cancer cells. Lipin‐1 is an enzyme that displays phosphatidate phosphatase activity and regulates the rate‐limiting step in the pathway of triglycerides and phospholipids synthesis. The objective of this study was to evaluate lipin‐1 expression, its prognostic significance, and its correlation with p53 tumor suppressor in patients with BC. In this study, 55 pairs of fresh samples of BC and adjacent noncancerous tissue were used to analyze lipin‐1, using quantitative real‐time polymerase chain reaction and immunohistochemistry (IHC) staining. The expression of other clinicopathological variables and p53 was also examined using IHC technique. The cell migration was studied in MCF‐7 and MDA‐MB231 cells following the inhibition of lipin‐1 by propranolol. Our results show that the relative expression of lipin‐1 messenger RNA was significantly higher in BC tissues compared with the adjacent normal tissue and its inhibition reduced cell migration in cancer cells. This upregulation was negatively correlated with histological grade of tumor and p53 status (p = .001 and p = .034) respectively and positively correlated with the tumor size (p = .006). Our results also seem to indicate that the high lipin‐1 expression is related to a good prognosis in patients with BC. The expression of lipin‐1 may be considered as a novel independent prognostic factor. The inhibition of lipin‐1 may also have therapeutic significance for patients with BC. The correlation between lipin‐1 and p53 confirms the role of p53 in the regulation of lipid metabolism in cancer cells.

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“…Emphasis needs to be placed on model-based biomarker development that ensures the right patients are identified to receive and likely benefit from the treatment. Lastly, significant advances are also being made in cancer ‘omics’; the recent collection and public availability of multi-‘omics’ databases (with accompanying clinical data) such as The Cancer Genome Atlas and more recently, the Cancer RNA-Seq Nexus [205], have and will enable cancer discoveries such as that of new oncogenic drivers and biomarkers. These headways in understanding the complex molecular landscape in patients, coupled with advances in tumor modeling and biomarker development, will pave the way for increased success in understanding, treating and preventing cancer.…”

Section: New Opportunities and Challenges In 3d Tumor Modelingmentioning

confidence: 99%

Heralding a new paradigm in 3D tumor modeling

et al. 2016

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Numerous studies to date have contributed to a paradigm shift in modeling cancer, moving from the traditional two-dimensional culture system to three-dimensional (3D) culture systems for cancer cell culture. This led to the inception of tumor engineering, which has undergone rapid advances over the years. In line with the recognition that tumors are not merely masses of proliferating cancer cells but rather, highly complex tissues consisting of a dynamic extracellular matrix together with stromal, immune and endothelial cells, significant efforts have been made to better recapitulate the tumor microenvironment in 3D. These approaches include the development of engineered matrices and co-cultures to replicate the complexity of tumor-stroma interactions in vitro. However, the tumor engineering and cancer biology fields have traditionally relied heavily on the use of cancer cell lines as a cell source in tumor modeling. While cancer cell lines have contributed to a wealth of knowledge in cancer biology, the use of this cell source is increasingly perceived as a major contributing factor to the dismal failure rate of oncology drugs in drug development. Backing this notion is the increasing evidence that tumors possess intrinsic heterogeneity, which predominantly homogeneous cancer cell lines poorly reflect. Tumor heterogeneity contributes to therapeutic resistance in patients. To overcome this limitation, cancer cell lines are beginning to be replaced by primary tumor cell sources, in the form of patient-derived xenografts and organoids cultures. Moving forward, we propose that further advances in tumor engineering would require that tumor heterogeneity (tumor variants) be taken into consideration together with tumor complexity (tumor-stroma interactions). In this review, we provide a comprehensive overview of what has been achieved in recapitulating tumor complexity, and discuss the importance of incorporating tumor heterogeneity into 3D in vitro tumor models. This work carves out the roadmap for 3D tumor engineering and highlights some of the challenges that need to be addressed as we move forward into the next chapter.

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Cancer RNA-Seq Nexus: a database of phenotype-specific transcriptome profiling in cancer cells

Cited by 104 publications

References 36 publications

Identification and functional annotation of metabolism‐associated lncRNAs and their related protein‐coding genes in gastric cancer

Identification and functional annotation of metabolism‐associated lncRNAs and their related protein‐coding genes in gastric cancer

Expression and clinicopathological significance of lipin‐1 in human breast cancer and its association with p53 tumor suppressor gene

Heralding a new paradigm in 3D tumor modeling

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