Cross-Database Analysis Reveals Sensitive Biomarkers for Combined Therapy for ERBB2+ Gastric Cancer

Xiang, Zhen; Huang, Xia; Wang, Jiexuan; Zhang, Jun; Ji, Jun; Yan, Ranlin; Zhu, Zhenggang; Cai, Wei; Yu, Yingyan

doi:10.3389/fphar.2018.00861

Cited by 17 publications

(16 citation statements)

References 57 publications

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“…The total protein, cytoplasmic protein and nuclear protein were extracted separately, and Western blot was performed as previously described [17, 19]. The antibodies used in this study were presented in Additional file 3: Table S3.…”

Section: Methodsmentioning

confidence: 99%

“…GSEA analysis was performed as previous study [17]. Other statistics were performed using GraphPad Prism 6.0 (Inc., La Jolla, CA, United States).…”

Section: Methodsmentioning

confidence: 99%

“…For instance, we reported expression levels of ERBB2 and RARA in GC cell lines were positively correlated with the sensitivity of ERBB2 targeted therapy. We also found that lncRNAs GIHCG and SPINT1-AS1 could regulate lapatinib sensitivity of cancer cells based on the CCLE analysis [17, 18].…”

Section: Introductionmentioning

confidence: 99%

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A positive feedback between IDO1 metabolite and COL12A1 via MAPK pathway to promote gastric cancer metastasis

Xiang

Song

et al. 2019

J Exp Clin Cancer Res

Self Cite

106

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Background IDO1 (Indoleamine 2,3-dioxygenase 1) inhibits host anti-tumor immune response by exhausting tryptophan in tumor microenvironment, but the pathogenic mechanisms of IDO1 in gastric cancer (GC) cells need to be further explored. Methods The aim of this study was to use CCLE (Cancer Cell Line Encyclopedia) transcriptomic data of GC cell lines for WGCNA (Weighted Gene Co-expression Network Analysis) analysis, and explore the potential functions and mechanisms of IDO1 in GC progression in vitro and in vivo. Results The higher expression level of IDO1 was identified in 4 out of 7 GC cell lines. Increased IDO1 expression strongly promoted cell migration via its metabolite kynurenine and was associated with pathways of immune activation according to GSEA (Gene Set Enrichment Analysis). The functions of IDO1 were closely associated with extracellular matrix, collagen metabolic and catabolic process by WGCNA analysis. Among five hub genes ( AXL , SGCE , COL12A1 , ANTXR1 , LOXL2 ), COL12A1 and LOXL2 were upregulated in GC tissues. IDO1 disclosed positive correlation with six collagen genes by coefficient matrix diagram. Knockdown of IDO1 decreased the expression of LOXL2, COL6A1, COL6A2 and COL12A1 in GC cells in both mRNA and protein levels. Of them, knockdown of COL12A1 inhibited cell migration more apparently than knockdown of others. IDO1 and COL12A1 revealed synergistic efficacy on promoting cell migration via a positive feedback sustained by MAPK pathway. This bioprocess was mediated by IDO1 metabolite kynurenine and integrin β1. A popliteal lymph nodemetastasis model was established for verifying metastatic promotion of IDO1 and COL12A1 in GC. Conclusions IDO1 and COL12A1 synergistically promoted GC metastasis. The novel findings suggested that both IDO1 and COL12A1 may be promising targets on anti-cancer treatment in GC. Electronic supplementary material The online version of this article (10.1186/s13046-019-1318-5) contains supplementary material, which is available to authorized users.

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Section: Methodsmentioning

confidence: 99%

“…GSEA analysis was performed as previous study [17]. Other statistics were performed using GraphPad Prism 6.0 (Inc., La Jolla, CA, United States).…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

A positive feedback between IDO1 metabolite and COL12A1 via MAPK pathway to promote gastric cancer metastasis

Xiang

Song

et al. 2019

J Exp Clin Cancer Res

Self Cite

106

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“…PI3K/Akt, Ras/Raf/MEK/ERK1/2, and PLCγ pathways are downstream pathways of EGFR and ERBB2 and play important roles in cell proliferation and survival of multiple cancers (Roskoski, 2014). The expression levels of EGFR and ERBB2 are positively correlated to Lapatinib sensitivity (Rusnak et al, 2007; Xiang et al, 2018). Trastuzumab (Herceptin) is a molecular targeted drug of ERBB2-positive metastatic/advanced breast cancer and gastric cancer (Bang et al, 2010; Loibl and Gianni, 2017).…”

Section: Discussionmentioning

confidence: 99%

LncRNAs GIHCG and SPINT1-AS1 Are Crucial Factors for Pan-Cancer Cells Sensitivity to Lapatinib

et al. 2019

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Lapatinib is a small molecule inhibitor of EGFR (HER1) and ERBB2 (HER2) receptors, which is used for treatment of advanced or metastatic breast cancer. To find the drug resistance mechanisms of treatment for EGFR/ERBB2 positive tumors, we analyzed the possible effects of lncRNAs. In this study, using CCLE (Cancer Cell Line Encyclopedia) database, we explored the relationship between the lncRNAs and Lapatinib sensitivity/resistance, and then validated those findings through in vitro experiments. We found that the expression of EGFR/ERBB2 and activation of ERBB pathway was significantly related to Lapatinib sensitivity. GO (Gene Oncology) analysis of top 10 pathways showed that the sensitivity of Lapatinib was positively correlated with cell keratin, epithelial differentiation, and cell-cell junction, while negatively correlated with signatures of extracellular matrix. Forty-four differentially expressed lncRNAs were found between the Lapatinib sensitive and resistant groups (fold-change > 1.5, P < 0.01). Gene set variation analysis (GSVA) was performed based on 44 lncRNAs and genes in the top 10 pathways. Five lncRNAs were identified as hub molecules. Co-expression network was constructed by more than five lncRNAs and 199 genes in the top 10 pathways, and three lncRNAs (GIHCG, SPINT1-AS1, and MAGI2-AS3) and 47 genes were identified as close-related molecules. The three lncRNAs in epithelium-derived cancers were differentially expressed between sensitive and resistant groups, but no significance was found in non-epithelium-derived cancer cells. Correlation analysis showed that SPINT1-AS1 ( R = −0.715, P < 0.001) and GIHCG ( R = 0.557, P = 0.013) were correlated with the IC50 of epithelium-derived cancer cells. In further experiments, GIHCG knockdown enhanced cancer cell susceptibility to Lapatinib, while high level of SPINT1-AS1 was a sensitive biomarker of NCI-N87 and MCF7 cancer cells to Lapatinib. In conclusions, lncRNAs GIHCG and SPINT1-AS1 were involved in regulating Lapatinib sensitivity. Up-regulation of GIHCG was a drug-resistant biomarker, while up-regulation of SPINT1-AS1 was a sensitive indicator.

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“…It has been implicated in the regulation of development, differentiation, apoptosis, and transcription of clock genes. In a recent study, Xiang et al [39] find that RARA is a drug sensitive biomarker of ERBB2-targeted treatment. ERBB2related pathways can help us finding sensitive molecules and potential combined therapeutic targets of ERBB2targeted therapy for gastric cancer.…”

Section: Influential Genes From Functional and Pathway Enrichment Anamentioning

confidence: 99%

Identification of most influential co-occurring gene suites for gastrointestinal cancer using biomedical literature mining and graph-based influence maximization

Wang

Jin

Chang

et al. 2020

BMC Med Inform Decis Mak

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Background: Gastrointestinal (GI) cancer including colorectal cancer, gastric cancer, pancreatic cancer, etc., are among the most frequent malignancies diagnosed annually and represent a major public health problem worldwide. Methods: This paper reports an aided curation pipeline to identify potential influential genes for gastrointestinal cancer. The curation pipeline integrates biomedical literature to identify named entities by Bi-LSTM-CNN-CRF methods. The entities and their associations can be used to construct a graph, and from which we can compute the sets of cooccurring genes that are the most influential based on an influence maximization algorithm. Results: The sets of co-occurring genes that are the most influential that we discover include RARA-CRBP1, CASP3-BCL2, BCL2-CASP3-CRBP1, RARA-CASP3-CRBP1, FOXJ1-RASSF3-ESR1, FOXJ1-RASSF1A-ESR1, FOXJ1-RASS F1A-TNFAIP8-ESR1. With TCGA and functional and pathway enrichment analysis, we prove the proposed approach works well in the context of gastrointestinal cancer. Conclusions: Our pipeline that uses text mining to identify objects and relationships to construct a graph and uses graph-based influence maximization to discover the most influential co-occurring genes presents a viable direction to assist knowledge discovery for clinical applications.

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Cross-Database Analysis Reveals Sensitive Biomarkers for Combined Therapy for ERBB2+ Gastric Cancer

Cited by 17 publications

References 57 publications

A positive feedback between IDO1 metabolite and COL12A1 via MAPK pathway to promote gastric cancer metastasis

A positive feedback between IDO1 metabolite and COL12A1 via MAPK pathway to promote gastric cancer metastasis

LncRNAs GIHCG and SPINT1-AS1 Are Crucial Factors for Pan-Cancer Cells Sensitivity to Lapatinib

Identification of most influential co-occurring gene suites for gastrointestinal cancer using biomedical literature mining and graph-based influence maximization

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