A pathway-based approach for identifying biomarkers of tumor progression to trastuzumab-resistant breast cancer.
Nam Seungyoon,Chang Hae Ryung,Jung Hae Rim,Gim Youme,Kim Nam Youl,Grailhe Regis,Seo Haeng Ran,Park Hee Seo,Balch Curt,Lee Jinhyuk,Park Inhae,Jung So Youn,Jeong Kyung-Chae,Powis Garth,Liang Han,Lee Eun Sook,Ro Jungsil,Kim Yon Hui
Although trastuzumab is a successful targeted therapy for breast cancer patients with tumors expressing HER2 (ERBB2), many patients eventually progress to drug resistance. Here, we identified subpathways differentially expressed between trastuzumab-resistant vs. -sensitive breast cancer cells, in conjunction with additional transcriptomic preclinical and clinical gene datasets, to rigorously identify overexpressed, resistance-associated genes. From this approach, we identified 32 genes reproducibly upregulated in trastuzumab resistance. 25 genes were upregulated in drug-resistant JIMT-1 cells, which also downregulated HER2 protein by >80% in the presence of trastuzumab. 24 genes were downregulated in trastuzumab-sensitive SKBR3 cells. Trastuzumab sensitivity was restored by siRNA knockdown of these genes in the resistant cells, and overexpression of 5 of the 25 genes was found in at least one of five refractory HER2 + breast cancer. In summary, our rigorous computational approach, followed by experimental validation, significantly implicate ATF4, CHEK2, ENAH, ICOSLG, and RAD51 as potential biomarkers of trastuzumab resistance. These results provide further proof-of-concept of our methodology for successfully identifying potential biomarkers and druggable signal pathways involved in tumor progression to drug resistance.
Systematic analysis of ovarian cancer platinum-resistance mechanisms via text mining.
Li Haixia,Li Jinghua,Gao Wanli,Zhen Cheng,Feng Limin
Journal of ovarian research
BACKGROUND:Platinum resistance is an important cause of clinical recurrence and death for ovarian cancer. This study tries to systematically explore the molecular mechanisms for platinum resistance in ovarian cancer and identify regulatory genes and pathways via text mining and other methods. METHODS:Genes in abstracts of associated literatures were identified. Gene ontology and protein-protein interaction (PPI) network analysis were performed. Then co-occurrence between genes and ovarian cancer subtypes were carried out followed by cluster analysis. RESULTS:Genes with highest frequencies are mostly involved in DNA repair, apoptosis, metal transport and drug detoxification, which are closely related to platinum resistance. Gene ontology analysis confirms this result. Some proteins such as TP53, HSP90, ESR1, AKT1, BRCA1, EGFR and CTNNB1 work as hub nodes in PPI network. According to cluster analysis, specific genes were highlighted in each subtype of ovarian cancer, indicating that various subtypes may have different resistance mechanisms respectively. CONCLUSIONS:Platinum resistance in ovarian cancer involves complicated signaling pathways and different subtypes may have specific mechanisms. Text mining, combined with other bio-information methods, is an effective way for systematic analysis.
Genetic Aberrations and Interaction of NEK2 and TP53 Accelerate Aggressiveness of Multiple Myeloma.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
It has been previously shown that (never in mitosis gene A)-related kinase 2 (NEK2) is upregulated in multiple myeloma (MM) and contributes to drug resistance. However, the mechanisms behind this upregulation remain poorly understood. In this study, it is found that amplification of NEK2 and hypermethylation of distal CpG islands in its promoter correlate strongly with increased NEK2 expression. Patients with NEK2 amplification have a poor rate of survival and often exhibit TP53 deletion, which is an independent prognostic factor in MM. This combination of TP53 knockout and NEK2 overexpression induces asymmetric mitosis, proliferation, drug resistance, and tumorigenic behaviors in MM in vitro and in vivo. In contrast, delivery of wild type p53 and suppression of NEK2 in TP53 MM cell lines inhibit tumor formation and enhance the effect of Bortezomib against MM. It is also discovered that inactivating p53 elevates NEK2 expression genetically by inducing NEK2 amplification, transcriptionally by increased activity of cell cycle-related genes like E2F8 and epigenetically by upregulating DNA methyltransferases. Dual defects of TP53 and NEK2 may define patients with the poorest outcomes in MM with p53 inactivation, and NEK2 may serve as a novel therapeutic target in aggressive MM with p53 abnormalities.
Clinical and genomic landscape of gastric cancer with a mesenchymal phenotype.
Oh Sang Cheul,Sohn Bo Hwa,Cheong Jae-Ho,Kim Sang-Bae,Lee Jae Eun,Park Ki Cheong,Lee Sang Ho,Park Jong-Lyul,Park Yun-Yong,Lee Hyun-Sung,Jang Hee-Jin,Park Eun Sung,Kim Sang-Cheol,Heo Jeonghoon,Chu In-Sun,Jang You-Jin,Mok Young-Jae,Jung WonKyung,Kim Baek-Hui,Kim Aeree,Cho Jae Yong,Lim Jae Yun,Hayashi Yuki,Song Shumei,Elimova Elena,Estralla Jeannelyn S,Lee Jeffrey H,Bhutani Manoop S,Lu Yiling,Liu Wenbin,Lee Jeeyun,Kang Won Ki,Kim Sung,Noh Sung Hoon,Mills Gordon B,Kim Seon-Young,Ajani Jaffer A,Lee Ju-Seog
Gastric cancer is a heterogeneous cancer, making treatment responses difficult to predict. Here we show that we identify two distinct molecular subtypes, mesenchymal phenotype (MP) and epithelial phenotype (EP), by analyzing genomic and proteomic data. Molecularly, MP subtype tumors show high genomic integrity characterized by low mutation rates and microsatellite stability, whereas EP subtype tumors show low genomic integrity. Clinically, the MP subtype is associated with markedly poor survival and resistance to standard chemotherapy, whereas the EP subtype is associated with better survival rates and sensitivity to chemotherapy. Integrative analysis shows that signaling pathways driving epithelial-to-mesenchymal transition and insulin-like growth factor 1 (IGF1)/IGF1 receptor (IGF1R) pathway are highly activated in MP subtype tumors. Importantly, MP subtype cancer cells are more sensitive to inhibition of IGF1/IGF1R pathway than EP subtype. Detailed characterization of these two subtypes could identify novel therapeutic targets and useful biomarkers for prognosis and therapy response.