Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UMLS:C0027627 (metastases)
 103,950 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Lymphatic metastasis of pancreatic cancer is a predictor of poor prognosis. However, the molecular mechanisms are largely unknown, thus, making the development of appropriate cell lines and experimental models critically important for future investigations. The purpose of the present study was to establish a 'pancreatic cancer cell and mouse model with high lymphatic metastasis potential' for in-depth study of the underlying mechanisms. The BxPC-3-LN subline, derived from the BxPC-3 human pancreatic cancer cell line, was established through serial passages in nude mice via footpad injections. The subline was able to develop notable lymphatic metastases in 100% of the recipient mice 8 weeks after tumor cell implantation. Compared with the parental BxPC-3 cells, BxPC-3-LN cells were more aggressive, displaying invasive ultrastructure, increased migration and invasion ability, and chemoresistance. Metastasis-related gene alteration including upregulation of MMP14, MMP24, MIF and ADRM1, and downregulation of TGFB2 and ROBO1 were also observed in BxPC-3-LN cells by cDNA microarrays. Thus, the newly selected BxPC-3-LN subline can serve as a unique model for further study of lymphatic metastasis of pancreatic cancer.
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PMID:Development of a unique mouse model for pancreatic cancer lymphatic metastasis. 2294 45

Metastasis is the leading cause of death in people with lung cancer, yet the molecular effectors underlying tumor dissemination remain poorly defined. Through the development of an in vivo spontaneous lung cancer metastasis model, we show that the developmentally regulated transcriptional repressor Capicua (CIC) suppresses invasion and metastasis. Inactivation of CIC relieves repression of its effector ETV4, driving ETV4-mediated upregulation of MMP24, which is necessary and sufficient for metastasis. Loss of CIC, or an increase in levels of its effectors ETV4 and MMP24, is a biomarker of tumor progression and worse outcomes in people with lung and/or gastric cancer. Our findings reveal CIC as a conserved metastasis suppressor, highlighting new anti-metastatic strategies that could potentially improve patient outcomes.
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PMID:Inactivation of Capicua drives cancer metastasis. 2786 30

BACKGROUND Tyrosine kinase inhibitors (TKIs) are used to treat metastatic disease associated with clear cell renal cell carcinoma (ccRCC); however, most patients develop resistance after 6 to 15 months. As such, identifying biomarkers of TKI resistance may be useful for prognosis. MATERIAL AND METHODS We analyzed ChIP-seq data related to TKI resistance from the Gene Expression Omnibus and RNA-Seq and clinical data from The Cancer Genome Atlas database. We used univariate Cox analysis and Cox regression/Lasso analysis to determine a risk score. The Kaplan-Meier estimate and receiver operating characteristic curve verified the risk score's sensitivity and specificity. The stratified analysis and the univariate and multivariate analyses revealed its predictive power. We predicted survival time by constructing a nomogram. RESULTS Of the 32 differentially expressed genes (DEGs) related to TKI resistance, 6 (ACE2, MMP24, SLC44A4, C1R, C1ORF194, ADAMTS15) were used to establish a risk score. Kaplan-Meier analysis showed that high-risk patients had shorter median survival times than low-risk patients, notably among those with metastatic disease (1.51 vs. 4.55 years). The stratified analysis revealed that patients with advanced disease had relatively higher risk scores than patients at early stages (P<0.001). Univariate analysis independently associated the 6-DEGs signature with the prognosis of metastatic ccRCC (hazard ratio, 1.217; 95% confidence interval, 1.090-1.358). The nomogram we constructed based on 6-DEGs signature and clinical parameters predicted survival time accurately. CONCLUSIONS We identified a 6-DEGs signature that permitted us to establish a risk score related to TKI resistance that can serve as a reliable biomarker for predicting the survival of patients with ccRCC.
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PMID:Identification of a 6-Gene Signature Associated with Resistance to Tyrosine Kinase Inhibitors: Prognosis for Clear Cell Renal Cell Carcinoma. 3329 52