Project description:Background - Hepatocellular carcinomas (HCCs) are heterogeneous tumors with respect to etiology, cell of origin and biology. The course of the disease is unpredictable and is in part dependent on the tumor microenvironment. One of the microenvironmental factors is hypoxia, which is known to promote aggressiveness in other malignant tumors. We hypothesized that certain regions in HCC exist with chronic hypoxia and a characteristic gene expression pattern. Moreover, during the development of HCC there is an important contribution of this chronic hypoxia on prognosis via this gene expression. Until now, most research has been performed in acute hypoxic models (< 24 hours). Methods – Human hepatoblastoma cells HepG2 were cultured in either normoxic (20% O2) or hypoxic (2% O2) conditions for 72 hrs, the time it takes to adapt to chronic hypoxia. After 3 days the cells were harvested and analyzed by microarray technology. The highly significant differentially expressed genes were selected and used to assess the clinical value of our in vitro chronic hypoxia gene signature in four published patient studies. Three of these independent microarray studies on HCC patients were used as training sets to determine a minimal prognostic gene set and one study was used for validation. Gene expression analysis and correlation with clinical outcome was assessed with the bioinfomatic method of Goeman et al (). Results – In the HepG2 cells, 3592 genes were differentially expressed in cells cultured at 2% oxygen for 72 hrs. Out of these, 265 showed a high significant change (2-fold change and p=0.0001). The level of gene expression after 72 hrs was different from the acute hypoxic response (during the first 24 hours) and represented chronicity. Using computational methods we identified 7 out of the 265 highly significant genes that showed correlation with prognosis in all three different training sets and this was independently validated in a 4th dataset. With our approach we could include the largest number of HCC patients in one single study. Conclusion – We identified a 7-gene signature, which is associated with chronic hypoxia and predicts prognosis in patients with HCC. In the future this signature could be used as a diagnostic tool. In addition, chronic hypoxia gene expression information can be used in the search for new therapeutic targets. Two conditions were compared and each sample has a biological replicate. Samples are hybridized in dye-swap, resulting in 4 hybridizations.

Project description:Background - Hepatocellular carcinomas (HCCs) are heterogeneous tumors with respect to etiology, cell of origin and biology. The course of the disease is unpredictable and is in part dependent on the tumor microenvironment. One of the microenvironmental factors is hypoxia, which is known to promote aggressiveness in other malignant tumors. We hypothesized that certain regions in HCC exist with chronic hypoxia and a characteristic gene expression pattern. Moreover, during the development of HCC there is an important contribution of this chronic hypoxia on prognosis via this gene expression. Until now, most research has been performed in acute hypoxic models (< 24 hours). Methods – Human hepatoblastoma cells HepG2 were cultured in either normoxic (20% O2) or hypoxic (2% O2) conditions for 72 hrs, the time it takes to adapt to chronic hypoxia. After 3 days the cells were harvested and analyzed by microarray technology. The highly significant differentially expressed genes were selected and used to assess the clinical value of our in vitro chronic hypoxia gene signature in four published patient studies. Three of these independent microarray studies on HCC patients were used as training sets to determine a minimal prognostic gene set and one study was used for validation. Gene expression analysis and correlation with clinical outcome was assessed with the bioinfomatic method of Goeman et al (). Results – In the HepG2 cells, 3592 genes were differentially expressed in cells cultured at 2% oxygen for 72 hrs. Out of these, 265 showed a high significant change (2-fold change and p=0.0001). The level of gene expression after 72 hrs was different from the acute hypoxic response (during the first 24 hours) and represented chronicity. Using computational methods we identified 7 out of the 265 highly significant genes that showed correlation with prognosis in all three different training sets and this was independently validated in a 4th dataset. With our approach we could include the largest number of HCC patients in one single study. Conclusion – We identified a 7-gene signature, which is associated with chronic hypoxia and predicts prognosis in patients with HCC. In the future this signature could be used as a diagnostic tool. In addition, chronic hypoxia gene expression information can be used in the search for new therapeutic targets.

Project description:BACKGROUND:In breast cancer, activation of bone morphogenetic protein (BMP) signaling and elevated levels of BMP-antagonists have been linked to tumor progression and metastasis. However, the simultaneous upregulation of BMPs and their antagonist, and the fact that both promote tumor aggressiveness seems contradictory and is not fully understood. METHODS:We analyzed the transcriptomes of the metastatic 66cl4 and the non-metastatic 67NR cell lines of the 4T1 mouse mammary tumor model to search for factors that promote metastasis. CRISPR/Cas9 gene editing was used for mechanistic studies in the same cell lines. Furthermore, we analyzed gene expression patterns in human breast cancer biopsies obtained from public datasets to evaluate co-expression and possible relations to clinical outcome. RESULTS:We found that mRNA levels of the BMP-antagonist Grem1, encoding gremlin1, and the ligand Bmp4 were both significantly upregulated in cells and primary tumors of 66cl4 compared to 67NR. Depletion of gremlin1 in 66cl4 could impair metastasis to the lungs in this model. Furthermore, we found that expression of Grem1 correlated with upregulation of several stem cell markers in 66cl4 cells compared to 67NR cells. Both in the mouse model and in patients, expression of GREM1 associated with extracellular matrix organization, and formation, biosynthesis and modification of collagen. Importantly, high expression of GREM1 predicted poor prognosis in estrogen receptor negative breast cancer patients. Analyses of large patient cohorts revealed that amplification of genes encoding BMP-antagonists and elevation of the corresponding transcripts is evident in biopsies from more than half of the patients and much more frequent for the secreted BMP-antagonists than the intracellular inhibitors of SMAD signaling. CONCLUSION:In conclusion, our results show that GREM1 is associated with metastasis and predicts poor prognosis in ER-negative breast cancer patients. Gremlin1 could represent a novel target for therapy.

Dataset Information

Epigenetic activation of LY6K predicts the presence of metastasis and poor prognosis in breast carcinoma.

Publications

Epigenetic activation of LY6K predicts the presence of metastasis and poor prognosis in breast carcinoma.

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