Project description:Background and Aim: Fra-1 (Fos-related antigen-1) is a member of the AP1 (activator protein-1) family of transcription factors. We have recently shown that Fra-1 is necessary for breast cancer cells to metastasize in vivo, and that breast cancer outcome can be predicted by a classifier comprising genes that are expressed in a Fra-1-dependent fashion. Here, we show that Fra-1 plays an important role also in colon cancer progression. Methods: We compared proliferation rates of parental and Fra-1-depleted colon cancer cells in vitro under 2D, 3D, and attachment-free conditions and in vivo upon subcutaneous and intravenous injections into mice. We also compared RNA expression profiles of colon cancer cells with and without Fra-1 expression. Results: Fra-1 depletion impair colony outgrowth of human colon cancer cells in soft agar and in suspension, whereas it does not affect proliferation on 2D culture plates. Consistent with this, upon subcutaneous injection into mice, tumors formed by Fra-1-depleted colon cancer cells are only three times smaller than those produced by control cells. In contrast, when injected intravenously, Fra-1 depletion causes 200-fold reduction in tumor burden. Consistent with the more aggressive characteristics of Fra-1-proficient tumors, the prognosis of colon cancer patients can be predicted by a Fra-1 classifier generated by comparing RNA profiles of parental and Fra-1-depleted colon cancer cells. Conclusions: Our results demonstrate that Fra-1 is an important determinant of the metastatic potential of human colon cancer cells, and suggest that a Fra-1 classifier can be used as a prognostic predictor in colon cancer patients.
Project description:Background and Aims: Staging inadequately predicts metastatic risk in colon cancer patients. We used a gene expression profile derived from invasive murine colon cancer cells that were highly metastatic in an immunocompetent mouse model to identify colon cancer patients at risk for recurrence in a phase I, exploratory biomarker study. Methods: 55 colorectal cancer patients from Vanderbilt Medical Center (VMC) were used as the training dataset and 177 patients from the Moffitt Cancer Center were used as the independent dataset. The metastasis-associated gene expression profile developed from the mouse model was refined using comparative functional genomics in the VMC gene expression profiles to identify a 34-gene classifier associated with high risk of metastasis and death from colon cancer. A recurrence score derived from the biologically based classifier was tested in the Moffitt dataset. Results: A high score was significantly associated with increased risk of metastasis and death from colon cancer across all pathological stages and specifically in stage II and stage III patients. The recurrence score was shown to independently predict risk of cancer recurrence and death in both univariate and multivariate models. For example, among stage III patients, a high score translated to increased relative risk for cancer recurrence (hazard ratio = 4.7 (95% CI=1.566-14.05)). Furthermore, the recurrence score identified stage III patients whose five-year recurrence-free survival was >88% and for whom adjuvant chemotherapy did not provide improved survival. Conclusion: Our biologically based gene expression profile yielded a potentially useful classifier to predict cancer recurrence and death independently of conventional measures in colon cancer patients. Experiment Overall Design: Gene expression array differences between highly invasive mouse colon cancer cells and non-invasive colon cancer cells were used to develop a metastasis gene expression profile. It was refined using gene expression data from 55 patient (VMC) samples and trained using 177 patient (Moffitt) samples.
Project description:Background and Aims: Staging inadequately predicts metastatic risk in colon cancer patients. We used a gene expression profile derived from invasive murine colon cancer cells that were highly metastatic in an immunocompetent mouse model to identify colon cancer patients at risk for recurrence in a phase I, exploratory biomarker study. Methods: 55 colorectal cancer patients from Vanderbilt Medical Center (VMC) were used as the training dataset and 177 patients from the Moffitt Cancer Center were used as the independent dataset. The metastasis-associated gene expression profile developed from the mouse model was refined using comparative functional genomics in the VMC gene expression profiles to identify a 34-gene classifier associated with high risk of metastasis and death from colon cancer. A recurrence score derived from the biologically based classifier was tested in the Moffitt dataset. Results: A high score was significantly associated with increased risk of metastasis and death from colon cancer across all pathological stages and specifically in stage II and stage III patients. The recurrence score was shown to independently predict risk of cancer recurrence and death in both univariate and multivariate models. For example, among stage III patients, a high score translated to increased relative risk for cancer recurrence (hazard ratio = 4.7 (95% CI=1.566-14.05)). Furthermore, the recurrence score identified stage III patients whose five-year recurrence-free survival was >88% and for whom adjuvant chemotherapy did not provide improved survival. Conclusion: Our biologically based gene expression profile yielded a potentially useful classifier to predict cancer recurrence and death independently of conventional measures in colon cancer patients. Experiment Overall Design: Gene expression array differences between highly invasive mouse colon cancer cells and non-invasive colon cancer cells were used to develop a metastasis gene expression profile. It was refined using gene expression data from 55 patient (VMC) samples and trained using 177 patient (Moffitt) samples.
Project description:Background and Aims: Staging inadequately predicts metastatic risk in colon cancer patients. We used a gene expression profile derived from invasive murine colon cancer cells that were highly metastatic in an immunocompetent mouse model to identify colon cancer patients at risk for recurrence in a phase I, exploratory biomarker study. Methods: 55 colorectal cancer patients from Vanderbilt Medical Center (VMC) were used as the training dataset and 177 patients from the Moffitt Cancer Center were used as the independent dataset. The metastasis-associated gene expression profile developed from the mouse model was refined using comparative functional genomics in the VMC gene expression profiles to identify a 34-gene classifier associated with high risk of metastasis and death from colon cancer. A recurrence score derived from the biologically based classifier was tested in the Moffitt dataset. Results: A high score was significantly associated with increased risk of metastasis and death from colon cancer across all pathological stages and specifically in stage II and stage III patients. The recurrence score was shown to independently predict risk of cancer recurrence and death in both univariate and multivariate models. For example, among stage III patients, a high score translated to increased relative risk for cancer recurrence (hazard ratio = 4.7 (95% CI=1.566-14.05)). Furthermore, the recurrence score identified stage III patients whose five-year recurrence-free survival was >88% and for whom adjuvant chemotherapy did not provide improved survival. Conclusion: Our biologically based gene expression profile yielded a potentially useful classifier to predict cancer recurrence and death independently of conventional measures in colon cancer patients. Keywords: Functional genomics, metastatic colon cancer, mouse model, human colon cancer
Project description:Background and Aims: Staging inadequately predicts metastatic risk in colon cancer patients. We used a gene expression profile derived from invasive murine colon cancer cells that were highly metastatic in an immunocompetent mouse model to identify colon cancer patients at risk for recurrence in a phase I, exploratory biomarker study. Methods: 55 colorectal cancer patients from Vanderbilt Medical Center (VMC) were used as the training dataset and 177 patients from the Moffitt Cancer Center were used as the independent dataset. The metastasis-associated gene expression profile developed from the mouse model was refined using comparative functional genomics in the VMC gene expression profiles to identify a 34-gene classifier associated with high risk of metastasis and death from colon cancer. A recurrence score derived from the biologically based classifier was tested in the Moffitt dataset. Results: A high score was significantly associated with increased risk of metastasis and death from colon cancer across all pathological stages and specifically in stage II and stage III patients. The recurrence score was shown to independently predict risk of cancer recurrence and death in both univariate and multivariate models. For example, among stage III patients, a high score translated to increased relative risk for cancer recurrence (hazard ratio = 4.7 (95% CI=1.566-14.05)). Furthermore, the recurrence score identified stage III patients whose five-year recurrence-free survival was >88% and for whom adjuvant chemotherapy did not provide improved survival. Conclusion: Our biologically based gene expression profile yielded a potentially useful classifier to predict cancer recurrence and death independently of conventional measures in colon cancer patients. Keywords: Functional genomics, metastatic colon cancer, mouse model, human colon cancer
Project description:Colorectal carcinoma is the third leading cause of cancer-related death in the United States. In order to understand the mechanism/signaling pathways responsible for invasion, migration and metastasis in colorectal cancer, we developed an integrative and comparative genetic approach to infer transcriptional regulatory mechanisms underlying colon cancer progression. Accordingly, we filtered fourteen human colorectal cancer (CRC) microarray data sets, from an immune competent mouse model of metastasis to identify known and novel transcriptional regulators in CRC. Using this approach, Nuclear Factor of Activated T cells (NFAT) family of transcription factors were identified as metastasis driver of colon cancer. NFAT family of transcription factors is known to induce gene transcription in various disease processes, including carcinogenesis. We used parental and metastatic derivatives of MC38 mouse colon cancer cells (MC38Par and MC38Met, respectively) to evaluate the role of NFATc1 in cancer cell invasiveness. We found that high NFATc1 expression correlates with significantly increased (p<0.0001) Trans-Endothelial Invasion (TEI) in MC38Met cells. Conversely, RNAi-based inhibition of NFATc1 expression and functional inhibition with calcineurin inhibitor FK506 in MC38Met cells, both resulted in significant decreased TEI (p=0.0193 & p=0.0003). Furthermore, a set of predicted NFATc1 target mRNAs identified in our original analysis were downregulated by knock-down of NFATc1 or functional inhibition with FK506 in MC38Met cells. The expression level (mRNA) of predicted gene targets were high in human CRC specimens which had higher than median NFATc1 mRNA expression (n=11 out of total 22). The tumor-associated NFATc1 co-regulated gene signature is significantly correlated with both disease-specific and disease-free survival in Stage II and III CRC patients. We have successfully demonstrated a bioinformatics approach to identify a tumor promoter driver gene NFATc1. Our studies suggest a role of NFATc1 towards invasion and its co-regulated gene signature for poor outcomes in colorectal cancer. We developed an integrative and comparative genetic approach to infer transcriptional regulatory mechanisms underlying colon cancer progression. Using this approach, the Nuclear Factor of Activated T cells (NFAT) family of transcription factors were identified as metastasis driver of colon cancer. We used parental and metastatic derivatives of MC38 mouse colon cancer cells (MC38Par and MC38Met, respectively) to evaluate the role of NFATc1 in cancer cell invasiveness [GSE19073]. We found that high NFATc1 expression correlates with significantly increased (p<0.0001) Trans-Endothelial Invasion (TEI) in MC38Met cells. Conversely, RNAi-based inhibition of NFATc1 expression and functional inhibition with calcineurin inhibitor FK506 in MC38Met cells, both resulted in significant decreased TEI (p=0.0193 & p=0.0003). Furthermore, a set of predicted NFATc1 target mRNAs identified in our original analysis were downregulated by knock-down of NFATc1 or functional inhibition with FK506 in MC38Met cells. Finally, we generated a microarray gene expression dataset based on tumor samples collected from 122 CRC patients and tested whether the tumor-associated NFATc1co-regulated gene signature is correlated with patient survival. The following clinical information can be found in the characteristics fields of each sample; AJCC_STAGE: stage of cancer classified by AJCC (American Joint Committee on Cancer) staging system DFS_EVENT: disease free survival; cancer recurrence=1, no recurrence=0 DFS_TIME: disease free survival time (months) DSS_EVENT: disease specific survival; death from cancer=1,no death=0 DSS_TIME: disease specific survival time (months)
Project description:The Fra-1 transcription factor promotes tumor cell growth, invasion and metastasis. While characterizing five breast cancer cell lines derived from primary human breast tumors, we identified BRC-31 as a novel basal-like cell model that expresses elevated Fra-1 levels. BRC-31 cells display elevated FAK, SRC and ERK2 phosphorylation relative to luminal breast cancer models. Inhibition of this signaling axis, through the use of pharmacological inhibitors, reduces the phosphorylation and stabilization of Fra-1. Elevated integrin αVβ3 expression in these cells suggested that integrin receptors might activate this FAK-SRC-ERK2 signaling axis to enhance Fra-1 phosphorylation. These cells also express high levels of uPAR, a GPI-anchored receptor that has been shown to enhance integrin-mediated signaling initiated by Vitronectin engagement. Transient knockdown of uPAR in BRC31 cells grown on Vitronectin reduces Fra-1 phosphorylation and stabilization and uPAR and Fra-1 are required for Vitronectin-induced cell invasion. In clinical samples, a molecular component signature consisting of Vitronectin-uPAR-uPA-Fra-1 predicts poor overall survival in patients with breast cancer and correlates with a Fra-1 transcriptional signature. Taken together, we have identified a novel-signaling axis that leads to phosphorylation and stabilization of Fra-1, a transcription factor that is emerging as an important modulator of breast cancer progression and metastasis.
Project description:This SuperSeries is composed of the following subset Series:; GSE17536: Metastasis Gene Expression Profile Predicts Recurrence and Death in Colon Cancer Patients (Moffitt Samples); GSE17537: Metastasis Gene Expression Profile Predicts Recurrence and Death in Colon Cancer Patients (VMC Samples) Experiment Overall Design: Refer to individual Series
Project description:The effect of Fra-2 overexpression in two stable Fra-2 overexpressing clones of the human breast cancer cell line MDA-MB-231 on survival and metastatic load was studied after subcutaneous injection into scid and E- and P-selectin deficient scid (select) mice. To identify Fra-2 target genes, we performed cDNA microarrays with mRNA isolated from xenograft tumour tissue. Fra-2 overexpression lead to a significantly shorter overall survival and a higher amount of spontaneous metastases in scid mouse lungs and compared to select mice indicating that Fra-2 regulates selectin binding sites on the tumour cell surface, which directly influence overall survival. By using cDNA microarray analysis of resected primary tumours a multitude of deregulated genes, which are known to be involved in metastasis formation