Similar Datasets
Project description:Chromatogram library generated of pooled sample. Coculture spheroids formed from fibroblast and colon cancer cell lines, and monoculture spheroids formed from the colon cancer cell line HCT116.
2023-11-13 | MSV000093395 | MassIVE
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.
2009-12-02 | E-GEOD-17537 | biostudies-arrayexpress
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.
2009-12-02 | E-GEOD-17536 | biostudies-arrayexpress
Project description:Gene expression profiling of ovarian cancer spheroids upon treatment with three chemotherapy drugs
2008-05-06 | E-MEXP-1319 | biostudies-arrayexpress
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
2009-11-14 | GSE17536 | GEO
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
2009-11-14 | GSE17537 | GEO
Project description:Neurological disorders induced by chemotherapy, including pain and other debilitating sensory conditions correlate with alterations in diverse systemic, cellular, and molecular processes. Chemotherapeutic agents variously induce inflammatory responses, metabolic disorders and associated gene expression changes, all of which have the capacity to impact sensory function . Early evidence of independent effects by cancer alone on some of these same processes led us to hypothesize that neurological symptoms may emerge from cooperativity in the effects of chemotherapy and cancer. We tested this hypothesis in a rodent model of human colon cancer after a full course of human-scaled treatment with the commonly used chemotherapeutic agent oxaliplatin. Transcriptional profiling of dorsal root ganglia demonstrated that cancer and chemotherapy in combination produced changes that were unpredictable or undetectable from those observed with either alone. Unique combinatorial effects of chemotherapy and cancer were conserved as dysregulation of select ion-channel proteins and associated reduction in excitability of sensory neurons responsible for proprioception. Recognition of the non-additive interactions between chemotherapy and cancer may lead to the development of more effective strategies for the prevention and/or treatment of chronic neurological disorders commonly associated with cancer therapy. We used microarrays to detail the global programme of gene expression underlying neurologic dysfunction following chemotherapy treatment in animals bearing and not bearing cancer.
2020-02-19 | GSE126773 | GEO
Project description:Cancer stem cells (CSCs) are profoundly associated with refractory nature of cancer. A quiescent population of CSCs is responsible for tumorigenesis and chemoresistance in leukemia, whereas neither the presence nor clinical importance of the quiescent CSCs is clearly established in solid tumors. In colon cancer, LGR5 is regarded as a functional marker of CSCs, but heterogeneity among LGR5+ cells was not clearly defined. Here we stratified LGR5+ cells by single-cell gene expression analyses and revealed that a tumorigenic population of mouse LGR5+ cells resides in a quiescent state. We identified 23 signature genes that were uniquely expressed in the quiescent CSCs of mouse tumors, and found that 7 of them were also specifically expressed in a quiescent population of LGR5+ cells in human colon xenograft tumors. Among them, PROX1 was expressed in invasive fronts of colon tumors. PROX1 was induced by TCF1 (TCF7), and the TCF1-mediated PROX1 expression was responsible for not only the maintenance of quiescence but also chemoresistance of colon cancer organoids. Knockout of PROX1 in patient-derived xenograft tumors resulted in inhibition of tumor recurrence after chemotherapeutic treatment. Our data underscore the therapeutic importance of a quiescent CSC population in colon cancer.
2019-11-30 | GSE141157 | GEO
Project description:Expression profiles of the spheroids derived from colon cancer patients
| PRJNA704563 | ENA