Expression data at each site in colon cancer
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE65480 | GEO | 2016/01/06
SECONDARY ACCESSION(S): PRJNA274136
REPOSITORIES: GEO
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Project description:Colon cancer invade to depper layer and the expression of major molecules at cancer front change. But the screening of expression changing at cancer front has not be adequtely clarified. We compared gene expression at cancer front with it at cancer center. We got cancer cells from cancer front(F) and cancer center(C) by lasermicrodissection.
2016-01-06 | E-GEOD-65480 | biostudies-arrayexpress
Project description:The goal was to identify gene expression signatures predictive of early relapse among stage IIA/MSS colon cancer patients. A secondary question addressed was whether the invasion front profiles could generate a competitive signature. 39 whole tumor and 35 matched invasion front profiles were generated (4 samples failed) and grouped into \\"early relapse\\" (relapse within 5 years) and \\"no relapse\\" (no relapse for at least 6 years) categories.
2024-03-25 | E-MTAB-13695 | biostudies-arrayexpress
Project description:In colorectal cancer, p53 is commonly inactivated, associated with chemo-resistance, and marks the transition from non-invasive to invasive disease. Cancers, including colorectal cancer, are thought to be diseases of aberrant stem cell populations, as stem cells are able to self-renew, making them long-lived enough to acquire mutations necessary to manifest the disease. We have shown that extracts from sweet sorghum stalk components eliminate colon cancer stem cells (CCSC) in a partial p53-dependent fashion. However, the underlying mechanisms are unknown. In the present study, CCSC were transfected with short hairpin-RNA against p53 (CCSC p53 shRNA) and treated with sweet sorghum phenolics extracted from different plant components (dermal layer, leaf, seed head and whole plant). While all components demonstrated anti-proliferative and pro-apoptotic effects in CCSC, phenolics extracted from the dermal layer and seed head were more potent in eliminating CCSC by elevating caspases 3/7 activity, PARP cleavage, and DNA fragmentation in a p53-dependent and p53-independent fashion, respectively. Further investigations revealed that the anti-proliferative and pro-apoptotic effects were associated with decreases in beta-catenin protein levels, and beta-catenin targets cyclin D1, cMyc, and survivin. These results suggest that the anti-proliferative and pro-apoptotic effects of sweet sorghum extracts against human colon cancer stem cells are via suppression of Wnt/beta-catenin pro-survival signaling in a p53-dependent (dermal layer) and partial p53-independent (seed head) fashion. LCMS used to identify phenolic compounds associated with extract activity
2014-05-01 | MTBLS69 | MetaboLights
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:To progress, tumors need to invade the surrounding tissues. However, the heterogeneity of cell types at the tumor-stroma interface and the complexity of their potential interactions hampered mechanistic insights for efficient therapeutic targeting. Here, combining single-cell and spatial transcriptomics on human basal cell carcinomas (BCCs), we define the cellular contributors of the invasive front. In the invasive niche, tumor cells harbor a collective migration phenotype, supported by the expression of cell-cell junction complexes. In physical proximity, we identify cancer-associated fibroblasts (CAFs) with extracellular matrix-remodeling features, as required to support collective migration. Moreover, while tumor cells specifically express Activin A, we find Activin A-induced gene signature enrichment in adjacent CAFs subpopulations, further supporting their biological crosstalk. Altogether, our data identify the subpopulations and their transcriptional reprogramming contributing to the spatial organization of the BCC invasive niche. They also bring the proof-of-concept for integrated spatial and single-cell multi-omics to decipher cancer-specific invasive properties and develop therapeutic targeting.
2022-08-06 | GSE210648 | GEO
Project description:To progress, tumors need to invade the surrounding tissues. However, the heterogeneity of cell types at the tumor-stroma interface and the complexity of their potential interactions hampered mechanistic insights for efficient therapeutic targeting. Here, combining single-cell and spatial transcriptomics on human basal cell carcinomas (BCCs), we define the cellular contributors of the invasive front. In the invasive niche, tumor cells harbor a collective migration phenotype, supported by the expression of cell-cell junction complexes. In physical proximity, we identify cancer-associated fibroblasts (CAFs) with extracellular matrix-remodeling features, as required to support collective migration. Moreover, while tumor cells specifically express Activin A, we find Activin A-induced gene signature enrichment in adjacent CAFs subpopulations, further supporting their biological crosstalk. Altogether, our data identify the subpopulations and their transcriptional reprogramming contributing to the spatial organization of the BCC invasive niche. They also bring the proof-of-concept for integrated spatial and single-cell multi-omics to decipher cancer-specific invasive properties and develop therapeutic targeting.
2022-06-29 | GSE181907 | GEO
Project description:Dana-Farber/Harvard Cancer Center Experimental Therapeutics Trials Network Site (DF/HCC ETCTN Site) Trial 10057
| PRJNA1069855 | ENA