Increase of blood CSF3R+ myeloid-derived suppressor cell predicts breast cancer recurrence [Immune]
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ABSTRACT:
PROVIDER: PRJNA924726 | ENA |
REPOSITORIES: ENA
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Project description:Increase of blood CSF3R+ myeloid-derived suppressor cell predicts breast cancer recurrence
| PRJNA924714 | ENA
Project description:Increase of blood CSF3R+ myeloid-derived suppressor cell predicts breast cancer recurrence [Myeloid]
| PRJNA924729 | ENA
Project description:Early detection of recurrence by using specific biomarkers is still a clinically unmet need although methodologies for monitoring tumor markers, cell-free DNA and circulating tumor cells have been established for decades. Because recurrence is developed from metastatic or dormant cancer cells that are under immune surveillance, alteration in the population and function of immune cells may promote recurrence. In this study, we utilized an animal model to imitate breast tumor recurrence after surgical resection and investigated the abundance and gene expression profile of immune cells by using two NanoString Panels. Our results showed that myeloid-derived-suppressor cells (MDSC) were significantly increased during recurrence. Comparison of our NanoString data with a single-cell RNA sequencing dataset of MDSC in another spontaneous breast cancer model identified colony-stimulating factor 3 receptor (Csf3r)-positive MDSC as a potential marker to predict tumor recurrence. In vitro experiments demonstrated that Csf3R+ MDSC exhibited enhanced ROS levels and stronger T cell suppression ability. Furthermore, these findings were validated in two published PBMC databases.
2024-08-18 | GSE223028 | GEO
Project description:Early detection of recurrence by using specific biomarkers is still a clinically unmet need although methodologies for monitoring tumor markers, cell-free DNA and circulating tumor cells have been established for decades. Because recurrence is developed from metastatic or dormant cancer cells that are under immune surveillance, alteration in the population and function of immune cells may promote recurrence. In this study, we utilized an animal model to imitate breast tumor recurrence after surgical resection and investigated the abundance and gene expression profile of immune cells by using two NanoString Panels. Our results showed that myeloid-derived-suppressor cells (MDSC) were significantly increased during recurrence. Comparison of our NanoString data with a single-cell RNA sequencing dataset of MDSC in another spontaneous breast cancer model identified colony-stimulating factor 3 receptor (Csf3r)-positive MDSC as a potential marker to predict tumor recurrence. In vitro experiments demonstrated that Csf3R+ MDSC exhibited enhanced ROS levels and stronger T cell suppression ability. Furthermore, these findings were validated in two published PBMC databases.
2024-08-18 | GSE223025 | GEO
Project description:This SuperSeries is composed of the SubSeries listed below.
2024-08-18 | GSE223029 | GEO
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
2009-11-23 | E-GEOD-17538 | 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-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. Keywords: Functional genomics, metastatic colon cancer, mouse model, human colon cancer
2009-11-14 | GSE17537 | 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 | 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. 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