PI3/Elafin expression predicts recurrence after chemotherapy with DNA-damaging drugs in gastric cancer
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ABSTRACT:
PROVIDER: PRJNA1180477 | ENA |
REPOSITORIES: ENA
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Project description:Despite recent advances in gastric cancer therapy, chemotherapy resistance and lack of methods for selecting combination regimens remain major problems. Organoids, which recapitulate the in vivo micro-environment, can be established from surgical specimens with a high success rate, and are widely used for drug sensitivity assays. In this study, we aimed to discover a novel biomarker for predicting multidrug resistance using gastric cancer organoids (GCOs), which provide in vivo-like culture system that more closely resembles tumor cell organization than traditional cell lines. We evaluated 5-fluorouracil or oxaliplatin-resistant GCOs to find novel biomarkers that reflect multidrug resistance in gastric cancer. To examine the resistance mechanisms, RNA-seq analysis and ex vivo drug sensitivity testing were performed. The association of biomarkers with patient prognosis and chemotherapy efficacy was evaluated using three original cohorts with a total of 230 cases. The results were also validated with two independent public cohorts and a single-cell RNA sequence data. Increased expression of PI3/Elafin was detected in all 5-fluorouracil or oxaliplatin-resistant GCOs. Our findings suggest a potential association of PI3/Elafin expression with ribosome biosynthesis and RNA metabolism under organoid conditions. We also found that PI3/Elafin overexpression promotes 5-fluorouracil/oxaliplatin/cisplatin resistance but not paclitaxel resistance. Immunohistochemical evaluation of Elafin expression revealed that the Elafin-positive gastric cancer group had a poorer outcome, especially in terms of time-to-recurrence. Elafin positivity was also an independent predictor of relapse after chemotherapy with DNA-damaging agents. PI3/Elafin promotes DNA-damaging drug resistance through multiple downstream regulations related to RNA and ribosomal metabolism. PI3/Elafin may be useful as a biomarker for therapeutic selection of non-DNA-damaging agents.
2024-12-25 | GSE280755 | 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:Chemotherapy Treatment alone with DNA damaging drugs might be as effective as chemotherapy combined with surgery in colorectal cancer (CRC) avoiding surgery complications.
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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 | 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:Increase of blood CSF3R+ myeloid-derived suppressor cell predicts breast cancer recurrence
| PRJNA924714 | ENA
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:Increase of blood CSF3R+ myeloid-derived suppressor cell predicts breast cancer recurrence [Immune]
| PRJNA924726 | ENA
Project description:Increase of blood CSF3R+ myeloid-derived suppressor cell predicts breast cancer recurrence [Myeloid]
| PRJNA924729 | ENA