Clinical study on the prevention of postoperative recurrence and metastasis of colorectal cancer by Zuojin pill combined with adjuvant chemotherapy
Ontology highlight
ABSTRACT:
DISEASE(S): Colorectal Cancer
PROVIDER: 2693767 | ecrin-mdr-crc |
REPOSITORIES: ECRIN MDR
Similar Datasets
Project description:BACKGROUND & AIMS: Sorafenib is the standard systemic therapy for advanced hepatocellular carcinoma (HCC). In early-stage HCC, survival benefits of resection/local ablation are compromised by high recurrence rates (70% at 5-years). In this setting, the phase-3 STORM-trial did not achieve its primary end-point of improving recurrence-free-survival (RFS) comparing sorafenib to placebo as adjuvant treatment. Herein we present results of the biomarker companion study BIOSTORM in which we define predictors of recurrence prevention with sorafenib and prognostic factors with B-level of evidence. METHODS: Tumor tissue from 188 patients randomized to receive sorafenib (83) or placebo (105) in the STORM trial was collected. Analyses included gene-expression profiling, targeted exome sequencing (18 known onco-drivers), immunohistochemistry (pERK, pVEGFR2, Ki67), FISH (VEGFA) and immunome. A gene signature capturing improved RFS in sorafenib-treated patients was generated. All 70 RFS events were recurrences, thus time-to-recurrence equaled RFS. Predictive and prognostic value was assessed using Cox regression models and interaction test. RESULTS: BIOSTORM recapitulates clinical and pathological characteristics of STORM patients. None of the biomarkers tested that are known to be related to angiogenesis and proliferation, or previously proposed gene-signatures, or mutations predicted sorafenib benefit. A newly generated 146-gene signature identifying 30% of patients captured benefit to sorafenib in terms of RFS (p-of-interaction=0.04). These sorafenib responders were significantly enriched in CD4+ T, B, and cytolytic Natural Killer cells, and showed absence of activated macrophages and other components of adaptive immunity. Hepatocytic pERK (HR=2.41; p=0.012) and microvascular invasion (HR=2.09; p=0.017) were independent prognostic factors. CONCLUSIONS: In BIOSTORM, hepatocytic pERK and microvascular invasion predicted poor RFS. No mutation, gene amplification or previously proposed gene-signatures predicted sorafenib benefit. A newly generated multi-gene signature associated with improved RFS on sorafenib warrants further validation. KEYWORDS: sorafenib; tyrosine-kinase inhibitor; trial enrichment; stratification.
2018-08-21 | GSE109211 | GEO
Project description:Background: One of the main fields of lung cancer research is identifying patients who are at high risk of post-resection recurrence. Individual recurrence risk evaluation by accurate but simple and reproducible method is needed for the clinical practice. Results: The log-rank test and further selection by our criteria of assayability generated 87 genes from microarray data with significant level 5%. Of these, by PTQ-PCR, the expression of most significant 18 genes was obtained. Using these gene expression information and clinical parameters, by stepwise variable selection method, the recurrence prediction model, which composed of 6 genes (CALB1, MMP7, SLC1A7, GSTA1, CCL19, IFI44) and pStage and cell differentiation, were developed. Validation into the two independent cohorts showed good results of the proposed model (p=0.0314, 0.0305, respectively). The predicted median recurrence-free survival times for each patient were reflected real ones well. Conclusions: Our method of individualized recurrence risk prediction is accurate, technically simple and reproducible to be used in clinical practice. Therefore, it would be useful in customizing the lung cancer management strategies. Keywords: Recurrence Free Survival Analysis
2007-11-20 | GSE8894 | GEO
Project description:Background:; One of the main fields of lung cancer research is identifying patients who are at high risk of post-resection recurrence. Individual recurrence risk evaluation by accurate but simple and reproducible method is needed for the clinical practice. Results:; The log-rank test and further selection by our criteria of assayability generated 87 genes from microarray data with significant level 5%. Of these, by PTQ-PCR, the expression of most significant 18 genes was obtained. Using these gene expression information and clinical parameters, by stepwise variable selection method, the recurrence prediction model, which composed of 6 genes (CALB1, MMP7, SLC1A7, GSTA1, CCL19, IFI44) and pStage and cell differentiation, were developed. Validation into the two independent cohorts showed good results of the proposed model (p=0.0314, 0.0305, respectively). The predicted median recurrence-free survival times for each patient were reflected real ones well. Conclusions:; Our method of individualized recurrence risk prediction is accurate, technically simple and reproducible to be used in clinical practice. Therefore, it would be useful in customizing the lung cancer management strategies. Experiment Overall Design: Methods: Experiment Overall Design: At first, we selected the statistically significant genes from the analysis of time-to-recurrence and censoring information from 138 whole-genome wide microarray data. Then, we further reduced the number of genes which could be reliably reproducible by RTQ-PCR. With these assayable genes and clinical parameters, construction of recurrence prediction model by Cox proportional hazard regression was done. After validation into two independent cohorts (n=59 and n=56), the model was transformed into recurrence prediction for the each patient.
2008-06-17 | E-GEOD-8894 | biostudies-arrayexpress
Project description:Interventions: experiment group:calcium + Vitamin D3;control group:Placebo
Primary outcome(s): colorectal incidence and recurrence
Study Design: Randomized parallel controlled trial
| 2673615 | ecrin-mdr-crc
Project description:Aim of this project was the evaluation of the effect of flushing (intraportal and intraoperative) hepatic allografts with tacrolimus before transplantation. Group A was administered tacrolimus, 20ng/ml in 1500ml albumin solution; and Group B was administered only albumin solution. Wedge biopsie of the allograft were harvested after 15 min flushing time and the gene expression profile were determined. The primary study objective was to determine on a genome-wide basis whether intraoperative and intraportal treatment of the allograft with tacrolimus reduces inflammatory signature in the liver. The secondary objective was the causally test, whether suppression of genes belongong to the ontologies of inflammation and immune response by tacrolimus will lead to a better initial function of the liver. randomized double-blind, placebo-controlled trial
2012-04-12 | E-GEOD-25338 | biostudies-arrayexpress
Project description:Background: Liver transplantation (LT) for Hepatocellular carcinoma (HCC) can be offered to patients beyond Milan criteria. However, there are currently no molecular markers that can be used on HCC explant histology to predict recurrence, which arises in up to 20% of LT recipients. The goal of our study was to identify proteins on HCC explant predictive of recurrence post-transplant, thereby guiding surveillance strategies and identifying patients beyond Milan criteria who would fare well following LT. Methods: LT recipients who had been transplanted at the University Health Network for HCC beyond Milan criteria in the context of Hepatitis B cirrhosis were identified. Snap-frozen samples from the dominant tumors of recurrent (N=7) and non-recurrent (N=4) patients were analyzed using LC-MS/MS on a Q-Exactive Plus mass spectrometer to delineate a distinctive proteomic signature. These tumors were also profiled by a Human Gene 2.0 ST microarray platform to identify a transcriptomic signature predictive of recurrence and analyzed with R packages. STRING database was used to characterize the implicated pathways. Kaplan-Meier estimator was used to generate a combined proteomic/transcriptomic signature predictive of HCC recurrence in patients with HCC beyond Milan criteria at time of LT. Significantly predictive proteins were verified and internally validated by immunoblotting or immunohistochemistry. Results: A total of 79 proteins and 636 genes were significantly differentially expressed in recurrent HCC, compared to non-recurrent (p<0.05). Among these, LGALS3, LGALS3BP, HAL, THBS1, and BLMH, were significantly increased in recurrent HCC at the protein and gene expression level. In turn, ALDH1A1 protein and gene expression were significantly decreased in recurrent HCC. Univariate survival analysis depicted ALDH1A1 (HR=0.084, 95%CI 0.01-0.68, p=0.02), LGALS3BP (HR=7.14, 95%CI 1.20-42.96, p=0.03), and LGALS3 (HR=2.89, 95%CI 1.01-8.3, p=0.049) as the key dysregulated proteins and genes in the patients with HCC recurrence versus those with non-recurrence by both proteomic and transcriptomic analysis. Decreased ALDH1A1 and significantly increased LGALS3 protein expression in recurrent HCC was verified by immunoblotting. Increased LGALS3BP protein expression in recurrent HCC was orthogonally verified and validated by immunohistochemistry in 30 independent HCC samples. Conclusion: Protein and gene expression of the cancer stem cell marker ALDH1A1 was protective against cancer recurrence in patients transplanted for HCC beyond Milan criteria. Conversely, increased expression of LGALS3 and LGALS3BP on explant was significantly predictive of post-transplant recurrence. These findings were internally validated, suggesting potential utility in identifying patients with HCC beyond Milan who would clearly benefit from transplant with limited recurrence risk and guiding post-transplant surveillance.
2022-02-22 | PXD022881 | Pride
Project description:This study is a prospective, multicenter, and exploratory study aimed at evaluating the effectiveness of Huaier Granules in preventing postoperative recurrence and metastasis of colorectal cancer.
| 109962 | ecrin-mdr-crc
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:Interventions: Experimental group:Sanwu Huangqin decoction;control group:placebo
Primary outcome(s): Recurrence rate of adenoma
Study Design: Parallel
| 2692741 | ecrin-mdr-crc