The Predictive Value of Guangzhou Panel for Recurrence in Early-stage Colorectal Cancer
Ontology highlight
ABSTRACT:
DISEASE(S): Colorectal Cancer,Colorectal Neoplasms
PROVIDER: 2303510 | ecrin-mdr-crc |
REPOSITORIES: ECRIN MDR
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2012-11-29 | E-TABM-1112 | biostudies-arrayexpress
Project description:Approximately one-third of aneurysmal subarachnoid hemorrhage (aSAH) patients develop delayed cerebral vasospasm (DCV) 3-10 days after aneurysm rupture resulting in additional, permanent neurologic disability. Currently, no validated biomarker is available to determine the risk of DCV in aSAH patients. MicroRNAs (miRNAs) have been implicated in virtually all human diseases, including aSAH, and are found in extracellular biofluids including plasma and cerebrospinal fluid (CSF). We used a custom designed TaqMan Low Density Array miRNA panel to examine the levels of 47 selected brain and vasculature injury related miRNAs in CSF and plasma specimens collected from 31 patients with or without DCV at 3 days and 7 days after aSAH, as well as from 8 healthy controls. The analysis of the first 18-patient cohort revealed a striking differential expression pattern of the selected miRNAs in CSF and plasma of aSAH patients with DCV from those without DCV. Importantly, this differential expression was observed at the early time point (3 days after aSAH), before DCV event occurs. Seven miRNAs were identified as reliable DCV risk predictors along with a prediction model constructed based on an array of additional 19 miRNAs on the panel. These chosen miRNAs were then used to predict the risk of DCV in a separate, testing cohort of 15 patients. The accuracy of DCV risk prediction in the testing cohort reached 87%. The study demonstrates that our novel designed miRNA panel is an effective predictor of DCV risk and has strong applications in clinical management of aSAH patients.
2021-06-02 | GSE165608 | GEO
Project description:Background Currently, no gene-expression signature (GES) established from node-positive cohorts, able to predict breast cancer evolution after systemic adjuvant chemotherapy, exists. Methods Gene-expression profiles of 252 node-positive patients (median follow-up: 7.7 years), mostly included in a randomized clinical trial (PACS01), receiving systemic adjuvant regimen, were determined by means of cDNA custom array representing 5,776 distinct genes. Findings In the training cohort, we established a 38-GES for the purpose of predicting time to distant metastasis. The 38-GES yielded unadjusted hazard ratio of 4.86 (95% CI=2.76-8.56). Even when adjusted with the two best clinicopathological prognostic scoring: NPI and Adjuvant!, 38-GES HR were 3.30 (1.81-5.99) and 3.40 (1.85-6.24), respectively. Furthermore, 38-GES improved mostly NPI and Adjuvant! intermediate-risk classified patients. NPI intermediate-risk patients (7-year MFS=87.2%) were divided into 2/3 (7-year MFS=95.5%) close to NPI low-risk group and 1/3 (7-year MFS=69.3%) close to NPI high-risk group (HR=6.97 [2.51-19.36]). Adjuvant! intermediate-risk patients (7-year MFS=88.0%) were divided into 2/3 (7-year MFS=94.8%) close to Adjuvant! low-risk group and 1/3 (7-year MFS=71.7%) close to Adjuvant! high-risk group (HR=5.31 [5.38-11.87]). The 38-GES was validated on gene-expression datasets from three external node-positive breast cancer subcohorts (n=224) generated from different microarray platforms. The 38-GES yielded unadjusted HR=2.95 (1.74-5.01). Furthermore, 38-GES showed performance in supplementary cohorts with different lymph-node status and endpoint (1,031 new patients). Interpretation The 38-GES represents a robust tool able to type systemic adjuvant treated node-positive patients at high risk of metastatic relapse, and especially powerful to separate NPI or Adjuvant! intermediate-risk node-positive patients. Keywords: disease-state analysis
2008-11-28 | GSE11264 | GEO
Project description:Sub-optimal fetal development is associated with an increased risk of developing cardiovascular disease, type 2 diabetes (T2D) and adiposity later in life. However, definitions of intrauterine growth restriction (IUGR) and small for gestational age (SGA) are based on simple statistical approaches that may misclassify infants with a normal developmental profile and vice versa. We used an unbiased global profiling approach to identify gene expression patterns in umbilical cord tissue from 38 infants and identified a set of 466 genes which separated the subjects into 2 distinct groups – one biased towards lower birth weight and one biased towards normal birth weight. The data suggest that approximately 30% of children of normal size have a molecular profile more typical of impaired fetal development and who may be on a programmed trajectory. Differences in expression between the two groups encompassed 384 upregulated and 82 downregulated genes. Molecular profiling at birth may have utility in identifying markers that potentially reflect antenatal developmental and may be predictive of future phenotypic development after birth. Importantly, it may provide an alternative to the current classification of infants using birth weights. RNA from umbilical cord tissue from full term neonates was extracted and hybridized. Separation into 2 distinct groups, independent of birth weight, but based solely on gene expression levels was analysed by Genespring. After appropriate statistical analysis, one group was keenly associated with a higher birth weight (22 samples) while the other was associated with a lower birth-weight (18 samples). Technical replicates were included for all 40 samples.
2011-10-20 | E-GEOD-24818 | biostudies-arrayexpress
Project description:Diabetes Mellitus (DM) is a chronic, severe disease rapidly increasing in incidence and prevalence and is associated with numerous complications. Patients with DM are at high risk of developing diabetic foot ulcers (DFU) that often lead to lower limb amputations, long term disability, and a shortened lifespan. Despite this, the effects of DM on human foot skin biology are largely unknown. Thus, the focus of this study was to determine whether DM changes foot skin biology predisposing it for healing impairment and development of DFU. Foot skin samples were collected from 20 patients receiving corrective foot surgery and, using a combination of multiple molecular and cellular approaches we performed comparative analyses of non-ulcerated non-neuropathic diabetic foot skin (DFS) and healthy non-diabetic foot skin (NFS). MicroRNA (miR) profiling of laser captured epidermis and primary dermal fibroblasts from both DFS and NFS samples identified 5 miRs de-regulated in the epidermis of DFS though none reached statistical significance. MiR-31-5p and miR-31-3p were most profoundly induced. Although none were significantly regulated in diabetic fibroblasts, miR-29c-3p showed a trend of up-regulation, which was confirmed by qPCR in a prospective set of 20 skin samples. Gene expression profiling of full thickness biopsies identified 36 de-regulated genes in DFS (>2 fold-change, unadjusted p-value ≤ 0.05). Of this group, three out of seven tested genes were confirmed by qPCR: SERPINB3 was up-regulated whereas OR2A4 and LGR5 were down-regulated in DFS. However no morphological differences in histology, collagen deposition, and number of blood vessels or lymphocytes were found. No difference in proliferative capacity was observed by quantification of Ki67 positive cells in epidermis. These findings suggest DM causes only subtle changes to foot skin. Since morphology, mRNA and miR levels were not affected in a major way, additional factors, such as neuropathy, vascular complications, or duration of DM, may further compromise tissue’s healing ability leading to development of DFUs.
2015-05-01 | GSE68184 | GEO
Project description:Background: Over 26 million people suffer from heart failure (HF) globally. Current diagnosis of HF relies on clinical evaluation, blood assays and imaging techniques at the time of diagnosis. Our aim is to develop a diagnostic assay to detect HF early in at risk individuals within the community using human saliva as a medium, paving the way towards precision medicine. Methods: Saliva samples were collected from healthy controls (n=36) and HF patients (n=75). Salivary proteome profiles were analysed by Sequential Window Acquisition of All Theoretical fragment ion spectra – Mass Spectrometry (SWATH-MS). A total of 738 proteins were quantified and 177 proteins demonstrated significant differences in saliva from HF patients and healthy controls. Candidate biomarkers were chosen based on their abundance and difference between the two cohorts. A multi-protein panel was developed using logistic regression analysis. The diagnostic performance of the multi-protein panel was assessed using the receiver operative characteristic curves. The candidate proteins were further validated technically, using western blot analysis as well as biologically, using an independent cohor.t. Results: A group of six proteins were chosen as potential protein candidates based on their differences in the abundance between the two cohorts. During the validation phase, two of the proteins were eliminated as these did not meet our criteria. The panel consists of four proteins with sensitivity of 83.3%, specificity of 62.5% with an area under ROC curve of 0.78 in discriminating healthy controls from NYHA class I/II HF patients. Conclusion: Analysis of salivary proteome using SWATH-MS analysis revealed novel HF-specific protein candidates when combined into a panel yielding high diagnostic performance. A multi-centre longitudinal clinical trial will be the next step before clinical implementation of this panel.
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Project description:Background Currently, no gene-expression signature (GES) established from node-positive cohorts, able to predict breast cancer evolution after systemic adjuvant chemotherapy, exists. Methods Gene-expression profiles of 252 node-positive patients (median follow-up: 7.7 years), mostly included in a randomized clinical trial (PACS01), receiving systemic adjuvant regimen, were determined by means of cDNA custom array representing 5,776 distinct genes. Findings In the training cohort, we established a 38-GES for the purpose of predicting time to distant metastasis. The 38-GES yielded unadjusted hazard ratio of 4.86 (95% CI=2.76-8.56). Even when adjusted with the two best clinicopathological prognostic scoring: NPI and Adjuvant!, 38-GES HR were 3.30 (1.81-5.99) and 3.40 (1.85-6.24), respectively. Furthermore, 38-GES improved mostly NPI and Adjuvant! intermediate-risk classified patients. NPI intermediate-risk patients (7-year MFS=87.2%) were divided into 2/3 (7-year MFS=95.5%) close to NPI low-risk group and 1/3 (7-year MFS=69.3%) close to NPI high-risk group (HR=6.97 [2.51-19.36]). Adjuvant! intermediate-risk patients (7-year MFS=88.0%) were divided into 2/3 (7-year MFS=94.8%) close to Adjuvant! low-risk group and 1/3 (7-year MFS=71.7%) close to Adjuvant! high-risk group (HR=5.31 [5.38-11.87]). The 38-GES was validated on gene-expression datasets from three external node-positive breast cancer subcohorts (n=224) generated from different microarray platforms. The 38-GES yielded unadjusted HR=2.95 (1.74-5.01). Furthermore, 38-GES showed performance in supplementary cohorts with different lymph-node status and endpoint (1,031 new patients). Interpretation The 38-GES represents a robust tool able to type systemic adjuvant treated node-positive patients at high risk of metastatic relapse, and especially powerful to separate NPI or Adjuvant! intermediate-risk node-positive patients. Keywords: disease-state analysis 252 breast cancer patients at diagnosis examined with spotted cDNA nylon membrane. Patient details: PACS01x are 2 parts of a clinical trial : PACS01A : patients had received 6 cycles of FEC100 PACS01B : patients had received 3 cycles of FEC100 then 3 cycles of Docetaxel CCRG are patients from our local cancer center (Cancer Center René Gauducheau) included with the same criteria as PACS01A (6 cycles of FEC100).
2008-11-27 | E-GEOD-11264 | biostudies-arrayexpress
Project description:To understand the molecular mechanism of rectal cancer and develop markers for disease prognostication, we generated and explored a dataset from 243 rectal cancer patients by gene expression microarray analysis of cancer samples and matched controls, and SNP-arrays of germline DNA. We found that two of the loci most strongly linked with colorectal cancer (CRC) risk, 8q24 (upstream of MYC) and 18q21 (in the intron of SMAD7), as well as 20q13 (in the intron of LAMA5), are tightly associated with the prognosis of rectal cancer patients. For SNPs on 18q21 (rs12953717 and rs4464148) and 20q13 (rs4925386), alleles that correlate with higher risk for the development of CRC are associated with shorter disease free survival (DFS). However, for rs6983267 on 8q24, the low risk allele is associated with a higher risk for recurrence and metastasis after surgery, and importantly, is strongly correlated with the resistance of CRC cell lines to chemoradiotherapy (CRT). We also found that although MYC expression is dramatically increased in cancer, patients with higher levels of MYC have a better prognosis. The expression of SMAD7 is weakly correlated with DFS. Notably, the presence of the 8q24 and 18q21 SNP alleles is not correlated with expression levels of MYC and SMAD7. rs4464148, and probably rs6983267 and rs4925386, are linked with overall survival time of patients. In conclusion, we show that several CRC risk SNPs detect subpopulations of rectal cancer patients with poor prognosis, and that rs6983267 probably affects prognosis through interfering with the resistance of cancer cells to CRT.
2017-11-28 | GSE87211 | GEO
Project description:A Highly Predictive MicroRNA Panel for Determining Delayed Cerebral Vasospasm Risk Following Aneurysmal Subarachnoid Hemorrhage
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