Colvera for Detection of Disease Recurrence
Ontology highlight
ABSTRACT:
DISEASE(S): Colorectal Adenocarcinoma
PROVIDER: 2286836 | ecrin-mdr-crc |
REPOSITORIES: ECRIN MDR
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Project description:To compare the sensitivity and specificity estimates of Colvera with that of a commercially available CEA test for detection of recurrent disease in subjects with colorectal cancer that have documented recurrence or no evidence of recurrence by CT.
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Project description:Previously, we reported that a combination of a collagen alpha-1(I) natural occurring peptide (NOP) AGPP(-OH)GEAGKP(-OH)GEQGVP(-OH)GDLGAP(-OH)GP (AGP) and serum carcinoembryonic antigen (CEA) has the potential to detect colorectal liver metastases (CRLM). The combined method needs to be adapted to increase the sensitivity and specificity before it can be implemented in the clinic. This mass spectrometry study aimed to identify additional collagen NOPs in urine to further increase the sensitivity and specificity of our previously published method and search for the most discriminating NOP panel. The new assay was developed based on urine samples from 100 healthy controls and 100 patients suffering from CRLM. Two additional NOPs were identified: GPPGEAGK(-OH)P(-OH)GEQGVP(-OH)GDLGAP(-OH)GP (GPP) originating from collagen alpha-1(I) and GNDGARGSDGQPGPP(-OH)GP(-OH)P(-OH)GTAGFP(-OH)GSP(-OH)GAK(-OH)GEVGP (GND) originating from collagen alpha-1(III). A molecular model combining NOPs (AGP, GPP, and GND) and CEA was generated. Molecules that did not contribute to the diagnostic power of the model were removed, resulting in a model only consisting of GND and CEA. In this model, 86% sensitivity and 84% specificity in the discovery set, and 92% sensitivity and 90% specificity in the validation set were reached. These percentages are significantly higher than the current model based on AGP and CEA (p=0.032). The performance of the new model is better than the currently used techniques in the clinic (e.g. CT-scan, ultrasound, serum CEA), which have a sensitivity between 57-70% and a specificity between 90-96%.
2019-11-15 | PXD013705 | Pride
Project description:Previously, we reported that a combination of a collagen alpha-1(I) natural occurring peptide (NOP) AGPP(-OH)GEAGKP(-OH)GEQGVP(-OH)GDLGAP(-OH)GP (AGP) and serum carcinoembryonic antigen (CEA) has the potential to detect colorectal liver metastases (CRLM). The combined method needs to be adapted to increase the sensitivity and specificity before it can be implemented in the clinic. This mass spectrometry study aimed to identify additional collagen NOPs in urine to further increase the sensitivity and specificity of our previously published method and search for the most discriminating NOP panel. The new assay was developed based on urine samples from 100 healthy controls and 100 patients suffering from CRLM. Two additional NOPs were identified: GPPGEAGK(-OH)P(-OH)GEQGVP(-OH)GDLGAP(-OH)GP (GPP) originating from collagen alpha-1(I) and GNDGARGSDGQPGPP(-OH)GP(-OH)P(-OH)GTAGFP(-OH)GSP(-OH)GAK(-OH)GEVGP (GND) originating from collagen alpha-1(III). A molecular model combining NOPs (AGP, GPP, and GND) and CEA was generated. Molecules that did not contribute to the diagnostic power of the model were removed, resulting in a model only consisting of GND and CEA. In this model, 86% sensitivity and 84% specificity in the discovery set, and 92% sensitivity and 90% specificity in the validation set were reached. These percentages are significantly higher than the current model based on AGP and CEA (p=0.032). The performance of the new model is better than the currently used techniques in the clinic (e.g. CT-scan, ultrasound, serum CEA), which have a sensitivity between 57-70% and a specificity between 90-96%.
2019-11-15 | PXD013533 | Pride
Project description:Although non muscle-invasive bladder cancer can be treated successfully by surgical resection, there is a high rate of recurrence, which frequently develops into an invasive form of cancer. Due to the lack of marker molecules to predict recurrence, it is currently recommended that after resection each patient is screened via cystoscopy at least twice a year. This results in a psychic burden to the patient and substantial economic costs to the health care system. Using antibody microarrays targeting 724 different cancer-related proteins, we studied protein profiles of patients with and without recurrence. The analysis revealed 255 proteins of differential abundance. Most are involved in the regulation and execution of apoptosis and cell proliferation. For prognosis, a signature of 20 proteins was determined that predicts bladder cancer recurrence with 100% sensitivity and 80% specificity. As a measure of overall accuracy, the area under the curve (AUC) value was found to be 90%. This is well within a clinically relevant window of quality and should support decision making about the stringency of surveillance or even different treatment options.
2014-04-07 | E-MEXP-3625 | biostudies-arrayexpress
Project description:Comparison of commercially available histone antibodies
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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:Lung cancer remains the leading cause of cancer death worldwide. Overall 5-year survival is about 10-15% and despite curative intent surgery, treatment failure is primarily due to recurrent disease. Conventional prognostic markers are unable to determine which patients with completely resected disease within each stage group are likely to relapse. To identify a gene signature associated with recurrent squamous cell carcinoma (SCC) of lung, we analyzed primary tumour gene expression for a total of fifty-one SCCs (stage I-III) on 22,323 element microarrays, comparing expression profiles for individuals who remained disease-free for a minimum of 36 months with those from individuals whose disease recurred within 18 months of complete resection. Cox proportional hazards modeling with leave-one-out cross-validation identified a 70-gene capable of predicting the likelihood of tumor recurrence and a 79-gene signature predictive for overall survival. These two signatures were pooled to generate a 111-gene classifier which achieved an overall predictive accuracy for disease recurrence of 72% (77% sensitivity, 67% specificity) in an independent set of fifty-eight stage I-III SCCs. This classifier also predicted differences in survival (log-rank P=0.0008, hazard ratio (HR), 3.8 [95% confidence interval, 1.6-8.7]), and was superior to conventional prognostic markers such as TNM stage or N stage in predicting patient outcome. Genome-wide profiling has revealed a distinct gene expression profile for recurrent lung SCC which may be clinically useful as a prognostic tool. Expression profiling using 22K element microarrays of 51 primary lung squamous cell carcinomas.
2010-07-01 | E-GEOD-5123 | biostudies-arrayexpress
Project description:nCounter miRNA Expression Assay data for all profiled miRQC samples prepared by the miRQC Consortium. In this study, we systematically compared 12 commercially available miRNA expression platforms by measuring an identical set of standardized positive and negative control samples, including human universal reference RNA, human brain RNA and titrations thereof, human serum samples, and synthetic spikes from miRNA family members with varying homology. We developed novel and robust quality metrics to objectively assess platform performance of very different technologies such as small RNA sequencing, RT-qPCR and (microarray) hybridization. We assessed reproducibility, sensitivity, accuracy, specificity, and concordance of differential expression. miRQC Consortium multi-platform comparision. *This represents the NanoString component only
2013-12-30 | E-GEOD-49600 | biostudies-arrayexpress
Project description:nCounter miRNA Expression Assay data for all profiled miRQC samples prepared by the miRQC Consortium. In this study, we systematically compared 12 commercially available miRNA expression platforms by measuring an identical set of standardized positive and negative control samples, including human universal reference RNA, human brain RNA and titrations thereof, human serum samples, and synthetic spikes from miRNA family members with varying homology. We developed novel and robust quality metrics to objectively assess platform performance of very different technologies such as small RNA sequencing, RT-qPCR and (microarray) hybridization. We assessed reproducibility, sensitivity, accuracy, specificity, and concordance of differential expression.
2013-12-30 | GSE49600 | GEO
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