Field construction for diagnosis tool inspection of colorectal cancer and precancerous lesions using newly developed biomarker
Ontology highlight
ABSTRACT:
DISEASE(S): Colorectal Cancer
PROVIDER: 2635555 | ecrin-mdr-crc |
REPOSITORIES: ECRIN MDR
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Project description:PurposeThis study was conducted to investigate the feasibility of a newly developed wide-field dual-array suprachoroidal-transretinal stimulation (STS) prosthesis in dogs and to examine its biocompatibility and stability over a 4-month period.MethodsThree types of STS dual arrays were designed and tested. The STS dual-array was implanted into a scleral pocket of the left eye of six healthy beagle dogs. Ophthalmic examinations, fundus photography, fluorescein angiography (FA), electroretinography (ERG), and functional testing of this system were conducted postoperatively. The dogs were euthanatized at the end of the experiment, and their eyes were enucleated and histologically examined.ResultsAll prostheses were successfully implanted without complications, and no serious adverse event occurred during the postoperative period. Fundus photographs and FA showed no serious damage in the retina surrounding the arrays. The ERGs recorded from the implanted eyes showed no significant differences from those from control eyes. Histological evaluations demonstrated good preservation of the retina over the array. However, system failure occurred in 50% of the dogs owing to dog-specific habits.ConclusionsImplantation of this prosthesis system in dogs is feasible and can be performed without significant damage to the eye. The biocompatibility and stability of the array were good during the observation period, but the low durability of the system against dogs (not humans) is an issue to be resolved in the future.Translational relevanceThis study suggests that this wide-field dual-array prosthesis might widen the visual field and might be useful for patients with retinitis pigmentosa.
| S-EPMC7961109 | biostudies-literature
Project description:Sub-clinical acute rejection (subAR) in kidney transplant recipients (KTR) leads to chronic rejection and graft loss. Non-invasive biomarkers are needed to detect subAR. 307 KTR were enrolled into a multi-center observational study. Precise clinical phenotypes (CP) were used to define subAR. Differential gene expression (DGE) data from peripheral blood samples paired with surveillance biopsies were used to train a Random Forests (RF) model to develop a gene expression profile (GEP) for subAR. A separate cohort of paired samples was used to validate the GEP. Clinical endpoints and gene pathway mapping were used to assess clinical validity and biologic relevance. DGE data from 530 samples (130 subAR) collected from 250 KTR yielded a RF model: AUC 0.85; 0.84 after internal validation with bootstrap resampling. We selected a predicted probability threshold favoring specificity and NPV (87% and 88%) over sensitivity and PPV (64% and 61%, respectively). We tested the locked model/threshold on a separate cohort of 138 KTR undergoing surveillance biopsies at our institution (rejection 42; no rejection 96): NPV 78%; PPV 51%; AUC 0.66. Both the CP and GEP of subAR within the first 12 months following transplantation were independently associated with worse graft outcomes at 24 months, including de novo donor-specific antibody (DSA). Serial GEP tracked with response to treatment of subAR. DGE data from both cohorts mapped to gene pathways indicative of allograft rejection.
2018-07-24 | GSE107503 | GEO
Project description:Sub-clinical acute rejection (subAR) in kidney transplant recipients (KTR) leads to chronic rejection and graft loss. Non-invasive biomarkers are needed to detect subAR. 307 KTR were enrolled into a multi-center observational study. Precise clinical phenotypes (CP) were used to define subAR. Differential gene expression (DGE) data from peripheral blood samples paired with surveillance biopsies were used to train a Random Forests (RF) model to develop a gene expression profile (GEP) for subAR. A separate cohort of paired samples was used to validate the GEP. Clinical endpoints and gene pathway mapping were used to assess clinical validity and biologic relevance. DGE data from 530 samples (130 subAR) collected from 250 KTR yielded a RF model: AUC 0.85; 0.84 after internal validation with bootstrap resampling. We selected a predicted probability threshold favoring specificity and NPV (87% and 88%) over sensitivity and PPV (64% and 61%, respectively). We tested the locked model/threshold on a separate cohort of 138 KTR undergoing surveillance biopsies at our institution (rejection 42; no rejection 96): NPV 78%; PPV 51%; AUC 0.66. Both the CP and GEP of subAR within the first 12 months following transplantation were independently associated with worse graft outcomes at 24 months, including de novo donor-specific antibody (DSA). Serial GEP tracked with response to treatment of subAR. DGE data from both cohorts mapped to gene pathways indicative of allograft rejection.
2018-07-24 | GSE107506 | GEO
Project description:Although preoperative chemoradiotherapy (CRT) and surgical mesorectal resection is the standard of care for locally advanced rectal carcinomas, it is still difficult to predict which patients will respond to treatment. We explored how differential stromal transcriptomic profiles from microdissected pretreatment rectal biopsies can be used to define an immunohistochemical score based on two CAF-specific proteins for predicting neoadjuvant treatment response. The analysis of differentially expressed genes (DEGs) of stroma and tumour glands from responder and non-responder patients shows that most changes were associated with the stromal compartment. Gene ontology analysis revealed that the DEGs codify mainly for extracellular matrix and ribosomal components. We built a CAF-specific classifier with genes showing monotonic changes in expression according to the tumour regression grade (coefficient >1; FN1, COL3A1, COL1A1, MMP2 and IGFBP5). These are the genes that display the biggest a priori differences in expression between non-responder and responder stroma. We translated these five genes at the protein level by means of immunohistochemical staining in a cohort of 38 patients. For predictive purposes we used a leave-one-out cross-validated (LOOCV) model with a positive predictive value (PPV) of 80%. Classifier optimisation with Random Forest identified FN1 and COL3A1 as the best predictors. Rebuilding the LOOCV regression model improved the classification performance with a PPV of 89.5% and a negative predictive value (NPV) of 73.7%. An independent cohort of 36 patients was used to validate the classifier performance, which had a PPV of 84.2% and an NPV of 70.6%. In a multivariate analysis the two-protein classifier proved to be the only independent predictor of response (HR=2.58; P=0.003). We also explored a pharmacogenomic approach to gather information about possible therapeutic strategies for non-responder patients. In conclusion, we developed a two-protein immunohistochemical classifier that performs well at predicting the absence of response to neoadjuvant treatment in rectal cancer.
2017-01-11 | GSE93375 | GEO
Project description:Interventions: Collection of whole-stool samples for stool testing primary to surveillance colonoscopy and the completion of a questionnaire.
Primary outcome(s): 1. The accuracy (sensitivity, specificity, PPV and NPV) of the molecular stool test (Cologuard) and FIT compared to colonoscopy in the detection of advanced neoplasia in a surveillance population.
2. Health outcomes and cost-effectiveness of multiple surveillance strategies based on accuracies from endpoint 1.
Study Design: N/A: single arm study, Double blinded (masking used), N/A , unknown, Parallel
| 19571 | ecrin-mdr-crc
Project description:Interventions: Gold Standard:Clinical outcome;Index test:Study on endogenous biomarkers by targeted metabonomics
Primary outcome(s): SEN, SPE, ACC, AUC of ROC, PPV, NPV
Study Design: Sequential
| 2698756 | ecrin-mdr-crc
Project description:Metabolic diseases are strongly associated with endoplasmic reticulum (ER) stress. Upon ER stress, the unfolded protein response (UPR) is activated to limit cellular damage. However, escalating cellular UPR response weakens with age. Here, we show that 5-day-old Caenorhabditis elegans fed a bacteria diet with 2% glucose (high glucose diet, HGD-5) extend their lifespan while shortening the lifespan of 1-day-old (HGD-1) animals. We observed a metabolic shift in HGD-1 as glucose and fertility synergistically prolonged the lifespan of HGD-5, independently of DAF-16. Notably, we identified that UPR stress sensors ATF-6 and PEK-1 extended the longevity of HGD-5 worms, while the ire-1 ablation drastically increased HGD-1 lifespan. Based on these observations, we postulate that HGD activates the otherwise quiescent UPR in aged worms to overcome ageing-related stress and restore ER homeostasis. In contrast, young animals subjected to HGD provokes unresolved ER stress, conversely leading to a detrimental stress response.
2021-08-31 | GSE182981 | GEO
Project description:BackgroundField pea (Pisum sativum L.) is among the prominent crops in the world as food and feed. There are relatively few simple sequence repeat (SSR) markers developed from expressed sequence tags (ESTs) in P. sativum.ResultsIn the present study, 15 new EST-SSR markers were developed from publicly available ESTs. These markers have successfully amplified their target loci across seven Pisum sativum subsp. sativum accessions. Eleven (73%) of these SSRs were trinucleotide repeats, two (13%) dinucleotide and two (13%) were hexanucleotide repeats. Across-taxa transferability of these new markers was also tested on other subspecies of Pisum as well as on P. fulvum, Vicia faba and Lens culinaris. In Pisum sativum subsp. sativum, 13 of the 15 markers were polymorphic and 12 of them subsequently used for genetic diversity analysis. Forty six accessions, of which 43 were from Ethiopia, were subjected to genetic diversity analysis using these newly developed markers. All accessions were represented by 12 individuals except two (NGB103816 and 237508) that were represented by 9 and 11 individuals, respectively. A total of 37 alleles were detected across all accessions. PS10 was the most polymorphic locus with six alleles, and the average number of alleles per locus over the 12 polymorphic loci was 3.1. Several rare and private alleles were also revealed. The most distinct accession (32048) had private alleles at three loci with 100% frequency.ConclusionThese newly developed EST-SSR primer-pairs successfully amplified expected loci in P. sativum subsp. sativum as well as in other subspecies of the genus Pisum and related genera. High levels of genetic variation were detected in field pea accessions from Ethiopia using these markers. This result implies the potential of the Ethiopian field pea gene pool for improvement of field peas in various desirable traits. In addition, these markers could be a valuable asset in resolving the inconsistency in the taxonomic status of the different subspecies of genus Pisum as well as for characterization of field pea accessions in different gene banks around the world for breeding and conservation purposes.
| S-EPMC4541747 | biostudies-literature
Project description:Purpose: Despite advances in radical surgery and chemotherapy delivery, ovarian cancer is the most lethal gynecologic malignancy. Most of these patients are treated with platinum-based chemotherapies, but there is no biomarker model to guide their responses to these therapeutic agents. We have developed and independently tested our novel multivariate molecular predictors for forecasting patients' responses to individual drugs on a cohort of 58 ovarian cancer patients. Experimental Design: We adapted and applied the previously-published COXEN algorithm to develop molecular predictors for therapeutic responses of patients' tumors based on expression signatures derived from the NCI-60 in vitro drug activities and genomic expression data. Genome-wide candidate biomarkers were first triaged by examining expression patterns of frozen and formalin-fixed paraffin embedded (FFPE) tissue samples. We then identify initial drug sensitivity biomarkers for carboplatin and paclitaxel, respectively. These biomarkers were further narrowed by examining concordant expression patterns between cell lines and a historical set of ovarian cancer patients. Multivariate predictors were obtained from the NCI-60 cell lines and refined using historical patient cohorts. To independent validate these molecular predictors, we performed genome-wide profiling on FFPE samples of 58 ovarian cancer patients obtained prior to adjuvant chemotherapy. Results: Carboplatin predictor significantly stratified platinum sensitive and resistant patients (p = 0.019) with sensitivity = 93%, specificity = 33%, PPV = 65%, and NPV = 78%. Paclitaxel predictor also significantly stratified patients' responses (p = 0.033) with sensitivity = 96%, specificity = 26%, PPV = 61%, and NPV = 86%. The combination predictor for platinum-taxane combination demonstrated a significant survival difference between the predicted responders and nonresponders with median survival of 12.9 months vs. 8.1 months (p = 0.045). Conclusions: COXEN predictors successfully stratified platinum resistance and taxane response in this retrospective cohort, especially based on their FFPE tumor samples. Accurate prediction of chemotherapeutic response, especially to platinum agents is highly clinically relevant and could alter primary management of ovarian cancer. Gene expression data from 58 stage III-IV ovarian cancer patients treated with Carboplatin and Taxol agents
2012-08-21 | E-GEOD-30161 | biostudies-arrayexpress
Project description:Purpose: Despite advances in radical surgery and chemotherapy delivery, ovarian cancer is the most lethal gynecologic malignancy. Most of these patients are treated with platinum-based chemotherapies, but there is no biomarker model to guide their responses to these therapeutic agents. We have developed and independently tested our novel multivariate molecular predictors for forecasting patients' responses to individual drugs on a cohort of 58 ovarian cancer patients. Experimental Design: We adapted and applied the previously-published COXEN algorithm to develop molecular predictors for therapeutic responses of patients' tumors based on expression signatures derived from the NCI-60 in vitro drug activities and genomic expression data. Genome-wide candidate biomarkers were first triaged by examining expression patterns of frozen and formalin-fixed paraffin embedded (FFPE) tissue samples. We then identify initial drug sensitivity biomarkers for carboplatin and paclitaxel, respectively. These biomarkers were further narrowed by examining concordant expression patterns between cell lines and a historical set of ovarian cancer patients. Multivariate predictors were obtained from the NCI-60 cell lines and refined using historical patient cohorts. To independent validate these molecular predictors, we performed genome-wide profiling on FFPE samples of 58 ovarian cancer patients obtained prior to adjuvant chemotherapy. Results: Carboplatin predictor significantly stratified platinum sensitive and resistant patients (p = 0.019) with sensitivity = 93%, specificity = 33%, PPV = 65%, and NPV = 78%. Paclitaxel predictor also significantly stratified patients' responses (p = 0.033) with sensitivity = 96%, specificity = 26%, PPV = 61%, and NPV = 86%. The combination predictor for platinum-taxane combination demonstrated a significant survival difference between the predicted responders and nonresponders with median survival of 12.9 months vs. 8.1 months (p = 0.045). Conclusions: COXEN predictors successfully stratified platinum resistance and taxane response in this retrospective cohort, especially based on their FFPE tumor samples. Accurate prediction of chemotherapeutic response, especially to platinum agents is highly clinically relevant and could alter primary management of ovarian cancer.
2012-08-21 | GSE30161 | GEO