Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR27875600_1.fastq.gz | Fastqsanger.gz | |||
| SRR27875600_2.fastq.gz | Fastqsanger.gz | |||
| SRR27875700_1.fastq.gz | Fastqsanger.gz | |||
| SRR27875700_2.fastq.gz | Fastqsanger.gz | |||
| SRR27875601_1.fastq.gz | Fastqsanger.gz |
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Project description:Nano-Enabled, Antimicrobial Toothbrushes – Hyper Hygienic or Health Hazard?
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Project description:Primary objectives: To investigate if Cox proportional hazard models based on tumor standardized uptake values and tumor volume measurements from 18FDG PET/CT and 64Cu-DOTATATE PET/CT are both prognostic of progression free survival and overall survival; and if Cox proportional hazard models based on tumor standardized uptake values and tumor volume measurements derived from combined 18FDG and 64Cu-DOTATATE PET/CT provide stronger prognostic information than 18FDG PET/CT or 64Cu-DOTATATE PET/CT alone.
Primary endpoints: Overall survival (OS) and progression free survival (PFS).
| 2756176 | ecrin-mdr-crc
Project description:A seven-lncRNA signature was identified in the training set, which is significantly associated with overall survival (OS) (Hazard Ratio [HR]: 3.535, 95% confidence interval [CI]: 2.113-5.915, P < 0.001) and disease-free survival (DFS) (Hazard Ratio [HR]: 2.413, 95% confidence interval [CI]: 1.573-3.703, P < 0.001). Patients in high-risk group have shorter overall survival (HR: 3.555, 95% CI: 2.195-5.757, p < 0.001) and disease-free survival (HR: 2.537, 95% CI: 1.646-3.909, p < 0.001) in the training set, and we found the same conclusion in the independent set for OS (HR 2.665, p < 0.001) and DFS (HR 2.360, p = 0.001). Combination of the signature and TNM staging system was more powerful than TNM staging system alone in predicting outcomes in both the training set (AUC: 0.772 vs 0.681, p = 0.002) and in the independent set (AUC: 0.772 vs 0.660, p = 0.003).
2020-02-10 | GSE92986 | GEO
Project description:There is a need to move from binary hazard assessment to more quantitative assessment of genotoxicity to better inform human health risk assessment and understand the relevance of positive in vitro genotoxicity findings. New approach methodologies (NAMs), including transcriptomic biomarkers combined with high-throughput technologies, enable the testing of a broad concentration range, which allows quantitative assessment of in vitro results. Initial work with the transcriptomic GENOMARK and TGx-DDI biomarkers demonstrate their potential use for hazard identification and chemical prioritization; however, no study has evaluated the concordance and complementarity of GENOMARK and TGx-DDI. The overall aim of this study is to examine if a combined approach of integrating both transcriptomic biomarkers for genotoxicity in human relevant HepaRGTM cells increases the certainty in hazard calls and potency rankings of chemicals. A sub-aim is to investigate whether GENOMARK is applicable to the TempO-Seq® high-throughput sequencing technology, to collect concentration-response data to rapidly perform hazard classification and potency ranking. Therefore, HepaRGTM cells were exposed to 10 chemicals (i.e. eight known in vivo genotoxicants and two in vivo non-genotoxicants) in increasing concentrations over 72h. TempO-Seq® was used to obtain concentration-response data for both biomarkers. Benchmark concentration (BMC) modelling of chemicals that were classified positive was conducted to obtain BMCs and transcriptomic points of departure (tPODs) for potency ranking. The results confirm that GENOMARK is applicable to TempO-Seq® since it achieved 100% predictive accuracy. In addition, a high concordance was observed in the hazard classifications and potency rankings between both biomarkers. Overall, our findings show that in vitro transcriptomic data can be used to rapidly and effectively identify genotoxic hazards while simultaneously providing additional insights on potency that is more informative in a modern hazard assessment paradigm. The results of this case study support the high value of integrating these NAMs in a weight of evidence evaluation of genotoxicity using the important human-liver cell line.
2024-03-27 | GSE241068 | GEO
Project description:There is a need to move from binary hazard assessment to more quantitative assessment of genotoxicity to better inform human health risk assessment and understand the relevance of positive in vitro genotoxicity findings. New approach methodologies (NAMs), including transcriptomic biomarkers combined with high-throughput technologies, enable the testing of a broad concentration range, which allows quantitative assessment of in vitro results. Initial work with the transcriptomic GENOMARK and TGx-DDI biomarkers demonstrate their potential use for hazard identification and chemical prioritization; however, no study has evaluated the concordance and complementarity of GENOMARK and TGx-DDI. The overall aim of this study is to examine if a combined approach of integrating both transcriptomic biomarkers for genotoxicity in human relevant HepaRGTM cells increases the certainty in hazard calls and potency rankings of chemicals. A sub-aim is to investigate whether GENOMARK is applicable to the TempO-Seq® high-throughput sequencing technology, to collect concentration-response data to rapidly perform hazard classification and potency ranking. Therefore, HepaRGTM cells were exposed to 10 chemicals (i.e. eight known in vivo genotoxicants and two in vivo non-genotoxicants) in increasing concentrations over 72h. TempO-Seq® was used to obtain concentration-response data for both biomarkers. Benchmark concentration (BMC) modelling of chemicals that were classified positive was conducted to obtain BMCs and transcriptomic points of departure (tPODs) for potency ranking. The results confirm that GENOMARK is applicable to TempO-Seq® since it achieved 100% predictive accuracy. In addition, a high concordance was observed in the hazard classifications and potency rankings between both biomarkers. Overall, our findings show that in vitro transcriptomic data can be used to rapidly and effectively identify genotoxic hazards while simultaneously providing additional insights on potency that is more informative in a modern hazard assessment paradigm. The results of this case study support the high value of integrating these NAMs in a weight of evidence evaluation of genotoxicity using the important human-liver cell line.
2024-03-27 | GSE241067 | GEO
Project description:Purpose Chromosomal aberrations are a hallmark of multiple myeloma but their global prognostic impact is largely unknown. Methods We performed a genome-wide analysis of malignant plasma cells from 192 newly myeloma patients using high-density, single-nucleotide polymorphism (SNP) arrays to identify genetic lesions associated with prognosis. Results Our analyses revealed deletions and amplifications in 98% of cases. Amplifications in 1q and deletions in 1p, 12p, 14q, 16q, and 22q were the most frequent lesions associated with adverse prognosis while recurrent amplifications of chromosomes 5, 9, 11, 15 and 19 conferred a favorable prognosis. Multivariate analysis retained three independent lesions: amp(1q23.3), amp(5q31.3) and del(12p13.31). When adjusted to the established prognostic variables ie t(4;14), and serum beta2-microglobulin (Sb2M), del(12p13.31) remained the most powerful independent marker (P <.0001; hazard ratio = 3.17) followed by Sb2M (P <.0001; hazard ratio = 2.78) and amp(5q31.3) (P =.0005; hazard ratio = 0.37). Cases with amp(5q31.3) alone and low Sb2M had an excellent prognosis (5-year overall survival = 87%) conversely cases with del(12p13.31) alone or amp(5q31.3) and del(12p13.31) and high Sb2M had a very poor outcome (5-year overall survival = 20%). Moreover, integration of SNP mapping and gene expression identified CD27 as potential critical gene responsible for poor prognosis of del(12p) myeloma patients. Conclusion These findings demonstrate the power and accessibility of molecular karyotyping to identify novel strong independent prognostic markers: amp(5q31.3) and del(12p13.31) and to provide insights into putative pathways deregulated in sub classes of cancer patients. Keywords: Human chromosome copy-number alterations study
2009-08-20 | GSE12896 | GEO