Thrombus proteomics reveals new candidate biomarkers of stroke etiology
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ABSTRACT:
ORGANISM(S): Homo Sapiens (human)
SUBMITTER: Maite Mendioroz
PROVIDER: PXD042442 | JPOST Repository | Fri May 24 00:00:00 BST 2024
REPOSITORIES: jPOST
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Project description:Acute myeloid leukemia (AML) in the elderly remains a clinical challenge, with a five-year overall survival less than 10%. The current ELN 2017 genetic risk classification considers cytogenetic and mutational characteristics to stratify fit AML patients into different prognostic groups. However, this classification is not validated for elderly patients treated with a non-intensive approach, and its performance seems to be suboptimal in this context. Indeed, the transcriptomic landscape of AML in the elderly has been less explored and it might help stratify this group of patients. In the current study, we analyzed the transcriptome of 224 AML patients > 65 years-old at diagnosis treated in the Spanish PETHEMA-FLUGAZA clinical trial and tried to define new prognostic groups in this population. We identified a specific transcriptomic signature for high-risk patients with mutated p53 or complex karyotype, revealing that low expression of B7H3 gene with high expression of BANP gene distinguish a subset of AML patients surviving more than 12 months. This specific signature highlights the potential of transcriptomics to identify biomarkers of good prognosis in elderly AML and recognizes these two genes as possible therapeutic targets in this malignancy.
2022-11-16 | GSE208218 | GEO
Project description:The clinical course of prostate cancer (PCa) is highly variable, demanding an individualized approach to therapy and robust prognostic markers for treatment decisions. We here present a random forest-based classification model to predict aggressive behaviour of PCa. DNA methylation changes between PCa cases with good or poor prognosis (discovery cohort with n=78) were used as input. The model was validated with data from two independent PCa cohorts from ICGC and TCGA. Ranking of cancer progression-related DNA methylation changes allowed selection of candidate genes for additional validation by immunohistochemistry. We identified loss of ZIC2 protein expression as a promising novel prognostic biomarker for PCa in >12,000 tissue micro-array tumors. The prognostic value of ZIC2 proved to be independent from established clinico-pathological variables including Gleason, stage, nodal stage and PSA. In summary, we have developed a PCa classification model which either directly or via expression analyses of the identified top ranked candidate genes might help in decision making related to the treatment of prostate cancer patients.
2019-10-29 | GSE127985 | GEO
Project description:Multi-omics molecular profiling was performed on post-radical prostatectomy material from a cohort of 132 patients with localized prostate adenocarcinoma. Unsupervised classification techniques were used to build a comprehensive classification of prostate tumours based on three molecular levels: DNA copy number, DNA methylation, and mRNA expression.
2018-07-09 | E-MTAB-6127 | biostudies-arrayexpress
Project description:Multi-omics molecular profiling was performed on post-radical prostatectomy material from a cohort of 132 patients with localized prostate adenocarcinoma. Unsupervised classification techniques were used to build a comprehensive classification of prostate tumours based on three molecular levels: DNA copy number, DNA methylation, and mRNA expression.
2018-06-24 | E-MTAB-6128 | biostudies-arrayexpress
Project description:Multi-omics molecular profiling was performed on post-radical prostatectomy material from a cohort of 132 patients with localized prostate adenocarcinoma. Unsupervised classification techniques were used to build a comprehensive classification of prostate tumours based on three molecular levels: DNA copy number, DNA methylation, and mRNA expression.
2018-06-24 | E-MTAB-6126 | biostudies-arrayexpress
Project description:Multi-omics molecular profiling was performed on post-radical prostatectomy material from a cohort of 132 patients with localized prostate adenocarcinoma. Unsupervised classification techniques were used to build a comprehensive classification of prostate tumours based on three molecular levels: DNA copy number, DNA methylation, and mRNA expression.
2018-06-24 | E-MTAB-6131 | biostudies-arrayexpress
Project description:Background: Preeclampsia (PE) is a placental disease characterized by hypertension and proteinuria in pregnant women, which is associated with a high maternal and infantile morbidity. However, circulating biomarkers able to predict the prognosis of PE are lacking. Methods: Thirty-eight women were included in the study. They consisted of 19 patients with PE (13 with severe PE and 6 women with non-severe PE) and 19 gestational age-matched normal pregnancy controls. We measured coagulation pathway, endothelial responses and microparticle release and circulating gene expression in PE patient groups and normotensive controls. Results: The measurement of markers associated with coagulation pathway, endothelial activation and circulating microparticles enabled to discriminate PE from normal pregnancy but were not sufficient to distinguish severe from non-severe PE. PE patients also exhibited a specific transcriptional program distinct from that of control women and subtle differences were observed between severe and non-severe PE. Functional annotation of the up-modulated signature in PE highlighted two main functions related to ribosome and complement. Importantly, we found that 8 genes were specifically up-modulated in severe preeclampsia. Among these genes, the expression of VSIG4 was significantly increased in patients with severe preeclampsia in comparison with controls and patients with non-severe preeclampsia. Conclusion: Using transcriptional signatures of blood samples, we identified the gene encoding the estrogen receptor as a potential diagnostic marker of severe preeclampsia. In addition, the determination of this gene may improve the prognostic assessment of severe preeclampsia. Thirty-eight women were included in the study: 19 patients with PE, including 6 women with non-severe PE and 13 with severe PE, and 19 women with normal pregnancy (NP) selected according to age, weight, smoking status, race, gestational age at the inclusion, and blood pH (Table 1 of manuscript). Women with NP had no history of medical illness or medication, and received routing prenatal care. The diagnostic of PE was based on a blood pressure of M-bM-^IM-% 140/90 mmHg taken twice, uricemia above normal laboratory range (120-420 M-BM-5mol/L), and proteinuria higher than 300 mg in a 24 hour-collection, occurring after 20 gestational weeks in previously normotensive women (Table 2). The criteria used to define severe PE included one of the following conditions: a blood pressure higher than 160/110 mmHg, a proteinuria higher than 1500 mg/24h), a multisystem disorder, maternal cerebral symptoms (seizures, stroke) or intrauterine growth restriction below the 3M-BM-0 percentile. Women with multiple gestations, fetal congenital malformations/chromosomal abnormalities, recent infection, antiphospholipid antibodies, trauma, drug or alcohol abuse during pregnancy, preexisting hypertension, thrombophilia with PE history, or women receiving anticoagulant or antiaggregation therapy were excluded from the study. Two microarrays (one non-severe PE and one normal) were discarded from the analysis for technical reasons. Thus, only 36 microarrays are included here.
2014-05-14 | E-GEOD-48424 | biostudies-arrayexpress
Project description:Background: Preeclampsia (PE) is a placental disease characterized by hypertension and proteinuria in pregnant women, which is associated with a high maternal and infantile morbidity. However, circulating biomarkers able to predict the prognosis of PE are lacking. Methods: Thirty-eight women were included in the study. They consisted of 19 patients with PE (13 with severe PE and 6 women with non-severe PE) and 19 gestational age-matched normal pregnancy controls. We measured coagulation pathway, endothelial responses and microparticle release and circulating gene expression in PE patient groups and normotensive controls. Results: The measurement of markers associated with coagulation pathway, endothelial activation and circulating microparticles enabled to discriminate PE from normal pregnancy but were not sufficient to distinguish severe from non-severe PE. PE patients also exhibited a specific transcriptional program distinct from that of control women and subtle differences were observed between severe and non-severe PE. Functional annotation of the up-modulated signature in PE highlighted two main functions related to ribosome and complement. Importantly, we found that 8 genes were specifically up-modulated in severe preeclampsia. Among these genes, the expression of VSIG4 was significantly increased in patients with severe preeclampsia in comparison with controls and patients with non-severe preeclampsia. Conclusion: Using transcriptional signatures of blood samples, we identified the gene encoding the estrogen receptor as a potential diagnostic marker of severe preeclampsia. In addition, the determination of this gene may improve the prognostic assessment of severe preeclampsia.
2014-05-14 | GSE48424 | GEO
Project description:Detection of DNA hypermethylation has emerged as a novel molecular biomarker for the evaluation of prostate cancer diagnosis and prognosis, but the use of single gene hypermethylation could produce unspecific results. Defining the specific gene hypermethylation profile for prostate cancer could provide groups of genes that specifically discriminate the patients with indolent and aggressive tumors. To compare the methylation profile of normal and malignant prostate we performed Genome-wide methylation analysis on 83 tumor samples, that included all clinical stages of the disease, 10 normal prostate samples and LNCaP, DU145 and PC3 prostate cancer cell lines using the GoldenGate Methylation Cancer Panel I (Illumina, Inc.) that interrogate for 1505 CpGs. We found 41 genes significantly hypermethylated in more than 20% of the tumors analyzed (p<0.01). Of these we identified GSTM2 and PENK as novel hypermethylated genes in prostate cancer that were simultaneously methylated in 40.9% of the tumors analyzed. We also identified panels of genes more frequently methylated in tumor samples with clinico-pathological indicators of poor prognosis: high Gleason score, elevated Ki-67 or advanced disease. Of these, we found that simultaneous hypermethylation of CFTR and HTR1B is common in patients with high Gleason score and high ki-67 levels and might signal the population at higher risk of therapeutic failure. DNA hypermethylation profile was associated with cancer-specific mortality (log-rank, p=0.007) and biochemical recurrence-free survival (log-rank, p=0.0008). In conclusion, our data strongly indicate that epigenetic silencing of GSTM2 and PENK is a common event in prostate cancer that could be used as a molecular marker for prostate cancer diagnosis. In addition, simultaneous HTR1B and CFTR hypermethylation could help discriminate aggressive from indolent prostate tumors.A DNA hypermethylation profile associated with cancer-specific mortality and biochemical recurrence in patients receiving radical prostatectomy is presented. GST2 and PENK are new hipermethylated genes identified. Simultaneous hypermethylation of CFTR and HTR1B could help discriminate aggressive disease.
2014-12-31 | GSE46177 | GEO
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