Methylation mediated LINC00261 suppresses pancreatic cancer progression
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE152012 | GEO | 2023/06/08
REPOSITORIES: GEO
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Project description:Background: Promising results from recent clinical trials on the approved antisense oligonucleotide nusinersen in pediatric patients with 5q-linked spinal muscular atrophy (SMA) still have to be confirmed in adult patients but are hindered by a lack of sensitive biomarkers that indicate an early therapeutic response. Changes of the overall neurochemical composition of cerebrospinal fluid (CSF) under therapy may yield additive diagnostic and predictive information. Methods: In this prospective proof-of-concept and feasibility study, we evaluated non-targeted CSF proteomic profiles by mass spectrometry along with basic CSF parameters of ten adult patients with SMA types II or III before and after ten months of nusinersen therapy, in comparison with ten age- and gender-matched controls. These data were bioinformatically analyzed and correlated with clinical outcomes assessed by the Hammersmith Functional Rating Scale Expanded (HFMSE). Results: CSF proteomic profiles of patients with SMA differed from controls. Two groups of SMA patients were identified based on unsupervised clustering. These groups differed in age and expression of proteins related to neuroregeneration or neurodegeneration. Intraindividual CSF differences in response to nusinersen treatment varied between patients who clinically improved and those who did not. Conclusions: Comparative CSF proteomic analysis in adult SMA patients before and after treatment identified subgroups and treatment-related changes and may therefore be suitable for diagnostic and predictive analysis. These results require verification in larger multicenter cohorts.
2019-12-18 | PXD015117 | Pride
Project description:BACKGROUND: Following fine needle aspiration, 15-30% of thyroid nodules are not clearly benign or malignant. These cytologically indeterminate nodules are often referred for diagnostic surgery, though most prove benign. A novel diagnostic test measuring the expression of 167 genes has shown promise in improving pre-operative risk assessment. We evaluated this test in a prospective, multicenter study. METHODS: Over 19 months, we performed a prospective study at 49 clinical sites enrolling 3,789 patients and collecting 4,812 samples from thyroid nodules >1cm requiring evaluation. We obtained 577 cytologically indeterminate aspirates with corresponding histopathology of excised lesions on 413. Central blinded histopathologic review served as the reference (“gold”) standard. After applying inclusion criteria, gene expression classifier results were obtained for 265 indeterminate nodules used in this analysis, and performance was calculated. RESULTS: 85 of 265 indeterminate nodules were malignant. The gene expression classifier correctly identified 78 of 85 as ‘suspicious’ (92% sensitivity, [84%-97%] 95% CI). Specificity was 52%, [44%-59%]. The negative predictive value was 95%, 94%, and 85%, respectively, for aspirates with AUS/FLUS, FN/SFN, or ‘suspicious’ cytology. Analysis of 7 false negative cases revealed 6 with a paucity of thyroid follicular cells, suggesting that insufficient sampling of the nodule had occurred. CONCLUSIONS: Though individualized clinical care is recommended, these data support consideration of a conservative approach for most patients with indeterminate FNA cytology and benign gene expression classifier results. 265 cytologically indetermine samples, 47 cytologically benign and 55 cytologically malignant samples
2012-06-24 | E-GEOD-34289 | biostudies-arrayexpress
Project description:Prospective, non-comparative Phase II multicenter trial (EXPRESSION EudraCT: 2008-006381-29) where the patients received three 3-week cycles of docetaxel (100 mg/m2) followed by three 3-week cycles of 5-fluorouracil (500 mg/m2), epirubicin (100 mg/m2), and cyclophosphamide (500 mg/m2) (FEC). The primary end point was the identification of a gene expression signature predictive of pathological complete response (pCR). In this trial, pCR was defined as absence of invasive or non-invasive cancer in the breast. External validation of the predictive performance was performed using publicly available data.
2020-11-15 | GSE140494 | GEO
Project description:Background: Preeclampsia (PE) is a multi-systemic maternal syndrome with substantial maternal and fetal morbidity and mortality. Currently, there is no clinically viable non-invasive biomarker assay for early detection, thus limiting the effective prevention and therapeutic strategies for PE. Methods: We conducted a discovery-training-validation three-phase retrospective and prospective study with cross-platform and multicenter cohorts. The initial biomarkers were discovered and verified in tissue specimens by small RNA sequencing and qRT-PCR. A miRNA signature (miR2PE-score) was developed using the Firth’s bias-reduced logistic regression analysis, and subsequently validated in two independent multinational retrospective cohorts and two prospective plasma cohorts. Results: We initially identified five PE-associated differentially expressed miRNAs from miRNA sequencing data and subsequently validated two miRNAs (miR-196b-5p and miR-584-5p) as robust biomarkers by association analysis with clinical characteristics and qRT-PCR in tissue specimens in the discovery phase. Using the Firth’s bias-reduced logistic regression analysis, we developed the miR2PE-score for the early detection of PE. The miR2PE-score showed a high diagnostic performance with an area under the receiver operating characteristic curve (AUROC) of 0.920, 0.848, 0.864 and 0.812 in training, internal and two external validation cross-platform and multicenter cohorts, respectively. Finally, we demonstrated the non-invasive diagnostic performance of the miR2PE-score in two prospective plasma cohorts with AUROC of 0.933 and 0.787. Furthermore, the miR2PE-score revealed superior performance in non-invasive diagnosis compared with previously published miRNA biomarkers. Conclusions: We developed and validated a novel and robust blood-based miRNA signature, which may serve as a promising clinically applicable non-invasive tool for the early detection of PE.
2022-09-21 | GSE206988 | GEO
Project description:Consider the problem of designing a panel of complex biomarkers to predict a patient's health or disease state when one can pair his or her current test sample, called a target sample, with the patient's previously acquired healthy sample, called a reference sample. As contrasted to a population averaged reference, this reference sample is individualized. Automated predictor algorithms that compare and contrast the paired samples to each other could result in a new generation of test panels that compare to a person's healthy reference to enhance predictive accuracy. This study develops such an individualized predictor and illustrates the added value of including the healthy reference for design of predictive gene expression panels. The objective is to predict each subject's state of infection, e.g., neither exposed nor infected, exposed but not infected, pre-acute phase of infection, acute phase of infection, post-acute phase of infection. Using gene microarray data collected in a large-scale serially sampled respiratory virus challenge study, we quantify the diagnostic advantage of pairing a person's baseline reference with his or her target sample.
2016-06-22 | GSE73072 | GEO
Project description:Advancing Negative Ion Mode Proteomics. The main objective of the project is the exploration of the unconvetional negative ion mode for proteomics studies. In this work, we thoroughly studied the best chromatographic conditions for negative ion mode proteomics before testing different enzymatic digestion. The final goal is to establish the best working conditions in the negative polarity for negative ion mode. The method also refrains from any fragmentation events, which are unpredictable in negative ion mode.
2023-07-20 | PXD040583 | Pride
Project description:Analysis of differentially expressing genes in whole genome wide analysis of aptamer SQ2 positive cells (Capan-1, Panc-1, Panc-1+ve) and SQ2 negative cells (Panc-1-ve and HPDE) Panc-1 +ve and Panc-1-ve cell lines were generated from Panc-1 cell line based upon its hetergenous binding to aptamer SQ2. Detailed procedure of generation of these cell lines are described in Pooja Dua, Hye Suk Kang, Seung-Mo Hong, Ming-Sound Tsao, Soyoun Kim, and Dong-ki Lee. 2012 Alkaline Phosphatase ALPPL2 is a novel pancreatic carcinoma-associated protein. Cancer Research A five chip study using total RNA recovered from Capan-1, Panc-1, Panc-1+ve, Panc-1-ve and HPDE cells. Each chip measures 45,033 genes with three 60 mer probe pairs per target.
2012-11-21 | E-GEOD-42428 | biostudies-arrayexpress
Project description:To develop and validate novel multigene signatures to facilitate individualized treatment of TNBC patients By integrating expression profiles of messenger RNAs (mRNAs) and long non-coding RNAs (lncRNAs). We analysed 165 TNBC samples and 33 paired normal breast tissues using transcriptome microarrays. Tumor-specific mRNAs and lncRNAs were identified and correlated with patientsâ?? recurrence-free survival (RFS). Using Cox regression model, we built two multigene signatures incorporating mRNAs and lncRNAs. The prognostic and predictive accuracy of the signatures were tested in a training set of 165 TNBC patients and validated in another 101 TNBC patients.
2016-01-04 | E-GEOD-76250 | biostudies-arrayexpress
Project description:PANC-1Tet/ZIC2 and PANC-1Tet/empty were established from human pancreatic cancer cell line PANC-1. PANC-1Tet/ZIC2 cells express FLAG-tagged human ZIC2 on the withdrawal of DOX. On the other hand, PANC-1Tet/empty was transfected an empty vector for the control experiment. To identify ZIC2 target genes, total RNAs were purified from the cells before and 48 hours after the DOX withdrawal. Gene expression profiles were analyzed by AGILENT human 4x44k cDNA microarray. As well as ZIC2-inducible system, we performed ZIC2-knockdown experiments in PANC-1 human pancreatic cancer cells. After 96 hours transfection of siRNAs for ZIC2 and its control, total RNAs were purified and gene expression profiles were analyzed by AGILENT human 4x44k cDNA microarray. ZIC2 target genes were identified in PANC-1 cells. Gene expression profiles of PANC-1Tet/ZIC2 and PANC-1Tet/empty cells were analyzed by AGILENT human 4x44k cDNA microarray before and 48 hours after the DOX withdrawal. As well as ZIC2-inducible system, gene expression profiles of control- and ZIC2-knocdown PANC-1 cells were also analyzed by AGILENT human 4x44k cDNA microarray.
2014-04-14 | E-GEOD-39704 | biostudies-arrayexpress
Project description:Background: Validated markers to predict outcome in rectal cancer patients treated with multimodal therapy remain elusive. Identifying molecular profiles for disease prognosis would be required for the design of clinical trials aimed at optimizing risk-adapted therapies. We have therefore used whole genome expression profiling of tumors of a large cohort of patients enrolled in the multicenter trials of the German Rectal Cancer Study Group (GRCSG) to identify molecular profiles for individualized therapy. Methods: We prospectively collected pretherapeutic biopsies from patients (n=300) treated according to the GRCSG trial guidelines from seven different German surgical departments using rigid quality controls. These samples were profiled by global gene expression analysis and a classifier developed to predict postoperative lymph node status and Disease Free Survival (DFS). The performance of the classifier was validated with an independent, prospectively collected set of samples. Findings: The final training and test set included 198 patients. Analyzes for postoperative nodal status and DFS revealed 69 and 674 differentially regulated genes, respectively. Depending on the classifier the accuracy to predict lymph node status ranged from 64% to 69% with negative predictive values between 72% and 74%. Stratification according to DFS resulted in a good (n=99), bad (n=96) and a small very bad prognosis group (n=3). Based on linear discriminant analysis the classifier for positive lymph node status was validated in 47 independent patients and revealed an accuracy of 72% and a positive predictive value of 100%. Thereby, prediction based on molecular profiling is superior to prediction based on conventional clinical markers. Interpretation: Whole genome expression analysis of pretherapeutical biopsies resulted in a molecular classifier of disease prognosis. This classifier was successfully validated. The high positive predictive value for post therapeutic lymph node status allows identification of patients requiring alternative or intensified treatment protocols. These data are currently validated for their clinical applicability and should be taken as basis for future molecular driven clinical trials to develop risk-adapted treatments.
2023-03-31 | GSE40492 | GEO