Assessment Of Long Noncoding RNA CCAT1 In Colorectal Cancer Patients
Ontology highlight
ABSTRACT:
DISEASE(S): Colorectal Cancer,Colorectal Neoplasms
PROVIDER: 2330122 | ecrin-mdr-crc |
REPOSITORIES: ECRIN MDR
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Project description:Background & Aims: MicroRNAs have been shown to offer great potential in the diagnosis of cancer. We aimed to identify microRNAs in peripheral blood mononuclear cells (PBMCs) for diagnosing pancreatic cancer (PC). Methods: PBMCs microRNA expression was investigated in three independent cohorts including 352 participants (healthy, benign pancreatic/peripancreatic diseases (BPD), and PC). First, we used sequencing technology to identify differentially expressed microRNAs in 60 PBMCs samples for diagnosing PC. Quantitative reverse-transcriptase polymerase chain reaction assay was then applied to evaluate the expression of selected microRNAs. A logistic regression model was constructed using an independent cohort. Area under the receiver operating characteristic curve (AUC) was used to evaluate diagnostic accuracy. Results: We found that PBMCs miR-27a-3p could efficiently discriminate PC from BPD (AUC=0.840; 95% CI, 0.787 to 0.885; sensitivity=82.2%, specificity=76.7%). A panel composed of PBMCs miR-27a-3p and serum CA19-9 provided a high diagnostic accuracy in differentiating PC from BPD in the clinical setting (AUC=0.886; 95% CI, 0.837 to 0.923; sensitivity=85.3%, specificity=81.6%). The satisfactory diagnostic performance of the panel persisted regardless of disease status (AUCs for tumour-node-metastasis stages?,?, and ? were 0.881, 0.884, and 0.893, respectively). Conclusion: PBMCs miR-27a-3p could be a potential marker for PC screening. A panel composed of PBMCs miR-27a-3p and serum CA19-9 has considerable clinical value in diagnosing early-stage PC. Therefore, patients who would have otherwise missed the curative treatment window can benefit from optimal therapy. Examination of different MicroRNA profiles in 3 types of PBMCs samples
2012-05-03 | E-GEOD-37710 | biostudies-arrayexpress
Project description:Background & Aims: MicroRNAs have been shown to offer great potential in the diagnosis of cancer. We aimed to identify microRNAs in peripheral blood mononuclear cells (PBMCs) for diagnosing pancreatic cancer (PC). Methods: PBMCs microRNA expression was investigated in three independent cohorts including 352 participants (healthy, benign pancreatic/peripancreatic diseases (BPD), and PC). First, we used sequencing technology to identify differentially expressed microRNAs in 60 PBMCs samples for diagnosing PC. Quantitative reverse-transcriptase polymerase chain reaction assay was then applied to evaluate the expression of selected microRNAs. A logistic regression model was constructed using an independent cohort. Area under the receiver operating characteristic curve (AUC) was used to evaluate diagnostic accuracy. Results: We found that PBMCs miR-27a-3p could efficiently discriminate PC from BPD (AUC=0.840; 95% CI, 0.787 to 0.885; sensitivity=82.2%, specificity=76.7%). A panel composed of PBMCs miR-27a-3p and serum CA19-9 provided a high diagnostic accuracy in differentiating PC from BPD in the clinical setting (AUC=0.886; 95% CI, 0.837 to 0.923; sensitivity=85.3%, specificity=81.6%). The satisfactory diagnostic performance of the panel persisted regardless of disease status (AUCs for tumour-node-metastasis stagesⅠ,Ⅱ, and Ⅲ were 0.881, 0.884, and 0.893, respectively). Conclusion: PBMCs miR-27a-3p could be a potential marker for PC screening. A panel composed of PBMCs miR-27a-3p and serum CA19-9 has considerable clinical value in diagnosing early-stage PC. Therefore, patients who would have otherwise missed the curative treatment window can benefit from optimal therapy.
2012-05-04 | GSE37710 | GEO
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2024-08-12 | PXD048034 | Pride
Project description:Clinical Utility of Circulating MicroRNA Signatures for Breast Cancer Diagnosis (Gene expression)
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Project description:Background: Autophagy plays important roles in cell homeostasis and protein quality control. Long non-coding RNAs (lncRNAs) have been revealed as an emerging class of autophagy regulators, but the majority of them function in regulating the expression of autophagy-related genes. LncRNAs that directly act on the core autophagic proteins remain to be explored. Methods: Immunofluorescence staining and Western blotting were used to evaluate the function of BCRP3 in autophagy and aggrephagy. RNA pull down and RNA immunoprecipitation were used to evaluate the interaction of BCRP3 with its target proteins. Phosphatidylinositol 3-phosphate ELISA assay was used to quantify the enzymatic activity of VPS34 complex. qRT-PCR analysis was used to determine BCRP3 expression under stresses, whereas Mass spectrometry and Gene Ontology analyses were employed to evaluate the effect of BCRP3 deficiency on proteome changes. Results: We identify lncRNA BCRP3 as a positive regulator of autophagy. BCRP3 is mainly localized in the cytoplasm and binds VPS34 complex to increase its enzymatic activity. In response to proteotoxicity induced by proteasome inhibition or oxidative stress, BCRP3 is upregulated to promote aggrephagy for the clearance of ubiquitinated protein aggregates. Proteomics analysis revealed that BCRP3 deficiency under proteotoxicity results in a preferential accumulation of proteins acting in growth inhibition, cell death, apoptosis, and Smad signaling. Accordingly, BCRP3 deficiency in proteotoxic cells compromises cell proliferation and survival, which is mediated in part through the upregulation of TGF-/Smad2 pathway. Conclusions: Our study identifies BCRP3 as an RNA activator of the VPS34 complex and a key role of BCRP3-mediated aggrephagy in protein quality control and selective degradation of growth and survival inhibitors to maintain cell fitness.
2022-05-20 | PXD030756 | Pride
Project description:To evaluate differentially regulated pathways contributing to poor prognosis in ealy postpartum breast cancer (PPBC) RNA sequncing was performed on early PPBC (PPBC1 samples (duration between last child birth and diagnosis of breast cancer ≤5years), n=3) and late PPBC tumors (PPBC2 samples (duration between last child birth and diagnosis of breast cancer 6-10 years), n=3) and PPBC3 samples (duration between last child birth and diagnosis of breast cancer >10 years), n=4).
2023-05-03 | GSE223470 | GEO
Project description:For optimal pancreatic cancer treatment, early and accurate diagnosis is vital. Blood-derived biomarkers and genetic predispositions can contribute to early diagnosis, but they often have limited accuracy or applicability. Here, we seek to exploit the synergy between both approaches by combining the standard clinical blood biomarker CA19-9 with novel genetic variants. Concretely, we aim to use deep sequencing and deep learning to improve pancreatic cancer diagnosis, to differentiate between resectable pancreatic ductal adenocarcinoma (rPDAC) from chronic pancreatitis (CP), and to estimate survival.
We obtained samples of nucleated cells found in peripheral blood from over 300 patients suffering from resectable pancreatic ductal adenocarcinoma, non-resectable pancreatic cancer (nrPC), chronic pancreatitis or none of these. We sequenced RNA with high coverage and reduced millions of raw to hundreds of high-quality, significant genetic variants. Together with CA19-9 levels, these served as input to deep learning to separate cancer from non-cancer, resectable PDAC from chronic pancreatitis, and resectable from non-resectable cancer.
All deep learning models achieved area under the curve (AUC) scores of over 90%. In particular, differentiating resectable PDAC from pancreatitis can be solved with an AUC of 98%. Moreover, we identified genetic variants to estimate survival in rPDAC patients.
Overall, we show that the blood transcriptome harbours genetic variants, which substantially improve non-invasive clinical diagnosis and patient stratification in pancreatic cancer.
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